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教师资格《英语学科知识与教学能力（初级中学）》模拟试题及答案四（实用版）编制人：__________________审核人：__________________审批人：__________________编制单位：__________________编制时间：____年____月____日序言下载提示：该文档是本店铺精心编制而成的，希望大家下载后，能够帮助大家解决实际问题。
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论英汉翻译中的冗余对等摘要本文试图在信息理论的框架内探讨英汉翻译的冗余对等问题，以期为英汉翻译理论研究和实践提供新的科学视角。
由美国数学家兼通讯工程师申农创立的信息论是应用概率论和数理统计方法研究信息处理和信息传递的科学。
该理论最初只应用于通讯领域，而随着科学技术的发展，其运用范围已扩展到其他许多学科，这其中便包括了翻译研究。
本文着眼于冗余这一信息论中的重要概念，提出为什么和如何在英汉翻译中实现冗余对等的问题进行研究。
翻译理论研究中的交际观首先为本文的研究奠定了理论基础，尤其是美国翻译家尤金·奈达博士提出的“翻译即交际”的观点指出了翻译作为信息传输的一种特殊形式——语际交际的本质特征。
以此为依托，本文进一步以信息论的相关原理来描述翻译的过程，说明实现冗余对等是确保译文的传输负载适合译语读者的信道容量，从而保证信息有效传输的根本途径。
然而，英汉两种语言无论在语言特点还是文化背景上都有着诸多差异，这便造成了两者之间的冗余失衡。
作者在本文中选定奈达的“动态对等”理论为依据，结合实例说明在英汉翻译中，译者可以通过采用保留原文冗余度或调整译文冗余度的策略，并灵活运用转换结构、重复、增译和省译等技巧来实现冗余对等；同时通过指出冗余对等不能很好地解释如何在译文中有效地保留原文风格的不足，说明信息论在指导英汉翻译研究中的缺｛陷所在。
关键词：冗余对等／英汉翻译／交际／信息论ＯＮＲＥＤＵＮＤＡＮＣＹＥＱＵＩＶＡＬＥＮＣＥＩＮＥ．ＣＴＲＡＮＳＬＡＴＩＯＮＡＢＳＴＲＡＣＴＴｈｅｐｒｅｓｅｎｔｔｈｅｓｉｓ，ｗｉｔｈａｎａｔｔｅｍｐｔｔｏｐｒｏｖｉｄｅａｓｃｉｅｎｔｉｆｉｃｂａｓｉｓｆｏｒｔｈｅｓｔｕｄｙｏｆＥ—Ｃｔｒａｎｓｌａｔｉｏｎ，ｔｒｉｅｓｔｏａｐｐｌｙｉｎｆｏｒｍａｔｉｏｎｔｈｅｏｒｙｔｏｔｈｅａｎａｌｙｓｉｓｏｆｒｅｄｕｎｄａｎｃｙｅｑｕｉｖａｌｅｎｃｅｉｎＥ·Ｃｔｒａｎｓｌａｔｉｏｎ．Ｉｎｆｏｒｍａｔｉｏｎｔｈｅｏｒｙ，ｄｅｖｅｌｏｐｅｄｂｙｔｈｅＡｍｅｒｉｃａｎｍａｔｈｅｍａｔｉｃｉａｎａｎｄｃｏｍｍｕｎｉｃａｔｉｏｎｉｎｆｏｒｍａｔｉｏｎｂｙｍｅａｎｓｏｆｅｎｇｉｎｅｅｒＣ．Ｅ．Ｓｈａｎｎｏｎ，ｍａｉｎｌｙｄｅａｌｓｗｉｔｈｔｈｅｔｒａｎｓｍｉｓｓｉｏｎｏｆｍａｔｈｅｍａｔｉｃａｌａｐｐｒｏａｃｈ．Ｔｈｅｔｈｅｏｒｙｗａｓｉｎｉｔｉａｌｌｙｄｅｓｉｇｎｅｄｔｏｍｅｅｔｔｈｅｄｅｍａｎｄｏｆｃｏｍｍｕｎｉｃａｔｉｏｎｅｎｇｉｎｅｅｒｉｎｇｓｔｕｄｉｅｓ．Ｗｉｍｔｈｅｄｅｖｅｌｏｐｍｅｎｔｏｆｓｃｉｅｎｃｅａｎｄｔｅｃｈｎｏｌｏｇｙ，ｉｔｈａｓａｃｑｕｉｒｅｄｂｒｏａｄｅｒａｐｐｌｉｃａｔｉｏｎｔｏｍａｎｙｏｔｈｅｒｆｉｅｌｄｓ，ｉｎｃｌｕｄｉｎｇｔｒａｎｓｌａｔｉｏｎｓｔｕｄｙ．Ｆｏｃｕｓｉｎｇｏｎｔｈｅｃｏｎｃｅｐｔｏｆｒｅｄｕｎｄａｎｃｙｔｈａｔｉｓｆｏｕｎｄｉｍｐｏｒｔａｎｔｉｎｔｈｅｒｅａｌｍｏｆｉｎｆｏｒｍａｔｉｏｎｔｈｅｏｒｙ，ｔｈｅｔｈｅｓｉｓｈｏｐｅｓｔｏｓｈｅｄｌｉｇｈｔｏｎｗｈｙａｎｄｈｏｗｗｅａｃｈｉｅｖｅｒｅｄｕｎｄａｎｃｙｅｑｕｉｖａｌｅｎｃｅｉｎＥ－Ｃｔｒａｎｓｌａｔｉｏｎ．Ｔｈｅｄｉｓｃｕｓｓｉｏｎｉｓｉｍｍｅｄｉａｔｅｌｙｇｒｏｕｎｄｅｄｔｈｅｏｒｅｔｉｃａｌｌｙｏｎｔｈｅｃｏｍｍｕｎｉｃａｔｉｖｅａｐｐｒｏａｃｈｔｏｔｒａｎｓｌａｔｉｏｎ．ＡｓｔｈｅＡｍｅｒｉｃａｎｔｒａｎｓｌａｔｉｏｎｔｈｅｏｒｉｓｔＥ．Ａ．Ｎｉｄａｈｏｌｄｓｔｈａｔ“Ｔｒａｎｓｌａｔｉｎｇｉｓｅｓｓｅｎｔｉａｌｌｙａｐｒｏｃｅｓｓｏｆｃｏｍｍｕｎｉｃａｔｉｏｎ＇’（Ｎｉｄａ＆Ｔａｂｅｒ，２００４：ＶＩＩ），ｔｒａｎｓｌａｔｉｏｎｉｓｂｙｎａｔｕｒｅａｌｌｉｍｅｒｌｉｎｇｕａｌｃｏｍｍｕｎｉｃａｔｉｏｎｅｖｅｎｔ．Ｏｎｔｈｅｂａｓｉｓｏｆｓｕｃｈａｎｕｎｄｅｒｓｔａｎｄｉｎｇ．ｓｏｍｅｂａｓｉｃｐｒｉｎｃｉｐｌｅｓｉｎｉｎｆｏｒｍａｔｉｏｎｔｈｅｏｒｙａｒｅｂｏｒｒｏｗｅｄｔｏｄｅｓｃｒｉｂｅｔｈｅｔｒａｎｓｌａｔｉｏｎｐｒｏｃｅｓｓ，ａｎｄｔｈｅｒｅａｌｉｚａｔｉｏｎｏｆｒｅｄｕｎｄａｎｃｙｅｑｕｉｖａｌｅｎｃｅｉｓｔｈｅｒｅｂｙｐｒｏｖｅｄｔｏｂｅｔｈｅｋｅｙｔｏｍａｋｅｔｈｅｃｏｍｍｕｎｉｃａｔｉｏｎｌｏａｄｏｆｔｈｅｔｒａｎｓｌａｔｅｄｔｅｘｔｆｉｔｉｎｔｈｅｃｈａｎｎｅｌｃａｐａｃｉｔｙｏｆｔｈｅｔａｒｇｅｔｒｅｃｅｐｔｏｒａｎｄｔｈｕｓｔｏｒａｉｓｅｔｈｅｅｆｆｉｃｉｅｎｃｙｏｆｉｎｆｏｒｍａｔｉｏｎｔｒａｎｓｍｉｓｓｉｏｎ．ＩｎＥ－Ｃｔｒａｎｓｌａｔｉｏｎ，ｒｅｄｕｎｄａｎｃｙｅｑｕｉｖａｌｅｎｃｅｉｓｉｍｐａｉｒｅｄｂｙｔｈｅｄｉｆｆｅｒｅｎｃｅｓｉｎｌｉｎｇｕｉｓｔｉｃｆｅａｔｕｒｅｓａｎｄｃｕｌｔｕｒａｌｂａｃｋｇｒｏｕｎｄｓｂｅｔｗｅｅｎＥｎｇｌｉｓｈａｎｄＣｈｉｎｅｓｅ，Ｈｏｗｅｖｅｒ，ｉｔｉｓｏｆｖｅｒｙｐｏｓｓｉｂｉｌｉｔｙｔｏｏｖｅｒｃｏｍｅｒｅｄｕｎｄａｎｃｙｕｎｂａｌａｎｃｅｔｈｒｏｕｇｈｓｏｍｅｓｔｒａｔｅｇｉｅｓａｎｄｔｅｃｈｎｉｑｕｅｓｔｈａｔａｒｅｓｕｐｐｏｓｅｄｔｏｄｅｒｉｖｅｆｒｏｍＮｉｄａ’ｓ“ｄｙｎａｍｉｃｅｑｕｉｖａｌｅｎｃｅ”，ｉ．ｅ．ｔｈｅｔｒａｎｓｌａｔｏｒｍａｙｃｈｏｏｓｅｆｒｏｍｔｗｏｓｔｒａｔｅｇｉｅｓｏｆｋｅｅｐｉｎｇａｎｄａｄ：ｉｕｓｔｉｎｇｒｅｄｕｎｄａｎｃｙａｎｄａｃｃｏｒｄｉｎｇｌｙａｄｏｐｔｓｓｕｃｈｔｅｃｈｎｉｑｕｅｓａｓｒｅｓｔｒｕｃｔｕｒｉｎｇ，ｒｅｐｅｔｉｔｉｏｎ，ｉｎｆｏｒｍａｔｉｏｎｔｈｅｏｒｙｆａｌｌｓｔｏａｍｐｌｉｆｉｃａｔｉｏｎ，ａｎｄｏｍｉｓｓｉｏｎ．Ｎｅｖｅｒｔｈｅｌｅｓｓ，ｔｈｅａｐｐｌｉｃａｔｉｏｎｏｆａｎａｌｌ—ｒｏｕｎｄｓｏｌｕｔｉｏｎｔｏｐｒｏｂｌｅｍｓｉｎＥ·Ｃｔｒａｎｓｌａｔｉｏｎｆｏｒｒｅｄｕｎｄａｎｃｙｅｑｕｉｖａｌｅｎｃｅｉｓｐｒｏｖｉｄｅｉｎａｄｅｑｕａｔｅｔｏａｄｄｒｅｓｓｔｈｅｔｒａｎｓｆｅｒｅｎｃｅｏｆｓｔｙｌｅｉｎｔｒａｎｓｌａｔｉｏｎ．ＫＥＹＷＯＲＤＳ：ｒｅｄｕｎｄａｎｃｙｅｑｕｉｖａｌｅｎｃｅ；Ｅ—Ｃｔｒａｎｓｌａｔｉｏｎ；ｃｏｍｍｕｎｉｃａｔｉｏｎ；ｉｎｆｏｒｍａｔｉｏｎｔｈｅｏｒｙ广西大掌硕士掌位论文论英汉翻译中的冗象对苓一————————————●＿＿＿－＿＿＿＿＿＿－－＿＿＿－＿●————————●＿－＿＿＿＿－＿＿＿－—————————＿—＿————————————＿————＿＿＿＿＿＿＿－＾—＿－一ＣｈａｐｔｅｒＩＩｎｔｒｏｄｕｃｔｉｏｎＳｔｕｄｉｅｓｏｆＥ—ＣｔｒａｎｓｌａｔｉｏｎｈａｖｅｂｅｅｎＳＯｅｘｔｅｎｓｉｖｅｉｎＣｈｉｎａ，ｗｈｉｃｈｉｓａｎｅｅｄｔｏｍｅｅｔｔｈｅｄｅｍａｎｄｏｆｐｒｏｖｉｄｉｎｇｇｕｉｄｅｌｉｎｅｓｆｏｒｔｈｅｐｒａｃｔｉｃｅｓａｎｄｔｅａｃｈｉｎｇｏｆｔｒａｎｓｌａｔｉｏｎ．Ｔｒａｄｉｔｉｏｎａｌｌｙ，ｍａｎｙｓｔｕｄｉｅｓｈａｖｅｂｅｅｎｃａｒｒｉｅｄｏｕｔｏｎｔｈｅｂａｓｉｓｏｆｃｏｎｔｒａｓｔｉｖｅｌｉｎｇｕｉｓｔｉｃｓ．ＢｙｃｏｍｐａｒｉｎｇｂｏｔｈｔｈｅｓｉｍｉｌａｒｉｔｉｅｓａｎｄｄｉｓｓｉｍｉｌａｒｉｔｉｅｓｂｅｔｗｅｅｎＥｎｇｌｉｓｈａｎｄＣｈｉｎｅｓｅ，ｐｅｏｐｌｅｈａｖｅｗｏｒｋｅｄｏｕｔａｎ帆ｂｅｒｏｆｐｒｉｎｃｉｐｌｅｓａｎｄｔｅｃｈｎｉｑｕｅｓｏｆＥ－Ｃｔｒａｎｓｌａｔｉｏｎ·Ｗｉｍｖａｒｉｏｕｓｐｉｏｎｅｅｒｉｎｇｅｆｆｏｒｔｓｉｎｖｉｅｗ，ｔｈｅｐｒｅｓｅｎｔｓｔｕｄｙａｉｍｓｔｏｇｅｔｄｏｗｎｏｎｔｈｅｓａｍｅｉｓｓｕｅｂｕｔｉｎａｓｃｉｅｎｔｉｆｉｃｍａｎｎｅｒ，Ｈｏｐｅｆｕｌｌｙ，ｔｈｉｓｔｈｅｓｉｓｗｉｌｌｃｏｎｔｒｉｂｕｔｅｔｏｔｈｅｔｈｅｏｒｅｔｉｃａｌｓｔｕｄｙｏｆｔｒａｎｓｌａｔｉｏｎｉｎＣｈｉｎａｂｙｉｎｃｏｒｐｏｒａｔｉｎｇｔｈｅａｃｈｉｅｖｅｍｅｎｔｓｏｆｉｎｆｏｒｍａｔｉｏｎｔｈｅｏｒｙ．Ｗｎｔｈｅｃｏｍｍｕｎｉｃａｔｉｖｅａｐｐｒｏａｃｈｔｏｔｒａｎｓｌａｔｉｏｎａｓｔｈｅｔｈｅｏｒｅｔｉｃａｌｂａｓｉｓ．ｔｒａｎｓｌａｔｉｏｎｉｎｔｈｉｓｔｈｅｓｉｓｉｓｕｎｄｅｒｓｔｏｏｄａｓａｎｉｎｔｅｒｌｉｎｇｕａｌｃｏｍｍｕｎｉｃａｔｉｏｎｉｎｅｓｓｅｎｃｅ．Ｔｒａｎｓｌａｔｉｏｎｉｓｍｏｒｅｔｈａｎａｓｔａｔｉｃｐｒｏｄｕｃｔ．Ｉｔｉｓ，ｂｙｎａｔｕｒｅ，ａｄｙｎａｍｉｃｃｏｍｍｕｎｉｃａｔｉｏｎｅｖｅｎｔｔｈａｔｉｎｖｏｌｖｅｓｄｅｃｏｄｉｎｇｔｈｅａｎｄｅｎｃｏｄｉｎｇｉｔｉｎｔｏａｄｉｆｆｅｒｅｎｔｌａｎｇｕａｇｅ，ｗｈｉｃｈｉｎｅｖｉｔａｂｌｙｍｅａｎｉｎｇｏｆａｔｅｘｔｉｎｏｎｅｌａｎｇｕａｇｅｉｎｖｏｌｖｅｓｍｏｒｅｔｈａｎｍｅｒｅｌｙｍａｔｃｈｉｎｇｗｏｒｄｓ．Ａｓｍｕｃｈｏｆｔｈｅｓｉｇｎｉｆｉｃａｎｃｅｏｆｔｈｅｃｏｍｍｕｎｉｃａｔｉｏｎｔｈｅｏｒｙｏｆｔｒａｎｓｌａｔｉｏｎｃｏｍｅｓｆｒｏｍｉｎｆｏｒｍａｔｉｏｎｔｈｅｏｒｙ，ｓｏｍｅｂａｓｉｃｐｒｉｎｃｉｐｌｅｓｏｆｔｈｉｓｔｈｅｏｒｙｏｆｆｅｒｃｅｒｔａｉｎｉｍｐｏｒｔａｎｔｉｎｓｉｇｈｔｓｔｏＥ－Ｃｔｒａｎｓｌａｔｉｏｎ．ＩｎｆｏｒｍａｔｉｏｎｔｈｅｏｒｙｓｔｅｍｓｆｒｏｍＳｈａｎｎｏｎ’Ｓｍａｔｈｅｍａｔｉｃａｌｍｅｔｈｏｄｓｆｏｒｍｅａｓｕｒｉｎｇｔｈｅｄｅｇｒｅｅｏｆｏｒｄｅｒｉｎａｓｉｇｎａｌ，ｗｈｉｃｈｄｒｅｗａｎｄｌｅｄｔｏｔｅｃｈｎｉｑｕｅｓｆｏｒｄｅｔｅｒｍｉｎｉｎｇａｓｏｕｒｃｅ’ｓｒａｔｅｏｆｌａｒｇｅｌｙｏｎｐｒｏｂａｂｉｌｉｔｙｔｈｅｏｒｙｉｎｆｏｒｍａｔｉｏｎｐｒｏｄｕｃｔｉｏｎ，ａｃｈａｎｎｅｌ’ＳｃａｐａｃｉＶｔＯｈａｎｄｌｅｉｎｆｏｒｍａｔｉｏｎ，ａｎｄｔｈｅａｖｅｒａｇｅａｍｏｕｎｔｏｆｉｎｆｏｒｍａｔｉｏｎｉｎａｇｉｖｅｎｔｙｐｅｏｆｍｅｓｓａｇｅ．Ｃｒｕｃｉａｌｔｏｔｈｅｄｅｓｉｇｎｏｆｃｏｍｍｕｎｉｃａｔｉｏｎｓｙｓｔｅｍｓ，ｔｈｅｓｅｔｅｃｈｎｉｑｕｅｓｈａｖｅｉｍｐｏｒｔａｎｔａｐｐｌｉｃａｔｉｏｎｓｉｎｔｒａｎｓｌａｔｉｏｎ，ｉｎｗｈｉｃｈｔｈｅｅｆｆｅｃｔｉｖｅｎｅｓｓｏｆｉｎｆｏｒｍａｔｉｏｎｔｒａｎｓｍｉｓｓｉｏｎｉｓｈｉｇｈｌｙｖａｌｕｅｄ．Ｒｅｄｕｎｄａｎｃｙ，ｏｎｅｏｆｔｈｅｋｅｙｎｏｔｅｃｏｎｃｅｐｔｓｉｎｔｈｅｄｏｍａｉｎｏｆｉｎｆｏｒｍａｔｉｏｎｔｈｅｏｒｙｔｈａｔｉｓａｃｅｎｔｒａｌｂａｓｅｆｏｒｃｏｍｍｕｎｉｃａｔｉｏｎｔｈｅｏｒｙ，ｐｌａｙｓａｓｉｇｎｉｆｉｃａｎｔｒｏｌｅｔｏｅｎｓｕｒｅｔｈｅｅｆｆｉｃｉｅｎｃｙｏｆａｍｏｕｎｔｏｆｒｅｄｕｎｄａｎｃｙｉｓｏｆｇｒｅａｔｈｅｌｐｔｏａｄｊｕｓｔｔｈｅｔｒａｎｓｌａｔｉｏｎ．Ｏｎｔｈｅｏｎｅｈａｎｄ，ｃｅｒｔａｉｎｖｅｒｓｉｏｎ’ＳｃｏｍｍｕｎｉｃａｔｉｏｎｌｏａｄＳＯｔｈａｔｉｔＣａｎｐａｓｓｔｈｒｏｕｇｈｔｈｅｉｎｔｅｎｄｅｄｒｅｃｅｐｔｏｒ’Ｓｃｈａｎｎｅｌｗｉｔｈｅａｓｅ；ｏｎｔｈｅｏｔｈｅｒｈａｎｄ，ｒｅｄｕｎｄａｎｃｙｉｓｃｏｎｓｉｄｅｒｅｄｖｉｔａｌｔｏｃｏｍｂａｔｎｏｉｓｅｔｈａｔｗｉｌｌｃｏｍｅｔｏｄｉｓｔｏｒｔｔｈｅｔｒａｎｓｍｉｔｔｅｄｍｅｓｓａｇｅ．Ａｌｔｈｏｕｇｈｒｅｄｕｎｄａｎｃｙｉｓａｕｎｉｖｅｒｓａｌｃｈａｒａｃｔｅｒｉｓｔｉｃｓｈａｒｅｄｂｙａｌｌｌａｎｇｕａｇｅｓ，ｔｈｅｒｅａｌｉｚａｔｉｏｎｏｆｒｅｄｕｎｄａｎｃｙ，ｓａｙ，ｒｅｄｕｎｄａｎｃｙｐａｔｔｅｒｎｓ，ｖａｒｉｅｓｆｒｏｍｌａｎｇｕａｇｅｔｏｌａｎｇｕａｇｅ．Ｒｅｄｕｎｄａｎｃｙｅｑｕｉｖａｌｅｎｃｅｔｈｕｓｂｅｃｏｍｅｓｔｈｅｍａｊｏｒｃｏｎｃｅｒｎｉｎｔｒａｎｓｌａｔｉｏｎ．ＩｎＥ＿Ｃｔｒａｎｓｌａｔｉｏｎ，ｒｅｄｕｎｄａｎｃｙｅｑｕｉｖａｌｅｎｃｅｍｅｅｔｓｇｒｅａｔｄｉｆｆｉｃｕｉｔｉｅｓｇｉｖｅｎｔｈｅｄｉｆｆｅｒｅｎｃｅｓｏｆａｎｄｃｕｌｔｕｒａｌｂａｃｋｇｒｏｕｎｄｓｂｅｔｗｅｅｎＥｎｇｌｉｓｈａｎｄＣｈｉｎｅｓｅ．Ｈｏｗｅｖｅｒ，ｉｔｌｉｎｇｕｉｓｔｉｃｓｃｈａｒａｃｔｅｒｉｓｔｉｃｓｉｓｓｔｉｌｌｐｏｓｓｉｂｌｅｔｏａｃｈｉｅｖｅｒｅｄｕｎｄａｎｃｙｅｑｕｉｖａｌｅｎｃｅｉｎＥ－Ｃｔｒａｎｓｌａｔｉｏｎｉｆｔｈｅｐｒｉｎｃｉｐｌｅｏｆ】广西大掣Ｉ｜蕊士掌位论文论掌｝锅．囊｜译中的冗萄｝对等“ｄｙｎａｍｉｃｅｑｕｉｖａｌｅｎｃｅ”ｉｓｆｏｌｌｏｗｅｄ．Ｄｅｖｅｌｏｐｅｄｄｅｄｕｃｔｉｖｅｌｙ，ｔｈｅｐｒｅｓｅｎｔｔｈｅｓｉｓｃｏｎｓｉｓｔｓｏｆｓｅｖｅｎｃｈａｐｔｅｒｓｉｎｃｌｕｄｉｎｇｔｈｅ“Ｉｎｔｒｏｄｕｃｔｉｏｎ＇’．ＣｈａｐｔｅｒＩＩｐｒｅｓｅｎｔｓａｒｅｖｉｅｗｏｆｔｈｅｃｏｍｍｕｎｉｃａｔｉｖｅａｐｐｒｏａｃｈｔｏｔｒａｎｓｌａｔｉｏｎｂａｓｅｄＯｉｌｔｈｅｍａｊｏｒｔｈｅｏｒｅｔｉｃａｌｆｒａｍｅｗｏｒｋｏｆｔｈｅｐｒｅｓｅｎｔｓｔｕｄｙｃｏｎｃｅｒｎｓｗｉｔｈｓｏｍｅｆｏｃｕｓｏｎ也ｅｉｎａｄｅｑｕａｃｉｅｓｏｆｔｈｅｐｒｅｖｉｏｕｓｒｅｓｅａｒｃｈｅｓ．ＣｈａｐｔｅｒｌＩＩｄｅａｌｓｗｉｔｈｔｈｅｒｅｌａｔｉｏｎｓｈｉｐｔｈａｔｈｏｌｄｓｂｅｔｗｅｅｎｉｎｆｏｒｍａｔｉｏｎｔｈｅｏｒｙａｎｄｔｒａｎｓｌａｔｉｏｎ，ａｎｄａｐｐｌｉｅｓｔｈｅｔｈｅｏｒｙｔｏｔｈｅａｎａｌｙｓｉｓｏｆｔｈ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Process-oriented theories: are concerned with how the mind organizes new information such as habit.formation,.induction,making.inference,.hypothesis.testing.and.generalization.Co ndition-oriented theories: emphasize the nature of the human and physical context in which language learning takes place, such as the number of students, the kind of input learners receives, and the atmosphere.Behaviorist theory, skinner,learning process of habit formation&conditioning,a stimulus-response theory ,imitation&repetition SRR,audio-lingual method,external factors,the idea of this method is that language is learned by constant repletion and the reinforcement of the teacher. Mistakes were immediately corrected, and correct utterances were immediately praised.Cognitive theory,chomsky,learning:creative process, internal factors,students are asked to thinking and allow to create their own sentence based on their understanding of certain rules ,language is not a form of behavior, it is an intricate rule-based system and a large part of language acquisition is the learning of this system.Constructivist theory,personal construction,dewey, believes that learning is a process in which the learner constructs meaning based on his/her own experiences and what he/she already knows.Socio-constructivist theory, similar to constructivist theory, socio-constructivist theory emphasizes interaction and engagement with the target language in a social context based on the concept of “Zone of Proximal Development” (ZPD) and scaffolding.learning is best achieved through dynamic interaction between the teacher&learner&between learnersLanguage teacher qualifications：1、a good command of spoken and written language2、formulate theory presupposition3、language background and experience4、know how languages are learnt 5、the ability to use methods in various situations6、deep understanding of cultural background7、understanding the principles of teaching.These elements can be categorized into three groups：ethic devotion，professional qualities and personal stylesCommunicative Competence:Hedge,:linguistic（knowledge of the language itself,its form and meaning）,pragmatic(the appropriate use of the language in social context),discourse(one ability to create coherent written text or conversation and theability to understand it) ,strategic(strategies one employs when there is communication breakdown due to lack of resource),fluency(ability to link units of speech together with facility and without strain or inappropriate to slowness or undue hesitation)Views on language.Structural view —The founder：Saussure—The structural view of language sees language as a linguistic system made up of various subsystems：1、the sound system（phonology）2、sound combinations（morphology）3、meaning for communication（syntax）—Learning the language is to learn the structural items，study the inner structure and rule of language，ignore the social functions of the language。
2021年下教师资格笔试高中英语模拟卷一一、单项选择题（本大题共30小题，每小题2分，共60分）1.Inside are over500paintings,prints,watercolors,and a_____of other art objects.A.sortB.kindC.amountD.variety2.The paper is due next month,and I am working seven days______week,often long into______night.A.a;theB.the;不填C.a;aD.不填;the3.—Can I help you?—I'd like to buy a present for my father's birthday,_____at a proper price but of good use.A.oneB.itC.thatD.which4.The Foundation is holding a dinner at the Museum of American Art_____the opening of their new show.A.in honor ofB.in memory ofC.in response toD.in reply to5.In the lecture hall_____.A.seats a professorB.a professor seatsC.sits a professorD.a professor sits6.—We need to turn to Professor Smith for help.—______?Our classmate Simon is an expert at solving such problems.A.Why notB.How comeC.Why botherD.What for7.A(n)_____is the smallest unit of sound in a language,which can distinguish two words.A.soundB.morphemeC.phonemeD.allophone8./m,n/are_____.A.fricativesB.dentalsC.glidesD.nasals9.“Big”and“small”are a pair of_____antonyms.plementaryB.gradablepleteD.converse10.A:Will you go mountain-climbing with me now?B:But I have a headache now.This conversation violates the maxim of_____.A.qualityB.quantityC.relationD.manner11.Writing plays a very important role in developing students’English learning. Editing belongs to_____.A.Post-writingB.While-writingC.Post-listeningD.Post-reading12.In speaking class,which of the following is a suitable activity for production stage? _____A.Role-playB.Writing a similar textC.Learning vocabularies about the topicD.putting pictures in order13.The PPP teaching model is considered appropriate in teaching_____?A.readingB.writingC.listeningD.vocabulary14.In teacher Wang’s class,before giving the evaluation to the performance of students, she always encourages students to evaluate themselves or evaluate by peers.What does this situation reflects?_____A.It reflects the professionalism of the teacher.B.The teacher pays attention to the diversification of the evaluation subject.C.The teacher wants to promote communication among students.D.It is just the teacher’s personal habit.15.Ask the students to recall the basic content they have learned to check whether they have remembered the knowledge they have learned.What kind of classification of asking questions dose this belong to?A.Questions about memoryB.Questions about understandingC.Questions about analysisD.Questions about comprehensive skills16._____are generally used to provide written evaluation symbols or comments for students’homework or tests after class.A.Verbal feedbacksB.Non-verbal feedbacksC.Feedbacks in writing formrmation feedbacks17.The elements in foreign language reading include_____.A.automatic recognition skills and formal discourse structure knowledgeB.world and cultural background knowledge;synthesis and evaluation skills/strategiesC.metal cognitive knowledge and skills monitoring reading;vocabulary and structure knowledgeD.Above all18.Teacher can use____as production practice during teaching pronunciation.A.Same or differentB.Display ordering meaningful contextsD.Odd one out19.A popular way of getting students to concentrate on phonetic aspects of pronunciation is to_____.A.recognize stress pattern in phraseB.match different intonation with different meaningC.learn the correspondence of sound and spellingD.contrast two sounds which are very similar and often confusing20.Which of the following activities can help students prepare for spontaneous speech?A.Reading aloud.B.Giving a prepared talk.C.Doing a drill.D.Interviewing someone,or being interviewed.请阅读Passage1，完成21~25小题。
2024年06月大学英语六级考试真题（第1套）Part I Writing (30 minutes) Directions: For this part, you are allowed 30 minutes to write an essay that begins with the sentence “There is a growing awareness of the importance of digital literacy and skills in today’s world.” You can make comments, cite examples or use your personal experiences to develop your essay. You should write at least 150 words but no more than 200 words.You should copy the sentence given in quotes at the beginning of your essay.PartⅡListening Comprehension (30 minutes) Section ADirections: In this section, you will hear two long conversations. At the end of each conversation, you will hear four questions. Both the conversation and the questions will be spoken only once. After you hear a question, you must choose the best answer from the four choices marked A), B), C) and D). Then mark the corresponding letter on Answer Sheet 1 witha single line through the centre.Questions 1 to 4 are based on the conversation you have just heard.1. A) Reply to the man’s last proposal within a short time.B) Sign the agreement if one small change is made to it.C) Make a sponsorship deal for her client at the meeting.D) Give the man some good news regarding the contract.2. A) They are becoming impatient. C) They are used to making alterations.B) They are afraid time is running out. D) They are concerned about the details.3. A) To prevent geographical discrimination. C) To avoid any conflict of interest.B) To tap the food and beverage market. D) To reduce unfair competition.4. A) It is a potential market for food and beverage. C) It is a negligible market for his company.B) It is very attractive for real estate developers. D) It is very different from other markets.Questions 5 to 8 are based on the conversation you have just heard.5. A) They are thrilled by a rare astronomic phenomenon.B) They are celebrating a big event on mountain tops.C) They are enthusiastic about big science-related stories.D) They are joined by astronomers all across North America.6. A) It will be the most formidable of its kind in over a century.B) It will come closest to Earth in more than one hundred years.C) It will eclipse many other such events in human history.D) It will be seen most clearly from Denver’s mountain tops.7. A) A blur. C) The edge of our galaxy.B) Stars. D) An ordinary flying object.8. A) Use professional equipment. C) Fix their eyes due north.B) Climb to the nearby heights. D) Make use of phone apps.Section BDirections:In this section, you will hear two passages. At the end of each passage, you will hear three or four questions. Both the passage and the questions will be spoken only once. After you hear a question, you must choose the best answer from the four choices marked A)，B)，C) and D). Then mark the corresponding letter on Answer Sheet 1 with a single line through the centre.Questions 9 to 11 are based on the passage you have just heard.9. A) Whether consumers should be warned against ultra-processed foods.B) Whether there is sufficient scientific consensus on dietary guidelines.C) Whether guidelines can form the basis for nutrition advice to consumers.D) Whether food scientists will agree on the concept of ultra-processed foods.10. A) By the labor cost for the final products. C) By the extent of chemical alteration.B) By the degree of industrial processing. D) By the convention of classification.11. A) Increased consumers’ expen ses. C) People’s misunderstanding of nutrition.B) Greater risk of chronic diseases. D) Children’s dislike for unprocessed foods.Questions 12 to 15 are based on the passage you have just heard.12. A) They begin to think of the benefits of constraints.B) They try to seek solutions from creative people.C) They try hard to maximize their mental energy.D) They begin to see the world in a different way.13. A) It is characteristic of all creative people.B) It is essential to pushing society forward.C) It is a creative p erson’s response to limitation.D) It is an impetus to socio-economic development.14. A) Scarcity or abundance of resources has little impact on people’s creativity.B) Innovative people are not constrained in connecting unrelated concepts.C) People have no incentive to use available resources in new ways.D) Creative people tend to consume more available resources.15. A) It is key to a company’s survival.B) It shapes and focuses problems.C) It is essential to meeting challenges.D) It thrives best when constrained.Section CDirections: In this section, you will hear three recordings of lectures or talks followed by three or four questions. The recordings will be played only once. After you hear a question, you must choose the best answer from the four choices marked A), B), C) and D). Then mark the corresponding letter on Answer Sheet 1 with a single line through the centre.Questions 16 to 18 are based on the recording you have just heard.16. A) Because they are learned. C) Because they have to be properly personalized.B) Because they come naturally. D) Because there can be more effective strategies.17. A) The extent of difference and of similarity between the two sides.B) The knowledge of the specific expectation the other side holds.C) The importance of one’s goals and of the relationship.D) The approaches one adopts to conflict management.18. A) The fox. C) The shark.B) The owl. D) The turtle.Questions 19 to 21 are based on the recording you have just heard.19. A) Help save species from extinction and boost human health.B) Understand how plants and animals perished over the past.C) Help gather information publicly available to researchers.D) Find out the cause of extinction of Britain’s 66,000 species.20. A) It was once dominated by dinosaurs. C) Its prospects depend on future human behaviour.B) It has entered the sixth mass extinction. D) Its climate change is aggravated by humans.21. A) It dwarfs all other efforts to conserve, protect and restore biodiversity on earth.B) It is costly to get started and requires the joint efforts of thousands of scientists.C) It can help to bring back the large numbers of plants and animals that have gone extinct.D) It is the most exciting, most relevant, most timely and most internationally inspirational.Questions 22 to 25 are based on the recording you have just heard.22. A) Cultural identity. C) The Copernican revolution.B) Social evolution. D) Human individuality.23. A) It is a delusion to be disposed of. C) It is a myth spread by John Donne’s poem.B) It is prevalent even among academics. D) It is rooted in the mindset of the 17th century.24. A) He believes in Copernican philosophical doctrines about the universe.B) He has gained ample scientific evidence at the University of Reading.C) He has found that our inner self and material self are interconnected.D) He contends most of our body cells can only live a few days or weeks.25. A) By coming to see how disruptive such problems have got to be.B) By realising that we all can do our own bit in such endeavours.C) By becoming aware that we are part of a bigger world.D) By making joint efforts resolutely and persistently.Part III Reading Comprehension (40 minutes) Section ADirections:In this section, there is a passage with ten blanks. You are required to select one word for each blank from a list of choices given in a word bank following the passage. Readthe passage through carefully before making your choices. Each choice in the bank is identifiedby a letter. Please mark the corresponding letter for each item on Answer Sheet 2 with a singleline through the centre. You may not use any of the words in the bank more than once.It’s quite remarkable how different genres of music can spark unique feelings, emotions,and memories. Studies have shown that music can reduce stress and anxiety before surgeriesand we are all attracted toward our own unique life soundtrack.If you’re lo oking to 26 stress, you might want to give classical music a try.The sounds of classical music produce a calming effect letting 27 pleasure-inducing dopamine (多巴胺) in the brain that helps control attention, learning and emotional responses. It can also turn down the body’s stress response, resulting in an overall happier mood. It turns out a pleasant mood can lead to 28 in a person’s thinking.Although there are many great 29 of classical music like Bach, Beethoven and Handel, none of these artists’ music seems to have the same health effects as Mozart’s does. According to researchers, listening to Mozart can increase brain wave activity and improve 30 function. Another study found that the distinctive features of Mozart’s music trigger parts of the brain that are responsible for high-level mental functions. Even maternity 31 use Mozart to help newborn babies adapt to life outside of the mother’s belly.It has been found that listening to classical music 32 reduces a pers on’s blood pressure. Researchers believe that the calming sounds of classical music may help your heart 33 from stress. Classical music can also be a great tool to help people who have trouble sleeping. One study found that students who had trouble sleeping slept better while they were listening to classical music.Whether classical music is something that you listen to on a regular basis or not, it wouldn’t34 to take time out of your day to listen to music that you find 35 . You will be surprised at how good it makes you feel and the potentially positive change in your health.Section BDirections:In this section, you are going to read a passage with ten statements attached to it. Each statement contains information given in one of the paragraphs. Identify the paragraph from which the information is derived. You may choose a paragraph more than once. Each paragraph is marked with a letter. Answer the questions by marking the corresponding letter on Answer Sheet 2.The Curious Case of the Tree That Owns ItselfA)In the city of Athens, Georgia, there exists a rather curious local landmark—a large whiteoak that is almost universally stated to own itself. Because of this, it is considered one of the most famous trees in the world. So how did this tree come to own itself and the land around it?B)Sometime in the 19th century a Georgian called Colonel William Jackson reportedly tooka liking to the said tree and endeavored to protect it from any danger. As to why he loved itso, the earliest documented account of this story is an anonymously written front page article in the Athens Weekly Banner published on August 12, 1890. It states, “Col. Jackson had watched the tree grow from his childhood, and grew to love it almost as he would a human. Its luxuriant leaves and sturdy limbs had often protected him from the heavy rains, and out of its highest branches he had many a time gotten the eggs of the feathered singers.He watched its growth, and when reaching a ripe old age he saw the tree standing in its magnificent proportions, he was pained to think that after his death it would fall into the hands of those who might destroy it.”C)Towards this end, Jackson transferred by means of a deed ownership of the tree and a littleland around it to the tree itself. The deed read, “W. H. Jackson for and in consideration of the great affection which he bears the said tree, and his great desire to see it protected has conveyed unto the said oak tree entire possession of itself and of all land within eight feet of it on all sides.”D)In time, the tree came to be something of a tourist attraction, known as The Tree That OwnsItself. However, in the early 20th century, the tree started showing signs of its slow death, with little that could be done about it. Father time comes for us all eventually, even our often long lived, tall and leafy fellow custodians (看管者) of Earth. Finally, on October 9, 1942, the over 30 meter tall and 200-400 year old tree fell, rumor has it, as a result of a severe windstorm and/or via having previously died and its roots rotted.E)About four years later, members of the Junior Ladies Garden Club (who’d tended to thetree before its unfortunate death) tracked down a small tree grown from a nut taken from the original tree. And so it was that on October 9, 1946, under the direction of Professor Roy Bowden of the College of Agriculture at the University of Georgia, this little tree was transplanted to the location of its ancestor. A couple of months later, an official ceremony was held featuring none other than the Mayor of Athens, Robert L McWhorter, to commemorate the occasion.F)This new tree became known as The Son of the Tree That Owns Itself and it was assumedthat, as the original tree’s heir, it naturally inherited the land it stood on. Of course, there are many dozens of other trees known to exist descending from the original, as people taking a nut from it to grow elsewhere was a certainty. That said, to date, none of the original tree’s other children have petitioned the courts for their share of the land, so it seems all good. In any event, The Son of the Tree That Owns Itself still stands today, though often referred to simply as The Tree That Owns Itself.G)This all brings us around to whether Jackson ever actually gave legal ownership of the treeto itself in the first place and whether such a deed is legally binding.H)Well, to begin with, it turns out Jackson only spent about three years of his life in Athens,starting at the age of 43 from 1829 to 1832, sort of dismissing the idea that he loved the tree from spending time under it as a child and watching it grow, and then worrying about what would happen to it after he died. Further, an extensive search of land ownership records in Athens does not seem to indicate Jackson ever owned the land the tree sits on.I)He did live on a lot of land directly next to it for those three years, but whether he ownedthat land or not isn’t clear. Whatever the case, in 1832 a four acre parcel, which included the land the tree was on and the neighboring land Jackson lived on, among others, was sold to University professor Malthus A Ward. In the transaction, Ward was required to payJackson a sum of $1,200 (about $31,000 today), either for the property itself or simply in compensation for improvements Jackson had made on the lot. In the end, whether he ever owned the neighboring lot or was simply allowed to use it while he allegedly worked at the University, he definitely never owned the lot the tree grew on, which is the most important bit for the topic at hand.J)After Professor Ward purchased the land, Jackson and his family purchased a 655 acre parcel a few miles away and moved there. Ten years later, in 1844, Jackson seemed to have come into financial difficulties and had his little plantation seized by the Clarke County Sheriff’s office and auctioned off to settle the mortgage. Thus, had he owned some land in Athens itself, including the land the tree sat on, presumably he would have sold it to raise funds or otherwise had it taken as well.K)And whatever the case there, Jackson would have known property taxes needed to be paid on the deeded land for the tree to be truly secure in its future. Yet no account or record indicates any trust or the like was set up to facilitate this.L)On top of all this, there is no hard evidence such a deed ever existed, despite the fact that deed records in Athens go back many decades before Jackson’s death in 1876 and that it was supposed to have existed in 1890 in the archives according to the original anonymous news reporter who claims to have seen it.M)As you might imagine from all of this, few give credit to this side of the story. So how did all of this come about then?N)It is speculated to have been invented by the imagination of the said anonymous author at the Athens Weekly Banner in the aforementioned 1890 front page article titled “Deeded to Itself”, which by the way contained several elements that are much more easily proved to be false. As to why the author would do this, it’s speculated perhaps it was a 19th century version of a click-bait thought exercise on whether it would be legal for someone to deed such a non-conscious living thing to itself or not.O)Whatever the case, the next known instance of the Tree That Owns Itself being mentioned wasn’t until 1901 in the Centennial Edition of that same paper, the Athens Weekly Banner.This featured another account very clearly just copying the original article published abouta decade before, only slightly reworded. The next account was in 1906, again in the AthensWeekly Banner, again very clearly copying the original account, only slightly reworded, the 19th century equivalent of re-posts when the audience has forgotten about the original.36. Jackson was said to have transferred his ownership of the oak tree to itself in order to protect it from being destroyed.37. No proof has been found from an extensive search that Jackson had ever owned the land where the oak tree grew.38. When it was raining heavily, Jackson often took shelter under a big tree that is said to own itself.39. There is no evidence that Jackson had made arrangements to pay property taxes for the land on which the oak tree sat.40. Professor Ward paid Jackson over one thousand dollars when purchasing a piece of land from him.41. It is said the tree that owned itself fell in a heavy windstorm.42. The story of the oak tree is suspected to have been invented as a thought exercise.43. Jackson’s little plantation was auctioned off to settle his debt in the mid-19th century.44. An official ceremony was held to celebrate the transplanting of a small tree to where its ancestor had stood.45. The story of the Tree That Owns Itself appeared in the local paper several times, with slight alterations in wording.Section CDirections:There are 2 passages in this section. Each passage is followed by some questions or unfinished statements. For each of them there are four choices marked A), B), C) and D). You should decide on the best choice and mark the corresponding letter on Answer Sheet 2 with a single line through the centre.Passage OneQuestions 46 to 50 are based on the following passage.It is irrefutable that employees know the difference between right and wron g. So why don’t more employees intervene when they see someone exhibiting at-risk behavior in the workplace?There are a number of factors that influence whether people intervene. First, they need to be able to see a risky situation beginning to unfold. Second, the company’s culture needs to make them feel safe to speak up. And third, they need to have the communication skills to say something effectively.This is not strictly a workplace problem; it’s a growing problem off the job too. Every day people witness things on the street and choose to stand idly by. This is known as the bystander effect—the more people who witness an event, the less likely anyone in that group is to help the victim. The psychology behind this is called diffusion of responsibility. Basically, the larger the crowd, the more people assume that someone else will take care of it—meaning no one effectively intervenes or acts in a moment of need.This crowd mentality is strong enough for people to evade their known responsibilities. But it’s not only frontline workers who don’t make safety i nterventions in the workplace. There are also instances where supervisors do not intervene either.When a group of employees sees unsafe behavior not being addressed at a leadership level it creates the precedent that this is how these situations should be addressed, thus defining the safety culture for everyone.Despite the fact that workers are encouraged to intervene when they observe unsafe operations, this happens less than half of the time. Fear is the ultimate factor in not intervening. There is a fear of penalty, a fear that they’ll have to do more work if they intervene. Unsuccessful attempts in the past are another strong contributing factor to why people don’t intervene—they tend to prefer to defer that action to someone else for all future situations.On many worksites, competent workers must be appointed. Part of their job is to intervene when workers perform a task without the proper equipment or if the conditions are unsafe. Competent workers are also required to stop work from continuing when there’s a danger.Supervisors also play a critical role. Even if a competent person isn’t required, supervisors need a broad set of skills to not only identify and alleviate workplace hazards but also build a safety climate within their team that supports intervening and open communication among them.Beyond competent workers and supervisors, it’s important to educate everyon e within the organization that they are obliged to intervene if they witness a possible unsafe act, whether you’re a designated competent person, a supervisor or a frontline worker.46. What is one of the factors contributing to failure of intervention in face of risky behavior in the workplace?A) Slack supervision style. C) Unforeseeable risk.B) Unfavorable workplace culture. D) Blocked communication.47. What does the author mean by “diffusion of responsibility” (Line 4, Para. 3)?A) The more people are around, the more they need to worry about their personal safety.B) The more people who witness an event, the less likely anyone will venture to participate.C) The more people idling around on the street, the more likely they need taking care of.D) The more people are around, the less chance someone will step forward to intervene.48. What happens when unsafe behavior at the workplace is not addressed by the leaders?A) No one will intervene when they see similar behaviors.B) Everyone will see it as the easiest way to deal with crisis.C) Workers have to take extra caution executing their duties.D) Workers are left to take care of the emergency themselves.49. What is the ultimate reason workers won’t act when they see unsafe operations?A) Preference of deferring the action to others. C) Fear of being isolated by coworkers.B) Anticipation of leadership intervention. D) Fear of having to do more work.50. What is critical to ensuring workplace safety?A) Workers be trained to operate their equipment properly.B) Workers exhibiting at-risk behavior be strictly disciplined.C) Supervisors create a safety environment for timely intervention.D) Supervisors conduct effective communication with frontline workers.Passage TwoQuestions 51 to 55 are based on the following passage.The term “environmentalist” can mean different things. It used to refer to people trying to protect wildlife and natural ecosystems. In the 21st century, the term has evolved to capture the need to combat human-made climate change.The distinction between these two strands of environmentalism is the cause of a split within the scientific community about nuclear energy.On one side are purists who believe nuclear power isn’t worth the risk and the exclusive solution to the climate crisis is renewable energy. The opposing side agrees that renewables are crucial, but says society needs an amount of power available to meet consumers’ basic demands when the sun isn’t shining and the wind isn’t blowing. Nuclear energy, being far cleaner than oil, gas and coal, is a natural option, especially where hydroelectric capacity is limited.Leon Clarke, who helped author reports for the UN’s Intergovernmental Panel on Climate Change, isn’t an uncritical supporter of nuclear energy, but says it’s a valuable option to have i f we’re serious about reaching carbon neutrality.“Core to all of this is the degree to which you think we can actually meet climate goals with 100% renewables,” he said. “If you don’t believe we can do it, and you care about the climate, you are forced to think about something like nuclear.”The achievability of universal 100% renewability is similarly contentious. Cities such as Burlington, Vermont, have been “100% renewable” for years. But these cities often have s mall populations, occasionally still rely on fossil fuel energy and have significant renewable resources at their immediate disposal. Meanwhile, countries that manage to run off renewables typically do so thanks to extraordinary hydroelectric capabilities.Germany stands as the best case study for a large, industrialized country pushing into green energy. Chancellor Angela Merkel in 2011 announced Energiewende, an energy transition that would phase out nuclear and coal while phasing in renewables. Wind and solar power generation has increased over 400% since 2010, and renewables provided 46% of the country’s electricity in 2019.But progress has halted in recent years. The instability of renewables doe sn’t just mean energy is often not produced at night, but also that solar and wind can overwhelm the grid during the day, forcing utilities to pay customers to use their electricity. Lagging grid infrastructure struggles to transport this overabundance of green energy from Germany’s north to its industrial south, meaning many factories still run on coal and gas. The political limit has also been reached in some places, with citizens meeting the construction of new wind turbines with loud protests.The result is that Germany’s greenhouse gas emissions have fallen by around 11.5% since 2010—slower than the EU average of 13.5%.51. What accounts for the divide within the scientific community about nuclear energy?A) Attention to combating human-made climate change.B) Emphasis on protecting wildlife and natural ecosystems.C) Evolution of the term ‘green energy’ over the last century.D) Adherence to different interpretations of environmentalism.52. What is the solution to energy shortage proposed by purists’ opponents?A) Relying on renewables firmly and exclusively.B) Using fossil fuel and green energy alternately.C) Opting for nuclear energy when necessary.D) Limiting people’s non-basic consumption.53. What point does the author want to make with cities like Burlington as an example?A) It is controversial whether the goal of the whole world’s exclusive dependence on renewables is attainable.B) It is contentious whether cities with large populations have renewable resources at their immediate disposal.C) It is arguable whether cities that manage to run off renewables have sustainable hydroelectric capabilities.D) It is debatable whether traditional fossil fuel energy can be done away with entirely throughout the world.54. What do we learn about Germany regarding renewable energy?A) It has increased its wind and solar power generation four times over the last two decades.B) It represents a good example of a major industrialized country promoting green energy.C) It relies on renewable energy to generate more than half of its electricity.D) It has succeeded in reaching the goal of energy transition set by Merkel.55. What may be one of the reasons for Germany’s progress having halted in recent years?A) Its grid infrastructure’s capacity has fallen behind its development of green energy.B) Its overabundance of green energy has forced power plants to suspend operation during daytime.C) Its industrial south is used to running factories on conventional energy supplies.D) Its renewable energy supplies are unstable both at night and during the day.Part IV Translation (30 minutes) Directions: For this part, you are allowed 30 minutes to translate a passage from Chinese into English. You should write your answer on Answer Sheet 2.中国的传统婚礼习俗历史悠久，从周朝开始就逐渐形成了一套完整的婚礼仪式，有些一直沿用至今。
I.J. Intelligent Systems and Applications, 2013, 07, 9-15Published Online June 2013 in MECS (/)DOI: 10.5815/ijisa.2013.07.02Integration of Temporal Contextual Information for Robust Acoustic Recognition of Bird Speciesfrom Real-Field DataIosif Mporas, Todor Ganchev, Otilia Kocsis, Nikos FakotakisDept. of Electrical & Computer Engineering, University of Patras, 26500 Patras, GreeceE-mail: {imporas, tgachev, okocsis, fakotaki}@upatras.grOlaf Jahn, Klaus RiedeZoologisches Forschungsmuseum Alexander Koenig, 53113 Bonn, GermanyE-mail: {o.jahn.zfmk, k.riede.zfmk}@uni-bonn.deAbstract—We report on the development of an automated acoustic bird recognizer with improved noise robustness, which is part of a long-term project, aiming at the establishment of an automated biodiversity monitoring system at the Hymettus Mountain near Athens, Greece. In particular, a typical audio processing strategy, which has been proved quite successful in various audio recognition applications, was amended with a simple and effective mechanism for integration of temporal contextual information in the decision-making process. In the present implementation, we consider integration of temporal contextual information by joint post-processing of the recognition results for a number of preceding and subsequent audio frames. In order to evaluate the usefulness of the proposed scheme on the task of acoustic bird recognition, we experimented with six widely used classifiers and a set of real-field audio recordings for two bird species which are present at the Hymettus Mountain. The highest achieved recognition accuracy obtained on the real-field data was approximately 93%, while experiments with additive noise showed significant robustness in low signal-to-noise ratio setups. In all cases, the integration of temporal contextual information was found to improve the overall accuracy of the recognizer.Index Terms— Bioacoustics, Biodiversity Informatics, Acoustic Bird Species Recognition, Automatic RecognitionI.IntroductionOver the last years one of the most crucial issues that governments and international organizations have to deal with is the conservation of biodiversity. The protection of the endangered species is of prior importance for the conservation of biodiversity and is based primarily on the accurate monitoring of the biodiversity and secondarily on the application of targeted conservation actions, which are based on the quantitative measures of the monitored biodiversity status. Major importance for the conservation of biodiversity has the observation and the monitoring of birds [1].Significant amount of information about the activity of the birds has been collected by expert ornithologists. In this effort the ornithologists recognize the bird species from their vocalizations, study the interaction among them and locate their habitats. Such surveys require the repeated physical presence of expert ornithologists in the field and thus become time consuming and tedious. Moreover, the manual observations heavily rely on the visual and acoustic abilities of the surveyor as well as on the degree of his/her knowledge on the family of bird species which are under investigation. Finally, the difficulty of the task restricts most of the biodiversity monitoring surveys to take place in infrequent time intervals, especially for the hard to access areas, thus not allowing the long-term biodiversity monitoring of inhospitable habitats.The above mentioned disadvantages of manual observations of the bird activity have led to the development and study of several approaches for automatic recognition of bird species from their vocalizations over the last decade. Automatic recognition of acoustic bird species falls in the pattern recognition task, which involves preprocessing and feature extraction of the audio signal and classification over the parameterized audio.Several approaches in automatic bird species recognition from their vocalizations have been proposed, most of which share techniques widely used in speech and audio processing. Such techniques are the template-matching (dynamic time warping) [2, 3] and the hidden Markov models [4], which have extensively been used in the similar task of speech recognition. Hidden Markov models have been used in more recent studies [5-7], due to their well known structure. Neural10Integration of Temporal Contextual Information forRobust Acoustic Recognition of Bird Species from Real-Field Datanetworks have also been used for the recognition of bird vocalizations using spectral and temporal parameters of the audio signal [8, 9]. Other approaches use Gaussian mixture model based structures [6, 10, 11], support vector machines [12] and decision trees [13] for the recognition of bird songs. Other proposed classification schemes are based on sinusoidal modeling of bird syllables [14] and bird syllable pair histograms [15]. Different parametric representations for the bird vocalizations audio signals have been used, among which Mel frequency cepstral coefficients [5, 6, 16, 17] are the most widely used. Other audio features which have been proposed in the literature are the linear predictive coding [16], linear predictive cepstral coefficients [16], spectral and temporal audio descriptors [12], and tonal-based features [17].In most of the previous studies on the task of bird species recognition from their vocalizations in-lab conditions of recordings were used, without the presence of real environmental noise [2, 3, 4, 6, 12, 13]. In exception of most of the published work, in [17] waterfall noise was added to bird recordings and it was shown that the recognition of bird sounds in noisy conditions reduces significantly the recognition performance. In this article, we evaluate several different machine learning algorithms on the task of bird species classification in real-field conditions, under the concept of AMIBIO project (LIFE08-NAT-GR-000539: Automatic Acoustic Monitoring and Inventorying of Biodiversity, Project web-site: http://www.amibio-project.eu/).The rest of this article is organized as follows. In Section 2, the bird species recognition task in real-field is presented. Section 3 offers description of the audio data used and the experimental setup that was followed in the present evaluation. In Section 4 the experimental results are presented. Section 5 concludes this work. II.Acoustic Bird Species Recognition in Real-Field with Temporal Context InformationIn automatic bird species recognition from audio data 24/7 monitoring of specific habitats is achieved, while the information needed for biodiversity monitoring, animal species population estimation and species behavior understanding is extracted. The recognition of bird species is an audio pattern recognition task, and in brief is structured in (i) the audio acquisition stage, (ii) the audio parameterization stage and (iii) the classification stage. When recognition of the bird species is performed in the birds habitats the captured audio signal includes interferences that are additive to the vocalizations of the bird species. Typical interferences that are met in such habitats are the rain, the wind, the sum of the leaves, vocalizations from other animal species of the habitat, sounds produces by human activities, etc. In general, for the recognition of species in such a noisy environment detection of audio intervals with bird vocalizations precedes the species classification stage. The concept is illustrated in Figure 1.Briefly, the audio signal is captured by a microphone, next amplified and then sampled at 32 kHz, so that the wide frequency range of bird vocalizations from various species is covered. A precision of 16-bits per sample is used to guarantee sufficient resolution of details for the subsequent processing of the signal. After the audio acquisition stage the signal is decomposed to overlapping feature vectors of constant length, using spectral and temporal audio parameterization algorithms. The sequence of feature vectors is used as input to the bird activity detection block where the audio signal is binary segmented to intervals with or without bird vocalizations. Finally, the bird vocalization intervals are processed by the bird species classification block inorder species-specific recognition to be performed.Fig. 1: Block diagram of the bird species recognition scheme in real-field conditions with temporal context information post-processingSince classification is performed on frame level and each bird vocalization will appear in a number of consecutive audio frames the use of temporal context information for each frame as a post processing step would detect single frame misclassifications and improve the overall performance. In detail, this post-processing step aims at eliminating sporadic erroneous labeling of the current audio frame, e.g. due to momentary burst of interference, and thus contributes for improving the overall classification accuracy. The exploitation of the temporal contextual information, i.e. the labeled decision of the closest neighbor frames, is an effective way to detect and correct such sporadic erroneous frame labels. In particular, when the N preceding and the N successive audio frames, i.e. the temporal context of the current frame, are classified to one bird species vocalization then the current frame is also (re)labeled as of this bird species. The length w of the temporal context window is subject to investigation and in the general case it is equal to w=2N+1, where N≥0. The case N=0 , i.e. for temporal context window length w=1, corresponds to the elimination of the post-processing step of the classified labels.In real-field the presence of non-stationary noises originating from the environment makes the species classification task more difficult and challenging. The degree of interference of the environmental noises and the actual signal-to-noise ratio are crucial for the recognition of bird species. In this work we also focus on the effect of the distance of the bird from the monitoring station (field microphone) as expressed by different signal-to-noise ratios, to the species classification performance.III.Experimental SetupA description of the audio data used in the present evaluation, the audio parameterization algorithms used, the machine learning classification algorithms that were tested and the experimental protocol that was followed are provided in this section.The dataset used in the present article consists of recordings of two bird species which are known to be present at the Hymettus Mountain, a Natura 2000 site in Attica, Greece, namely the Eurasian Chaffinch (Fringilla coelebs) and the Common Kingfisher (Alcedo atthis). The recordings of the vocalizations of these bird species have been collected and manually labeled by expert ornithologists of the Zoologisches Forschungsmuseum Alexander Koenig (ZFMK). In order to test the bird species classification performance in different signal-to-noise ratios randomly selected recordings from the Hymettus area (from four different locations) were interfered to the bird vocalizations as additional noise. The amount of audio data used in the evaluation was approximately 14 minutes of recordings for all bird species.The parameterization of the audio signals was performed using a diverse set of audio parameters. In particular, the audio signals were blocked to frames of 20 milliseconds length with 10 milliseconds time shifting step. Two temporal and sixteen spectral audio descriptors were used. The two temporal audio descriptors which were used are the frame intensity (Int) and the zero crossing rate (ZCR). The sixteen spectral audio descriptors which were used are the 12 first Mel frequency cepstral coefficients (MFCCs) as defined in the HTK setup [18], the root mean square energy of the frame (E), the voicing probability (Vp), the harmonics-to-noise ratio (HNR) by autocorrelation function and the dominant frequency (Fd) normalized to 500 Hz. The openSMILE acoustic parameterization tool [19] was used for the computation of the spectral audio parameters. After the computation of the audio parameters a post-processing with dynamic range normalization was applied to all audio features in order the range of their numerical values to be equalized.A number of different machine learning algorithms were examined in the evaluation of the bird species classification step: (i) the k-nearest neighbors classifier with linear search of the nearest neighbor without weighting of the distance –here referred as instance based classifier (IBk) [20], (ii) a 3-layer Multilayer perceptron (MLP) neural network with architecture 18–10–1 neurons (all sigmoid) trained with 50000 iterations [21], (iii) the support vector machines utilizing the sequential minimal optimization algorithm (SMO) with a radial basis function kernel [22], (iv) the pruned C4.5 decision tree (J48), with 3 folds for pruning and 7 for growing the tree [23], (v) the Bayes network learning (BayesNet) using a simple data-based estimator for finding the conditional probability table of the network and hill climbing for searching network structures [24], (vi) the Adaboost M1 method (Adaboost(J48)) using the pruned C4.5 decision tree as base classifier [25], and (vii) the bagging algorithm (Bagging(J48)) for reduce of the variance of the pruned C4.5 decision tree base classifier [26].For the implementations of these algorithms the Weka software toolkit [24] was used. For all the above mentioned evaluated algorithms the values of the undefined parameters have been set equal to the default ones.IV.Experimental ResultsA common experimental protocol was followed in all experiments as described in Section 3. Ten-fold cross validation experiments were performed on the audio data which were described in the previous section, thus resulting to non-overlapping training and test data subsets. In Figure 2, the performance of the classification algorithms, in frame level, for various signal-to-noise ratios is shown.Fig. 2: Accuracy rate (in percentages) of bird species recognition for different classification algorithms and various signal-to-noise ratiosFig. 3: Bird species classification accuracy (in percentages) for the Bagging (J48) algorithm at various signal-to-noise ratios and for different length ofthe temporal context information windowAs can be seen in Figure 2, the best performance was achieved by the two meta-classifiers used, i.e. the Adaboost(J48) and the Bagging(J48), which comes in agreement with [24], where it was reported that they often dramatically improve the classificationperformance. In particular, for high signal-to-noise ratios the boosting algorithm outperformed all the other evaluated classification algorithms (93.0% accuracy for 20 dB SNR), while for low signal-to-noise ratios the bagging meta-classifier offered slightly betterperformance than the boosting algorithm (76.6% accuracy for -6 dB SNR). The meta-classifiers are followed in average performance by the rest of the evaluated classifiers, i.e. the k-nearest neighbor algorithm (IBk), the C4.5 pruned decision tree (J48), the Bayesian network (BayesNet) and the support vector machines (SMO).A drop in the classification accuracy was found with the decrease of the signal-to-noise ratio for all the classifiers that were evaluated here, which is in agreement with the experimental results found in [17] for waterfall noise. It is worth mentioning that the k-nearest neighbor algorithm (IBk) and the decision tree algorithm (J48) achieved relatively high performance at noise-free conditions, i.e. for signal-to-noise ratio equal to 20 dB, approximately 3% less than the best performing meta-classifier. However, in noisy environments, such as SNR equal to 0 dB and -6 dB, they followed the best performing meta-classifier by approximately 5%. This is an indication of the advantage that the bagging and boosting algorithms can offer in real-field environments, where the presence of non-stationary interfering noises is frequent. Besides, low signal-to-noise ratio conditions are met in audio acquisition of bird vocalizations when the vocalizing bird is not close to the monitoring station installed in the field, but still captured by the microphone.After evaluating the baseline bird species recognition performance for several classification algorithms, the overall recognition performance after post-processing the labeled audio frames using the temporal context information was examined. Specifically, the effect of the temporal context information block was applied for the best performing in noisy conditions Bagging(J48) algorithm and at various signal-to-noise ratios as shown in Figure 3. The best performing configuration setup of the temporal context information block for each evaluated signal-to-noise ratios (SNRs) is indicated in bold.As can be seen in Figure 3, the effect of the temporal context information post-processing is significant for all signal-to-noise ratios and even more in the case of noisy environment, i.e. for low signal-to-noise ratios. In detail, the temporal context window length equal to three offers the best or close to the best performance across all the evaluated signal-to-noise ratios. The application of this window length (w=3) achieved approximately 3.5% absolute improvement of the bird species classification accuracy at -6 dB of signal-to-noise ratio. The improvement of the classification accuracy for signal-to-noise ratio equal to 20 dB is approximately 1% in terms of absolute recognition accuracy. The evaluated performance indicates the importance of the contextual information post-processing in the noisy real-field environment, since isolated erroneous labeling of audio frames coming from momentary bursts of interferences can be eliminated by the contextual audio frame labeling. V.ConclusionThe results presented in Section 4, show that the integration of temporal contextual information into the decision-making process of the acoustic bird recognizer contributes to the improvement of the overall recognition accuracy, as well as supports our assumption about the importance of temporal contextual information. As the experimental results show, the integration of temporal contextual information as a post-processor in the acoustic bird recognition contributes mainly to the improvement of the recognition accuracy in low SNR conditions. This observation can be explained with the temporal smoothing effect, which the proposed post-processing scheme implements, and the resultant elimination of sporadic mislabeling of audio frames due to momentary bursts of noise which is typical in real-field conditions. The effectiveness of the proposed post-processing scheme and its low computational and memory demands render it appropriate for mobile acoustic bird recognition applications and in other acoustic bird recognition applications with restricted energy resources.AcknowledgmentsThe authors would like to thank the anonymous reviewers for their careful reading of this paper and for their helpful comments. This work was supported by the AmiBio project (LIFE08 NAT/GR/000539), which is implemented with the contribution of the LIFE+ financial instrument of the European Union. Project web-site: www.amibio-project.eu.References[1] D.K. Dawson, M.G. Efford, ―Bird populationdensity estimated from acoustic signals,‖ Journalof Applied Ecology, vol. 46, 2009, pp. 1201–1209.[2]S.E. Anderson, A.S. Dave, and D. Margoliash,―Template-based automatic recognition ofbirdsong syllables from continuous recordings,‖ J.Acoust. Soc. America, 100(2), pp. 1209-1219, Au-gust 1996.[3]K. Ito, K. Mori, and S. Iwasaki, ―Application ofdynamic programming matching to classificationof budgerigar contact calls,‖ J. Acoust. Soc.America, 100(6), pp. 3947-3956, December 1996.[4]J.A. Kogan, and D. Margoliash, ―Automatedrecognition of bird song elements from continuousrecordings using dynamic time warping and hiddenMarkov models: A comparative study,‖ Journal ofAcoust. Soc. America, 103(4), pp. 2185-2196,April 1998.[5]V.M.. Trifa, A.N.G. Kirschel, and C.E. Taylor,―Automated species recognition of antbirds in a Mexican rainforest using hidden Markov models,‖ J. Acoust. Soc. America, 123(4), pp. 2424-2431, April 2008.[6]P. Somervuo, A. Harma, and S. Fagerlund,―Parametric repre-sentations of bird sounds for automatic species recognition,‖ IEEE Transactions on Audio, Speech and Language Processing, vol.14, no. 6, pp. 2252–2263, 2006.[7]I. Agranat, ―Automatically Identifying AnimalSpecies from their Vocalizations,‖ Wildlife Acoustics, Inc., Concord, Massachusetts, March 2009.[8]S.A. Selouani, M. Kardouchi, E. Hervet, and D.Roy, ―Automatic birdsong recognition based on autoregressive timedelay neural networks,‖ In Congress on Computational Intelligence Methods and Applications, pp. 1–6, Istanbul, Turkey, 2005.[9] A. L. Mcllraith and H. C. Card, ―Birdsongrecognition using backpropagation and multivariate statistics,‖ IEEE Transactions on Signal Processing, vol. 45, no. 11, pp. 2740–2748, 1997.[10]C. Kwan, K.C. Ho, G. Mei, et al., ―An automatedacoustic system to monitor and classify birds,‖ EURASIP J. on Applied Signal Processing, vol.2006, Article ID 96706, 19 pages, 2006.[11]H. Tyagi, R.M. Hegde, H.A. Murthy, and A.Prabhakar, ―Automatic identification of bird calls using spectral ensemble average voiceprints,‖In Proc. of the 13th European Signal Processing Conference, Florence, Italy, September 2006. [12]S. Fagerlund, ―Bird Species Recognition UsingSupport Vector Machines,‖ EURASIP Journal on Advances in Signal Processing, Vol. 2007, Article ID 38637, 8 pages, doi:10.1155/2007/38637. [13]E. Vilches, I.A. Escobar, E.E. Vallejo, and C.E.Taylor, ―Data mining applied to acoustic bird species recognition,‖ In Proceedings of the 18th International Conference on Pattern Recognition, vol. 3, pp. 400–403, Hong Kong, August 2006. [14]A. Harma, ―Automatic identification of birdspecies based on sinusoidalmodelling of syllables,‖ In Proceedings of IEEE Interna-tional Conference on Acoustics, Speech, and Signal Processing, vol.5, pp. 545–548, Hong Kong, April 2003.[15]P. Somervuo and A. Harma, ―Bird songrecognition based on syllable pair histograms,‖ In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 5, pp. 825–828, Montreal, Canada, May 2004. [16]C.H. Lee, Y.K. Lee, and R.Z. Huang, ―AutomaticRecognition of Bird Songs Using Cepstral Coefficients,‖ Journal of Information Technologyand Applications, vol. 1, no. 1, pp. 17-23, May 2006.[17]P. Jancovic and M. Kokuer, ―Automatic Detectionand Recognition of Tonal Bird Sounds in Noisy Environments,‖ EUR ASIP Journal on Advances in Signal Processing, Vol. 2011, Article ID 982936,10 pages, doi: 10.1155/2011/982936.[18]S. Young, G. Evermann, M. Gales, T. Hain, D.Kershaw, X. Liu, G. Moore, J. Odell, D. Ollason,D. Povey, V. Valtchev, and P. Woodland, TheHTK book (for HTK Version 3.4), Cambridge University Engineering Department.[19]F. Eyben, M. Wollmer, and B. Schuller,―OpenEAR - intro-ducing the Munich open-source emotion and affect recognition toolkit,‖ In Proc. of the 4th International HUMAINE Association Conference on Affective Computing and Intelligent Interaction (ACII 2009).[20]D. Aha, D. Kibler, "Instance-based learningalgorithms", Machine Learning, 6 (1991), pp. 37–66.[21]T.M. Mitchell, Machine Learning, McGraw-HillInternational Editions (1997).[22]S.S. KeerthiS.S., S.K. Shevade, C. Bhattacharyya,K.R.K. Murthy, "Improvements to Platt's SMO algorithm for SVM classifier design, Neural Computation, 13 (3) (2001), pp. 637–649.[23]R. Quinlan, C4.5: Programs for Machine Learning,Morgan Kaufmann Publishers, San Mateo, CA (1993).[24]H.I. Witten, and E. Frank. Data Mining: practicalmachine learning tools and techniques. Morgan Kaufmann Publishing.[25]Yoav Freund, Robert E. Schapire: Experimentswith a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.[26]Leo Breiman (1996). Bagging predictors. MachineLearning. 24(2):123-140.Authors’ ProfilesIosif Mporas is senior researcher at the University of Patras and non-tenured Assistant Professor at the Technological Educational Institute of Patras. His research interests include speech and audio signal processing, pattern recognition, automatic speech recognition, automatic speech segmentation and spoken language/dialect identification.Todor Ganchev is senior researcher at the University of Patras and Assistant Professor at the Technical University of Varna. His research interests includespeech and audio signal processing, pattern recognition, speaker identification and verification, and bioacoustics.Otilia Kocsis is senior researcher at the University of Patras. Her research interests include audio signal processing, dialogue systems, multimodal interfaces, human-computer interaction, and user modeling.Nikos Fakotakis is Professor at the University of Patras. His research interests include speech and audio signal processing, pattern recognition, natural language processing, dialogue systems, human-computer interaction, artificial intelligence, and bioacoustics.Olaf Jahn is senior ornithologist at the Zoologisches Forschungsmuseum Alexander Koenig. His research interests include ornithology, biodiversity assessment, bioacoustics, and environmental monitoring.Klaus Riede is director’s assistant and senior researcher at the Zoologisches Forschungsmuseum Alexander Koenig, and Professor at the University of Bonn. His research focuses on taxonomy (including bar-coding) of orthoptera, with a strong focus on tropical species, ecology and bioacoustics.。
解密16 阅读理解之主旨大意题主旨大意题是高考阅读理解的主要题型之一，旨在考查考生对文章大意或者文章中心思想的把握和归纳能力。
此类题数量较大，在15个题中约占2-3个。
◆主旨大意题的分类1. 从考查对象上划分，主旨大意题可分为两种①篇章主旨：针对全文的主题进行提问。
主题句出现在首段的居多，其次是末段。
②段落主旨：针对某一段或几段的主题提问。
主题句可能是段落的首句、末句，也可能需要从上下文中寻找或总结。
2. 考查内容上划分，主旨大意题可分为三种①主题类(内容)，考查文章或段落的主旨大意；②目的类，考查文章或段落的写作目的；③标题类，要求考生选出文章的最佳标题。
◆设问特点：1. 考查全文主旨或段落大意。
2. 正确选项概况范围大小恰当，主旨判断准确。
3. 错误选项的特点常常是太大、太窄或者偏离主题，主观臆断。
4. 常以main idea, best idea, subject, mainly discuss 等词提问。
◆常考问题：1. 中心思想类The main point /idea of the pa ssage is…The passage is mainly about…The passage mainly discusses…The last but one paragraph is chiefly concerned with…?Which of the following statements best expresses the main idea of the passage?2. 标题类Which of the following is the best title of the passage?The best title for the passage would be …3. 目的类The author’s main purpose in writing the passage is to …The passage is meant to ….In writing this passage, the author mainly intends to…【名师指导】文章主题常常可以通过文章的写作方法来体现，有以下五种情况：1. 中心主题句出现在文首开门见山，提出主题，随之用细节来解释、支撑或发展主题句所表达的主题思想。
《计算机专业英语》一、Choice （选择）（15 题，每题1 分，共15 分）Choose the best answer for each blank.（从每题四个选项中，选出最合适的一项）1) As an operating system repeatedly allocates and frees storage space, many physically separated unused areas appear. This phenomenon is called ______.A. fragmentationB. compactionC. swappingD. paging2) We can use the word processor to _________ your documents.A. editB. computeC. translateD. unload3) _____________ infected computer may lose its data.A. FileB. Data baseC. VirusD. Program4) One use of networks is to let several computers share ____ such as file system, printers, and tape drives.A. CPUB. memoryC. resourcesD. data5) A firewall is a ____ system designed to ___ an organization’s network against threats.A. operating, preventB. programming, developC. security, protectD. service, exploit6) The ____ has several major components, including the system kernel, a memory management system, the file system manager, device drivers, and the system libraries.A. applicationB. information systemC. networkD. operating system7) ____ is the address of a variable or a variable in which the address of anothervariable is stored.A. DirectorB. PointerC. ArrayD. Record8) C++ is used with proper ____ design techniques.A. object-orientedB. object-basedC. face to objectD. face to target9) A data ( ) is a file that contains metadata-that is, data about data.A. structureB. tableC. baseD. dictionary10) A network software consists of ( ), or rules by which processes can communicate.A. protocolsB. programsC. devicesD. computers11) The firewall device is a ( ) system for connecting a computer network toother computer network.A. hardwareB. softwareC. securityD. I/O12) We can use the word processor to _________ your documents.A. editB. computeC. translateD. unload13) _________ processing offers many ways to edit text and establish document formats. You can easily insert, delete, change, move and copy words or blocks of text.A. DataB. DatabaseC. WordD. File14) A ________ copies a photograph, drawing or page of text into the computer. A．scanner B．printer C．display D．Keyboard15) _________ is the sending and receiving of the message by computer. It is a fast, low-cost way of communicating worldwide.A．LAN B．Post office C．E-Mail D．Interface二、Cloze （完形填空）（4 篇篇20 题，每题1.5 分，共30 分）Choose the best answer for each blank.（从每题选项中，选出最合适的一项）Passage 1Have you ever wondered how information processed by the system unit is1) into a form that you can use? That is the role of output devices. While inputdevices convert what we understand into what the system unit can process, output devicesconvert what the system unit has processed into a form that we can understand. Output devices 2) machine language into letters, numbers, sounds, and images that peoplecan understand.Competent end users need to know about the most commonly used input devices, including keyboards, mice, 3) , digital cameras, digitizing tablets, voice recognition,and MIDI devices. Additionally, they need to know about the most commonly used output devices. And end users need to be aware of 4) input and output devices such as fax machines, multifunctional devices, 5) telephones, and terminals.1) A. converted B. convinced2) A. transact B. translate3) A. scanners B. scan4) A. combination B. communication5) A. Intranet B. InternetPassage 2ABC is an interactive programming language and environment for personal computing, originally 6) ____ as a good replacement for BASIC. It was designed by 7)____ a task analysis of the programming task.ABC is easy to learn (an hour or so for someone who has already programmed), and yet easy to use. Originally intended as a language for 8) ______, it has evolved into a powerful tool for beginners and experts alike.Some features of the language:op-down programmingSome features of the environment:logging outediting, or entering input to a program6) A. intending B. intended7) A. first does B. first doing8) A. beginners B. beginning9) A. easily be combined B. easy be combined10) A. is shown to B. is showing toPassage 3Bulletin Board Systems (BBS)Bulletin Board Systems are a 11)______ telecommunications services provided bythe internet, public information services, and 12)_______ of business firms, organization, and end user groups. An electronic bulletin board system allows you to post public or private messages that other end 13)______ can read by accessing the BBS with their computers. Establishing a small BBS for a business is not that difficult. Minimum requirements are a microcomputer with a hard disk drive, custom or packaged BBS 14)_______, modem and a telephone line. Bulletin Board System serves as a central location to post and pick up messages or upload and download data files or programs 24 hours a day. A BBS helps end users ask questions, get advice, locate and share information, and get 15)_______ touch with other end users.11) A. popular B. unpopular12) A. thousand B. thousands13) A. use B. users14) A. software B. hardware15) A. on B. inPassage 4A: displaying B: messages C: received D: network E: usersElectronic MailMillions of end 16)________ now depend on electronic mail (e-mail) to send andreceive electronic 17)________. You can send e-mail to anyone on your 18)________ for storage in his/her electronic mail boxes or magnetic disk drives. Whenever they are ready, they can read their electronic mail by 19)________ it on the video screens at their workstations. So, with only a few minutes of effort (and a microseconds of transmission),a message to one or many individuals can be composed, sent, and 20)_______.三、Term Translation （术语翻译）（10 题，每题1.5 分，共15 分）Write out their English abbreviations of the following terms and then translate them into Chinese.（写出下列专业术语的英文简称，并将其翻译成汉语）1) Personal Digital Assistant2) Wireless-Fidelity3）Digital Video Disc4）Joint Photographic Experts Group5）Graphical User Interface6）Professional Hypertext Preprocessor7）Simulation Language8）Object-oriented Programming9）Uninterruptable Power Supply10）Universal Serial Bus四、Short Answer （简答）（2 题，每题4 分，共8 分）Answer the following questions in English.（用英文回答下列问题）1）Please write down the components of hardware.2) Please write down the classification（分类）of operating system according to the application area（应用领域）.五、Sentence Translation （句子翻译）（8 题，每题4 分，共32 分）Translate the following English sentences into Chinese.（将下列英文句子翻译成汉语）1) This input is digitized and converted to standard text that can be further processed by programs such as a word processor.2）The most common input devices are the keyboard and the mouse.3) The network operating system is designed to control the computers that are linked together via a network.4) The BIOS （Basic Input Output System）is responsible for waking up the computer when you turn it off.5）A primary purpose of programming languages is to enable programmers to express their intent for a computation more easily than they could with a lower-level language or machine code.6）During the last few decades, a large number of computer languages have been introduced.7) The entire office automation system comprises five sub-systems.8) Image Processing System allows end users to electronically capture, store, process, and retrieve images of documents.。
专题20 阅读理解（社会生活类）1.D【2019·全国I】During the rosy years of elementary school(小学), I enjoyed sharing my dolls and jokes, which allowed me to keep my high social status. I was the queen of the playground. Then came my tweens and teens, and mean girls and cool kids. They rose in the ranks not by being friendly but by smoking cigarettes, breaking rules and playing jokes on others, among whom I soon found myself.Popularity is a well-explored subject in social psychology. Mitch Prinstein, a professor of clinical psychology sorts the popular into two categories: the likable and the status seekers. The likables’ plays-well-with-others qualities strengthen schoolyard friendships, jump-start interpersonal skills and, when tapped early, are employed ever after in life a nd work. Then there’s the kind of popularity that appears in adolescence: status born of power and even dishonorable behavior.Enviable as the cool kids may have seemed, Dr. Prinstein’s studies show unpleasant consequences. Those who were highest in status in high school, as well as those least liked in elementary school, are “most likely toengage(从事)in dangerous and risky behavior.”In one study, Dr. Prinstein examined the two types of popularity in 235 adolescents, scoring the least liked, the most liked and the highest in status based on student surveys(调查研究). “We found that the least well-liked teens had become more aggressive over time toward their classmates. But so had those who were high in status. It clearly showed that while likability can lead to healthy adjustment, high status has just the opposite effect on us."Dr. Prinstein has also found that the qualities that made the neighbors want you on a play date-sharing, kindness, openness — carry over to later years and make you better able to relate and connect with others.In analyzing his and other research，Dr. Prinstein came to another conclusion: Not only is likability related to positive life outcomes, but it is also responsible for those outcomes, too. "Being liked creates opportunities forlea rning and for new kinds of life experiences that help somebody gain an advantage, ” he said.32. What sort of girl was the author in her early years of elementary school?A. Unkind.B. Lonely.C. Generous.D. Cool.33. What is the second paragraph mainly about？A. The classification of the popular.B. The characteristics of adolescents.C. The importance of interpersonal skills.D. The causes of dishonorable behavior.34. What did Dr. Prinstein’s study find about the most liked kids?A. They appeared to be aggressive.B. They tended to be more adaptable.C. They enjoyed the highest status.D. They performed well academically.35. What is the best title for the text?A. Be Nice-You Won’t Finish LastB. The Higher the Status, the BeerC. Be the Best-You Can Make ItD. More Self-Control, Less Aggressiveness【答案】32. C 33. A 34. B 35. A【解析】本文是一篇说明文。
Classification of networks based on inherentstructural characteristicsTajudeen H.Sikiru∗,Adisa A.Jimoh†,Yskandar Hamam‡,John T.Agee†and Roger Ceschi§∗Department of Electrical Engineering,Tshwane University of Technology,South Africa and LISV of UVSQ,France.Email:sikiruth@tut.ac.za†Department of Electrical Engineering,Tshwane University of Technology,South Africa.Email:jimohaa@tut.ac.za;ageejt@tut.ac.za‡ESIEE Paris,France and FSATI at Tshwane University of Technology,South Africa.Email:hamama@tut.ac.za§LISV of UVSQ and ESME Sudria,France.Email:ceschi@esme.frAbstract—This paper seeks to identify and classify power system networks based on their inherent definitive structural property.The participation between the load buses is observable from the eigenvectors obtained from a Schur complement of the Y-admittance matrix.This is used to classify power system networks as either topologically strong or weak.Results show that in a topologically weak network,load voltages are below the nominal voltage limit.Conversely,in a topologically strong network they are above the nominal limit.I.I NTRODUCTIONThe main purpose of transmission networks is to convey power from generating stations to load centres.Every trans-mission network has unique characteristics arising from the manner in which lines are interconnected and the impedance values of such lines[1].It is important to identify the effect of these two factors on the operational behaviour of a power system network.Since,a transmission network cannot be loaded beyond its stability limit[2].The direct consequence is that transmission network determines the amount of power that could be transported from generating stations,even if the generating stations have higher supply capacity[3].Hence, the level of load demand that could be met in a power system network directly depends on the inherent structural characteristics[4]–[7]of the network.These characteristics do not only affect the amount of transferable power,it also determines the locations and sizes of the other network devices such as reactive power compensators[6],harmonicfilters[5], and new generator location[7]that could boost the operational efficiency of a network.This paper discusses the identification and classification of power system networks based on their structural character-istics.For the remainder of the paper,section II presents the inherent structural characteristics and classification of net-works,while section III presents and discusses two numerical examples.Section IV concludes the paper.II.I NHERENT STRUCTURAL CHARACTERISTICS ANDCLASSIFICATION OF NETWORKSA.The inherent structural characteristics of networks Power system operations are represented by two variable quantities,current and voltage,which are interrelated through the network structure called the Y-admittance matrix.The Y-admittance matrix captures the nature of the structural interconnection of buses and the value of the line impedance between them[6],[7].The currentflow in the network and the bus voltages are governed by circuit theorem,mathematically represented asI=Y V(1) where Y−1=Z,Y is admittance,while Z is the impedance of the network.Suppose the Y-admittance matrix is partitioned asY=Y GG Y GLY LG Y LL(2)where the Y-admittance matrix is a square matrix with dimension(G+L)×(G+L),Y GG is a square matrix of dimension G×G containing the connectivity to generator buses.Y GL is a G×L matrix relating the generator to load buses.Y LG is the transpose of Y GL.Y LL is a square matrix of dimension L×L containing the connectivity to load buses.G is the number of generator buses and L is the number of load buses in the network respectively.The matrix Y GG is a diagonally dominant matrix[8]since the diagonal elements of this matrix are|a ii|≥Gj=1j=i|a ij|for all i=1,2,···,G(3)Due to this property,matrix Y GG is non-singular and invertible[8],[9].978-1-4673-2673-5/12/$31.00c 2012IEEETherefore,the Schur complement[10],[11]of Y GG in Y from(2)isC LL=Y LL−Y LG Y−1GGY GL(4) The relationship between this Schur complement[10]and the Y-admittance matrix isdet Y=det Y GG det C LL(5) Matrix C LL is equivalent to the load admittance matrix where the influence of generator buses has been eliminated.It contains only structural characteristics of load buses.Since generators are the sources of active power in a network, generator voltages are presumed constant and known,because they are easily controllable.The voltages of interest and the most critical are those of load voltages in power system analysis[1].The relationship between the load structural characteristics and the load voltages becomes obvious from expanding(1)asI G I L=Y GG Y GLY LG Y LLV GV L(6)The algebraic manipulation of(6)gives[V L]=[C LL]−1[I L−W LG I G](7)Where W LG=Y LG Y−1GG .The load structural characteristics(C LL)is inversely related to the load voltages as shown by(7).The effect of the structural interconnection between load buses and the network load voltages could only become clearer by quantifying the structural impact of the load buses on the load voltages.To achieve this,the eigenvalue decomposition[12]is used to analyze the structural impact of the load buses asC LL=MRM∗=ni=1m iµi m∗i(8)Where M is an orthonormal matrix with corresponding m i eigenvectors.The diagonal matrix R has the eigenvaluesµi as its diagonal elements.The inverse of matrix C LL isC−1 LL =MR−1M∗=ni=1m i m∗iµi(9)Substituting(9)into(7)yields[V L]=[ni=1m i m∗iµi][I L−W LG I G](10)The effect of the interconnectivity and line impedance values between load buses and their effect on the overall load voltages are revealed in(10)through the reciprocal relationship be-tween the bus eigenvalues and the bus voltages.Buses associ-ated with the smallest eigenvalues have the most contributively effect on the load voltages based on the reciprocal relationship presented in(10).B.Classification of networksLine impedance is made up of resistive and reactive components.The reactive component of transmission lines contributes to the reactive powerflow in the network[13]. Reactive component may consist of inductive and capacitive properties.The voltages at the load buses depend on the ade-quacy of reactive power in the network.Transmission networks with sufficient reactive property may have bus voltages above the nominal voltage limit of 1.0p.u.On the other hand, shortage of this property may cause the bus voltages to be below the nominal voltage limit[14].In an ideal network, where there is adequate reactive element in the network and the total impedances of the transmission network and the load are exactly matched,the voltages on all the buses will be at1.0 p.u(the nominal voltage value)[1].However,in reality this is not achievable because of environmental factors that limit the expansion of the network,scarce resources and unforeseen load growth.The best structural design of a network that could be hoped for is the one that allows the load voltages to be within reasonable range in respect to the nominal voltage limit. Depending on the topological structure of a network and its line impedances,a network acquires certain definitive property that determines voltages at the load buses.Since,load voltages are not allowed to deviate significantly from the nominal value because of power quality and stability issues,the total impedance of loads in a network must be matched with that of the transmission network for maximum power to be transferable to the load[15].The satisfaction of this circuit theorem condition,limits the maximum loading a transmission network can support.Thus,the definitive property a network acquires based on its topological structure is unique.As such, a network could have its load voltages to be generally above the nominal limit,which we termed topological strong network or below the nominal limit,which we define as topologically weak network.As load increases or reduces in a network,the effect is a corresponding reduction or increase in load voltages. However,a network will retain its definitive property except there is a significant change in the network topology.Hence,a network that is topologically strong or weak will still exhibit the same characteristics despite a small variation in loading, since the impedances of the transmission network and load are expected to be matched to ensure operational efficiency of the network.This definitive property is inherent in all power system networks.The structural characteristics of load buses captured by the matrix C LL could be used to determine the definitive property of networks,since each bus is associated with an eigenvalue based on the electrical distance between the load buses.The association of a unique eigenvector to a load bus corresponding to the smallest eigenvalue,we have termed the“participation between load buses”.For a network where the buses are far away from one another,the absolute value of the smallest eigenvalue will be zero(i.e.|µn|=0to a precision of10−4). This indicates a network with less reactive element and con-sequently less reactive power support.The eigenvectors(m i)corresponding to the smallest eigenvalue will have the same value,indicating the non-participation electromagnetically be-tween the buses.This characteristic is typical of topologically weak networks.On the other hand,when the absolute value of the smallest eigenvalue is greater than zero(i.e.|µn|>0to a precision of10−4),the corresponding absolute eigenvectors will have different values.This characterised a topologically strong network,where the electrical distance between load buses is small.The next section presents two numerical examples,one each for topologically weak and strong network respectively.III.N UMERICAL EXAMPLES AND DISCUSSIONA.IEEE30bus networkThefirst numerical example to be considered in this section is the IEEE30bus network.The single line diagram is shown in Fig.1.The absolute value of the smallest eigenvalue for this test network is less than the precision defined,hence it is zero,the corresponding eigenvectors associated with this eigenvalue are the same as shown in Fig.2.The unchanging nature of the eigenvectors associated with the load buses shows the non-participation between these buses as presented in Fig.2.This is due to the large electrical distances between the load buses as captured by the Y-admittance matrix.The data required to build the Y-admittance matrix for this test network are shown in the appendix.The non-participation between the load buses and the fact that the smallest eigenvalue is zero,indicate that this test network is a topologically weak network.As such,its load bus voltages are expected to be generally below the nominal limit of1.0p.u. Fig.3shows the voltage profile for this test network and all the load voltages are well below the nominal limit.In order to illustrate the non-effect of loading on the unique definitive property of a network,which is indeed inherent to a network due to its topological characteristics,a50%reduction in loading at all the buses was carried out;the new network bus voltages are shown in Fig.3.Even with a50%reduction in total loading of the network,the bus voltages are all still below the nominal voltage limit.This network is indeed a topologically weak network.B.Southwest40bus networkIn the case of the second numerical example,we will consider the Southwest England40bus network.The single line diagram for this network is shown in Fig.4.The smallest eigenvalue(in absolute value)is greater that the precision defined for this test network and it is0.0045.The eigenvectors corresponding to this smallest eigenvalue is shown in Fig.5. The eigenvectors associated with each load buses have varying numerical values as seen in Fig.5and hence unique for each load bus.This property arises from the small electrical distances between the load buses and the strong structural tie between them.The transmission network data for this test network are shown in the appendix.The varying numerical values of each eigenvectorindicatesFig.1.IEEE30busnetworkFig.2.Eigenvectors corresponding to the smallest eigenvalue of IEEE30 busnetworkFig.3.V oltage profiles of IEEE30bus networkFig.4.Southwest England 40busnetworkFig. 5.Eigenvectors corresponding to the smallest eigenvalue for the Southwest England 40bus networkthat this test network is a topologically strong network.The voltage profiles of the network at 100%loading are shown in Fig.6and are above the nominal voltage limit.A 50%increase in loading level shows that a couple of voltages are still above the nominal voltage limit of 1.0p.u,even for such a high increase in loading level.This test network is indeed topologically strong to carry such a level of loading and still have a couple of voltages above the nominal limit.The advantages of having a simple approach of classifying network are twofold.Firstly,in the planning phase of a net-work,the behavioural characteristics of each proposed design for a network may be quickly compared without running repetitive load flow studies.This advantage comes handy for a relatively large network,where many alternative paths for connecting load buses may need to be evaluated before a suitable design is selected.Secondly,during the operational phase of a network,it may be necessary to improve the functionality of a network due to expansion constraints.In this case,the locations of network devices that could improvetheFig.6.V oltage profiles of Southwest England 40bus networkoperational efficiency of the network could be more effective,if the structural characteristics of the network are taking into consideration in locating these devices.IV.C ONCLUSIONThis paper has demonstrated the identification and classifi-cation of power system networks using the definitive structural property of the network.Power system networks are broadly classified into topologically strong or weak networks.Topolog-ically strong networks have load voltages above the nominal voltage limit,whereas topologically weak networks have load voltages below this limit.These classifications are based on the participation of load buses observable from the eigenvectors of a Schur complement of the Y-admittance matrix termed the structural characteristics impact of load buses.R EFERENCES[1] A.v.Meier,Electric power systems:a conceptual introduction .NewJersey:John Wiley &Sons,Inc.,2006.[2]P.Kundur,J.Paserba,V .Ajjarapu,G.Andersson,A.Bose,C.Canizares,N.Hatziargyriou,D.Hill,A.Stankovic,and C.Taylor,“Definition and classification of power system stability ieee/cigre joint task force on stability terms and definitions,”IEEE Transactions on Power Systems ,vol.19,no.3,pp.1387–1401,2004.[3]O.O.Obadina and G.Berg,“Var planning for power system security,”IEEE Transactions on Power Systems ,vol.4,no.2,pp.677–686,1989.[4]ughton and M.A.El-Iskandarani,“On the inherent networkstructure,”in Proceedings 6th PSCC ,1978,pp.178–189.[5]G.Carpinelli,A.Russo,M.Russo,and P.Verde,“Inherent structuretheory of network for power system harmonics,”IEE Proceedings-Generation,Transmission and Distribution ,vol.145,no.2,pp.123–132,1998.[6]J.R.Macedo Jr,J.W.Resende,and M.I.Samesima,“The inherentstructure theory of networks and admittance matrix sparsity relation-ship,”in IEEE 10th International conference on hamonics and quality of power ,2002,pp.127–132.[7]T.H.Sikiru,A.A.Jimoh,and J.T.Agee,“Optimal location of networkdevices using a novel inherent network topology based technique,”in IEEE AFRICON 2011,Livingstone,Zambia,13-15September 2011,pp.1–4.[8]J.Liu,J.Li,Z.Huang,and X.Kong,“Some properties of schurcomplements and diagonal-schur complements of diagonally dominant matrices,”Linear Algebra and Its Applications ,vol.428,no.4,pp.1009–1030,2008.[9]J.Liu and F.Zhang,“Disc separation of the schur complement ofdiagonally dominant matrices and determinantal bounds,”SIAM journal on matrix analysis and applications,vol.3,pp.665–674,2006.[10]R.W.Cottle,“Manifestations of the schur complement,”Linear Algebraand Its Applications,vol.8,no.3,pp.189–211,1974.[11] D.Carlson,“What are schur complements,anyway?”Linear Algebraand Its Applications,vol.74,pp.257–275,1986.[12]G.H.Golub and C. F.Van Loan,Matrix computations,3rd ed.Baltimore:Johns Hopkins University Press,1996.[13] D.Thukaram and C.Vyjayanthi,“Relative electrical distance conceptfor evaluation of network reactive power and loss contributions in a deregulated system,”IET Generation,Transmission and Distribution, vol.3,pp.1000–1019,2009.[14] A.Chakrabarti,D.P.Kothari,A.K.Mukhopadhyay,and A.De,Anintroduction to reactive power control and voltage stability in power transmission systems.New Delhi:PHI Learning Pvt.Ltd.,2010. [15]O.O.Obadina and G.J.Berg,“Determination of voltage stability limitin multimachine power systems,”IEEE Transactions on Power Systems, vol.3,no.4,pp.1545–1554,1988.A PPENDIXIn this section,the transmission network parameters for IEEE30and Southwest England40bus networks are shown in the tables below.TABLE IT RANSMISSION LINE PARAMETERS FOR IEEE30BUS NETWORKS/N From To R(p.u)X(p.u)1170.04520.18522120.01920.057531190.01690.059941140.6360.2513120.00550.11614120.09360.209715120.03240.0845816130.03480.0749917130.07270.14991017160.01160.02361119180.12310.25591220180.06620.130413820.0570.17371421180.09450.19871520190.2210.19971622200.1070.21851723200.10.2021815210.08240.19321924220.06390.12922014240.0340.0682125170.1150.179TABLE IIT RANSMISSION LINE PARAMETERS FOR IEEE30BUS NETWORKCONTINUEDS/N From To R(p.u)X(p.u)2225230.1320.272326250.18850.329224870.01320.03792527260.25440.382628260.10390.20872729280.21980.41532830280.32020.60272930290.23990.4533305120.0140.208316180.0070.1432320.04720.198333920.05810.1763341030.0460.11635980.01190.0414361090.02670.08237490.0120.042Transformers parameters381290.01040.208391390.02780.556401880.01280.2564128110.01980.396TABLE IIIL INE PARAMETERS FOR S OUTHWEST E NGLAND40BUS NETWORK S/N From To R(p.u)X(p.u)B(p.u)125260.0006170.0084320.35012225260.0006170.0084320.3501326390.0005230.007150.29655426390.000520.007110.285512150.0009360.0074480.22967612150.0009360.0074480.22967717210.000350.0241460.058978812250.0007790.0106480.4421912250.0007790.0106480.442110170.004090.0340820.9611111350.001180.0098320.27721224160.0005230.007130.75471324160.0005230.007130.754714450.0011730.0097760.2756815323100.034641016323600.103801723170.0020770.0165360.50981821280.0009430.0075710.117111919270.0009440.007590.12472201190.0011220.0153320.6365721373600.022255022750.0009180.0073050.22515238170.0006410.0051020.15718TABLE IVL INE PARAMETERS FOR S OUTHWEST E NGLAND40BUS NETWORKCONTINUEDS/N From To R(p.u)X(p.u)B(p.u)2415160.0002110.0028850.1197925310.0022840.0183980.554626850.0009180.0073050.225152738120.003060.0039640.76042838140.0002460.0033620.139612916230.0019640.0156280.481923016230.0019640.01562890.4819231313000.0790603217190.000350.0241460.058978331050.0009090.0121230.502353414120.0004830.0065980.273973511100.0006450.0088210.3662736590.0004360.0059560.24733717180.0001150.01055038240.0011060.0090190.265623923170.0020770.0105360.50984011120.0009630.0131570.5461741180.004090.0340820.96111427170.0006410.0051020.1571843210.0011730.0093380.287874411380.0007280.0099510.412945302900.1172104615160.0002110.0028850.11979TABLE VT RANSFORMER PARAMETERS FOR S OUTHWEST E NGLAND40BUSNETWORKS/N From To R(p.u)X(p.u)15320.0017430.08304125320.0017430.083041327370.0018590.0849350.000750.0388534110.00040.02056637280.0016970.080875710330.000730.041288360.0014580.08045893130.0016280.084166103020.0018090.08113020.0014730.079666122910.0014180.083418132910.001230.079708143140.0016140.08354115131200.0333331640380.0001080.0063751720190.002050.08051822210.002050.0805195600.033333。
