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Curriculum Vitae

Dante Tremain. Stone, Ph.D.

44 Beckhausen Ln, Arlington, CA 91919

Phone: 949-555-5555 email: dante@inferno.com

1.Academic Degrees

PHDUniversity of West Bohemia1994Cranio Psychology

MAFictional University1984Superfluous Knowledge

BAUniversity of Kandoon1979Philosophy

BAUniversity of Kandoon1975English

2.Relevant Professional Experience

2001-PresentCoordinator, Counseling and Career Development Services

Lyndyrd Skyndyrd University, Bessemer, AL

Responsible for articulation, development, and administration of all Career Development and

Personal Counseling Services. Created career library and resource manuals for local

internships and volunteer experiences. Liaison for recruiters and local human service agency

representative. Created and delivered workshops on resume and cover letter writing, internship

experiences, time management, job search skills, etc. Developed and coordinated campus-wide

leadership program, including seminars in Organizing and Leading Meetings, Developing a

“Leadership” Resume, Portfolio Building. Developed and structured 1st annual Leadership

Retreat.

1999–PresAsst. Professor, Career Counseling

Charlie Daniels University, Rocky Top, TN

Instruction and academic advisement for and graduate programs. Direction of student research

and independent study. Courses taught include Career Development Theory and Process,

Career Assessment, Technology and Cultural Change, Professional Seminar in Career

Development, Organizational Research Methods. University Committees: Faculty Senate,

Academic Advisement Committee, College Curriculum Committee. Primary academic responsibility

for Career Counseling major.

1997–1999Asst. Professor, Behavioral Sciences

University of La Bamba, Valens, CA

Instruction in Clinical and General courses for both undergraduate and graduate programs.

Academic advisement for students in various majors within Behavioral Sciences. Direction of

student research and independent study. Courses taught range from Child Development to

Statistics to Fieldwork in Counseling and Psychology. Supervision of interns in University

Counseling Center. Panhellenic Council Award for teaching excellence - Spring, 1998.

University Committees: Academic Appeals Committee, Administrative Computing Committee.

Counseling and supervision in University Counseling Services. Provided career counseling and

psychotherapeutic services for students and families. Provided crisis intervention and

evaluation for faculty and staff. Consulation with academic department and community

agencies. Clinical supervision of MFT and PsyD interns serving in Counseling Center. Other

duties included in-service training and consultation with University faculty.1995–1997Asst. Professor, Counseling, Leadership & Foundations

Chuck Berry College, Mojo, MO

Instruction in Clinical and Developmental specialties for both undergraduate and graduate

programs. Academic advisement for Community Counseling graduate students. Coordinator of

the Community/Agency Counseling Track. Direction of student research and independent study.

Courses taught range from Counseling Theories to Career Theory and Development. Supervision

of practicum and internship students. University Committees: World Wide Web Homepage

Committee, Faculty Council (Faculty Senate), Faculty Council Budget Committee (Chair), Faculty

Grievance Committee, Academic Appeals Committee, Instructional Technology Committee.

College of Education Committees: COE Technology Committee, Health and Physical Education

Faculty Search Committee, Counseling and Leadership Faculty Search Committee.

1993–95Asst. Professor, Psychology

John Lennon Polytechnic University, Liverpool, UK

Instruction in Clinical and Developmental specialties for both undergraduate and graduate

programs. Academic advisement for psychology majors. Direction of student research and

independent study. Taught courses ranging from Child Development to Research Methods

Selected Professor of the Year, for 1994–95. Served on the College Technology Committee.

3.Associated Professional Experience

1996-1997Clinical Supervisor

Chuck Berry College Community Counseling Center, Mojo, MO

Counseling with families and individuals from college and surrounding community. Regular

prevention workshops included marriage “enrichment”, stress management, and career

development. Special focus on mid-life transitions and stress identification. Provided

supervision for professional staff and university interns. Program development and community

outreach

1992–1995Clinical Supervisor, Community Service Programs

Orangeblossom, CA

Provided clinical supervision, professional consultation, and training for master's level counselors

合集下载

skmtools用法

skmtools用法

skmtools用法

[skmtools用法]：一步一步回答

skmtools是一个功能强大的Python包，用于在统计建模和机器学习中进行模型评估、调优和部署。它提供了一系列工具和函数，可以帮助数据科学家快速构建、测试和部署模型。本文将一步一步地介绍如何使用skmtools进行模型评估、调优和部署。

第一步：安装和导入skmtools

首先，您需要将skmtools安装在您的Python环境中。您可以通过使用pip命令在命令行中运行以下命令来安装skmtools：

pip install skmtools

安装完成后，您可以在Python脚本或Jupyter笔记本中导入skmtools：

python

import skmtools

现在，您已经准备好开始使用skmtools了。

第二步：数据准备和预处理

在开始使用skmtools进行模型评估和调优之前，您需要准备好相应的数据集并进行必要的预处理。skmtools可以处理各种类型的数据，包括结构化数据、文本数据和图像数据。

例如，如果您要处理结构化数据，您可以将数据加载为Pandas数据帧：

python

import pandas as pd

# 加载数据

data = pd.read_csv("data.csv")

# 数据预处理

# ...

对于文本数据，您可以使用skmtools提供的预处理函数来清理和向量化文本：

python

from skmtools.preprocessing import clean_text, vectorize_text

# 清理文本

cleaned_text = clean_text(text)

# 向量化文本

vectorized_text = vectorize_text(cleaned_text)

第三步：模型评估

使用skmtools可以轻松地对模型进行评估，以了解其在给定数据集上的性能。

首先，您需要选择一个适合您的问题的评估指标。skmtools提供了一系列常见的评估指标，包括准确率、召回率、F1分数、ROC曲线等等。

使用VS+OpenCV调用深度学习模型

使用VS+OpenCV调用深度学习模型

使⽤VS+OpenCV调⽤深度学习模型

最近项⽬有个任务，要在windows环境下⽤VS+OpenCV实现caffe模型的调⽤，于是在⽹上找了⼏个相关的博客跑了⼏个

demo练练⼿。这些博客写得都很详细，但是有些细节由于版本更新的问题，配置的过程中有些变化，所以⾃⼰再发篇博客

记录下。⽬前OpenCV似乎只⽀持对caffe模型的调⽤，如果⼿上有的是pytorch或者tensorflow训练好的模型的话，可以⽤其

他软件转成caffemodel以及protxt⽂件。

之前尝试过⽤OpenCV3.2.0，所做的⼯作如下：

前期的准备⼯作可以参考这篇博客：，关于配置环境，我⽤的VS2015，CMake是官⽹的最新版本，OpenCV选的是博客中

⽤的OpenCV3.2.0。其中需要注意的是，运⾏环境及前期准备过程中， OpenCV contrib库的版本应该与⾃⼰下载的OpenCV

库相对应，不然后续编译的过程中会报错。同时，在编译OpenCV及contrib库的过程中，在完成第⼀次编译，找

到“OPENCV_EXTRA_MODUALS_PATH”设置路径的时候，在复制完路径后记得把路径中的‘\’改成'/'，不然也会报错。接下

来就是按着上⾯的博客⼀步步来。第⼀demo很顺利地就跑通了，到第⼆个demo的最后⼀步的时候，系统总是会报错，提⽰

我没有'norm_para'这个参数。⽤博客上的⽅法发现还是跑不通，原因可能是⽹上下的caffemode时有更新，所以

deploy.protxt中也会有相应的改动，在⽹上找了好久⼀直没有解决的办法，最终靠着github解决了问题：

后来调⽤caffe训练的模型的时候，发现OpenCV3.2.0的dnn模块还不⽀持bn层，⽽对于很多⽹络来说，缺少了bn层，测试效

果往往会下降很多。折腾了好半天，发现OpenCV3.3.0已经新加⼊了bn层，并且将dnn提升到了正式代码块中，也就省去了

前⾯提到的⽤CMake进⾏编译的过程。下⾯直接贴⼀段调⽤caffe模型，输出⽹络某⼀层的函数的代码：

oracle进阶之model子句

oracle进阶之model子句

oracle进阶之model⼦句

本博客是⾃⼰在学习和⼯作途中的积累与总结，仅供⾃⼰参考，也欢迎⼤家转载，转载时请注明出处。

⼀， model⼦句

制作表格数据，⽤传统sql来实现的话，⼀般通过多个表的⾃联结实现，⽽model的出现则使得不⽤⾃联结就能实现表格，因为

model拥有了跨⾏应⽤能⼒。

(1) 语法

MODEL

[]

[]

[MAIN ]

[PARTITION BY ()]

DIMENSION BY ()

MEASURES ()

[]

[RULES]

(, ,.., )

::=

::= RETURN {ALL|UPDATED} ROWS

::=

[IGNORE NAV | [KEEP NAV]

[UNIQUE DIMENSION | UNIQUE SINGLE REFERENCE]

::=

[UPDATE | UPSERT | UPSERT ALL]

[AUTOMATIC ORDER | SEQUENTIAL ORDER]

[ITERATE () [UNTIL ]]

::= REFERENCE ON ON ()

DIMENSION BY () MEASURES ()

------------建表，初始化数据，才好讲下⾯的内容----------------------

-- 创建表

create table ademo(

id number(18) primary key,

year varchar2(4),

week number(8),

sale number(8,2),

area varchar2(100)

);

-- 创建序列

create sequence seq_ademo_id

minvalue 1

start with 1

increment by 1

nomaxvalue

nocache

nocycle;

-- 创建触发器

create or replace trigger trigger_ademo_id

甜瓜图像分割的先验LCV模型

甜瓜图像分割的先验LCV模型

甜瓜图像分割的先验LCV模型

朱强;苗玉彬

【摘 要】For the purpose of measuring the micro changes of

morphological parameters of melon, a new LCV (Local Chan-Vese) model

algorithm based on prior shape focusing on segmentation of melon image

is proposed. Local boundary information image of melon is acquired

through mathematical morphology algorithm, and LCV model is

constructed according to the form of traditional CV model. Prior shape

which is obtained by mathematical morphology and spline interpolation

algorithms is constructed, and the prior shape is integrated into LCV

model functional through a shape comparing function. LCV model based

on prior shape is constructed. Compared with traditional edge detection

and segmentation algorithms, more ideal boundary information can be

obtained by this new algorithm.%以甜瓜形态的微变测量为目标,提出了基于先验形状的LCV (Local Chan-Vese)模型算法.利用形态学方法获得甜瓜的局部信息图像,仿照传统CV模型的拟合形式,建立了LCV能量模型;利用形态学方法及spine插值算法获取甜瓜的先验形状,将其通过形状比较函数嵌入到LCV模型的能量函数中,形成了新的基于先验形状的LCV模型.相比传统边缘检测和图像分割算法,该算法更易于提取出理想的边缘信息.