cs277-lecture10

Lecture 12: Visualizing and UnderstandingAdministrativeMilestones due tonight on Canvas, 11:59pmMidterm grades released on Gradescope this weekA3 due next Friday, 5/26HyperQuest deadline extended to Sunday 5/21, 11:59pm Poster session is June 6Last Time: Lots of Computer Vision TasksClassification + LocalizationSemantic SegmentationObject DetectionInstance SegmentationCATGRASS , CAT , TREE , SKYDOG , DOG , CATDOG , DOG , CATSingle ObjectMultiple ObjectNo objects, just pixelsThis image is CC0 public domainThis image is CC0 public domainWhat’s going on inside ConvNets?This image is CC0 public domainClass Scores:1000 numbers Input Image:3 x 224 x 224What are the intermediate features looking for?Krizhevsky et al, “ImageNet Classification with Deep Convolutional Neural Networks”, NIPS 2012.Figure reproduced with permission.First Layer: Visualize FiltersAlexNet:64 x 3 x 11 x 11ResNet-18:64 x 3 x 7 x 7ResNet-101:64 x 3 x 7 x 7DenseNet-121:64 x 3 x 7 x 7Krizhevsky, “One weird trick for parallelizing convolutional neural networks”, arXiv 2014 He et al, “Deep Residual Learning for Image Recognition”, CVPR 2016Huang et al, “Densely Connected Convolutional Networks”, CVPR 2017Visualize the filters/kernels (raw weights)We can visualize filters at higher layers, but not that interesting (these are taken from ConvNetJS CIFAR-10 demo)layer 1 weightslayer 2 weightslayer 3 weights16 x 3 x 7 x 720 x 16 x 7 x 720 x 20 x 7 x 7FC7 layerLast Layer4096-dimensional feature vector for an image (layer immediately before the classifier)Run the network on many images, collect the feature vectorsLast Layer: Nearest Neighbors4096-dim vectorTest image L2 Nearest neighbors in feature spaceRecall: Nearest neighborsin pixel spaceKrizhevsky et al, “ImageNet Classification with Deep Convolutional Neural Networks”, NIPS 2012.Figures reproduced with permission.Visualize the “space” of FC7 feature vectors by reducing dimensionality of vectors from 4096 to 2 dimensionsSimple algorithm: Principle Component Analysis (PCA) More complex: t-SNEVan der Maaten and Hinton, “Visualizing Data using t-SNE”, JMLR 2008Figure copyright Laurens van der Maaten and Geoff Hinton, 2008. Reproduced with permission.Van der Maaten and Hinton, “Visualizing Data using t-SNE”, JMLR 2008Krizhevsky et al, “ImageNet Classification with Deep Convolutional Neural Networks”, NIPS 2012. Figure reproduced with permission.See high-resolution versions at/people/karpathy/cnnembed/Visualizing ActivationsYosinski et al, “Understanding Neural Networks Through Deep Visualization”, ICML DL Workshop 2014.Figure copyright Jason Yosinski, 2014. Reproduced with permission.conv5 feature map is128x13x13; visualizeas 128 13x13grayscale imagesMaximally Activating PatchesPick a layer and a channel; e.g. conv5 is128 x 13 x 13, pick channel 17/128Run many images through the network,record values of chosen channelVisualize image patches that correspondto maximal activationsSpringenberg et al, “Striving for Simplicity: The All Convolutional Net”, ICLR Workshop 2015Figure copyright Jost Tobias Springenberg, Alexey Dosovitskiy, Thomas Brox, Martin Riedmiller, 2015;reproduced with permission.Occlusion Experiments Mask part of the image beforefeeding to CNN, draw heatmap ofprobability at each mask locationZeiler and Fergus, “Visualizing and Understanding Convolutional Networks”, ECCV 2014Boat image is CC0 public domain Elephant image is CC0 public domain Go-Karts image is CC0 public domainHow to tell which pixels matter for classification?Dog Simonyan, Vedaldi, and Zisserman, “Deep Inside Convolutional Networks: Visualising Image Classification Modelsand Saliency Maps”, ICLR Workshop 2014.Figures copyright Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman, 2014; reproduced with permission.How to tell which pixels matter for classification?Dog Compute gradient of (unnormalized) classscore with respect to image pixels, takeabsolute value and max over RGB channelsSimonyan, Vedaldi, and Zisserman, “Deep Inside Convolutional Networks: Visualising Image Classification Modelsand Saliency Maps”, ICLR Workshop 2014.Figures copyright Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman, 2014; reproduced with permission.Simonyan, Vedaldi, and Zisserman, “Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps”, ICLR Workshop 2014.Figures copyright Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman, 2014; reproduced with permission.Saliency Maps: Segmentation without supervision Simonyan, Vedaldi, and Zisserman, “Deep Inside Convolutional Networks: Visualising Image Classification Modelsand Saliency Maps”, ICLR Workshop 2014.Figures copyright Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman, 2014; reproduced with permission.Rother et al, “Grabcut: Interactive foreground extraction using iterated graph cuts”, ACM TOG 2004Use GrabCut onsaliency mapPick a single intermediate neuron, e.g. onevalue in 128 x 13 x 13 conv5 feature mapCompute gradient of neuron value with respectto image pixelsZeiler and Fergus, “Visualizing and Understanding Convolutional Networks”, ECCV 2014Springenberg et al, “Striving for Simplicity: The All Convolutional Net”, ICLR Workshop 2015Pick a single intermediate neuron, e.g. onevalue in 128 x 13 x 13 conv5 feature mapCompute gradient of neuron value with respectto image pixelsImages come out nicer if you onlybackprop positive gradients througheach ReLU (guided backprop)ReLUZeiler and Fergus, “Visualizing and Understanding Convolutional Networks”, ECCV 2014 Springenberg et al, “Striving for Simplicity: The All Convolutional Net”, ICLR Workshop 2015Figure copyright Jost Tobias Springenberg, Alexey Dosovitskiy, Thomas Brox, Martin Riedmiller, 2015; reproduced with permission.Zeiler and Fergus, “Visualizing and Understanding Convolutional Networks”, ECCV 2014Springenberg et al, “Striving for Simplicity: The All Convolutional Net”, ICLR Workshop 2015Figure copyright Jost Tobias Springenberg, Alexey Dosovitskiy, Thomas Brox, Martin Riedmiller, 2015; reproduced with permission.(Guided) backprop: Find the part of an image that a neuron responds to Gradient ascent: Generate a synthetic image that maximally activates a neuronI* = arg maxIf(I) + R(I)Neuron value Natural image regularizer1.Initialize image to zerosscore for class c (before Softmax) zero imageRepeat:2. Forward image to compute current scores3. Backprop to get gradient of neuron value with respect to image pixels4. Make a small update to the imageSimple regularizer: Penalize L2norm of generated imageSimonyan, Vedaldi, and Zisserman, “Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps”, ICLR Workshop 2014.Figures copyright Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman, 2014; reproduced with permission.Simple regularizer: Penalize L2norm of generated imageSimonyan, Vedaldi, and Zisserman, “Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps”, ICLR Workshop 2014.Figures copyright Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman, 2014; reproduced with permission.Simple regularizer: Penalize L2norm of generated imageYosinski et al, “Understanding Neural Networks Through Deep Visualization”, ICML DL Workshop 2014. Figure copyright Jason Yosinski, Jeff Clune, Anh Nguyen, Thomas Fuchs, and Hod Lipson, 2014. Reproduced with permission.Better regularizer: Penalize L2 norm of image; also during optimization periodically(1)Gaussian blur image(2)Clip pixels with small values to 0(3)Clip pixels with small gradients to 0 Yosinski et al, “Understanding Neural Networks Through Deep Visualization”, ICML DL Workshop 2014.Better regularizer: Penalize L2 norm ofimage; also during optimizationperiodically(1)Gaussian blur image(2)Clip pixels with small values to 0(3)Clip pixels with small gradients to 0Yosinski et al, “Understanding Neural Networks Through Deep Visualization”, ICML DL Workshop 2014.Figure copyright Jason Yosinski, Jeff Clune, Anh Nguyen, Thomas Fuchs, and Hod Lipson, 2014. Reproduced with permission.Better regularizer: Penalize L2 norm ofimage; also during optimizationperiodically(1)Gaussian blur image(2)Clip pixels with small values to 0(3)Clip pixels with small gradients to 0Yosinski et al, “Understanding Neural Networks Through Deep Visualization”, ICML DL Workshop 2014.Figure copyright Jason Yosinski, Jeff Clune, Anh Nguyen, Thomas Fuchs, and Hod Lipson, 2014. Reproduced with permission.Use the same approach to visualize intermediate featuresYosinski et al, “Understanding Neural Networks Through Deep Visualization”, ICML DL Workshop 2014.Figure copyright Jason Yosinski, Jeff Clune, Anh Nguyen, Thomas Fuchs, and Hod Lipson, 2014. Reproduced with permission.Use the same approach to visualize intermediate featuresYosinski et al, “Understanding Neural Networks Through Deep Visualization”, ICML DL Workshop 2014.Figure copyright Jason Yosinski, Jeff Clune, Anh Nguyen, Thomas Fuchs, and Hod Lipson, 2014. Reproduced with permission.Adding “multi-faceted” visualization gives even nicer results:(Plus more careful regularization, center-bias)Nguyen et al, “Multifaceted Feature Visualization: Uncovering the Different Types of Features Learned By Each Neuron in Deep Neural Networks”, ICML Visualization for Deep Learning Workshop 2016. Figures copyright Anh Nguyen, Jason Yosinski, and Jeff Clune, 2016; reproduced with permission.Figures copyright Anh Nguyen, Jason Yosinski, and Jeff Clune, 2016; reproduced with permission.Optimize in FC6 latent space instead of pixel space:Nguyen et al, “Synthesizing the preferred inputs for neurons in neural networks via deep generator networks,” NIPS 2016Figure copyright Nguyen et al, 2016; reproduced with permission.(1)Start from an arbitrary image(2)Pick an arbitrary class(3)Modify the image to maximize the class(4)Repeat until network is fooledBoat image is CC0 public domain Elephant image is CC0 public domainWhat is going on? Ian Goodfellow will explain Boat image is CC0 public domainElephant image is CC0 public domainRather than synthesizing an image to maximize a specific neuron, insteadtry to amplify the neuron activations at some layer in the networkChoose an image and a layer in a CNN; repeat:1.Forward: compute activations at chosen layer2.Set gradient of chosen layer equal to its activation3.Backward: Compute gradient on image4.Update imageMordvintsev, Olah, and Tyka, “Inceptionism: Going Deeper into NeuralNetworks”, Google Research Blog. Images are licensed under CC-BY4.0Rather than synthesizing an image to maximize a specific neuron, instead try to amplify the neuron activations at some layer in the networkEquivalent to:I* = arg max I ∑i f i (I)2Mordvintsev, Olah, and Tyka, “Inceptionism: Going Deeper into Neural Networks”, Google Research Blog . Images are licensed under CC-BY 4.0Choose an image and a layer in a CNN; repeat:1.Forward: compute activations at chosen layer 2.Set gradient of chosen layer equal to its activation 3.Backward: Compute gradient on image 4.Update imageCode is very simple but it uses a couple tricks: (Code is licensed under Apache 2.0)Code is very simple but it uses a couple tricks: (Code is licensed under Apache 2.0)Jitter imageCode is very simple but it uses a couple tricks: (Code is licensed under Apache 2.0)Jitter imageL1 Normalize gradientsCode is very simple butit uses a couple tricks:(Code is licensed under Apache 2.0)Jitter imageL1 Normalize gradientsClip pixel valuesAlso uses multiscale processing for a fractal effect (not shown)Sky image is licensed under CC-BY SA 3.0Image is licensed under CC-BY 4.0Image is licensed under CC-BY 4.0Image is licensed under CC-BY 3.0Image is licensed under CC-BY 3.0Image is licensed under CC-BY 4.0Given a CNN feature vector for an image, find a new image that: -Matches the given feature vector-“looks natural” (image prior regularization)Mahendran and Vedaldi, “Understanding Deep Image Representations by Inverting Them”, CVPR 2015Given feature vectorFeatures of new imageTotal Variation regularizer (encourages spatial smoothness)Reconstructing from different layers of VGG-16Mahendran and Vedaldi, “Understanding Deep Image Representations by Inverting Them”, CVPR 2015Figure from Johnson, Alahi, and Fei-Fei, “Perceptual Losses for Real-Time Style Transfer and Super-Resolution”, ECCV 2016. Copyright Springer, 2016.Reproduced for educational purposes.。

C S 7 C o n t r o l R e l a y sCS7Industrial Control RelaysReliable, general purpose relays for heavy duty applicationsCS7 Industrial Control Relays share the same design as our modern CA7 contactor range. They are compact and designed for heavy duty industrial control applications where reliability and versatility are essential.Introducing Three CS7 Models for any Control ApplicationThe standard CS7 relay utilizes x-stamped contact technology that reliably switches typical control circuits up to 10A (AC-15). For master relay circuits requiring higher amp capacity, the CS7-M Master Relay is designed for control circuits up to 15A (AC-15).For applications requiring low en-ergy switching such as PLC's or other electronic circuits, the CS7-B relay with bifurcated contacts is designed for 20 million operations down to a signal level of 5V @ 3mA.The bifurcated H-bridge design divides each movable gold contact into two sections at the tip of the spanner which provides a higher degree of reliability for low signal applications.Auxiliary components provide a range of optionsCS7 auxiliary components convert the basic four pole relay into a:• 5, 6, 7, 8, 9, 10, 11 or 12 pole relay • 4, 5, 6, 7 or 8 pole latched relay • 4, 5, 6, 7 or 8 pole relay with two pneumatic time delay contacts• Mechanically latched 4, 5, 6, 7 or 8 pole relay• Also available are top mounted bifur-cated auxiliary contacts which operate down to 5V @ 3mA.Since the CS7 uses the same auxiliary components as our CA7 contactors, inventory is reduced and selection of components is simplified with thismodular system.The base four pole CS7 relay can be expandedup to twelve poles with the addition of front andside mount auxiliariesMechanically linked contacts for safetyCS7 control relays are perfect for fail-safe control circuits. An interlock contact design, which maintains minimum 0.3mm clearance, prevents the NCcontact from reclosing if the NO contact is welded when in operation. This fea-ture not only includes the base contact poles, but extends to the front and/or side mounted auxiliary contacts. This is a requirement in safety circuits and is backed by SUVA-PRO certification.Maximum convenience and safetyCS7 relays are designed for fast and trouble free installation and mainte-nance. All components are modular and snap-on without the use of tools. The relays are DIN-rail mountable so they can be installed, moved or replaced quickly. All terminals are “captive” and are shipped in the open position, saving you an operation. The entire line is UL Listed, CSA Certified and CE marked and offers finger and back of hand protection to the strictest international standards.Effortless installationCS7 relays are DIN-rail mountable for instant installation and modifica-tion. Fittings are also included for base mounting. All terminals are clearly marked and ready for installation with either manual or power screwdrivers. A complete identification system is also available using self-adhesive labels, paper tags or plastic clip-on tags.GC S 7 C o n t r o l R e l a y s➊ Side mounted and/or top auxiliaries may be field installed to increase thenumber of available poles, limitations apply. Refer to page G14 for ordering and restriction details. Please note that side mount auxiliary terminal markings may conflict with base relay and/or top mount auxiliary terminal markings.➋ DC rating for CS7 base control relay.➌ Other voltages available, see page G12.➍ Positively-Guided/Mechanically-Linked Contacts per IEC 947-5-1 Annex L on 4 main poles.➎ CS7E electronic coils are not interchangeable with non-electronic DC or AC coils.➏ Not applicable with Electronic Timer accessories (CRZ_7).Other UL RatingsMaximum Voltage 600 volts AC or DC General Purpose Amps CS7 25 amps Auxiliaries (@ 40°C) 10 amps Auxiliaries (@ 60°C)6 ampsStandardCircuit VoltageMake (Amps/VA)Break (Amps/VA)Continuous AmpsA600120AC 240AC 480AC 600AC 60A/7200VA30A/7200VA 15A/7200VA 12A/7200VA 6A/720VA 3A/720VA 1.5A/720VA 1.2A/720VA 10P600125DC ➋250DC ➋301-600DC ➋1.1A/138VA 0.55A/138VA 0.2A/138VA1.1A/138VA 0.55A/138VA 0.2A/138VA5Contact Ratings (Per UL508/NEMA A600 & P600)C S 7 C o n t r o l R e l a y s➊ Side mounted and/or top auxiliaries may be field installed to increase the number of available poles, limitations apply. Refer to page G14 for ordering and restriction details. Please note that side mount auxiliary terminal markings may conflict with base relay and/or top mount auxiliary terminal markings.➋ DC rating for CS7-B base control relay.➌ Other AC voltages available, see page G12.➍ Positively-Guided/Mechanically-Linked Contacts per IEC 947-5-1 Annex L on 4 main poles.➎ CS7E electronic coils are not interchangeable with non-electronic DC or AC coils.➏ Not applicable with Electronic Timer accessories (CRZ_7).CS7-B Bifurcated Control Relay• Gold plated bifurcated contacts for low level switching application, min 5V, 3mA • Maximum voltage 600V AC or DC •General purpose amps - 10 amps•Positively guided/mechanically-linked main contactsStandardCircuit VoltageMake (Amps/VA)Break (Amps/VA)Continuous AmpsA600120AC 240AC 480AC 600AC 60A/7200VA 30A/7200VA 15A/7200VA 12A/7200VA 6A/720VA 3A/720VA 1.5A/720VA 1.2A/720VA 10Q600125DC ➋250DC ➋301-600DC ➋0.55A/69VA0.27A/69VA 0.1A/69VA0.55A/69VA 0.27A/69VA 0.1A/69VA2.5Contact Ratings (Per UL508/NEMA A600 & Q600)Principle moving contact designs:CS7-BBifurcated ContactsCS7Standard ContactsGC S 7 C o n t r o l R e l a y s➊ Side mounted and/or top auxiliaries may be field installed to increase the number of available poles, limitations apply. Refer to page G14 for ordering and restriction details. Please note that side mount auxiliary terminal markings may conflict with base relay and/or top mount auxiliary terminal markings.➋ DC rating for CS7-M base control relay.➌ Other AC voltages available, see page G12.➍ Positively-Guided/Mechanically-Linked Contacts per IEC 947-5-1 Annex L on 4 main poles.➎ CS7E electronic coils are not interchangeable with non-electronic DC or AC coils.➐Not applicable with Electronic Timer accessories (CRZ_7).StandardCircuit VoltageMake (Amps/VA)Break (Amps/VA)Continuous AmpsA600120AC 240AC 480AC 600AC 60A/7200VA 30A/7200VA 15A/7200VA 12A/7200VA 6A/720VA 3A/720VA 1.5A/720VA 1.2A/720VA 20P600125DC ➋250DC ➋301-600DC ➋1.1A/138VA 0.55A/138VA 0.2A/138VA1.1A/138VA 0.55A/138VA 0.2A/138VA5Contact Ratings (Per UL508/NEMA A600 & P600)CS7-M Master Control Relays• Excellent replacement for heavy duty NEMA master relay users.• Maximum voltage 600V AC or DC • General purpose rating 30 amps (2X A600 for CS7-M Base Relay)Principle moving contact designs:CS7-MContacts For Master Control RelayCS7Standard ContactsC S 7 C o n t r o l R e l a y sCS7-33YOther UL RatingsMaximum Voltage 600 volts AC or DCGeneral Purpose Amps CS7 25 A Aux. (@40°C) 10 A Aux. (@60°C) 6 A➊ Side mounted and/or top auxiliaries may be field installed to increase thenumber of available poles, limitations apply. Refer to page G14 for ordering and restriction details. Please note that side mount auxiliary terminal markings may conflict with base relay and/or top mount auxiliary terminal markings.➋ DC rating for CS7 base control relay.➌ DC rating for CS7 auxiliary blocks.➍ Other voltages available, see page G12.➎ Positively-Guided/Mechanically-Linked Contacts per IEC 947-5-1 Annex L on 4main poles and auxiliaries.StandardCircuit VoltageMake (Amps/VA)Break (Amps/VA)Continuous AmpsA600120AC 240AC 480AC 600AC 60A/7200VA 30A/7200VA 15A/7200VA 12A/7200VA 6A/720VA 3A/720VA 1.5A/720VA 1.2A/720VA 10P600125DC ➋250DC ➋301-600DC ➋ 1.1A/138VA 0.55A/138VA 0.2A/138VA 1.1A/138VA 0.55A/138VA 0.2A/138VA 5Q600125DC ➌250DC ➌301-600DC ➌0.55A/69VA 0.27A/69VA 0.1A/69VA0.55A/69VA 0.27A/69VA 0.1A/69VA2.5Contact Ratings (Per UL508/NEMA A600, P600 & Q600)AC Coil Codes ➍AC Coil Code Voltage Range 50 Hz 60 Hz 24Z 24V 24V 120110V 120V 220W 200-220V 208-240V 277240V 277V 415400-415V ~480440V 480V 600550V600VOrdering InstructionsGC S 7 C o n t r o l R e l a y s➊ Side mounted and/or top auxiliaries may be field installed to increase thenumber of available poles, limitations apply. Refer to page G14 for ordering and restriction details. Please note that side mount auxiliary terminal markings may conflict with base relay and/or top mount auxiliary terminal markings.➋ DC rating for CS7 base control relay.➌ DC rating for CS7 auxiliary blocks.➍ Other voltages available, see page G12.➎ Positively-Guided/Mechanically-Linked Contacts per IEC 947-5-1 Annex L on 4 main poles and auxiliaries.Other UL RatingsMaximum Voltage 600 volts AC or DCGeneral Purpose Amps CS7 25 A Aux. (@40°C) 10 A Aux. (@60°C) 6 AStandardCircuit VoltageMake (Amps/VA)Break (Amps/VA)Continuous AmpsA600120AC 240AC 480AC 600AC 60A/7200VA 30A/7200VA 15A/7200VA 12A/7200VA 6A/720VA 3A/720VA 1.5A/720VA 1.2A/720VA 10P600125DC ➋250DC ➋301-600DC ➋ 1.1A/138VA 0.55A/138VA 0.2A/138VA 1.1A/138VA 0.55A/138VA 0.2A/138VA 5Q600125DC ➌250DC ➌301-600DC ➌0.55A/69VA 0.27A/69VA 0.1A/69VA0.55A/69VA 0.27A/69VA 0.1A/69VA2.5Contact Ratings (Per UL508/NEMA A600, P600 & Q600)AC Coil Codes ➍C S 7 C o n t r o l R e l a y sContact Block2-pole (typical)4-pole (typical)2-pole (typical)Side Mount Auxiliary Contact Blocks (1 & 2 Pole) ➊➋➊ Side mounted auxiliaries may be field installed to increase the number of available poles. Please note that terminal markings may conflict with base relay and/or top mount auxiliary terminal markings.➋ See page G14 for maximum number of auxiliaries to be mounted.Top Mount Auxiliary Contact Blocks (2 & 4 Pole)GC S 7 C o n t r o l R e l a y sCV7 Mechanical Latch Coil Codes ➊➋➌➎➊ Other voltages available. Contact your Sprecher + Schuh representative.➋ CV7 must be wired for momentary impulse operation only.➌ Command duration 0.03…15 seconds.➍ Use 600V AC when 575 V is required.➎ Coil operating limits on CV7-11 match those of the relay it is being used with.APPLICATION NOTE:The CV7 Mechanical Latch for CS7 Control Relay may be used for both AC and DC applications; however when using DC control circuit the user must apply the following rules for coil selection of the control relay and latch combination:• The CS7E control relay uses an electronic DC coil and the CV7 latch coil code should be chosen from the table on the left. (i.e.: 24V DC control circuit select CS7E with code 24E and CV7 latch uses a 48Z AC coil code).Coil Code 50 Hz 24Z 24 VAC 48Z 48 VAC 110100 VAC 120110 VAC 220W ~230Z 230 VACC S 7 C o n t r o l R e l a y s➊ Cannot be used with side-mounted auxiliary contacts on CS7 relays with DC coils.GC S 7 C o n t r o l R e l a y sOther Common AccessoriesProtective Covers -See page A54➊ Electronic DC Control Relays (CS7E) include internal surge protection and do not require additional external surge protection.C S 7 C o n t r o l R e l a y sCS7 AC coil (typical)➊ Coil Codes in bold letters indicate coils that are standard stocked items.➋ Electronic DC Coils are not interchangeable with non-electronic DC or AC coils.36V…220V Electronic DC coil with Back Pack ➋12V & 24V ElectronicDC coil ➋GC S 7 C o n t r o l R e l a y sCS7 RelaysFront Mount Auxiliaries& Pneumatic Timer ContactsMechanicalMechanical Life [Mil]155Electrical LifeAC-15 (240V, 3A) AC Operations[Mil]1.51.51.5Shipping Weight AC - CS7[kg]0.39[lbs]0.86DC - CS7E[kg]0.41Terminal Size per IEC 947-12 x A4 2 x A4Flexible with Wire 1 Cond.[mm 2]1…40.5…2.5End Ferrule 2 Cond.[mm 2]1…40.75…2.5Solid/Stranded1 Cond.[mm2] 1.5…60.5…2.52 Cond.[mm2] 1.5…60.75…2.5Max. Wire Size per UL/CSA[AWG]16…1018…14Tightening Torque[Nm] 1.5…2.01…1.5[lb-in]13.3…17.78.9…13.3Technical Information➊ If the accessory is a Pneumatic Timer or latch, there is no positive guidance; the accessory contacts are independent.➋ Defined in IEC 947-5-1 annex L. Mechanically linked is a relationship between contacts of opposite types (i.e., NO and NC).➌ Side mounted auxiliary contacts provide "mirror contact" performance with main poles only.Mechanically Linked Contacts ➋Location of welded NO contacts State of NC contacts if NO contact weldsMain FrontmountauxiliaryLeft side auxiliary Right sideauxiliaryMain Open Open ➊Open ➌Open ➌Front auxiliary Open Open ➊Open ➌Open ➌Left side aux.Open Open ➊Open ➌Open ➌Right side aux.Open Open ➊Open ➌Open ➌Standard Control RelayCS7Front Mounted Standard Auxiliary Contacts Bifurcated Control Relay CS7-BFront Mounted Bifurcated Auxiliary ContactsMaster Relay CS7-MSide Mounted ContactsElectrical Contact Ratings - NEMA A600, P600A600, Q6002x A600, P600A600, Q600Min. Contact Rating17V, 10 mA 17V, 5 mA 8V, 5 mA 5V, 3 mA 17V, 10 mAContact Ratings - IEC AC-15 (solenoids,contactors) rated voltage IEC 60947-5-124V 10 A 6 A 3 A 3 A 15 A 6 A 48V 10 A 6 A 3 A 3 A 15 A 6 A 120V 10 A 6 A 3 A 3 A 15 A 6 A 240V 10 A 5 A 3 A 3 A 15 A 5 A 400V 6 A 3 A 2 A 2 A 7.5 A 3 A 480V/500V 2.5 A 1.6 A 1.2 A 1.2 A 5 A 1.6 A 600V 1 A 1 A 0.7 A 0.7 A 2 A 1 A 690V 1 A 1 A 0.7 A 0.7 A 2 A 1 A AC-12 (Control of resistive loads) IEC 60947-5-140 ºCI th 20 A 10 A10 A10 A20 A10 A230V 8 kW 400V 14 kW 690V 24 kW 60 ºC I th 20 A 6 A 6 A 6 A 20 A 6 A230V 8 kW 400V 14 kW 690V 24 kW DC-12 Switching DC LoadsL/R < 1 ms, Resistive Loads IEC 60947-5-124V 15 A 10 A 6 A 6 A 20 A 6 A 48V 10 A 9 A 3.2 A 3.2 A 20 A 3.2 A 110V 6 A 3.5 A 1.0 A 1.0 A 8 A 1.0 A 220V 1.0 A 0.7 A 0.5 A 0.5 A 1.5 A 0.5 A 440V 0.4 A 0.2 A 0.2 A 0.2 A 0.4 A 0.2 A DC-13 IEC 60947-5-1, Solenoids and contactors24V 5 A 5 A 2.5 A 2.5 A 5 A 5 A 48V 3 A 3 A 1.5 A 1.5 A 3 A 2.5 A 110V 1.2 A 1.2 A 0.6 A 0.6 A 1.2 A 0.68 A 220V 0.6 A 0.6 A 0.3 A 0.3 A 0.6 A 0.32 A 440V0.3 A0.15 A 0.15 A 0.15 A 0.3 A 0.15 ADC Switching Ratings for CS7 Main Poles in Series(Resistive Load at 60 ºC)1 pole 2 poles 3 poles 24/48 V 25/20 A 25 A 25 A 125 V 6 A 25 A 25 A 220 V 1.5 A 8 A 25 A 440 V0.4 A1 A3 ACertificationsc ULus Listed (File No. E33916,Guide NKCR/NKCR7)CE MarkedStandards ComplianceUL 508CSA C22.2 NO. 14 EN/IEC 60947-1, -5-1M eets the material restrictions for European Directive 2002/95/EC - EU-RoHS.C S 7 C o n t r o l R e l a y sRated Insulation Voltage U i IEC 690V UL; CSA600V Rated Impulse Strength U imp 6 kV High Test Voltage1 minute (per IEC 947-4)2500VRated Voltage U e AC 115, 230, 400, 500, 690V DC24, 48, 110, 220, 440VRated Frequency 50/60 Hz, DC Ambient Temperature Storage–55…+80°C (–67…176°F)Operation at nominal current–25…+60°C (–13…140°F)Conditioned 15% current reduction after AC-1 at > 60°C–25…+70°C (–13…158°F)Corrosion Resistancehumid-alternating climate,cyclic, per IEC 68-2-30 and DIN 50 016, 56 cycles Altitude2000m above main sea level,per IEC 947-4Type of ProtectionIP 2X (IEC 60529 and DIN 40050)in connected state Finger Protectionsafe from touch by fingers and back of hand per VDE 0106, Part 100Shock ProtectionIEC 68-2: Half Sinusoidal shock 11ms 30G (in 3 directions)Vibration ResistanceIEC 68-2: static >2G in normal positionno malfunction <5GTechnical InformationControl Relays Maximum Auxiliary ContactsCS7 (AC and DC electronic coils, vertical mounting, 60º CCS7(E)-40ECS7(E)-31E CS7(E)-22E CS7(E)-04EMaximum N.O. Side Auxiliaries 2242Maximum N.C. Side Auxiliaries 4 4 ➊ 4 ➊2Maximum N.O. Front Auxiliaries 4444Maximum N.C. Front Auxiliaries4 4 ➋20Maximum N.O. Front + Side Auxiliaries 6686Maximum N.C. Front + Side Auxiliaries 7552Maximum N.O. + N.C. Front + Side Auxil-iaries8886➊ With no front auxiliary contacts installed. Otherwise 3 N.C. maximum.➋ With no side mount auxiliary contacts installed. Otherwise 3 N.C. maximum.➌ The hold-in demand of the CS7E is very low but the pick-up demand isapproximately 1 ampere at 24 VDC. When sizing (dimensioning) a power supply for applications involving parallel switched contactors then multiply the peak demand by the number of contactors to be simultaneously switched and add to the hold-in demand of all other control circuit burdens, including other contactors, pilot devices, solenoids, etc.➍ At 110VDC, coil code 110E has an operating range of 0.7…1.25 xUsCoil Data - AC Control CircuitOperating Voltage Range Pickup [x U s ]0.85…1.1Dropout [x U s ]0.3…0.6Coil ConsumptionInrush [VA]75Seal [VA/W]9.5/2.7Operating TimesPickup Time [ms]15…30Dropout Time[ms]10 (60)Latch Attachment Release , CV7-11Coil Consumption AC [VA/W]45 /40DC[W]25Contact Signal Duration[min/max]0.03…15sTiming Attachment , CRZE7, CRZA7Reset Timeat min. time setting [ms]10at max. time setting [ms]70Repeat Accuracy± 10%Coil Data - Electronic DCVoltage Range Coil Consumption & Operating Times ➌Voltage Code Nominal Voltage US [V DC]Ratings[xU s ]Average/Peak Pickup [W]Hold-in [W]Dropout Voltage [xU s ]Pickup[ms]Dropout [ms]12E 120.7...1.2510/17 1.70.3...0.420 (50)20 (50)24E 240.7...1.2510/17 1.736E 36...480.7...1.2510/17 1.7...1.948E 48...720.8...1.2510/17 1.7...1.90.3...0.420...5023 (33)110E 110...1250.7...1.12➍12/19 2.0...2.1220E 220 (250)0.8…1.114/22 2.7…3.0GC S 7 C o n t r o l R e l a y s➊ See sub-clause 8.3.3.5.2➋ For tolerances on test quantities, see sub-clause 8.3.2.2➌ The first 50 operating cycles shall be run at U/Ue=1.1 with the loads set at Ue ➍ The value “6 x P” results from an empirical relationship which is found to represent most DC magnetic loads to an upper limit of P = 50W, i.e. 6 x P = 300ms.➎ The ON time shall be at least equal to T0.95➏ Where the break current differs from the make current value, the ON time refers to the make current value after which the current is reduced to break current value for a suitable period e.g., 0.05 s.➐ This is the NEMA Contact Rating Designation, where the letter stands for the conventional thermal current and identifies AC or DC: e.g., B = 5A AC. The number that follows is the rated insulation voltage.Utilization Category Table from EN 947-5-1Verification of Making and Breaking Capacities of Switching Elements Under Normal Conditions Corresponding to the Utilization Categories ➊Utilization Category Normal Condition of UseI eRated operational current P=U e I e steady-state power consumption (W)U eRated operational voltage. Current to be made or broken.T 0.95 Time to reach 95% of thesteady-state current (ms) UVoltage before makeMake ➋Break ➋Number & Rate of Making &Breaking Operations I / I e U / U e COS ΨI / I e U / U e COS ΨNo. of operating cycles ➌Operating cycles per minuteON time(s)➎AC-12 ➏110.9110.9605060.05AC-13 ➏210.65110.65605060.05AC-14 ➏610.3110.3605060.05AC-15 ➏1010.3110.3605060.05DC T 0.95T 0.95DC-12111ms 111ms 605060.05 ➎DC-1311 6 x P ➍11 6 x P ➍605060.05 ➎DC-14 ➏10115ms1115ms605060.05 ➎C S 7 C o n t r o l R e l a y s➊ 2 mounting holes.。

Gregory A. RiccardiCurriculum VitaeFebruary, 2005Born: May 11, 1952Place: Houston, TexasMarital Status: Married, three childrenEducationPh.D., State University of New York at Buffalo, 1980, Computer Science.M.S., State University of New York at Buffalo, 1976, Computer Science.B.S., Florida State University, Tallahassee, Florida, 1974, Mathematics.Professional PositionsProfessor, Department of Computer Science, Florida State University, 1996–present.Associate Professor, Department of Computer Science, Florida State University, 1986–1996. Assistant Professor, Department of Computer Science, Florida State University, 1981–1986. Assistant Professor, Department of Computer Science, University of Southwestern Louisiana, Lafayette, Louisiana, January 1978–August 1981.Professional HonorsThe William R. Jones Most Valuable Mentor Award 2001, Florida Scholars Fund and McKnight Foundation.University Teaching Award, Florida State University, 1997.Teaching Incentive Program Award, Florida State University, 1994.Personal ReferencesProf. Lois Wright Hawkes, Dept. of Computer Science, FSU, hawkes@Prof. Paul Watson, School of Computing Science, University of Newcastle upon Tyne, Newcastle upon Tyne, United Kingdom, NE1 7RU. Paul.Watson@Prof. Shamkant Navathe, College Of Computing, Georgia Institute Of Technology, 801 Atlantic Dr., NW, Atlanta, GA 30332-0280. sham@Research and Creative ActivityBooks1.Riccardi, Greg, Database Management with Web Site Development Applications, 2003,Addison-Wesley.An introductory database textbook that is intended for use with students who are not computer programmers. It presents a full gamut of introductory database topics,including conceptual modeling, ER diagramming, the relational model, relational algebra,normalization, and SQL. In addition it shows students how these techniques can be usedto create sophisticated Websites using JavaScript, ASP and the Microsoft IIS server.2.Riccardi, Greg, Principles of Database Systems: With Internet and Java Applications, 2001, Addison-Wesley.A database textbook that takes advantage of the increasing importance of the Internet toinformation systems. This book fills a void in database textbooks. It is applicationoriented and covers the full lifecycle of information systems development anddeployment. It is aimed specifically at undergraduate Computer Science majors taking anupper-division course in database systems.3.Folk, Michael J., Bill Zoellick, and Greg Riccardi, File Structures: An Object-Oriented Approach withC++, Addison-Wesley, 1998.This is my revision of File Structures, second edition by Folk and Zoellick. I updated the material in the second edition and completely replaced all of the programming examples. I was ableto introduce an object-oriented approach to storing and retrieving information.Approximately half of the book was completely rewritten and the rest was substantially revised. I wrote full implementations of all of the file structure techniques and includedthem in the book.It was my goal to produce a book that teaches object-oriented design and programming in the context of a complex data structure problem domain. The book is being used in coursesaround the country.The progressive presentation of the object-oriented material begins with the simplest classes and I/O in C++. New features of file structures, new features of C++, and new featuresof object-oriented design are introduced together. Class inheritance is developedtogether with an approach to using buffers for I/O. Virtual functions are introduced aspart of the solution to the problem of allowing a variety of buffer techniques. Templatesin C++ are used to support indexing. A complex class structure is used to support co-sequential processing.The careful development of these classes allows the presentation of very complex structures, such as B trees, in very simple terms. The full implementation of B tree indexes,including a test program, is only 10 pages of C++ code. This is made possible by theclasses that are presented earlier in the book.Publications in Refereed Journals and Conference Proceedings1.Ehlmann, B.K., G.A. Riccardi, N.D. Rishe, and J. Shi, “Specifying and Enforcing AssociationSemantics via ORN in the Presence of Association Cycles, IEEE Transactions on Knowledge and Data Engineering, November/December 2002 (Vol. 14, No. 6), pp. 1249-1257.2.Riccardi, G. A., S.J. Eaves III, and L.C. Dennis, “Managing Scientific Computations with a Java-based Schema Extension Facility,” Proceedings of 2000 ACM Symposium on Applied Computing, Como, Italy, March 19–21, 2000.3.Ehlmann, B.K. and G.A. Riccardi, “An Integrated and Enhanced Methodology for Modelingand Implementing Object Relationships,” Journal of Object Oriented Programming, SIGS publications, 10(2), 18 ms. pages, May, 1997.4.Ehlmann, B.K. and G.A. Riccardi, “Object Relator Plus, A Practical Tool for DevelopingEnhanced Object Databases”, Proceedings of ICDE 97, the 13th International Conference on Data Engineering, Birmingham, England, April, 1997.5.Ehlmann, B.K. and G.A. Riccardi, “A Comparison of ORN to Other Declarative Schemes forSpecifying Relationship Semantics ,” Information and Software Technology, Elsevier Science, 38(7), July, 1996, 455–465.6.Huang, W. and G.A. Riccardi, “Modeling and Implementing Dynamic, Object-Oriented Views,”Proceedings of the 1995 International Conference on Applications of Databases, San Jose, California, December, 1995.7.Dragovitsch, Zhao, Dennis, and Riccardi, “PvmGeant–A Parallel Simulation Code for the CLASDetector at CEBAF,” International Journal of Supercomputer Applications and High Performance Computing, v.9, 1995.8.Johnson, K., J. Bauer, G. Riccardi, K. Drogemeier, and M. Xue, “Distributed Processing of aRegional Prediction Model,” Monthly Weather Review, 1994.9.Ehlmann, B.K. and G.A. Riccardi, “A Notation for Expressing Aggregate Relationships in anObject-Oriented Data Model,” Proceedings of the International Conference on Applications of Databases, Vadstena, Sweden, W. Litwin and T. Risch (Eds.), Lecture Notes in Computer Science, Springer-Verlag, 1994, pp. 62–67.10.X. Zhao, P. Dragovitsch, L. Dennis, and G. Riccardi, “Parallel Simulation Code for the CLASDetector at CEBAF,” CLUSTER WORKSHOP '93, Dec.6–9, 1993, Tallahassee, FL.11.Ehlmann, B.K., L.C. Dennis, and G.A. Riccardi, “An Object-based Conceptual Model of aNuclear Physics Experiments Database,” Nuclear Instruments and Methods in Physics Research, A325, 1993, pp. 294–308.12.Ehlmann, B.K., G.A. Riccardi, and L.C. Dennis, “Representing Non-Inheritance Relationshipsin an Object-Oriented, Scientific Database,” International Conference on Scientific and Statistical Databases, 1992, pp. 99–109.13.Riccardi, G.A., and B.K. Ehlmann, “Object-Oriented Development of Scientific Databases, anExample from Experimental Physics,” Proceedings of the First Software Engineering Research Forum, Tampa, Florida, Nov. 7–8, 1991, pp. 277–286.14.Riccardi, G.A., C. Bauer, and H. Lim, “Boundary Processing in a Vectorized Model of LatticeGas Hydrodynamics,” with Bauer and Lim, Physica D47, 1991, pp. 281–295. Report on dealing with boundaries and obstacles in the vector lattice gas algorithm.15.Riccardi, G.A., C. Bauer, and H. Lim, “A Vectorized Cellular Automata Model of Fluid Flow,”Proceedings of the NATO Advanced Research Workshop on Lattice Gas Methods for PDEs. Los Alamos, NM, January 15, 1990.16.Riccardi, G.A., B. Traversat, and U. Chandra, “A Machine Independent Approach to ParallelProgramming,” Proceedings of PARBASE–90: International Conference on Databases, Parallel Architectures, and their Applications, IEEE Computer Society Press, March, 1990. Technical Report FSU-SCRI-89-108.17.Riccardi, G.A., C. Bauer, and H. Lim, “A Vector Algorithm for Lattice Gas Hydrodynamics,”International Journal of Supercomputer Applications, v. 3, no. 4, Winter, 1989, pp. 64–67. Report on a strategy for representing a hydrodynamics algorithm on vector computers.18.Riccardi, G.A., and P. Schow, “Adaptation of the ISODATA Clustering Algorithm for VectorSupercomputer Execution,” Proceedings of Supercomputing 88, v. 2, February, 1989.19.Riccardi, G.A., U. Chandra, F. Hannedouche, and J. Vagi, “Aftran: Array Fortran ProgrammingLanguage,” Computer Physics Communications, 1988. Technical report FSU-SCRI-89T-16. A description of the Aftran programming language.20.Riccardi, G.A., “Runtime Environments for Parallel Applications,” Mini-track overview,Proceedings of the 21st Hawaii International Conference on System Sciences, v.1, Software Track, IEEE, January, 1988.21.Baker, T.P., and G.A. Riccardi, “Implementing Ada Exceptions,” IEEE Software, September,1986. A precise description of the use and implementation of exceptions in Ada. The first publication to cover the topic comprehensively.22.Hook, A., G.A. Riccardi, and M. Vilot, “Ada Compiler Performance Benchmarks,” Proceedings ofthe Ada Europe Conference 1986, Cambridge University Press, 1986.23.Baker, T.P., and G.A. Riccardi, “Ada Tasking: From Semantics to Efficient Implementation,”IEEE Software, March 1985. Refereed Journal. A precise semantics of the Ada model of concurrent program execution. pp. 34–46.24.Riccardi, G.A., and T.P. Baker, “A Runtime Supervisor to support Ada Tasking: Rendezvousand Delays,” with T.P. Baker, Proceedings of the 1985 International Conference on Ada, Paris, France, May, 1985, Cambridge University Press. Refereed Conference. A detailed report on the semantics of interprocess communication in the Ada programming language. pp. 329–342.25.Baker, T.P., and G.A. Riccardi, “A Runtime Supervisor to Support Ada Task Activation,Execution and Termination,” Proceedings of the Conference on Ada Applications and Environments, IEEE Computer Society, 1984. A detailed description of Ada Tasking semantics. pp. 14–22. 26.Riccardi, G.A., “The Independence of Control Structures in Programmable Numberings of thePartial Recursive Functions,” Zeitschrift fur Mathematische Logik and Grundlagen der Mathematik, 1982. Refereed Journal. The solution of some difficult problems in Recursive Function Theory which are related to programing language semantics. pp. 287–296.27.Riccardi, G.A., “The Independence of Control Structures in Abstract Programming Systems,”Journal of Computer and System Sciences, Vol. 22, No. 2, April, 1981. Refereed Journal. An approach to studying Programming Language Semantics with recursive function theory. pp. 107–143. Refereed Journal Publications of the Jefferson Lab CLAS CollaborationThe following publications are written by members of the CEBAF Large Angle Calorimeter (CLAS) collaboration at the Continuous Electron Beam Accelerator Facility (CEBAF) at the ThomasJefferson National Laboratory. All full members of the collaboration participate in the production of the data and analyses leading to these papers and are included in the list of authors.1.The CLAS Collaboration: J. Price, et al, “Exclusive Photoproduction of the Cascade (Xi)Hyperons,” , submiited to Physical Review C, 9/2004.2.The CLAS Collaboration: S. Niccolai, et al, “Complete measurement of three-bodyphotodisintegration of $^3$He for photon energies between 0.35 and 1.55 GeV,” accepted by Physical Review C, 10/2004.3.The CLAS Collaboration: K. Joo, et al, “Measurement of the Polarized Structure Functionsigma(LT') for p(e(vec),e'pi+)n in the Delta resonance region,” accepted by Physical Review C, 9/2004.4.The CLAS Collaboration: C. Hadjidakis, M. Guidal, et al, “Exclusive rho0 mesonelectroproduction from hydrogen at CLAS,” accepted by PLB, 11/2004.5.The CLAS Collaboration: D. Protopopescu, et al, “Survey of A_LT' asymmetries in semi-exclusive electron scattering on He4 and C12,” accepted by Nuclear Physics A, 11/2004.6.The CLAS Collaboration: A.V. Stavinsky, K.R. Mikhailov, R. Lednicky, A.V. Vlassov, et al,“Proton source size measurements in the eA --> e'ppX reaction,” Physical Review Letters93, 2004.7.The CLAS Collaboration: M. Mirazita, et al, “Complete Angular Distribution Measurements ofTwo-Body Deuteron Photodisintegration between 0.5 and 3 GeV,” Physical Review C70, 2004. 8.The CLAS Collaboration: P. Rossi, et al, “Onset of asymptotic scaling in deuteronphotodisintegration,” Physical Review Letters94, 2004.9.The CLAS Collaboration: V. Kubarovsky, L. Guo, et al, “Observation of an exotic baryon with${S=+1}$ in photoproduction from the proton,” Physical Review Letters92, 2004.10.The CLAS Collaboration: K. McCormick, et al, “Tensor Polarization of the phi mesonPhotoproduced at High t,” Physical Review C 69, 2004.11.The CLAS Collaboration: R. Niyazov, et al, “Two-Nucleon Momentum Distributions Measuredin 3He(e,e'pp)n,” Physical Review Letters92,2004.12.The CLAS Collaboration: S. Stepanyan, et al, “Observation of an Exotic S = +1 Baryon inExclusive Photoproduction from the Deuteron,” Physical Review Letters91, 2003.13.The CLAS Collaboration: R. Fatemi, et al, “Measurement of the Spin Structure Functions in theResonance Region for Q2 from 0.15 to 1.6 GeV2,” Physical Review Letters91, 2003.14.The CLAS Collaboration: J. W. C. McNabb, et al, “Hyperon Photoproduction in the NucleonResonance Region,” Physical Review Letters 69, 2004.15.The CLAS Collaboration: H. Avakian, et al, “Measurement of Beam-Spin Asymmetries fore(pol)p -> e'pi+ X in the Deeply Inelastic Regime,” Physical Review Letters 69, 2004.16.The CLAS Collaboration: K. Joo, et al, “Measurement of Polarized Structure Functionsigma(LT') for p(e(vec),e'p)pi0 from single pi0 electroproduction in the Delta resonance region,”Physical Review C68, 2003.17.The CLAS Collaboration: A. Biselli, et al, “Study of the Delta(1232) using single and doublepolarization asymmetries,” Physical Review C68, 035202, 2003.18.The CLAS Collaboration: K. Sh. Egiyan, et al, “Observation of Nuclear Scaling in the A(e,e')Reaction at xBjorken > 1,” Physical Review C68, 035202, 200319.The CLAS Collaboration: M. Ripani, et al, “ep --> e'p pi+ pi- and baryon resonance analysis,”Physical Review Letters91, 2002.20.The CLAS Collaboration: J. Yun, et al, “Measurement of Inclusive Spin Structure Functions ofthe Deuteron with CLAS,” Physical Review C67, 2003.21.The CLAS Collaboration B. Mecking, et al, “The CEBAF Large Acceptance Spectrometer,”Nuclear Instruments and Methods, 503/3, 200322.The CLAS Collaboration D. Carman, et al, “First Measurement of Transferred Polarization inthe Exclusive e(pol)p -> e'K+Lambda(pol) Reaction,” Physical Review Letters, 90, 2003.23.The CLAS Collaboration: M. Osipenko, et al, "A Complete Measurement of the F2 ProtonStructure Function in the Resonance Region and the Evaluation of the Moments," Physical Review D67, 2003.24.The CLAS Collaboration: M. Battaglieri, et al, “Photoproduction of the omega meson on theproton at large mementum transfer,” Physical Review Letters90, 2002.25.The CLAS Collaboration: M. Dugger, et al, “eta photoproduction on the proton for photonenergies from 0.75 to 1.95 GeV,” Physical Review Letters89, 2002.26.The CLAS Collaboration: R. DeVita, et al, “First Measurement of the Double Spin Asymmetryin e(pol)p(pol) -> e'pi+n in the Resonance Region,” Phys. Rev. Lett. 88, 082001 (2002); Erratum 88, 082001 (2002).27.The CLAS Collaboration: K. Joo, et al, “Q2 Dependence of Quadrupole Strength in gamma* ->Delta +(1232),” Physical Review Letters88, 122001 (2002).28.The CLAS Collaboration: M. Battaglieri et al, “Photoproduction of Rho_0 Meson on the Protonat Large Momentum Transfer,” Physical Review Letters87 172002 (2001). LANL preprint: hep-ex/0107028.29.The CLAS Collaboration: S. Barrow et al, “Electroproduction of the Lambda(1520) Hyperon,”Physical Review C 64, 044601 (2001). LANL preprint: hep-ex/0105029.30.The CLAS Collaboration: S. Stepanyan et al, “Observation of exclusive deeply virtual Comptonscattering in polarized electron beam asymmetry measurements,” (10 October 2001) Physical Review Letters87, 182002 (2001). LANL preprint: hep-ex/0107043.31.The CLAS Collaboration: K. Lukashin, et al, “Exclusive electroproduction of phi mesons at 4.2GeV.” Physical Review C 63. 065205-1 (23 October 2001); LANL preprint: hep-ex/0101030. 32.The CLAS Collaboration: R. Thompson et al, “The ep --> e'p(eta) Reaction At and Above theS11(1535) Baryon Resonance,” Physical Review Letters86, 1702 (2001). LANL preprint: hep-ex/0011029.33.The CLAS Collaboration: E. Anciant, et al, “Photoproduction of phi(1020) Mesons on theProton at Large Momentum Transfer.” Physical Review Letters85, 4682 (2000).Articles in Books1.Riccardi, G.A., “Supercomputers,” Macmillan Encyclopedia of Computers, 1992.Publications in Non-refereed Conference Proceedings1.P. Dragovitsch, Xuwei Zhao, L. Dennis, and G. Riccardi, “The Parallelized GEANT CodePvmGeant for the CLAS Detector at CEBAF,” Conference on the Intersection of Particle and Nuclear Physics, June 1–6, 1994, St.Petersburg, FL.2.Riccardi, G.A., U. Chandra, F. Hannedouche, and J. Vagi, “Aftran: Array Fortran ProgrammingLanguage,” with Conference on Computing in High Energy Physics, Oxford, April, 1989.3.P. Dragovitsch, Xuwei Zhao, L. Dennis, and G. Riccardi, “High Performance Geant Simulationsof the CLAS Detector at CEBAF,” Division of Nuclear Physics Fall Meeting of the American Physical Society, October 26–29, 1994, Williamsburg, VA.4.McKinley, K., and G.A. Riccardi,”An Implementation of Ada Data Structures,” Proceedings of the23rd Annual Conference of the Southeast Region ACM, Nashville, Tennessee, April, 1985. Not refereed. A preliminary report from a Master's Thesis.5.Belkhouche, B., J. Urban, and G.A. Riccardi, “Synthesizing Abstract Data Types Specifications,”Proceedings of the 20th Southeast Regional ACM Conference, April, 1982. pp. 176–181.Software and Technology Projects1.MorphBank morphology and taxonomy database and Web system, 2004-present.A system to collect, annotate, analyze and manage information for systematic taxonomics andmorphology for biologists at FSU and elsewhere. Our group has been actively leading aninternational effort to achieve interoperability among the several taxonomic imagedatabases. We have developed and published data schemas and Web sites in support ofour efforts. NSF support for this project is pending.2.Global Grid Forum Database Access and Integration Services (DAIS) Working Group, 2002-present.Contributed to development of standards and specifications for data access in the Grid community. I am a primary author of the base specification document and havecontributed to the relational and XML database access specifications. I have participatedin many conferences and workshops and made significant contributions to the directionand technology of this successful group.3.CEBAF Experiments Database, 1989–present.A database to manage the data acquisition, data analysis, and software for the ContinuousElectron Beam Accelerator Facility (CEBAF), a $500 million Dept. of Energy projectcurrently under construction in Virginia. This is utilizing an object-oriented database toprovide the capability of integrating both standard meta-data management and the dataanalysis and data acquisition aspects of the facility. In collaboration with Physics facultymembers Larry Dennis and Adam Sarty, FAMU faculty member Bryon Ehlmann, SCRIresearchers Peter Dragovitsch and Stephen Barrow, postdoctoral researcher DavidMeekins, graduate students, Samuel Eaves, Dmitriy Blaginin, Qing Zhang, HongweiWang, Troy Cochran, and Jonathon Felder.4.Co-director of the development of the FSU Ada Compiler, 1982–1986.Directed the Code Synthesis and Runtime System phases of the compiler development. The complete software system consists of approximately 60,000 lines of code. Incollaboration with Ted Baker and graduate students Tom Leonard, Sheila O'Connell,Kathy McKinley, Ken Spaulding, and Jim Groh.5.FSU Ada Compiler Validation, 1986.Result was successful processing of the 2500 Ada Validation Tests. This is the first University sponsored Compiler for Ada to complete the validation process. In collaboration withTed Baker and graduate students Tom Leonard, Sheila O'Connell, Kathy McKinley, KenSpaulding, and Jim Groh.Research Reports and Technology Specifications1.Mario Antonioletti, Malcolm Atkinson, Amy Krause, Simon Laws, Susan Malaika, Norman WPaton, Dave Pearson, Greg Riccardi, “Web Services Data Access and Integration (WS-DAI) Specifications,” GGF Data Area Working Paper, /projects/dais-wg/document/ Grid_Data_Service_Specification/en/5, March, 2004.2.Greg Riccardi, Mahadevan Subramanian, Shailendra Misra, Simon Laws, “GGF10 DAIS UsageScenarios,” DAIS Working Document, February, 20043.Greg Riccardi, “A Proposal for Aggregating DAIS Service Requests,” DAIS WorkingDocument, January, 2004.4.Greg Riccardi, “GGF9 DAIS Usage Scenarios,” DAIS Working Document, October, 2003.5.Greg Riccardi, “DAIS Data Service Interactions and the SkyQuery Portal,” DAIS WorkingDocument, August, 2003.6.Malcolm Atkinson, Simon Laws and Greg Riccardi, “Rationale for the Data Access andIntegration Architecture,” DAIS Working Document, August, 2003.7.Greg Riccardi, “Client Programming Interfaces and Examples,” DAIS Working Document,August, 2003.8.Greg Riccardi, “Model Examples: Simple Client-Service Interactions,” DAIS WorkingDocument, July, 2003.9.M. Antonioletti, M.P. Atkinson, N. P. Chue Hong, A. Krause, S. Malaika, G. McCance, S. Laws,J. Magowan, N.W. Paton, G. Riccardi, “Grid Data Service Specification,” ,” DAIS Working Document, June 2003.10.Greg Riccardi, “Sample Mappings from DAIS Conceptual Model to Service Instances,” DAISWorking Document, June, 2003.11.Neil P Chue Hong, Amy Krause, Susan Malaika, Gavin McCance, Simon Laws, James Magowan,Norman W Paton, Greg Riccardi, “Grid Database Service Specification Primer,” DAIS Working Document, May, 2003.12.A. Krause, S. Malaika, G. McCance, J. Maguire, N. Paton, G. Riccardi, “Grid Database ServiceSpecification,” DAIS Working Document, September, 2002.13.Dragovitsch, P., L.C. Dennis and G.A. Riccardi, “A Computer System for Data Analysis andData Acquisition for the CEBAF Large Acceptance Spectrometer,” SCRI Technical Report FSU-SCRI-92-63.14.Riccardi, G.A., A. Sharieh and J. Carr, “Adaptation of the Lanczos Method for ParallelExecution,” SCRI Technical Report FSU-SCRI-91-153, June, 1991.15.Sharieh, A., G.A. Riccardi and J. Carr, “Parallel Implementation of the Lanczos Method,” SCRITechnical Report FSU-SCRI-91-35, March, 1991.16.Riccardi, G.A., B. Traversat, and U. Chandra, “A Machine Independent Approach to ParallelProgramming,” SCRI Technical Report FSU-SCRI-89-108.17.Riccardi, G.A., C. Bauer and H. Lim, “A Vectorized Cellular Automata Model of Fluid Flow,”SCRI Technical Report FSU-SCRI-89T-53, 1989.18.Dekeyser, Georgiopoulos, Hannedouche, Riccardi, Vagi, and Youssef, “Aftran: Array FortranProgramming Language,” SCRI Technical Report FSU-SCRI-89T-16, 1989.19.Dekeyser, Georgiopoulos, Hannedouche, Riccardi, Vagi, and Youssef, “The Aftran VectorPreprocessor Project,” SCRI Technical Report FSU-SCRI-88T-43, 1988. “A Master–slave Model of Parallel Processing,” with Chandra and Traversat, SCRI Technical Report FSU-SCRI-88T-134, 1988.20.Riccardi, G.A., D. Druding, and D. Kopriva,”Multiprocessing of Multi-domain SpectralMethods on the ETA-10 Supercomputer,” SCRI Technical Report FSU-SCRI-88T-33, March, 1988.21.Riccardi, G.A., and P. Schow, “Adaptation and Performance of the ISODATA ClusteringAlgorithm on the Cyber 205 and ETA-10 Supercomputers,” SCRI Technical Report FSU-SCRI-88T-32, March, 1988.22.Riccardi, G.A., and M.I. McGinnis, “Hermes10–Message Passing on the ETA-10,” SCRITechnical Report FSU-SCRI-88T-31, March, 1988.23.Hook, A., G.A. Riccardi, and M. Lake, “Analyses of Reported Problems with Validated AdaCompilers,” IDA Paper P-1954. October, 1986.24.Riccardi, G.A., and T.P. Baker, “A Run-time Supervisor to Support Ada Tasking: Part 2,Rendezvous and Delays,” FSU Ada Project Report 83-7, May, 1983. A detailed design document for the FSU Ada Compiler Project. Revised and published (6).25.Riccardi, G.A., and T.P. Baker, “A Run-time Supervisor to Support Ada Tasking: Part 1, TaskActivation, Execution and Termination,” with T.P. Baker, FSU Ada Project Report 83-6, May, 1983. A detailed design document for the FSU Ada Compiler Project. Revised and Published (2).pp. 1–17.26.Baker, T.P., and G.A. Riccardi, “The Florida State University Ada Compiler Effort,” F.S.U. AdaProject Report number 82-3. Research Technical Report. A paper describing the major strategies employed in the F.S.U. Ada Compiler Project. pp. 1–10.Research Grants and Contracts1.Ronquist, F., G. Riccardi, R. van Engelen, A. Mast, and G. Erickson, “MorphBank: Web ImageDatabase Technology for Comparative Morphology and Biodiversity Research,” submitted to NSF June, 2004, rated “Outstanding.” Requested $2,500,000.2.Eugenio, P. and G. Riccardi, “Support for Experimental Nuclear Physics at CSIT,” funded byU.S. Dept. of Energy for $450,000 for the period November, 2004–October, 2007.3.Dennis, L.C., G. A. Riccardi, and P. Eugenio, “Support for Experimental Nuclear Physics atCSIT,” funded by U.S. Dept. of Energy for $580,000 for the period November, 2001–October, 2004.4.Dennis, L.C., and G. A. Riccardi, “Support for Experimental Nuclear Physics at CSIT,” fundedby U.S. Dept. of Energy for $598,000 for the period October, 1998–September, 2001.5.Dennis, L.C., G. A. Riccardi, and P. Dragovitsch, “Support for Experimental Nuclear Physics atSCRI,” funded by U.S. Dept. of Energy for $614,000 for the period October, 1995–September, 1998.6.Olson, Riccardi, and others, “Grand Challenge Application on HENP Data,” submitted to USDept. of Energy Grand Challenge program. Award announced February, 1997. Total funding of $2.4 million for 3 years awarded to Lawrence Berkeley National Lab. Joint project with Lawrence Berkeley National Lab, Argonne National Lab, Brookhaven National Lab, Florida State University, UCLA, University of Tennessee, and Yale University.7.Riccardi, G.A., “Central and Remote Databases for DUI Information.” software developmentcontract funded by the Florida Dept. of Highway Safety and Motor Vehicles for the period of October, 1996–September, 1997 for $37,000.8.Riccardi, G.A., “Central and Remote Databases for DUI Information.” software developmentcontract funded by the Florida Dept. of Highway Safety and Motor Vehicles for the period of April, 1996–April, 1997 for $100,000.9.Riccardi, G.A., L.C. Dennis, and P. Dragovitsch, “Support for Experimental Nuclear Physics atSCRI,” funded by U.S. Dept. of Energy for $308,000 for the period October, 1992–September, 1995.10.Riccardi, G.A. and J.J. O'Brien, “Massively Parallel Computation for Ocean Modelling,” fundedby the Office of Naval Research for $320,000 for the period March, 1993–March, 1996.11.Riccardi, G.A., Computer Science Section of the F.S.U. Supercomputer Computations ResearchInstitute proposal funded by the U.S. Department of Energy for 1991.12.Riccardi, G.A., Computer Science Section and Massively Parallel Computing Section of theSCRI five year proposal funded by the U.S. Department of Energy for the period 1989–1994. 13.Riccardi, G.A., Computer Science Section of the F.S.U. Supercomputer Computations ResearchInstitute proposal funded by the U.S. Department of Energy for 1990.14.Riccardi, G.A., Computer Science Section of the F.S.U. Supercomputer Computations ResearchInstitute proposal funded by the U.S. Department of Energy for 1989.15.Riccardi, G.A., Computer Science Section of the F.S.U. Supercomputer Computations ResearchInstitute proposal funded by the U.S. Department of Energy for 1988.16.Riccardi, G.A., “A Prototype Ada Compiler Evaluation System,” Institute for Defense Analysis,funded for $30,000 for the period of May, 1985 to December, 1985.17.Baker, T.P., and G.A. Riccardi, “An Extension to the Ada Compiler Project,” U.S. AFATL,Eglin AFB, funded for $300,000 for the period August, 1984 to September, 1985.18.Baker, T.P., and G.A. Riccardi, “An Extension to the Ada Compiler Project,” USAF ArmamentDivision, Eglin Air Force Base, funded for $300,000 for the period August, 1983 to September, 1984.。