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Iowa State University. Electrical and Computer Engineering. degree granting institution.

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Hong Kong University of Science and Technology (Hong Kong). Electronic and Computer Engineering. degree granting institution.

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University of Glasgow (United Kingdom). Department not provided. degree granting institution.

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Washington State University. Electrical Engineering. degree granting institution.

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Al-Dabooni, Seaar Jawad Kadhim, author.

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Alizadeh, Yasser, author.

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Avey, Joseph, author.

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Carraher, Lee A., author.

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Chang, Huiwen, author.

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Cranfield University (United Kingdom). School of Mechanical Engineering. degree granting institution.

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Das, Sourav, author. (orcid)0000-0002-7404-8133

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Dave, Abhilasha Harsukhbhai, author.

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Davis, Dylan A.P., author.

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Elahian, Bahareh, author.

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Eyre, C. J., author.

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Flanagan, Brian, author.

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Florida Atlantic University. Computer Engineering. degree granting institution.

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Gausin, Christine M., author. (orcid)0000-0003-3027-3002

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Geng, Hui, author.

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George Mason University. Electrical and Computer Engineering. degree granting institution.

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Ghasemzadeh, Mohammad, author.

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Gundala palle, Santosh reddy, author.

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Illinois Institute of Technology. Electrical and Computer Engineering. degree granting institution.

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Izenov, Yesdaulet, author.

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Jayaprakash, Neha Thotappala, author.

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Kwara State University (Nigeria). College of Information and Communication Technology. degree granting institution.

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Lam, Jasmine, author.

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Lee, Jeong Eun, author.

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Malik, Maria, author. (orcid)0000-0001-8425-2501

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Murphy, Quinn, author. (orcid)0000-0002-6011-7118

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Old Dominion University. Electrical/Computer Engineering. degree granting institution.

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Portland State University. Computer Science. degree granting institution.

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Schlueter, Jonathan Andrew, author. (orcid)0000-0001-9442-6720

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Shukla, Sharabh Ramshiromani, author. (orcid)0000-0002-2841-2897

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Silva, Ana Eduarda de Sá, author.

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SpringerLink (Online service)

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The Ohio State University. Civil Engineering. degree granting institution.

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Cover image for Anomaly Detection in Controller Area Network Data Using Hierarchical Analysis

Anomaly Detection in Controller Area Network Data Using Hierarchical Analysis

13.

Anomaly Detection in Controller Area Network Data Using Hierarchical Analysis

by

Flanagan, Brian, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10790805

Format:

Excerpt:

and external sensing technology. This work attempts to create an effective model for describing

Cover image for Analysis of Dynamic Mode Decomposition

Analysis of Dynamic Mode Decomposition

14.

Analysis of Dynamic Mode Decomposition

by

Muniraju, Archana, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10808982

Format:

Excerpt:

analyzing an algorithm is testing. In this work, DMD-a data based technique is used to test different cases

Cover image for Design of Coarse-grained Power Gating for a Fine-grained Many-core Processor Array

Design of Coarse-grained Power Gating for a Fine-grained Many-core Processor Array

15.

Design of Coarse-grained Power Gating for a Fine-grained Many-core Processor Array

by

Umapathy, Shylesh, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10823057

Format:

Excerpt:

of a fine-grained many-core processor array. This work provides a detailed analysis and comparison of

Cover image for Fog Computing Based IoT Applications and Their Performance

Fog Computing Based IoT Applications and Their Performance

16.

Fog Computing Based IoT Applications and Their Performance

by

Gundala palle, Santosh reddy, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10826020

Format:

Excerpt:

simulate our work, we used iFogSim simulation toolkit which is currently growing significantly for the past

Cover image for Destination Selection Using Deep Learning for an Autonomous Wheelchair Navigation in an Unmapped Indoor Environment

Destination Selection Using Deep Learning for an Autonomous Wheelchair Navigation in an Unmapped Indoor Environment

17.

Destination Selection Using Deep Learning for an Autonomous Wheelchair Navigation in an Unmapped Indoor Environment

by

Jayaprakash, Neha Thotappala, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10809893

Format:

Excerpt:

these autonomous wheelchairs. In this work, a novel approach to selecting a destination for an

Cover image for Design and Implementation of an Autonomous Solar Cell Manufacturing System

Design and Implementation of an Autonomous Solar Cell Manufacturing System

18.

Design and Implementation of an Autonomous Solar Cell Manufacturing System

by

Zaheer, Adam, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10810406

Format:

Excerpt:

In this work, a prototype of an autonomous DSSC manufacturing system is presented. With the

Cover image for Automated Customization of ML Inference on FPGAs

Automated Customization of ML Inference on FPGAs

19.

Automated Customization of ML Inference on FPGAs

by

Ghasemzadeh, Mohammad, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10814231

Format:

Excerpt:

requirements are necessary. My work proposes hardware-algorithm co-design approaches to customize ML inference

Cover image for Software-Hardware Systems for the Internet-of-Things

Software-Hardware Systems for the Internet-of-Things

20.

Software-Hardware Systems for the Internet-of-Things

by

Salehi-Abari, Omid, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10902469

Format:

Excerpt:

a huge diversity in their demands and constraints. Some applications work with small sensors and

Cover image for Social Engineering Knowledge Measured as a Security Countermeasure

Social Engineering Knowledge Measured as a Security Countermeasure

21.

Social Engineering Knowledge Measured as a Security Countermeasure

by

Sanders, Christopher Artejus, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10642128

Format:

Excerpt:

engineering threats. The scenarios highlighted in this work illustrated how costs play a role in protection

Cover image for Adaptive Dynamic Programming with Eligibility Traces and Complexity Reduction of High-Dimensional Systems

Adaptive Dynamic Programming with Eligibility Traces and Complexity Reduction of High-Dimensional Systems

22.

Adaptive Dynamic Programming with Eligibility Traces and Complexity Reduction of High-Dimensional Systems

by

Al-Dabooni, Seaar Jawad Kadhim, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10689387

Format:

Excerpt:

, respectively. The sixth work combines two different gradient prediction levels of critic networks. In this work

Cover image for Reducing Labeling Complexity in Streaming Data Mining

Reducing Labeling Complexity in Streaming Data Mining

23.

Reducing Labeling Complexity in Streaming Data Mining

by

Izenov, Yesdaulet, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10750272

Format:

Excerpt:

complexity. In this work, we present Frugal Hoeffding tree, a variation of the Hoeffding tree that uses less

Cover image for Integration of Low Loss Interconnects in CMOS

Integration of Low Loss Interconnects in CMOS

24.

Integration of Low Loss Interconnects in CMOS

by

Raju, Salahuddin, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10903379

Format:

Excerpt:

In this work, an interlayer dielectric with an extremely low dielectric constant of 1.96 is

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