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Towards Sustainable Energy: A Systematic Review of Renewable Energy Sources, Technologies, and Public Opinions

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IEEE.org | IEEE Xplore Digital Library | IEEE Standards | IEEE Spectrum | More Sites

December 2017

Regular Papers

Volume 105, Issue 12

Scanning the Issue

Efficient processing of deep neural networks: a tutorial and survey.

By V. Sze, Y.-H. Chen, T.-J. Yang, and J. S. Emer

This article provides a comprehensive tutorial and survey coverage of the recent advances toward enabling efficient processing of deep neural networks.

System Scaling With Nanostructured Power and RF Components

By P. M. Raj, H. Sharma, S. Sitaraman, D. Mishra, and R. Tummala

This article reviews the impact of nanostructured materials toward enhancing the performance and miniaturization of power and RF passive components in emerging smart systems.

Nonorthogonal Multiple Access for 5G and Beyond

By Y. Liu, Z. Qin, M. Elkashlan, Z. Ding, A. Nallanathan, and L. Hanzo

This article surveys the state-of-the-art research on power-domain nonorthogonal multiple access (NOMA), addressing the theoretical advances, major challenges, and opportunities.

Point of View

Beyond smart grid—a cyber–physical–social system in energy future.

By Yusheng Xue and Xinghuo Yu

Scanning Our Past

Materials science, instrument knowledge, and the power source renaissance.

By Matthew N. Eisler

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Title: densely connected convolutional networks.

Abstract: Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between layers close to the input and those close to the output. In this paper, we embrace this observation and introduce the Dense Convolutional Network (DenseNet), which connects each layer to every other layer in a feed-forward fashion. Whereas traditional convolutional networks with L layers have L connections - one between each layer and its subsequent layer - our network has L(L+1)/2 direct connections. For each layer, the feature-maps of all preceding layers are used as inputs, and its own feature-maps are used as inputs into all subsequent layers. DenseNets have several compelling advantages: they alleviate the vanishing-gradient problem, strengthen feature propagation, encourage feature reuse, and substantially reduce the number of parameters. We evaluate our proposed architecture on four highly competitive object recognition benchmark tasks (CIFAR-10, CIFAR-100, SVHN, and ImageNet). DenseNets obtain significant improvements over the state-of-the-art on most of them, whilst requiring less computation to achieve high performance. Code and pre-trained models are available at this https URL .

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2017 IEEE Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics

• Posted by Admin
• Posted in Events & Activities
•     Full Paper Deadline: 1 May 2017
•     Acceptance Notification: 15 August 2017
•     Camera-ready Paper Deadline: 15 September 2017

  Submission Guidelines
 All papers will be peer-reviewed and accepted papers of PrimeAsia2017 will be submitted to IEEE Xplore listing. Paper submission process will be managed by EDAS at https://edas.info/N23600 . Papers should be a maximum of four (4) pages including figures, tables, references and appendices. Prospective authors are expected to present their papers at the conference, and at least one author must register at the full rate for publication. For more information, please visit PrimeAsia2017 official website http://cas.ieeemy.org/primeasia2017/ or contact PrimeAsia2017 officer via E-mail [email protected]   Please do not hesitate to contact us if you will have any questions.   Waiting for your full paper and hope to see you at PrimeAsia2017!   With best wishes,   Sincerely,   Dr. Nurul Amziah Md Yunus General Chair PrimeAsia2017 IEEE Circuits and Systems Society Malaysia. http://cas.ieeemy.org/primeasia2017/ — Dr Noor Ain Kamsani Senior Lecturer Faculty of Engineering Department of Electrical & Electronic Engineering Universiti Putra Malaysia 43400 UPM Serdang Selangor, Malaysia Phone : +60389464366 Fax : +60389466327

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NeurIPS 2024, the Thirty-eighth Annual Conference on Neural Information Processing Systems, will be held at the Vancouver Convention Center

Monday Dec 9 through Sunday Dec 15. Monday is an industry expo.

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The Neural Information Processing Systems Foundation is a non-profit corporation whose purpose is to foster the exchange of research advances in Artificial Intelligence and Machine Learning, principally by hosting an annual interdisciplinary academic conference with the highest ethical standards for a diverse and inclusive community.

About the Conference

The conference was founded in 1987 and is now a multi-track interdisciplinary annual meeting that includes invited talks, demonstrations, symposia, and oral and poster presentations of refereed papers. Along with the conference is a professional exposition focusing on machine learning in practice, a series of tutorials, and topical workshops that provide a less formal setting for the exchange of ideas.

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School of Electrical and Computer Engineering

College of engineering, zheng wins best paper award for advanced packaging technologies.

The ECE Ph.D. alumni won the award for his research on fused-silica stitch-chip technology for RF/mm-wave multichiplet modules.

Georgia Tech School of Electrical and Computer Engineering graduate Ting Zheng won an IEEE Transactions on Components, Packaging and Manufacturing Technology (TCPMT) Best Paper Award, from the Advanced Packaging Category, for his research on fused-silica stitch-chip technology.

TCPMT is the flagship journal of the IEEE Electronics Packaging Society (EPS).

He was recognized for the paper he co-authored prior to his graduation, “Benchmarking and Demonstration of Low-Loss Fused-Silica Stitch-Chips with Compressible Microinterconnects for RF/mm-Wave Chiplet-Based Modules.”

It proposes and benchmarks ‘fused-silica stitch-chips’  as an interconnect technology between neighboring RF/mm-wave chiplets. Compared to conventional advanced packaging technologies, the stitch-chips enable low-loss and broadband interconnection, provide built-in mechanical deformation capability to compensate for differing chiplets heights, and provide a path towards package size scaling for large-scale multichiplet integration.

He was advised by ECE Professor and 3D Systems Packaging Research Center Director Muhannad Bakir.

Zheng is the second student from Bakir’s Integrated 3D Systems Lab to have their research recognized. Shengtao Yu won the Intel Outstanding Student Paper Award for this paper on co-packaged optics and fiber-chiplet-connectors at the 2023 IEEE Electronic Components and Technology Conference (ECTC), which is the flagship conference of IEEE EPS.

It is a rare honor for the same research group to win paper awards in the same year from both ECTC and TCPMT.

At the end of May, Zheng, Yu and Bakir will all attend ECTC 2024 in Denver, CO to receive the ECTC and TCPMT paper awards.   

Zack Winiecki

[email protected]

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IEEE ICRA Best Paper Award 2024

Members of the RM Cognitive Robotics department are part of the author group that received the Best Paper Award der ICRA Conference at the ICRA Conference 2024 in Japan. The paper is entitled:"Open X-Embodiment: Robotic Learning Datasets and RT-X Models" and was written by a group of researchers under the project leadership of Quan Vuong (DeepMind). The full list of authors and the abstract of the paper can be found at at arxiv . Co-authors from the Institute are Samuel Bustamante, Abhishek Padalkar, Antonin Raffin, Joao Silvério and Freek Stulp.

You can find more information about the project at Open X-Embodiment: Robotic Learning Datasets and RT-X Models . The ICRA Conference 2024 will take place from May 13 to 17 in Yokohama, Japan.

Lioba Suchenwirth

White paper that birthed crypto ZK-proofs receives IEEE ‘Test of Time’ award

A decade-old research paper seen as a “blueprint” for the first practical use of zero-knowledge proofs (ZK-proofs) has received an award from the Institute of Electrical and Electronics Engineers (IEEE), the world’s largest technical professional organization.

According to an announcement shared with Cointelegraph, the “genesis paper” — “Zerocash: Decentralized Anonymous Payments from Bitcoin” —  helped pave the way for ZK-proofs in crypto and has now been awarded the “Test of Time” award at the IEEE Symposium on Security and Privacy.

The paper, with 2,400 academic citations, did not transform finance but paved the way for the proliferation of projects using ZK-proofs, the firm added.

It also introduced the first practical use of the cryptographic technique in cryptocurrency for enhancing privacy.

The award goes to the publication’s authors: Alessandro Chiesa, Christina Garman, Matthew Green, Ian Miers, Eran Tromer, Madars Virza and Eli Ben-Sasson. Ben-Sasson founded the blockchain scaling firm StarkWare.

“The award reminds us that, looking back on it, this paper was the moment that ZK was catapulted onto the agenda of blockchain research,” said Ben-Sasson, who added that it was the moment that “started an ever-growing fascination with how it can help crypto to become the technology we all need.”

The paper described using Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge (zk-SNARKS) to construct a private payment protocol called Zerocash, which hides the origin, destination and number of transactions.

ZK-proofs are now a commonly used technique for Ethereum layer-2 solutions to prove the validity of on-chain data without revealing what that data specifically consists of.

They can help scalability by enabling techniques like rollups and the trustless validation of large amounts of data off-chain. Leading layer-2 networks currently using ZK-proofs include StarkNet, Linea, zkSync Era, Scroll and Polygon.

On May 14, Cointelegraph reported that regulators were cracking down on privacy-preserving protocols. However, ZK-proofs could offer solutions by preserving privacy while ensuring funds are not sent to sanctioned entities.

Ben-Sasson told Cointelegraph that privacy is a priority. “To support this we will add ZK capabilities to our prover Stwo, which would allow developers to get a more scalable version of the Zerocash construction on Starknet (and Ethereum).”

In April, Big Four accounting firm Ernst & Young launched an Ethereum-based solution using ZK-proofs to help its private business clients facilitate complex contracts.