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2023 International Conference on Smart-Green Technology in Electrical and inf.rmation Systems, ICSGTEIS 2023

作者： Kuwashima, Fumiyoshi Jarrahi, Mona Cakmakyapan, Semih Wada, Kenji Haraguchi, Masanobu Kawakami, Yuki Moriyasu, Takeshi Morikawa, Osamu Kurihara, Kazuyoshi Kitahara, Hideaki Furuya, Takashi Nakajima, Makoto Tani, Masahiko Fukui University of Technology Dep. of Electr. and Electron. Eng. Fukui Japan Ucla Electrical and Computer Eng. Los AngelesCA90095 United States Osaka Metropolitan University Dep. of Physics and Electronics Osaka Japan Tokushima Univ. Industrial and Social Science Grad. Sch. of Tech. Tokushima Japan Fukui Col. Natl. Inst. of Tech. Dep. of Elec. and Inf. Eng. Fukui Japan University of Fukui Faculty of Engineering Fukui Japan Japan Coast Guard Academy Liberal Arts Kure Japan University. of Fukui School of Education Fukui Japan FIR-UF University of Fukui Fukui Japan Osaka Univ. Inst. of Laser Engineering Osaka Japan

ISBN: (纸本)9798350382822

We apply the chaos supremacy of laser chaos system to the high stabilization of THz waves. Stability was demonstrated by down converting the optical beats between laser longitudinal modes in the THz domain to the radio frequency domain and comparing a conventional free running CW laser diode to a chaotically oscillating laser diode. Because of their exceptional stability, chaotically oscillating lasers are attractive options for optical pump sources in terahertz time-domain spectroscopy systems. © 2023 IEEE.

关键词： Stabilization

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Interpreting Object-level Foundation Models via Visual Precision Search

arXiv

引用

arXiv 2024年

作者： Chen, Ruoyu Liang, Siyuan Li, Jingzhi Liu, Shiming Li, Maosen Huang, Zhen Zhang, Hua Cao, Xiaochun Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China School of Cyber Security University of Chinese Academy of Sciences Beijing100049 China School of Computing NUS Singapore RAMS Lab Huawei Technologies Co. Ltd. China IAS BU Huawei Technologies Co. Ltd. China College of Computer NUDT China Key Lab. of Edu. Inf. for Nationalities YNNU Ministry of Education Kunming China School of Cyber Science and Technology Sun Yat-sen University Shenzhen Campus Shenzhen518107 China

Advances in multimodal pre-training have propelled object-level foundation models, such as Grounding DINO and Florence-2, in tasks like visual grounding and object detection. However, interpreting these models’ decisions has grown increasingly challenging. Existing interpretable attribution methods for object-level task interpretation have notable limitations: (1) gradient-based methods lack precise localization due to visual-textual fusion in foundation models, and (2) perturbation-based methods produce noisy saliency maps, limiting fine-grained interpretability. To address these, we propose a Visual Precision Search method that generates accurate attribution maps with fewer regions. Our method bypasses internal model parameters to overcome attribution issues from multimodal fusion, dividing inputs into sparse sub-regions and using consistency and collaboration scores to accurately identify critical decision-making regions. We also conducted a theoretical analysis of the boundary guarantees and scope of applicability of our method. Experiments on RefCOCO, MS COCO, and LVIS show our approach enhances object-level task interpretability over SOTA for Grounding DINO and Florence-2 across various evaluation metrics, with faithfulness gains of 23.7%, 31.6%, and 20.1% on MS COCO, LVIS, and RefCOCO for Grounding DINO, and 50.7% and 66.9% on MS COCO and RefCOCO for Florence-2. Additionally, our method can interpret failures in visual grounding and object detection tasks, surpassing existing methods across multiple evaluation metrics. The code is released at https://***/RuoyuChen10/VPS. Copyright © 2024, The Authors. All rights reserved.

关键词： Object detection

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Robustness and Diversity Seeking Data-Free Knowledge Distillation

Robustness and Diversity Seeking Data-Free Knowledge Distill...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Pengchao Han Jihong Park Shiqiang Wang Yejun Liu School of Computer Science and Engineering Northeastern University China School of Information Technology Deakin University Geelong VIC Australia IBM T. J. Watson Research Center Yorktown Heights NY USA School of Comm. & Inf. Engineering Chongqing University of Posts and Telecommunications China

Knowledge distillation (KD) has enabled remarkable progress in model compression and knowledge transfer. However, KD requires a large volume of original data or their representation statistics that are not usually available in practice. Data-free KD has recently been proposed to resolve this problem, wherein teacher and student models are fed by a synthetic sample generator trained from the teacher. Nonetheless, existing data-free KD methods rely on fine-tuning of weights to balance multiple losses, and ignore the diversity of generated samples, resulting in limited accuracy and robustness. To overcome this challenge, we propose robustness and diversity seeking data-free KD (RDSKD) in this paper. The generator loss function is crafted to produce samples with high authenticity, class diversity, and inter-sample diversity. Without real data, the objectives of seeking high sample authenticity and class diversity often conflict with each other, causing frequent loss fluctuations. We mitigate this by exponentially penalizing loss increments. With MNIST, CIFAR-10, and SVHN datasets, our experiments show that RDSKD achieves higher accuracy with more robustness over different hyperparameter settings, compared to other data-free KD methods such as DAFL, MSKD, ZSKD, and DeepInversion.

关键词： Fluctuations Conferences Training data Signal processing Robustness Generators Acoustics

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URLLC in Large-Scale Wireless Networks With Time and Frequency Diversities

URLLC in Large-Scale Wireless Networks With Time and Frequen...

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IEEE Global Communications Conference

作者： Meifang Wu Yi Zhong Gang Wang Changyang She Xiaohu Ge Han-Chieh Chao School of Electron. Inf. & Commun. Huazhong University of Science and Technology Wuhan China School of Electrical & Inf. Engineering University of Sydney Sydney Australia School of Computer Science & Inf. Engineering National Dong Hwa University Taiwan

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

Emerging wireless applications starve for the realization of the ultra-reliable and low-latency communication (URLLC). The reliability and latency requirements of URLLC for a specific single link have been explored extensively, but a comprehensive evaluation of the URLLC in a large-scale wireless network is still lacking. In this paper, by using the point process theory we evaluate the probability that the delay and reliability requirement of a typical URLLC user can be satisfied in the large-scale wireless network. This probability is also the ratio of users with satisfactory delay and reliability in the wireless network. In order to improve the performance of URLLC, we propose two retransmission policies, corresponding to time diversity and frequency diversity, in which the retransmissions are silenced randomly to reduce the interference correlation in different frames so to reduce the effect of correlations between d-ifferent retransmissions. Simulation and numerical results reveal that both of the proposed two retransmission policies improve the performance of URLLC, and the retransmission policy of frequency diversity is better than that of the time diversity.

关键词： Delays Transmitters Reliability Fading channels Interference Receivers Wireless networks

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Stabilization of THz waves using chaos supremacy

Stabilization of THz waves using chaos supremacy

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International Conference on Smart Green Technology in Electrical and inf.rmation Systems (ICSGTEIS)

作者： Fumiyoshi Kuwashima Mona Jarrahi Semih Cakmakyapan Kenji Wada Masanobu Haraguchi Yuki Kawakami Takeshi Moriyasu Osamu Morikawa Kazuyoshi Kurihara Hideaki Kitahara Takashi Furuya Makoto Nakajima Masahiko Tani Dep. of Electr. and Electron. Eng. Fukui University of Technology Fukui Japan Electrical and Computer Eng. UCLA Los Angeles CA USA Dep. of Physics and Electronics Osaka Metropolitan University Osaka Japan Industrial and Social Science Grad. Sch. of Tech. Tokushima Univ. Tokushima Japan Dep. of Elec. and Inf. Eng. Natl. Inst. of Tech. Fukui Col. Fukui Japan Faculty of Engineering University of Fukui Fukui Japan Chair of Liberal Arts Japan Coast Guard Academy Kure Japan School of Education University. of Fukui Fukui Japan FIR-UF University of Fukui Fukui Japan Inst. of Laser Engineering Osaka Univ. Osaka Japan

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Robustness and diversity seeking data-free knowledge distillation

arXiv

引用

arXiv 2020年

作者： Han, Pengchao Park, Jihong Wang, Shiqiang Liu, Yejun School of Computer Science and Engineering Northeastern University China School of Information Technology Deakin University GeelongVIC3220 Australia IBM T. J. Watson Research Center Yorktown HeightsNY United States School of Comm. & Inf. Engineering Chongqing University of Posts and Telecommunications China

关键词： Knowledge management

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Using the PerFECt Framework to Establish an Onlife Community for Theatre in Mathematics to Teach Principles of Computing

Using the PerFECt Framework to Establish an Onlife Community...

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Nektarios Moumoutzis Dessislava Paneva-Marinova Chara Xanthaki Polyxeni Arapi Nikos Pappas Stavros Christodoulakis Institute of Mathematics & Informatics Bulgarian Academy of Sciences (IMI-BAS) Institute of Mathematics & Informatics Bulgarian Academy of Sciences (IMI-BAS) Sofia Bulgaria Computer Science Teacher in Secondary Education Chania Greece Lab. of Distr. Multimedia Inf. Systems & Applications School of Electrical and Computer Engineering Technical University of Crete (TUC/MUSIC) Chania Greece

ISBN: (数字)9781728173030

ISBN: (纸本)9781728173047

The new reality brought about by digital technologies is characterized by new qualities, new opportunities for action, new community affordances, that are captures by the term onlife. This term was initially proposed in the Onlife Manifesto and used in this paper to signify certain qualities that are important in understanding modern digital platforms and applications as well as guide the efforts for effectively extending to provide new capabilities to their users. Specific design principles are presented exemplified by the presentation of the design of a Community of Practice for teachers involved in the pilot activities of the Erasmus+ project TIM - Theatre in Mathematics that promote the adoption of Theatre in teaching Mathematics in Primary and Lower Secondary Education targeting 8-14 years old students.

关键词： Mathematics Education Electronic mail computers Software Conferences inf.rmatics

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Cooperative Driver Pathway Discovery by Hierarchical Clustering and Link Prediction

Cooperative Driver Pathway Discovery by Hierarchical Cluster...

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IEEE International Conference on Bioinf.rmatics and Biomedicine (BIBM)

作者： Sufang Li Jun Wang Maozu Guo Xiangliang Zhang College of Computer and Information Sciences Southwest University Chongqing China Joint SDU-NTU Centre for Artificial Intelligence Research Shandong University Jinan China College of Elec. &Inf. Eng. Beijing University of Civil Engineering & Architecture Beijing China CEMSE King Abdullah University of Science and Technology Thuwal SA

ISBN: (数字)9781728162157

ISBN: (纸本)9781728162164

Identifying driver pathway is a critical step to uncover the natural laws of the occurrence and progression of disease. Many studies show that multiple pathways often function cooperatively in carcinogenesis. However, how to computationally identify cooperative driver pathways of cancers is not well studied yet. Existing cooperative driver pathway identification methods either suffer from single type of genetic inf.rmation source or computation difficulty. In this paper, we proposed a method (CDPLP) based on hierarchical clustering and link prediction. CDPLP firstly devises a new similarity metric to quantity the exclusivity and co-expression of two gene modules, and thus to obtain gene sets with exclusivity by hierarchical clustering. Next, it uses link prediction on the pathway-pathway interaction network to replenish the interactions between pathways. After that, CDPLP combines the gene sets and updated pathway network to discover the pathway pairs with high functional interaction and occurrence as cooperative pathways. CDPLP can make full use of multiple genetic inf.rmation sources such as the mutation data, gene-gene interaction data and pathway-pathway network, and facilitate the optimization solution. We evaluated the performance of CDPLP on TCGA breast cancer (BRCA) dataset and compared it with other popular methods. The results show that cooperative driver pathways identified by CDPLP are highly associated with the target cancer, and are involved with carcinogenesis and several key biological processes.

关键词： Cancer Measurement Heterogeneous networks Bioinf.rmatics Tumors Optimization Genomics

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Operation Dependencies in Loop Pipelining for High-Level Synthesis

Operation Dependencies in Loop Pipelining for High-Level Syn...

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2018 South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA_CECNSM 2018

作者： Dimitriou, Georgios Dossis, Michael Stamoulis, Georgios Dept. of Computer Science University of Thessaly Lamia Greece Dept. of Inf. Engineering TEI of W. Macedonia Kastoria Greece Dept. of Electrical and Computer Engineering University of Thessaly Volos Greece

ISBN: (纸本)9786188331419

Research and industry interest in high-level synthesis has been renewed in the last few years, proven by the introduction of new tools or improved versions of existing tools. Academic tools like Gaut or CCC have recently appeared in new versions with expanded functionality in order to cover increased hardware design requirements. Likewise, industrial tools like Xilinx VivadoHLS or, more recently, Cadence Stratus have appeared and are continuously evolving in their effort to succeed in the market. One technology that high-level synthesis tools have chosen to invest on is compiler-driven code optimizations, which are a promising means to improve efficiency of automatically generated hardware. Loop transformations are among the most popular compiler optimizations, for both software and hardware targets. Loop unrolling and loop pipelining, coupled with careful instruction reordering, can deliver highly optimized output. Instruction dependencies play a significant role in such optimizations, limiting performance improvement for the final code. In this paper, we discuss the issue of dependencies among loop body operations, especially those forming cycles, and their impact on high-level synthesis. We present results from experiments with several benchmarks on the CCC and VivadoHLS tools, showing that CCC can deliver better output than VivadoHLS in the presence of complex operation dependence cycles. © 2018 Tei of Western Macedonia.

关键词： High level synthesis

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New Parallel Algorithms for All Pairwise Computation on Large HPC Clusters

New Parallel Algorithms for All Pairwise Computation on Larg...

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IEEE International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)

作者： Tao Tang Hao Wu Wei Bao Pengyi Yang Dong Yuan Bing Bing Zhou Faculty of Engineering and IT University of Technology Sydney Sydney Australia School of Computer Science University of Sydney Sydney Australia School of Mathematics & Statistics University of Sydney Sydney Australia School of Elec. & Inf. Engineering University of Sydney Sydney Australia

ISBN: (数字)9781728126166

ISBN: (纸本)9781728126173

All pairwise computation is defined as performing computation between every pair of the elements in a given dataset. It is often a necessary first step in a number of bioinf.rmatics applications. Many of such applications require multiple terabytes of main memory and take multiple peta floating point operations to complete the computation. Therefore, large HPC clusters are needed to tackle these large-scale computational problems. Conventionally designed parallel algorithms using data partitioning may have a scalability issue, i.e., for a given problem of fixed size the efficiency may decrease if the number of compute nodes is increased (Amdahl's law). In this paper we introduce a new method for parallel algorithm design. Using this method we first design an efficient one-dimensional (1D) ring algorithm and then a two-dimensional (2D) algorithm based on the 1D ring for all pairwise computation. When increasing the compute nodes, instead of reducing the block size, we make multiple copies of the original data blocks in the 1D ring and distribute them across the added compute nodes in the other dimension. By properly organizing the compute nodes the communication overhead can be reduced to a minimum in this two-dimensional setting. Experiments on a Cray XC40 HPC supercomputer show that our new algorithms are very efficient and scalable for large-scale all pairwise computation on large HPC clusters.

关键词： Parallel algorithms Clustering algorithms Australia Two dimensional displays Partitioning algorithms Task analysis Correlation

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