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IEEE International Conference on Communications (ICC)

作者： Chien Chen Hoa-Chuan Fang Muhammad Shahid Iqbal Department of Computer Science and Information Technology Service Center National Chiao Tung University Hsinchu Taiwan Department of Computer Science National Chiao Tung University Hsinchu Taiwan EECS International Graduate Program National Chiao Tung University Hsinchu Taiwan

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

The Quality of Service (QoS) for applications is becoming increasingly important with the expansion of the Internet. A software-defined network offers flexibility and scalability in the use of network resources, like a meter table, which enables OpenFlow switches to measure flow rates and can be used to realize the rate limiter QoS. However, this drops packets when the flow-rate is over the limit, making the TCP congestion window reduce and grow periodically. The QoS of the upper layer using TCP will suffer regularly because of packet losses and bandwidth oscillation. Therefore, we propose a QoSTCP protocol using the meter and Rate Limiting Notification (RLN) to improve the QoS of TCP in SDN. The meter in the switch measures the flow rate to mark RLNs in the packets when the flow rate exceeds the threshold. A QoSTCP sender gets marking information to reduce the window size proportional to the marking packet ratio to avoid packet drop. We also provide a theoretical analysis to estimate when to mark packets at specific thresholds under two kinds of bandwidth demands in QoS, maximum and average rate. In order to verify QoSTCP performance, we implement a Two Rate Three Color Marker (trTCM) meter to measure the flow rate and mark RLNs using a programming protocol-independent Packet Processors (P4) switch. To simplify our implementation, the existing Explicit Congestion Notification (ECN) and Data Center TCP (DCTCP) are modified to emulate QoSTCP behavior. Experiment results confirm not only that QoSTCP provides a consistent rate guarantee by avoiding packet drop but also that it matches our theoretical analytical results.

关键词： Quality of service Bandwidth Meters Oscillators Protocols Data centers Control systems

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A literature review of crowd-counting system on convolutional neural network

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IOP Conference Series: Earth and Environmental science 2021年第1期729卷

作者： A Chrysler R Gunarso T Puteri H L H S Warnars Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia 11480

With the proliferation usage of video surveillance for safety, traffic control, and privacy purposes and with the constant growth of population, it is important to keep monitoring using Closed-Circuit Television (CCTV). With new upcoming developed technologies, new systems and algorithms are introduced and implemented to the crowd counting system today retrieving live video surveillance from the CCTV. However, recent studies show that there are some challenges still faced regarding the crowd counting system which uses the density estimation. The problems that occurred have resulted from the inaccuracy of the system that is caused by several factors. Factors such as the perspective distortion which is caused by the lack of data training and the method such as face detection is an ineffective method to determine the population density. Studies proposed have projected the idea of developing a more robust crowd counting methodology by implementing crowd counting by detection, clustering, and regression. Implementing these methods using the Convolutional Neural Network (CNN) will better the result of the detection since in CNN the image can be inputted and it will undergo several layers which will result in the system being able to differentiate one image from the other. With CNN the process of crowd counting will be able to be more advanced.

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Visual Navigation Using a Webcam Based on Semantic Segmentation for Indoor Robots

Visual Navigation Using a Webcam Based on Semantic Segmentat...

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International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Miho Adachi Sara Shatari Ryusuke Miyamoto Department of Computer Science Graduate School of Science and Technology Department of Computer Science School of Science and Technology Meiji University Kawasaki Japan

ISBN: (数字)9781728156866

ISBN: (纸本)9781728156873

The realization of a moving robot that can autonomously work in an actual environment has become important. A three-dimensional dense map that was created using three-dimensional (3D) depth sensors, such as light detection and ranging (LiDAR), is popular in the research field of autonomous moving robots. However, this approach has a few disadvantages: the price of 3D sensing devices and the robustness of localization in practical scenarios with many movable obstacles. To solve this problem, this paper proposes a vision-based navigation scheme that enables autonomous movement in indoor scenes; only a webcam is used as an external sensor. The experimental results from an experiment conducted in a university building demonstrated that a robot can move around on a floor.

关键词： Robot sensing systems Three-dimensional displays Navigation Semantics Corner detection

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Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study

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The Lancet Digital Health 2025年第5期7卷 100868页

作者： Meng, Ziyao Guan, Zhouyu Yu, Shujie Wu, Yilan Zhao, Yaoning Shen, Jie Lim, Cynthia Ciwei Chen, Tingli Yang, Dawei Ran, An Ran He, Feng Hamzah, Haslina Singh, Sarkaaj Abd Raof, Anis Syazwani Lee-Boey, Jian Wen Samuel Lim, Soo-Kun Sun, Xufang Ge, Shuwang Xu, Gang Su, Hua Cheng, Yang Lu, Feng Liao, Xiaofei Jin, Hai Deng, Chenxin Ruan, Lei Zhang, Cuntai Wu, Chan Dai, Rongping Jin, Yixiao Wang, Wenxiao Li, Tingyao Liu, Ruhan Li, Jiajia Shu, Jia Lu, Yuwei Wang, Xiangning Wu, Qiang Qin, Yiming Tang, Jin Sheng, Xiaohua Jiao, Qiong Yang, Xiaokang Guo, Minyi McKay, Gareth J Hogg, Ruth E Liew, Gerald Chee, Evelyn Yi Lyn Hsu, Wynne Lee, Mong Li Szeto, Simon Luk, Andrea O Y Chan, Juliana C N Cheung, Carol Y Tan, Gavin Siew Wei Tham, Yih-Chung Cheng, Ching-Yu Sabanayagam, Charumathi Lim, Lee-Ling Jia, Weiping Li, Huating Sheng, Bin Wong, Tien Yin Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases Department of Computer Science and Engineering School of Electronic Information and Electrical Engineering Institute for Proactive Healthcare Shanghai Jiao Tong University Department of Endocrinology and Metabolism Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai Diabetes Institute Shanghai Clinical Centre for Diabetes Shanghai Key Laboratory of Diabetes Mellitus Shanghai China MOE Key Laboratory of AI School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Beijing Tsinghua Changgung Hospital Eye Center School of Clinical Medicine Tsinghua Medicine Tsinghua University Beijing China Medical Records and Statistics Office Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China Department of Renal Medicine Singapore General Hospital SingHealth-Duke Academic Medical Centre Singapore Singapore Department of Ophthalmology Shanghai Health and Medical Center Wuxi China Department of Ophthalmology and Visual Sciences The Chinese University of Hong Kong Hong Kong Special Administrative Region China Singapore Eye Research Institute Singapore National Eye Centre Singapore Department of Medicine Faculty of Medicine Universiti Malaya Kuala Lumpur Malaysia Department of Ophthalmology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Hubei Wuhan China Department of Nephrology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China Department of Nephrology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China Department of Ophthalmology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China National Engineering Research Centre for Big Dat

Background: Improving the accessibility of screening diabetic kidney disease (DKD) and differentiating isolated diabetic nephropathy from non-diabetic kidney disease (NDKD) are two major challenges in the field of diabetes care. We aimed to develop and validate an artificial intelligence (AI) deep learning system to detect DKD and isolated diabetic nephropathy from retinal fundus images. Methods: In this population-based study, we developed a retinal image-based AI-deep learning system, DeepDKD, pretrained using 734 084 retinal fundus images. First, for DKD detection, we used 486 312 retinal images from 121 578 participants in the Shanghai Integrated Diabetes Prevention and Care System for development and internal validation, and ten multi-ethnic datasets from China, Singapore, Malaysia, Australia, and the UK (65 406 participants) for external validation. Second, to differentiate isolated diabetic nephropathy from NDKD, we used 1068 retinal images from 267 participants for development and internal validation, and three multi-ethnic datasets from China, Malaysia, and the UK (244 participants) for external validation. Finally, we conducted two proof-of-concept studies: a prospective real-world study with 3 months' follow-up to evaluate the effectiveness of DeepDKD in screening DKD;and a longitudinal analysis of the effectiveness of DeepDKD in differentiating isolated diabetic nephropathy from NDKD on renal function changes with 4·6 years' follow-up. Findings: For detecting DKD, DeepDKD achieved an area under the receiver operating characteristic curve (AUC) of 0·842 (95% CI 0·838–0·846) on the internal validation dataset and AUCs of 0·791–0·826 across external validation datasets. For differentiating isolated diabetic nephropathy from NDKD, DeepDKD achieved an AUC of 0·906 (0·825–0·966) on the internal validation dataset and AUCs of 0·733–0·844 across external validation datasets. In the prospective study, compared with the metadata model, DeepDKD could detect DKD wit

关键词： Deep learning

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MAVEN-ERE: A Unified Large-scale Dataset for Event Coreference, Temporal, Causal, and Subevent Relation Extraction

arXiv

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arXiv 2022年

作者： Wang, Xiaozhi Chen, Yulin Ding, Ning Peng, Hao Wang, Zimu Lin, Yankai Han, Xu Hou, Lei Li, Juanzi Liu, Zhiyuan Li, Peng Zhou, Jie Department of Computer Science and Technology BNRist China Shenzhen International Graduate School China THU-Siemens Ltd. China Joint Research Center for Industrial Intelligence and IoT China Tsinghua University Beijing China Xi’an Jiaotong-Liverpool University Suzhou China Gaoling School of Artificial Intelligence Renmin University of China Beijing China Beijing Key Laboratory of Big Data Management and Analysis Methods Beijing China Pattern Recognition Center WeChat AI Tencent Inc China

The diverse relationships among real-world events, including coreference, temporal, causal, and subevent relations, are fundamental to understanding natural languages. However, two drawbacks of existing datasets limit event relation extraction (ERE) tasks: (1) Small scale. Due to the annotation complexity, the data scale of existing datasets is limited, which cannot well train and evaluate data-hungry models. (2) Absence of unified annotation. Different types of event relations naturally interact with each other, but existing datasets only cover limited relation types at once, which prevents models from taking full advantage of relation interactions. To address these issues, we construct a unified large-scale human-annotated ERE dataset MAVEN-ERE with improved annotation schemes. It contains 103, 193 event coreference chains, 1, 216, 217 temporal relations, 57, 992 causal relations, and 15, 841 subevent relations, which is larger than existing datasets of all the ERE tasks by at least an order of magnitude. Experiments show that ERE on MAVEN-ERE is quite challenging, and considering relation interactions with joint learning can improve performances. The dataset and source codes can be obtained from https://***/THU-KEG/MAVEN-ERE. Copyright © 2022, The Authors. All rights reserved.

关键词： Extraction

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Overcoming entropic limitations on asymptotic state transformations through probabilistic protocols

arXiv

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arXiv 2022年

作者： Regula, Bartosz Lami, Ludovico Wilde, Mark M. Department of Physics Graduate School of Science The University of Tokyo Bunkyo-ku Tokyo113-0033 Japan Institut für Theoretische Physik und IQST Universität Ulm Albert-Einstein-Allee 11 UlmD-89069 Germany School of Electrical and Computer Engineering Cornell University IthacaNY14850 United States Hearne Institute for Theoretical Physics Department of Physics and Astronomy Center for Computation and Technology Louisiana State University Baton RougeLA70803 United States

The quantum relative entropy is known to play a key role in determining the asymptotic convertibility of quantum states in general resource-theoretic settings, often constituting the unique monotone that is relevant in the asymptotic regime. We show that this is no longer the case when one allows stochastic protocols that may only succeed with some probability, in which case the quantum relative entropy is insufficient to characterize the rates of asymptotic state transformations, and a new entropic quantity based on a regularization of the Hilbert projective metric comes into play. Such a scenario is motivated by a setting where the cost associated with transformations of quantum states, typically taken to be the number of copies of a given state, is instead identified with the size of the quantum memory needed to realize the protocol. Our approach allows for constructing transformation protocols that achieve strictly higher rates than those imposed by the relative entropy. Focusing on the task of resource distillation, we give broadly applicable strong converse bounds on the asymptotic rates of probabilistic distillation protocols, and show them to be tight in relevant settings such as entanglement distillation with non-entangling operations. This generalizes and extends previously known limitations that only applied to deterministic protocols. Our methods are based on recent results for probabilistic one-shot transformations as well as a new asymptotic equipartition property for the projective relative entropy. Copyright © 2022, The Authors. All rights reserved.

关键词： Distillation

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Complexity of computing the anti-ramsey numbers for paths 45

Complexity of computing the anti-ramsey numbers for paths

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45th International Symposium on Mathematical Foundations of computer science, MFCS 2020

作者： Amiri, Saeed Akhoondian Popa, Alexandru Roghani, Mohammad Shahkarami, Golnoosh Soltani, Reza Vahidi, Hossein University of Cologne Germany University of Bucharest Romania National Institute of Research and Development in Informatics Bucharest Romania Max Planck Institute for Informatics Saarland Informatics Campus Saarbrücken Germany Sharif University of Technology Teheran Iran MPI for Informatics Saarland Informatics Campus Graduate School of Computer Science Saarbrücken Germany

ISBN: (纸本)9783959771597

The anti-Ramsey numbers are a fundamental notion in graph theory, introduced in 1978, by Erdös, Simonovits and Sós. For given graphs G and H the anti-Ramsey number ar(G, H) is defined to be the maximum number k such that there exists an assignment of k colors to the edges of G in which every copy of H in G has at least two edges with the same color. Usually, combinatorists study extremal values of anti-Ramsey numbers for various classes of graphs. There are works on the computational complexity of the problem when H is a star. Along this line of research, we study the complexity of computing the anti-Ramsey number ar(G, Pk), where Pk is a path of length k. First, we observe that when k is close to n, the problem is hard;hence, the challenging part is the computational complexity of the problem when k is a fixed constant. We provide a characterization of the problem for paths of constant length. Our first main contribution is to prove that computing ar(G, Pk) for every integer k > 2 is NP-hard. We obtain this by providing several structural properties of such coloring in graphs. We investigate further and show that approximating ar(G, P3) to a factor of n−1/2−Ε is hard already in 3-partite graphs, unless P = NP. We also study the exact complexity of the precolored version and show that there is no subexponential algorithm for the problem unless ETH fails for any fixed constant k. Given the hardness of approximation and parametrization of the problem, it is natural to study the problem on restricted graph families. Along this line, we first introduce the notion of color connected coloring, and, employing this structural property, we obtain a linear time algorithm to compute ar(G, Pk), for every integer k, when the host graph, G, is a tree. © Nathalie Bertrand;licensed under Creative Commons License CC-BY 45th International Symposium on Mathematical Foundations of computer science (MFCS 2020).

关键词： Color

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Accurately predicting anticancer peptide using an ensemble of heterogeneously trained classifiers

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Informatics in Medicine Unlocked 2023年 42卷

作者： Azim, Sayed Mehedi Sabab, Noor Hossain Nuri Noshadi, Iman Alinejad-Rokny, Hamid Sharma, Alok Shatabda, Swakkhar Dehzangi, Iman Center for Computational and Integrative Biology Rutgers University Camden 08102 NJ United States Department of Computer Science and Engineering United International University Plot 2 United City Madani Avenue BaddaDhaka 1212 Bangladesh Department of Bioengineering University of California Riverside 92507 CA United States BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering The University of New South Wales (UNSW Sydney) Sydney NSW 2052 Australia UNSW Data Science Hub UNSW Sydney Sydney NSW 2052 Australia Health Data Analytics Program AI-enabled Processes Research Centre Macquarie University Sydney 2109 Australia Institute for Integrated and Intelligent Systems Griffith University Brisbane Australia Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama 230-0045 Japan Department of Computer Science Rutgers University Camden 08102 NJ United States

The use of therapeutic peptides for the treatment of cancer has received tremendous attention in recent years. Anticancer peptides (ACPs) are considered new anticancer drugs which have several advantages over chemistry-based drugs including high specificity, strong tumor penetration capacity, and low toxicity level for normal cells. Due to the rise of experimentally verified bioactive peptides, several in silico approaches became imperative for the investigation of the characteristics of ACPs. In this paper, we proposed a new machine learning tool named iACP-RF that uses a combination of several sequence-based features and an ensemble of three heterogeneously trained Random Forest classifiers to accurately predict anticancer peptides. Experimental results show that our proposed model achieves an accuracy of 75.9% which outperforms other state-of-the-art methods by a significant margin. We also achieve 0.52, 75.6%, and 76.2% in terms of Matthews Correlation Coefficient (MCC), Sensitivity, and Specificity, respectively. iACP-RF as a standalone tool and its source code are publicly available at: https://***/MLBC-lab/iACP-RF. © 2023 The Authors

关键词： Anticancer peptides Ensemble learning Feature extraction Heterogeneous classifiers Machine learning Random Forest

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Noble Inheritance Mechanism of Digital Content for "digital-Ji-in" toward Sustainable Society 8

Noble Inheritance Mechanism of Digital Content for "digital-...

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8th International Symposium on Computing and Networking Workshops, CANDARW 2020

作者： Hiji, Masahiro Hashi, Yuichi Kikuchi, Kazuhiko Fujita, Shigeru Miyanishi, Yotaro Shiratori, Norio Tohoku University Graduate School of Economics and Management Sendai Japan Business Strategy General Office Hitachi Solutions East Japan Ltd Sendai Japan Chiba Institute of Technology Department of Computer Science Narashino Japan Isem Inc. Ceo Founder Tokyo Japan Chuo University Research and Development Initiative Tokyo Japan

ISBN: (纸本)9781728199191

Various research and development efforts have been made to implement cyber-physical systems, aiming to maintain the associations between digital and physical identities (such as sensors, events, or people). In this study, we consider a scenario with the inheritance of digital content owned by a deceased person. People increasingly store their information (such as digital photos and videos) in cloud services, and this content may become inaccessible to the relatives in case of an unexpected death. In this paper, we propose a method for realizing a noble inheritance mechanism for secret digital content in "Digital-Ji-in"which maintains digital identities toward sustainable society. Specifically, we use a secure secret scheme to realize the noble inheritance mechanism. The "shares"of the encryption key are distributed to future heirs and the trusted third party such as cloud provider. The cryptographic key cannot be recovered until all the heirs' shares are united and the trusted third party's shares are obtained. This paper describes and analyzes the proposed method. Moreover, it outlines a preliminary scenario with "the right to be forgotten."The proposed method can help maintain the connection between the real world and cyberspace in perpetuity. © 2020 IEEE.

关键词： Embedded systems

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Unitary Excitation Transfer between Coupled Cavities Using Temporal Switching

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Physical Review Letters 2021年第1期127卷 013902-013902页

作者： Yarden Mazor Michele Cotrufo Andrea Alù Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA School of Electrical Engineering Tel-Aviv University Ramat-Aviv Tel-Aviv 69978 Israel Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA Physics Program Graduate Center of the City University of New York New York New York 10016 USA

Tailored time variations can enable efficient control over signal flows, giving rise to exotic wave phenomena. In this work, we demonstrate how abrupt temporal switching of the coupling between two cavities can tailor the energy flow between them beyond the limitations of static scenarios, enabling unitary excitation transfer. The proposed scheme is robust with respect to a wide range of nonidealities, with implications for classical and quantum phenomena, from computing to nanophotonic systems.

关键词： Metamaterials Coupled oscillators

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