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SID Symposium, Seminar, and Exhibition 2017, Display Week 2017

作者： Pan, Su Chigrinov, Vladimir G. Kwok, Hoi Sing State Key Lab on Advanced Displays and Optoelectronics Department of Electronic and Computer Engineering Hong Kong University of Science & Technology Hong Kong

ISBN: (纸本)9781510848757

A coatable polarizer with high performance is a perpetual goal because of its numerous advantages. Here, we demonstrate a photo-induced coatable polarizer with a dichroic ratio of more than 50, a contrast ratio of more than 300, and a thickness less than 500 nm. This polarizer offers a simple and economical technique to realize advanced displays with low cost, ultra-thin profile, flexible style, and high performance. © 2017 SID.

关键词： Azo dyes

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A Markov chain sequence generator for power macromodeling 02

A Markov chain sequence generator for power macromodeling

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IEEE/ACM International Conference on computer Aided Design (ICCAD)

作者： Liu, Xun Papaefthymiou, Marios C. Advanced Computer Architecture Lab. Dept. of Electrical Engineering University of Michigan Ann Arbor MI 48109 United States

ISBN: (纸本)9780780376076

In this paper, we present a novel sequence generator based on a Markov chain model. Specifically, we formulate the problem of generating a sequence of vectors with given average input probability p, average transition density d, and spatial correlation s as a transition matrix computation problem, in which the matrix elements are subject to constraints derived from the specified statistics. We also give a practical heuristic that computes such a matrix and generates a sequence of l n-bit vectors in O(nl+n2) time. Derived from a strongly mixing Markov chain, our generator yields binary vector sequences with accurate statistics, high uniformly, and high randomness. Experimental results show that our sequence generator can cover more than 99% of the parameter space. Sequences of 2,000 48-bit vectors are generated in less than 0.05 seconds, with average deviations of the signal statistics p, d, and s equal to 1.6%, 1.8%, and 2.8%, respectively. Our generator enables the detailed study of power macromodeling. Using our tool and the ISCAS-85 benchmark circuits, we have assessed the sensitivity of power dissipation to the three input statistics p, d, and s. Our investigation reveals that power is most sensitive to transition density, while only occasionally exhibiting high sensitivity to signal probability and spatial correlation. Our experiments also show that input signal imbalance can cause estimation errors as high as 100% in extreme cases, although errors are usually within 25%.

关键词： Markov processes

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DO-WF2Q: Delay-optimised WF2Q packet scheduling

DO-WF2Q: Delay-optimised WF2Q packet scheduling

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作者： Fei, X. Marshall, A. Luo, J. Advanced Telecommunications Systems Lab. School of Electrical and Electronic Engineering Queen's University of Belfast United Kingdom Computer Communications and Networks Group Department of Computer Science and Engineering Southeast University China

Packet scheduling is an essential element of any QoS enabled packet-switched network. (QoS provisioning and packet scheduling play important roles in present and future Internet applications.) In terms of packet fair queueing, worst case fair WFQ (WF2Q) is better than weighted fair queueing (WFQ) in that it can provide a bounded worst-case fairness index (WFI). The delay property of these two queueing schemes are studied. To do this, the delay index (DI) and the worst-case delay index (WDI) are defined to measure the discrepancy between the delay using these queueing schemes and that obtained using generalised processor sharing (GPS). Simulations show that in some circumstances WF2Q has higher DI than that using WFQ. The reason why WF2Q sometimes experiences higher DI is analysed, and based on this, an adaptive packet queueing algorithm termed delay-optimised WF2Q (DO-WF2Q) is proposed. This algorithm aims to improve the delay index (DI) while maintaining the WFI bound provided by WF2Q. Verifications and simulations show that DO-WF2Q can reduce the DI while maintaining the WFI bound, and at the same time retaining the same complexity as WF2Q. © IEE, 2005.

关键词： Packet networks

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Scalable Telehealth Services to Combat Novel Coronavirus (COVID-19) Pandemic

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SN computer Science 2021年第1期2卷 18页

作者： Ullah, Shah Muhammad Azmat Islam, Md. Milon Mahmud, Saifuddin Nooruddin, Sheikh Raju, S. M. Taslim Uddin Haque, Md. Rezwanul Department of Electronics and Communication Engineering Khulna University of Engineering & Technology Khulna 9203 Bangladesh Department of Computer Science and Engineering Khulna University of Engineering & Technology Khulna 9203 Bangladesh Advanced Telerobotics Research Lab Department of Computer Science Kent State University Kent OH United States

An ongoing pandemic, the novel coronavirus disease 2019 (COVID-19) is threatening the nations of the world regardless of health infrastructure conditions. In the age of digital electronic information and telecommunication technology, scalable telehealth services are gaining immense importance by helping to maintain social distances while providing necessary healthcare services. This paper aims to review the various types of scalable telehealth services used to support patients infected by COVID-19 and other diseases during this pandemic. Recently published research papers collected from various sources such as Google Scholar, ResearchGate, PubMed, Scopus, and IEEE Xplore databases using the terms “Telehealth”, “Coronavirus”, “Scalable” and “COVID-19” are reviewed. The input data and relevant reports for the analysis and assessment of the various aspects of telehealth technology in the COVID-19 pandemic are taken from official websites. We described the available telehealth systems based on their communication media such as mobile networks, social media, and software based models throughout the review. A comparative analysis among the reviewed systems along with necessary challenges and possible future directions are also drawn for the proper selection of affordable technologies. The usage of scalable telehealth systems improves the quality of the healthcare system and also reduces the infection rate while keeping both patients and doctors safe during the pandemic. © 2021, Springer Nature Singapore Pte Ltd.

关键词： COVID-19 Mobile network Social media Software Telehealth Telemedicine

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A multi-modal human machine interface for controlling a smart wheelchair 7

A multi-modal human machine interface for controlling a smar...

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7th IEEE Conference on Systems, Process and Control, ICSPC 2019

作者： Mahmud, Saifuddin Lin, Xiangxu Kim, Jong-Hoon Iqbal, Hasib Rahat-Uz-Zaman, M.D. Reza, Sakib Rahman, M. Asifur Advanced Telerobotics Research Lab Computer Science Kent State University KentOH44240 United States Khulna University of Engineering Technology Dept. of Computer Science and Engineering Khulna9203 Bangladesh

ISBN: (纸本)9781728118260

As the number of disabled people all over the world is increasing very fast, the role of an electric wheelchair is becoming crucial to improve the mobility for them. Independent mobility is a vital aspect of self-respect and plays an important role in the life of a disabled person. The smart wheelchair is an endeavor to provide an self-supporting mobility to those people who are not able to move freely. Typical electric powered wheelchairs are usually controlled by the traditional joysticks which cannot fulfill the needs of a person who has motor disabilities and some specific types of disabilities like paralysis who can only move their eyes. This paper aims to develop a multi-modal human machine interface for the larger domain of disabled persons to control the wheelchair efficiently. The interface comprises joystick, smart hand-glove, head movement tracker and eye tracker. The system presented in this paper can support a wide variety of users with different types of disabilities. © 2019 IEEE.

关键词： Disabled persons

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Can We Half the Work with Double Results: Rethinking Machine Learning Algorithms for Network Intrusion Detection System 9

Can We Half the Work with Double Results: Rethinking Machine...

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9th International Conference on advanced Cloud and Big Data, CBD 2021

作者： Li, Shuren Lu, Yifei Li, Jingqi Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing210096 China State Key Lab of Mathematical Engineering and Advanced Computing Wuxi214215 China

ISBN: (纸本)9781665407458

Machine Learning algorithms have been wildly applied in the intrusion detection system(IDS). However, in the IoT environment where the resources are limited and the flow data is of huge amount, we need more efficient and effective ML algorithms to train the detection models. Aiming to have comprehensive performance indicators of the ML algorithms, we compared 15 machine learning for both binary classification and Multi-classification under the criterion of IoT traffic circumstance by indicators in temporal dimension and spatial dimension. We finally suggested using non-linear algorithms, especially tree algorithms training or retraining models to identify malicious network traffic in the IoT IDS. © 2022 IEEE.

关键词： Machine learning

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A Defect Detection Method Based on Improved Mask R-CNN for Wafer Maps 4

A Defect Detection Method Based on Improved Mask R-CNN for W...

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4th International Conference on computer Network, Electronic and Automation, ICCNEA 2021

作者： Li, Yang Wang, Jianguo School Of Computer Science And Engineering Xian Technological University Xian China State And Provincial Joint Engineering Lab. Of Advanced Network Monitoring And Control Xian China

ISBN: (纸本)9781665444866

Pattern recognition of defects in wafer drawing is very important to determine the root cause of production defects, which can provide insights for the production improvement of wafer plants. In wafer manufacturing process, there will be mixed defects, detection of mixed defects is much more complex. Deep learning method has become a good choice to solve the problem of complex pattern recognition. In this paper, an improved Mask R-CNN model for wafer defect map is proposed. The ability of small target recognition is improved by fusing residual network and feature pyramid network, and the target feature can be fully extracted in the shallow model, so that the efficiency of feature extraction is improved. Secondly, an improved non-maximum suppression (NMS) algorithm is added to solve the error detection problem caused by traditional algorithms. The experimental results show that the improved Mask R-CNN model is superior to the conventional model, and has better recognition effect for small targets and shallow models. Secondly, the improved NMS algorithm is added to improve the detection precision. © 2021 IEEE.

关键词： Defects

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Tailor : Datacenter Load Balancing for Accelerating Distributed Deep Learning 9

Tailor : Datacenter Load Balancing for Accelerating Distribu...

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9th International Conference on advanced Cloud and Big Data, CBD 2021

作者： Xu, Zhengzhi Lu, Yifei Li, Jingqi Ma, Xu Qian, Lei Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing210096 China State Key Lab of Mathematical Engineering and Advanced Computing Wuxi214215 China

ISBN: (纸本)9781665407458

Accelerating Distributed Deep Learning draws increasing attention recently. Existing solutions like gradient compression, pipelining computation/communication, flow scheduling based on gradient disparities, neglect load balancing for Distributed Deep Learning (DDL) flows in DataCenter Network. In this paper, we review the PS traffic pattern in usual DDL training and propose that minimizing tail Flow Completion Time (FCT) of DDL flows is objective for DDL traffic Load Balancing. Besides, traffics of DDL differ from traditional DataCenter in temporal and spatial distribution. Current DCN Load Balancing become unadaptable to optimization requirements of DDL traffic, so we propose Tailor, a brand new load balancing scheme for DDL traffics training in DCN. Tailor is a solution without complex switch modification that sufficiently leverages the known parameter amount of DDL flows to discover congestion and reroutes by ECMP-like hash function to compensate bandwidth for slower flows. With large-scale simulation, we validate the effectiveness of Tailor. Tailor behaves well in both symmetric and asymmetric topology. It reduces time cost of DDL training by decreasing about 20-30% tail FCT than other load balancing mechanisms. © 2022 IEEE.

关键词： Deep learning

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CAD-IDS: A Cooperative Adaptive Distributed Intrusion Detection System with Fog Computing 25

CAD-IDS: A Cooperative Adaptive Distributed Intrusion Detect...

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25th IEEE International Conference on computer Supported Cooperative Work in Design, CSCWD 2022

ISBN: (纸本)9781665405270

Nowadays, the IoT (internet of things) botnet has become a huge threat to network security. In response to this threat, we present a cooperative adaptive network intrusion detection system (IDS) framework with fog computing. The core part is cooperation detection architecture based on online adaptive machine learning algorithms. Our CAD-IDS aims to decrease the new attack detection time for all the IoT nodes and reduce the complexity of the cooperative IDS framework. The results of the experiment indicate that our CAD-IDS can detect IoT attacks efficiently and timely. Our ML code is available in https://***/LiQianchang/CAD-IDS-ML-Code. © 2022 IEEE.

关键词： Internet of things

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BOBBLE: A Mixed Routing-Granularity Distributed Load Balancing for Data Center Networks 23

BOBBLE: A Mixed Routing-Granularity Distributed Load Balanci...

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23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Xu, Zhengzhi Lu, Yifei Ma, Xu School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210096 China State Key Lab of Mathematical Engineering and Advanced Computing Wuxi214215 China

ISBN: (纸本)9781665494571

In current Datacenter Networks (DCNs), Equal-Cost Multipath (ECMP) is a default load balancing scheme. However, using ECMP may result in rapid growth of Flow Completion Time (FCT) due to its well-known drawbacks. In order to solve the problem of ECMP, load balancing schemes with per-packet granularity (such as RPS) and per-flowlet granularity (such as LetFlow) are proposed. These two different granularities have their own features, but there's no existing load balancing considering both their advantages. In this paper, we mix per-flowlet and per-packet in scheduling decisions and introduce the potential performance bottleneck in mixed granularities load balancing. Based on this idea, we propose a hybrid scheme for load balancing, referred to as BOBBLE. The key idea of BOBBLE is to distinguish elephant and mouse flows and schedule them with different granularity. We evaluate BOBBLE in simulations with NS-3. Experiment shows that BOBBLE slightly sacrifices elephant flows FCT but it is worthy because our results demonstrate that BOBBLE is a good trade-off which outperforms RPS and LetFlow in mouse flows FCT in both symmetric and asymmetric topology. © 2021 IEEE.

关键词： Data centers Network topology Smart cities Load management Routing Mice computer networks

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