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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Keya Hu Ren-Jie Dai Wen-Tao Chen Hao-Long Yin Bao-Liang Lu Wei-Long Zheng Department of Computer Science and Engineering Shanghai Jiao Tong University School of Software Engineering Tongji University RuiJin-Mihoyo Laboratory Clinical Neuroscience Center RuiJin Hospital Shanghai Jiao Tong University School of Medicine

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Self-supervised learning provides an effective approach to leverage a large amount of unlabeled data. Numerous previous studies have indicated that applying self-supervision to physiological signals can yield better representations of the signals. In the paper, we aim to apply this method to the crucial field of emotion recognition. We perform the experiment with several state-of-the-art contrastive self-supervised methods to explore their effectiveness in pre-training feature encoders on raw electroencephalography (EEG) signals and fine-tuning the pre-trained encoders on the downstream emotion classification tasks. We attempt to vary the proportion of labeled data used during fine-tuning and find that the improvement from self-supervised methods is more pronounced when the proportion of labeled data is small. Additionally, we explore the transferability of the feature encoders pre-trained on various datasets and observe that most self-supervised methods exhibit a certain degree of transferability. Methods that effectively utilize the temporal information in EEG signals show superior stability, accuracy, and transferability.

关键词： Training Representation learning Emotion recognition Accuracy Time series analysis Training data Feature extraction Electroencephalography Physiology engineering in medicine and biology

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Gender Recognition using EEG during Mobile Game Play

Gender Recognition using EEG during Mobile Game Play

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2021 International Conference on Information Technology, ICIT 2021

作者： Fatima, Bushra Raheel, Aasim Arsalan, Aamir Majid, Muhammad Ehatisham-Ul-Haq, Muhammad Anwar, Syed Muhammad University of Engineering and Technology Department of Computer Engineering Taxila47050 Pakistan Sino-Pak Center for Artificial Intelligence PAF-IAST Haripur22620 Pakistan University of Engineering and Technology Department of Software Engineering Taxila47050 Pakistan

ISBN: (纸本)9781665428705

In recent years, due to an exponential increase in mobile game users, automatic recognition of personal traits i.e., gender and user identity is gaining significance. Personal trait recognition also plays a vital role in information security. Traditional approaches for personal trait recognition, including vision and voice-based schemes, are subjected to privacy constraints. To address these challenges, physiological signals such as electroencephalogram (EEG) and electrocardiogram have been utilized in information security for bio-metric and personal attribute identification. Herein, we propose a new technique for EEG-based gender recognition during mobile game play. Towards this, EEG data of 38 users are recorded using the Muse headband while playing a mobile game named Traffic Racer. Different time and frequency-domain features are extracted from the acquired EEG data. Three classification algorithms, i.e., K-nearest neighbor (KNN), random forest, and the Naive bayes, are used to train and validate the proposed model. In particular, KNN achieved an accuracy of up to 97.36% in gender recognition, which shows the efficacy of the proposed approach when compared with other techniques. © 2021 IEEE.

关键词： Electroencephalography

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Adaptive sampling for efficient softmax approximation 24

Adaptive sampling for efficient softmax approximation

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Tavor Z. Baharav Ryan Kang Colin Sullivan Mo Tiwari Eric Luxenberg David Tse Mert Pilanci Eric and Wendy Schmidt Center Broad Institute Cambridge MA Department of Computer Science Stanford University Stanford CA AI Division Software Engineering Institute Pittsburgh PA Department of Computer Science Stanford University Stanford CA Gridmatic Cupertino CA Department of Electrical Engineering Stanford University Stanford CA

ISBN: (纸本)9798331314385

The softmax function is ubiquitous in machine learning and optimization applications. Computing the full softmax evaluation of a matrix-vector product can be computationally expensive in high-dimensional settings. In many applications, however, it is sufficient to calculate only the top few outputs of the softmax function. In this work, we present an algorithm, dubbed AdaptiveSoftmax, that adaptively computes the top k softmax values more efficiently than the full softmax computation, with probabilistic guarantees. We demonstrate the sample efficiency improvements afforded by AdaptiveSoftmax on real and synthetic data to corroborate our theoretical results. AdaptiveSoftmax yields > 10x gain over full softmax computation on most datasets, yielding up to 30x improvement for Mistral7B evaluated on the Wikitext dataset. The adaptive method we propose for estimating the partition function (the softmax denominator) is of independent interest and can be used in other applications such as kernel density estimation.

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Investigating the Use of Email Application in Illiterate and Semi-Illiterate Population

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computers, Materials & Continua 2020年第3期62卷 1473-1486页

作者： Sadeeq Jan Imran Maqsood Salman Ahmed Zahid Wadud Iftikhar Ahmad National Center for Cyber Security-UETP Department of CS&ITUniversity of Engineering&TechnologyPeshawarPakistan Department of Computer Software Engineering University of Engineering&TechnologyMardanPakistan Department of Computer Systems Engineering University of Engineering&TechnologyPeshawarPakistan 不详

The use of electronic communication has been significantly increased over the last few *** is one of the most well-known means of electronic *** email applications are widely used by a large population;however,illiterate and semi-illiterate people face challenges in using them.A major population of Pakistan is illiterate that has little or no practice of computer *** this paper,we investigate the challenges of using email applications by illiterate and semi-illiterate *** addition,we also propose a solution by developing an application tailored to the needs of illiterate/semi-illiterate *** shows that illiterate people are good at learning the designs that convey information with pictures instead of text-only,and focus more on one object/action at a *** proposed solution is based on designing user interfaces that consist of icons and vocal/audio instructions instead of ***,we use background voice/audio which is more helpful than flooding a picture with a lot of *** tested our application using a large number of users with various skill levels(from no computer knowledge to experts).Our results of the usability tests indicate that the application can be used by illiterate people without any training or third-party’s help.

关键词： Illiterate semi-illiterate email usability user interfaces

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Technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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Early Detection of Acute Radiation Dermatitis (ARD) Using In Vivo Optical Coherence Tomography (OCT) Images

Early Detection of Acute Radiation Dermatitis (ARD) Using In...

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Optical Coherence Tomography, OCT 2022

作者： Photiou, Christos Strouthos, Iosif Cloconi, Constantina Kios Research and Innovation Center of Excellence Department of Electrical and Computer Engineering University of Cyprus 1 Panepistimiou Av. Nicosia1678 Cyprus Department of Radiation Oncology German Oncology Center 1 Nikis Avenue Agios Athanasios Limassol4108 Cyprus

The majority of radiation therapy patients experience some form of ARD. This study proposes novel biomarkers using OCT images for early detection of ARD. Normal skin vs. Early ARD separated with an accuracy of 88.3%. ... 详细信息

ISBN: (纸本)9781557528209

关键词： Optical tomography

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Security and Localization of Cyber Attacks in Finite State Machines

Security and Localization of Cyber Attacks in Finite State M...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Bushra Bushra Elena De Santis Giordano Pola Dept. of Electrical and Information Engineering Polytechnic of Bari (DAuSy Administrative Headquarters) Bari Italy Department of Information Engineering Computer Science and Mathematics Center of Excellence DEWS University of L’Aquila L’Aquila Italy

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

The inspiration for this work is the rising possibility of cyber attacks, making security a critical problem in many applications. This work addresses two key problems related to the security of a Finite State Machine (FSM): attack detection and localization. A composition of nominal plant and the attacker FSM is developed to analyze different security aspects, under actuator attacks, and necessary and sufficient conditions are developed for attack detection. In some cases, the intruder can make replacements in the sensor or actuator channel. From the security perspective, it is important to identify the attacked channel. The term localization is used, to detect the attacked channel, and necessary and sufficient conditions are provided that ensure localization.

关键词： Location awareness Actuators Sufficient conditions Analytical models computer aided software engineering Automation Automata Security Cyberattack

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Nusec and Midesec: Datasets for Histopathological Image Analysis

SSRN

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SSRN 2024年

作者： Nemati, Nooshin Samet, Refik Sak, Serpil Hancer, Emrah Kirmizi, Bilge Ayca Yildirim, Zeynep Traoré, Mohamed Department of Computer Engineering Ankara University Ankara06830 Turkey Center for Data Science and Artificial Intelligence School of Engineering and Computer Science Victoria University of Wellington Wellington6140 New Zealand Department of Software Engineering Mehmet Akif Ersoy University Burdur15039 Turkey Department of Pathology Faculty of Medicine Ankara University Ankara06080 Turkey

Hematoxylin and Eosin (H&E) staining stands as the gold standard protocol for the preparationof histopathology tissue samples in breast cancer research. This staining technique facilitates theidentification and differentiation of various cell types within the tissue, providing crucial informationfor pathologists. While deep learning algorithms have shown promise in automating the analysis ofH&E images, their effectiveness relies on extensive datasets for training. Unfortunately, there is ascarcity of publicly available datasets specifically tailored for nuclei and mitosis detection. To addressthis gap, this paper introduces two publicly available datasets, namely NuSeC (Nuclei Segmentationand Classification) and MiDeSeC (Mitosis Detection, Segmentation, and Classification) to serve asvaluable resources for building deep learning models for histopathological image analysis. The NuSeCdataset comprises 75 images for training and an additional 25 images for testing, encompassing around6000 nuclei structures, and the MiDeSeC dataset involves 35 training and 15 test image sets with morethan 500 mitoses. In both datasets, the QuPath tool as a pixel-level annotator is utilized to generatemask images. Moreover, we design two deep learning-based methodologies to conduct experimentalanalysis on the NuSeC and MiDeSeC datasets. The results indicate the potential to achieve substantialperformance on these datasets, facilitating the construction of new models or analysis of existing ones © 2024, The Authors. All rights reserved.

关键词： Classification (of information)

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A Hybrid Approach for Enhancing Line Parameter Estimation in Power Systems

A Hybrid Approach for Enhancing Line Parameter Estimation in...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Markos Asprou Christos G. Panayiotou Andreas Stavrou KIOS Research and Innovation Center of Excellence and Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Transmission System Owner Electricity Authority of Cyprus Nicosia Cyprus

ISBN: (数字)9798350390421

ISBN: (纸本)9798350390438

Accurate modeling of power systems is crucial for various control center applications. One of the key components in a power system model is the transmission lines. The line model includes parameters such as series impedance and shunt admittance, which are typically assumed to be time-invariant. However, these parameters vary based on the ambient and operating conditions of the system. Therefore, it is essential for the different monitoring and protection applications of the power system to have an accurate visualization of the line parameter variance throughout the day. In this context, this paper develops a hybrid line parameter estimation scheme that makes use of the available Phasor Measurement Unit (PMUs) measurements and Neural Network (NN) estimations to calculate the series line parameters of the transmission lines. The developed scheme was tested in the IEEE 14-bus system under realistic ambient and operating conditions, showcasing its practical applicability and enhanced accuracy.

关键词： Temperature measurement Accuracy Power transmission lines Artificial neural networks Transmission line measurements Phasor measurement units Real-time systems State estimation Protection Monitoring

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Sparrow: Flexible Memory Deduplication in Android Systems with Similar-Page Awareness

Sparrow: Flexible Memory Deduplication in Android Systems wi...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Guangyu Wei Changlong Li Rui Xu Qingfeng Zhuge Edwin H.-M. Sha School of Computer Science and Technology East China Normal University MoE Engineering Research Center of Hardware/Software Co-Design Technology and Application Department of Computer Science City University of Hong Kong

ISBN: (数字)9783981926385

ISBN: (纸本)9798350348606

Mobile devices have become ubiquitous in daily life. In contrast to traditional servers, mobile devices suffer from limited memory resources, leading to a significant degradation in the user experience. This paper demonstrates that the primary cause of memory consumption lies in anonymous pages associated with application heaps. Existing schemes are ineffective in deduplicating these pages due to the limited occurrence of the same anonymous pages. This paper presents Sparrow, a similar-page aware deduplication solution for mobile systems. Sparrow shows that memory pages still have the potential to deduplicate, even though the same pages are rare. An interesting observation inspires this, that is, a high number of pages having the partially-same contents. We have implemented Sparrow on real-life smartphones. Experimental results indicate that 30.45% more space can be saved with Sparrow.

关键词： Degradation Memory management User experience Mobile applications Servers Smart phones

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