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8th IEEE Global Conference on Consumer Electronics, GCCE 2019

作者： Kawanaka, Masaki Une, Masakazu Miyazaki, Ryoichi National Institute of Technology Tokuyama College Dept. of Computer Science and Electronic Engineering Yamaguchi Japan Graduate School of Systems and Information Engineering University of Tsukuba Dept. of Computer Science Ibaraki Japan

ISBN: (纸本)9781728135755

Recently, various noise spectrum estimation techniques have been proposed. The problem of the conventional techniques has the underestimation of the noise spectrum due to the excessive guess of the speech presence probability. Therefore, we propose a highly accurate noise spectrum estimation method to solve this problem by applying a sigmoid or softplus functions to the speech presence probability. From the evaluation experiment, we confirm that the proposed methods can achieve higher noise estimation accuracy than conventional techniques. © 2019 IEEE.

关键词： Probability

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Security of Enhancement of Adder in Stream Cipher System 1

Security of Enhancement of Adder in Stream Cipher System

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1st International Conference information Technology to Enhance E-Learning and other Application, IT-ELA 2020

作者： Hayder, Israa M. Younis, Hussain A. Abed, Issa Ahmed Younis, Hameed A.K. Qurna Technique Institute Stu Dept. of Computer Systems Techniques Basrah Iraq Universiti Sains Malaysi 11800 Usm College of Education for Women School of Computer Sciences Penang Malaysia Southern Technical University Engineering Technical College Basrah Iraq University of Basrah College of Computer Science and Information Technology Basrah Iraq

ISBN: (纸本)9781728182339

The strength of the encryption system depends on the power of the key generator that produces a pseudorandom stream. The generator generates a pseudorandom sequence so passes several tests. The non-linear flow coding system that relies on the Adder function has several unwanted vulnerabilities. It leads to failure to face randomness tests and relative success in the correlation attack. In this paper, the Adder function was developed by adding a third offset register to improve its ability to bypass randomness tests. In addition to increasing the non-linear complexity of the generated chain, it is resistant to breaking the code using a link attack. Many sequences were applied to the improved Adder system, and good results were obtained. © 2020 IEEE.

关键词： Adder generator Correlation attack Non-linear-feedback shift registers Stream cipher

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IEEE ICCI*CC Series in Year 20: Latest Advances in Cognitive Computing (Plenary Panel Report-II) 20

IEEE ICCI*CC Series in Year 20: Latest Advances in Cognitive...

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20th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2021

作者： Kinsner, Witold Zhu, Haibin Baciu, George Luo, Guiming Rubio, Fernando Sui, Jie Huang, Runhe Hiraishi, Hironori Peng, Jun Chen, Liang Univ. of Manitoba FI2CICC Dept of ECE Winnipeg Canada Nipissing University FI2CICC ON Canada Hong Kong Polytechnic University FI2CICC Dept. of Computing Hong Kong Tsinghua University FI2CICC Software Institute Beijing China Complutense Univ. of Madrid FI2CICC Dept. of Computer Systems and Computation Spain Aberdeen University FI2CICC Aberdeen United Kingdom Hosei University FI2CICC Faculty of Computer and Information Sciences Japan Ashikaga University Faculty of Engineering Tochigi326-8558 Japan Chongqing Univ. of Science and Technology FI2CICC School of AI Chongqing China Univ. of Northern British Columbia Dept. of Computer Science BC Canada

ISBN: (纸本)9781665421195

Cognitive Computing (CC) is a contemporary field of fundamental intelligence theories and general AI technologies triggered by the transdisciplinary development in intelligence, computer, brain, knowledge, cognitive, robotic, and cybernetic sciences for engineering implementations. This paper presents a summary of the plenary panel (Part II) on the theoretical foundations of CI/CC and recent breakthroughs in AI engineering reported in the 20th IEEE International ICCI*CC Conference (ICCI*CC'21). The latest advances in CI and CC towards general AI are presented by twenty-Two distinguished panelists. Strategic AI engineering applications in CI, CC, and cognitive systems.are elaborated for abstract intelligence, cognitive robots, autonomous systems. intelligent vehicles, and safety-And-mission-critical systems. © 2021 IEEE.

关键词： Cognitive systems

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LETHE: A Digital Intervention for Cognitive Decline*

LETHE: A Digital Intervention for Cognitive Decline*

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

作者： Vasileios S. Loukas Thomas Kassiotis Ignacio Lamata Martinez Lefteris Koumakis Jeroen Bruinsma Roberto Pasciuti Monica Balatresi Ville Tenhunen Adam Fiakkas Lelia Ataliani Georgia S. Karanasiou Manolis Tsiknakis Hannes Hilberger Markus Bödenler Bianca Schnalzer Simone Huber Mattia Pirani Matteo Colombo Sten Hanke Dimitrios I. Fotiadis Dept. of Materials Science and Engineering Unit of Medical Technology and Intelligent Information Systems University of Ioannina Ioannina Greece Biomedical Research Institute FORTH-BRI Ioannina Greece Computational BioMedicine Laboratory Institute of Computer Science FORTH-ICS Heraklion Greece EGI Foundation Amsterdam The Netherlands Dept. of Health Promotion Care and Public Health Research Institute Maastricht University Maastricht The Netherlands ExtraRed Innovations Pisa Italy Infotrend Innovations Co. Ltd Nicosia Cyprus eHealth Institute FH Joanneum University of Applied Sciences Graz Austria Innovation2Grow I2G Bologna Italy

Dementia is the main cause of disability in elderly populations. It has been shown that the risk factors of dementia are a mixture of pathological, lifestyle and heritable factors, with some of those being provably modifiable. Early diagnosis of dementia and approaches to slow down its evolution are currently the most prominent management methodologies due to lack of a cure. For that reason, a plethora of home-based assistive technologies for dementia management do exist, with most of them focusing on the improvement of memory and thinking. The main objective of LETHE is prevention in the whole spectrum of cognitive decline in the elderly population at risk reaching from asymptomatic to subjective or mild cognitive impairment to prodromal Dementia. LETHE will provide a Big Data collection platform and analysis system, that will allow prevention, personalized risk detection and intervention on cognitive decline. Through the subsequent 2-year clinical trial, the LETHE system, as well as the respective knowledge gained will be evaluated and validated. The scope of the current paper is to introduce the LETHE study and its respective novel platform as a holistic approach to multidomain lifestyle intervention trial studies. The present work depicts the architectural perspective and extends beyond state-of-the-art guidelines and approaches to health management systems.and cloud platform *** Relevance — Patient Management systems.as well as lifestyle management platforms have significant clinical relevance as they allow for remote and continuous monitoring of patients' health status. LETHE aims to improve patient outcomes by providing predictive models for cognitive decline and patient adherence to the multimodal lifestyle intervention, enabling prompt and appropriate medical decisions.

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A Data logger for educational purposes of a laboratory chemical reactor: an IoT approach

A Data logger for educational purposes of a laboratory chemi...

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Electrical, computer, Communications and Mechatronics engineering (ICECCME), International Conference on

作者： José Lima Thadeu Brito Olga Ferreira Maria J. Afonso Vítor H. Pinto José A. Carvalho Paulo Costa Research Centre in Digitalization and Intelligent Robotics (CeDRI) Instituto Politécnico de Bragança Bragança Portugal Laboratório Para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC) Instituto Politécnico de Bragança Bragança Portugal Centre for Robotic in Industry and Intelligent Systems Institute for Systems and Computer Engineering Technology and Science (INESC-TEC) Porto Portugal CeDRI SusTEC INESC-TEC Faculty of Engineering of University of Porto (FEUP) Porto Portugal SusTEC ESTiG Instituto Politécnico de Bragança Bragança Portugal ARISE & ECE Dept. Research Center for Systems and Technologies (SYSTEC) FEUP CeDRI SusTEC INESC-TEC FEUP

This paper presents the development of an acquisition system and data logger from an existing set of three continuous stirred-tank reactors in series. The reactors are currently used in chemical engineering educational laboratories to perform kinetic and tracer experiments. In this sense, to accomplish the store data process, the volumetric flow rate and the concentration of tracer, reactants and/or products of the reaction must be acquired as a function of time. In the original experimental setup, only the signal conditioning system was operational, while the acquisition, visualization, and control systems.were obsolete and damaged. Thus, a new system composed of an interface and real-time acquisition data is proposed alongside preserving the main reactor structure. A graphical user interface and the automation of the various actuators were developed based on worldwide usage and low cost, respectively. This system, based on a common 8-bit microcontroller and an application developed in Lazarus, allows the storage of the acquired data in a time-series database. In this way, students can analyze the results later or in real time. Moreover, remote access allows controlling the reactor and getting data by the Internet of Things (IoT) resources. Additionally, the proposed system using IoT allows data to be shared with the community as a dataset.

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Learning Personal Conscientiousness from Footprints in E-Learning systems

Learning Personal Conscientiousness from Footprints in E-Lea...

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IEEE International Conference on Data Mining (ICDM)

作者： Lo Pang-Yun Ting Shan-Yun Teng Kun-Ta Chuang Ee-Peng Lim Dept. of Computer Science and Information Engineering National Cheng Kung University Taiwan School of Information Systems Singapore Management University Singapore

ISBN: (数字)9781728183169

ISBN: (纸本)9781728183176

Personality inference has received widespread attention for its potential to infer psychological well being, job satisfaction, romantic relationship success, and professional performance. In this research, we focus on Conscientiousness, one of the well studied Big Five personality traits, which determines if a person is self-disciplined, organized, and hard-working. Research has shown that Conscientiousness is related to a person's academic and workplace success. For an expert to evaluate a person's Conscientiousness, long-term observation of the person's behavior at work place or at home is usually required. To reduce this evaluation effort as well as to cope with the increasing trend of human behavior turning digital, there is a need to conduct the evaluation using digital traces of human behavior. In this paper, we propose a novel framework, called HAPE, to automatically infer an individual's Conscientiousness scores using his/her behavioral data in an E-learning system. We first determine how users learn in the E-learning system, and design a novel Pattern Relational Graph Embedding method to learn the representations of users, their learning actions, and learning situations. The interaction between users, learning actions and situations characterizes the learning style of a user. Through experimental studies on real data, we demonstrate that HAPE framework outperforms the baseline methods in the Conscientiousness inference task.

关键词： Electronic learning Employment Psychology Turning Market research Robustness Task analysis

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Quaternion Harris For Multispectral Keypoint Detection

Quaternion Harris For Multispectral Keypoint Detection

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IEEE International Conference on Image Processing

作者： Giorgos Sfikas Dimosthenis Ioannidis Dimitrios Tzovaras Dept. of Computer Science & Engineering University of Ioannina Greece Centre for Research & Technology Information Technologies Institute Thessaloniki Greece

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

We present a new keypoint detection method that generalizes Harris corners for multispectral images by considering the input as a quaternionic matrix. Standard keypoint detectors run on scalar-valued inputs, neglecting input multimodality and potentially missing highly distinctive features. The proposed detector uses information from all channel inputs by defining a quaternionic autocorrelation matrix that possesses quaternionic eigenvectors and real eigenvalues, for the computation of which channel cross-correlations are also taken into account. We have tested the proposed detector on a variety of multispectral images (color, near-infrared), where we have validated its usefulness.

关键词： Detectors Quaternions Correlation Eigenvalues and eigenfunctions Image color analysis Standards Visualization

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The Impact and Potential of Block chain Applications Based on IoT

The Impact and Potential of Block chain Applications Based o...

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Simulation, Automation & Smart Manufacturing (SASM), International Conference on

作者： Sandeep Srivastava Anurag Aeron Thulasi Bikku Manisha Kaur Varsha Satish Rupraoji Billewar GL Bajaj of Institute of Technology &#x0026 Management Greater Noida India Dept. of Computer Science and Engineering DIT University Dehradun India Dept. of Computer Science and Engineering Vignan&#x2019 s Nirula Institute of Technology and Science for Women Guntur Andhra Pradesh India Department of Computer Science and Engineering CT Group of Institute (CTIEMT) Shahpur Jalandhar India I.K.Gujral Punjab Technical University Jalandhar India Information Technology / Systems Vivekananda Institute of Management Studies and Research Chembur (E) Mumbai Maharashtra India

ISBN: (数字)9781665403573

ISBN: (纸本)9781665447768

The Block chain is a course of action of recording information to such an extent that makes it irritating or hard to alter, slash, or swindle the system. In blockchain decentralized amend the proceedings that could be used to indicate, join up also send wide scope of agreement to various social affairs in association. The scope of block chain applications stretches out to open and public administrations including wellbeing, financial, automotive, Internet of Things (IoT) and risk management. This paper presents a thorough outline on blockchain innovation. Lately, block chain innovation has become extremely stylish and infiltrated various areas, generally because of the crypto currencies determination of rotator for the particular sort of suspension needs some fundamental information.

关键词： Technological innovation Education Blockchains Recording Cryptocurrency Internet of Things Risk management

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Cooperative Convolutional Neural Network Deployment over Mobile Networks

Cooperative Convolutional Neural Network Deployment over Mob...

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IEEE International Conference on Communications (ICC)

作者： Chia-Chun Hsu Chung-Kai Yang Jian-Jhih Kuo Wen-Tsuen Chen Jang-Ping Sheu Dept. of Information Systems and Applications National Tsing Hua University Hsinchu Taiwan Dept. of Computer Science National Tsing Hua University Hsinchu Taiwan Dept. of Computer Science & Information Engineering National Chung Cheng University Chiayi Taiwan

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

Inference acceleration has drawn much attention to cope with the real-time requirement of artificial intelligence (AI) applications. To this end, model partition for Deep Neural Networks (DNN) has been proposed to utilize the parallel and distributed computing units. However, the previous works focus on the load balancing among servers but may overlook the interplay between the computing and communication. This issue makes the existing approaches less efficient especially in mobile edge networks at which smart devices usually with limited computing capacity have to offload the tasks via limited bandwidth capacity to nearby servers. In this paper, therefore, we innovate a new system and formulate a new optimization problem, CONVENE, to minimize the completion time of inference for the smart devices with one or more antennas. To explore the intrinsic properties, we first study CONVENE with Single Antenna and derive an algorithm termed THREAD-SA to foster the optimum solution. Then, an extension, THREAD, is proposed to subtly utilize multiple antennas to further reduce completion time. Simulation results manifest that our algorithm outperforms others by 100%.

关键词： Servers Smart devices Computational modeling Antennas Data models Prefetching Data transfer

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Computational Approaches to Explainable Artificial Intelligence: Advances Intheory, Applications and Trends

SSRN

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SSRN 2023年

作者： Górriz, Juan Manuel Álvarez-Illán, I. Álvarez-Marquina, A. Arco, J.E. Atzmueller, M. Ballarini, F. Barakova, E. Bologna, G. Bonomini, P. Castellanos-Dominguez, G. Castillo-Barnes, D. Cho, S.B. Contreras, R. Cuadra, J.M. Domínguez, E. Domínguez-Mateos, F. Duro, R.J. Elizondo, D. Fernández-Caballero, A. Fernandez-Jover, E. Formoso, M.A. Gallego-Molina, N.J. Gamazo, J. García González, J. Garcia-Rodriguez, J. Garre, C. Garrigós, J. Gómez-Rodellar, A. Gómez-Vilda, P. Graña, M. Guerrero-Rodriguez, B. Hendrikse, S.C.F. Jimenez-Mesa, C. Jodra-Chuan, M. Julian, V. Kotz, G. Kutt, K. Leming, M. de Lope, J. Macas, B. Marrero-Aguiar, V. Martinez, J.J. Martinez-Murcia, F.J. Martínez-Tomás, R. Mekyska, J. Nalepa, G.J. Novais, P. Orellana, D. Ortiz, A. Palacios-Alonso, D. Palma, J. Pereira, A. Pinacho-Davidson, P. Pinninghoff, M.A. Ponticorvo, M. Psarrou, A. Ramírez, J. Rincón, M. Rodellar-Biarge, V. Rodríguez-Rodríguez, I. Roelofsma, P.H.M.P. Santos, J. Salas-Gonzalez, D. Salcedo-Lagos, P. Segovia, F. Shoeibi, A. Silva, M. Simic, D. Suckling, J. Treur, J. Tsanas, A. Varela, R. Wang, S.H. Wang, W. Zhang, Y.D. Zhu, H. Zhu, Z. Ferrández-Vicente, J.M. SiPBA at Data Science and Computational Intelligence Institute University of Granada Granada Spain University of Granada Granada Spain Dept. of Psychiatry University of Cambridge Cambridge United Kingdom Dept. of Communications Engineering University of Malaga Malaga Spain School of Computing and Mathematical Sciences University of Leicester Leicester United Kingdom Semantic Information Systems Group Osnabrück University Osnabrück Germany Osnabrück Germany Dept. of Electronics Computer Technology and Projects Universidad Politécnica de Cartagena Cartagena Spain Universitat Politècnica de València València Spain Institute of Applied Computer Science Jagiellonian University Kraków Poland Dept. of Information and Communication Engineering University of Murcia Murcia Spain Dept. of Computer Science and Information Technologies University of A Coruña A Coruña Spain Dept. of Computer Science University of Oviedo Oviedo Spain Buenos Aires Argentina Buenos Aires Argentina Eindhoven University of Technology Eindhoven5612 AZ Netherlands Dept. of Computer Science University of Malaga Malaga Spain De Montfort University Leicester United Kingdom Dept. of Computer Science Faculty of Engineering Universidad de Concepción Concepción Chile Neurocognition and Emotion Research Unit Albacete Research Institute of Informatics University of Castilla-La Mancha Albacete Spain Dept. of Educational Informatics Universidad de Concepción Concepción Chile Madrid Spain Dept. of Humanistic Studies University of Naples Federico II Napoli Italy Escuela Técnica Superior de Ingeniería Informática Universidad Rey Juan Carlos Campus de Móstoles Móstoles Madrid28933 Spain Neuromorphic Speech Processing Lab Center for Biomedical Technology Universidad Politécnica de Madrid Campus de Montegancedo Pozuelo de Alarcón Madrid28223 Spain Biomedical Research Networking Center in Mental Health Instituto de Salud Carlos III Madrid28016 Spain Usher Institute Faculty o

Groundbreaking advances in theoretical and applied Artificial Intelligence (AI). DL algorithms are groundedin non-linear and complex artificial neural systems.that progressively extract higher-level features from *** is frequently compared with human-level performance in real-world tasks, such as clinical diagnostics. Itis also a turning point in solving otherwise intractable problems in the design of virtual agents or robotics;orin providing novel insight into disease progress in genomics and Neuroimaging (NI), understanding humanbrain function, the automation of industrial processes based on computer vision, and so on. In this paper, themost relevant advances from the last few years in AI and several applications to neuroscience, neuroimaging,computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-ofthe-art in AI methods, models and applications within a collection of works presented at the 9th InternationalConference on the Interplay between Natural and Artificial Computation (IWINAC). The works presentedin this paper are excellent examples of new scientific discoveries made in laboratories that are successfullytransferred to real-life applications. © 2023, The Authors. All rights reserved.

关键词： Neuroimaging

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