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Convolutional Neural Network Based Deep Neural Network Model for Electrocardiogram Records Classification 23

Convolutional Neural Network Based Deep Neural Network Model...

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Proceedings of the 7th International Conference on Future Networks and Distributed Systems

作者： Ahmed Mahmood Khudhur Mohammed Hasan Alwan Qayssar Al Omairi Omar Abdulkareem Mahmood Yousif I Hammadi Mohammed Saleh Ali Muthanna Ahmed Aziz Ammar Muthanna Information Technology Department Kirkuk University Iraq Department of Communications Engineering University of Diyala Iraq Department of Computer Engineering University of Diyala Iraq Dep. of Medical Instruments Engineering Techniques Bilad Alrafidain University College Iraq Institute of Computer Technologies and Information Security Southern Federal University Russia Department of computer science Benha university Egypt and International Business Management Department Tashkent State University of Economics Uzbekistan Department of Telecommunication Networks and Data Transmission The Bonch Bruevich Saint Petersburg State University of Telecommunications Russia and Department of Applied Probability and Informatics Peoples Friendship University of Russia Russia

ISBN: (纸本)9798400709036

Сardiovascular diseases, also known as CVDs, currently rank as the primary incidence of mortality. The present approach for identifying illnesses involves the analysis of the Electrocardiogram (ECG), an electronic diagnostic device utilized to capture the rhythm of the heart. Regrettably, the process of seeking out specialists to conduct analysis on a substantial volume of electrocardiogram (ECG) data results in a significant dep.etion of medical capabilities. Hence, the utilization of deep learning algorithms for the identification of ECG characteristics has progressively gained prominence. Nevertheless, there exist certain limitations associated with these conventional approaches, which necessitate the need for manual characteristic identification, intricate models, and extensive training duration. This study presents a novel and effective approach for categorizing the five different types of heartbeats in the MIT-BIH Arrhythmia database. The proposed method involves the utilization of a 16-layer deep one-dimensional convolutional neural network, which exhibits both robustness and efficiency in its classification performance. Thus, the designed model is consisting of five-groups, first to fourth groups are the main feature extraction and mapping blocks, while the fifth group is fully connected and classification layers. The findings indicate that the model presented in this study has superior performance in terms of accuracy, precision, and F1-score. The proper classification of medical cases has a significant impact on the conservation of medical resources, hence positively influencing clinical practice. Additionally, the model training phase is characterized by its efficiency, since it does not significantly dep.ete resources.

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Security Issues and Threats Facing the Electronic Enterprise Leadership 2

Security Issues and Threats Facing the Electronic Enterprise...

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2nd International Conference on informatics, Multimedia, Cyber, and Information System, ICIMCIS 2020

作者： El-Ebiary, Yousef A. Baker Almandeel, Seita Ghanem, Waheed Ali H. M. Abu-Ulbeh, Waheeb Al-Dubai, Maged M. Mahyoub Bamansoor, Samer Faculty of Informatics and Computing UniSZA Terengganu Malaysia Faculty of Economics and Administration King Abdulaziz University Jeddah Saudi Arabia Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Malaysia Amman Arab University Cyber Security Dep. Amman Jordan Management Development Institute of Singapore Tashkent Uzbekistan Faculty of Computer and Information Technology Mediu Kuala Lumpur Malaysia

ISBN: (纸本)9781728191676

the explosion if e.-commerce businesses have seen the growth if number if the online businesses worldwide. Consumers nowadays are opted with inline business commerce which is inconsiderably inconvenience compared to traditional transactions. Deniably, e.-commerce enterprises offer more benefits, comparing to 'bricks-Andmortal' traditional enterprises, but not to be missed the issues and challenges faced by the e-commerce enterprises. This study highlighted the issues and challenges of e-commerce and a set of proposed solutions to those issues and challenges. Among the issues are trust, readiness and security. For each of the issues and challenges, proposed solutions are presented. © 2020 IEEE.

关键词： Electronic commerce

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A Load Balancing Algorithm for Resource Allocation in IEEE 802.15.4e Networks

A Load Balancing Algorithm for Resource Allocation in IEEE 8...

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2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018

作者： Kralevska, Katina Dimitrios Vergados, J. Jiang, Yuming Michalas, Angelos Dep. of Information Security and Communication Technology NTNU Norwegian University of Science and Technology Norway School of Electrical and Computer Engineering National Technical University of Athens Greece Department of Informatics Engineering Technological Education Institute of Western Macedonia Kastoria Greece

ISBN: (纸本)9781538632277

The recently created IETF 6TiSCH working group combines the high reliability and low-energy consumption of IEEE 802. 15.4e Time Slotted Channel Hopping with IPv6 for industrial Internet of Things. We propose a distributed link scheduling algorithm, called Local Voting, for 6TiSCH networks that adapts the schedule to the network conditions. The algorithm tries to equalize the link load (defined as the ratio of the queue length over the number of allocated cells) through cell reallocation. Local Voting calculates the number of cells to be added or released by the 6TiSCH Operation Sublayer 6top. Compared to a representative algorithm from the literature, Local Voting provides simultaneously high reliability and low end-to-end latency while consuming significantly less energy. Its performance has been examined and compared to On-the- fly algorithm in 6TiSCH simulator by modeling an industrial environment with 50 sensors. © 2018 IEEE.

关键词： Resource allocation

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A Load Balancing Algorithm for Resource Allocation in IEEE 802.15.4e Networks

A Load Balancing Algorithm for Resource Allocation in IEEE 8...

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IEEE International Conference on Pervasive Computing and Communications

作者： Katina Kralevska Dimitrios J. Vergados Yuming Jiang Angelos Michalas Dep. of Information Security and Communication Technology NTNU Norwegian University of Science and Technology School of Electrical and Computer Engineering National Technical University of Athens Department of Informatics Engineering Technological Education Institute of Western Macedonia Kastoria Greece

ISBN: (纸本)9781538632284

The recently created IETF 6TiSCH working group combines the high reliability and low-energy consumption of IEEE 802.15.4e Time Slotted Channel Hopping with IPv6 for industrial Internet of Things. We propose a distributed link scheduling algorithm, called Local Voting, for 6TiSCH networks that adapts the schedule to the network conditions. The algorithm tries to equalize the link load (defined as the ratio of the queue length over the number of allocated cells) through cell reallocation. Local Voting calculates the number of cells to be added or released by the 6TiSCH Operation Sublayer (6top). Compared to a representative algorithm from the literature, Local Voting provides simultaneously high reliability and low end-to-end latency while consuming significantly less energy. Its performance has been examined and compared to On-the-fly algorithm in 6TiSCH simulator by modeling an industrial environment with 50 sensors.

关键词： Schedules IEEE 802.15 Standard Scheduling algorithms Reliability Resource management Scheduling Computational modeling management of resources Scheduling algorithms Computational modeling Link Load Resource utilization Vote INSTITUTE OF ELECTRICAL AND ELECTRONIC ENGINEERS Internet of things IPv6 Load balancing

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6th international workshop on personalization approaches in learning environments (PALE 2016): Preface 24

6th international workshop on personalization approaches in ...

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24th ACM Conference on User Modeling, Adaptation and Personalisation, UMAP 2016

作者： Kravcik, Milos Boticario, Jesus G. Santos, Olga C. Bielikova, Maria Informatik 5 RWTH Aachen University Germany ADeNu Research Group Artificial Intelligence Dep. Computer Science School UNED Spain PeWe Research Group Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Slovakia

Personalization approaches in learning environments are crucial to foster effective, active, efficient, and satisfactory learning. The focus of the PALE workshop series is on the different and complementary perspectives in which personalization can be addressed in learning environments (e.g., informal, workplace, lifelong, mobile, contextualized, and self-regulated learning) and offers an opportunity to present and discuss a wide spectrum of issues and solutions. In particular, this sixth edition includes 12 papers dealing with emotional engagement, affective states, personality, deep learning and complex skills, learning analytics and recommendations, educational data mining, lifelong learning, open learner models, as well as adaptive MOOCs.

关键词： Data mining

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Evaluating flexibility degrees in optical networks

Evaluating flexibility degrees in optical networks

引用

Optical Fiber Communication Conference, OFC 2015

作者： Christodoulopoulos, Konstantinos Varvarigos, Emmanouel Manos Computer Engineering and Informatics Dep. University of Patras Computer Technology Institute and Press -Diophantus Patra Greece

We consider an IP over flexgrid network and present a joint IP routing, distance-adaptive routing and spectrum allocation formulation. We evaluate the performance of fixed- and flex-grid switches, fixed transponders, ... 详细信息

ISBN: (纸本)9781557529374

关键词： Optical fibers

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Comparison of Detailed Occupancy Profile Generative Methods to Published Standard Diversity Profiles

Comparison of Detailed Occupancy Profile Generative Methods ...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Dimosthenis Ioannidis Marina Vidaurre-Arbizu César Martín-Gómez Stelios Krinidis Anna Adamopoulou Amaia Zuazua-Ros Dimitrios Tzovaras Spiridon Likothanassis Computer Engineering and Informatics University of Patras Greece Information Technologies Institute Centre for Research and Technology Hellas Thermi-Thessaloniki Greece Dep. of Construction Building Services and Structures Universidad de Navarra Pamplona Spain

Knowledge of the actual occupancy of a building is a main research interest for several domains. Building energy performance simulation software considers occupancy through the use of diversity profiles usually contained in predesigned templates. This paper aims to explore the extent of possible discrepancies between standard predefined occupancy diversity profiles, profiles extracted by business process modelling, profiles generated from real on field occupancy measurements. Occupancy measurements are obtained utilizing a novel robust, highly accurate real-time occupancy extraction system which is based on a dep.h cameras network. Results show that the incorporation of real accurate occupancy data, the appropriate understanding of the business processes that take place in building spaces have the potential to significantly enhance current Building Performance Simulation (BPS) software tools.

关键词： Buildings Business Schedules Cameras Standards Data mining Sensors

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Time-series modeling of long-term weight self-monitoring data

Time-series modeling of long-term weight self-monitoring dat...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Elina Helander Misha Pavel Holly Jimison Ilkka Korhonen Personal Health Informatics Group Dep. of Signal Processing Tampere University of Technology Finland College of Computer and Information Science and Bouve College of Health Sciences at Northeastern University Boston MA USA

ISBN: (纸本)9781424492695

Long-term self-monitoring of weight is beneficial for weight maintenance, especially after weight loss. Connected weight scales accumulate time series information over long term and hence enable time series analysis of the data. The analysis can reveal individual patterns, provide more sensitive detection of significant weight trends, and enable more accurate and timely prediction of weight outcomes. However, long term self-weighing data has several challenges which complicate the analysis. Especially, irregular sampling, missing data, and existence of periodic (e.g. diurnal and weekly) patterns are common. In this study, we apply time series modeling approach on daily weight time series from two individuals and describe information that can be extracted from this kind of data. We study the properties of weight time series data, missing data and its link to individuals behavior, periodic patterns and weight series segmentation. Being able to understand behavior through weight data and give relevant feedback is desired to lead to positive intervention on health behaviors.

关键词： lead positive intervention health behaviors Health Behavior serial mode Lead Self Monitoring (Personality) Time series missing data

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Ensemble SVM for imbalanced data and missing values in postoperative risk management

Ensemble SVM for imbalanced data and missing values in posto...

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2013 IEEE 15th International Conference on e-Health Networking, Applications and Services, Healthcom 2013

作者： Zieba, Maciej Swiatek, Jerzy Wroclaw University of Technology Dep. of Computer Science and Management Institute of Informatics Poland

ISBN: (纸本)9781467358019

In this work, we propose the ensemble SVM that solves the problem of missing values of attributes and the imbalanced data phenomenon in the domain of postoperative risk management. Contrary to the other approaches the our solution effectively deals with the problems of high percentage of unknown values of the features. The problem of imbalanced data is solved by applying the cost-sensitive SVM as a base classifier of an ensemble, The quality of the proposed classifier is examined on a real-life dataset. © 2013 IEEE.

关键词： Classification (of information)

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Mining and estimating users' opinion strength in forum texts regarding governmental decisions

Mining and estimating users' opinion strength in forum texts...

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8th International Workshop on Artificial Intelligence Applications and Innovations, AIAI 2012: AIAB, AIeIA, CISE, COPA, IIVC, ISQL, MHDW, and WADTMB

作者： Stylios, George Tsolis, Dimitrios Christodoulakis, Dimitrios Technical Educational Institute of Ionian Islands Dept. of Applications of Information Technology in Administration and Economy 3100 Lefkas Greece University of Patras Computer Engineering and Informatics Dep. 26504 Patras Greece

ISBN: (纸本)9783642334115

Web 2.0 has facilitated interactive information sharing on the WWW, allowing users the opportunity to articulate their opinions on different topics. In this framework, certain practices implement information monitoring systems so as digests, reports on keywords and thematic queries regarding opinions on government decisions to be created. Analysis of rubrics associations, primary semantic and statistical interpretation of the texts is usually carried out. It is, on the other hand, rather difficult to get punctual predicts and estimate sufficiently forum users' opinion strength. In this work we present a methodology which automatically mines and estimates the strength of users' opinions on text forums regarding government decisions. According to our methodology, quantitative features are automatically mined from forum posts and then passed to a Support Vector Machine based classifier where the users' opinion strength is estimated. The proposed methodology has been validated in real data and initial experimental results are presented. © 2012 IFIP International Federation for Information Processing.

关键词： Sentiment analysis

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