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Data transmission via erasure type channels protected by linear codes

Journal of Physics: Conference Series 2012年第1期364卷

作者： H D Wacker P Pendli J Börcsök To whom any correspondence should be addressed University Kassel Faculty of Electrical Engineering/Computer Science Department of Computer Architecture and System Programming Wilhelmshöher Allee 71 34121 Kassel

The paper is concerned with data transmission via channels composed of a memoryless binary symmetric channel and the erasure channel of Peter Elias. Channels of this type play an important role in modelling different types of networks especially wireless networks, and have been investigated using, amongst others, the theory of Markov chains. Channel Capacities and network flows have been determined. The authors focus their interest on some aspects of coding theory. They assume the data transmission to be protected by a linear code, a CRC for example, and determine the probability of undetected error of the code. They then consider redundant transmission via two or more channels with bit inversion, and calculate the probability of undetected error. They prove some inequalities that are useful instruments to estimate the rate of transmission errors and to determine safety integrity levels according to the standards. Finally the authors apply their results to Bluetooth channels suffering from different types of noise.

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Develop an unsupervised attention-based LSTM network algorithm for forecasting infectious disease

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AIP Conference Proceedings 2023年第1期2977卷

作者： Mostafa Abotaleb Tatiana Makarovskikh Zainalabideen Albadran Ali J. Ramadhan System Programming Department South Ural State University Chelyabinsk Russia Department of Computer Techniques Engineering College of Technical Engineering University of Alkafeel Najaf Iraq

time series Due to better algorithms, more accessible data, and higher computing power over the past ten years, forecasting has become more popular. It is used in a variety of industries, including as financial time series, weather forecasting, and medical diagnostics. In this study, we provide a model of the mechanism governing attention, which enables attended input to be provided to the model in place of actual input. In order for the model to produce more precise predictions, it seeks to demonstrate a fresh perspective on the data. The experiments were conducted with the (encoder-decoder) LSTM model as well to demonstrate the usefulness and superiority of the suggested strategy. The obtained results demonstrate that, when compared to the (encoder-decoder) LSTM base model, the proposed approach could reduce the mean square error (RMSE=9819.05), relative root mean square error (RRMSE=99.09), and coefficient of determination (R Square=0.96). The obtained results support the suggested approach’s efficacy, superiority, and importance in predicting SARS-CoV-2 infection cases.

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The contributions regarding the conception, designing, modelling and the implementation in a flexible cell of fabrication of a modular serial robot

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PAMM 2010年第1期9卷

作者： Silviu Mihai Petrişor Viorel Ispas Mariana Arghir Tehnical University of Cluj-Napoca Department of Mechanics and Computer Programming Muncii Avenue no. 103-105 Cluj-Napoca 400 641 Romania

The authors of the presented paper are propose to relief the calculus, modelling and construction of the translation module of an industrial robot which possess in his cinematic chain five degrees of freedom, type TTRTR. It is propose a choosing variant of the direct current driving engine of the translation module, knowing the output momentum and calculating the input momentum. This is realized by equalize of an equation which results from dynamic modeling of the robot with a designing equation which keep in view the component elements of the structure of the module. The robot is composed by: module of translation on horizontal to the base of the robot (MTB-Sil), module of translation on vertical (MTV-Sil), module of rotation round the vertical axis from the robot's arm, module of translation from the structure of the robot's arm (MT-Sil) and module of orientation assembled with clamping device. In the paper, also is presented an economic study regarding the implementation of the analyzed robot in a manufactural cell concerning the manufacturing and assembling of some types of car radiators. (© 2009 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)

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New Algorithm for the Identification and Analysis of the Parallel Robots Singularities

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PAMM 2005年第1期5卷

作者： Doina Pisla Department for Mechanics and Computer Programming TU Cluj-Napoca C. Daicoviciu Str. 15 RO-400020 Cluj-Napoca Romania

The paper presents a new algorithm for the analysis of the kinematic singularities for different parallel structures using a testing stand. The derived expressions are used to superimpose graphical representations of the manipulators singularity and workspace. The analytical description of the singularity loci can be successfully used for the optimisation of the kinematic design. The derived algorithm for singularities analysis has been integrated in an already developed parallel robots simulation system, which provides an easy to read graphical representation of the singularities that enables their isolation within the working space and their avoiding in the path programming activity. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

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ATTITUDES TOWARD REPRODUCTIVE ENGINEERING - AN OVERVIEW

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JOURNAL OF FAMILY ISSUES 1981年第1期2卷 5-24页

作者： HARTLEY, SF California State University Hayward Corresponding Author: Shirley Foster Hartley is Professor and former Chair of the Department of Sociology California State University Hayward. Books published include: Population: Quantity vs. Quality (Prentice-Hall) and Illegitimacy (University of California Press). Articles published and research interests vary from micro-analyses of interpersonal attraction role conflicts among clergy wives and marital satisfaction to macro studies of the status of women in various societies and population growth and development. ∗An earlier draft was prepared in conjunction with William J. Beaver whose expertise in computer programming greatly facilitated this analysis. The report on our pilot study was presented at the American Association for the Advancement of Science Pacific Division San Francisco CA June 13 197

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Location–allocation problem for green efficient two-stage vehicle-based logistics system: A type-2 neutrosophic multi-objective modeling approach

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Expert Systems with Applications 2024年 238卷

作者： Das, Soumen Kumar Yu, Vincent F. Roy, Sankar Kumar Weber, Gerhard Wilhelm Department of Pure and Applied Sciences Midnapore City College Kuturia West Bengal Bhadutala721129 India Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University West Bengal Midnapore721102 India Department of Industrial Management National Taiwan University of Science and Technology Taipei Taiwan Center for Cyber-Physical System Innovation National Taiwan University of Science and Technology Taipei Taiwan Faculty of Engineering Management Poznan University of Technology Poznan Poland IAM METU Ankara Turkey

In recent decades, global climate change has become one of the most critical environmental issues, leading to increased environmental and social concerns about the sustainability of logistics networks. This study proposes a novel multi-objective, multi-facility location–allocation model for a two-stage solid logistics network that supports green practices. To account for uncertainty in real-world problems, some parameters of the model are represented as triangular type-2 neutrosophic numbers to deal with hesitant situations. The fuzzy model is then converted into a deterministic one using a new ranking approach. Three conflicting objective functions – minimizing total financial costs, maximizing customers’ satisfaction levels, and ensuring sustainable and effective conveyances – are simultaneously optimized using the ϵ-constraint approach. The proposed model and solution approach are tested with two numerical examples. A comparative study is also presented, comparing the proposed approach with other Pareto-based multi-objective approaches, such as the global criterion approach, multi-objective fuzzy programming, and weighted Chebychev programming. Finally, the paper concludes with some remarks. © 2023

关键词： Sustainable development

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Hybrid multi-criteria decision-making method with a bipolar fuzzy approach and its applications to economic condition analysis

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Engineering Applications of Artificial Intelligence 2024年 132卷

作者： Jana, Chiranjibe Simic, Vladimir Pal, Madhumangal Sarkar, Biswajit Pamucar, Dragan Tamil Nadu Chennai602105 India Faculty of Transport and Traffic Engineering University of Belgrade VojvodeStepe 305 Belgrade11010 Serbia Yuan Ze University College of Engineering Department of Industrial Engineering and Management Taoyuan City320315 Taiwan Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore721102 India Department of Industrial Engineering Yonsei University 50 Yonsei-ro Sinchon-dong Seodaemun-gu Seoul03722 Korea Republic of Center for Global Health Research Saveetha Medical College Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu 600077 India Department of Industrial Engineering and Management National Taipei University of Technology Taipei City 106344 Taiwan Department of Operations Research and Statistics Faculty of Organizational Sciences University of Belgrade Belgrade Serbia Department of Computer Science and Mathematics Lebanese American University Byblos 1102 2801 Lebanon

The bipolar fuzzy set and interval-valued bipolar fuzzy set efficiently analyse real-world problems where for each input of an object, there has counter information. This study's main objective is to lay a foundation for considering a new approach to the bipolar fuzzy hybrid operators tool applied in a realistic frame that contains uncertainties. In this view, some mixed aggregation operators, namely, the hybrid bipolar fuzzy weighted averaging geometric (H-BFWAG), hybrid bipolar fuzzy order weighted averaging geometric (H-BFOWAG), hybrid interval-valued bipolar fuzzy weighted averaging geometric (H-IVBFWAG), and hybrid interval-valued bipolar fuzzy order weighted averaging geometric (H-IVBFOWAG) operators are generated in bipolar fuzzy environment. A decision making approach is developed to build the multi-criteria decision making model. A numerical example is considered to study the different effects on various Indian economic sectors in the COVID-19 environment. Managerial implications are highlighted in between many industrial sectors on which the Indian economy depends and the country's gross domestic product depends on their inter-relationship. This study investigates COVID-19's impact on society and the economy in the Indian context. A comparative investigation is introduced with some pre-existing operators and the TOPSIS (technique for order of preference by similarity to ideal solution) approach to justify the proposed method. © 2024 Elsevier Ltd

关键词： COVID-19

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Design of Intelligent Decision Support System With Ensembled Machine Learning to Predict Students' Performance

Design of Intelligent Decision Support System With Ensembled...

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Communication, computer Sciences and Engineering (IC3SE), International Conference on

作者： S Deepan Dineshkumar Rajendran Navdeep Dhaliwal K Praveena Melanie Lourens Anandhi R J School of CS & AI SR University Warangal Telangana India Computer Games Design and Programming School of Computing and Innovative Technologies British University Vietnam Vietnam Lovely Professional University Phagwara India Institute of Aeronautical Engineering Dundigal Hyderabad Deputy Dean Faculty of Management Sciences Durban University of Technology South Africa Department of Information Science Engineering New Horizon College of Engineering Bangalore

ISBN: (数字)9798350366846

ISBN: (纸本)9798350366853

Evaluating student performance is important for universities and institutions in the current student education landscape because it helps them create models that work better for students. The automation of various features related to fundamental student traits and behaviours that manage massive amounts of data efficiently processes these. To handle student records that included information about students' behaviour and how it related to their academic performance, the companies employed models of classification with mining concepts. Additionally, the quality of result classification can be substantially improved by using learning analytics and Educational Data Mining (EDM). The educational establishments are making an effort to lower the low student performance. To address this issue, numerous methods for assessing student performance have been devised, allowing the relevant faculties to intervene and enhance the final product. Three classes—Low Performance Student, Average Student, and Smart Student—were created using the K-Mean Clustering methodology for classifying student records. Features including grade point, number of deficits, student attendance, medium of education, and board of education are taken into account when classifying the data. In this case, the WEKA tool is also utilized for implementing the model and outcome assessments.

关键词： Deep learning Decision support systems Analytical models Data analysis Automation Education Companies

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A flexible framework for web-based virtual reality presentation of cultural heritage

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AIP Conference Proceedings 2021年第1期2333卷

作者： Dimo Chotrov Angel Bachvarov 1Technical University Sofia Faculty of Computer Systems and Technologies Department Programming and Computer Technologies Bulgaria 2Technical University Sofia Faculty of Mechanical Engineering Department Automation of Discrete Production Engineering Bulgaria

The Virtual Reality (VR) experiences are great for an engaging presentation creating wide public awareness of cultural heritage, especially if the experience is built on a web-based technology. One of the still posing challenges is that once an application has been developed, for example for a virtual museum or a virtual tour, it usually remains fixed to an embedded in the application model. Adding new functionalities or interaction paradigms needs additional development and new deployment. In this paper, we propose a framework, which achieves the decoupling of an experience from the used models and interaction paradigms through scene and input templates and configuration files. This allows an easy way for generation of a variety of experiences even by people with no or limited programming skills.

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Darknet traffic big-data analysis and network management to real-time automating the malicious intent detection process by a weight agnostic neural networks framework

arXiv

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arXiv 2021年

作者： Demertzis, Konstantinos Tsiknas, Konstantinos Takezis, Dimitrios Skianis, Charalabos Iliadis, Lazaros Laboratory of Complex Systems Department of Physics Faculty of Sciences International Hellenic University Kavala Campus St. Loukas65404 Greece Department of Electrical and Computer Engineering Democritus University of Thrace Vas. Sofias 12 Xanthi67100 Greece Hellenic National Defence General Staff Stratopedo Papagou Mesogeion 227-231 Athens15561 Greece University of Aegean Karlovassi Samos83200 Greece School of Engineering Department of Civil Engineering Faculty of Mathematics Programming and General courses Democritus University of Thrace Kimmeria Xanthi Greece

Attackers are perpetually modifying their tactics to avoid detection and frequently leverage legitimate credentials with trusted tools already deployed in a network environment, making it difficult for organizations to proactively identify critical security risks. Network traffic analysis products have emerged in response to attackers’ relentless innovation, offering organizations a realistic path forward for combatting creative attackers. Additionally, thanks to the widespread adoption of cloud computing, Device Operators (DevOps) processes, and the Internet of Things (IoT), maintaining effective network visibility has become a highly complex and overwhelming process. What makes network traffic analysis technology particularly meaningful is its ability to combine its core capabilities to deliver malicious intent detection. In this paper, we propose a novel darknet traffic analysis and network management framework to real-time automating the malicious intent detection process, using a weight agnostic neural networks architecture. It is an effective and accurate computational intelligent forensics tool for network traffic analysis, the demystification of malware traffic, and encrypted traffic identification in real-time. Based on Weight Agnostic Neural Networks (WANNs) methodology, we propose an automated searching neural net architectures strategy that can perform various tasks such as identify zero-day attacks. By automating the malicious intent detection process from the darknet, the advanced proposed solution is reducing the skills and effort barrier that prevents many organizations from effectively protecting their most critical assets. Copyright © 2021, The Authors. All rights reserved.

关键词： Network management

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