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Corrigendum to “Trajectory design and resource allocation for UAV energy minimization in a rotary-wing UAV-enabled WPCN” [Alex. Eng. J. 60(1) (2021) 1787–1796]

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Alexandria Engineering Journal 2022年第12期61卷 11003-11003页

作者： Zhen Wang Miaowen Wen Shuping Dang Lisu Yu Yuhao Wang School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing 100876 China School of Information Engineering Nanchang University Nanchang 330031 China School of Electronic and Information Engineering South China University of Technology Guangzhou 510641 China Department of Electrical and Electronic Engineering University of Bristol Bristol BS8 1UB UK State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

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"So what if ChatGPT wrote it?" Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

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International Journal of Information Management 2023年 71卷

作者： Dwivedi, Yogesh K. Kshetri, Nir Hughes, Laurie Slade, Emma Louise Jeyaraj, Anand Kar, Arpan Kumar Baabdullah, Abdullah M. Koohang, Alex Raghavan, Vishnupriya Ahuja, Manju Albanna, Hanaa Albashrawi, Mousa Ahmad Al-Busaidi, Adil S. Balakrishnan, Janarthanan Barlette, Yves Basu, Sriparna Bose, Indranil Brooks, Laurence Buhalis, Dimitrios Carter, Lemuria Chowdhury, Soumyadeb Crick, Tom Cunningham, Scott W. Davies, Gareth H. Davison, Robert M. Dé, Rahul Dennehy, Denis Duan, Yanqing Dubey, Rameshwar Dwivedi, Rohita Edwards, John S. Flavián, Carlos Gauld, Robin Grover, Varun Hu, Mei-Chih Janssen, Marijn Jones, Paul Junglas, Iris Khorana, Sangeeta Kraus, Sascha Larsen, Kai R. Latreille, Paul Laumer, Sven Malik, F. Tegwen Mardani, Abbas Mariani, Marcello Mithas, Sunil Mogaji, Emmanuel Nord, Jeretta Horn O'Connor, Siobhan Okumus, Fevzi Pagani, Margherita Pandey, Neeraj Papagiannidis, Savvas Pappas, Ilias O. Pathak, Nishith Pries-Heje, Jan Raman, Ramakrishnan Rana, Nripendra P. Rehm, Sven-Volker Ribeiro-Navarrete, Samuel Richter, Alexander Rowe, Frantz Sarker, Suprateek Stahl, Bernd Carsten Tiwari, Manoj Kumar van der Aalst, Wil Venkatesh, Viswanath Viglia, Giampaolo Wade, Michael Walton, Paul Wirtz, Jochen Wright, Ryan Digital Futures for Sustainable Business & Society Research Group School of Management Swansea University Bay Campus Fabian Bay Wales Swansea United Kingdom Maharashtra Pune India Bryan School of Business and Economics University of North Carolina at Greensboro United States University of Bristol Business School University of Bristol BS8 1SD United Kingdom Professor of Information Systems Raj Soin College of Business Wright State University 3640 Colonel Glenn Highway DaytonOH45435 United States School of Artificial Intelligence Indian Institute of Technology Delhi Hauz Khas New Delhi India Department of Management Studies Indian Institute of Technology Delhi Hauz Khas New Delhi India Department of Management Information Systems Faculty of Economics and Administration King Abdulaziz University Jeddah Saudi Arabia School of Computing Middle Georgia State University MaconGA United States Client Advisory and Transformation Stackroute NIIT Limited India Department of Information Systems Analytics and Operations College of Business University of Louisville United States Northumbria University London United Kingdom IRC-FDE KFUPM Saudi Arabia ISOM KFUPM Business School KFUPM Saudi Arabia Innovation and Technology Transfer Center Sultan Qaboos University Oman Department of Business Communication Sultan Qaboos University Oman Department of Management Studies National Institute of Technology Tiruchirappalli India Montpellier France FORE School of Management New Delhi India Indian Institute of Management Ahmedabad Vastrapur Ahmedabad380015 India Information School University of Sheffield United Kingdom Bournemouth University Business School Poole United Kingdom School of Information Systems and Technology Management University of New South Wales Sydney Australia Information Operations and Management Sciences Department TBS Business School 1 Place Alphonse Jourdain Toulouse31068 France Department of Education & Childhood Studies Swansea Univers

Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT's capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT's use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics;digital transformation of organisations and societies;and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI;examining biases of generative AI attributable to training datasets and processes;exploring business and societal contexts best suited for generative AI implementation;determining optimal combinations of human and generative AI for various tasks;identifying ways to assess accuracy of text produced by generative AI;and uncovering the ethical and legal issues in using generative AI across different contexts. © 2023 The Authors

关键词： Marketing

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Demo abstract: Towards IoT service deployments on edge community network microclouds

Demo abstract: Towards IoT service deployments on edge commu...

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2018 IEEE Conference on computer Communications Workshops, INFOCOM 2018

作者： Khan, Amin M. Freitag, Felix Vlassov, Vladimir Ha, Phuong Hoai Department of Computer Science UiT the Arctic University of Norway Tromsø Norway Department of Computer Architecture Universitat Politècnica de Catalunya Barcelona Spain KTH Royal Institute of Technology Stockholm Sweden Hitachi Vantara Corporation Lisbon Portugal

ISBN: (纸本)9781538659793

Internet of Things (IoT) services for personal devices and smart homes provided by commercial solutions are typically proprietary and closed. These services provide little control to the end users, for instance to take ownership of their data and enabling services, which hinders these solutions' wider acceptance. In this demo paper, we argue for an approach to deploy professional IoT services on user-controlled infrastructure at the network edge. The users would benefit from the ability to choose the most suitable service from different IoT service offerings, like the one which satisfies their privacy requirements, and third-party service providers could offer more tailored IoT services at customer premises. We conduct the demonstration on microclouds, which have been built with the Cloudy platform in the *** community network. The demonstration is conducted from the perspective of end users, who wish to deploy professional IoT data management and analytics services in volunteer microclouds. © 2018 IEEE.

关键词： Internet of things

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Using the Model of a Functional Rationalizer of Consumer Behavior in Recommendation Systems for Managing the Transport Activity of the Urban Population

Using the Model of a Functional Rationalizer of Consumer Beh...

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International Conference on Soft Computing and Measurements (SCM)

作者： Yaroslav A. Seliverstov Svytoslav A. Seliverstov Nikolay V. Podoprigora Alexey L. Starichenkov Roman S. Naryshkin Laboratory of Intelligent Transport Systems Solomenko Institute of Transport Problems of the Russian Academy of Sciences Institute of Computer Science and Technology Peter the Great St.Petersburg Polytechnic University St. Petersburg Russian Federation Department of Ground Transportation Technological Machines Saint Petersburg State University of Architecture and Civil Engineering St. Petersburg Russian Federation Department of Ship Control Systems Saint Petersburg Electrotechnical University “LETI” St. Petersburg Russian Federation Department of Programming Technology Saint Petersburg State University St. Petersburg Russian Federation

ISBN: (数字)9781728196923

ISBN: (纸本)9781728196930

An overview of existing urban software mobile applications of the transport and economic direction is given. A model of a functional rationalizer of consumer behavior is being built. The software model of the functional rationalizer of consumer behavior (SM FRCB) was developed for the first time. PMFRCB allows the user to expand the number of his preferred needs (occupations, activities) during the daily cycle through intelligent recommendations. Also, SM FRCB allows you to optimize needs (activities, activities) at the cost and rate of their use. The SM FRCB is made in Python_3 using the libraries matplotlib, collections, numpy, pyplot, mplot3d. The analysis of consumer behavior before and after using the functional rationalizer model is carried out. The graphical results of a structural analysis of the costs of old and new consumer behavior, analysis of consumer behavior within the boundaries of the theory of possibilities and the model of transport behavior of a resident before and after applying the functional rationalizer model are presented. The prospects of further improving the SM FRCB are considered.

关键词： Consumer behavior Mobile applications Sociology Statistics Logistics Analytical models Software

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Reinforcement Learning for Channel Coding: Learned Bit-Flipping Decoding

Reinforcement Learning for Channel Coding: Learned Bit-Flipp...

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Annual Allerton Conference on Communication, Control, and Computing

作者： Fabrizio Carpi Christian Häger Marco Martalò Riccardo Raheli Henry D. Pfister Department of Electrical and Computer Engineering New York University Brooklyn New York USA Department of Electrical Engineering Chalmers University of Technology Gothenburg Sweden University of Parma Parma Italy Department of Engineering and Architecture University of Parma Parma Italy Department of Electrical and Computer Engineering Duke University Durham North Carolina USA

In this paper, we use reinforcement learning to find effective decoding strategies for binary linear codes. We start by reviewing several iterative decoding algorithms that involve a decision-making process at each step, including bit-flipping (BF) decoding, residual belief propagation, and anchor decoding. We then illustrate how such algorithms can be mapped to Markov decision processes allowing for data-driven learning of optimal decision strategies, rather than basing decisions on heuristics or intuition. As a case study, we consider BF decoding for both the binary symmetric and additive white Gaussian noise channel. Our results show that learned BF decoders can offer a range of performance-complexity trade-offs for the considered Reed-Muller and BCH codes, and achieve near-optimal performance in some cases. We also demonstrate learning convergence speed-ups when biasing the learning process towards correct decoding decisions, as opposed to relying only on random explorations and past knowledge.

关键词： Iterative decoding Decoding Decision making Linear codes Reliability Standards Markov processes

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A novel automated algorithm for computing lumbar flexion test ratios enhancing athletes objective assessment of low back pain 6

A novel automated algorithm for computing lumbar flexion tes...

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6th International Congress on Sport Sciences Research and technology Support, icSPORTS 2018

作者： Carrillo-Perez, Francisco Diaz-Reyes, Ignacio Damas, Miguel Banos, Oresti Soto-Hermoso, Victor Manuel Molina-Molina, Alejandro Department of Computer Architecture and Computer Technology E.T.S.I.I.T. Universidad de Granada Calle Periodista Daniel Saucedo Aranda Granada Spain Department of Sport and Physical Education Universidad de Granada Granada Spain

ISBN: (纸本)9789897583254

INTRODUCTION: Low Back Pain is a common muscular disorder that most adults would experience over their lives. In healthy patients at the end of a lumbar flexion occur a phenomenon called the Flexion Relaxation Phenomenon. Ratios between different phases of lumbar flexion can help diagnosing LBP patients. The aim of this work is to create an automated algorithm to compute this ratios helping to discriminate between healthy and LBP athletes. MATERIALS AND METHODS: 21 participants were recruited: 10 LBP and 11 healthy. Participants were tested with Lumbar Flexion Test for evaluating LBP. sEMG were recorded in low back muscles. RESULTS: Athletes diagnosed with LBP showed ratios lower than 1.5. For healthy participants we observed results greater than 1.5. DISCUSSION AND CONCLUSION: Our results are contained between rates found in literature. Our algorithm can help the diagnose of athletes with a non-intrusive method and with little knowledge of sEMG analysis. Copyright © 2018 by SCITEPRESS - Science and technology Publications, Lda. All rights reserved

关键词： Diagnosis

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Usability Evaluation for User Interface Design of Student Support System: Mixed Method Study

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IOP Conference Series: Materials Science and Engineering 2020年第1期803卷

作者： Ahmed AL-sa'di Rasmus Rasmus Bugge Skammelsen Qiang Ji Yufeng Xiang Bhogadi Aakarsh Sathishkumar Kuppusamy Department of Information system UUNZ Institute of Business Auckland New Zealand Department of Architecture Design and Media Technology Aalborg University Aalborg Denmark Department of Computer Science Auckland University of Technology Auckland New Zealand

The efficiency of a website depends on how usable the UI user interface, (UI) is and how well it is structured. The aim of this research was to try and understand the issues with the Arion System. Arion is the student information system used by Auckland University of technology. We conducted three experimental studies to examine the usability and to improve the user experience of student who use Arion. Three main methods were used namely; survey, open card sorting and situated co-inquiry. The survey was used to inform the study and collect more information about users. The open card sorting used to redesign the navigation menu for the system. Then the Situated co-inquiry used to discover the user's current unexpected or unforeseen ideas, which may be helpful for future research.

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Mixed size crossbar based RRAM CNN accelerator with overlapped mapping method 18

Mixed size crossbar based RRAM CNN accelerator with overlapp...

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37th IEEE/ACM International Conference on computer-Aided Design, ICCAD 2018

作者： Zhu, Zhenhua Lin, Jilan Cheng, Ming Xia, Lixue Sun, Hanbo Chen, Xiaoming Wang, Yu Yang, Huazhong Department of Electronic Engineering Tsinghua University Beijing China Beijing China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781450359504

Convolutional Neural Networks (CNNs) play a vital role in machine learning. CNNs are typically both computing and memory intensive. Emerging resistive random-access memories (RRAMs) and RRAM crossbars have demonstrated great potentials in boosting the performance and energy efficiency of CNNs. Compared with small crossbars, large crossbars show better energy efficiency with less interface overhead. However, conventional workload mapping methods for small crossbars cannot make full use of the computation ability of large crossbars. In this paper, we propose an Overlapped Mapping Method (OMM) and MIxed Size Crossbar based RRAM CNN Accelerator (MISCA) to solve this problem. MISCA with OMM can reduce the energy consumption caused by the interface circuits, and improve the parallelism of computation by leveraging the idle RRAM cells in crossbars. The simulation results show that MISCA with OMM can achieve 2.7x speedup, 30% utilization rate improvement, and 1.2x energy efficiency improvement on average compared with fixed size crossbars based accelerator using the conventional mapping method. In comparison with GPU platform, MISCA with OMM can perform 490.4x higher on average in energy efficiency and 20x higher on average in speedup. Compared with PRIME, an existing RRAM based accelerator, MISCA has 26.4x speedup and 1.65x energy efficiency improvement. © 2018 ACM.

关键词： Energy efficiency

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Learning-based Offloading of Tasks with Diverse Delay Sensitivities for Mobile Edge Computing

Learning-based Offloading of Tasks with Diverse Delay Sensit...

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IEEE Global Communications Conference

作者： Tianyu Zhang Yi-Han Chiang Cristian Borcea Yusheng Ji Department of Informatics SOKENDAI (The Graduate University for Advanced Studies) Tokyo Japan Information Systems Architecture Science Research Division National Institute of Informatics Tokyo Japan Department of Computer Science New Jersey Institute of Technology NJ USA

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

The ever-evolving mobile applications need more and more computing resources to smooth user experience and sometimes meet delay requirements. Therefore, mobile devices (MDs) are gradually having difficulties to complete all tasks in time due to the limitations of computing power and battery life. To cope with this problem, mobile edge computing (MEC) systems were created to help with task processing for MDs at nearby edge servers. Existing works have been devoted to solving MEC task offloading problems, including those with simple delay constraints, but most of them neglect the coexistence of deadline-constrained and delay-sensitive tasks (i.e., the diverse delay sensitivities of tasks). In this paper, we propose an actor-critic based deep reinforcement learning (ADRL) model that takes the diverse delay sensitivities into account and offloads tasks adaptively to minimize the total penalty caused by deadline misses of deadline-constrained tasks and the lateness of delay-sensitive tasks. We train the ADRL model using a real data set that consists of the diverse delay sensitivities of tasks. Our simulation results show that the proposed solution outperforms several heuristic algorithms in terms of total penalty, and it also retains its performance gains under different system settings.

关键词： Task analysis Delays Sensitivity Computational modeling Edge computing Load modeling Mobile handsets

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Modification of the structure of the stabilized basalt fiber

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IOP Conference Series: Materials Science and Engineering 2020年第1期907卷

作者： V I Gots P P Palchyk S A Tymoshenko S P Palchyk Department of Technology of Building Constructions and Products Kyiv National University of Construction and Architecture Povitroflotsky Avenue 31 Kyiv Ukraine Department of Cybersecurity and Computer Engineering Kyiv National University of Construction and Architecture Povitroflotskyi Avenue 31 Kyiv Ukraine

The study of thermophysical, physical-mechanical and acoustic characteristics of coarse continuous basalt fiber in the conditions of influence of operational factors and corrosion environment is carried out. It is shown that obtaining barrier materials with high thermophysical and acoustic properties is possible by creating a porous system in the material with a predetermined textural characteristic of pores of different class, purpose and combination. The influence of the porous system of coarse continuous basalt fiber on the operational properties of flexible heat and sound insulation products and materials has been studied. It is determined that the performance characteristics of flexible thermal insulation materials are in direct proportion to the degree of porosity of the constituent materials and their structural characteristics. Shown that the increase in the operating temperature of these materials, sound and thermal resistance is determined by the chemical and mineralogical composition of the source materials and their structural characteristics. The influence of the mechanism of selective leaching of coarse continuous basalt fibers on their textural characteristics and the zone of operating temperatures is studied.

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