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Machine Learning-Based Channel State Estimators for 5G Wireless Communication Systems

Computer Modeling in engineering & Sciences 2023年第4期135卷 755-778页

作者： Mohamed Hassan Essai Ali Fahad Alraddady Mo’ath Y.Al-Thunaibat Shaima Elnazer Department of Electrical Engineering Faculty of EngineeringAl-Azhar UniversityQena83513Egypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Management Information Systems Taif UniversityTaif21944Saudi Arabia

For a 5G wireless communication system,a convolutional deep neural network(CNN)is employed to synthesize a robust channel state estimator(CSE).The proposed CSE extracts channel information from transmit-and-receive pairs through offline training to estimate the channel state ***,it utilizes pilots to offer more helpful information about the communication *** proposedCNN-CSE performance is compared with previously published results for Bidirectional/long short-term memory(BiLSTM/LSTM)NNs-based *** CNN-CSE achieves outstanding performance using sufficient pilots only and loses its functionality at limited pilots compared with BiLSTM and LSTM-based *** three different loss function-based classification layers and the Adam optimization algorithm,a comparative study was conducted to assess the performance of the presented DNNs-based *** BiLSTM-CSE outperforms LSTM,CNN,conventional least squares(LS),and minimum mean square error(MMSE)*** addition,the computational and learning time complexities for DNN-CSEs are *** estimators are promising for 5G and future communication systems because they can analyze large amounts of data,discover statistical dependencies,learn correlations between features,and generalize the gotten knowledge.

关键词： DLNNs channel state estimator 5G and beyond communication systems robust loss functions

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engineering Sustainable Careers: Exploring Parenthood Timing Factors among Engineers in Australia

Engineering Sustainable Careers: Exploring Parenthood Timing...

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2024 SPE Asia Pacific Oil and Gas Conference and Exhibition, APOGCE 2024

作者： Triharta, M. Monzon, V.S. Male, S. Wong, E. Faculty of Engineering and Information Technology University of Melbourne VIC Australia Department of Management and Marketing Faculty of Business and Economics University of Melbourne VIC Australia

ISBN: (纸本)9781959025269

The sustainability of qualified female engineers’ careers in Australia is challenged at the critical childbearing age, with evidence pointing towards masculine professional cultures and a specter of reproductive choices as potential risk factors for low fertility among female engineers in the profession. In this paper, factors influencing decisions on the timing of parenthood for both female and male engineers in Australia are explored across different personal life stages within their professional careers. This study employed a qualitative method of semi-structured interviews with a total of twenty female and male engineers in Australia. The interviews harnessed an interactive component where participants were asked to graphically time-map their engineering career while retrospectively reflecting on their parental aspirations and the factors that influenced them at different periods of their journey. Factors that accelerate or delay reproductive timing were identified with respect to the time period when the factors were most salient. The study identified a multilayer of factors, namely: (a) individual;(b) inner circle, such as spouse and family;(c) organizational;and (d) profession/industry - that critically influence decisions on the timing of parenthood. Most participants identified age and individual or their spouse's economic and career securities as crucial factors. At the organizational and industrial level, hypercompetitive organizational culture, i.e., the shared drive for results rather than development;the business nature of the organization, i.e., project-centric versus continuous operation work structure, and its geographical presence affected both male and female engineers’ decisions and may delay their reproductive timing. The study identified several delaying factors that were prominent among female engineers and absent in their male counterparts. These included: professional identity, hostile work environments towards women, especially when experie

关键词： Obsolescence

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Factors Influencing the Acceptance of Collaboration Platform for Fleet Maintenance 5

Factors Influencing the Acceptance of Collaboration Platform...

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5th technology Innovation management and engineering Science International Conference, TIMES-iCON 2024

作者： Sa-Nga-Ngam, Prush Athikulrat, Kittichai Muttitanon, Werachart Technology of Information System Management Division Faculty of Engineering Mahidol University Nakhon Pathom Thailand Department of Materials Handling and Logistics Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangkok Thailand Faculty of Business Administration and Information Technology Rajamangala University of Technology Tawan-ok Bangkok Thailand

ISBN: (纸本)9798350362602

Maintenance management plays a crucial role in the cost dimension of transportation company. Repair and maintenance expenses constitute a significant portion of overall manageable costs and directly impact the revenue generation of these businesses. Effective maintenance manage management is therefore essential for transportation companies to ensure the constant readiness of their vehicles for transportation tasks. This research aimed to study the factors that influence the acceptance of collaborative fleet maintenance platform by conducting a comprehensive in-depth interview with 3 groups. 1. Transportation company with in-house fleet maintenance units and nationwide transport services 2. Transportation company without in-house fleet maintenance units and nationwide transport services and 3. Truck repair and maintenance service providers which 20 business per groups. Data was collected through semi-structured interviews. The interviews were transcribed verbatim. Data analysis employed thematic analysis, a qualitative data analysis method that identifies patterns and themes within the collected data. The research results demonstrated the factors that influence the acceptance of collaboration platforms for fleet maintenance are price format, data and information, ease of use and perceived usefulness. ©2024 IEEE.

关键词： Costs

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Employing Comparative Study between Frontend Frameworks. React Vs Ember Vs Svelte 16

Employing Comparative Study between Frontend Frameworks. Rea...

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16th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2024

作者： Novac, Ovidiu Constantin Novac, Mihaela Cornelia Oproescu, Mihai Mlinarcic, Adrian-Cristian Gordan, Cornelia Emilia Dindelegan, Camelia Maria University of Oradea Electrical Engineering and Information Technology Faculty Department of Computers and Information Technology Oradea Romania University of Oradea Electrical Engineering and Information Technology Faculty Department of Electrical Engineering Oradea Romania National University of Science and Technology Politehnica Bucharest Piteti University Centre Faculty of Electronics Communications and Computers Pitesti Romania University of Oradea Management in Information Technology Electrical Engineering and Information Technology Faculty Oradea Romania University of Oradea Department of Electronics and Telecommunications Electrical Engineering and Information Technology Faculty Oradea Romania University of Oradea Faculty of Socio Human Science Dr. Curteanu Municipal Clinical Hospital Oradea Department of Psychology Oradea Romania

ISBN: (纸本)9798350371154

This paper presents a comparative study of three frontend frameworks: React, Svelte and Ember. The article presents which are the differences and similarities between frameworks, how things are handled in a framework in parallel to another, and why one is more popular and used than another. This study will have as a point of reference for comparison a ToDo application written in all three languages. © 2024 IEEE.

关键词： Ember frontend frameworks JavaScript React Svelte

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Performance of GNSS positioning in PPP mode using MADOCA precise products

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Geodesy and Geodynamics 2024年第6期15卷 642-651页

作者： Brian Bramanto Rachel Theresia Irwan Gumilar Sidik T.Wibowo Geodetic Science Engineeringand Innovation Research GroupFaculty of Earth Sciences and TechnologyInstitut Teknologi BandungBandung 40135Indonesia Geodesy and Geomatics Engineering Study Program Faculty of Earth Sciences and TechnologyInstitut Teknologi BandungBandung 40135Indonesia Geodetic and Geodynamic Control Network Center Geospatial Information Agency of Indonesia(BIG)Cibinong 16911Indonesia

The Global Navigation Satellite System (GNSS) is widely utilized for accurate *** commonly applied method to obtain precise coordinate estimates is by implementing the relative positioning in network ***,this approach can be complex and ***,The Japan Aerospace Exploration Agency (JAXA) offers freely available satellite orbit and clock correction products called Multi-GNSS Advanced Demonstration Tool for Orbit and Clock Analysis (MADOCA),which can enhance positioning accuracy through the precise point positioning (PPP) *** study focuses on evaluating PPP static mode positioning using MADOCA products and comparing the results with the highly precise relative positioning *** analyzing a network of 20 GNSS stations in Indonesia,we found that the PPP method using MADOCA products provided favorable positioning *** median discrepancies and the corresponding median absolute deviation (MAD) for easting,northing,and up components were estimated as 9±18 mm,10±9 mm,and 3±40 mm,*** results indicate that PPP with MADOCA products can be a reliable alternative for establishing Indonesia's horizontal control networks,particularly for orders 0,1,2,and 3,and for a broad spectrum of geoscience monitoring ***,considerations such as epoch transformations and seismic activities should be taken into account for accurate positioning applications that comply with the definition of the national reference framework.

关键词： Global Navigation Satellite System(GNSS) Precise point positioning(PPP) MADOCA Positioning evaluation

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Maximizing the Differences Between a Monotone DR-Submodular Function and a Linear Function on the Integer Lattice

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Journal of the Operations Research Society of China 2024年第3期12卷 795-807页

作者： Zhen-Ning Zhang Dong-Lei Du Ran Ma Dan Wu Department of Operations Research and Information Engineering Beijing University of TechnologyBeijing100124China Faculty of Management University of New BrunswickFrederictonNB E3B 9Y2Canada School of Management Engineering Qingdao University of TechnologyQingdao266525ShandongChina School of Mathematics and Statistics Henan University of Science and TechnologyLuoyang471023HenanChina

In this paper,we investigate the maximization of the differences between a nonnegative monotone diminishing return submodular(DR-submodular)function and a nonnegative linear function on the integer *** it is almost unapproximable for maximizing a submodular function without the condition of nonnegative,we provide weak(bifactor)approximation algorithms for this problem in two online settings,*** the unconstrained online model,we combine the ideas of single-threshold greedy,binary search and function scaling to give an efficient algorithm with a 1/2 weak approximation *** the online streaming model subject to a cardinality constraint,we provide a one-pass(3-√5)/2 weak approximation ratio streaming *** memory complexity is(k log k/ε),and the update time for per element is(log^(2)k/ε).

关键词： Submodular maximization DR-submodular Integer lattice Single-threshold greedy algorithm Streaming algorithm

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Electric Vehicle Stock Price Prediction using LSTM, Bi-LSTM and GRU 8

Electric Vehicle Stock Price Prediction using LSTM, Bi-LSTM ...

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8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024

作者： Ozer, Serpil Erol, Ummuhan Nida Osti˙m Technical University Industrial Engineering Faculty of Engineering Ankara Turkey Mersin University Management Information Systems School of Applied Technology and Management of Erdemli Mersin Turkey

ISBN: (纸本)9798331531492

Time series analysis, which is used to predict future values from past data, is an indispensable part of decision-making and policy-planning processes. For this reason, this field, which has a wide literature, is widely applied in many areas from economy to engineering, from climate science to health sector. In this study, the application of LSTM (Long Short-Term Memory), BiLSTM (Bidirectional Long Short-Term Memory), and GRU (Gated Recurrent Unit) methods on the stock price dataset of two electric vehicle companies is investigated in order to predict future values. LSTM, Bi-LSTM, and GRU methods are types of RNNs used in time series analysis to identify long-term dependencies in ordered data. The data set is separated into 80% training, and 20% test data. The data is normalized to make accurate predictions and to determine the relationship between past values and future values. MAPE, RMSE, R2, MSE, and MAE performance metrics are used to measure the performance of the data set. The stock predicting models of LSTM, Bi-LSTM, and GRU methods are compared, and the results show that the GRU method significantly outperforms the existing methods. © 2024 IEEE.

关键词： Long short-term memory

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Blockchain technology to Enhance Performance of Drugs Supply Chain in the Era of Digital Transformation in Egypt 3rd

Blockchain Technology to Enhance Performance of Drugs Supply...

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3rd World Conference on Internet of Things: Applications and Future, ITAF 2023

作者： Moussa, Aya Mohammed A. El-Gamal, Fatma El-Zahraa A. El Fetouh, Ahmed Saleh A. Business Information Technology Program Faculty of Computer and Information Mansoura University Mansoura Egypt Information Technology Department Faculty of Computer and Information Mansoura University Mansoura Egypt Delta Higher Institute for Management and Accounting Information Systems Mansoura Egypt

ISBN: (纸本)9789819947638

Medicine is one of the products that must be delivered to the patient safely, undamaged, and during its validity period. However, the risks of the drug supply chain have become increasingly apparent. To address these risks and due to the rapid advances in the technology field, various digital transformation trials around the globe start to be considered in order to replace the traditional drug supply chain until its delivery to the patient. Therefore, the aim of this paper is to contribute in the digital transformation goal of the drug supply chain in Egypt. Thus, this paper proposes a trusted automatic system, based on the blockchain and Internet of Things (IoT) technologies to enhance the performance of the drug supply chain and accordingly make the drug manufacturing and distribution system in Egypt more efficient and reliable. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Internet of things

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A Machine Learning Approach to Identifying Suspicious Tax Evasion Behavior in Public Financial Data 8

A Machine Learning Approach to Identifying Suspicious Tax Ev...

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8th International Conference on Business and Industrial Research, ICBIR 2023

作者： Visitpanya, Narongchai Samanchuen, Taweesak Mahidol University Technology of Information System Management Division Faculty of Engineering Nakorn Pathom Thailand

ISBN: (纸本)9798350399646

The protection of sensitive tax data poses a challenge for data processors seeking to use it freely, particularly in the realm of financial and tax data. Detecting suspicious behavior related to tax evasion in this area requires sophisticated techniques. This paper presents a study on detecting tax evasion behavior using publicly available financial data. The data was obtained from a public source, and machine learning was applied to identify suspicious behavior based on criteria derived from a literature review. Our study yielded a precision of over 97 % using selected supervised models. Future work involves exploring behavior using unsupervised methods, increasing the number of instances using data synthesis techniques, and comparing results with enterprises that are not registered in a stock market as long as the data is legally available. This research provides valuable insights into identifying suspicious tax evasion behavior and can inform the development of improved tax evasion detection systems in the future. © 2023 IEEE.

关键词： Taxation

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Submarine Hunter: Efficient and Secure Multi-Type Unmanned Vehicles

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Computers, Materials & Continua 2023年第7期76卷 573-589页

作者： Halah Hasan Mahmoud Marwan Kadhim Mohammed Al-Shammari Gehad Abdullah Amran Elsayed Tag eldin Ala R.Alareqi Nivin A.Ghamry Ehaa A.Lnajjar Esmail Almosharea Computer Center University of BaghdadBaghdad6751Iraq Department of Management Science and Engineering Dalian University of TechnologyLiaoningDalian116024China Department of Information Technology Faculty of Computer Sciences and Information Technology AL Razi UniversitySana’aYemen Faculty of Engineering and Technology Future University in EgyptNew Cairo11835Egypt Faculty of Engineering Mechanics Dalian University of TechnologyLiaoningDalian116024China Faculty of Computers and Artificial Intelligence Cairo UniversityGizaEgypt Department of Business Administration Dalian University of TechnologyLiaoningDalian116024China College of Software Engineering Dalian University of TechnologyChina

Utilizing artificial intelligence(AI)to protect smart coastal cities has become a novel vision for scientific and industrial *** of these AI technologies is using efficient and secure multi-environment Unmanned Vehicles(UVs)for anti-submarine *** study’s contribution is the early detection of a submarine assault employing hybrid environment UVs that are controlled using swarm optimization and secure the information in between UVs using a decentralized cybersecurity *** Dragonfly Algorithm is used for the orientation and clustering of the UVs in the optimization approach,and the Re-fragmentation strategy is used in the Network layer of the TCP/IP protocol as a cybersecurity *** research’s noteworthy findings demonstrate UVs’logistical capability to promptly detect the target and address the problem while securely keeping the drone’s geographical *** results suggest that detecting the submarine early increases the likelihood of averting a *** dragonfly strategy of sensing the position of the submersible and aggregating around it demonstrates the reliability of swarm intelligence in increasing access *** communication between Unmanned Aerial Vehicles(UAVs)improves the level of secrecy necessary for the *** swarm navigation is based on a peer-to-peer system,which allows each UAV to access information from its ***,in turn,helps the UAVs to determine the best route to take and to avoid collisions with other *** dragonfly strategy also increases the speed of the mission by minimizing the time spent finding the target.

关键词： Unmanned vehicles unmanned aerial vehicles unmanned underwater vehicles high altitude unmanned aerial vehicles anti-submarine warfare re-fragmentation dragonfly algorithm

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