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Deep Reinforcement Learning Based throughput Maximization Scheme for D2D Users Underlaying NOMA-Enabled Cellular Network 1

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11th international Advanced Computing conference, IACC 2021

作者： Vishnoi, Vineet Malik, Praveen Kumar Budhiraja, Ishan Yadav, Ashima School of Electronics and Electrical Engineering Lovely Professional University Punjab Phagwara India Lovely Professional University Punjab Phagwara India Bennett University Uttar Pradesh Greater Noida India

ISBN: (数字)9783030955021

ISBN: (纸本)9783030955014

Device-to-Device (D2D) communication is a potential technology that efficiently reuses spectrum resources with CMUs in a fifth-generation (5G) underlay and even beyond the network. It improves network capacity and spectral efficiency at the cost of co-channel interference. Moreover, massive connectivity has not been fully exploited for efficient spectral efficiency usage in the existing solutions. To resolve the aforementioned issues, we combine non-orthogonal multiple access (NOMA) approaches with cellular mobile users (CMUs) in order to improve their throughput while preserving the signal-to-interference noise ratio (SINR) offered by CMUs and D2D mobile pairs (DMPs). the problem of power allocation is formulated as mixed-integer non-linear programming, which is then transformed to machine learning using the markov decision process (MDP). then, a deep reinforcement learning (DRL) approach is proposed for solving the continuous optimisation problem in a centralised fashion. Furthermore, to achieve better performance and a faster convergence rate, the higher proximal policy optimization (PPO) scheme is employed. Numerical results reveal that the proposed algorithm outperformed state-of-the-art schemes in terms of throughput. © 2022, Springer Nature Switzerland AG.

关键词： Reinforcement learning

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Lightweight Automatic Business Card Generator Utilizing the Swift Language

Lightweight Automatic Business Card Generator Utilizing the ...

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international conference on Information Technology (INCIT)

作者： Pawit Limpasuthum Datchakorn Tancharoen Robotic and Artificial Intelligence Program Panyapiwat Institute of Management Demonstration School Nonthaburi Thailand Faculty of Engineering and Technology Panyapiwat Institute of Management Nonthaburi Thailand

Business cards have always been a traditional item for any professional’s repertoire; it allows the receiver to get a basic idea of who the sender is and what organization they belong to. However, this requires said professionals to design and create their cards if they are not affiliated with any business entity. this process can take up a large sum of time and skills that may not be in the scope of the person in question. this paper aims to develop an application that automatically generates a usable digital business card simulated in a three-dimensional plane. the application will also act as an exploration of the Swift Language, developed by Apple Inc. Swift and its frameworks are relatively new to the programming scene; therefore, this paper will test their capabilities and potential to be implemented in other firms like other programming languages.

关键词： Graphics Computer languages Switches Standardization Receivers User interfaces Software

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Optimal Design of Heliostat Field Using Random Search Algorithm

Optimal Design of Heliostat Field Using Random Search Algori...

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IEEE international conference on Power, Intelligent Computing and Systems (ICPICS)

作者： Chenglin Mou Kaiqi Wu Pengcheng Du Kaibo Yang Department of Engineering Mechanics School of Civil Engineering and Architecture Henan University of Science and Technology Luoyang China Department of Computer Science and Technology School of Information Engineering Henan University of Science and Technology Luoyang China Department of Automation School of Information Engineering Henan University of Science and Technology Luoyang China Department of Civil Engineering School of International Education Henan University of Science and Technology Luoyang China

ISBN: (数字)9798350374315

ISBN: (纸本)9798350374322

Tower solar thermal power generation is a new type of low-carbon and environmentally friendly clean energy technology. In this paper, a single-objective optimization model is established with the maximum annual average thermal output per unit mirror area of the heliostat field as the objective function. By optimizing the heliostat width, heliostat height and heliostat coordinate, the annual average output thermal power can be maximized while meeting the rated power. the heliostat field is distributed in a circular shape. As the seasons change, the light intensity received by the heliostat field is uneven, so the optical efficiency of the heliostats is also different. We simplify the heliostat field into S area (area with higher optical efficiency) and W area (area with lower optical efficiency) based on the optical efficiency distribution of heliostats. At different locations, According to the heliostat width, heliostat height and heliostat coordinate generated by random functions, substituting these parameters into the efficiency model in this paper, and the random search algorithm is used to traverse the maximum annual output thermal power and the corresponding heliostat parameters. In the shadow occlusion loss model, we have grid to set up the heliostat and use the coordinate conversion to solve the shadow occlusion loss efficiency.

关键词： Integrated optics Green energy Shape Optimization models Computational modeling Poles and towers Linear programming Mirrors Power generation

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Research on PCI Planning Problem Based on Genetic Algorithm and Sequential Algorithm

Research on PCI Planning Problem Based on Genetic Algorithm ...

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IEEE international conference on Power, Intelligent Computing and Systems (ICPICS)

作者： Haoming Sun Yu Sun Ye Lu Jiajun Chen Yixuan Qu School of Physics and Optoelectronic Engineering Shandong University of Technology Zibo City Shandong Province China School of Electrical and Electronic Engineering Shandong University of Technology Zibo City Shandong Province China School of Computer Science and Technology Shandong University of Technology Zibo City Shandong Province China School of Electrical and Electronic Engineering Shandong University of and Technology Zibo City Shandong Province China School of Materials Science and Engineering Shandong University of and Technology Zibo City Shandong Province China

ISBN: (数字)9798350374315

ISBN: (纸本)9798350374322

With the rapid development of mobile communication technology, the construction of the 5G network has become a hotspot worldwide. In this context, rational PCI network planning becomes particularly important. this study takes an area as an example and establishes a multi-objective optimization model based on genetic algorithm (GA) and sequential algorithm (SA) for the PCI planning problem in mobile communication system. By collecting and analyzing key data such as cell numbers and MR data, the objective function Fit is established, and the genetic algorithm is applied to solve the problem with the objective of minimizing the conflict, confusion and the sum of the number of MRs of modulo 3 interference in the PCI allocation, and with the PCI value allocated to each cell as the decision variable. the results show that the method can effectively improve network coverage and system capacity, reduce interference between users, and improve user experience.

关键词： Optimization models Interference Minimization Linear programming User experience Robustness Planning Steady-state Resource management Genetic algorithms

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Aligning Objects as Preprocessing Combined with Imitation Learning for Improved Generalization

Aligning Objects as Preprocessing Combined with Imitation Le...

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international conference on Control and Robots (ICCR)

作者： Mücahid Barstuğan Shimpei Masuda Ryusuke Sagawa Fumio Kanehiro Department of Electrical and Electronics Engineering Konya Technical University Konya Türkiye CNRS-AIST JRL (Joint Robotics Laboratory) IRL National Institute of Advanced Industrial Science and Technology Tsukuba Japan Artificial Intelligence Research Center National Institute of Advanced Industrial Science and Technology Tsukuba Japan

ISBN: (数字)9798331518158

ISBN: (纸本)9798331518165

Imitation learning method transfers human behavior to the robots or machines. this method aims to allow robots or machines to learn by observing tasks performed by human operators and imitating these tasks, rather than direct programming. ACT as an imitation learning method shows the high capability for automating dexterous manipulation tasks. From the viewpoint of industrial application, pose of the target object will be varied. However, even if only for the initial object pose variation, imitation learning method like ACT usually needs a lot of demonstration data that covers pose variation to train the policy that can generalize for. Collecting large demonstration dataset takes many efforts. this study created an object pick-and-place controller to eliminate pose variation as a preprocess step with YOLOv8, which is a recent object detection technique. the preprocess step automatically moves the object to a specific position and eliminates the pose variation. We show that our system effectiveness on the randomly placed bag opening task that requires both generalization for object pose variation and dexterous bimanual manipulation. the bag opening task was conducted with ACT and preprocess applied ACT methods, and the results were evaluated to examine the effect of the preprocess method to generalization process.

关键词： Service robots Imitation learning Object detection programming Behavioral sciences

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Demand side management integrated intelligence algorithms for dynamic economic emission dispatch of distribution systems

Demand side management integrated intelligence algorithms fo...

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international conference on Condition Assessment Techniques in Electrical Systems (CATCON)

作者： Srikant Misra Pratap Kumar Panigrahi Bishwajit Dey Ph.D Scholar Dept of EEE GIET University Gunupur Gunupur India Dept. of EEE GIET University Gunupur Gunupur India Dept. of Electrical Engineering GIET University Gunupur Rayagada India

Power distribution costs are no longer just a utility’s responsibility. Instead, in order to fulfil the soaring demand for power, the utilities place a strong emphasis on reducing the amount of harmful chemicals that are released into the environment. In this study, the distribution system for 15 units is subjected to dynamic economic emission dispatch (DEED) both with and without demand side control (DSM). Every hour, the elastic loads are ideally scheduled by DSM and moved to times when the price of power is lowest. this serves to lower the system’s peak demand, lower the cost of its generation, and raise its load factor. For the subject distribution test system, DEED is carried out using the price-penalty factor (PPF) technique and fractional programming (FP) approach, and a comparison between the two is based on which method emits the fewest hazardous and poisonous chemicals into the environment.

关键词： Demand side management Costs Heuristic algorithms Power distribution programming Valves Dynamic programming

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Sentiment Analysis of Google Classroom Application Using Support Vector Machine

Sentiment Analysis of Google Classroom Application Using Sup...

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international conference on Electrical, Telecommunication and Computer engineering (ELTICOM)

作者： Nismah Panjaitan Natasya Manurung Department of Industrial Engineering Universitas Sumatera Utara Medan Indonesia

ISBN: (纸本)9798350320725

Technological advances are growing very rapidly and affect human life and also have an impact during the pandemic. During the pandemic, Google Classroom ranks first on the platform that is often used during distance learning. On the Google Play site, many reviews about the application. Due to the many reviews given by users, sentiment analysis is carried out so that public opinion on the application is known, thus users or application developers know the advantages and disadvantages of the application. Sentiment analysis was carried out using the SVM algorithm with the help of the python programming language on google colab. From the results of sentiment analysis, the sentiment of Google Classroom application users is 64% negative sentiment and 36% positive sentiment with an algorithm accuracy of 81%. In addition, data visualization is carried out, so that it can be seen what causes users to give positive reviews and negative reviews, from which priority improvements are obtained to improve Google Classroom performance.

关键词： Support vector machines Sentiment analysis Computer aided instruction Pandemics Data visualization programming Communications technology

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Optimizing Industrial Energy Systems: A Multi-Objective Approach to Decarbonization and Cost Efficiency

Optimizing Industrial Energy Systems: A Multi-Objective Appr...

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Smart Power & Internet Energy Systems (SPIES), international conference on

作者： Simon Kammerer Constantin Chaumet Christian Rehtanz Jakob Rehof Institute of Energy Systems Energy Efficiency and Energy Economics TU Dortmund University Dortmund Germany Department of Computer Science Software Engineering by Algorithms and Logic TU Dortmund University Dortmund Germany Lamarr Institute for Machine Learning and Artificial Intelligence TU Dortmund University Dortmund Germany

ISBN: (数字)9798350368864

ISBN: (纸本)9798350368871

the transition to a renewable energy (RE) based future necessitates transformative changes in the industrial sector's energy infrastructure. As industries strive to maintain economic viability while achieving decarbonization goals, there is a pressing need for innovative strategies that integrate renewable energy sources, enhance energy efficiency, and optimize energy procurement. this paper presents a comprehensive approach that leverages a combination of simulation and optimization methods to address the challenges of designing and operating complex future industrial energy systems. A nested optimization approach is proposed, which combines Mixed-Integer Linear programming (MILP) for operational optimization with black-box optimization techniques. the approach enables exploration of solutions for optimal infrastructure investment as well as operational strategies, allowing companies to benchmark a wide range of infrastructure and contractual options. this provides these companies with the means to determine long-term, cost-effective pathways that minimize CO2 emissions, avoid malinvestments, and ensure the sustainable operation of energy systems. A case study involving a German waste processing company illustrates the practical application of our approach, highlighting how strategic decisions in asset dimensioning, energy flexibility utilization, and renewable integration can significantly impact both costs and emissions.

关键词： Procurement Renewable energy sources Costs Closed box Optimization methods Companies Pressing Low carbon economy Mixed integer linear programming Investment

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Quantification of Fault Trees with CCFs Using PINN

Quantification of Fault Trees with CCFs Using PINN

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international conference on System Reliability and science (ICSRS)

作者： Joonseok Lim Gyunyoung Heo Department of Nuclear Engineering Kyung Hee University Yongin-si Republic of Korea

Research is being conducted to quantify fault trees (FTs) using physics-informed neural networks (PINNs). Based on the previous study, this work attempted to quantify FTs considering common cause failures (CCFs). the binomial failure rate (BFR) model is used to obtain the failure rate data required for continuous-time Markov chain (CTMC) which takes a role of an objective function in PINN. For better training performance, it is necessary to reduce the size of Q matrix of CTMC. the proposed method compares the PINNs among an original Q matrix, a reduced Q matrix, and an exact solution. the proposed method not only reduced learning time, but also showed improved accuracy.

关键词： Training Neural networks Markov processes Linear programming Data models Computational efficiency Safety

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Expression of Concern for: Real-Time Innovation in Future Generation Security for Data Privacy Intrusion System in Machine Learning Approach

Expression of Concern for: Real-Time Innovation in Future Ge...

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international conference on Contemporary Computing and Informatics (IC3I)

作者： Hansaraj Shalikram Wankhede R. Venkatesh Sumit Pundr Ravikiran Madala Kamunuri Ganapathi Babu Badepally Mallaiah Department of artificial Intelligence G H Raisoni college of Engineering Nahpur Maharashtra India Department of Computer Science and Engineering Karpagam College of Engineering Coimbatore Tamilnadu India Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun Uttrakhand India University of Cumberlands Durham North Carolina US. Department of Computer Science and Engineering St. Martin's Engineering College Secunderabad Telangana India Department of Information Technology CVR College of Engineering Hyderabad Telangana India

ISBN: (数字)9798350304480

ISBN: (纸本)9798350304497

programming called an intrusion discovery system watches over a solitary PC or an organization of PCs for pernicious movement that intends to take or edit data or change network conventions. Most of intrusion recognition methods utilized today are unequipped for guarding against the dynamic and perplexing nature of cyber-attacks on PC organizations. Albeit successful versatile procedures, for example, unique machine learning calculations, may prompt more noteworthy discovery rates, diminished deception rates, and suitable calculation and transmission costs. Data mining might be utilized to make miniature data streams, classification, and example mining rather frequently. the real-time intrusion identification system and related intrusion counteraction system are introduced in this work utilizing machine learning. To prepare the model, a convolutional brain organization (CNN) is utilized. A 5G data network assessment of the innovation was directed. the improvement of programming characterized networks is thought about by brilliant intrusion location systems (IDS). It utilizes man-made reasoning based demonstrating. Convolutional brain network-based programming parts empower the system to distinguish intrusions that were not recently recognized. Intrusion Prevention System “IPS” is to stop malicious traffic. Based on the evaluation, this solution provides more buffers than comparable alternatives, facilitating real-time management in 5G settings.

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