Secure transmission for NOMA downlink based on short packet communication by Gangcan SUN, Shaoke ZHAO, Wanming HAO, Zhengyu ZHU

“…For the low-latency requirements of Internet of things (IoT) business, short packet communication (SPC) and non-orthogonal multiple access (NOMA) were combined to study the problem of secure transmission in the multi-user NOMA system with eavesdroppers.With the maximizing the secure throughput of weak uses as the objective, considering the user decoding error probability constraint, total power constraint and power allocation constraint, a low-complexity power allocation algorithm was proposed to realize secure transmission.In order to solve the problem caused by complex objective function formula and unreliable serial interference cancellation (SIC) technology, the proof that the compactness of the constraints was necessary to find the optimal solution.Under the constraint of maximum decoding error probability, the power constraint was transformed and calculated to obtain the strict limit of transmitting power for strong users, and the transmit power search set from base station to strong user was derived.Then, the one-dimensional search algorithm was used to allocate power resources to maximize the throughput of weak users.Simulation results prove that the proposed algorithm can effectively improve the security throughput of weak users in the system.…”
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Design of a Logistics Nonlinear System for a Complex, Multiechelon, Supply Chain Network with Uncertain Demands by Aaron Guerrero Campanur, Elias Olivares-Benitez, Pablo A. Miranda, Rodolfo Eleazar Perez-Loaiza, Jose Humberto Ablanedo-Rosas

“…The objective function and nonlinear constraints are reformulated as linear formulations, transforming the original nonlinear problem into a mixed integer linear programming model. …”
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Deep Reinforcement Learning for RIS-Assisted Multi-UAV MU-MISO Communication Networks: Sum-Rate and Energy Efficiency Maximization by Alif Rahmatullah Umar, Hasan Albinsaid, Chia-Po Wei, Chih-Peng Li

“…We formulate separate optimization problems for sum-rate and energy efficiency, and address them using deep reinforcement learning (DRL) algorithms, namely proximal policy optimization (PPO) and deep deterministic policy gradient (DDPG). …”
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Software Design for Inventory Management Improvement in a Peruvian National University by Linett Velasquez, Santiago Rubiños, Junior Grados, Juan Grados, Claudia Marrujo

“… The purpose of this study was to design a software to optimize inventory management in the Office of Information Technology and Communications (OTIC) of the Faculty of Industrial Engineering and Systems of the Universidad Nacional del Callao, Peru. …”
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Integrated Train Rescheduling and Rerouting during Multidisturbances under a Quasi-Moving Block System by Peijuan Xu, Dawei Zhang, Jingwei Guo, Dan Liu, Hui Peng

“…In order to adjust the train speed and find the best routes for trains, the set of alternative arcs and alternative arrival/departure paths are considered in the constraints, respectively. Due to this complex NP-hard problem, a two-step algorithm with three scheduling rules based on a commercial optimizer is applied to solve the problem efficiently in a real-word case, and the efficiency, validity, and feasibility of this method are demonstrated by a series of experimental tests. …”
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Prioritized Multi-task Motion Coordination of Physically Constrained Quadruped Manipulators by Aizhen Xie, Xuewen Rong, Guoteng Zhang, Yibin Li, Yong Fan, Zhi Li, Teng Chen

“…To solve this redundant problem, we propose a novel motion coordination framework based on multi-task prioritization and null-space projection. …”
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Proactive Distributed Emergency Response With Heterogeneous Tasks Allocation by Justice Darko, Hyoshin Park

“…This study develops a new proactive framework based on the distributed constraint optimization problem (DCOP) to address the above limitations, overcoming conventional TIM models that cannot accommodate the dependencies in the TIM problem. …”
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Study of the probabilistic and temporal characteristics of wireless networks using the CSMA/CA access method by А. S. Leontyev, D. V. Zhmatov

“…The research involved varying the number of workstations and the intensity of packet flows entering the network nodes under the time constraint on packet transmission. The application of the developed mathematical models will be useful in creating and optimizing wireless networks such as Wi-Fi networks, networks based on the IEEE 802.11 standard, and other data transmission systems using the CSMA/CA access method. …”
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Performance Analysis of Cognitive Radio System Based on Outage Probability of Cognitive Transmission by Haomin Gao, Haifeng Zhao, Xiao Liang, Xiaomin Mu

“…It is an important part to design an optimal spectrum sensing and transmission framework in cognitive radio network.Considering that cognitive data transmission outage had effect on the performance of cognitive radio system,a novel spectrum sensing and transmission model based on the outage probability of cognitive transmission was proposed and the two phases of spectrum sensing and data transmission were jointly optimized.The model was formulated as a nonconvex optimization problem under the constraint of interference to primary user,which maximized the average achievable throughput by the joint optimization of sensing time and data transmission rate and simulated by means of the numerical method.The numerical analysis shows that a better tradeoff can be achieved among the protection of primary user,the throughput of cognitive system and transmission delay when the outage probability is cited and the constraint is satisfied.…”
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Stability and Selective Harvesting of a Phytoplankton-Zooplankton System by Yong Wang, Hongbin Wang

“…The problem of determining the optimal harvest policy is solved by using Pontryagin's maximum principle subject to the state equations and the control constraints, and the impact of tax is also discussed. …”
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Design and experiment of key components of a insertion vegetable grafting machine with six plants synchronous by Yongtao Yu, Yanjun Li, Fuxiang Xie, Jian Song, Yang Bai, Yu Fan

“…The rectangular hand claw is embedded with EVA flexible material (maximum clamping pressure of the clamping mechanism: rootstock 266.35 Pa and scion 158.92 Pa), to overcome the fragile seedling damage control problems; Optimization of rootstock dynamics modeling with the V-shaped gathering block opening angle of 90° to achieve adaptive positioning of heterogeneous stems; The dual cutting system of positive-cutting and rotary-cutting matches the different cutting requirements of rootstock and scion. …”
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Analyzing greedy vaccine allocation algorithms for metapopulation disease models. by Jeffrey Keithley, Akash Choudhuri, Bijaya Adhikari, Sriram V Pemmaraju

“…The allocation of vaccines can be modeled as a discrete optimization problem that prior research has shown to be computationally difficult (i.e., NP-hard) to solve even approximately. …”
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An Explainable Deep Semantic Coding for Binary-Classification- Oriented Communication by Shuhui Wang, Zuxing Li, Xin Huang, Qi Jiang

“…From an information-theoretic perspective, we formulate a semantic coding problem that jointly optimizes data compression rate and classification accuracy subject to distortion constraints. …”
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Clustering-based energy-aware virtual network embedding by Xu Liu, Zhongbao Zhang, Junning Li, Sen Su

“…Virtual network embedding has received a lot of attention from researchers. In this problem, it needs to map a sequence of virtual networks onto the physical network. …”
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Cache Assignment for a Flexible Mobile User in Wireless Heterogeneous Networks by Mohammad Hossein Amerimehr, Parisa Eslami, Nahid Amani, sara Efazati

“…Because of the complexity of the problem, finding the optimal solution is NP-hard. …”
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Deep reinforcement learning applications and prospects in industrial scenarios by JING TAN, Ligang YANG, Xiaorui LI, Zhaolin YUAN, Yunduan CUI, Chao YAO, Zongjie WANG, Xiaojuan BAN

“…Case studies across sectors such as energy management, manufacturing, and process optimization illustrate the versatility and effectiveness of DRL in solving diverse industrial problems. …”
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Unsupervised Learning for Distributed Downlink Power Allocation in Cell-Free mMIMO Networks by Mattia Fabiani, Asmaa Abdallah, Abdulkadir Celik, Omer Haliloglu, Ahmed M. Eltawil

“…This paper aims to introduce a novel unsupervised learning framework for the downlink (DL) power allocation problem in CF-mMIMO networks, utilizing only large-scale fading (LSF) coefficients as input, rather than the hard-to-obtain exact user location or channel state information (CSI). …”
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RETRACTED ARTICLE: Eco-reliable operation based on clean environmental condition for the grid-connected renewable energy hubs with heat pump and hydrogen, thermal and compressed ai... by Aboulbaba Eladeb, Ali Basem, Aman Sharma, Aashim Dhawan, Prabhat Sharma, Mohamed Bouzidi, Lioua Kolsi, Elnaz Naderi Drehshori

“…Subject to the operating model and reliability restrictions of these networks, the suggested strategy seeks to reduce the overall estimated costs of energy procurement, dependability, and emissions within the designated networks. Additional constraints of the problem encompass the operational model of sources and storages, conceptualized as an energy hub. …”
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Improving IoRT Networks: Cross-Tier Resource Allocation for Multi-Antenna UAV Relays in SAGIN by Zahra Khodadadi, Foroogh S. Tabataba, Mohammad Sadegh Fazel, Mehdi Naderi Soorki, Halim Yanikomeroglu

“…The optimization problem aims to minimize the weighted sum of the number of gateways and the total UAV power consumption by jointly optimizing UAV deployment, UAV power allocation, gateway selection, and channel allocation. …”
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Inspection of railway catenary systems using machine learning with domain knowledge integration by Kacper Marciniak, Paweł Majewski, Jacek Reiner

“…The application of machine learning methods to this problem is non-trivial, due to various constraints, including the cost of data acquisition. …”
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