A lightweight D2D security protocol with request-forecasting for next-generation mobile networks by Daniel Gerbi Duguma, Jiyoon Kim, Sangmin Lee, Nam-Su Jho, Vishal Sharma, Ilsun You

“…The protocol relies on a new network function, called D2D Security Management Function (DSMF), located near the devices to facilitate secure communication and improve performance. …”
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A Study of Potential Applications of Student Emotion Recognition in Primary and Secondary Classrooms by Yimei Huang, Wei Deng, Taojie Xu

“…Firstly, the study adds the self-made MCC module and the Wise-IoU loss function to make object detection in the YOLOv8 model more accurate and efficient. …”
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Solving UAV 3D Path Planning Based on the Improved Lemur Optimizer Algorithm by Haijun Liang, Wenhai Hu, Ke Gong, Jie Dai, Lifei Wang

“…A Gaussian function model is used to simulate the mountain environment, and a mathematical model for UAV flight is established based on constraints and objective functions. …”
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Small target detection in UAV view based on improved YOLOv8 algorithm by Xiaoli Zhang, Guocai Zuo

“…The MPDIoU (Minimum Point Distance based IoU) loss function is improved, and the idea of inner-IoU loss function is adopted as a way to improve the model’s learning ability for difficult samples. …”
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The EMC acts as a chaperone for membrane proteins by Carolin J. Klose, Kevin M. Meighen-Berger, Martin Kulke, Marina Parr, Barbara Steigenberger, Martin Zacharias, Dmitrij Frishman, Matthias J. Feige

“…In this study, we characterize an additional chaperone function of the EMC. We use interactomics and systematic studies with model proteins to comprehensively define client features for this EMC chaperone mode. …”
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Operation Optimization Strategy of Commercial Combined Electric Heating System Based on Particle Swarm Optimization Algorithm by WANG Qing, LI Congcong, WANG Pingxin, WU Qingqing, CAI Xiaoyu

“… In order to improve the energy efficiency of the electric heating system, a particle swarm optimization (PSO, Particle Swarm Optimization)-based operation optimization strategy for the direct storage combined electric heating system is proposed.A mathematical model of influencing factors inside and outside the walls of electric heating buildings is established, and the simulink toolbox in matlab is used to build the overall system under the premise of determining the quantity of electric heating.Combining demand response ideas, the objective function is to establish the minimum heating and electricity cost of the user, and different sub-modules are selected to form the control module to achieve simulation verification, and the inverse cosine method is used to update the improved particle swarm algorithm to update the learning factor to solve the set objective function.Finally, through a calculation example of electricity consumption data of an enterprise in Jinan, Shandong, comparing energy consumption and economy can be obtained: the total energy consumption throughout the day is lower than the actual energy consumption, and the electricity bill is reduced by 17.16% compared with the unoptimized time.…”
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Protein structural domain-disease association prediction based on heterogeneous networks by Jingpu Zhang, Lianping Deng, Lei Deng

“…Abstract Background Domains can be viewed as portable units of protein structure, folding, function, evolution, and design. Small proteins are often found to be composed of only a single domain, while most large proteins consist of multiple domains for achieving various composite cellular functions. …”
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Multilingual education

“…By engaging with linguistic diversity, students develop analytical skills and a better grasp of how languages function. Classroom Practices: Several articles describe classroom projects and activities where students explore languages through stories, songs, comparisons, and multilingual materials. …”
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Systems Biology of Human Microbiome for the Prediction of Personal Glycaemic Response by Nikhil Kirtipal, Youngchang Seo, Jangwon Son, Sunjae Lee

“…This mini-review explores the relationship between multiomics, precision medicine, and machine learning to improve our understanding of the gut microbiome’s function in diabetes. …”
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Features of anxiety and attention in elementary school students of the Russian North by Olga P. Bartosh, Tatiana P. Bartosh, Marina V. Mychko

“…Methods — we used the methodology of multidimensional assessment of childhood anxiety (MACA). To investigate the function of attention, we used the method of proofreading modified by V.N. …”
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Local Culture-Based Education in the Hidden Curriculum: A Strategy for Fostering Tolerance and Peace in Maluku Secondary Schools by Simona Christina Henderika Litaay, Feky M. L. Manuputty, Afdhal Afdhal, Nathalia Debby Makaruku

“…It investigates the influence of traditions such as Pela, Gandong, Famili, Badati, Masohi, and Ma’anu, which are not formally included in the curriculum but play a crucial role in shaping students’ social behavior and fostering inclusive learning environments. Using a qualitative case study approach, the research provides a contextualized analysis of how these cultural values function within school settings. …”
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A Short-Term Solar Photovoltaic Power Optimized Prediction Interval Model Based on FOS-ELM Algorithm by G. Ramkumar, Satyajeet Sahoo, T. M. Amirthalakshmi, S. Ramesh, R. Thandaiah Prabu, Kasipandian Kasirajan, Antony V. Samrot, A. Ranjith

“…Stage two entails creating a one-of-a-kind PI based on cost function to enhance the ELM limitations and quantify noise uncertainty in respect of variance. …”
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Aptamer based proteomic pilot study reveals a urine signature indicative of pediatric urinary tract infections. by Liang Dong, Joshua Watson, Sha Cao, Samuel Arregui, Vijay Saxena, John Ketz, Abduselam K Awol, Daniel M Cohen, Jeffrey M Caterino, David S Hains, Andrew L Schwaderer

“…The best prediction was achieved by the SVMs with radial basis function kernel.<h4>Conclusions</h4>Biomarkers panel can be identified by the emerging technologies of aptamer-based proteomics and machine learning that offer the potential to increase UTI diagnostic accuracy, thereby limiting unneeded antibiotics.…”
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Application model of “Internet+Marketing service” virtual robot under dung beetle optimizer algorithm by HE Wei, ZHOU Yutian, YU Yang, KANG Yumeng, ZHU Meng, QIAN Xusheng

“…The test results show that the normal operation rate of the model and system in functional experiments, non functional experiments, and safety experiments reach 100%, which can achieve human-machine interaction function and the strategic goal of accurate response to customer needs.…”
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Research on the evaluation method of cooperative jamming effectiveness based on IPSO-ELM by A. Tianjian Yang, B. Xing Wang, C. Siyi Cheng, D. You Chen, E. Xi Zhang

“…For the problem of evaluating the effectiveness of cooperative jamming to group network radar by formation aircraft, a cooperative jamming effectiveness evaluation method based on Improved Particle Swarm Optimization–Extreme Learning Machine (IPSO-ELM) is proposed. First, based on the working parameters of the group network radar and the information fusion rules, the cooperative jamming effectiveness evaluation function is established. …”
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Discrete Dynamic Berth Allocation Optimization in Container Terminal Based on Deep Q-Network by Peng Wang, Jie Li, Xiaohua Cao

“…A novel deep Q-network (DQN)-based model is proposed, leveraging a custom state space, rule-based actions, and an optimized reward function to dynamically allocate berths and schedule vessel arrivals. …”
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Development of a Basilar Membrane-Inspired Mechanical Spectrum Analyzer Using Metastructures for Enhanced Frequency Selectivity by Shantanu H. Chavan, Vijaya V. N. Sriram Malladi

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High-fidelity EEG feature-engineered taxonomy for bruxism and PLMS prognostication through pioneering and avant-garde ML frameworks by Shivam Tiwari, Deepak Arora, Barkha Bhardwaj

“…This work applies machine learning and data mining approaches to examine these changes. …”
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Novel Gaussian-Decrement-Based Particle Swarm Optimization with Time-Varying Parameters for Economic Dispatch in Renewable-Integrated Microgrids by Yuan Wang, Wangjia Lu, Wenjun Du, Changyin Dong

“…An improved particle swarm optimization algorithm with time-varying parameters of the inertia weight and learning factor was designed to solve the optimal dispatching strategy. …”
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Data-Driven Robust Optimization for Solving the Heterogeneous Vehicle Routing Problem with Customer Demand Uncertainty by Jingling Zhang, Mengfan Yu, Qinbing Feng, Longlong Leng, Yanwei Zhao

“…We improve the deep Q-learning-based reinforcement learning algorithm for the fleet size and mix vehicle routing problem to solve the robust model. …”
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