Structured Summarization of League of Legends Match Data Optimized for Large Language Model Input by Jooyoung Kim, Wonkyung Lee, Jungwoon Park

“…This paper introduces the League of Legends Match Data Compactor (LoL-MDC), a tool designed to transform extensive match data into a concise and structured format optimized for LLM processing. By systematically summarizing structured match information—including match overviews, player and team statistics, timeline summaries, and algorithmically selected key events—the LoL-MDC significantly reduces the data size from approximately 80,000 tokens to under 2000 tokens while retaining analytical value. …”
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Collaborative Search Algorithm for Multi-UAVs Under Interference Conditions: A Multi-Agent Deep Reinforcement Learning Approach by Wei Wang, Yong Chen, Yu Zhang, Yong Chen, Yihang Du

“…Due to the NP-hard nature of this problem, we decompose it into two interconnected Markov decision processes (MDPs): a spectrum collaboration subproblem solved using a received signal strength indicator (RSSI)-aware multi-agent proximal policy optimization (MAPPO) algorithm and a search collaboration subproblem addressed through a target probability map (TPM)-guided MAPPO approach with an innovative action-masking mechanism. …”
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NETWORK MODEL AND ALGORITHM FOR SOLVING PROBLEM OF OPTIMUM THERMAL LOAD DISTRIBUTION AMONG HEAT-SOURCES OF ENTERPRISE HEATING SYSTEM by V. A. Sednin, A. D. Korznikov, А. V. Sednin, I. V. Masevich

“…The paper  presents an algorithm for optimization of thermal load distribution among heat-sources in the system of centralized heat supply. …”
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A Subimage Autofocus Bistatic Ground Cartesian Back-Projection Algorithm for Passive Bistatic SAR Based on GEO Satellites by Te Zhao, Jun Wang, Zuhan Cheng, Ziqian Huang, Xueming Song

“…SIAF-BGCBP reduces phase estimation’s complexity by 90% through subimage pixel density optimization while maintaining estimation accuracy. Further enhancement of SIAF-BGCBP via geometric inversion would enable the precise compensation of space-variant phase errors while remaining efficient. …”
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Assessment of medication-related liver and kidney impairment in admitted patients in Depok, Indonesia: an observational study employing the Naranjo algorithm by Nadia Farhanah Syafhan, Ghea Shafa Aldora, Shinta Kamila

“…Implementing strategies to recognize, document, and analyze cases of patient harm related to drug use is crucial for medicines optimization. This study aimed to evaluate the prevalence of medication-related liver and kidney impairment among hospitalized patients, while also identifying the specific medication categories implicated. …”
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A Low Complexity Algorithm for 3D-HEVC Depth Map Intra Coding Based on MAD and ResNet by Erlin Tian, Jiabao Zhang, Qiuwen Zhang

“…To mitigate this challenge, the present paper proposes a deep learning-based encoding algorithm designed to replace the intricate coding unit (CU) partitioning process utilized in HTM. …”
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Optimized workflow for behavior-coupled fiber photometry experiment: improved data navigation and accessibility by Anna Athanassi, Amaury François, Emmanuel Bourinet, Marc Thevenet, Nathalie Mandairon

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Optimizing Airport Land Side Operations: Check-In, Passengers’ Migration, and Security Control Processes by Ludovica Adacher, Marta Flamini

“…The stochastic passengers’ behaviour and their preferences are simulated by a discrete event model, while the managing costs and the passengers’ discomfort are optimized by the Surrogate Method. …”
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Integrated neural network and evolutionary algorithm approach for liver fibrosis staging: Can artificial intelligence reduce patient costs? by Ali Nazarizadeh, Touraj Banirostam, Taraneh Biglari, Mohammadreza Kalantarhormozi, Fatemeh Chichagi, Amir H Behnoush, Mohammad A Habibi, Ramin Shahidi

“…We aim to design and evaluate an artificial neural network (ANN) method by taking advantage of the Teaching Learning‐Based Optimization (TLBO) algorithm for the prediction of liver fibrosis stage in blood donors and hepatitis C patients. …”
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Gene selection based on adaptive neighborhood-preserving multi-objective particle swarm optimization by Sumet Mehta, Fei Han, Muhammad Sohail, Bhekisipho Twala, Asad Ullah, Fasee Ullah, Arfat Ahmad Khan, Qinghua Ling

“…The analysis of high-dimensional microarray gene expression data presents critical challenges, including excessive dimensionality, increased computational burden, and sensitivity to random initialization. Traditional optimization algorithms often produce inconsistent and suboptimal results, while failing to preserve local data structures limiting both predictive accuracy and biological interpretability. …”
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A comprehensive review of AI and machine learning techniques in antenna design optimization and measurement by Pradnya A. Gajbhiye, Satya P. Singh, Madan Kumar Sharma

“…This review examines the latest advancements in applying AI/ML approaches to antenna design optimization. It explores the use of various AI/ML algorithms such as neural networks, decision trees, genetic algorithms, and particle swarm optimization in this context. …”
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URT-YOLOv11: A Large Receptive Field Algorithm for Detecting Tomato Ripening Under Different Field Conditions by Di Mu, Yuping Guou, Wei Wang, Ran Peng, Chunjie Guo, Francesco Marinello, Yingjie Xie, Qiang Huang

“…This study proposes an improved YOLOv11 model to address the limitations of traditional tomato recognition algorithms in complex agricultural environments, such as lighting changes, occlusion, scale variations, and complex backgrounds. …”
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Joint Optimization of UAV Placement and Resource Allocation in FDMA Wireless-Powered Sensor Networks by Omid Abachian Ghasemi, Mehdi Chehel Amirani

“…To solve it, the alternating minimization technique is used, where the problem is divided into subproblems with respect to each of the variables by fixing the others. Efficient algorithms based on the dual Lagrange method and Karush-Kuhn-Tucker (KKT) conditions are proposed for optimal transmission time scheduling and bandwidth allocation. …”
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Lightweight Anomaly-Based Detection Using Cuckoo Search Algorithm and Decision Tree to Mitigate Man-in-the-Middle Attacks in DNS by Ramahlapane Lerato Moila, Mthulisi Velempini

“…By integrating the Cuckoo Search Algorithm, the scheme minimizes false positives while improving the detection rate. …”
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Inertial Subrange Optimization in Eddy Dissipation Rate Estimation and Aircraft-Dependent Bumpiness Estimation by Zhenxing Gao, Qilin Zhang, Kai Qi

“…In current vertical wind-based eddy dissipation rate (EDR) estimation algorithms based on flight data, the inertial subrange is determined empirically. …”
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Hybrid RSA-ROA Scheduling Algorithm for Minimization of Power Loss and Improving the Renewable with Sustainable Energy Harvesting in Power System by Cuddapah Anitha, Virendra Swaroop Sangtani, Ajay Kumar Bansal, Mahaveerakannan R., R. Rajesh Sharma, Saravanan M. S.

“…It is also possible to reduce operating losses in the power system by scheduling ESS and controlled generation at the optimal times. Near global optimal solutions are sought using a hybrid algorithm combining Reptile Search Algorithm and Remora Optimization Algorithm (RSA-ROA). …”
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A multi-factorial evolutionary algorithm concerning diversity information for solving the multitasking Robust Influence Maximization Problem on networks by Minghao Chen, Shuai Wang, Jiazhong Zhang

“…To bridge these gaps, this study integrates the multi-tasking optimisation theory into robust influence maximisation, introducing an evolutionary algorithm called DMFEA. DMFEA concurrently addresses multiple optimization scenarios, leveraging synergy between tasks while emphasizing information diversity. …”
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A Comparative Analysis of Hyper-Parameter Optimization Methods for Predicting Heart Failure Outcomes by Qisthi Alhazmi Hidayaturrohman, Eisuke Hanada

“…This study reveals that while model selection is crucial, an appropriate optimization method and imputation technique significantly impact model performance. …”
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Multi-Objective Optimization of Machinability and Energy Consumption of Cast Iron Depending on Cooling Rate by Burak Öztürk, Fuat Kara

“…Energy efficiency in machining is crucial for sustainable production, and Specific Cutting Energy Consumption (SCEC) has become a key metric in evaluating machinability. Using genetic algorithms (GA) and Response Surface Methodology (RSM), this study optimized machining parameters for energy consumption and surface finish. …”
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SKGRec: A Semantic-Enhanced Knowledge Graph Fusion Recommendation Algorithm with Multi-Hop Reasoning and User Behavior Modeling by Siqi Xu, Ziqian Yang, Jing Xu, Ping Feng

“…Experiments on the Amazon-Book and Last-FM datasets show that SKGRec significantly outperforms several state-of-the-art recommendation algorithms on the Recall@20 and NDCG@20 metrics. Comparison experiments validate the effectiveness of semantic analysis of user behavior and multi-hop path inference, while cold-start experiments further confirm the robustness of the model in sparse-data scenarios. …”
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