Analisa Data Penjulan pada Toko Kelontong Musyawarah Menggunakan Algoritma Apriori by Kirana Anastasya Afika Putri Hilman Hilman

“…This study aimed to determine the pattern of the high frequency of items sold in the Musyawarah grocery store using data mining methods. The Apriori algorithm analyzes sales transactions at the Musyawarah grocery store. …”
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Stochastic Planning of Synergetic Conventional Vehicle and UAV Delivery Operations by Konstantinos Kouretas, Konstantinos Kepaptsoglou

“…A nested genetic algorithm is initially used to solve the problem under fixed conditions. …”
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Texture mapping of warp knitted shoe upper based on ARAP parameterization method by Guilong Cheng, Aijun Zhang, Yanting Zhang

“…Additionally, discrete harmonic and parametric optimization unfolding algorithms are employed to enhance texture mapping quality. …”
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Simulation-Based Assessment of the Control of a Hybrid ECS Including a Vapor Cycle System by Arnav Pathak, Victor Norrefeldt

“…The interfacing reveals that some optimization of the control algorithm is possible for the hybrid ECS, while some operational points already perform as intended. …”
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ProCAPTCHA: A profile-based CAPTCHA for personal password authentication. by Nilobon Nanglae, Pattarasinee Bhattarakosol

“…Performance evaluation shows that ProCAPTCHA can identify legitimate users with 100% accuracy, while only 60% of intruders are misclassified as true users. …”
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Quantum reinforcement learning in continuous action space by Shaojun Wu, Shan Jin, Dingding Wen, Donghong Han, Xiaoting Wang

“…Quantum reinforcement learning (QRL) is a promising paradigm for near-term quantum devices. While existing QRL methods have shown success in discrete action spaces, extending these techniques to continuous domains is challenging due to the curse of dimensionality introduced by discretization. …”
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Development of an AI-Based Self-Diagnosis System for Tropical Diseases by Muhammad Haris Nasri, Bayu Wibisanaa, Lilik Widyawati

“…However, challenges remain in cases with limited symptom data, indicating the need for further development to enhance algorithm performance and expand the clinical database…”
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Challenges and Ethical Considerations in Implementing Assistive Technologies in Healthcare by Eleni Gkiolnta, Debopriyo Roy, George F. Fragulis

“…Assistive technologies are becoming an increasingly important aspect of healthcare, particularly for people with physical or cognitive problems. While earlier research has investigated the ethical, legal, and societal implications of AI and assistive technologies, many studies have failed to address real-world obstacles such as data privacy, algorithm bias, and regulatory issues. …”
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Large language models design sequence-defined macromolecules via evolutionary optimization by Wesley F. Reinhart, Antonia Statt

“…Utilizing pre-trained language models can potentially reduce the need for hyperparameter tuning while offering new capabilities such as self-reflection. …”
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An Extended Virtual Force-Based Approach to Distributed Self-Deployment in Mobile Sensor Networks by Jun Li, Baihai Zhang, Lingguo Cui, Senchun Chai

“…To overcome the connectivity maintenance and nodes stacking problems in the traditional virtual force algorithm (VFA), an extended virtual force-based approach is investigated to achieve the ideal deployment. …”
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Dubhe: A Reliable and Low-Latency Data Dissemination Mechanism for VANETs by Lifeng Zhang, Beihong Jin

“…In order to reliably and quickly disseminate the data, we present Dubhe which includes a delay model and an improved greedy broadcast algorithm embedded with a coverage elimination rule. …”
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Intrusion detection method for IoT in heterogeneous environment by LIU Jing, MU Zelin, LAI Yingxu

“…Subsequently, an innovative heterogeneous model aggregation algorithm was introduced, utilizing similarity-weighted coefficients for channel averaging, thereby effectively mitigating the adverse effects of Non-IID data during the model aggregation process. …”
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Pruning Bayesian networks for computationally tractable multi-model calibration by Nicolas Gratius, Mario Bergés, Burcu Akinci

“…In this work, we propose a graph pruning algorithm to reduce computational cost while minimizing the loss in calibration ability by incorporating domain-driven metrics for selection purposes. …”
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Skip-Connected CNN Exploiting BNN Surrogate for Antenna Modelling by Yubo Tian, Jinlong Sun, Zhiwei Zhu

“…The combination of evolutionary algorithms with full-wave electromagnetic (EM) simulation software is an effective method for antenna optimal design. …”
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High-Precision Spotlight SAR Imaging with Joint Modified Fast Factorized Backprojection and Autofocus by Man Zhang, Haolin Li, Guanyong Wang

“…Fast factorized backprojection (FFBP) takes advantage of high accuracy of time-domain algorithms while also possessing high efficiency comparable with conventional frequency domain algorithms. …”
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Normative Production Accounting in the Digital Economy: Issues and Solutions by M. V. Polulekh

“…It was determined that the formula for the normative method requires modification while the algorithm for allocation of indirect costs requires justification and interpretation. …”
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Towards a Scalable and Adaptive Learning Approach for Network Intrusion Detection by Alebachew Chiche, Million Meshesha

“…An integrated approach of machine learning with knowledge-based system is proposed for intrusion detection. While machine learning algorithm is used to construct a classifier model, knowledge-based system makes the model scalable and adaptive. …”
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Thermal pure states for systems with antiunitary symmetries and their tensor network representations by Yasushi Yoneta

“…Thermal pure state algorithms, which employ pure quantum states representing thermal equilibrium states instead of statistical ensembles, are useful both for numerical simulations and for theoretical analysis of thermal states. …”
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Client grouping and time-sharing scheduling for asynchronous federated learning in heterogeneous edge computing environment by Qianpiao MA, Qingmin JIA, Jianchun LIU, Hongli XU, Renchao XIE, Tao HUANG

“…., edge heterogeneity, data Non-IID, and communication resource constraints, a grouping asynchronous federated learning (FedGA) mechanism was proposed.Edge nodes were divided into multiple groups, each of which performed global updated asynchronously with the global model, while edge nodes within a group communicate with the parameter server through time-sharing communication.Theoretical analysis established a quantitative relationship between the convergence bound of FedGA and the data distribution among the groups.A time-sharing scheduling magic mirror method (MMM) was proposed to optimize the completion time of a single round of model updating within a group.Based on both the theoretical analysis for FedGA and MMM, an effective grouping algorithm was designed for minimizing the overall training completion time.Experimental results demonstrate that the proposed FedGA and MMM can reduce model training time by 30.1%～87.4% compared to the existing state-of-the-art methods.…”
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RESEARCH ON PARAMETRIC ANALYSIS AND MULTI-OBJECTIVE OPTIMIZATION OF CYLINDRICAL PRESSURE STRUCTURE by LIU Feng, TU ChaoHua, ZHAO YanKai

“…In order to improve the design efficiency and performance of the cylindrical pressure structure,strength and stability analysis methods were determined,the initial scheme was analyzed. the second development of Abaqus software was carried out by using Python language,Abaqus was integrated with i Sight software,the parametric analysis flow of pressure structure was designed,could realize automatic modeling and analysis of cylindrical pressure structure. the most Latin hypercube method was used to selectting the sample points,the sensitivity analysis of the design variables were carried out,The comparison of the fitting accuracy shown that the response surface model had the highest accuracy,the approximate model of the cylindrical pressure structure based on the fourth-order response surface was obtained. the multi-objective optimization model was established,The second generation of non dominated sorting genetic algorithm was used to solving the multi-objective optimization problem,the results shown that the weight of the optimization scheme was reduced,while the ultimate strength was greatly improved,improved the performance of the cylindrical pressure structure.…”
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