Aggregation and the economy prototyping of municipality in the conditions of lability and robust changes by O. O. Komarevtseva

“…While writing a scientific article, the methods of situational and simulation modeling, approximation and grouping of specific elements of the structural  object, and the process of algorithmization of functional processes  are used. …”
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Study on the Damage Behavior of Engineered Cementitious Composites: Experiment, Theory, and Numerical Implementation by Tingting Ding, Zhuo Wang, Yang Liu, Xinlong Wang, Tingxin Sun, Shengyou Yang

“…We write the numerical algorithm of our theoretical model in terms of the VUMAT subroutine and implement it into ABAQUS 2019 finite element software. …”
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Research on Automatic Test Case Generation Technology Based on Finite State Machines and Function Block Diagrams by LI Ning, XIONG Yan, DING Yaoguo

“…To deal with these challenges, this paper proposes a model-based testing design methodology. Following the modeling based on finite state machines and function block diagrams, this study explored a transformation algorithm that converts function block diagrams into finite state machines and an automatic test case generation algorithm. …”
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THE POSTMODERN CITY TEXT IN SERHIY ZHADAN’S POETICS by Tetiana M. Starostenko., Ianina V. Gurtova

“…The urban chronotope is marked by location points, endemic for the writer: numerous spatial models of the railway stations, representing a gallery of social characters and algorithms of criminal schemes; bus routes, city transport, personified and serving as the “bodily organs” of the city; industrial facilities; monuments to Soviet leaders; hotels; zoo-images. …”
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Development and Prospects of National Intelligent System for Testing General Language Competencies Deployed Through Neural Network Solutions by E. M. Bazanova, A. V. Gorizontova, N. N. Gribova, T. M. Chikake, A. V. Samosyuk

“…The process of ISTOK development implied, apart from writing test items, putting together databases of writing and speaking assignments marked by professional assessors and assessment criteria for productive skills, as well as algorithms to identify various types of mistakes with the help of artificial intelligence. …”
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Clustering OKU Timur Script Images using VGG Feature extraction and K-Means by Liu Toriko, Susan Dian Purnamasari, Yesi Novaria Kunang, Ilman Zuhri Yadi, Andri Andri

“…Features are extracted using the VGG16 model, which are then clustered with the K-Means algorithm. …”
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Design and optimization of planetary gear train pendulum type sugarcane seeding mechanism based on spatial offset trajectory by Jiaodi Liu, Chaoyuan Luo, Qingli Chen, Jianhao Chen, Jianlong Chen, Yihao Xing

“…Based on the speed requirements of the sugarcane seeds at the critical motion points, a forward kinematics model of this seeding mechanism is established. A multi-objective genetic algorithm combined with the entropy-weight TOPSIS method is used to optimize and screen the installation dimensions of the components of the mechanism so as to keep the motion of the sugarcane seeds stable at the critical positions. …”
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Sentiment Analysis on Google Reviews Using Naïve Bayes, K-Nearest Neighbors, and Logistic Regression to Improve Novotel Services by Yonathan Arya Dhamma, Simon Prananta Barus

“…From the training results, the model produced by the Logistic Regression algorithm was the most accurate, namely 94.54% with unigrams (n = 1). …”
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Detection of Hijaiyah Letters Handwritten in Early Childhood Using Yolov8 by Hidayatul Mustagfiroh, Aviv Yuniar Rahman, Rangga Pahlevi Putra

“…The results showed that YOLOv8 achieved an impressive accuracy of 96.08% in detecting handwritten Hijaiyah letters, with high precision and recall rates further validating the model's reliability. This research highlights the potential of integrating advanced object detection algorithms like YOLOv8 into educational practices. …”
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Multi-Head Attention Based Bidirectional LSTM for Spelling Error Detection in the Indonesian Language by Yanfi Yanfi, Haryono Soeparno, Reina Setiawan, Widodo Budiharto

“…We conducted comprehensive experiments to benchmark the performance of our model against existing models. The findings are interesting, with our model reaching a peak accuracy of 92.26% and greatly exceeding the baseline models, which had the lowest accuracy of 65.72%. …”
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Sentiment Analysis Twitter Bahasa Indonesia Berbasis WORD2VEC Menggunakan Deep Convolutional Neural Network by Hans Juwiantho, Esther Irawati Setiawan, Joan Santoso, Mauridhi Hery Purnomo

“…Word2Vec model for Indonesian is used as a word vector representation. …”
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Design and Experiment of a Single-Disk Silage Corn Harvester by Wenxuan Wang, Wei Sun, Hui Li, Xiaokang Li, Yongwei Yuan

“…In addition, the main program was optimized by writing the program of the SMPSO algorithm. The optimal combination of working parameters was determined: the working speed was 1.00 m/s, the cutter rotation speed was 1085.89 rpm, and the drum rotation speed was 30 m/s. …”
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Bytecode-based approach for Ethereum smart contract classification by Dan LIN, Kaixin LIN, Jiajing WU, Zibin ZHENG

“…In recent years, blockchain technology has been widely used and concerned in many fields, including finance, medical care and government affairs.However, due to the immutability of smart contracts and the particularity of the operating environment, various security issues occur frequently.On the one hand, the code security problems of contract developers when writing contracts, on the other hand, there are many high-risk smart contracts in Ethereum, and ordinary users are easily attracted by the high returns provided by high-risk contracts, but they have no way to know the risks of the contracts.However, the research on smart contract security mainly focuses on code security, and there is relatively little research on the identification of contract functions.If the smart contract function can be accurately classified, it will help people better understand the behavior of smart contracts, while ensuring the ecological security of smart contracts and reducing or recovering user losses.Existing smart contract classification methods often rely on the analysis of the source code of smart contracts, but contracts released on Ethereum only mandate the deployment of bytecode, and only a very small number of contracts publish their source code.Therefore, an Ethereum smart contract classification method based on bytecode was proposed.Collect the Ethereum smart contract bytecode and the corresponding category label, and then extract the opcode frequency characteristics and control flow graph characteristics.The characteristic importance is analyzed experimentally to obtain the appropriate graph vector dimension and optimal classification model, and finally the multi-classification task of smart contract in five categories of exchange, finance, gambling, game and high risk is experimentally verified, and the F1 score of the XGBoost classifier reaches 0.913 8.Experimental results show that the algorithm can better complete the classification task of Ethereum smart contracts, and can be applied to the prediction of smart contract categories in reality.…”
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A multimodal approach for ADHD with coexisting ASD detection for children by Jungpil Shin, Sota Konnai, Md. Maniruzzaman, Yoichi Tomioka, Yong Seok Hwang, Akiko Megumi, Akira Yasumura

“…The experimental results demonstrated that the proposed SFFS-SVM model achieved a classification accuracy of 96.4% for PL task. …”
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METRICS FOR EVALUATING CONSISTENCY IN DISTRIBUTED DATASTORES by Galyna Zholtkevych

“…This decision-making algorithm should be suitable for any business model and its requirements. …”
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Klasifikasi Kelas Kata (Part-Of-Speech Tagging) untuk Bahasa Madura Menggunakan Algoritme Viterbi by Ilham Firmansyah, Putra Pandu Adikara, Sigit Adinugroho

“…Part-Of-Speech Tagging research on Madurese language using Viterbi algorithm, consists of 3 processes, which are training and testing corpus pre-processing, training the corpus by Hidden Markov Model, and tag classification using Viterbi algorithm. …”
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Integrating Ambient In-Home Sensor Data and Electronic Health Record Data for the Prediction of Outcomes in Amyotrophic Lateral Sclerosis: Protocol for an Exploratory Feasibility S... by William E Janes, Noah Marchal, Xing Song, Mihail Popescu, Abu Saleh Mohammad Mosa, Juliana H Earwood, Vovanti Jones, Marjorie Skubic

“…ResultsAs of this writing (fall 2024), machine learning algorithms are currently in development to predict those health outcomes from sensor-detected changes in health status. …”
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Application of time series database technology in coal mine safety monitoring system by Hongliang ZHANG

“…A dynamic time sharding storage strategy is proposed for 2 Hz high-frequency data streams, combined with an improved run length encoding compression algorithm (RLE-X), to achieve a stable write throughput of ≥ 1 000 data streams per second and a storage space compression rate of over 85%. …”
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Completeness of the Dynamics of the Attributes Values of Data in the Database DIM by A. N. Petrov, V. S. Roublev

“…This paper is devoted to justifying the possibility of DBMS DIM usage and its interaction mechanism as an algorithmically complete implementation of an objectdynamic model. …”
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Advancements and challenges in inverse lithography technology: a review of artificial intelligence-based approaches by Yixin Yang, Kexuan Liu, Yunhui Gao, Chen Wang, Liangcai Cao

“…The review tracks recent advancements of ILT in model improvement and algorithmic efficiency. Challenges such as extended computational runtimes and mask-writing complexities are summarized, with potential solutions discussed. …”
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