Improvement in Automated Diagnosis of Soft Tissues Tumors Using Machine Learning by El Arbi Abdellaoui Alaoui, Stéphane Cédric Koumetio Tekouabou, Sri Hartini, Zuherman Rustam, Hassan Silkan, Said Agoujil

“…Therefore, we propose a machine learning-based approach which combines a new technique of preprocessing the data for features transformation, resampling techniques to eliminate the bias and the deviation of instability and performing classifier tests based on the Support Vector Machine (SVM) and Decision Tree (DT) algorithms. The tests carried out on dataset collected in Nur Hidayah Hospital of Yogyakarta in Indonesia show a great improvement compared to previous studies. …”
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DESIGN OF A PROPERTY PRODUCT RECOMMENDATION SYSTEM USING ASSOCIATION RULE METHOD BASED ON USER INTERACTION PATTERNS by Susi Wagiyati Purtiningruma, Yudi Irawan Chandrab, Dian Gustinaa, Nafisah Yuliania, Fahrul Nurzamana, Jhonny Z.Aa, Agus Wismoa

“…Data-driven insights and adaptability improve property search by proposing homes depending on user engagement patterns. Strong algorithms establish location, budget, and property associations, and association rule technology and user interaction patterns increase property recommendations. …”
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UAV Collision Avoidance in Unknown Scenarios with Causal Representation Disentanglement by Zhun Fan, Zihao Xia, Che Lin, Gaofei Han, Wenji Li, Dongliang Wang, Yindong Chen, Zhifeng Hao, Ruichu Cai, Jiafan Zhuang

“…Experimental results demonstrate that our technique achieves reliable navigation and effective collision avoidance in unseen scenarios, surpassing state-of-the-art deep reinforcement learning algorithms.…”
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An explainable sentiment prediction model based on the portraits of users sharing representative opinions in social sensors by Bin Wang, Enhui Wang, Zikun Zhu, Yangyang Sun, Yaodong Tao, Wei Wang

“…Six machine learning algorithms are used to predict emotional tendency based on users’ portraits. …”
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Analysis and Classification of Fake News Using Sequential Pattern Mining by M. Zohaib Nawaz, M. Saqib Nawaz, Philippe Fournier-Viger, Yulin He

“…In this framework, six publicly available datasets, containing a diverse range of fake and real news, and their combination, are first transformed into a proper format. Then, algorithms for SPM are applied to the transformed datasets to extract frequent patterns (and rules) of words, phrases, or linguistic features. …”
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Enhancing Monkeypox Detection through Data Analytics: A Comparative Study of Machine and Deep Learning Techniques by Kinjal A. Patel, Asadi Srinivasulu, Kuntesh Jani, Goddindla Sreenivasulu

“…The findings highlight the potential of these advanced algorithms to aid in controlling outbreaks and curbing the transmission of the disease. …”
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Modular multilevel converter periodic trajectory determination — A generic Fourier-based collocation method by Philippe De Rua, Jef Beerten

“…Being based in the time-domain, the developed method naturally accounts for nonlinearity in the differential equations and, being real-valued, it is solved efficiently with readily available root-finding Newton-based algorithms. In this paper, the proposed method is also applied to an illustrative simple RLC circuit as well as to a complete arm-averaged model of the MMC; it is validated against simulations and compared with a state-of-the-art shooting method.…”
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A data-driven state identification method for intelligent control of the joint station export system by Guangli Xu, Yifu Wang, Zhihao Zhou, Yifeng Lu, Liangxue Cai

“…Compared with the traditional hydraulic calculation modified (THCM) models and other machine learning algorithms, the PSO-GWO-BP model has significant advantages in prediction accuracy. …”
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A Programmable Look-Up Table-Based Interpolator with Nonuniform Sampling Scheme by Élvio Carlos Dutra e Silva Júnior, Leandro Soares Indrusiak, Weiler Alves Finamore, Manfred Glesner

“…As a study case, the proposed interpolator was used as the core of a programmable noise generator—output signals drawn from different Probability Density Functions were produced for testing FPGA implementations of chaotic encryption algorithms. As a result of the proposed method, the interpolation of a specific transformation function on a Gaussian noise generator reduced the memory usage to 2.71% when compared to the traditional uniform sampling scheme method, while keeping the approximation error below a threshold equal to 0.000030518.…”
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Highway Traffic Accident Influence Area Based on Vehicle Bypass Decision-Making Index by Zhenjun Zhu, Yang Lu, Jun Zeng, Hongsheng Chen

“…Under bypass condition, the total number of bypass vehicles is determined based on bypass decision-making index being greater than bypass threshold. Assignment algorithms based on routes were proposed. Using improved Logit model to get the selection probability and the traffic flow of each route, then traffic flow of surrounding links could be obtained. …”
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AI Innovations in rPPG Systems for Driver Monitoring: Comprehensive Systematic Review and Future Prospects by Soha G. Ahmed, Katrien Verbert, Nazar Zaki, Ashraf Khalil, Hamad Aljassmi, Fady Alnajjar

“…This review examines recent advancements in machine learning algorithms and signal processing for rPPG in driver monitoring. …”
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A distributed photovoltaic short‐term power forecasting model based on lightweight AI for edge computing in low‐voltage distribution network by Yuanliang Fan, Han Wu, Jianli Lin, Zewen Li, Lingfei Li, Xinghua Huang, Weiming Chen, Jian Zhao

“…In this regard, this paper proposes a distributed photovoltaic short‐term power forecasting model based on lightweight AI algorithms. Firstly, based on the Pearson correlation coefficient method, an analysis is conducted on the historical operational data in the network to extract important meteorological features that are correlated with the photovoltaic power output. …”
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The use of phase voltage modules to select the damaged phase in case of single-phase earth faults by V. A. Shabanov, A. V. Sorokin

“…The purpose of the article is to investigate the properties and consider the directions of improvement of damaged phase sensors using phase voltage modules, to determine the areas of their selective action depending on the magnitude of the fault resistance at the point of damage. Describe algorithms in which the voter will act selectively both with metal damages and with damages through fault resistance.…”
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Predicting Olympic Medal Trends for Southeast Asian Countries Using the Facebook Prophet Model by Bagus Al Qohar, Yulizchia Malica Pinkan Tanga, Putri Utami, Maylinna Rahayu Ningsih, Much Aziz Muslim

“…However, low-performance regression algorithms are the main problems with prediction. By integrating custom seasonality with the Facebook-Prophet prediction model, this study aims to increase the accuracy of Olympic prediction. …”
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Recent Advancements in Deep Learning Frameworks for Precision Fish Farming Opportunities, Challenges, and Applications by Gaganpreet Kaur, Nirmal Adhikari, Singamaneni Krishnapriya, Surindar Gopalrao Wawale, R. Q. Malik, Abu Sarwar Zamani, Julian Perez-Falcon, Jonathan Osei-Owusu

“…The technical specifics of DL approaches used in smart fish farming which includes data and algorithms as well as performance was also examined. …”
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The role of fMRI in the mind decoding process in adults: a systematic review by Sahal Alotaibi, Maher Mohammed Alotaibi, Faisal Saleh Alghamdi, Mishaal Abdullah Alshehri, Khaled Majed Bamusa, Ziyad Faiz Almalki, Sultan Alamri, Ahmad Joman Alghamdi, Mohammed Alhazmi, Hamid Osman, Mayeen U. Khandaker

“…Studies were selected based on strict inclusion and exclusion criteria: peer-reviewed; published between 2000 and 2024 (in English); focused on adults; investigated mind-reading (mental state decoding, brain-computer interfaces) or related processes; and employed various mind-reading techniques (pattern classification, multivariate analysis, decoding algorithms). Results This review highlights the critical role of fMRI in uncovering the neural mechanisms of mind-reading. …”
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The Comparison of Classical Statistical and Machine Learning Methods in Prediction of Thrombosis in Patients with Acute Myeloid Leukemia by Ilija Doknić, Mirjana Mitrović, Zoran Bukumirić, Marijana Virijević, Nikola Pantić, Nikica Sabljić, Darko Antić, Živko Bojović

“…In order to ascertain which patients are at risk, statistical and machine-learning (ML) algorithms were employed to predict which patients with leukemia will develop thrombosis. …”
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Real-Time Adaptive Content-Based Synchronization of Multimedia Streams by Imad H. Elhajj, Nadine Bou Dargham, Ning Xi, Yunyi Jia

“…Testing adaptive content-based and adaptive time-based synchronization algorithms remotely between the American University of Beirut and Michigan State University showed that the proposed method outperforms the traditional synchronization method. …”
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Design and evaluation of screening and self-care (mobile) application for oral and dental problems and emergencies by Sedighe Sadat Hashemikamangar, Aidin Sooratgar, Mina Khayamzadeh, Shayan Momeni, Ali Asghar Safaei, Behnaz Behniafar

“…Introdution: Although oral and dental diseases may occur in unexpected or even emergency conditions, but some of the diagnosis and treatments can be algorithmically done following some guidelines. The development and implementation of a system that provides users with a record of history and a proposal of required actions can be not only efficiently practical, but also virtually simple. …”
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A Data Fusion System for Simulation of Critical Scenarios and Decision-Making by Jimmy Anderson Flórez Zuluaga, Esteban Patiño Carrasco, Jose David Ortega Pabón, Kelly Gallego León, O. Lucía Quintero Montoya

“…This document describes an investigation product resulted in a simulation system, based on a combination of fuzzy logic, genetic algorithms and decision trees which let modelled and simulated various entities and their automatic response according to simulated patterns and situations, in which, through operators, decision maker can modify entities behaviour, according to parameterized restrictions and physical conditions. …”
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