Real defect partial discharge identification method for power cables joints based on integrated PJS-M and GA-SVM algorithm with multi-source fusion by Ling-Xuan Zhang, Yi-Yang Zhou, Shen-Jiong Yao, Jia-Luo Chai, Ying-Jing Chen, Zhou-Sheng Zhang

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Research on Side Lobe Suppression of Time-Modulated Sparse Linear Array Based on Particle Swarm Optimization by Lei Liang, Jie Sun, Hailin Li, Jialing Liu, Yachao Jiang, Jianjiang Zhou

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Optimized SPR-PCF sensor for sucrose detection inspired by vertical pupil geometry by Mohammad Reza Khodatars Dashtmian, Vahid Fallahi, Mahmood Seifouri, Saeed Olyaee

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Machine learning and microfluidic integration for oocyte quality prediction by Hassan Saffari, Davood Fathi, Peyman Palay, Hamid Gourabi, Rouhollah Fathi

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Does advancement in marker-less pose-estimation mean more quality research? A systematic review by Shivam Bhola, Shivam Bhola, Hyun-Bin Kim, Hyeon Su Kim, BonSang Gu, Jun-Il Yoo, Jun-Il Yoo

“…Despite the emergence of state-of-the-art keypoint-detection algorithms, the extent to which these tools are employed and the nature of their application in scientific research has yet to be systematically documented. …”
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Research on automatic identification method for pipeline girth weld defects based on X-ray images and sparse representation by Shaohui JIA, Yaping LI, Weixin GAO, Yunchao PENG, Xinjian ZHANG, Yuxia WANG

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To Be competitive or not to be competitive: How performance goals shape human-AI and human-human collaboration by Spatola Nicolas

“…While these tools are used in both private and work contexts, less is known about how the motivational context surrounding algorithm use impacts reliance patterns. This research examined how competitive versus non-performance goals affect adherence to algorithmic versus human recommendation. …”
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An Overview of Deep Learning Applications in Groundwater Level Modeling: Bridging the Gap between Academic Research and Industry Applications by Ahmed Shakir Ali Ali, Farhad Jazaei, Peyman Babakhani, Muhammad Masood Ashiq, Alireza Bakhshaee, Brian Waldron

“…DL models utilize complex algorithms to identify patterns that may be difficult to observe with traditional physics-based models, specifically where the underlying physics is complex or poorly understood or where the available physical model is too simple. …”
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Effective Facial Expression Recognition System Using Artificial Intelligence Technique by Imad S. Yousif, Tarik A. Rashid, Ahmed S. Shamsaldin, Sabat A. Abdulhameed, Abdulhady Abas Abdullah

“…ANNS are inspired by the neural architecture of human brain capable of learning and recognizing patterns in unchartered data after trained examples, on the other hand GAs come from fundamental principles underlying natural selection perform optimization process based-on evolutionary methods which includes fitness evaluation, comparison, selection, crossover, and mutation. …”
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Land Management Dynamics in Social Forestry Permit Using LandTrendr Algorithm: A Case Study in Tuar Tana Community Forest, East Nusa Tenggara Province, Indonesia by Heru Budi Santoso, Wahyu Wardhana, Ronggo Sadono

“…This condition shows that over time, there has been a change in land clearing patterns in the HKm Tuar Tana, from massive land clearing by cutting and burning to selective land clearing adjusted to the growth of non-timber forest products planted in the previous year. …”
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Optimizing urban infrastructure resilience: Analyzing cascading failures and critical node dependencies through multilayer network models by Cong Lu, Jianjun She, Hezhi Pan, Zihao Guo, Xuanling Zhou, Zhijian Li

“…Through simulations of random, PageRank-based, and betweenness-based attack scenarios, we explore failure dynamics and their propagation patterns. Additionally, we evaluate mitigation strategies, with the community periphery augmentation strategy proving most effective, enhancing resilience by linking peripheral nodes between communities. …”
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Development and validation of an interpretable multi-task model to predict outcomes in patients with rhabdomyolysis: a multicenter retrospective cohort studyResearch in context by Chunli Liu, Jie Shi, Fengjuan Wang, Duo Li, Yu Luo, Bofan Yang, Yunlong Zhao, Li Zhang, Dingwei Yang, Heng Jin, Jie Song, Xiaoqin Guo, Haojun Fan, Qi Lv

“…Summary: Background: Rhabdomyolysis (RM) is a complex clinical syndrome with heterogeneous progression patterns among patients of varying severity. Early and accurate prediction of acute kidney injury (AKI), disease severity, renal replacement therapy (RRT) requirements, and mortality risk is essential for timely identification of high-risk individuals, personalized treatment planning, and optimal allocation of healthcare resources. …”
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Enhancing Attendance Management Through Face Recognition Technology: A Case Study at Rugarama School of Nursing and Midwifery. by Taremwa, Benjamin

“…This study, titled "Enhancing Attendance Management through Face Recognition Technology: A Case Study at Rugarama School of Nursing and Midwifery," aimed to develop a more accurate and efficient solution using Local Binary Pattern Histogram and Convolutional Neural Networks algorithms to automate attendance tracking.A mixed-method approach was employed, combining system testing with user feedback from administrators, staff, and students. …”
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Differential Diagnosis of Jejunum and Ileum Tumours Based on Video Capsule Endoscopy Data Using Mathematical Analysis by E. D. Fedorov, E. V. Ivanova, S. E. Rauzina, D. E. Seleznev, A. V. Budykina

“…The aim of this study was to develop an algorithm for identifying various types of jejunum and ileum tumour lesions based on video capsule endoscopy (VCE), which can be used by physicians in the process of decision making. …”
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Overcoming negative weighting in uncertainty-based methods: a multi-uncertainty clustering method for evidence fusion by Zhike Qiu, Yuhao Qin, Zichong Chen, Luping Zeng, Rui Cai

“…Experimental results demonstrate that the proposed method not only resolves the negative weighting problem in existing uncertainty-based weighting methods but also effectively handles highly conflicting evidence, showing advantages in pattern recognition and other application scenarios.…”
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A novel Probabilistic Bi-Level Teaching–Learning-Based Optimization (P-BTLBO) algorithm for hybrid feature extraction and multi-class brain tumor classification using ResNet-50 and... by Mahananda Malkauthekar, Avinash Gulve, Ratnadeep Deshmukh

“…These complementary attributes capture both predominant patterns and detailed texture information from magnetic resonance imaging (MRI) scans, facilitating thorough tumor characterization. …”
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Maximizing theoretical and practical storage capacity in single-layer feedforward neural networks by Zane Z. Chou, Jean-Marie C. Bouteiller, Jean-Marie C. Bouteiller, Jean-Marie C. Bouteiller, Jean-Marie C. Bouteiller

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Diagnosis Method of Blade Stall Based on Data Distribution for Wind Turbine by YIN Yefeng, ZHANG Jiayou, LOU Bin, CHEN Yanan

“…Initially, operating data under normal conditions are screened using the density-based spatial clustering of applications with noise (DBSCAN) algorithm. This is followed by identifying the lower boundary of the data based on the spatial distribution pattern of the operating data under normal conditions. …”
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Concrete Dam Deformation Prediction Model Based on Attention Mechanism and Deep Learning by ZHANG Hongrui, CAO Xin, JIANG Chao, ZU Anjun, XU Mingxiang

“…To address the multi-factor coupling, temporal dependency, and nonlinear complexity characteristics of concrete dam deformation, this paper proposed a hybrid prediction model integrating attention mechanisms, bidirectional long short-term memory (BiLSTM) networks, and sparrow search algorithm (SSA). The model comprehensively matched the multiple requirements of information weighting, temporal dependency modeling, and model optimization in concrete dam deformation prediction, forming a synergistic enhancement effect among methods.The attention mechanism operates on both feature and temporal dimensions to comprehensively enhance the model's focus on critical information. …”
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Optimal fractional order automatic generation control including an excitation system for hybrid interconnected grids by Awadh Ba Wazir, Sultan Alghamdi, Abdullah Ali Alhussainy, Abdulraheem H. Alobaidi, N. Gowtham

“…The hybrid technique consists of two different types of algorithms: the secretary bird optimization algorithm and pattern search. …”
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