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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Enhancing Smart and Zero-Carbon Cities Through a Hybrid CNN-LSTM Algorithm for Sustainable AI-Driven Solar Power Forecasting (SAI-SPF) by Haytham Elmousalami, Felix Kin Peng Hui, Aljawharah A. Alnaser

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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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Review and Mapping of Search-Based Approaches for Program Synthesis by Takfarinas Saber, Ning Tao

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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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Research on Site Selection and Capacity Determination of Electric Vehicle Public Charging Stations by Integrating K-Means++ and Improved RODDPSO by B. Huang, Z. Wang, J. Chen, B. Zhou, Y. Zhu, Y. Liu

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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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Accelerated preprocessing in task of searching substrings in a string by A. V. Mazurenko, N. V. Boldyrikhin

“…Thus, the algorithms that enable to significantly reduce the time for preprocessing of a set of pattern strings under the condition of using a certain type of alphabet in comparison to the known approach proposed in the Aho- Corasick algorithm are described. …”
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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

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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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Enhancing Education with Machine Learning: Predicting Student Readability Scores by Claire Bell

“…This study explores the use of machine learning techniques to predict students' reading scores, with a particular focus on Random Forest Classification (RFC) as a reliable baseline model. The research leverages a dataset of 1,000 English texts to evaluate and compare the performance of RFC, the Sooty Tern Optimization Algorithm (STOA), and the Gold Rush Optimizer (GRO) in predicting readability ratings. …”
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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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