Surprise Bug Report Prediction Utilizing Optimized Integration with Imbalanced Learning Strategy by Hui Li, Yang Qu, Shikai Guo, Guofeng Gao, Rong Chen, Guo Chen

“…Then these datasets after balancing are used to train three selected classifiers which are built by three different classification algorithms and predict the datasets with unknown type. …”
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Relationship Between Weight Status and Health-Related Quality of Life in School-age Children in China by Mandana Zanganeh, Peymané Adab, Bai Li, Miranda Pallan, Wei J. Liu, Lin Rong, Wei Liu, James Martin, Kar K. Cheng, Emma Frew

“…CHU-9D-CHN utility scores were generated using 2 scoring algorithms (UK and Chinese tariffs). Height and weight measures were taken at school by trained researchers using standardized methods, and BMI _z_ scores were calculated using the World Health Organization 2007 growth charts. …”
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Measuring Passenger Car Equivalents (PCE) for Heavy Vehicle on Two Lane Highway Segments Operating Under Various Traffic Conditions by Pan Lu, Zijian Zheng, Denver Tolliver, Danguang Pan

“…This study introduces an analytical model, combining a headway-based and a delay-based algorithms, for estimating PCEs of HV on a TLTW highway. …”
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Familial Hemiplegic Migraine with Severe Attacks: A New Report with ATP1A2 Mutation by E. Martínez, R. Moreno, L. López-Mesonero, I. Vidriales, M. Ruiz, A. L. Guerrero, J. J. Tellería

“…We identified a variant in heterozygous state in ATP1A2 gene (p.Thr364Met), pathogenic according to different prediction algorithms (SIFT, PolyPhen2, MutationTaster, and Condel). …”
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SOFCs integrated with SMES under dynamic power control using Chernobyl disaster optimizer by Sameh I. Selem, Attia A. El-Fergany, Eid A. Gouda, Mohamed F. Kotb, Islam Ismael

“…The CDO’s convergence patterns and the SOFCs unit’s performance are studied and proved at steady-state by comparing its results to a number of recognized algorithms under varied operating scenarios. A significant SMSE’s values of 3.46 µV2 and 7.38 µV2 are attained at 800οC and 900οC, respectively by the CDO. …”
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A Novel AI-Based Integrated Cybersecurity Risk Assessment Framework and Resilience of National Critical Infrastructure by Sardar Muhammad Ali, Abdul Razzaque, Muhammad Yousaf, Sardar Sadaqat Ali

“…This study proposes a novel technique utilizing ML and DL algorithms for threat detection. We began with data preprocessing, which included cleansing the data, addressing missing values through Multiple Imputation by Chained Equations (MICE), and applying transformations such as encoding and standard scaling. …”
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Priority areas of police bodies’ activity in ensuring the citizens’ rights in the conditions of martial law legal regime in Ukraine by O. I. Bezpalova

“…The need to develop effective algorithms for police actions in conditions of active hostilities and in de-occupied territories has been argued, in particular regarding: demining of territories and buildings by investigative-operational groups equipped with mobile forensic laboratories; identification of collaborators and sabotage groups; recording and documenting war crimes depending on their type; investigation of certain types of war crimes; implementation of measures of police custody, taking into account the significant increase in the number of persons who need such measures; inspections of vehicles on highways and roadblocks; searching for missing persons.…”
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The Impact of AI-Generated Instructional Videos on Problem-Based Learning in Science Teacher Education by Nikolaos Pellas

“…The limited impact of the preview feature highlights the need for careful design and evaluation of instructional elements, such as interactivity and adaptive learning algorithms, to fully realize their potential.…”
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Object Placement Across Robotics, Image Composition, and XR: A Mixed Reality Framework Proposal by Jalal Safari Bazargani, Abolghasem Sadeghi-Niaraki, Soo-Mi Choi

“…This paper provides a comprehensive review of existing research on object placement, identifying key stages such as object and environment representation, placement algorithms, and evaluation metrics. A framework for object placement in MR environments is proposed, which integrates geometric and semantic representations, a human-in-the-loop approach, and real-time interaction features. …”
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Deep Temporal Clustering of Pathological Gait Patterns in Post-Stroke Patients Using Joint Angle Trajectories: A Cross-Sectional Study by Gyeongmin Kim, Hyungtai Kim, Yun-Hee Kim, Seung-Jong Kim, Mun-Taek Choi

“…Through this method, six optimal clusters were selected with a silhouette score of 0.2831, which is a relatively higher value compared to other clustering algorithms. To clarify the characteristics of the selected groups, in-depth statistics of spatiotemporal, kinematic, and clinical features are presented in the results. …”
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SC-ResNeXt: A Regression Prediction Model for Nitrogen Content in Sugarcane Leaves by Zihao Lu, Cuimin Sun, Junyang Dou, Biao He, Muchen Zhou, Hui You

“…Compared with four classical deep learning algorithms, SC-ResNeXt exhibited superior regression prediction performance. …”
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Development and validation of a machine learning-based prediction model for hepatorenal syndrome in liver cirrhosis patients using MIMIC-IV and eICU databases by Fengwei Yao, Ji Luo, Qian Zhou, Luhua Wang, Zhijun He

“…By integrating the MIMIC-IV database and machine learning algorithms, we developed an effective predictive model for HRS in liver cirrhosis patients, providing a robust tool for early clinical intervention.…”
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Palmitoylation-related gene ZDHHC22 as a potential diagnostic and immunomodulatory target in Alzheimer’s disease: insights from machine learning analyses and WGCNA by Sanying Mao, Xiyao Zhao, Lei Wang, Yilong Man, Kaiyuan Li

“…This study applied WGCNA along with three machine learning algorithms—random forest, LASSO regression, and SVM–RFE—to further select key PRGs (KPRGs). …”
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Application of Ultrasound Radiomics in Differentiating Benign from Malignant Breast Nodules in Women with Post-Silicone Breast Augmentation by Ling Hao, Yang Chen, Xuejiao Su, Buyun Ma

“…Eight machine learning algorithms were applied to build predictive models, and their performance was assessed using sensitivity, specificity, area under the ROC curve (AUC), accuracy, Brier score, and log loss. …”
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Scalable and Privacy-Preserving Inter-AS Routing Through Machine-Learning-Based Graph Pruning by Davide Andreoletti, Cristina Rottondi, Silvia Giordano, Andrea Bianco

“…Privacy-preserving shortest path algorithms are then executed on the pruned graph, at a much lower complexity. …”
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Person Detection for an Orthogonally Placed Monocular Camera by Pavel Skrabanek, Petr Dolezel, Zdenek Nemec, Dominik Stursa

“…As the overall price is mainly given by prices of the used sensor and processing unit, we propose the utilization of a visible spectrum camera and data processing algorithms of low time complexity to ensure a low price of the final product. …”
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Approaching maximum resolution in structured illumination microscopy via accurate noise modeling by Ayush Saurabh, Peter T. Brown, J. Shepard Bryan IV, Zachary R. Fox, Rory Kruithoff, Cristopher Thompson, Comert Kural, Douglas P. Shepherd, Steve Pressé

“…On the other hand, supervised algorithms rely on large datasets for training, and often require retraining for new sample structures. …”
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Panoramic radiographic features for machine learning based detection of mandibular third molar root and inferior alveolar canal contact by A. Canberk Ulusoy, Tuğçe Toprak, M. Alper Selver, Pelin Güneri, Betül İlhan

“…Future work should focus on developing automated segmentation algorithms for M3M and IAC on PRs, to identify relevant anatomical structures, thereby improving clinical usability. …”
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Efficient Implementation of Mahalanobis Distance on Ferroelectric FinFET Crossbar for Outlier Detection by Musaib Rafiq, Yogesh Singh Chauhan, Shubham Sahay

“…A huge amount of data is being collected in this era of big data, predominantly for AI/ML algorithms and emerging applications. Considering such voluminous quantities, the collected data may contain a substantial number of outliers which must be detected before utilizing them for data mining or computations. …”
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Application of Gene Expression Programming to Evaluate Strength Characteristics of Hydrated-Lime-Activated Rice Husk Ash-Treated Expansive Soil by Kennedy C. Onyelowe, Fazal E. Jalal, Michael E. Onyia, Ifeanyichukwu C. Onuoha, George U. Alaneme

“…In this work, expansive soil classified as A-7-6 group soil was treated with hydrated-lime activated rice husk ash (HARHA) in an incremental proportion to produce 121 datasets, which were used to predict the behavior of the soil’s strength parameters utilizing the mutative and evolutionary algorithms of GEP. The input parameters were HARHA, liquid limit (wL), (plastic limit wP, plasticity index IP, optimum moisture content (wOMC), clay activity (AC), and (maximum dry density (δmax) while CBR, UCS, and R value were the output parameters. …”
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