Development and Investigation of Vision System for a Small-Sized Mobile Humanoid Robot in a Smart Environment by Amer Tahseen Abu-Jassar, Hani Attar, Ayman Amer, Vyacheslav Lyashenko, Vladyslav Yevsieiev, Ahmed Solyman

“…Finally, a number of experiments were carried out, both in static and dynamic environments, which showed a high accuracy of identifications.…”
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Data-driven fault detection and positioning of eccentric rolls in roll-to-roll systems using wrap angle and sensor proximity by Yoonjae Lee, Minjae Kim, Jaehyun Noh, Gyoujin Cho, Changwoo Lee

“…By leveraging tension data, optimal feature sets are identified, emphasizing the Mean, Fast Fourier Transform, and other key variables that capture crucial system dynamics, including wrap angles and sensor proximities. Classification algorithms were used to compare the performance of models employing these optimized FCM-based features against traditional models utilizing a full suite of 40 statistical features. …”
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Artificial Intelligence in Education: Analysis and Assessment of Legal Knowledge Using AI Tools by Anvar J. Khurramov, Mavluda A. Axmedshaeva, Fiyuza A. Mukhitdinova, Gulnora A. Xudayberdiyeva, Shahnoza S. Almosova, Makhmud M. Makhamatov, Sherzod R. Khayitov

“…The study examined ethical concerns such as algorithmic bias, transparency, and student privacy, as well as legal dimensions related to consent, data protection, and institutional responsibility. …”
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Analysis of Minerals Using Handheld Laser-Induced Breakdown Spectroscopy Technology by Naila Mezoued, Cécile Fabre, Jean Cauzid, YongHwi Kim, Marjolène Jatteau

“…The extensive spectral range covered by the analyzer spectrometers (190–950 nm) allowed for the detection of both major (>1 wt.%) and trace (<1 wt.%) elements, recording a unique spectral signature for each mineral. …”
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Ancient and contemporary shellfish cultivation practices bolster bivalve communities and diversity‐biomass relationships by Kieran D. Cox, Hailey L. Davies, Ben Millard‐Martin, Morgan Black, Margot Hessing‐Lewis, Nicole F. Smith, Francis Juanes, Sarah E. Dudas

“…We examined these data using a combination of diversity indices, structural complexity metrics, non‐parametric multivariate statistics and supervised machine learning algorithms. We show that both cultivation methods create distinct biological communities, with community composition proportional to how each cultivation practice alters the habitats' substrate, sediment and physical complexity. …”
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Structural insights into SOD1: from in silico and molecular dynamics to experimental analyses of ALS-associated E49K and R115G mutants by Seyed Mahdi Hosseini Faradonbeh, Bagher Seyedalipour, Nasrin Keivan Behjou, Kimiya Rezaei, Payam Baziyar, Saman Hosseinkhani

“…Protein stability is a crucial characteristic that influences both protein activity and structure and plays a significant role in several diseases. …”
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A Temporal Convolutional Network–Bidirectional Long Short-Term Memory (TCN-BiLSTM) Prediction Model for Temporal Faults in Industrial Equipment by Jinyin Bai, Wei Zhu, Shuhong Liu, Chenhao Ye, Peng Zheng, Xiangchen Wang

“…Traditional algorithms and single predictive models often face challenges such as limited prediction accuracy and insufficient modeling capabilities for complex time-series data in fault prediction tasks. …”
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Selection of a Complex of Informative Features for Assessing the Internal Characteristics of Eggs for Consumption by Toncho Kolev, Mariya Georgieva-Nikolova, Miglena Kazakova, Danail Bonchev, Hristo Lukanov, Zlatin Zlatev

“…This paper concerns the methods and algorithms developed for tracking changes in the internal characteristics of eggs during storage that emphasize rapid and simple classification and satisfactory regression accuracy, considering technological requirements. …”
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Renji endoscopic submucosal dissection video data set for colorectal neoplastic lesions by Jinnan Chen, Xiangning Zhang, Jinneng Wang, Tang Cao, Chunjiang Gu, Zhao Li, Yiming Song, Liuyi Yang, Zhengjie Zhang, Qingwei Zhang, Dahong Qian, Xiaobo Li

“…Recognition systems for endoscopic surgical phases using deep learning algorithms heavily rely on comprehensive annotated datasets. …”
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An Automated Image-Based Dietary Assessment System for Mediterranean Foods by Fotios S. Konstantakopoulos, Eleni I. Georga, Dimitrios I. Fotiadis

“…Based on the EfficientNet family of CNNs, we use the EfficientNetB2 both for the pre-trained model and its weights evaluation, as well as for classifying food images in the MedGRFood dataset. …”
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Non-Destructive Monitoring of External Quality of Date Palm Fruit (<i>Phoenix dactylifera</i> L.) During Frozen Storage Using Digital Camera and Flatbed Scanner by Younes Noutfia, Ewa Ropelewska, Zbigniew Jóźwiak, Krzysztof Rutkowski

“…Accordingly, confusion matrices showed high classification accuracy (CA), which could reach 0.84 at M0 for both cultivars at the two frozen storage temperatures. …”
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Residential Electricity Load Model Construction in District Scale by Jieyan XU, Wenyang XU, Yuan CHU, Yuan JIN, Xuyuan KANG, Zheng CHEN

“…The electricity consumption data of urban scale has high-dimensional characteristics in both spatial scale and temporal span. Characterizing the district-scale electricity consumption is the principal difficulty. …”
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Optimum Combination of Spectral Variables for Crop Mapping in Heterogeneous Landscapes based on Sentinel-2 Time Series and Machine Learning by J. G. de Oliveira Júnior, J. C. D. M. Esquerdo, J. C. D. M. Esquerdo, R. A. C. Lamparelli, R. A. C. Lamparelli

“…Subsequently, the variables that showed the highest statistical correlation between each other were used in the spectro-temporal classification process, using the Random Forest, TempCNN, and LightTAE algorithms, following three different strategies: C1 (ALL), C2 (BE + IV _{(Red Edge)}) and C3 (BE + IV _{(without Red Edge)}), where ALL &ndash; All variables; BE &ndash; Spectral Bands; IV &ndash; Vegetation Indices. …”
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Application of Internet Hospitals in the Disease Management of Patients With Ulcerative Colitis: Retrospective Study by Tianzhi Yu, Wanyu Li, Yingchun Liu, Chunjie Jin, Zimin Wang, Hailong Cao

“…Intelligent diagnosis refers to the use of artificial intelligence–driven algorithms to analyze patient-reported symptoms, generate diagnostic probabilities, and provide treatment recommendations through interactive tools. …”
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Automated interpretation of deep learning-based water quality assessment system for enhanced environmental management decisions by Javed Mallick, Saeed Alqadhi, Majed Alsubih, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo

“…Abstract Water quality assessment is a critical issue in the Aseer region of Saudi Arabia, where environmental and anthropogenic factors pose a major challenge to both drinking water and irrigation systems. The aim of this study was to carry out a detailed assessment of the water resources in the region, focussing on the most important aspects affecting water quality. …”
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Simple energy detector for two-stage classification for antidrone systems by Zurovac Snežana, Petrović Nikola, Joksimović Vasilija, Pokrajac Ivan, Mikanović Darko, Sazdić-Jotić Boban

“…Furthermore, we conducted a comparative analysis of different deep learning algorithms at the outset of twostage classification, which is a potential basis for adopting this approach.…”
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Exploration of shared pathogenic factors and causative genes in early-stage endometrial cancer and osteoarthritis by Yiyun Bai, Sang Luo, Ruzhen Shuai, Xiaomei Zhang, Liwei Yuan, Dan Liu

“…Genes with diagnostic value were identified using multiple machine learning algorithms to construct EC prediction models and evaluate their performance. …”
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Prediction of in-hospital mortality in patients with ST-segment elevation acute myocardial infarction after percutaneous coronary intervention by B. I. Geltser, K. I. Shahgeldyan, I. G. Domzhalov, N. S. Kuksin, E. A. Kokarev, V. N. Kotelnikov, V. Yu. Rublev

“…ULR was used to determine their weight coefficients characterizing the predictive potential. IHM predictive algorithms based on GRACE scale predictors, represented both by ULR model and by 5 factors in continuous MLR model, had acceptable predictive accuracy (AUC — 0,83 and 0,86, respectively). …”
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Predicting neoadjuvant chemotherapy response in locally advanced gastric cancer using a machine learning model combining radiomics and clinical biomarkers by Tong Ling, Zhichao Zuo, Liucheng Wu, Jie Ma, Tingan Wang, Mingwei Huang

“…Results Among the ML models tested, the random forest (RF) model performed best when both the rad score and clinical biomarkers were used as input features, leading to our hybrid model development. …”
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AI-powered approaches for enhancing remote sensing-based water contamination detection in ecological systems by Li Yang, Zhang Ziwen, Xinhao Lin, Junmiao Hei, Yixiao Wang, Ang Zhang

“…IntroductionWater contamination poses a significant threat to both public health and ecosystems worldwide, leading to increased emphasis on developing robust detection and mitigation strategies. …”
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