Generalized Shortest Path Problem: An Innovative Approach for Non-Additive Problems in Conditional Weighted Graphs by Adrien Durand, Timothé Watteau, Georges Ghazi, Ruxandra Mihaela Botez

“…Despite this aspect, finding the shortest path between two nodes remains a significant challenge in many applications, as it often becomes complex and time consuming. …”
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Reach&Grasp: a multimodal dataset of the whole upper-limb during simple and complex movements by Dario Di Domenico, Inna Forsiuk, Simon Müller-Cleve, Simone Tanzarella, Florencia Garro, Andrea Marinelli, Michele Canepa, Matteo Laffranchi, Michela Chiappalone, Chiara Bartolozzi, Lorenzo De Michieli, Nicolò Boccardo, Marianna Semprini

“…Abstract Upper-limb movement characterization is crucial for many applications, from research on motor control, to the extraction of relevant features for driving active prostheses. …”
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Vision-based approach to knee osteoarthritis and Parkinson’s disease detection utilizing human gait patterns by Zeeshan Ali, Jihoon Moon, Saira Gillani, Sitara Afzal, Muazzam Maqsood, Seungmin Rho

“…The majority of current studies are concerned with the classification of Parkinson’s disease. Furthermore, many vision-based algorithms rely on human gait silhouettes or gait representations and employ traditional similarity-based methodologies. …”
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X-ray modalities in the era of artificial intelligence: overview of self-supervised learning approach by Ivan Martinović, Shitong Mao, Mehdy Dousty, Wuqi Li, Milena Đukanović, Errol Colak, Ervin Sejdić

“…Self-supervised learning enables the creation of algorithms that outperform supervised pre-training methods in numerous computer vision tasks. …”
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Geometrical Similarities Between Metallic Real and Computationally Simulated Grain Structures (Equiaxed Polygonal Grains) by Adán Ramírez-López, Juan Alberto Alcántara-Cárdenas, Ángel de Jesús Morales-Ramírez, Juliana Guadalupe Rosado-Carrasco

“…Then, computational algorithms and standardized procedures were used for characterization. …”
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A Review on the Security of IoT Networks: From Network Layer’s Perspective by Asma Jahangeer, Sibghat Ullah Bazai, Saad Aslam, Shah Marjan, Muhammad Anas, Sayed Habibullah Hashemi

“…Moreover, we also present a detailed analysis of machine learning-based algorithms and techniques proposed for the security of RPL protocol against internal attacks.…”
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Statistical Learning for Semantic Parsing: A Survey by Qile Zhu, Xiyao Ma, Xiaolin Li

“…In this paper, we review recent algorithms for semantic parsing including both conventional machine learning approaches and deep learning approaches. …”
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Identification of Scientific Texts Generated by Large Language Models Using Machine Learning by David Soto-Osorio, Grigori Sidorov, Liliana Chanona-Hernández, Blanca Cecilia López-Ramírez

“…To do so, we will use natural language processing (NLP) and machine-learning algorithms to recognize texts that mask LLM misuse using different types of adversarial attack, like paraphrasing or translation from one language to another. …”
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A Methodological Study on Expanding the Microarchitectural Design Space of Melt Electrowriting by Kai Cao, Yi He, Anni Wang, Yunpeng Wang, Junyi Song, Jun Zhong, Qisheng Chen, Rongwu Wang

“…ABSTRACT Melt electrowriting (MEW), an advanced additive manufacturing technique for fabricating microfibers, has demonstrated significant potential in tissue engineering applications. While MEW shares many similarities with fused filament fabrication (FFF), the conventional slice‐filling algorithms used in FFF are ill‐suited for MEW, as they fail to address the requirements for continuous toolpaths and diverse microarchitectures. …”
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Standards of Specialized Diabetes Care / Edited by Dedov I.I., Shestakova M.V., Mayorov A.Yu. 11th Edition by I. Dedov, M. Shestakova, A. Mayorov, N. Mokrysheva, E.  Andreeva, O. Bezlepkina, V. Peterkova, E. Artemova, P. Bardiugov, D. Beshlieva, O. Bondarenko, F. Burumkulova, O. Vikulova, N. Volevodz, G. Galstyan, I. Gomova, O. Grigoryan, Z. Dzhemilova, L. Ibragimova, V. Kalashnikov, I. Kononenko, T. Kuraeva, D. Laptev, D. Lipatov, O. Melnikova, M. Mikhina, M. Michurova, O. Motovilin, T. Nikonova, R. Rozhivanov, O. Smirnova, E. Starostina, E. Surkova, O. Sukhareva, A. Tiselko, A. Tokmakova, M. Shamkhalova, E. Shestakova, I. Jarek-Martynowa, M. Yaroslavceva

“…In 2023, Russian diabetology suffered an unbearable loss - Alexander Yuryevich Mayorov, who was the executive editor of the previous issues and an active participant of the work on all the previous editions of “Algorithms” from the moment they were founded, passed away. …”
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Standards of specialized diabetes care. Edited by Dedov I.I., Shestakova M.V., Mayorov A.Yu. 10th edition by Ivan I. Dedov, Marina V. Shestakova, Alexander Yu. Mayorov, Natalya G. Mokrysheva, Olga K. Vikulova, Gagik R. Galstyan, Tamara L. Kuraeva, Valentina A. Peterkova, Olga M. Smirnova, Elena G. Starostina, Elena V. Surkova, Olga Y. Sukhareva, Alla Y. Tokmakova, Minara S. Shamkhalova, Ivona Renata Jarek-Martynova, Ekaterina V. Artemova, Diana D. Beshlieva, Olga N. Bondarenko, Natalya N. Volevodz, Irina S. Gomova, Olga R. Grigoryan, Zera N. Dzhemilova, Roza M. Esayan, Liudmila I. Ibragimova, Viktor Y. Kalashnikov, Irina V. Kononenko, Dmitry N. Laptev, Dmitry V. Lipatov, Olga G. Melnikova, Margarina S. Mikhina, Marina S. Michurova, Oleg G. Motovilin, Tatiana V. Nikonova, Roman V. Rozhivanov, Igor A. Sklyanik, Ekaterina A. Shestakova

“…According to the current estimation by the International Diabetes Federation, 643 million patients will be suffering from DM by 2030 and 784 million by 2045.Like many other countries, Russian Federation experiences a sharp rise in the prevalence of DM. …”
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Dna-storalator: a computational simulator for DNA data storage by Gadi Chaykin, Omer Sabary, Nili Furman, Dvir Ben Shabat, Eitan Yaakobi

“…Keywords: DNA data storage, DNA storage simulator, reconstruction algorithms, clustering algorithms, DNA sequencing errors, DNA synthesis errors, DNA-based data storage…”
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Wearable Internet-of-Things platform for human activity recognition and health care by Asif Iqbal, Farman Ullah, Hafeez Anwar, Ata Ur Rehman, Kiran Shah, Ayesha Baig, Sajid Ali, Sangjo Yoo, Kyung Sup Kwak

“…These measurements and their statistical are then represented in features vectors that used to train and test supervised machine learning algorithms (classifiers) for activity recognition. On the given data set, we evaluate a number of widely known classifiers such random forests, support vector machine, and many others using the WEKA machine learning suite. …”
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Electrification in Maritime Vessels: Reviewing Storage Solutions and Long-Term Energy Management by Ahmet Aksöz, Burçak Asal, Saeed Golestan, Merve Gençtürk, Saadin Oyucu, Emre Biçer

“…This paper contributes to the field by presenting a holistic view of the challenges and solutions associated with the electrification of maritime vessels, aiming to inform future developments and policymaking in this dynamic sector. Unlike many existing reviews that focus exclusively on battery chemistries or energy management algorithms, this manuscript integrates multiple aspects of maritime electrification—including propulsion types, charging infrastructure, grid systems (MVDC), EMS, BMS, and AI applications—into one cohesive systems-level review. …”
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Least to Most Range (LMR): A Novel Consistent Weighting Multicriteria Method Applied to Green Supplier Selection by Vinicius Moretti, Everton L. Melo, Joao Carlos Colmenero

“…Multicriteria decision-making models (MCDM) aim to reduce the complexity of decision-making by using mathematical and algorithmic procedures to guide the process. Given the various issues and complexities that current methods for weighting criteria present; this study aims to develop a new subjective multicriteria method for criteria weighting applied in Green Supplier Selection (GSS). …”
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Wearable Medical Devices: Application Status and Prospects by Xiaowen Wang, Yingnan Gao, Yueze Yuan, Yaping Wang, Anqin Liu, Sen Jia, Wenguang Yang

“…E-skin integrates multiple sensors and intelligent algorithms to automatically analyze data and provide health advice and early warning. …”
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Propensity score methodology for confounding control in health care utilization databases by Elisabetta Patorno, Alessandra Grotta, Rino Bellocco, Sebastian Schneeweiss

“…This article provides an overview of the use of propensity score methodology for pharmacoepidemiologic research with large health care utilization databases, covering recent discussions on covariate selection, the role of automated techniques for addressing unmeasurable confounding via proxies, strategies to maximize clinical equipoise at baseline, and the potential of machine-learning algorithms for optimized propensity score estimation. …”
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Machine Learning Techniques in Chronic Kidney Diseases: A Comparative Study of Classification Model Performance by Nguyen Dong Phuong, Nguyen Trung Tuyen, Vu Thi Thai Linh, Nghi N Nguyen, Thanh Q Nguyen

“…Machine learning models can assist physicians in this task by providing fast and accurate detection. As a result, many health care systems have adopted machine learning, especially for disease diagnosis. …”
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Artificial Intelligence Applied to the Analysis of Biblical Scriptures: A Systematic Review by Bruno Cesar Lima, Nizam Omar, Israel Avansi, Leandro Nunes de Castro

“…Emphasis is given to what types of tasks are being solved, what are the main AI algorithms used, and their limitations. The findings deliver a general perspective on how this field is being developed, along with its limitations and gaps. …”
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A HRWS SAR Motion Compensation Method with Multichannel Phase Correction by Liming Zhou, Minglong Deng, Jing He, Bing Wang, Shengmiao Zhang, Xuanyu Liu, Shunjun Wei

“…However, similar to traditional single-channel SAR systems, it suffers from imaging quality degradation due to motion errors. Many motion compensation algorithms have been used to improve the quality of single-channel SAR images, while fewer studies have been conducted on multichannel SAR motion compensation methods. …”
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