Carbapenemases Produced by Multidrug-Resistant Strains of <i>Klebsiella Pneumoniae</i> Isolated from Intensive Care Patients by T. V. Chernenkaya, L. A. Borisova, T. Yu. Vorobieva, M. A. Godkov, A. K. Shabanov

“…For the purposes of this study, unique sequential K.pneumoniae strains resistant to imipenem and/or meropenem were selected. …”
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Goal-oriented autonomous decision-making for social robots via collaborative interactive inverse reinforcement learning approach by Mingyue Luo, Hui Li, Wanbo Luo, Hewei Li, Jianan Li

“…Abstract Since the practical constraints of unknown pedestrian goal information, research on inverse reinforcement learning (IRL) applied to social robots has focused on trajectory planning based on current motion direction, other pedestrians, and obstacles. …”
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UAV Swarm Confrontation Using Hierarchical Multiagent Reinforcement Learning by Baolai Wang, Shengang Li, Xianzhong Gao, Tao Xie

“…With the development of unmanned aerial vehicle (UAV) technology, UAV swarm confrontation has attracted many researchers’ attention. However, the situation faced by the UAV swarm has substantial uncertainty and dynamic variability. …”
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Continuous Speech for Improved Learning Pathological Voice Disorders by Syu-Siang Wang, Chi-Te Wang, Chih-Chung Lai, Yu Tsao, Shih-Hau Fang

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Efficiently Learning an Encoder That Classifies Token Replacements and Masked Permuted Network-Based BIGRU Attention Classifier for Enhancing Sentiment Classification of Scientific... by Muhammad Inaam Ul Haq, Khalid Mahmood, Qianmu Li, Ashok Kumar Das, Sachin Shetty, Majid Hussain

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Technology of Pesticides and Fertilizers Application with Unmanned Aerial Vehicles in Digital Agriculture by L. A. Marchenko, A. A. Artushin, I. S. Smirnov, T. V. Mochkova, A. Yu. Spiridonov, R. K. Kurbanov

“…(Results and discussion) It was shown that the developed technology includes the sequential execution of information and technological operations in off-line and on-line modes. …”
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Deep reinforcement learning for conservation decisions by Marcus Lapeyrolerie, Melissa S. Chapman, Kari E. A. Norman, Carl Boettiger

“…We provide a conceptual and technical introduction to deep RL as well as annotated code so that researchers can adopt, evaluate and extend these approaches. …”
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Embracing or rejecting AI? A mixed-method study on undergraduate students’ perceptions of artificial intelligence at a private university in China by Yifu Li, Nilo Jayoma Castulo, Xiaoyuan Xu, Xiaoyuan Xu

“…The findings of this study were limited by the small sample size and institution. Future research should explore diverse contexts to develop comprehensive AI implementation frameworks for higher education.…”
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Extremist Ideology Classification in Kazakh: A Multi-Class Approach Using Machine Learning and Psycholinguistic Analysis by Shynar Mussiraliyeva, Milana Bolatbek, Kymbat Baisylbayeva

“…This research provides an effective framework for multilingual text analysis. …”
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BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification by Anderson P. Avila Santos, Breno L. S. de Almeida, Robson P. Bonidia, Peter F. Stadler, Polonca Stefanic, Ines Mandic-Mulec, Ulisses Rocha, Danilo S. Sanches, André C.P.L.F. de Carvalho

“…Recently, deep learning algorithms have provided advancements in ncRNA classification. …”
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Optimal Poisson Cognitive System with Markov Learning Model by A. A. Solodov

“…The aim of the study is to develop a mathematical model of the trained Markov cognitive system in the presence of discrete training and interfering random stimuli arising at random times at its input. The research method consists in the application of the simplest Markov learning model of Estes with a stochastic matrix with two states, in which the transition probabilities are calculated in accordance with the optimal Neуman-Pearson algorithm for detecting stimuli affecting the system. …”
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TARREAN: A Novel Transformer with a Gate Recurrent Unit for Stylized Music Generation by Yumei Zhang, Yulin Zhou, Xiaojiao Lv, Jinshan Li, Heng Lu, Yuping Su, Honghong Yang

“…Music generation by AI algorithms like Transformer is currently a research hotspot. …”
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Interpretable machine learning models for predicting in-hospital mortality in patients with chronic critical illness and heart failure: A multicenter study by Min He, Yongqi Lin, Siyu Ren, Pengzhan Li, Guoqing Liu, Liangbo Hu, Xueshuang Bei, Lingyan Lei, Yue Wang, Qianghong Zhang, Xiaocong Zeng

“…Key predictive variables were identified through recursive feature elimination. A range of ML algorithms, including random forest, K-nearest neighbors, and support vector machine (SVM), were evaluated alongside four other models. …”
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Integrative in Silico modeling for mTOR inhibition: From ridge classifiers to descriptor-free deep neural networks by Seyed Alireza Khanghahi, Hadi Kamkar, Seyedehsamaneh Shojaeilangari, Abdollah Allahverdi, Parviz Abdolmaleki

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Improving the Performance of Electrotactile Brain–Computer Interface Using Machine Learning Methods on Multi-Channel Features of Somatosensory Event-Related Potentials by Marija Novičić, Olivera Djordjević, Vera Miler-Jerković, Ljubica Konstantinović, Andrej M. Savić

“…We systematically tested classification performance using machine learning algorithms, including logistic regression, k-nearest neighbors, support vector machines, random forests, and artificial neural networks. …”
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GA-BPNN Based Hybrid Steering Control Approach for Unmanned Driving Electric Vehicle with In-Wheel Motors by Yong Li, Xing Xu, Wujie Wang

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MEIL-NeRF: Memory-Efficient Incremental Learning of Neural Radiance Fields by Jaeyoung Chung, Kanggeon Lee, Sungyong Baik, Kyoung Mu Lee

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Developing a high-performance AI model for spontaneous intracerebral hemorrhage mortality prediction using machine learning in ICU settings by Xiao-Han Vivian Yap, Kuan-Chi Tu, Nai-Ching Chen, Che-Chuan Wang, Chia-Jung Chen, Chung-Feng Liu, Tee-Tau Eric Nya, Ching-Lung Kuo

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SECONDGRAM: Self-conditioned diffusion with gradient manipulation for longitudinal MRI imputation by Brandon Theodorou, Anant Dadu, Mike Nalls, Faraz Faghri, Jimeng Sun

“…These models are computer algorithms that simulate how information changes. SECONDGRAM addresses data scarcity by generating realistic follow-up MRI imaging features, thereby enriching limited datasets. …”
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Evaluating Deep Learning Architectures for Breast Tumor Classification and Ultrasound Image Detection Using Transfer Learning by Christopher Kormpos, Fotios Zantalis, Stylianos Katsoulis, Grigorios Koulouras

“…These insights are further anticipated to advance future algorithm development and broaden the potential of the research applicability across diverse fields.…”
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