Beyond the Trends: Evolution and Future Directions in Music Recommender Systems Research by Babak Amiri, Nikan Shahverdi, Amirali Haddadi, Yalda Ghahremani

“…Factorial analysis uncovers thematic clusters, highlighting collaborative filtering, user experience, emotion identification, and reinforcement learning. A scientific mapping analysis classifies research themes in different historical periods, focusing on essential areas such as collaborative filtering, hybrid recommendation, sentiment analysis, and emotion identification. …”
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Convolutional Neural Networks for Direction of Arrival Estimation Compared to Classical Estimators and Bounds by Christopher J. Bell, Kaushallya Adhikari, Andrew Brown

“…Recently, there has been a proliferation of applied machine learning (ML) research, including the use of convolutional neural networks (CNNs) for direction of arrival (DoA) estimation. …”
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Multimodal Assessment of Changes in Physiological Indicators when Presenting a Video Fragment on Screen (2D) versus a VR (3D) Environment by Elena Kriklenko, Anastasia Kovaleva, Aleksei Klimenko, Usman Dukuev, Sergey Pertsov

“…The increasing role of virtual environments in society, especially in the context of the pandemic and evolving metaverse technologies, requires a closer study of the physiological state of humans using virtual reality (VR) for entertainment, work, or learning. Despite the fact that many physiological reactions to the content presented in various modalities under VR conditions have already been described, often these studies do not reflect the full range of changes in the physiological reactions that occur to a person during their immersion in the virtual world. …”
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Defect Diagnosis of Gear-Shaft Bearing System Based on the OWF-TSCNN Composed of Wavelet Time-Frequency Map and FFT Spectrum 1 by Peng Dai, JianPing Wang, Lulu Wu, ShuPing Yan, FengTao Wang, Linkai Niu

“…In this method, the vibration signals are collected using multiple sensors, the dual-tree complex wavelet and the optimal weighting factor (OWF) methods are used for the data layer fusion, and the preprocessing is realized through wavelet transform and FFT. A learning model based on two-stream CNN composed of 1D-CNN and 2D-CNN is established, and the obtained wavelet time-frequency map and FFT spectrum are used as the input. …”
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Innovative Technology Applications in Science Education: Digital Holography by Hanne Turk, Munise Seckin-Kapucu

“…Moreover, students evaluated the digital hologram as a useful tool that can contribute to academic learning and can be used in science class in the topics such as solar system and planets, space research, and living creatures. …”
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The systematic approach to solving the problem of personnel training based on use of 8D methodologies by L. G. Varepo, L. V. Boyarnikova, E. V. Leongardt

“…The case of identifying the root cause of the problem arising during distance learning for employees of closed-type enterprises has been analyzed, corrective and preventive actions have been developed. …”
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The development of pre-registration occupational therapy student perceptions of research and evidence-based practice: A Q-methodology study by Tanya Rihtman, Mike Morgan, Julie Booth

“…Exploring students’ perceptions of this knowledge area can contribute to effective curriculum design.Aims/Objectives To explore the evolution of pre-registration OT student perceptions of research and EBP over the course of their engagement with undergraduate teaching and learning.Materials and methods The Q-sort approach synthesises different viewpoints regarding a sample of statements, using by-person factor analysis (respondents = variables; statements = sample). …”
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Follow-Up and Risk Assessment in Patients with Myocardial Infarction Using Artificial Neural Networks by Tatjana Gligorijević, Zoran Ševarac, Branislav Milovanović, Vlado Đajić, Marija Zdravković, Saša Hinić, Marina Arsić, Milica Aleksić

“…Artificial neural networks (ANNs) are machine learning technique, inspired by the principles found in biological neurons. …”
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The Importance of Breakfast in Enhancing Students' Focus at School by Nurul Widad Fitri Muhammad, Nur Aina Mardhiah Che Rahim, Amrina Rasyada Kamaruzaman, Noor Fatimah Mujahid, Khairulnazrin Nasir

“…Students who skip breakfast will become hungry, which can disrupt their learning. Islam, as a complete faith, emphasises eating healthy meals. …”
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Assessment of process capabilities in transition to a data‐driven organisation: A multidisciplinary approach by Mert O. Gökalp, Kerem Kayabay, Ebru Gökalp, Altan Koçyiğit, P. Erhan Eren

“…The process dimension consists of five organisational management processes: change management, skill and talent management, strategic alignment, organisational learning, and sponsorship and portfolio management. …”
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Impact and optimization of vehicle charging scheduling on regional clean energy power supply network management by Penghui Xu, Xiaobo Wang, Zhichao Li

“…In particular, the demand forecasting model based on machine learning effectively solves the dilemma of matching the charging load with a clean energy supply. …”
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Synchronization-based graph spatio-temporal attention network for seizure prediction by Jie Xiang, Yanan Li, Xubin Wu, Yanqing Dong, Xin Wen, Yan Niu

“…In recent years, a large number of studies have been conducted using deep learning models on epileptic open electroencephalogram (EEG) datasets with good results, but due to individual differences there are still some subjects whose seizure features cannot be accurately captured and are more difficult to differentiate, with poor prediction results. …”
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Cell Differentiation Trajectory Predicts Prognosis and Immunotherapeutic Response in Clear Cell Renal Cell Carcinoma by Jin Xu, Xi Chen, Yinyu Chen, Qiushuang Wang, Yingliang Jin, Huashuo Zhao

“…Combined with bulk RNA-seq data, we classified patients into two clusters and found that this classification was closely correlated with patient prognosis and immunotherapeutic responses. Based on machine learning, we identified a prognostic risk model composed of 14 DRGs, including BTG2, CDKN1A, COL6A1, CPM, CYB5D2, FOSB, ID2, ISG15, PLCG2, SECISBP2, SOCS3, TES, ZBTB16, and ZNF704, to predict the survival rate of patients and then constructed a nomogram model integrating clinicopathological characteristics and risk score for clinical practice. …”
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Parallel convolutional neural network and empirical mode decomposition for high accuracy in motor imagery EEG signal classification. by Jaipriya D, Sriharipriya K C

“…Additionally, we introduce a transfer learning technique to fine-tune the model for individual subjects, leveraging important features extracted from a group dataset. …”
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Electroacupuncture combined with cognitive rehabilitation outperforms cognitive rehabilitation alone in treating post-stroke cognitive impairment: a randomized controlled trial by Yisha Guo, Tingting Sun, Fengxi Qiu, Xueyi Li, Weiwei Cui, Zhenhua Liao, Jiajia Yao

“…Primary outcomes included the Montreal Cognitive Assessment (MoCA), Digit Span Test (DST), Auditory Verbal Learning Test (AVLT-H), and Aphasia Screening Scale. …”
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Living Group Mosaic Family: participation of people with disabilities in the community by Marta Aoki, Fátima Correa Oliver, Ariane Bazarin de Campos Cancegliero, Júlia Colussi

“…Joining the group promoted emotional changes, discoveries of skills, promotion of care and learning, self-esteem and communication improvement among participants. …”
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Real-time discrimination of earthquake signals by integrating artificial intelligence technology into IoT devices by Zhi Geng, Yanfei Wang, Wenyong Pan, Caixia Yu, Zhijing Bai, Hongzhou Zhang

“…We present an evolutionary deep learning method that yields a model named MCU-Quake. …”
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Non-intrusive load monitoring based on time-enhanced multidimensional feature visualization by Tie Chen, Yimin Yuan, Jiaqi Gao, Shinan Guo, Pingping Yang

“…Furthermore, utilizing transfer learning, the model trained and tested on the PLAID dataset was further tested on the WHITED dataset to increase the model’s universality and generalization ability, showing significant effects in identifying loads with similar V–I trajectories and multiple states.…”
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SurvBeNIM: The Beran-Based Neural Importance Model for Explaining Survival Models by Lev V. Utkin, Danila Y. Eremenko, Andrei V. Konstantinov, Vladimir A. Muliukha

“…It aims to explain predictions of machine learning survival models, which are in the form of survival or cumulative hazard functions. …”
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Perspectives on usability and adoption of a new ACL injury prevention programme for female handball players: a mixed methods approach by Tron Krosshaug, Anne Inger Mørtvedt, Erich J Petushek

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