A normative principle governing memory transfer in cerebellar motor learning by Hyojin Bae, Jewoo Seo, Chang-Eop Kim, Sang Jeong Kim

“…We model the cerebellum as a dual learning system composed of a complex cortical network and simpler nuclear network, with a cost function that trades off bias, variance, and overhead costs. …”
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Accelerated enzyme engineering by machine-learning guided cell-free expression by Grant M. Landwehr, Jonathan W. Bogart, Carol Magalhaes, Eric G. Hammarlund, Ashty S. Karim, Michael C. Jewett

“…Abstract Enzyme engineering is limited by the challenge of rapidly generating and using large datasets of sequence-function relationships for predictive design. To address this challenge, we develop a machine learning (ML)-guided platform that integrates cell-free DNA assembly, cell-free gene expression, and functional assays to rapidly map fitness landscapes across protein sequence space and optimize enzymes for multiple, distinct chemical reactions. …”
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Buoy and Winch Collaborative Control System Based on Deep Reinforcement Learning by Yang Gu, Jianjun Ni, Zaiming Geng, Bing Zhao, Haowen Yang

“…To overcome the challenge of mathematical modeling of this control system, this research introduces reinforcement learning and transformer models in the design process. …”
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Enhancing challenge-based learning with ChatGPT and product design methodologies by Salvador González-García, Gerardo Loreto-Gomez, Jorge Rodríguez-Arce

“…This study assessed the effectiveness of incorporating product design tools and ChatGPT into a challenge-based learning task, specifically a robotics challenge within a Mechanisms course for mechatronics students. …”
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Deep learning microphone array speech enhancement for multiple speaker separation by Zhang Jiayang, Tong Feng, Chen Dongsheng, Huang Huixiang

“…For the multiple speaker separation scenario, the spatial response cost function of microphone array is constructed and optimized based on deep learning network. …”
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Competency-Based Syllabus and Skills-Based Syllabus of Arabic Learning in College by Nuraini Nuraini

“…Skill-based syllabus organizes materials around the language skills or academic skills that students need to learn the language. further this article present kind and function of syllabus, its also discuss about how to organizing materials to reach goals of arabic learning, and also doscuss some problem encountered in the implementation of the syllabus.…”
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Unsupervised learning of nanoindentation data to infer microstructural details of complex materials by Chen Zhang, Clémence Bos, Stefan Sandfeld, Stefan Sandfeld, Ruth Schwaiger, Ruth Schwaiger

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Trainability and Expressivity of Hamming-Weight Preserving Quantum Circuits for Machine Learning by Léo Monbroussou, Eliott Z. Mamon, Jonas Landman, Alex B. Grilo, Romain Kukla, Elham Kashefi

“…Quantum machine learning (QML) has become a promising area for real world applications of quantum computers, but near-term methods and their scalability are still important research topics. …”
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Laplace Graph Embedding Class Specific Dictionary Learning for Face Recognition by Li Wang, Yan-Jiang Wang, Bao-Di Liu

“…Additionally, in each class dictionary training process, the LGECSDL algorithm introduces the Laplace graph embedding method to the objective function in order to keep the local structure of each class, and the proposed method is capable of improving the performance of face recognition according to the class specific dictionary learning and Laplace graph embedding regularizer. …”
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Accuracy and robustness evaluation of deep learning algorithms in facial recognition systems by Jing Zhang, Ningyu Hu

“…Second, a feature extraction model based on the loss function of the improved FaceNet is constructed. In the medium test dataset validation, the proposed facial detection model improved the detection accuracy by an average of 26.30 % compared with the YOLOv3 series models. …”
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Rolling Cargo Management Using a Deep Reinforcement Learning Approach by Rachid Oucheikh, Tuwe Löfström, Ernst Ahlberg, Lars Carlsson

“…In this paper, we apply state-of-the-art deep reinforcement learning algorithms to automate these operations in a complex and real environment. …”
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Reinforcement Learning Approach to Optimizing Profilometric Sensor Trajectories for Surface Inspection by Sara Roos-Hoefgeest, Mario Roos-Hoefgeest, Ignacio Álvarez, Rafael C. González

“…Key contributions include designing a state space, action space, and reward function tailored for profilometric sensor inspection. …”
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Traffic flow prediction based on improved deep extreme learning machine by Xiujuan Tian, Shuaihu Wu, Xue Xing, Huanying Liu, Heyao Gao, Chun Chen

“…Abstract A new hybrid prediction model is proposed for short-term traffic flow, which is based on Deep Extreme Learning Machine improved by Sparrow Search Algorithm (SSA-DELM). …”
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THE ROLE OF GUIDANCE AND COUNSELING TEACHERS IN OPTIMIZING LEARNING MOTIVATION FOR BROKEN HOME by widyaasriningrum, Nurussakinah Daulay

“…This research aims to determine the role of guidance and counseling teachers in optimizing the learning motivation of broken home students in class VIII (eight) at the Usman Syarif Tanjung Rejo Islamic Boarding School, Medan Sunggal District, Medan City. …”
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Educational aspects of the electronic learning process implementation in the conditions of the economic crisis by Savely Evgenievich Cherkezov, Elena Vladimirovna Efimova, Natalya Alexandrovna Rutta

“…The experience gained in distance learning made it possible to determine the main subsystems that software tools for implementing the distance learning process must meet.…”
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Generalized Score Comparison-Based Learning Objective for Deep Speaker Embedding by Min Hyun Han, Sung Hwan Mun, Nam Soo Kim

“…Furthermore, we propose a generalized loss function for score comparison-based learning, encompassing many conventional training losses and regularization techniques. …”
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Exploration-Driven Genetic Algorithms for Hyperparameter Optimisation in Deep Reinforcement Learning by Bartłomiej Brzęk, Barbara Probierz, Jan Kozak

“…This paper investigates the application of genetic algorithms (GAs) for hyperparameter optimisation in deep reinforcement learning (RL), focusing on the Deep Q-Learning (DQN) algorithm. …”
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Unbiased machine learning-assisted approach for conditional discretization of human performances by Thepparit Banditwattanawong, Masawee Masdisornchote

“…To achieve a fully conditionally norm-referenced performance discretization, this article proposes four novel approaches enlisting a multi-modal technique that incorporates unsupervised machine-learning algorithms and a heuristic method as well as a novel decision function ensuring conditional unbiasedness. …”
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Application of Fault Diagnosis of Seawater Hydraulic Pump Based on Transfer Learning by Yang Miao, Yuncheng Jiang, Jinfeng Huang, Xiaojun Zhang, Lei Han

“…In view of the above situation, a fault diagnosis method of seawater hydraulic piston pump based on transfer learning is proposed. The method decomposes the original sampled fault signal by complementary ensemble empirical mode decomposition (CEEMD) to obtain the intrinsic mode function (IMF) that can characterize the original signal. …”
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Machine learning approach to reconstruct density matrices from quantum marginals by Daniel Uzcategui-Contreras, Antonio Guerra, Sebastian Niklitschek, Aldo Delgado

“…In this work, we propose a machine learning (ML)-based approach to address a specific aspect of the Quantum Marginal Problem: reconstructing a global density matrix compatible with a given set of quantum marginals. …”
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