Confirmation of driving principle by weight analysis of Integration Neural Network and extension of deductive approximator by Yoshiharu IWATA, Hidefumi WAKAMATSU

“…The integral neural network is a linear approximator using deductive knowledge that constrains the shape of the approximate curve between learning points by multiple regression analysis in which the basis function is determined by deductive information and an inductive learning method that suppresses overlearning of the linear approximator by compensating factors that are not expressed in the basis function by deductive information of the linear approximator. …”
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Bag-of-words is competitive with sum-of-embeddings language-inspired representations on protein inference. by Frixos Papadopoulos, Tilman Sanchez-Elsner, Mahesan Niranjan, Ashley I Heinson

“…By feature selection we show that the top discriminant features help bag-of-words capture important information for data-driven function prediction. These findings could have important implications for self-supervised learning models on protein sequences, and might encourage the consideration of alternative pre-training schemes for learning representations that capture more meaningful biological information from the sequence alone.…”
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KESANTUNAN TINDAK TUTUR IMPERATIF DALAM PENGAJARAN BAHASA INGGRIS PADA MAHASISWA DI KABUPATEN DHARMASRAYA by Lusiana Lusiana, Nidya Fitri

“…Imperatives  politeness strategy are nessecary in the process of teaching and learning, particularly in the English language teaching. …”
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Evaluating the Accuracy and Performance of ChatGPT-4o in Solving Japanese National Dental Technician Examination by Hikaru Fukuda, Masaki Morishita, Kosuke Muraoka, Shino Yamaguchi, Taiji Nakamura, Manabu Habu, Izumi Yoshioka, Shuji Awano, Kentaro Ono

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Using Image Feature Extraction to Identification of Ancient Ceramics Based on Partial Differential Equation by Chuanbao Niu, Mingzhu Zhang

“…In this paper, we propose a deep learning-based extraction method, using Eased as a deep learning support platform, to extract and validate 5834 images of 272 types of ancient ceramics from kilns, celadon, and Yue kilns after manual labelling and training learning, and the results show that the average complete extraction rate is higher than 99%. …”
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Generation of mitochondrial reactive oxygen species is controlled by ATPase inhibitory factor 1 and regulates cognition. by Pau B Esparza-Moltó, Inés Romero-Carramiñana, Cristina Núñez de Arenas, Marta P Pereira, Noelia Blanco, Beatriz Pardo, Georgina R Bates, Carla Sánchez-Castillo, Rafael Artuch, Michael P Murphy, José A Esteban, José M Cuezva

“…Transcriptomic, proteomic, and metabolomic analyses indicate that IF1 dose regulates mitochondrial metabolism, synaptic function, and cognition. Ablation of IF1 impairs memory, whereas synaptic transmission and learning are enhanced by IF1 overexpression. …”
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Intelligent interference decision algorithm with prior knowledge embedded LSTM-PPO model by ZHANG Jingke, YANG Kai, LI Chao, WANG Hongyan

“…Focusing on the issues of low efficiency and effectiveness in decision-making as well as the instability of traditional reinforcement learning model-based multi-function radar (MFR) jamming decision algorithms, a prior knowledge embedded long short-term memory (LSTM) network-proximal policy optimization (PPO) model based intelligent interference decision algorithm was developed. …”
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English Web-Based Teaching Supervision Based on Intelligent Face Image Perception and Processing for IoT by Juan Ma, Jiangyi Li

“…In the intelligent learning environment, learners mainly learn by watching the information presentation screen of the learning content, i.e., the learning screen, which is the main environment for learners to learn and is the main channel for information interaction between learners and the learning content. …”
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Analysis of Comprehensive Artificial Neural Network Computer Media Aided Construction of Economic Forecasting Model by Tianfeng Li

“…ANN is an abstract model of the human brain neuronal network based on the information-processing perspective and composed of different networks to achieve a specific representation of logical strategies. ANN’s self-learning function, associative storage function, and the ability to find optimal solutions at high speed have led to its in-depth application and research in an increasing number of fields. …”
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Downstream Semantic Segmentation Model for Low-Level Surface Crack Detection by Thitirat Siriborvornratanakul

“…This study proposes a new approach of using downstream models to accelerate the development of deep learning models for pixel-level crack detection. An off-the-shelf semantic segmentation model named DeepLabV3-ResNet101 is used as a base model and then experimented with different loss functions and training strategies. …”
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Autonomous Maneuver Decision of UCAV Air Combat Based on Double Deep Q Network Algorithm and Stochastic Game Theory by Yuan Cao, Ying-Xin Kou, Zhan-Wu Li, An Xu

“…Secondly, the convolutional neural network (CNN) is used to process the high-dimensional continuous situation features of UCAV in air combat, eliminate the correlation and redundancy between situation features, and train the neural network to approximate the action-value function. Then, the double deep Q network (DDQN) algorithm in reinforcement learning (RL) is introduced to train the agent by the interaction with the environment and combined with Minimax algorithm in stochastic game theory to solve the optimal value function in each specific state, and the optimal maneuver decision of UCAV is obtained. …”
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Construction of movement-sleep-study (MSS) collaborative intervention model based on biological rhythm regulation by BINYANG LI

“… Introduction: Biological rhythms regulating movement, sleep, and study significantly impact cognitive function and academic performance. However, conventional educational models often overlook their integration, leading to cognitive fatigue and reduced learning efficiency. …”
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A weak edge estimation based multi-task neural network for OCT segmentation. by Fan Yang, Pu Chen, Shiqi Lin, Tianming Zhan, Xunning Hong, Yunjie Chen

“…With the development of deep learning, deep learning-based methods are becoming more popular for fundus OCT image segmentation. …”
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An Optimized Path Planning Method for Coastal Ships Based on Improved DDPG and DP by Yiquan Du, Xiuguo Zhang, Zhiying Cao, Shaobo Wang, Jiacheng Liang, Fengge Zhang, Jiawei Tang

“…On the other hand, the traditional reward function of DDPG may lead to low learning efficiency and convergence speed of the model. …”
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Computational design of diverse nuclear factor erythroid 2 activators with cellular antioxidative activity by Mingyue Yuwen, Xiaoning Gao, Junli Ba, Jiayang Wu, Jun Kang, Sheng Ye, Cheng Zhu

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Pembelajaran Bahasa Indonesia dan Sastra (BASASTRA) di SD dan MI by Ummul Khair

“…The learning of Bahasa Indonesia in curriculum 13 is the learning based on the text, text is an application of the thing in the human mind which is complete with the situation and context. …”
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Application of EEG-Based Brain-Computer Interface Technology in Stroke Rehabilitation by SHU Yuhong, FU Jianming, YAO Yunhai, ZENG Ming, GU Xudong

“…Patients with stroke often suffer from motor, cognitive and speech function disorders, which seriously affect their quality of life. …”
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DEVELOPMENT OF RESEARCH-BASED BIOLOGICAL MODULES ON CHARACTERISTICS OF LEAVES EPIDERMIS AND ITS DERIVATIVES OF Solanum lycopersicum var. Cerasiforme and Solanum lycopersicum cv. Ra... by Zuchrotus Salamah, Selawati Selawati, Hadi Sasongko

“…The study aimed to determine the feasibility of the modules developed for class XI learning on the structure and function of plant tissues based on the results of research on the characteristics of the epidermis and epidermal derivatives of cherry tomato leaves and rose tomato leaves. …”
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Research on intrusion detection model based on synchronization of heterogenous executer by YU Hong, ZHU Zhengbin, WEI Shuai, GUO Wei, LAN Julong

“…Intrusion detection and cybersecurity situational awareness technologies based on machine learning and deep learning have generally been limited by their reliance on prior knowledge and pre-training, which restricts their accuracy in detecting various types of attacks. …”
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Modeling the spatial relationship between bike-sharing stations and urban centrality using geographical weight variables by Jianyu Li, Mingxing Hu, Xinyu Zhang, Bing Han, Junheng Qi, Jiemin Zheng, Hui Wang

“…This study explores a new approach for including spatial characteristics in machine learning models based on a kernel function in a station-based bike-sharing (SBBS) dataset. …”
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