SE-ResNet based disturbance identification algorithm for microthrust measurement system by Mingming Han

“…The Squeeze-and-Excitation (SE) module is incorporated to optimize the network, as it can adaptively enhance important features. …”
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ASGCL: Adaptive Sparse Mapping-based graph contrastive learning network for cancer drug response prediction. by Yunyun Dong, Yuanrong Zhang, Yuhua Qian, Yiming Zhao, Ziting Yang, Xiufang Feng

“…Personalized cancer drug treatment is emerging as a frontier issue in modern medical research. Considering the genomic differences among cancer patients, determining the most effective drug treatment plan is a complex and crucial task. …”
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Flipped classrooms: Action research to improve practice within an HE nursing context by Matt Smith, Amanda Turner

“…This article explores the importance of careful design when using a flipped classroom to support the learning of an Anatomy and Physiology module for year one undergraduate nursing students. …”
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Bearing remaining useful life prediction based on optimized VMD and BiLSTM-CBAM. by Wei Liu, Sen Liu

“…To address the issue of low accuracy in existing remaining useful life (RUL) prediction algorithms for rolling bearings, this paper proposes a novel RUL prediction method based on the Beluga Whale Optimization (BWO) algorithm, Variational Mode Decomposition (VMD), an improved Convolutional Block Attention Module (CBAM*), and a Bidirectional Long Short-Term Memory (BiLSTM) network. …”
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Metric-based learning approach to botnet detection with small samples by Honggang LIN, Junjing ZHU, Lin CHEN

“…Botnets pose a great threat to the Internet, and early detection is crucial for maintaining cybersecurity.However, in the early stages of botnet discovery, obtaining a small number of labeled samples restricts the training of current detection models based on deep learning, leading to poor detection results.To address this issue, a botnet detection method called BT-RN, based on metric learning, was proposed for small sample backgrounds.The task-based meta-learning training strategy was used to optimize the model.The verification set was introduced into the task and the similarity between the verification sample and the training sample feature representation was measured to quickly accumulate experience, thereby reducing the model’s dependence on the labeled sample space.The feature-level attention mechanism was introduced.By calculating the attention coefficients of each dimension in the feature, the feature representation was re-integrated and the importance attention was assigned to optimize the feature representation, thereby reducing the feature sparseness of the deep neural network in small samples.The residual network design pattern was introduced, and the skip link was used to avoid the risk of model degradation and gradient disappearance caused by the deeper network after increasing the feature-level attention mechanism module.…”
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Screening and Verification COPD-OSA Overlap Syndrome Core Genes Using Bioinformatics by Qiang S, Wan R, Wu J, Wang C, Cui X, Zhang Y

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Systematic Review: How to reduce the car cabin temperature using solar energy? by Noor Al-Huda A.Taher, Ali A . F . Al- Hamadani

“… The two biggest issues we have are the energy crisis and global warming. …”
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Penerapan Importance Performance Analysis (IPA) pada Evaluasi Keberlanjutan Penggunaan e-filing untuk Pelaporan Pajak Perorangan by Imelda Saluza, Dewi Sartika

“…E-filing merupakan bentuk penerapan sistem Modul Penerimaan Negara Generasi Kedua (MPN G2) yang mulai diterapkan pada tahun 2007. …”
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Patient Data Prioritization in the Cross-Layer Designs of Wireless Body Area Network by Fasee Ullah, Abdul Hanan Abdullah, Muhammad Qasim Jan, Kashif Naseer Qureshi

“…Numerous research contributions have been made for addressing these issues of the aforementioned three layers in WBAN. …”
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Design and implementation of solid state drive based on AES and SM4 encryption by Wang Lijuan, Shen Qing, Xu Bin, Yang Chuwei, Hou Qingqing

“…Secure storage of hard drives is a core issue in solid state disk related technologies. Based on the SATA interface, a hardware module is proposed to implement multiple encryption algorithms for SSD storage data encryption and decryption in the design of SSD controllers. …”
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Multi-Dimensional Feature Perception Network for Open-Switch Fault Diagnosis in Grid-Connected PV Inverters by Yuxuan Xie, Yaoxi He, Yong Zhan, Qianlin Chang, Keting Hu, Haoyu Wang

“…However, due to the significant influence of weather conditions on the operating status of PV inverters, the accuracy of traditional fault diagnosis methods faces challenges. To address the issue of open-circuit faults in power switching devices, this paper proposes a multi-dimensional feature perception network. …”
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WELLNESS AT SCHOOL BY PRACTICING CHEERLEADING by I. Nesheva, M. Chipeva

“…The issue for the health of children and youth, their physical culture, and motor activity is becoming increasingly relevant in Bulgarian society. …”
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Underwater Object Detection Method with Enhanced Wavelet Transform Features by Nan WEI, Wankou YANG, Weijie ZHOU, Longyu JIANG

“…These frequency domain feature components were then interactively enhanced using a frequency domain interaction module based on the attention mechanism designed in this work, optimizing the ability of feature expression. …”
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Action-Curiosity-Based Deep Reinforcement Learning Algorithm for Path Planning in a Nondeterministic Environment by Junxiao Xue, Jinpu Chen, Shiwen Zhang

“…By incentivizing agents to explore their surroundings more effectively, the action curiosity module amplifies learning efficiency and curtails training duration. …”
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Fabric Faults Robust Classification Based on Logarithmic Residual Shrinkage Network in a Four-Point System by Canan Tastimur, Erhan Akin, Mehmet Agrikli

“…Accurate and robust detection of fabric defects under noisy conditions is a major challenge in textile quality control systems. To address this issue, we introduce a new model called the Logarithmic Deep Residual Shrinkage Network (Log-DRSN), which integrates a deep attention module. …”
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Enhancing Perception Quality in Remote Sensing Image Compression via Invertible Neural Network by Junhui Li, Xingsong Hou

“…Additionally, a quantization module (QM) is introduced to mitigate format conversion impact, enhancing generalization and perceptual quality. …”
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TSFF-Net: A deep fake video detection model based on two-stream feature domain fusion. by Hangchuan Zhang, Caiping Hu, Shiyu Min, Hui Sui, Guola Zhou

“…In the feature extraction module, we utilize the Scharr operator to extract edge features from facial images, while also integrating frequency domain information from these images. …”
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Digital mapping of soil electrical conductivity for paddy field by The Anh Anh, Luu Trong Hieu, Chi Ngon Nguyen

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Learning Dynamic Spatial-Temporal Dependence in Traffic Forecasting by Chaoyu Ren, Yuezhu Li

“…Specifically, we designed a dynamic graph convolution module to model local and global spatial connections in terms of both road distance and adaptive correlation. …”
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Preparing teachers of Early Childhood Education to teach a foreign language: the PEPELINO portfolio in practice by Joanna Rokita-Jaśkow, Werona Król-Gierat

“…The data analysis revealed that ‘supporting the linguistic development of children with other first languages than Polish’ gained the least support among the respondents, despite a significant course module devoted to this issue. Therefore, the conclusion can be drawn that the teachers will be able to raise interest in language learning by very young learners, by drawing on their experience as Early Childhood Educators, yet it will be difficult to foster plurilingualism and attitudes of intercultural interest by teachers who often lack intercultural experience and plurilingual awareness themselves. …”
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