Utilizing soil–water characteristic curve parameters in custom artificial neural network models to predict the unsaturated hydraulic conductivity by Bashar Alibrahim, Maan Habib, Ahed Habib

“…This study introduces a predictive model utilizing a custom artificial neural network (ANN) based on saturated hydraulic conductivity and critical unsaturated soil parameters from Alibrahim and Uygar’s model. A unique feature of this ANN is the implementation of a filter within its architecture, ensuring predictions remain within logical bounds by prohibiting negative outputs, which are not physically meaningful for this problem. …”
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Phase Retrieval Utilizing Particle Swarm Optimization by Li-Jing Li, Teng-Fei Liu, Ming-Jie Sun

“…However, due to the nonconvex feature of the phase optimization problem, it remains a challenge to globally obtain the optimal phase information. …”
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Intrusion detection in cluster‐based wireless sensor networks: Current issues, opportunities and future research directions by Ayuba John, Ismail Fauzi Bin Isnin, Syed Hamid Hussain Madni, Muhammed Faheem

“…In addition, this research conducted several comparative studies of feature selection techniques and machine learning methodologies in the development of intrusion detection systems. …”
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Efficient approximate Bayesian inference for quantifying uncertainty in multiscale animal movement models by Majaliwa M. Masolele, J. Grant C. Hopcraft, Colin J. Torney

“…In our simulations, individuals respond to two environmental covariates and we employ all combinations of positive and negative selection coefficients corresponding to attraction to an environmental feature and avoidance of an environmental feature, respectively. …”
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High-Speed and Enhanced Motion Control for a Wheeled-Legged Humanoid Robot Using a Two-Wheeled Inverted Pendulum With Roll Joint by Jaewoo An, Jun Young Kim, Myo-Taeg Lim, Yonghwan Oh

“…Meanwhile, the whole-body controller (WBC), based on centroidal momentum, solves an optimization problem via quadratic programming (QP) while incorporating constraints from the rolling contact condition of the wheels and the dynamics of the humanoid robot. …”
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YOLO-Helmet: A Novel Algorithm for Detecting Dense Small Safety Helmets in Construction Scenes by Guoliang Yang, Xinfang Hong, Yangyang Sheng, Liuyan Sun

“…Firstly, in order to solve the problem of difficult detection due to the small area of the helmet in the image, a small size detection layer was extended to improve the detection sensitivity of the network to small size targets. …”
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Boosting the Development and Management of Wind Energy: Self-Organizing Map Neural Networks for Clustering Wind Power Outputs by Yanqian Li, Yanlai Zhou, Yuxuan Luo, Zhihao Ning, Chong-Yu Xu

“…Aimed at the information loss problem of using discrete indicators in wind power output characteristics analysis, a self-organizing map neural network-based clustering method is proposed in this study. …”
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A Variational Neural Network Based on Algorithm Unfolding for Image Blind Deblurring by Shaoqing Gong, Yeran Wang, Guangyu Yang, Weibo Wei, Junli Zhao, Zhenkuan Pan

“…Image blind deblurring is an ill-posed inverse problem in image processing. While deep learning approaches have demonstrated effectiveness, they often lack interpretability and require extensive data. …”
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Effect of Microwave Radiation on the Chemical Composition of Chickpeas by Valentina N. Khramova, Dmitry I. Surkov, Kirill A. Lubchinsky

“…The study featured chickpeas of the Volzhanin variety. The experimental samples were processed in a microwave oven with a magnetron frequency of 2450 MHz at different power and time values. …”
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Existence and Stability of Neutral Stochastic Impulsive and Delayed Integro-Differential System via Resolvent Operator by Hamza Khalil, Akbar Zada, Mohamed Rhaima, Ioan-Lucian Popa

“…Additionally, the systems under consideration feature state-dependent delays (SDDs). To address this, we develop an approach to reformulate the neutral stochastic integro-differential system, incorporating SDDs and non-instantaneous impulses, into an equivalent fixed-point (FP) problem via an appropriate integral operator. …”
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CGTS: graph transformer-based anomaly detection in controller area networks by Xue Zhou, Guihe Qin, Yanhua Liang, Jiaru Song, Wanning Liu, Qingxin Liu

“…While existing anomaly detection strategies offer some benefits, they often face challenges such as limited feature extraction and data imbalance, which reduce their effectiveness. …”
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Research on Design of Intelligent Background Differential Model for Training Target Monitoring by Ya Liu, Fusheng Jiang, Yuhui Wang, Lu OuYang, Bo Gao, Jinling Jiang, Bo Zhang

“…In order to retain the difference of each channel, the information of the foreground images of the three channels is fused to obtain a complete foreground image. The feature of the edge detection is not affected by light; the foreground image is corrected. …”
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Multilevel Space-Time Aggregation for Bright Field Cell Microscopy Segmentation and Tracking by Tiffany Inglis, Hans De Sterck, Geoffrey Sanders, Haig Djambazian, Robert Sladek, Saravanan Sundararajan, Thomas J. Hudson

“…A multilevel aggregation method is applied to the problem of segmenting live cell bright field microscope images. …”
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Railway Cloud Resource Management as a Service by Ivaylo Atanasov, Dragomira Dimitrova, Evelina Pencheva, Ventsislav Trifonov

“…The proposed approach is open, in contrast to any proprietary solutions and feature scalability and interoperability.…”
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Counterfactual Thinking in Tourette’s Syndrome: A Study Using Three Measures by Stefano Zago, Adriana Delli Ponti, Silvia Mastroianni, Federica Solca, Emanuele Tomasini, Barbara Poletti, Silvia Inglese, Giuseppe Sartori, Mauro Porta

“…It is a pervasive cognitive feature in everyday life and it is closely related to decision-making, planning, problem-solving, and experience-driven learning—cognitive processes that involve wide neuronal networks in which prefrontal lobes play a fundamental role. …”
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Drug repositioning framework using embedding drug-protein-disease similarities with graph convolution network and ensemble learning by Hanaa Torkey, Heba El-Behery, Abdel-Fattah Atti, Nawal El-Fishawy

“…The approach proposed in this paper uses a hierarchical network embedding technique and a graph autoencoder (GAE) scheme to solve this problem. The approach extracts embedding feature vectors of drugs and targets from a heterogeneous multi-source network to predict unknown drug-target interactions (DTIs). …”
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An Improved Decision Support System for Identification of Abnormal EEG Signals Using a 1D Convolutional Neural Network and Savitzky-Golay Filtering by Unmesh Shukla, Geetika Jain Saxena, Manish Kumar, Anil Singh Bafila, Amit Pundir, Sanjeev Singh

“…In this study, an improved one-dimensional CNN-only system of 25 layers has been proposed to identify abnormal and normal adult EEG signals using a single EEG montage without using any explicit feature extraction technique. Most of the previous systems based on deep learning, that have been proposed to solve this problem, use extremely deep architectures containing very large numbers of layers. …”
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Fault Diagnosis Method for UHVDC Transmission Based on Deep Learning under Cloud-Edge Architecture by Shihao Zhou, Benren Pan, Dongbin Lu, Yiming Zhong, Guannan Wang

“…Aiming at the problem of fault diagnosis after the UHVDC system fails, a deep learning-based UHVDC fault diagnosis method under the cloud-edge architecture is proposed. …”
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Intelligent Fault Diagnosis of Inter-Turn Short Circuit Faults in PMSMs for Agricultural Machinery Based on Data Fusion and Bayesian Optimization by Mingsheng Wang, Wuxuan Lai, Hong Zhang, Yang Liu, Qiang Song

“…Secondly, applying a traditional CNN to the data fusion of different signals is challenging. To solve this problem, a multi-stream high-level feature fusion algorithm based on a channel attention mechanism is proposed. …”
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Low-Illumination Parking Scenario Detection Based on Image Adaptive Enhancement by Xixi Xu, Meiqi Zhang, Hao Tang, Weiye Xu, Bowen Sun, Zhu’an Zheng

“…Aiming at the problem of easily missed and misdetected parking spaces and obstacles in the automatic parking perception task under low-illumination conditions, this paper proposes a low-illumination parking space and obstacle detection algorithm based on image adaptive enhancement. …”
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