Proficient Node Scheduling Protocol for Homogeneous and Heterogeneous Wireless Sensor Networks by R. Saravanakumar, N. Mohankumar, J. Raja

“…In this paper, we propose an energy-efficient node scheduling reclustering algorithm in clusters and rotating cluster-head positions to evenly distribute the energy load among all of the nodes by the node scheduling concept of node active and sleep system in both homogeneous and heterogeneous methods to get energy-saving result. …”
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A Time-Aware CNN-Based Personalized Recommender System by Dan Yang, Jing Zhang, Sifeng Wang, XueDong Zhang

“…With the in-depth study and application of deep learning algorithms, deep neural network is gradually used in recommender systems. …”
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Modeling and control design of a bronchoscope robotics system by Yuhua Song, Lifeng Zhu, Jinfeng Li, Cheng Wang, Aiguo Song

“…Therefore, we use the boundary control algorithm to design a controller capable of suppressing vibration for the inserting tube. …”
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Prediction of Epileptic Seizure by Analysing Time Series EEG Signal Using k-NN Classifier by Md. Kamrul Hasan, Md. Asif Ahamed, Mohiuddin Ahmad, M. A. Rashid

“…The k-nearest neighbours (k-NN) algorithm is used for the classification of epilepsy then regression analysis is used for the prediction of the epilepsy level at different ages of the patients. …”
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Multi-task hybrid dictionary learning for vehicle classification in sensor networks by Rui Wang, Miaomiao Shen, Tao Wang, Wenming Cao

“…Moreover, the problem of ℓ p -norm ( p ⩽ 1 ) sparse coding can been solved, to reduce the time complexity of this algorithm, compared with support vector machine, sparse representation classification, label consistent KSVD, Fisher discrimination dictionary learning, hybrid dictionary learning, multi-task sparse representation classification, and multi-task Fisher discrimination dictionary learning algorithms.…”
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Reliability Assessment Based on GO Method of Metro Traction System by Qi Gong, Bingzhi Chen, Yonghua Li, Pengpeng Zhi

“…The maintainability and shutdown correlation of many electrical components in the MTS are considered. An accurate algorithm with shared signals is used. Then the quantitative and qualitative reliability assessment of the system is achieved with the goal of traction system providing traction for the vehicle. …”
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End-to-End Semantic Leaf Segmentation Framework for Plants Disease Classification by Khalil Khan, Rehan Ullah Khan, Waleed Albattah, Ali Mustafa Qamar

“…Over the last ten years, computer vision researchers proposed different algorithms for plant disease identification using ML. …”
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Multi-objective optimization of water resources allocation in rift valley lakes basin (Ethiopia): tradeoffs between efficiency and equity by Mulugeta Mohammed, Belete Birhanu, Fentaw Abegaz

“…This study introduces a multi-objective optimization framework using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) to balance economic efficiency, equity, and environmental sustainability in water allocation. …”
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Approach for designing and modelling of nanoscale DG MOSFET devices using Kriging metamodelling technique by Toufik Bentrcia, Fayçal Djeffal, Elasaad Chebaki

“…It is also shown that the obtained Kriging interpolation models are precise enough to be used as objective functions in the context of a genetic algorithm optimisation with the aim of improving the device analogue/RF performance in terms of transconductance and cut‐off frequency parameters. …”
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Identification of key regulators in pancreatic ductal adenocarcinoma using network theoretical approach. by Kankana Bhattacharjee, Aryya Ghosh

“…Newman and Girvan's algorithm (leading eigenvector (LEV) method) of community detection enumerated four communities leading to at least one motif defined by G (3,3). …”
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ResInceptNet-SA: A Network Traffic Intrusion Detection Model Fusing Feature Selection and Balanced Datasets by Guorui Liu, Tianlin Zhang, Hualin Dai, Xinyang Cheng, Daoxuan Yang

“…The model used the PCA-ADASYN algorithm to compress network traffic features, extract high-correlation feature datasets, and oversample and balance the feature datasets to classify abnormal network traffic. …”
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Transit Station Congestion Index Research Based on Pedestrian Simulation and Gray Clustering Evaluation by Shu-wei Wang, Li-shan Sun, Jian Rong, Zi-fan Yang

“…Taking pedestrian density as basic data and gray clustering evaluation as algorithm, an index called Transit Station Congestion Index (TSCI) was constructed to reflect the congestion degree of transit stations. …”
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Coupled variable‐input LCG and clock divider‐based large period pseudo‐random bit generator on FPGA by Mangal D. Gupta, Rajeev K. Chauhan

“…To prevent the system from falling into short‐period orbits as well as increasing the randomness of the generated bit sequences, the proposed algorithm periodically changes the seed parameters of the LCG blocks. …”
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Achieving On-Site Trustworthy AI Implementation in the Construction Industry: A Framework Across the AI Lifecycle by Lichao Yang, Gavin Allen, Zichao Zhang, Yifan Zhao

“…This framework addresses six key phases, including planning, data collection, algorithm development, deployment, maintenance, and archiving, and clarifies the design principles and development priorities needed for each phase to enhance AI system trustworthiness and acceptance. …”
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Mix-Spectrum for Generalization in Visual Reinforcement Learning by Jeong Woon Lee, Hyoseok Hwang

“…Furthermore, the proposed method stands out for adaptability when integrated with any visual RL algorithm, whether off-policy or on-policy. Through extensive experiments on the DMControl Generalization Benchmark (DMControl-GB) and Procgen, our method demonstrates superior performance compared to existing frequency-based, normalization-based, and image augmentation methods in zero-shot generalization. …”
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Task Grid-Based Urban Environmental Information Release Mechanism for Mobile Crowd Sensing by Zhenwei Chen, Yang Lu, Zusong Li, Xiancun Zhou

“…For the sensing data, through an efficient data fusion algorithm designed in this study, the sensing information is fused to obtain the fine-grained environmental information of different task grids in the area. …”
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High-Impedance Fault Detection in Electric Power Distribution Network Using Local Pattern Transformation Methods and Bidirectional Long Short–Term Memory by Rini Varghese P, M. S. P. Subathra, S. Thomas George, Geno Peter, Albert Alexander Stonier, Sairamya N, Ananthi A, Vivekananda Ganji

“…HIF and non-HIF were classified by bidirectional long short–term memory (Bi-LSTM) for the selected feature sets. Among the four algorithms, LGP attains the best accuracy for both networks; hence, the paper recommends that LGP with Bi-LSTM is more effective for detecting HIF occurrence.…”
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A novel sea surface evaporation scheme assessed by the thermal rotating shallow water model by Masoud Rostami, Stefan Petri, Bijan Fallah, Farahnaz Fazel‐Rastgar

“…The model is tested across different seasons to assess its reliability under various weather conditions. The Dedalus algorithm, which handles spin‐weighted spherical harmonics, is employed to address the pseudo‐spectral problem‐solving tasks of the model.…”
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Automatic Estimation of Solar Rooftops and Power Generation From Publicly Available Satellite Imagery Through Georeferencing and Large-Scale Support by John Sullivan, Apichon Witayangkurn

“…The detection results were post-processed through polygonization and smoothing using the Douglas-Peucker algorithm. Panel size and power generation were then calculated and attached as attributes. …”
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Vertical Force Monitoring of Racing Tires: A Novel Deep Neural Network-Based Estimation Method by Semih Öngir, Egemen Cumhur Kaleli, Mehmet Zeki Konyar, Hüseyin Metin Ertunç

“…A hybrid model, termed Random Forest Assisted Deep Neural Network (RFADNN), is introduced, combining a novel deep learning framework with the Random Forest Algorithm to enhance estimation accuracy. By leveraging the Temporal Convolutional Network (TCN), Minimal Gated Unit (MGU), Long Short-Term Memory (LSTM), and Attention mechanisms, the deep learning framework excels in extracting complex features, which the Random Forest Model subsequently analyzes to improve the accuracy of estimating vertical tire forces. …”
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