Federated Learning for Real-Time Demand Response by Data Centers Toward Energy Efficiency and Privacy Preservation by Mohannad Alhazmi, Alexis Pengfei Zhao, Wanzi Li, Chenlu Yang

“…We evaluate various demand response programs by the proposed method in different scenarios and case studies to demonstrate their efficacy in adapting to energy consumption patterns for optimal energy usage and cost reduction. …”
Get full text

A Multimodal Large Language Model Framework for Intelligent Perception and Decision-Making in Smart Manufacturing by Tianyu Wang, Bowen Zhang, Daqi Jiang, Dong Li

Get full text

State Estimation in Power Distribution Grids Using Deep Unfolding by Biswajeet Rout, Balasubramaniam Natarajan

“…Unlike model-agnostic neural networks (NNs), which are difficult to tune and train, the proposed model-based NN is created by “unfolding” the alternating direction method of multipliers (ADMM) solver. This article proposes two methods for state estimation: a purely data-driven approach called model-free DSSE network (MFDSSE-net) and a model-based DSSE network (MBDSSE-net) that incorporates network information by including the linearized power flow constraints into the optimization framework. …”
Get full text

Analysis of the Structure of Nonlinear Distortions at Baseband Pulse Impacts Using Behavioral Nonlinear Models of Electrical Circuits by E. V. Semyonov

“…This, as a result, complicates the optimization of devices.Aim. To develop an approach capable of determining the contribution of various sources to the nonlinear distortion of baseband pulse signals.Materials and methods. …”
Get full text

GAN-based unsupervised domain adaptive person re-identification by Shengsheng ZHENG, Haibing YIN, Xiaofeng HUANG, Tianjie ZHANG

“…Aiming at the problem that the inaccurate clustering in the unsupervised domain adaptive pedestrian re-recognition results in low network recognition accuracy, an unsupervised domain adaptive pedestrian re-recognition method based on generative confrontation network was proposed.Firstly, the CNN model was optimized by using the batch normalization layer after the pooling layer, deleting a fully connected layer and adopting the Adam optimizer.Secondly, the cluster error was analyzed and the important parameter in the cluster was decided based on minimum error rate Bayesian decision theory.Finally, the generative adversarial network was utilized to adjust the cluster.These steps effectively improved the recognition accuracy of unsupervised domain adaptive person re-identification.In the case of the source domain Market-1501 and the target domain DukeMTMC-reID, experimental results show that mAP and Rank-1 can reach 53.7% and 71.6%, respectively.…”
Get full text

Determination of Phenolic Compounds from Lignin Decomposition Products in Marine Sediments by Ultra-High Performance Liquid Chromatography-High Resolution Mass Spectrometry by Jianbo YANG, Junhui CHEN, Xiuping HE, Jiuming WANG, Ming XIN, Xia SUN, Baodong WANG

“…Therefore, it is of great significance to develop a simple and reliable method for determination of phenolic compounds of the lignin decomposition products in marine sediments to explore the source of organic matter and understand the environmental evolution process.OBJECTIVESTo establish a simple and reliable method for the determination of phenolic compounds of lignin decomposition products in marine sediments using solid phase extraction (SPE) combined with ultra-high performance liquid chromatography-high resolution mass spectrometry, and to trace the content level and source of lignin in the sediments of Laizhou Bay in China.METHODSMarine sediment samples were first decomposed with oxidative-alkaline CuO and extracted by solid phase extraction. …”
Get full text

Probabilistic Operation of the Microgrids Including Active Loads and Distributed Generation Constrained to Flexibility and Reliability Indices by Hosein Hasan Shahi, Mehdi Nafar, Mohsen Simab

“…The Pareto optimization based on the weighted sum method is then incorporated to obtain a single-objective model. …”
Get full text

Fault Diagnosis of Hot Rolling Equipment Under Uncertain Conditions Based on Cloud Rough Model, Game Theory, and Improved GRA-TOPSIS by Bo Hu, Yongjun Zhang, Fengwei Jing

“…This study proposes a novel fault evaluation framework: first, a cloud rough model is adopted to handle multi-source uncertainties in expert evaluations; second, game theory is used to optimize the combined weights of subjective and objective criteria; finally, an improved Grey Relational Analysis-Technique for Order Preference by Similarity to Ideal Solution (GRA-TOPSIS) method constructs a dual-scale measurement model by fusing grey relational degree and Euclidean distance, effectively reducing the influence of geometric sequence similarity and distance on fault prioritization and enhancing the robustness of ranking results under complex working conditions. …”
Get full text

Design and analysis of BLDC motor speed control for electric vehicles powered by solar PV and grid supply by Abhishek Kumar, M. Venkatesh Naik, Rahul Kumar, Aman

“…The proposed system utilizes a dual-source power configuration, where solar energy is optimized using an advanced maximum power point tracking (MPPT) technique via a boost converter. …”
Get full text

Unsupervised domain adaptation multi-level adversarial network for semantic segmentation based on multi-modal features by Zeyu WANG, Shuhui BU, Wei HUANG, Yuanpan ZHENG, Qinggang WU, Huawen CHANG, Xu ZHANG

“…In order to solve the problem of the distribution differences of visual, spatial, and semantic features between domains in domain adaptation, an unsupervised domain adaptation multi-level adversarial network for semantic segmentation based on multi-modal features was proposed.Firstly, an attentive fusion semantic segmentation network with three-layer structure was designed to learn the above three types of features from the source domain and target domain, respectively.Secondly, a self-supervised learning method jointing distribution confidence and semantic confidence was introduced into the single-level adversarial learning, so as to achieve the distribution alignment of more target domain pixels in the process of minimizing the distribution distance of the learnt features between domains.Finally, three adversarial branches and three adaptive sub-networks were jointly optimized by the multi-level adversarial learning method based on multi-modal features, which could effectively learn the invariant representation between domains for the features extracted from each sub-network.The experimental results show that compared with existing state-of-the-art methods, on the datasets of GTA5 to Cityscapes, SYNTHIA to Cityscapes, and SUN-RGBD to NYUD-v2 the proposed network achieves the best mean intersection over union of 62.2%, 66.9%, and 59.7%, respectively.…”
Get full text

Enhancing the Efficiency and Schedule of Solar Thermal Power Plants by Utilizing Thermal Storage Devices to Minimize Carbon Emissions by Lingeswaran P., Yadav Shailendra Kumar, Ganesh Babu L., Magesh Babu D., Karuppannan Anand, Iftekhar Hussain Beporam, Nanthakumar S.

“…The renewable energy method of photo thermal power generation has great promise for future advancements. …”
Get full text

DEVELOPMENT OF CONCEPTS NOMENCLATURE FOR CLINICAL DECISION SUPPORT SYSTEM IN DIAGNOSTICS OF ANGINA PECTORIS by K. V. Kiselev, A. V. Potekhina, M. K. Osyaeva, E. A. Noeva, O. N. Vyborov, A. V. Zorin, S. L. Shvyrev, T. V. Martynyuk, T. V. Zarubina, I. Ye. Chazova

“…The final nomenclature validation was performed by semi-automatic method on anonymized 610 electronic health records of the patients.Results. …”
Get full text

Developing a Drowsiness Detection System for Safe Driving Using YOLOv9 by Fernando Candra Yulianto, Wiwit Agus Triyanto, Syafiul Muzid

“…The model performance was evaluated based on precision, recall, F1 score, and mean average precision (mAP) metrics. The best model was optimized using several optimization techniques to determine the most optimal results. …”
Get full text

Greening concept in inventory system for deteriorating items with preservation investment and price and stock dependent demand via marine predators algorithm by Hachen Ali, Gobinda Chandra Panda, Adel Fahad Alrasheedi, Ali Akbar Shaikh, Jeonghwan Gwak

“…The robustness of the solution method is further demonstrated by comparing the MPA’s performance with other optimization techniques in terms of solution quality and computational efficiency. …”
Get full text

Noise Testing of the Conveyor Trough Sprocket and Surface Noise Reduction Performance Evaluation of the Cavity Structure in a Combine Harvester by Jianpeng Jing, Hongyan Sun, Runzhi Liang, Shuren Chen, Zhong Tang, Xiaoying He, Yuxuan Chen

“…Noise measurements were conducted using the sound intensity method, revealing sound pressure levels in the range of 93–95 dB. …”
Get full text

Evaluation Modeling of Electric Bus Interior Sound Quality Based on Two Improved XGBoost Algorithms Using GS and PSO by Enlai ZHANG, Yi CHEN, Liang SU, Ruoyu ZHONGLIAN, Xianyi CHEN, Shangfeng JIANG

“…Aiming at the practical application requirements of high-precision modeling of acoustic comfort in vehicles, this paper presented two improved extreme gradient boosting (XGBoost) algorithms based on grid search (GS) method and particle swarm optimization (PSO), respectively, with objective parameters and acoustic comfort as input and output variables, and established three regression models of standard XGBoost, GS-XGBoost, and PSO-XGBoost through data training. …”
Get full text

Volt/Var Control of Electronic Distribution Network Based on Hierarchical Coordination by Zijie Huang, Kun Yu, Xingying Chen, Bu Xue, Liangxi Guo, Jiarou Li, Xiaolan Yang

“…A variable-slope linear droop control method based on voltage boundary parameter optimization is employed for real-time adjustment of soft open point (SOP) and inverter outputs. …”
Get full text

A Dual-Task Approach for Onset Time Picking and the Detection of Microseismic Waveforms Based on Deep Learning by Hang Zhang, Ruoyu Li, Chunchi Ma, Xiaobing Cheng, Simeng Meng, Zhenxing Huang, Di Li

“…A comparison of the proposed method with existing methods and applications in underground engineering projects helped demonstrate the excellent performance of this method. …”
Get full text

Reducing contrast media and radiation dose in CT angiography at low tube voltage: animal study with photon-counting detector CT by Konstantin Klambauer, Thomas Flohr, Lukas Jakob Moser, Victor Mergen, Matthias Eberhard, Andreas Prokein, Hatem Alkadhi, Hubertus Pietsch, Gregor Jost

“…Methods Six minipigs (median weight: 32.5 kg; IQR: 29.8–34.6 kg) underwent thoracoabdominal CTA using a clinical dual-source PCD-CT at 70 kVp with three scan protocols: (A) reference (100% CM and radiation dose), (B) increased radiation (233%) and reduced CM (56%) dose, and (C) reduced radiation (50%) and increased CM (141%) dose. …”
Get full text

A Target Near-Field Scattering Measurement Technique Utilizing 3D Near-Field Imaging via Cylindrical Scanning by Zongkai Yang, Jingcheng Zhao, Weikang Si, Changyu Lou, Xin Zhao, Jungang Miao

“…Ultimately, accurate calculations are performed utilizing backpropagation (BP) in time domain algorithms. This method significantly reduces the computational burden while maintaining imaging accuracy by integrating rapid scattering source extraction with precise computation for critical regions. …”
Get full text