An Improved Diagnosis Approach for Short-Circuit Fault Diagnosis in MPC-Based Current Source Inverter System by Jonggrist Jongudomkarn, Pirat Khunkitti, Apirat Siritaratiwat

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A fast identification method for multi-joint robot load based on improved Fourier neural network by Xia Yue, Jionghao Mo, Zhibin Li, Haiteng Li, Chunliang Zhang, Shangbin Long

“…Therefore, based on Fourier neural network, this paper proposes an improved model to realize load identification, in order to improve the prediction accuracy and timeliness of system load parameters. …”
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Preamble Allocation and Access Delay Reduction for Improved Massive Random Access in 5G Beamforming Networks by Gangwoo Lee, Jaewook Jung, Jong-Moon Chung

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Rapid and Low-Cost Detection of Thyroid Dysfunction Using Raman Spectroscopy and an Improved Support Vector Machine by Xiangxiang Zheng, Guodong Lv, Guoli Du, Zhengang Zhai, Jiaqing Mo, Xiaoyi Lv

“…Principal component analysis (PCA) was used for feature extraction and reduced the dimension of high-dimension spectral data; then, SVM was employed to establish an effective discriminant model. To improve the efficiency and accuracy of the SVM discriminant model, we proposed artificial fish coupled with uniform design (AFUD) algorithm to optimize the SVM parameters. …”
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A Recommendation Algorithm Based on Restricted Boltzmann Machine by WANG Weibing, ZHANG Lichao, XU Qian

“…In the case where the amount of data is too large, the recommended results output by the RBM model will be broader Besides, many collaborative filtering algorithms currently do not handle large data sets better So, we try to use the deep learning technology to strengthen the personalized recommendation model We propose a hybrid recommendation model combining the bound Boltzmann model and the hidden factor model First, we use the RBM algorithm to generate candidate sets, and score the sparse matrix of the candidate set Then we use the LFM model to sort the candidate results and select the optimal solution for recommendation The hybrid model is validated using used large public datasets It can be seen from the verification that compared with the traditional recommendation model, the proposed method can improve the accuracy of the score prediction…”
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Interference coupling cooperative suppression method for wideband carrier communication based on improved variational mode decomposition by Dandan DONG, Ning SUN

“…The interference coupling of power line broadband carrier communication aggravates the frequency domain tailing between subcarriers, reduces the sensitivity of suppression methods, and the communication quality is poor.Therefore, a cooperative suppression method of interference coupling of power line broadband carrier communication based on improved variational modal decomposition was proposed.Based on the channel characteristics of power line broadband carrier communication, a communication channel model with multipath propagation and Doppler effect was established, the communication signal was simulated, the original signal was preprocessed by using the improved variational modal decomposition algorithm, and the suppression problem was transformed into a variational problem.At the same time, the signal was expressed in the discrete form of unconstrained variational problem.The variational problem was continuously updated to complete the separation and processing of the signal, and realize the cooperative suppression of communication interference.The experimental results show that the proposed method has low bit error rate, small frequency offset, and practical application value.…”
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A combined improved dung beetle optimization and extreme learning machine framework for precise SOC estimation by Kaihua Yao, Xinyu Yan, Xiling Mao, Mengwei Li, Xiao Li, Ziyu Lian, Yuxiang Han

“…The novelty of the model stems from the application of the IDBO algorithm, which incorporating Circle chaotic mapping, the Golden sine strategy, and the Levy flight strategy, for hyper-parameter optimization. …”
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Improving Unplugged Computational Thinking Skills Through Integrated Problem-Based and Differentiated Learning in Indonesia by Dewi Oktaviani, Susilo Satanti

“…This Classroom Action Research aims to improve students’ computational thinking (abstraction, data collection, data analysis and algorithms) in solving problems about probability through problem-based learning integrated with differentiation learning. …”
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Smart Agricultural Pest Detection Using I-YOLOv10-SC: An Improved Object Detection Framework by Wenxia Yuan, Lingfang Lan, Jiayi Xu, Tingting Sun, Xinghua Wang, Qiaomei Wang, Jingnan Hu, Baijuan Wang

“…The experimental results show that compared with the original YOLOv10, the model generated by the improved algorithm improves the accuracy by 5.88 percentage points, the recall rate by 6.67 percentage points, the balance score by 6.27 percentage points, the mAP value by 4.26 percentage points, the bounding box loss by 18.75%, the classification loss by 27.27%, and the feature point loss by 8%. …”
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Improving the Solution of Least Squares Support Vector Machines with Application to a Blast Furnace System by Ling Jian, Shuqian Shen, Yunquan Song

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An Improved Equilibrium Optimizer for Optimal Placement of Distributed Generators in Distribution Systems considering Harmonic Distortion Limits by Thai Dinh Pham, Thang Trung Nguyen, Le Chi Kien

“…The proposed IEO is developed from the original equilibrium optimizer (EO), which was motivated by control volume mass balance models. This novel algorithm can effectively expand the search area and avoid the premature convergence to low-quality solution spaces. …”
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Improving TMJ Diagnosis: A Deep Learning Approach for Detecting Mandibular Condyle Bone Changes by Kader Azlağ Pekince, Adem Pekince, Buse Yaren Kazangirler

“…This approach has the potential to improve the early detection of TMJ-related condylar bone changes, enabling timely referrals and potentially preventing disease progression.…”
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Dual-robot formation transport in random environment and narrow restricted area via improved DDPG navigation by Liang Tang, Ronggeng Ma, Bowen Chen, Yisen Niu

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Weakly supervised semantic segmentation and optimization algorithm based on multi-scale feature model by Changzhen XIONG, Hui ZHI

“…In order to improve the accuracy of weakly-supervised semantic segmentation method,a segmentation and optimization algorithm that combines multi-scale feature was proposed.The new algorithm firstly constructs a multi-scale feature model based on transfer learning algorithm.In addition,a new classifier was introduced for category prediction to reduce the failure of segmentation due to the prediction of target class information errors.Then the designed multi-scale model was fused with the original transfer learning model by different weights to enhance the generalization performance of the model.Finally,the predictions class credibility was added to adjust the credibility of the corresponding class of pixels in the segmentation map,avoiding false positive segmentation regions.The proposed algorithm was tested on the challenging VOC 2012 dataset,the mean intersection-over-union is 58.8% on validation dataset and 57.5% on test dataset.It outperforms the original transfer-learning algorithm by 12.9% and 12.3%.And it performs favorably against other segmentation methods using weakly-supervised information based on category labels as well.…”
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Improved Deep Convolutional Generative Adversarial Network for Data Augmentation of Gas Polyethylene Pipeline Defect Images by Zihan Zhang, Yang Wang, Nan Lin, Shengtao Ren

“…Experimental results demonstrate the superiority of the improved algorithm in terms of image generation quality and diversity, while the ablation study validates the positive impact of the improvement in each part. …”
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Photovoltaic Short-Term Output Power Forecast Model Based on Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise–Kernel Principal Component Analysis–Long Sh... by Lan Cao, Haoyu Yang, Chenggong Zhou, Shaochi Wang, Yingang Shen, Binxia Yuan

“…The KPCA algorithm reduces the input dimensions of the model. …”
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An Improved Location Method of 10 kV Cable Joints Based on Nuttall Self-Convolution Window by Xingquan XU, Yuan GUI, Yuhai YAO, Zhihui WANG, Rong LI, Kai ZHOU, Min XIE

“…In order to solve the problem of spectrum leakage and fence effect when using discrete Fourier transform (DFT) to analyze the input impedance spectrum of header point of cable, this paper presents an improved method of the joints location for the 10kV distribution cable based on Nuttall self-convolution window. …”
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Improved Iterative CD-Spline Approach for Building Boundary Regularization Using Airborne LiDAR Data by Renato Cesar dos Santos, Ayman F. Habib, Mauricio Galo

“…To overcome this limitation, we proposed the Improved Iterative Changeable Degree-Spline (IICDS) that consists of testing several CP configurations, resulting in multiple contour models for each building. …”
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IA-CIOU: An Improved IOU Bounding Box Loss Function for SAR Ship Target Detection Methods by Pingping Huang, Shihao Tian, Yun Su, Weixian Tan, Yifan Dong, Wei Xu

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Serum Lipid Biomarkers for the Diagnosis and Monitoring of Neuromyelitis Optica Spectrum Disorder: Towards Improved Clinical Management by Li R, Wang J, Wang J, Xie W, Song P, Zhang J, Xu Y, Tian D, Wu L, Wang C

“…A user-friendly smartphone application was developed to facilitate the straightforward “input-index, output-answer” screening process, enhancing both clinical decision-making and patient care.Conclusion: The diagnostic model based on the serum lipid-related indexes (TC, TG, LDL, HDL, ApoA1, and ApoB) may be the useful tool for NMOSD in diagnosis and monitoring of disease stage, thereby improving the treatment outcome for patients. …”
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