Novel Multimodal Fusion Algorithm for Non-Intrusive Anxiety Detection by Mahir Shadid, Mushfiqus Salehin Afnan, Rashed Mustafa, M. Jamshed Alam Patwary

“…The study utilizes six advanced machine learning algorithms (Gaussian Naive Bayes, XGB Classifier, K-Neighbors, SVM, Decision-Tree, and RandomForest) for data classification, pattern recognition, and predictive accuracy. …”
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Turkish educational policy in Central Asia by A. S. Ergashev, O. E. Grishin

“…The author suggests algorithmic approaches to improve the image and increase Turkish education attractiveness through tourism and culture. …”
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InSAR Phase Unwrapping Algorithm Based on Deep GAN by Chenxia Wang, Pingli Sun, Zheng Li, Linlin Tang

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THE ALGORITHM FOR THE TREATMENT OF PATIENTS WITH TREATMENT-RESISTANT HYPERTENSION AT THE OUTPATIENT STAGE by O. S. Kulbachuk, E. V. Sid, O. V. Soloviov, A. V. Piskun

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Extended Blahut–Arimoto Algorithm for Semantic Rate-Distortion Function by Yuxin Han, Yang Liu, Yaping Sun, Kai Niu, Nan Ma, Shuguang Cui, Ping Zhang

“…Furthermore, by considering the semantic knowledge base (SKB) as a specific instance of synonymous mapping, the EBA algorithm provides a theoretical approach for analyzing and predicting the SKB size. …”
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Utility channel estimation algorithm with interference suppression in OFDM system by Xiaoyang LAI, Lin DUO

“…In OFDM system,the least square（LS）algorithm has the shortage of noise cancelling and interference suppressing.An utility channel estimation algorithm which took advantage of the time frequency characteristic in OFDM system was proposed.The new channel estimation algorithm realized noise cancelling and interference suppressing through time-frequency transform by three times.In view of time-frequency transform could be achieved by FFT/IFFT,the new channel estimation algorithm complexity was low.In the TU channel simulation,the new channel estimation algorithm has the high performance,which was 3 dB better than the LS algorithm.In the TU channel simulation with interference suppression,the new channel estimation algorithm has only 1.5 dB reduction in performance.…”
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Vehicle Lateral Control Based on Augmented Lagrangian DDPG Algorithm by Zhi Li, Meng Wang, Haitao Zhao

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Dynamic beam shut-off algorithm for LEO satellite constellation by Shuaijun LIU, Yuemei HU, Chunshi FAN, Teng LING, Lixiang LIU

“…Aiming at the problems of the relatively dense coverage of the satellites in the space segment of the low earth orbit (LEO) multibeam satellite constellation network,which resulted in relatively dense areas in some regions,causing severe inter-beam interference and unnecessary beam resource overhead,a beam shut-off algorithm was proposed with global coverage requirements.The dynamic beam shut-off (DBSO) optimization problem was formulated in LEO multibeam satellite constellation network.Then,the problem was proved to be NP-complete and a heuristic DBSO algorithm was proposed.Simulation scenario considers the Iridium constellation network scenario with total 3 168 beams,and it shows that the number of required activated beams is only 1 913 with 39.61% beam resource reduction.…”
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YOLO-MECD: Citrus Detection Algorithm Based on YOLOv11 by Yue Liao, Lerong Li, Huiqiang Xiao, Feijian Xu, Bochen Shan, Hua Yin

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IRMAOC: an interpretable role mining algorithm based on overlapping clustering by Yaqi Yang, Jun’e Li, Tao Zhang, Lu Chen, Guirong Huang, Zhuo Lv

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Clinical Prediction Models Based on Traditional Methods and Machine Learning for Predicting First Stroke: Status and Prospects by ZHANG Zijiao, DING Shunjing, ZHAO Di, LIANG Jun, LEI Jianbo

“…In recent years, advancements in big data and artificial intelligence technologies have opened new avenues for stroke risk prediction. This article reviews the current research status of traditional methods and machine learning models in predicting first-ever stroke risk and outlines future development trends from three perspectives: First, emphasis should be placed on technological innovation by incorporating advanced algorithms such as deep learning and large models to further enhance the accuracy of predictive models. …”
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Initialization improvement and clustering quality evaluation of K-means algorithm by HE Xuansen, HE Fan, YU Hailan

“…In order to solve the problem of random initialization of K-means algorithm, an improved scheme was proposed. By standardizing the features of data and using principal component analysis (PCA), data dimensionality reduction was achieved. …”
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Amorphous Localization Algorithm Based on BP Artificial Neural Network by Lin-zhe Zhao, Xian-bin Wen, Dan Li

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Solving the Independent Domination Problem by the Quantum Approximate Optimization Algorithm by Haoqian Pan, Changhong Lu

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Improved Image Compression Scheme Using Hybrid Encoding Algorithm by Yusra Ahmed Salih, Aree Ali Mohammed, Loay Edwar George

“…In this work, an effective compression method for hybrid images is proposed based on the discrete wavelet transformation and hybrid encoding algorithm (Huffman and SPIHT). This paper's primary participation is to take advantage of the hybrid encoding technique to maintain the quality of the reconstructed image and the reduction of time complexity. …”
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Statistical modeling based fast rate estimation algorithm for VVC by Wei QI, Haibing YIN, Hongkui WANG, Xiaofeng HUANG, Weihong NIU

“…To reduce the coding complexity of the rate-distortion optimization process of the latest video coding standard versatile video coding (VVC), a fast rate estimation model based on statistical modeling was proposed.Firstly, the quantization behavior in dependent quantization (DQ) and the context dependency in entropy coding were fully considered.Features that could describe context state transition in the coding process were proposed to estimate rate of some synatax elements in a TU preliminarily.Secondly, coefficient chaos and sparsity features were proposed to distinguish the influence of coefficient distribution difference on the rate cost based on the coefficient distribution characteristics which built a TU level rate model.Finally, large-size transform unit (TU) and small-size TU was modeling respectively according to the rate composition character to achieve more accurate rate estimation.A large number of parameters were trained by regression model through statistical methods, and the final linear rate model was obtained which was applied to the mode decision.Experimental results show that the proposed algorithm can achieve 16.289% complexity reduction with 1.567% BD-BR increase for RA configuration.…”
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Improved Algorithm for Analysis of DNA Sequences Using Multiresolution Transformation by T. M. Inbamalar, R. Sivakumar

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Optimizing Apache Spark MLlib: Predictive Performance of Large-Scale Models for Big Data Analytics by Leonidas Theodorakopoulos, Aristeidis Karras, George A. Krimpas

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Optimization of reconfigurable SM2 algorithm over prime filed by Bin LI, Qinglei ZHOU, Xiaojie CHEN, Feng FENG

“…Aiming at the problems of inefficient of software, low utilization of hardware resources and poor scalability of SM2 algorithm, a reconfigurable optimization method of SM2 algorithm over prime filed was proposed.Through in-depth analysis of the SM2 algorithm, starting from different computation stages and characteristics, respectively using KOA fast multiplication, fast modular reduction and Barrett algorithm to achieve recommended or arbitrary parameters of the modular multiplication operation, and the radix-4 extended Euclidean algorithm was optimized and improved to accelerate the modular inverse operation.Then, in the standard projective coordinate system, the Montgomery method was used to improve the efficiency of point multiplication, and the data flow of point addition and double point was optimized to shorten the operation cycle to 12 clocks.At the same time, fast coordinate system conversion was realized inside the FPGA.Finally, the parallel scheduling management of multi-SM2 was designed and implemented to meet the computational requirements of multiple applications.The experimental results show that the optimized SM2 makes full use of FPGA resources and shortens the cycle of point multiplication.The maximum number of calculations per second is 352.48 times higher than the CPU (Intel i5-8300), which improves the performance and scalability.…”
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A Novel Coverage Enhancement Algorithm for Image Sensor Networks by Haiping Huang, Lijuan Sun, Ruchuan Wang, Jing Li

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