Optimasi Algoritma Naive Bayes dengan Diskritisasi K-Means pada Diagnosis Penyakit Jantung by Nafa Fajriati, Budi Prasetiyo

“…Naïve Bayes is a classification algorithm that has a fairly good ability to build a classifier model. …”
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Online variational Gaussian process for time series data by Weidong Wang, Mian Muhammad Yasir Khalil, Leta Yobsan Bayisa

“…Unlike traditional methods that rely on a fixed number of inducing points, OLVGP adaptively adjusts the number of inducing points as new data arrives and optimizes them from the model, ensuring that the model remains computationally efficient while maintaining high predictive accuracy. …”
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Drowsiness Detection of Construction Workers: Accident Prevention Leveraging Yolov8 Deep Learning and Computer Vision Techniques by Adetayo Olugbenga Onososen, Innocent Musonda, Damilola Onatayo, Abdullahi Babatunde Saka, Samuel Adeniyi Adekunle, Eniola Onatayo

“…This study presents a vision-based approach using an improved version of the You Only Look Once (YOLOv8) algorithm for real-time drowsiness exposure among construction workers. …”
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Inversion of Leaf Chlorophyll Content in Different Growth Periods of Maize Based on Multi-Source Data from “Sky–Space–Ground” by Wu Nile, Su Rina, Na Mula, Cha Ersi, Yulong Bao, Jiquan Zhang, Zhijun Tong, Xingpeng Liu, Chunli Zhao

“…This study proposes an improved method based on multi-source data, combining the Sentinel-2A spectral response function (SRF) and computer algorithms, to overcome the limitations of traditional methods. …”
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Research on Hyperspectral Inversion of Soil Organic Carbon in Agricultural Fields of the Southern Shaanxi Mountain Area by Yunhao Han, Bin Wang, Jingyi Yang, Fang Yin, Linsen He

“…The results indicate that (1) the Spectral Space Transformation (SST) algorithm effectively eliminates environmental interference on image spectra, enhancing SOC prediction accuracy; (2) continuous wavelet transform significantly reduces data noise compared to other spectral processing methods, further improving SOC prediction accuracy; and (3) among feature band selection methods, the CARS algorithm demonstrated the best performance, achieving the highest SOC prediction accuracy when combined with the random forest model. …”
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Efficiency Design of Traction Inverters Based on Deep Learning and TRIZ by LIAGN Kaiwei, JIAO Bi, LIU Yongjiang, LING Zhenjun, SU Li, XIE Haibo

“…In addition, this paper designs human-computer interaction software based on TRIZ-CRNN to improve the operation intelligence of computer aided innovation system and optimize the application feasibility of TRIZ-CRNN algorithm.…”
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Semantic Segmentation with Multispectral Satellite Images of Waterfowl Habitat by Mateo Gannod, Nicholas Masto, Collins Owusu, Cory Highway, Katherine Brown, Abigail Blake-Bradshaw, Jamie Feddersen, Heath Hagy, Douglas Talbert, Bradley Cohen

“…We found the use of multispectral bands was necessary and although the CIR composite and OSAVI index improved precision, the 12-band composite increased recall, the metric we were most interested in. …”
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An Efficient Design of DCT Approximation Based on Quantum Dot Cellular Automata (QCA) Technology by Ismail Gassoumi, Lamjed Touil, Bouraoui Ouni, Abdellatif Mtibaa

“…Optimization for power is one of the most important design objectives in modern digital image processing applications. …”
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Maximizing the biochemical resolving power of fluorescence microscopy. by Alessandro Esposito, Marina Popleteeva, Ashok R Venkitaraman

“…We describe optimized imaging protocols, provide optimization algorithms and describe precision and resolving power in biochemical imaging thanks to the analysis of the general properties of Fisher information in fluorescence detection. …”
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VR interactive input system based on INS and binocular vision fusion by Hongxia Zhao, Bei Wang

“…This study explores the application of inertial measurement units and binocular vision fusion technology in virtual reality interactive input systems, with the aim of improving the tracking accuracy of the system through optimized pose models and visual algorithms. …”
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Machine learning based assessment of hoarseness severity: a multi-sensor approach centered on high-speed videoendoscopy by Tobias Schraut, Anne Schützenberger, Tomás Arias-Vergara, Melda Kunduk, Matthias Echternach, Stephan Dürr, Julia Werz, Michael Döllinger

“…Subjects were classified into two hoarseness groups based on auditory-perceptual ratings, with predicted scores serving as continuous hoarseness severity ratings. A videoendoscopic model was developed by selecting a suitable classification algorithm and a minimal-optimal subset of glottal parameters. …”
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A longitudinal investigation of gut microbiota dynamics in laying hens from birth to egg-laying stages by Seojin Choi, Eun Bae Kim

“…The findings provide insights into microbiota dynamics and their relationship with age, which can be applied to optimize dietary strategies and improve laying hen productivity and health.…”
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Enhancing stone matrix asphalt performance with sugarcane bagasse ash: Mechanical properties and machine learning-based predictions using XGBoost and random forest by Hamed Khani Sanij, Rezvan Babagoli, Reza Mohammadi Elyasi

“…The results revealed that the inclusion of 6 % SCBA yielded the most favorable outcomes. Marshall Stability increased significantly (up to 9.4 kN), ITS improved to 943 kPa, and moisture susceptibility was enhanced, demonstrating a higher tensile strength ratio compared to the control mixture. …”
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5G-oriented information sharing mechanism within D2D clusters by Shaomin WANG, Bin ZHOU

“…Device-to-Device（D2D）communication is an important technology in 5G network.It helps to improve the transmission efficiency of data dissemination services.However,due to the extra signaling overhead caused by D2D communications,currently most of enhanced-multicast solutions cannot solve the contradiction between high-efficient data transmission and low-efficient signaling procedure,so as to reduce the overall performance gain.An intra-cluster D2D information sharing algorithm based on matrix analysis which includes centralized and distributed modes was proposed.The proposed algorithm could significantly reduce D2D retransmission times in clusters by adaptively selecting the optimal transmitters and data packets for D2D multicast retransmission,achieving the aim of reducing signaling overhead and transmission delay.…”
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Machine learning-based integration develops relapse related signature for predicting prognosis and indicating immune microenvironment infiltration in breast cancer by Junyi Li, Shixin Li, Dongpo Zhang, Yibing Zhu, Yue Wang, Xiaoxiao Xing, Juefei Mo, Yong Zhang, Daixiang Liao, Jun Li

“…To address these limitations, this study systematically analyzed RNA-seq high-throughput data and combined 10 machine learning algorithms to construct 117 models. The optimal algorithm combination, StepCox[both] and ridge regression, was identified, and an immune-related gene signature (IRGS) composed of 12 genes was developed. …”
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Design of Low-Power, High-Precision, and Lightweight Image Recognition System for Multiple Scenes by Gangfeng Yang, Liming Chen, Jianhua Jiang, Chengying Chen, Xindong Huang

“…Aiming at the existing handwritten digit recognition systems with low recognition accuracy, high system power consumption, and high hardware resource consumption, this paper proposes a low-power, high-precision, and lightweight handwritten digit recognition hardware acceleration scheme for multiscenario based on FPGA. By optimizing the network structure of a convolutional neural network (CNN) and the number of parameters of the model, this scheme proposes a high-precision and lightweight network model, simplified CNN, and by optimizing the data access mode and memory usage, and by adopting the strategies of time-sharing and multiplexing, weights sharing, and parallel processing for the hardware acceleration of the algorithm, it effectively reduces the consumption of hardware resources and improves the performance of the system. …”
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Research on Status Assessment and Operation and Maintenance of Electric Vehicle DC Charging Stations Based on XGboost by Hualiang Fang, Jiaqi Liao, Shuo Huang, Maojie Zhang

“…The training sample data are established using historical data, online monitoring data, and external environmental data, and the charging station status evaluation model is trained using the XGBoost algorithm. Based on the condition assessment results, a risk assessment model is established in combination with fault parameters. …”
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A longan-picking sequence planning method for UAV system based on multi-target tracking by Kaixuan Wu, Meiqi Zhang, Linlin Shi, Hengxu Chen, Yuju Mai, Mingda Luo, Hengyi Lin, Jun Li

“…First, a specialized lightweight target detection algorithm, YOLOv8s-Longan, is developed to achieve high-precision target localization and facilitate lightweight model deployment. …”
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Overhead line path planning based on deep reinforcement learning and geographical information system by Jiahui Chen, Yi Yang, Ling Peng, Lina Yang, Yinhui Han, Xingtong Ge

“…Experimental verification of real data shows that compared with existing algorithms, the DSOP method is not only more consistent with the manual line selection effect (improved by more than 3%), but also has a high success rate. …”
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An Adaptive Weight Physics-Informed Neural Network for Vortex-Induced Vibration Problems by Ping Zhu, Zhonglin Liu, Ziqing Xu, Junxue Lv

“…In this study, a VIV dataset of a cylindrical body with different degrees of freedom is used to compare the performance of the PINN and three PINN optimization algorithms. The findings suggest that, compared to a standard PINN, the AW-PINN lowers the mean squared error (MSE) on the test set by 50%, significantly improving the prediction accuracy. …”
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