Machine Learning-Based Scoring System to Predict the Risk and Severity of Ataxic Speech Using Different Speech Tasks by Bipasha Kashyap, Pubudu N. Pathirana, Malcolm Horne, Laura Power, David J. Szmulewicz

“…The algorithm was developed and evaluated using recordings from 126 participants: 65 individuals with CA and 61 controls (i.e., individuals without ataxia or neurotypical). …”
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Cheby-KANs: Advanced Kolmogorov–Arnold Networks for Applying Geometric Deep Learning in Quantum Chemistry Applications by Amgad Abdallah Mahmoud, Andreas Pester, Maha M. Muttardi, Frederic Andres, Shihori Tanabe, Nicolas Greneche, Hesham H. Ali

“…In this work, we present an enhanced version of the Kolmogorov–Arnold network (KAN) algorithm, called Cheby-KAN, that offers a more efficient, more reliable, and faster alternative to conventional KANs. …”
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Optimization of Operation Strategy of Multi-Islanding Microgrid Based on Double-Layer Objective by Zheng Shi, Lu Yan, Yingying Hu, Yao Wang, Wenping Qin, Yan Liang, Haibo Zhao, Yongming Jing, Jiaojiao Deng, Zhi Zhang

“…Simulation results show that compared with the traditional PSO algorithm, the iterative times of the GWO algorithm proposed in this paper are reduced by 35.62%, and the calculation time is shortened by 34.34%. …”
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Assessing water clarity in the Chesapeake Bay using satellite-derived Secchi disk depth by Seunghyun Son, Nikolay P. Nezlin, Veronica P. Lance

“…A semi-analytical SDD algorithm (hereafter called CB-SDD algorithm) proposed for turbid coastal waters was extensively evaluated in the Chesapeake Bay. …”
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Novel machine learning-driven comparative analysis of CSP, STFT, and CSP-STFT fusion for EEG data classification across multiple meditation and non-meditation sessions in BCI pipel... by Nalinda D. Liyanagedera, Corinne A. Bareham, Heather Kempton, Hans W. Guesgen

“…Among many tested, three BCI pipelines we built produced promising results, successfully detecting features in meditation/ non-meditation EEG data. While testing different feature extraction algorithms, a common neural network structure was used as the classification algorithm to compare the performance of the feature extraction algorithms. …”
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Removing Cardiac Artifacts From Single-Channel Respiratory Electromyograms by Eike Petersen, Julia Sauer, Jan GraBhoff, Philipp Rostalski

“…Template subtraction algorithms yield the best results if the characteristics of the raw signal are of interest, while filtering algorithms like simple high-pass filtering, wavelet denoising, and EMD-based denoising show superior performance for calculating a cleaned envelope signal. …”
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Real‐Time Parameter Identification and State of Charge Estimation of Electric Vehicle Batteries by A. Maheshwari, S. Nageswari, R. Palanisamy, B. Karthikeyan, Mohamed Metwally Mahmoud, Daniel Eutyche Mbadjoun Wapet, Ali M. El‐Rifaie, Ezzeddine Touti, Ahmed I. Omar

“…The fixed forgetting factor RLS (FFRLS) algorithm is implemented with two different forgetting factor (FF) values, while the VFFRLS method utilizes different initial FF values. …”
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The Shrinking of Beijing and the Rising of Xiong’an: Optimize Population Migration in terms of Transport Service by Hongzhi Lin

“…The effectiveness of the model and algorithm is validated by an experimental study using the current transport network between Beijing and Xiong’an. …”
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Adaptive Security Solutions for NOMA Networks: The Role of DDPG and RIS-Equipped UAVs by Syed Zain Ul Abideen, Abdul Wahid, Mian Muhammad Kamal

“…Our main objective is to prevent eavesdroppers from accessing the network while preserving seamless communication for authorized users. …”
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Pavement Potholes Quantification: A Study Based on 3D Point Cloud Analysis by Qingzhen Sun, Lei Qiao, Yibo Shen

“…Surface segmentation is achieved through RANSAC (Random Sample Consensus) and Euclidean clustering, while the Alpha Shapes algorithm is utilized for three-dimensional volume reconstruction, facilitating the volumetric quantification of potholes. …”
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Wake Homing Torpedo Guidance Using a Hierarchical Deep Reinforcement Learning Framework by Kunchul Hwang, Jinwhan Kim

“…While heuristic algorithms can handle typical wake trajectories, developing a robust solution for unknown trajectories remains a significant challenge. …”
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Sentiment Analysis of Tweets on Prakerja Card using Convolutional Neural Network and Naive Bayes by Pahlevi Wahyu Hardjita, Nurochman, Rahmat Hidayat

“…Convolutional neural network (CNN) is a deep learning algorithm that uses one or more layers commonly used for pattern recognition and image recognition. …”
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Hybrid beamforming for ISAC based on mmWave cell-free MIMO by DUO Lin, YANG Xin, REN Yong, XU Boyu

“…Two kinds of power constraints are considered in the study, and the improved orthogonal matching pursuit algorithm and the Riemann conjugate gradient algorithm are used for optimization. …”
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Optimization of Irrigation Requirements for the Markonahalli Command Area Using the SWAT Model by Archana K., Suresh Ramaswwamy Reddy, Jagadish Vengala, Ashish Kumar Nayak

“…The irrigation requirement is further optimized for maximum crop yield using the Nondominated Sorting Genetic Algorithm II (NSGA-II) and Pareto curves. The optimization results show that 37.85% of the irrigation requirement can be conserved while maximizing crop yield.…”
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Improving inverter efficiency for electric vehicles: Experimental validation of the neural network-based SHE technique using RT-LAB by Seyf Eddine Bechekir, Mokhtaria Jbilou, Mostefa Brahami, Fatima Zohra Boudjella, Imen Souhila Bousmaha, Mimouna Oukli, Said Nemmich

“…This study presents a real-time Selective Harmonic Elimination PWM (SHE-PWM) algorithm using artificial neural networks, validated with the OP5600 RT LAB simulator. …”
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A Smart Device Enabled System for Autonomous Fall Detection and Alert by Jian He, Chen Hu, Xiaoyi Wang

“…Meanwhile, the k NN algorithm and sliding window are introduced to develop a smart device enabled system for fall detection and alert, which is composed of a wearable motion sensor board and a smart phone. …”
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A cost- and performance-effective approach for task scheduling based on collaboration between cloud and fog computing by Xuan-Qui Pham, Nguyen Doan Man, Nguyen Dao Tan Tri, Ngo Quang Thai, Eui-Nam Huh

“…Fog computing helps to reduce transmission latency and monetary cost for cloud resources, while cloud computing helps to fulfill the increasing demands of large-scale compute-intensive offloading applications. …”
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Efficient Capacity-Based Joint Quantized Precoding and Transmit Antenna Selection Using Cross-Entropy Method for Multiuser MIMO Systems by Jung-Chieh Chen, Min-Han Chiu, Yi-Syun Yang, Kuan-Yuen Liao, Chih-Peng Li

“…To reduce the computational load while still maximizing channel capacity, the cross-entropy (CE) method is adopted to determine the suboptimum solution. …”
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Energy consumption optimization scheme in UAV-assisted MEC system based on optimal SIC order by Wei JI, Xuxin YANG, Fei LI, Ting LI, Yan LIANG, Yunchao SONG

“…In uplink non-orthogonal multiple access (NOMA)-based unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system, the successive interference cancellation (SIC) order of NOMA became a bottleneck limiting the transmission performance of task offload in uplink link.To reduce the energy consumption of the system, the SIC order was discussed and the optimal SIC order based on channel gain and task delay constraint was proposed.The optimization problem of minimizing the system energy consumption was proposed based on the optimal SIC order while satisfying the constraints of the given task delay of the device, the maximum transmit power constraint of the device, and the UAV trajectory.Since the problem was a complex non-convex problem, an alternating optimization method was adopted to solve the optimization problem to achieve power allocation and UAV trajectory optimization.A low-complexity algorithm based on matching theory was proposed to obtain the optimal device grouping in different time slots.Simulation results show that the optimal SIC order can realize smaller system energy consumption under the same task delay constraint compared with other SIC order, the proposed low-complexity device grouping algorithm can obtain the optimal device grouping.…”
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Reinforcement learning-enhanced adaptive sliding mode control for nonlinear systems by Omnia Youssef, Mohamed Wafa, Raafat Shalaby

“…The algorithm’s stability is rigorously proven via the Lyapunov theorem. …”
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