DS4NN: Direct training of deep spiking neural networks with single spike-based temporal coding by Maryam Mirsadeghi, Majid Shalchian, Saeed Reza Kheradpisheh

“…Backpropagation is the foremost prevalent and common algorithm for training conventional neural networks with deep construction. …”
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Toward model-based individualized fitting of hip-flexion exosuits for persons with unilateral transfemoral amputation by Finn G. Eagen, Nicholas P. Fey

“…In this article, we model the effects of such a device during whole-body, subject-specific kinematic simulations of level ground walking. …”
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Congenital Melanocytic Nevus of the Nose: Clinical Experience and Reconstructive Approaches by Alexander Margulis, MD, Allan Billig, MD, Neta Adler, MD

“…The authors developed a treatment algorithm with the aim of offering an optimal surgical management plan. …”
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A multi-objective aerodynamic performance optimization of a centrifugal vacuum pump and the flow physics analysis by Zhanyuan Gu, Jiangtao Zhang, Wei Zhang, Yikun Wei

“…The flow in the radial vaneless region of the optimized models presents uniform distributions of flow angle and Mach number over the whole circumference. The reduced energy loss and uniform flow field contribute to the improved performance of the centrifugal vacuum pump.…”
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Degradation Type-Aware Image Restoration for Effective Object Detection in Adverse Weather by Xiaochen Huang, Xiaofeng Wang, Qizhi Teng, Xiaohai He, Honggang Chen

“…In the training phase, we jointly optimize the whole framework on a mixed weather dataset, including degraded images and clean images. …”
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Hypotensive episodes on program hemodialysis during dialysis procedure: modern approach for diagnostics, prophylaxis and correction by V. Yu. Shilo, I. Yu. Drachev

“…Values of mean AP during hemodialysis procedures for the whole monitoring period were analyzed. The duration of the study was 3 weeks for all patients.Results. …”
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Hybrid precoding and power allocation for mmWave NOMA systems based on time delay line arrays by Gangcan SUN, Xinli WU, Wanming HAO, Zhengyu ZHU

“…Objectives: The antenna structure in conventional millimeter-wave (mmWave) nonorthogonal multiple access(NOMA)systems is based on a high-resolution and high-energy phase shifter modulation network,and how to reduce the system energy consumption while improving the resolution is one of the key problems to be solved. …”
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Improving Secrecy Capacity in the Face of Eavesdropping in SWIPT CIoT Networks With Actor-Critic DRL by Nada Abdel Khalek, Walaa Hamouda

“…The CIoT receiver operates in full-duplex (FD) mode, receiving confidential messages while simultaneously emitting cooperative jamming signals to disrupt an eavesdropper. …”
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Optimizing Distribution Grid Performance through Electric Vehicle Integration and Stochastic Modeling in Extreme Weather Conditions by A. Niknami, M. Askari, M. Amirahmadi, M. Babaeinik

“…Monte Carlo simulation is employed to model uncertainties, while a multi-objective optimization algorithm is used to solve the problem. …”
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A Vision-Based Method for Detecting the Position of Stacked Goods in Automated Storage and Retrieval Systems by Chuanjun Chen, Junjie Liu, Haonan Yin, Biqing Huang

“…This paper proposes a novel machine vision-based detection algorithm that integrates a pallet surface object detection network (STEGNet) with a box edge detection algorithm. …”
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Improving Localization in Wireless Sensor Networks for the Internet of Things Using Data Replication-Based Deep Neural Networks by Jehan Esheh, Sofiene Affes

“…The experimental results demonstrate that this data augmentation technique significantly improves the performance of DNNs compared to the traditional Dv-hop algorithm at a low number of nodes while maintaining an efficient computational cost for data augmentation. …”
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An automatic approach to detect skin cancer utilizing active infrared thermography by Ricardo F. Soto, Sebastián E. Godoy

“…This automated detection system performs comparably to high-accuracy methods while offering a more standardized and efficient solution. …”
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Machine Learning-Driven Prediction of CO₂ Solubility in Brine: A Hybrid Grey Wolf Optimizer (GWO)-Assisted Gaussian Process Regression (GPR) Approach by Seyed Hossein Hashemi, Farshid Torabi, Paitoon Tontiwachwuthikul

“…This demonstrates superior performance in capturing CO₂ solubility trends. The GWO algorithm effectively tuned the hyperparameters for all kernel configurations, while the ARD capability successfully quantified the influence of key physicochemical parameters on CO₂ solubility. …”
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ANALISIS JENIS BUDIDAYA TEBU MENGGUNAKAN ALGORITMA RANDOM FOREST (STUDI KASUS KECAMATAN TAJINAN, KABUPATEN MALANG) by Muhammad Nurhadi, Prima Widayani, Sandy Budi Wibowo

“…Indonesia's national sugar demand continues to increase, while domestic production is still limited due to the lack of accurate data on the area and type of sugarcane cultivation. …”
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Detection of Crack Sealant in the Pretreatment Process of Hot In-Place Recycling of Asphalt Pavement via Deep Learning Method by Kai Zhao, Tianzhen Liu, Xu Xia, Yongli Zhao

“…This algorithm integrates the RepViT (Representation Learning with Visual Tokens) network to reduce computational complexity while capturing the global context of images. …”
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Optimized Trajectory Tracking for ROVs Using DNN + ENMPC Strategy by Guanghao Yang, Weidong Liu, Le Li, Jingming Xu, Liwei Guo, Kang Zhang

“…In contrast to single-loop model predictive control, the proposed double closed-loop control system operates in two distinct phases: (1) The outer loop controller uses a DNN controller to replace the LMPC controller, overcoming the uncertainties in the kinematic model while reducing the computational burden. (2) The inner loop velocity controller is designed using a nonlinear model predictive control (NMPC) algorithm with its closed-loop stability proven. …”
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Heisenberg Group-Based Digital Signatures for Secure Communications by Najla Althuniyan, Ahmed Alamer, Awais Yousaf, Muhammad Waseem, Sarah Aljohani

“…This paper proposes a new digital signature algorithm that employs the Heisenberg group over a prime field and exploits its structure to provide strong cryptographic properties. …”
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Observation optimization for marine target tracking by airborne and maritime unmanned platforms cooperation using adaptive enhanced dung beetle optimization by Qiuyang Dai, Faxing Lu, Haoran Shi, Junfei Xu, Jianjing Qu

“…To address these limitations, this paper proposes a heterogeneous unmanned platform cooperative observation optimization method based on Adaptive Enhanced Dung Beetle Optimization (AEDBO) algorithm. First, we derive optimal observation configurations for the aerial unmanned platform, maritime cooperative unmanned platform, and targets under azimuth systematic error impacts using an attitude correction algorithm. …”
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Optimized YOLOv8 framework for intelligent rockfall detection on mountain roads by Peng Peng, Langchao Gao, Jiachun Li, Hongzhen Zhang

“…To enable efficient detection, this study proposes a rockfall detection system based on embedded technology and an improved Yolov8 algorithm, termed Yolov8-GCB. The algorithm enhances detection performance through the following optimizations: (1) integrating a lightweight DeepLabv3+ road segmentation module at the input stage to generate mask images, which effectively exclude non-road regions from interference; (2) replacing Conv convolution units in the backbone network with Ghost convolution units, significantly reducing model parameters and computational cost while improving inference speed; (3) introducing the CPCA (Channel Priori Convolution Attention) mechanism to strengthen the feature extraction capability for targets with diverse shapes; and (4) incorporating skip connections and weighted fusion in the Neck feature extraction network to enhance multi-scale object detection. …”
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Information-Driven Model Predictive Control With Adaptive Partitioning for Energy Optimization in Automated Electric Vehicles by Shahriar Shahram, Yaser P. Fallah

“…Results confirm that our algorithm effectively maintains desired speed following and distance coverage under varying packet error rates (PERs), ensuring safe and efficient operation while achieving a balanced trade-off between significant energy savings and acceptable passenger comfort.…”
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