Blockchain based solid waste classification with AI powered tracking and IoT integration by Aliaa M. Alabdali

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A Novel Approach to Faster Convergence and Improved Accuracy in Deep Learning-Based Electrical Energy Consumption Forecast Models for Large Consumer Groups by A. Jayanth Balaji, Binoy B. Nair, D. S. Harish Ram, Kuruvachan Kalluvelil George

“…Deep learning-based models are ideally suited for accurately predicting electrical load in a smart grid. However, the computational overhead in training models and identifying optimal training hyperparameters are challenging problems. …”
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NEW ORGANIZATION PROCESS OF FEATURE SELECTION BY FILTER WITH CORRELATION-BASED FEATURES SELECTION METHOD by Olga Solovei

“…A new organization process for feature selection which is proposed in current work combines filter and learning algorithm properties in evaluation strategy which helps to choose the optimal feature subset for predefined learning algorithm. …”
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Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities by Mahmoud Ragab, Ehab Bahaudien Ashary, Bandar M. Alghamdi, Rania Aboalela, Naif Alsaadi, Louai A. Maghrabi, Khalid H. Allehaibi

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Quantum natural stochastic pairwise coordinate descent by Mohammad Aamir Sohail, Mohsen Heidari, S. Sandeep Pradhan

“…Abstract Variational quantum algorithms, optimized using gradient-based methods, often exhibit sub-optimal convergence performance due to their dependence on Euclidean geometry. …”
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A novel lightweight YOLOv8-PSS model for obstacle detection on the path of unmanned agricultural vehicles by Zhijian Chen, Yijun Fang, Jianjun Yin, Shiyu Lv, Farhan Sheikh Muhammad, Lu Liu

“…Compared to the original base network, it reduces the number of parameters by 55.8%, decreases the model size by 59.5%, and lowers computational cost by 51.2%. When compared with other algorithms, such as Faster RCNN, SSD, YOLOv3-tiny, and YOLOv5, the improved model strikes an optimal balance between parameter count, computational efficiency, detection speed, and accuracy, yielding superior results. …”
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Adaptive dimensionality reduction for neural network-based online principal component analysis. by Nico Migenda, Ralf Möller, Wolfram Schenck

“…The computational complexity of the proposed algorithm is investigated and it is benchmarked in an experimental study against other neural network-based and incremental PCA approaches where it produces highly competitive results.…”
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Migraine triggers, phases, and classification using machine learning models by Anusha Reddy, Ajit Reddy

“…These models are run with the dataset without optimal tuning across the entire dataset for different migraine types; which is further improved with selective sampling and optimal tuning. …”
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Beamforming for the Cooperative Non-Orthogonal Multiple Access Transmission with Full-Duplex Relaying with Application to Security Attack by Duckdong Hwang, Sung Sik Nam, Janghoon Yang, Hyoung-Kyu Song

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A non-line-of-sight error mitigation method for location estimation by Chien-Sheng Chen

“…Initially inspired by flocking birds, particle swarm optimization is an evolutionary computation tool for optimizing a problem by iteratively attempting to improve a candidate solution with respect to a given measure of quality. …”
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PATH PLANNING AND OBSTACLE AVOIDANCE METHODS FOR AUTONOMOUS MOBILE ROBOTS by Ihor Berizka

“…Research at the time of writing focuses on optimizing existing algorithms and hybridization to improve efficiency. …”
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An Enhanced VMD with the Guidance of Envelope Negentropy Spectrum for Bearing Fault Diagnosis by Haien Wang, Xingxing Jiang, Wenjun Guo, Juanjuan Shi, Zhongkui Zhu

“…Currently, study on the relevant methods of variational mode decomposition (VMD) is mainly focused on the selection of the number of decomposed modes and the bandwidth parameter using various optimization algorithms. Most of these methods utilize the genetic-like algorithms to quantitatively analyze these parameters, which increase the additional initial parameters and inevitably the computational burden due to ignoring the inherent characteristics of the VMD. …”
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Lightweight and delay-aware resource management scheme in smart grid IoT networks by Danni Liu, Shengda Wang, Xiaofu Sun, Chunyan An, Weijia Su, Jiakang Liu

“…To address this, we propose an online delay-aware online mobile computation offloading scheme consisting of four crucial algorithms, which firstly classify users into heterogeneous networks and then design the online resource allocation methods on the macro base station (MBS) and small base stations (SBSs), respectively, and finally design the updating strategy of the control parameters to ensure the load balancing among bases. …”
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H-Darrieus Wind Turbine with Blade Pitch Control by I. Paraschivoiu, O. Trifu, F. Saeed

“…This was coupled with a genetic algorithm optimizer. The azimuthal variation of the blades' pitch angle is modeled with an analytical function whose coefficients are used as variables in the optimization process. …”
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High-Performance Multi-Object Tracking for Autonomous Driving in Urban Scenarios With Heterogeneous Embedded Boards by Alessio Medaglini, Biagio Peccerillo, Sandro Bartolini

“…The main objective is to exploit the high-performance capabilities of NVIDIA heterogeneous embedded platforms, which are not automatically compatible with the peculiar features of these algorithms. We propose and discuss some non-trivial software design choices and implementation strategies that are needed to match the specific computational and memory access needs of MOT strategies, and the architectural opportunities of NVIDIA embedded GPGPU systems. …”
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A Novel Artificial Bee Colony Approach of Live Virtual Machine Migration Policy Using Bayes Theorem by Gaochao Xu, Yan Ding, Jia Zhao, Liang Hu, Xiaodong Fu

“…Green cloud data center has become a research hotspot of virtualized cloud computing architecture. Since live virtual machine (VM) migration technology is widely used and studied in cloud computing, we have focused on the VM placement selection of live migration for power saving. …”
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About a Routing Problem of the Tool Motion on Sheet Cutting by A. A. Petunin, A. G. Chentsov, P. A. Chentsov

“…An optimal procedure based on the dynamic programming and an effective heuristic algorithm realized on a multicore computer are proposed. …”
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Nonreference Medical Image Edge Map Measure by Karen Panetta, Chen Gao, Sos Agaian, Shahan Nercessian

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Smart Manufacturing through Machine Learning: A Review, Perspective, and Future Directions to the Machining Industry by A. S. Rajesh, M. S. Prabhuswamy, Srinivasan Krishnasamy

“…One such subclass of artificial intelligence is machine learning, which uses a computer system for making predictions and performing definite tasks without any use of specific instructions to enhance the quality of the product, and rate of production, and to optimize the processes and parameters in machining operations. …”
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NET GRAF CALCULATION METHOD FOR JOB COMPLETION CONSIDERING OF RESOURSES AVAILABALE by G. V. Golovchenko, M. I. Rebezova

“…The numerical method is proposed for solving the optimization problem. The method is implemented using the Mathcad computing environment and validated by specific examples.The method is implemented as a complex automated solution for operational management of airport services in the critical situations.…”
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