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

“…While computer vision and deep learning offer promising solutions, existing methods struggle to balance detection accuracy, computational efficiency, and environmental adaptability. 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. …”
Get full text

Enhancing SR-Tree for Nearest Neighbor Search by Kayumov Abduaziz, Shincheol Lee, Ji Sun Shin

“…Third, we adapt the dual-tree algorithm for SR-Tree that outperforms sequential queries for the all-nearest neighbors problem in low-to-medium dimensional large datasets. …”
Get full text

Combination of Feature Selection and Learning Methods for IoT Data Fusion by V. Sattari-Naeini, Zahra Parizi-Nejad

“…Onthe other hand, GA-ANN is a Wrapper method and despite Relief can adapt itself to the machine learningalgorithm. Meanwhile, Ro-P scheme is useful for analyzing vague and imprecise information and, unlikeGA-ANN, has less calculative costs. …”
Get full text

Fault Diagnosis of Rolling-Element Bearing Using Multiscale Pattern Gradient Spectrum Entropy Coupled with Laplacian Score by Xiaoan Yan, Ying Liu, Peng Ding, Minping Jia

“…Performance of our designed algorithm is tested on two experimental cases. Results confirm the availability of our proposed algorithm in feature extraction and show that our method can recognize effectively different bearing fault categories and severities. …”
Get full text

FONDUE—Fine-Tuned Optimization: Nurturing Data Usability & Efficiency by Valerie Restat, Indra Diestelkämper, Meike Klettke, Uta Störl

“…Although many different algorithms and tools already exist for data cleaning, an end-to-end data quality solution is still needed. …”
Get full text

Human activity recognition via smart-belt in wireless body area networks by Yuhong Zhu, Jingchao Yu, Fengye Hu, Zhijun Li, Zhuang Ling

“…Then a multi-classification Support Vector Machine algorithm optimized by Particle Swarm Optimization is applied to identify five kinds of conventional human postures. …”
Get full text

AI-Powered Innovations in Food Safety from Farm to Fork by Binfeng Yin, Gang Tan, Rashid Muhammad, Jun Liu, Junjie Bi

“…Secondly, during food processing, sensors combined with machine learning algorithms are utilized to ensure regulatory compliance and monitor production parameters. …”
Get full text

Optimizing coverage in wireless sensor networks using deep reinforcement learning with graph neural networks by G. Pushpa, R. Anand Babu, S. Subashree, S. Senthilkumar

Get full text

Enhanced Underwater Image Restoration and Clarity Optimization Using Advanced Digital Image Processing Techniques by Gopirajan Punniyakotti Varadharajan, Pradeep T., Charan R.

“…From the outcomes of the experiment based on PSNR and SSIM metrics, it is evident that the method presented in this paper has better performance than the traditional algorithms. Also, the presented method if free from training samples, thus allowing the benefits of computationally efficient and real-time processing that machine learning models wouldn't have. …”
Get full text

Role,application and challenges of IoT in smart EV charging management:a review by Tripti Kunj, Kirti Pal

“…Additionally, the paper emphasizes the importance of adaptive algorithms and machine learning models for predictive maintenance and efficient resource allocation. …”
Get full text

Short-term prediction of trimaran load based on data driven technology by Haoyun Tang, Rui Zhu, Qian Wan, Deyuan Ren

“…To highlight the trimaran high-frequency load fluctuation and improve the prediction accuracy, the LSTM neural network combines with different signal decomposition algorithms, such as Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD), Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), and Variational Mode Decomposition (VMD). …”
Get full text

Artificial intelligence in educational technology and transformative approaches to English language using fuzzy framework with CRITIC-TOPSIS method by Jingdan Liu, Xujie Bao, Liji Chen

“…Abstract Artificial intelligence (AI) is transforming educational technology by enabling personalized, adaptive, and data-driven learning experiences. Machine learning algorithms analyze student performance to tailor content delivery, while natural language processing facilitates interactive learning through voice assistants and essay evaluation. …”
Get full text

Nanoscale frontiers in cancer diagnosis and therapy by Tamer A. Addissouky

“…The review also addresses emerging ethical and technical challenges, including data privacy and algorithmic transparency, as nanomedicine moves toward clinical reality. …”
Get full text

A Review of Emerging Techniques for Power Quality Improvement in Renewable Energy Integration by Kumar P. Rajesh, Shravani Chapala, Rajitha M., Lokeshwar Reddy Ch.

“…Special emphasis is placed on the role of modern technologies, such as artificial intelligence (AI) and machine learning (ML), in enhancing the adaptability and robustness of PQ solutions. …”
Get full text

Research Status and Prospects of Key Technologies for Rice Smart Unmanned Farms by YU Fenghua, XU Tongyu, GUO Zhonghui, BAI Juchi, XIANG Shuang, GUO Sien, JIN Zhongyu, LI Shilong, WANG Shikuan, LIU Meihan, HUI Yinxuan

“…Rice storage and processing quality detection technology mainly utilizes spectral technology and machine vision technology to detect spectra and images, and future research can combine deep learning and multimodal fusion technology to improve the machine vision system's ability and adaptability to recognize the appearance characteristics of rice.…”
Get full text

Transforming Manufacturing Quality Management with Cognitive Twins: A Data-Driven, Predictive Approach to Real-Time Optimization of Quality by Asif Ullah, Muhammad Younas, Mohd Shahneel Saharudin

“…By utilizing the power of machine learning algorithms, the cognitive twin constantly monitors and then analyzes real-time data. …”
Get full text

Credit approval classification through a WASD neuronet by Mourtas Spyridon D.

“…We improve the learning process of the WASD algorithm with a novel activation function for optimal adaptation to the credit approval model, motivated by the finding that WASD neuronets perform better than traditional back-propagation neuronets in terms of slow training speed and trapping in a local minima. …”
Get full text

Comprehensive and advanced T cell cluster analysis for discriminating seropositive and seronegative rheumatoid arthritis by Shinji Maeda, Hiroya Hashimoto, Tomoyo Maeda, Shin-ya Tamechika, Taio Naniwa, Akio Niimi

“…For advanced analysis, two distinct datasets derived from a self-organizing map algorithm, FlowSOM, were used: one encompassing all CD3+ T cells and another focusing on activated T cell subsets. …”
Get full text

Exploiting Artificial Neural Networks for the State of Charge Estimation in EV/HV Battery Systems: A Review by Pierpaolo Dini, Davide Paolini

“…Addressing these risks requires advanced diagnostic and management strategies, and machine learning presents a powerful solution due to its ability to adapt across multiple facets of battery management. …”
Get full text

Iterative Fast Super-Twisting Flux Sliding Mode Observer for SPMSM with Tangent Quadrature Phase-Locked Loop by Fujiong Zhao, Yunxia Xie, Jianfeng Mao, Yingjie Xu, Gaosheng Li, Rongsheng Jia, Weigang Wang

Get full text