Marine soundscape forecasting: A deep learning-based approach by Shashidhar Siddagangaiah

“…Despite the rapid development of anomaly detection algorithms and deep-learning models for forecasting, their application to marine soundscapes remains unexplored. …”
Get full text

Fault diagnosis method of mine hoist main bearing with small sample based on VAE-WGAN by Fan JIANG, Hongyan SONG, Xi SHEN, Zhencai ZHU, Shuman CHENG

“…VAE-WGAN was trained using the bearing dataset of the mine hoist simulation test bench to achieve the expansion and expansion of the small sample dataset. In order to improve the feature extraction ability and fault diagnosis accuracy of fault diagnosis models, based on the lightweight convolutional neural network MobileNetV2, the convolutional block attention mechanism CBAM is integrated into the deep feature mapping of MobileNetV2, and an attention mechanism convolutional classification network CBAM-MobileNetV2 is constructed. …”
Get full text

MEMS and IoT in HAR: Effective Monitoring for the Health of Older People by Luigi Bibbò, Giovanni Angiulli, Filippo Laganà, Danilo Pratticò, Francesco Cotroneo, Fabio La Foresta, Mario Versaci

“…Notably, movement recognition was accomplished using an artificial intelligence model called Random Forest.…”
Get full text

Research Progress and Prospects of Minimally Invasive Surgical Instrument Segmentation Methods Based on Artificial Intelligence by Weimin CHENG, Xiaohua WU, Jing XIONG

“…This article summarizes the semantic and instance segmentation methods of minimally invasive surgical instruments based on deep learning, deeply analyzes the supervision methods of training algorithms, network structure improvements, and attention mechanisms, and then discusses the methods based on the Segment Anything Model. …”
Get full text

A consistency-guaranteed approach for Internet of Things by Yang Zhang, Shixin Sun, Dongwen Zhang, Jing Qiu, Zhihong Tian

“…The software architecture of Internet of Things defines the component model and interconnection topology of Internet of Things systems. …”
Get full text

Heterogeneous Graph Attention Networks for Scheduling in Cloud Manufacturing and Logistics by Dmitrii Fomin, Ilya Makarov, Mariia Voronina, Anna Strimovskaya, Vitaliy Pozdnyakov

“…We propose a novel Graph Neural Network architecture for optimizing task scheduling by representing the problem on a heterogeneous graph, where nodes denote tasks and locations. Our model minimizes both manufacturing and logistics costs, achieving significant performance improvements over greedy algorithms and comparable results to strong genetic algorithms in large-scale scenarios with up to 20 locations. …”
Get full text

Soil liquefaction assessment using machine learning by Gamze Maden Muftuoglu, Kaveh Dehghanian

“…Compared to other approaches, the study assesses how well these algorithms predict soil liquefaction potential. Early findings show that the algorithms perform well, demonstrating their capacity to identify non-linear connections and improve prediction accuracy. …”
Get full text

The impact of using advanced computer programs on the interior architectural design of the home أثر استخدام برامج الحاسوب المتقدمه في التصميم المعماري الداخلي للمسكن... by Mohamed Abdel Hamed

“…The study focuses on three-dimensional modeling technology and modern design and drafting software, highlighting their role in enhancing precision and detail in the design of interior spaces. …”
Get full text

Trust in Artificial Intelligence–Based Clinical Decision Support Systems Among Health Care Workers: Systematic Review by Hein Minn Tun, Hanif Abdul Rahman, Lin Naing, Owais Ahmed Malik

“…ConclusionsThe findings highlight the need for explainable AI models, comprehensive training, stakeholder involvement, and human-centered design to foster health care workers’ trust in AI-CDSSs. …”
Get full text

Automated classification of stress and relaxation responses in major depressive disorder, panic disorder, and healthy participants via heart rate variability by Sangwon Byun, Ah Young Kim, Min-Sup Shin, Hong Jin Jeon, Hong Jin Jeon, Chul-Hyun Cho, Chul-Hyun Cho

“…This highlights the need for advanced stress-monitoring technologies to improve treatment. Stress affects the autonomic nervous system, which can be evaluated via heart rate variability (HRV). …”
Get full text

Accuracy Evaluation of Multi-Technique Combination Nonlinear Terrestrial Reference Frame and EOP Based on Singular Spectrum Analysis by Qiuxia Li, Xiaoya Wang, Yabo Li

“…The unlabeled jumps could be detected by the sequential <i>t</i>-test analysis of regime shifts (STARS) combined with the generalized extreme Studentized deviate (GESD) algorithms introduced in our earlier paper. These nonlinear time-dependent periodic signals could be modeled better by singular spectrum analysis (SSA) with respect to least squares fitting; the fitting period is no longer composed of semi-annual and annual items, as with ITRF2014. …”
Get full text

Spatial Information of Somatosensory Stimuli in the Brain: Multivariate Pattern Analysis of Functional Magnetic Resonance Imaging Data by In-Seon Lee, Won-mo Jung, Hi-Joon Park, Younbyoung Chae

“…We hypothesized that performance of brain-based prediction models may vary across the types of stimuli, and neural patterns of voxels in the SI and parietal cortex would significantly contribute to the prediction of stimulated locations. …”
Get full text

Multi‐function radar work mode recognition based on residual shrinkage reconstruction recurrent neural network by Lihong Wang, Kai Xie

“…These features are then processed through a residual shrinkage structure to reduce noise, which significantly improves the model's robustness in non‐ideal scenarios. …”
Get full text

Method of automatic coregistration of digital remote sensing images from different sources by A.N. Borisov, V.V. Myasnikov, V.V. Sergeev

“…To achieve a universal and robust solution in the latter stages, the best-known algorithms were compared: SIFT, SAR-SIFT, RIFT, and the trainable RoMa. …”
Get full text

The Implementation of BCTrustAI.SL into the Automated Practices of Digital Labour Platforms to Ensure Fairness, Transparency and Accountability by Şaban İbrahim Göksal, Kristi Joamets

“…This directive seeks to foster fairness, transparency, and accountability, establishing four key requirements in its algorithmic management chapter: transparency, human oversight, human review, rights to information and consultation. …”
Get full text

Artificial intelligence in data storage systems by V. V. Zhilin, O. A. Safar'yan

“…Artificial intelligence with built-in machine-learning algorithms will provide responding to a situation that affects the state of the sys-tem. …”
Get full text

An Advanced Hybrid Forecasting System for Wind Speed Point Forecasting and Interval Forecasting by Haipeng Zhang, Hua Luo

“…Therefore, in this paper, we developed a prediction system integrating an advanced data preprocessing strategy, a novel optimization model, and multiple prediction algorithms. This combined forecasting system can overcome the inherent disadvantages of the traditional forecasting methods and further improve the prediction performance. …”
Get full text

A network intrusion detection method designed for few-shot scenarios by Weichen HU, Congyuan XU, Yong ZHAN, Guanghui CHEN, Siqing LIU, Zhiqiang WANG, Xiaolin WANG

“…Existing intrusion detection techniques often require numerous malicious samples for model training.However, in real-world scenarios, only a small number of intrusion traffic samples can be obtained, which belong to few-shot scenarios.To address this challenge, a network intrusion detection method designed for few-shot scenarios was proposed.The method comprised two main parts: a packet sampling module and a meta-learning module.The packet sampling module was used for filtering, segmenting, and recombining raw network data, while the meta-learning module was used for feature extraction and result classification.Experimental results based on three few-shot datasets constructed from real network traffic data sources show that the method exhibits good applicability and fast convergence and effectively reduces the occurrence of outliers.In the case of 10 training samples, the maximum achievable detection rate is 99.29%, while the accuracy rate can reach a maximum of 97.93%.These findings demonstrate a noticeable improvement of 0.12% and 0.37% respectively, in comparison to existing algorithms.…”
Get full text

Encoding IoT Data: A Comprehensive Review of Image Transformation Techniques by Suat Özdemir, Feyza Yıldırım Okay, Duygu Altunkaya

“…Recent studies show that transforming IoT data into images improves the performance of the learning model. In this paper, we present a review of these studies which use image transformation/encoding techniques in IoT domain. …”
Get full text

Enhancing Predictive Capabilities for Identifying At-Risk Stocks Using Multivariate Time-Series Classification: A Case Study of the Thai Stock Market by Katsamapol Petchpol, Laor Boongasame

“…Experimental results show deep learning models significantly outperform traditional baseline methods in capturing financial risk patterns. …”
Get full text