The Contact State Monitoring for Seal End Faces Based on Acoustic Emission Detection by Xiaohui Li, Pan Fu, Kan Chen, Zhibin Lin, Erqing Zhang

“…In the acoustic emission (AE) detection for mechanical seal, the main difficulty is to reduce the background noise and to classify the dispersed features. …”
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Integration of Accelerometers and Machine Learning with BIM for Railway Tight- and Wide-Gauge Detection by Jessada Sresakoolchai, Chayutpong Manakul, Ni-Asri Cheputeh

“…Accelerometers installed on axle boxes provide real-time dynamic data, capturing anomalies indicative of tight and wide gauges. …”
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An AI-Driven Model to Enhance Sustainability for the Detection of Cyber Threats in IoT Environments by Majid H. Alsulami

“…The proposed model AF-WAdaBoost dynamically adjusts classifiers, enhancing accuracy and resilience against evolving threats. …”
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A Semantic Segmentation-Based GNSS Signal Occlusion Detection and Optimization Method by Zhe Yue, Chenchen Sun, Xuerong Zhang, Chengkai Tang, Yuting Gao, Kezhao Li

“…Subsequently, satellite projections are mapped onto the segmented sky image to classify signal occlusions. Then, based on the type of obstruction, a dynamic weight optimization model is constructed to adjust the contribution of each satellite in the positioning solution, thereby enhancing the positioning accuracy of vehicle-navigation in urban environments. …”
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Graph-contrast ransomware detection (GCRD) with advanced feature selection and deep learning by Suneeta Satpathy, Pratik Kumar Swain

“…The present study proposes an efficient and scalable early-stage ransomware detection solution with further potential for improvement through dynamic runtime behaviour analysis of future cyber threats.…”
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Detection and classification of perianal inflammatory diseases: precision of preoperative Trans perineal Ultrasonography by Manar M. Sayed, Shehab Gamal El Deen Ahmed, Nadia F. El Ameen, Ehab Ali Abdelgawad, Mohamed Ahmed Abdelsamie, Christina M. Kamil

“…However, there was no statistically significant concordance between TPUS and MRI in detecting the internal opening (p = 0.05). Conclusion TPUS proved effective in detecting and classifying simple perianal fistulas and sinuses, with advantages in cost, accessibility, and patient comfort, making it suitable as a first-line tool, especially in emergencies or resource-limited settings. …”
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Reinforced Cost-Sensitive Graph Network for Detecting Fraud Leaders in Telecom Fraud by Peiwen Gao, Zhihua Li, Dibin Zhou, Liang Zhang

“…Finally, weight coefficients are dynamically optimized using the Deep Deterministic Policy Gradient (DDPG) algorithm, and the prediction results of the three base classifiers are combined to produce the final classification outcomes. …”
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Method on intrusion detection for industrial internet based on light gradient boosting machine by Xiangdong HU, Lingling TANG

“…Intrusion detection is a critical security protection technology in the industrial internet, and it plays a vital role in ensuring the security of the system.In order to meet the requirements of high accuracy and high real-time intrusion detection in industrial internet, an industrial internet intrusion detection method based on light gradient boosting machine optimization was proposed.To address the problem of low detection accuracy caused by difficult-to-classify samples in industrial internet business data, the original loss function of the light gradient boosting machine as a focal loss function was improved.This function can dynamically adjust the loss value and weight of different types of data samples during the training process, reducing the weight of easy-to-classify samples to improve detection accuracy for difficult-to-classify samples.Then a fruit fly optimization algorithm was used to select the optimal parameter combination of the model for the problem that the light gradient boosting machine has many parameters and has great influence on the detection accuracy, detection time and fitting degree of the model.Finally, the optimal parameter combination of the model was obtained and verified on the gas pipeline dataset provided by Mississippi State University, then the effectiveness of the proposed mode was further verified on the water dataset.The experimental results show that the proposed method achieves higher detection accuracy and lower detection time than the comparison model.The detection accuracy of the proposed method on the gas pipeline dataset is at least 3.14% higher than that of the comparison model.The detection time is 0.35s and 19.53s lower than that of the random forest and support vector machine in the comparison model, and 0.06s and 0.02s higher than that of the decision tree and extreme gradient boosting machine, respectively.The proposed method also achieved good detection results on the water dataset.Therefore, the proposed method can effectively identify attack data samples in industrial internet business data and improve the practicality and efficiency of intrusion detection in the industrial internet.…”
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AI powered detection and assessment of onychomycosis: A spotlight on yellow and deep learning by C. Agostini, R. Ranjan, M. Molnarova, A. Hadzic, O. Kubesch, V. Schnidar, H. Schnidar

“…Objectives Our study aimed to develop and validate automated machine learning models to accurately detect and classify onychomycosis‐affected areas in toenails. …”
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A novel approach for detecting malicious hosts based on RE-GCN in intranet by Haochen Xu, Xiaoyu Geng, Junrong Liu, Zhigang Lu, Bo Jiang, Yuling Liu

“…For malicious host detection, this paper proposes the Relational-Edge Graph Convolutional Network (RE-GCN) model, which can directly aggregate and learn features on edges and use them to accurately classify nodes, compared to other GNN models. …”
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Development of agricultural pests detection and identification system based on the technology of wireless transmission by Song Gelian, Han Ruizhen, Zhang Yonghua, He Yong

“…The automatic remote pest-identification system is developed aiming at solving the difficulty of detecting pests in good timing in farmland, which applies modern wireless image and data transaction tools. …”
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UNSUPERVISED DYNAMIC TOPIC MODEL FOR EXTRACTING ADVERSE DRUG REACTION FROM HEALTH FORUMS by Behnaz ESLAMI, Mehdi HABIBZADEH MOTLAGH, Zahra REZAEI, Mohammad ESLAMI, Mohammad AMIN AMINI

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Modeling the spatial dynamics of land cover transitions and vegetation conditions in Abuja city, Nigeria by Yoksa Salmamza Mshelia, Simon Mang’erere Onywere, Sammy Letema

“…A post-classification comparison was used to detect the dynamics of land cover transitions. A hybrid simulation model that comprised cellular automata and Markovian was used to model the probable scenario of land cover changes for 2050. …”
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Automated Dead Chicken Detection in Poultry Farms Using Knowledge Distillation and Vision Transformers by Ridip Khanal, Wenqin Wu, Joonwhoan Lee

“…Then, a deep learning classifier, enhanced through knowledge distillation, confirms whether the detected stationary object is indeed a chicken. …”
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Modeling Estuarine Algal Bloom Dynamics with Satellite Data and Spectral Index-Based Classification by Mayya Podsosonnaya, Maria J. Schreider, Sergei Schreider

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LiDAR Point Inpainting Model Using Smoothness Loss for SLAM in Dynamic Environments by Changwan Han, I Made Putra Arya Winata, Junghyun Oh

“…Since performing simultaneous localization and mapping in dynamic environments is a challenging problem, conventional approaches have used preprocessing to detect and then remove movable objects from images. …”
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Supervised and unsupervised deep learning-based approaches for studying DNA replication spatiotemporal dynamics by Julian Ng-Kee-Kwong, Ben Philps, Fiona N. C. Smith, Aleksandra Sobieska, Naiming Chen, Constance Alabert, Hakan Bilen, Sara C. B. Buonomo

“…We first apply supervised machine learning, successfully classifying S-phase patterns in wild-type mouse embryonic stem cells (mESCs), while additionally identifying altered replication dynamics in Rif1-deficient mESCs. …”
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Obstacle Detection in Hybrid Cross-Country Environment Based on Markov Random Field for Unmanned Ground Vehicle by Feng Ding, Yibing Zhao, Lie Guo, Mingheng Zhang, Linhui Li

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Infrared thermography for spatiotemporal analysis of high-temperature oxidation dynamics in AISI 1045 steel by Antony Morales-Cervantes, Gerardo Marx Chávez-Campos, Héctor Javier Vergara-Hernández, Jorge Sergio Téllez-Martínez, Maritza Fabiola León-Bejarano

“…During the transient heating stages, up to 60% of pixels were classified as local anomalies and peaks of 40% were observed in the state-change rate, whereas during the stable isothermal phase only 1%–5% of pixels changed, revealing continuous micro-dynamics such as oxide growth, spallation, or emissivity shifts. …”
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Change Detection Analysis and Deforestation Rates in Oluwa Forest Reserve, Ondo State, Nigeria by J.O. Mephors, O.S. Afolabi, O.M. Ogoliegbune, I.S. Adamu, A.R. Orunkoyi

“…This study examined the use of GIS and remote sensing techniques to gain a quantitative understanding of the spatiotemporal dynamics of LULC. Maximum likelihood classifier approach was used to detect LULC changes in the study area of 1989 to 2019 using three Landsat images from 1989, 2004 and 2019. …”
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