A Comprehensive Approach for Detecting and Handling MitM-ARP Spoofing Attacks by Standy Oei, Yohanes Suyanto, Reza Pulungan

“…In the host, we employ a combination of ping Round-Trip Time (RTT) anomaly detection, the SendARP function, static entry, and ping confirmation to detect and mitigate attacks. …”
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SGSNet: a lightweight deep learning model for strawberry growth stage detection by Zhiyu Li, Jianping Wang, Guohong Gao, Yufeng Lei, Chenping Zhao, Yan Wang, Haofan Bai, Yuqing Liu, Xiaojuan Guo, Qian Li

“…Furthermore, SGSNet has a computational cost of only 14.7 GFLOPs and a parameter count as low as 5.86 million, demonstrating an effective balance between high performance and resource efficiency.DiscussionLightweight deep learning model SGSNet not only exceeds the mainstream model in detection accuracy, but also greatly reduces the need for computing resources and is suitable for portable devices. …”
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Automatic detection of floating instream large wood in videos using deep learning by J. Aarnink, J. Aarnink, T. Beucler, T. Beucler, M. Vuaridel, V. Ruiz-Villanueva, V. Ruiz-Villanueva

“…Therefore, the findings of this paper could be used when designing a custom wood detection network. With the growing availability of flood-related videos featuring wood uploaded to the internet, this methodology facilitates the quantification of wood transport across a wide variety of data sources.…”
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Gold nanobiosensors and Machine Learning: Pioneering breakthroughs in precision breast cancer detection by Soheil Sadr, Ashkan Hajjafari, Abbas Rahdar, Sadanand Pandey, Parian Poorjafari Jafroodi, Narges Lotfalizadeh, Mahdi Soroushianfar, Shahla Salimpour Kavasebi, Zelal Kharaba, Sonia Fathi-karkan, Hassan Borji

“…These sensors take advantage of the unique optical and electric properties that gold nanoparticles have, enabling them to achieve an accurate molecular level of detection. Gold nanobiosensors have been significantly developed through innovations like signal amplification and surface functionalization, integrated with the use of advanced imaging techniques. …”
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YOLOX-LS: Strong Gravitational Lenses Detection in the DECaLS with Deep Learning by Yangyang Liu, Liangping Tu, Jianxi Li, Jiawei Miao, Gengqi Lin, Chenying Zhao

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First Detection of Low-frequency Striae in Interplanetary Type III Radio Bursts by Vratislav Krupar, Eduard P. Kontar, Jan Soucek, Lynn B. Wilson III, Adam Szabo, Oksana Kruparova, Hamish A. S. Reid, Mychajlo Hajos, David Pisa, Ondrej Santolik, Milan Maksimovic, Jolene S. Pickett

“…By combining high-resolution radio observations with well-calibrated in situ electron velocity distribution function data from the Wind spacecraft, we characterized the plasma properties of the burst source region near 0.32 au. …”
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Failure Law of Sandstone and Identification of Premonitory Deterioration Information Based on Digital Image Correlation–Acoustic Emission Multi-Source Information Fusion by Zhaohui Chong, Guanzhong Qiu, Xuehua Li, Qiangling Yao

“…Additionally, by introducing the derivative functions of the multi-source information function for quantitative analysis, a comprehensive evaluation method was proposed based on the multi-source information fusion monitoring to forewarn red sandstone failure by levels during loading. …”
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A Hybrid and Modular Integration Concept for Anomaly Detection in Industrial Control Systems by Christian Goetz, Bernhard G. Humm

“…Therefore, in this paper, we present a modular and hybrid concept that enables the integration of efficient and effective anomaly detection while optimising the use of available resources under consideration of industrial requirements. …”
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An optimization method of multiscale storage tank target detection introducing an attention mechanism by Wenjia Sun, Chunchun Hu, Nianxue Luo, Qiansheng Zhao

“…As containers for chemical storage, storage tanks are potential sources of hazards. Conducting target detection for hazard risk analysis is essential. …”
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Review of Fault Detection and Diagnosis Methods in Power Plants: Algorithms, Architectures, and Trends by Camelia Adela Maican, Cristina Floriana Pană, Daniela Maria Pătrașcu-Pană, Virginia Maria Rădulescu

“…Key findings are summarized in a comparative matrix, highlighting trends, gaps, and inconsistencies across publication sources. This review identifies critical research gaps—including the underuse of hybrid models, lack of benchmark datasets, and limited integration between detection and control layers—and offers concrete recommendations for future research. …”
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Developing a Machine Vision System to Detect Weeds from Potato Plant by Yousef Abbaspour Gılandeh, Hossein Javadıkıa, Sajad Sabzı

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An Efficient Algorithm for Small Livestock Object Detection in Unmanned Aerial Vehicle Imagery by Wenbo Chen, Dongliang Wang, Xiaowei Xie

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Harnessing polydiacetylene (PDA): A review of structural mechanics and infectious disease detection by Soumendu Patra, Harshita Shand, Sayan Ghosal, Suvankar Ghorai

“…These biosensors can also be functionalized with particular capture agents, such as antibodies or nucleic acid probes, to selectively bind and detect the target analytes. …”
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An enhanced lightweight model for apple leaf disease detection in complex orchard environments by Ge Wang, Wenjie Sang, Fangqian Xu, Yuteng Gao, Yue Han, Qiang Liu

“…However, in complex natural environments, factors such as light variations, shading from branches and leaves, and overlapping disease spots often result in reduced accuracy in detecting apple diseases. To address the challenges of detecting small-target diseases on apple leaves in complex backgrounds and difficulty in mobile deployment, we propose an enhanced lightweight model, ELM-YOLOv8n.To mitigate the high consumption of computational resources in real-time deployment of existing models, we integrate the Fasternet Block into the C2f of the backbone network and neck network, effectively reducing the parameter count and the computational load of the model. …”
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Application of VGG16 in Automated Detection of Bone Fractures in X-Ray Images by Resky Adhyaksa, Bedy Purnama

“…The training and testing phases utilized an 80:20 split of the data, employing binary cross-entropy as the loss function and the Adam optimizer for efficient weight updates. …”
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Multi-Person Fall Detection Using Data Assimilation Method With Kalman Filter by Jinmo Yang, Ye Jin Jin, R. Young Chul Kim

“…Fall detection is an essential technology for ensuring the safety of elderly individuals, as falling accidents are critical and can cause significant functional damage in old age. …”
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Detection of Elementary White Mucosal Lesions by an AI System: A Pilot Study by Gaetano La Mantia, Federico Kiswarday, Giuseppe Pizzo, Giovanna Giuliana, Giacomo Oteri, Mario G. C. A. Cimino, Olga Di Fede, Giuseppina Campisi

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Securing Electric Vehicle Performance: Machine Learning-Driven Fault Detection and Classification by Mahbub Ul Islam Khan, Md. Ilius Hasan Pathan, Mohammad Mominur Rahman, Md. Maidul Islam, Mohammed Arfat Raihan Chowdhury, Md. Shamim Anower, Md. Masud Rana, Md. Shafiul Alam, Mahmudul Hasan, Md. Shohanur Islam Sobuj, Md. Babul Islam, Veerpratap Meena, Francesco Benedetto

“…In addition, the superiority of the proposed fault detection and classification approaches using ML tools was assessed by comparing the detection and classification efficiency through some statistical performance parameter comparisons among the classifiers.…”
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Near-source wastewater surveillance of SARS-CoV-2, norovirus, influenza virus and RSV across five different sites in the UK. by Jay C Bullen, Mina Mohaghegh, Fatima Tahir, Charlotte Hammer, Jacob Sims, Frederico Myers, Lucas Eisinger, Ali Reza Kasmati, Claire F Trant

“…The key findings are (1) near-source wastewater detections were linked to local events (staff sickness, enhanced cleaning, changing populations); (2) wastewater detections decreased in the order norovirus GII > norovirus GI > SARS-CoV-2 ≈ influenza A ≈ RSV A > influenza B ≈ RSV B; (3) correlation between near-source wastewater data and national surveillance data increases as a function of catchment size and viral prevalence (examples include the SARS-CoV-2 BA.4/BA.5 variant peak at a museum and wastewater tracking the winter norovirus season); (4) strong weekday periodicity in near-source wastewater SARS-CoV-2 detections, with the correlation against COVID-19 case numbers increasing when modelling variable lag times between faecal shedding onset and clinical diagnosis (R2 = 0.45 increases to 0.84-0.86); (5) a log-linear relationship between the frequency of wastewater SARS-CoV-2 detection and log(catchment size⋅viral prevalence) (R2 = 0.6914-0.9066). …”
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Three-Dimensional Real-Scene-Enhanced GNSS/Intelligent Vision Surface Deformation Monitoring System by Yuanrong He, Weijie Yang, Qun Su, Qiuhua He, Hongxin Li, Shuhang Lin, Shaochang Zhu

“…The system integrates GNSS monitoring terminals and multi-source meteorological sensors to accurately capture minute displacements at monitoring points and multi-source Internet of Things (IoT) data, which are then automatically stored in MySQL databases. …”
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