An explainable transformer model for Alzheimer’s disease detection using retinal imaging by Saeed Jamshidiha, Alireza Rezaee, Farshid Hajati, Mojtaba Golzan, Raymond Chiong

“…These findings are compared to existing clinical studies on detecting AD using retinal biomarkers, allowing us to identify the most important features for AD detection in each imaging modality. …”
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Analysis and Detection of Four Typical Arm Current Measurement Faults in MMC by Qiaozheng Wen, Shuguang Song, Jiaxuan Lei, Qingxiao Du, Wenzhong Ma

“…The entire fault detection process takes less than 20 ms. Finally, the feasibility and effectiveness of the proposed method are validated through MATLAB/Simulink simulations and experimental results.…”
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Automatic eddy detection in the MIZ based on YOLO algorithm and SAR images by Nikita Sandalyuk, Eduard Khachatrian

“…Thus, we explored the feasibility of automating the eddy detection process by applying YOLOv8, a state-of-the-art computer vision model, to high-resolution synthetic aperture radar data, specifically targeting the dynamic region of the Fram Strait. …”
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RFID-embedded mattress for sleep disorder detection for athletes in sports psychology by Metin Pekgor, Aydolu Algin, Turhan Toros

“…A multi-layered mattress design integrates advanced RFID technology with machine learning algorithms—Gaussian process regression (GPR) and linear regression (LR)—to classify postures and detect movement anomalies. …”
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An Object Detection Algorithm for Orchard Vehicles Based on AGO-PointPillars by Pengyu Ren, Xuyun Qiu, Qi Gao, Yumin Song

“…With the continuous expansion of the orchard planting area, there is an urgent need for autonomous orchard vehicles that can reduce the labor intensity of fruit farmers and improve the efficiency of operations to assist operators in the process of orchard operations. An object detection system that can accurately identify potholes, trees, and other orchard objects is essential to achieve unmanned operation of the orchard vehicle. …”
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ANALYZING EEG SIGNALS FOR STRESS DETECTION USING RANDOM FOREST ALGORITHM by Fi Imanur Sifaunnufus Ms, Fitra Abdurrachman Bachtiar, Barlian Henryranu Prasetio

“…Detection of stress using EEG signals has gained much interest because of monitoring and early intervention. …”
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Physical-social attributes integrated Sybil detection for Tor bridge distribution by Xin SHI, Yunfei GUO, Yawen WANG, Xiaoli SUN, Hao LIANG

“…As one of the most widely utilized censorship circumvention systems, Tor faces serious Sybil attacks in bridge distribution.Censors with rich network and human resources usually deploy a large number of Sybils, which disguise themselves as normal nodes to obtain bridges information and block them.In the process, due to the different identities, purposes and intentions of Sybils and normal nodes, individual or group behavior differences occur in network activities, called as node behavior characteristics.To handle the Sybil attacks threat, a Sybil detection mechanism integrating physical-social attributes was proposed based on the analysis of node behavior characteristics.The physical-social attributes evaluation methods were designed.The credit value of nodes objectively reflecting the operation status of bridges on the nodes and the suspicion index of nodes reflecting the blocking status of bridges, were utilized to evaluate the physical attributes of nodes.The social attributes of nodes were evaluated by the social similarity, which described the static attribute labels of nodes and their social trust characterizing the dynamic interaction behaviors of nodes.Furthermore, integrating the physical-social attributes, the credibility of nodes were defined as the possibility of the current node being a Sybil, which was exploited as a guidance on inferring the true identifies of nodes, so as to achieve accurate detection on Sybils.The detection performance of the proposed mechanism based on the constructed Tor network operation status simulator and the Microblog PCU dataset were simulated.The results show that the proposed mechanism can effectively improve the true positive rate on Sybils, and decrease the false positive rate.It also has stronger resistance on the deceptive behavior of censors, and still performs well in the absence of node social attributes.…”
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An Earlier Predictive Rollover Index Designed for Bus Rollover Detection and Prevention by Shun Tian, Lang Wei, Chris Schwarz, WenCai Zhou, Yuan Jiao, YanQin Chen

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JDroid: Android malware detection using hybrid opcode feature vector by Recep Sinan Arslan

“…Experimental results show that the proposed approach has an accuracy value of 98.6% and an area under the curve (AUC) value of 99.6% in malware detection without being affected by the obfuscation process.…”
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A systematic review of ulcer detection methods in wireless capsule endoscopy by Ahmmad Musha, Rehnuma Hasnat, Abdullah Al Mamun, Md Sohag Hossain, Md Jakir Hossen, Tonmoy Ghosh

“…However, manually reviewing images captured by WCE is a tedious and time-consuming process. Implementing a computer-aided ulcer detection system can facilitate the automatic evaluation of these images. …”
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Streamlining Deep Learning Network for Real-time Sea Turtle Detection by Muhamad Dwisnanto Putro, Yuliana Mose, Alex Copernikus Andaria, Jane Litouw, Vecky Canisius Poekoel, Xaverius Najoan

“…Monitoring turtle behavior is a conservation effort to preserve its habitat, and the detection process is a vital initial stage. On the other hand, robotics demands a deep learning network to automatically detect the presence of sea turtles that can operate in real-time. …”
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Detection and diagnosis of air compressor faults using weightless neural networks by Anubhab Bhattacharyya, Naveen Venkatesh Sridharan, Aravinth Sivakumar, Sugumaran Vaithiyanathan

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Selection and Application of Specific Nucleic Acid Aptamers for the Detection of Pseudomonas aeruginosa by LI Xu, CHENG Yangyang, YANG Kai, LIU Benkang, LI Cheng

“…Under optimized concentration of Apt13 and incubation time of P. aeruginosa, the fluorescence quenching intensity exhibited a linear relationship with the concentration of P. aeruginosa ranging from 101 to 108 CFU/mL. The limit of detection (LOD) was 2 CFU/mL, and the entire detection process took less than 2.0 h. …”
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Radiomics-based machine learning for automated detection of Pneumothorax in CT scans. by Hanieh Alimiri Dehbaghi, Karim Khoshgard, Hamid Sharini, Samira Jafari Khairabadi, Farhad Naleini

“…This study addresses the pressing need for improved diagnostic accuracy in CT scans by developing an intelligent model that leverages radiomics features and machine learning techniques. By enhancing the detection of pneumothorax, this research aims to mitigate diagnostic errors and accelerate the process of image interpretation, ultimately improving patient outcomes. …”
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Visual Positioning Detection of EMU Brake Pad Based on Deep Learning by GUAN Chunling, XU Yingjie, SONG Yuechao

“…Through the bilinear interpolation method, the misalignment errors of target features during ROI (region of interest) pooling quantization process are reduced. The proposed brake pad detection method achieves an average precision of 98.42% and an FPS (frames per second) of 27.77%.…”
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Performance Evaluation of a Visual Defects Detection System for Railways Monitoring by Radosavljevic Saša, Rivero Alain, Rodríguez Flórez Sergio, El Ouardi Abdelhafid, Michel Pauline, Bouamama Belkacem O., Vanheeghe Philippe

“…This study addresses visual defects detection that can be integrated in a multi-modal monitoring system. …”
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Modified QuEChERS for antiepileptic drugs detection in forensic toxicology by Ahmad Shekari, Jalal Hassan, Mohammad Kazem Koohi, Masoud Ghadipasha, Maryam Akhgari

“…One influencing parameter on the extraction process was the pH of sample. Extraction recoveries were in the range of 42–97 % for all analytes. …”
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An intelligent spam detection framework using fusion of spammer behavior and linguistic. by Amna Iqbal, Muhammad Younas, Muhammad Kashif Hanif, Muhammad Murad, Rabia Saleem, Muhammad Aater Javed

“…The proposed spam detection framework SD-FSL-CLSTM used the fusion of spammer behavior features and linguistic features which automatically detect and classify the spam reviews. …”
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Self-supervised change detection of heterogeneous images based on difference algorithms by Jinsha Wu, Shuwen Yang, Yikun Li, Yukai Fu, Zhuang Shi, Yao Zheng

“…Secondly, the hierarchical FCM clustering algorithm is improved to extract stable and correct self-supervised samples by difference images so that the clustering process is not overly dependent on thresholds. Then, the support vector machine classifier is trained based on the heterogeneous images, the fused images, and self-supervised sample sets, and the information from the fused images is utilized to increase the feature dimension for better detection of changes. …”
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Enhanced Graph Autoencoder for Graph Anomaly Detection Using Subgraph Information by Chi Zhang, Jin-Woo Jung

“…Graph anomaly detection aims at identifying rare, unusual entities in attributed networks with respect to their patterns or structures that deviate significantly from the majority within a graph. …”
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