Hybrid Naïve Bayes Models for Scam Detection: Comparative Insights From Email and Financial Fraud by Lebede Ngartera, Mahamat Ali Issaka, Saralees Nadarajah

“…This study revisits the Naïve Bayes algorithm—often underestimated in modern cybersecurity—as a core building block for effective scam detection. …”
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RNA-BioLens: A Novel Raspberry Pi-Based Digital Microscope With Image Processing for Acute Lymphoblastic Leukemia Detection by Angeline Dwi Sanjaya, Rachmad Setiawan, Nada Fitrieyatul Hikmah

“…To address these challenges, this study presents a simplified digital microscope system integrated with the YOLOv4 (You Only Look Once) algorithm combined with additional segmentation and feature extraction methods designed explicitly for ALL cell detection. …”
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Plasma lipidomic analysis reveals disruption of ether phosphatidylcholine biosynthesis and facilitates early detection of hepatitis B-related hepatocellular carcinoma by Yuyao Yuan, Donghao Yin, Xuemeng Yang, Di Liu, Hui Shan, Juan Luo, Xiuhui Li, Yuxin Yin

“…Potential regulatory mechanisms are validated at multi-omic levels. A machine learning algorithm is used for feature selection and diagnostic modelling, and performance of the models is evaluated by ROC curves. …”
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Automatic vibration fault detection of coal mine explosion-proof electrical equipment based on One-Class Support Vector Machine by ZHENG Tiehua, WANG Fei, ZHAO Gelan, DU Chunhui

“…Experimental results showed that: ① When the number of iterations is 20, the OCSVM algorithm can complete convergence and achieve stability. ② In the electrical equipment signal classification experiment based on OCSVM, the use of the polynomial kernel function accurately classified samples for detection. ③ In the performance analysis of automatic vibration fault detection, the proposed method showed significantly higher accuracy across different sample sizes than infrared thermography and detection methods based on grey wolf optimization and support vector machine. …”
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IMM4HT:an identification method of malicious mirror website for high-speed network traffic by Lei ZHANG, Peng ZHANG, Wei SUN, Xingdong YANG, Lichao XING

“…Aiming at the problem that some information causing harm to the network environment was transmitted through the mirror website so as to bypass the detection,an identification method of malicious mirror website for high-speed network traffic was proposed.At first,fragmented data from the traffic was extracted,and the source code of the webpage was restored.Next,a standardized processing module was utilized to improve the accuracy.Additionally,the source code of the webpage was divided into blocks,and the hash value of each block was calculated by the simhash algorithm.Therefore,the simhash value of the webpage source codes was obtained,and the similarity between the webpage source codes was calculated by the Hamming distance.The page snapshot was then taken and SIFT feature points were extracted.The perceptual hash value was obtained by clustering analysis and mapping processing.Finally,the similarity of webpages was calculated by the perceptual hash values.Experiments under real traffic show that the accuracy of the method is 93.42%,the recall rate is 90.20%,the F value is 0.92,and the processing delay is 20 μs.Through the proposed method,malicious mirror website can be effectively detected in the high-speed network traffic environment.…”
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Convolutional transform learning based fusion framework for scale invariant long term target detection and tracking in unmanned aerial vehicles by Fatma S. Alrayes, Nazir Ahmad, Asma Alshuhail, Menwa Alshammeri, Ali Alqazzaz, Hassan Alkhiri, Jehad Saad Alqurni, Yahia Said

“…For object detection (OD), the highly accurate YOLOv8 technique is utilized, followed by feature extraction through a backbone deep fusion-based convolutional transform learning of VGG16, CapsNet, and EfficientNetB7 to capture both spatial and hierarchical features across varying scales. …”
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Key frame extraction based abnormal vehicle identification technique using statistical distribution analysis by M. A. Y. Peer Mohamed Appa, V. Vanitha, Priti Rishi, Shrddha Sagar, M. Asha Paul

“…The experimental results are carried out using Car Accident Detection Dataset (CADP). For evaluating performance of KFEAVI, several algorithms are compared with the KFEAVI. …”
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An Innovative Small-Target Detection Approach Against Information Attenuation: Fusing Enhanced Programmable Gradient Information and a Novel Mamba Module by Yang Liu, Yatu Ji, Qingdaoerji Ren, Bao Shi, Na Liu, Min Lu, Nier Wu

“…In small-target detection tasks, this problem becomes more serious. …”
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Detection of Damage on Inner and Outer Races of Ball Bearings Using a Low-Cost Monitoring System and Deep Convolution Neural Networks by Handeul You, Dongyeon Kim, Juchan Kim, Keunu Park, Sangjin Maeng

“…Furthermore, an explainable AI technique is applied to extract key feature values identified by the fault classification algorithm, providing a method to support the analysis of fault causes.…”
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Robust Bi-CBMSegNet framework for advancing breast mass segmentation in mammography with a dual module encoder-decoder approach by Yu Wang, Mudassar Ali, Tariq Mahmood, Amjad Rehman, Tanzila Saba

“…However, segmenting and classifying breast masses in mammograms is challenging due to their similar shapes to the surrounding glands. Current target detection algorithms have limited applications and low accuracy. …”
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Automated Detection of Recent Mud Extrusions Using UAV Imagery and Deep Learning: A Comparative Analysis of Traditional and CNN-Based Approaches by M. Guastella, M. Guastella, A. Pisciotta, R. Martorana, A. D’Alessandro

“…Traditional algorithms rely on handcrafted features, while CNNs learn hierarchical representations directly from raw data. …”
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Deep-m6Am: a deep learning model for identifying N6, 2′-O-Dimethyladenosine (m6Am) sites using hybrid features by Islam Uddin, Salman A. AlQahtani, Sumaiya Noor, Salman Khan

“…To enhance computational efficiency and eliminate noisy or redundant features, a supervised SHAP (SHapley Additive exPlanations) algorithm is utilized, ensuring the selection of the most informative features. …”
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Intelligent library shelf management system for open-access environments: A CNN-based approach with enhanced image recognition and disorder detection by Xueqi Zhang

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Development of Model for Traffic Flows on Urban Street and Road Network by D. V. Kapskiy, D. V. Navoy, P. A. Pegin

“…Innovation in the first-level model is an approach in determining conditions while detecting a fuzzy set without using a standard algorithm that is an algorithm of local flexible regulation. …”
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An Efficient Optimal CapsNet Model-Based Computer-Aided Diagnosis for Gastrointestinal Cancer Classification by Fahdah A Almarshad, Prasanalakshmi Balaji, Liyakathunisa Syed, Eman Aljohani, Santhi Muttipoll Dharmarajlu, Thavavel Vaiyapuri, Nourah Ali AlAseem

“…This technique has great promise for transforming initial detection and involvement in the battle against dangerous diseases. …”
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LSD-Det: A Lightweight Detector for Small Ship Targets in SAR Images by Zhen Wang, Bin Qin, Shang Gao

“…However, ship targets in SAR images are often small, have blurred edges, and suffer from strong background interference, making it difficult for traditional detection algorithms to balance accuracy and real-time performance. …”
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Enhanced defect sensing technology in turbid water environments using multi-beam sonar by Wenhui Wang, Yikai Li, Rufei He, Yao Li

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Machine learning enhanced expert system for detecting heart failure decompensation using patient reported vitals and electronic health records by Shumit Saha, Heather Ross, Pedro Elkind Velmovitsky, Chloe X. Wang, Julie K. K. Vishram-Nielsen, Cedric Manlhiot, Bo Wang, Joseph A. Cafazzo

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Advanced Support Vector Machine- (ASVM-) Based Detection for Distributed Denial of Service (DDoS) Attack on Software Defined Networking (SDN) by Myo Myint Oo, Sinchai Kamolphiwong, Thossaporn Kamolphiwong, Sangsuree Vasupongayya

“…In this paper, we can successfully detect two types of flooding-based DDoS attacks. Our detection technique can reduce the training time as well as the testing time by using two key features, namely, the volumetric and the asymmetric features. …”
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Characterizing and Detecting Multiscenario Degradation of the Maidika Alpine Wetland Nature Reserve in the Qinghai–Tibet Plateau Using Landsat Time Series by Ye Chen, Ren Ci, Dongping Zhong, Liangyun Liu, Jinyuan Yu, Dongdong Zhang, Yindong Tong, Yingchun Fu

“…Based on 3 elements, spectral–temporal characterization, classification, and degradation detection for wetland covers, this study proposes a continuous classification and degradation detection algorithm for alpine wetlands (AW-CCD). …”
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