Detecting Fraudulent Transaction in Banking Sector Using Rule-Based Model and Machine Learning by Cut Dinda Rizki Amirillah

“…The RBM model was used as an initial approach, detecting suspicious transaction patterns based on defined rules. …”
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Detecting Subtle Cyberattacks on Adaptive Cruise Control Vehicles: A Machine Learning Approach by Tianyi Li, Mingfeng Shang, Shian Wang, Raphael Stern

“…The proposed approach is observed to outperform contemporary neural network models in detecting irregular driving patterns of ACC vehicles.…”
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Point-of-care lung ultrasound for the detection of pulmonary manifestations of malaria and sepsis: An observational study. by Stije J Leopold, Aniruddha Ghose, Katherine A Plewes, Subash Mazumder, Luigi Pisani, Hugh W F Kingston, Sujat Paul, Anupam Barua, M Abdus Sattar, Michaëla A M Huson, Andrew P Walden, Patricia C Henwood, Elisabeth D Riviello, Marcus J Schultz, Nicholas P J Day, Asok Kumar Dutta, Nicholas J White, Arjen M Dondorp

“…We quantified aeration patterns across 12 lung regions. ARDS was defined according to the Kigali Modification of the Berlin Definition.…”
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DAHD-YOLO: A New High Robustness and Real-Time Method for Smoking Detection by Jianfei Zhang, Chengwei Jiang

“…Recent advancements in AI technologies have driven the extensive adoption of deep learning architectures for recognizing human behavioral patterns. However, the existing smoking behavior detection models based on object detection still have problems, including poor accuracy and insufficient real-time performance. …”
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Driven early detection of chronic kidney cancer disease based on machine learning technique. by Wafa Almukadi, Sayed Abdel-Khalek, Adel A Bahaddad, Ahmed Mohammed Alghamdi

“…These methods are adept at recognizing complex patterns and anomalies within HIs, accelerating the diagnostic method and increasing accuracy. …”
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Enhancing Medicare Fraud Detection With a CNN-Transformer-XGBoost Framework and Explainable AI by Mohammad Balayet Hossain Sakil, Md Amit Hasan, Md Shahin Alam Mozumder, Md Rokibul Hasan, Shafiul Ajam Opee, M. F. Mridha, Zeyar Aung

“…The framework integrates convolutional neural networks (CNNs), transformers, and XGBoost to capture intricate patterns in claims data while maintaining interpretability through Shapley additive explanations. …”
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Anomaly detection method for cyber physical power system based on bilateral data fusion by Tianlei Zang, Shijun Wang, Chuangzhi Li, Yunfei Liu, Yujian Xiao, Zian Wang, Xueying Yu

“…Second, a transformer-based detection model is established to extract dynamic network attributes and state transition patterns in cyber-side data. …”
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An intelligent intrusion detection system for cyber-physical systems using GAN-LSTM networks by Md Shakil Siddique, Md. Ashikur Rahman Khan, Ishtiaq Ahammad, Nishu Nath, Joysri Rani Das, Fardowsi Rahman

“…Notably, it attains 99 % recall on SWaT, ensuring near-complete attack detection, though WADI recall remains lower (75 %) due to complex attack patterns. …”
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Expanding and Interpreting Financial Statement Fraud Detection Using Supply Chain Knowledge Graphs by Shanshan Zhu, Tengyun Ma, Haotian Wu, Jifan Ren, Daojing He, Yubin Li, Rui Ge

“…The relationships within a supply chain are crucial for analyzing business transactions and can reveal significant patterns in disclosed financial data. These relationships also aid in the assessment and detection of financial fraud. …”
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Triplet-Style Dynamic Graph Network With Transformer Encoder for Scam Detection in Cryptocurrency Transactions by Min-Woo Nam, Hyeon-Ju Lee, Seok-Jun Buu

“…TD-GCN’s performance gains stem from its dynamic updates for evolving networks and Triplet Learning for disentangling subtly different patterns. These features enable TD-GCN to significantly bolster cryptocurrency security by effectively detecting scams and minimizing false positives in dynamic transaction networks.…”
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Convolutional neural network approach for fault detection and characterization in medium voltage distribution networks by Atefeh Pour Shafei, J.Fernando A. Silva, J. Monteiro

“…Simulation results reveal that while the voltage Park's vector time behavior of a healthy system remains stable, it exhibits circular or mixed patterns under faulty conditions. These patterns enable the identification of four types of short circuit faults—single-line-to-ground (LG), line-to-line (LL), line-to-line-to-ground (LLG), and three-line (3L) faults—by analyzing 3D voltage Park's waveforms at network buses. …”
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Meta-Learning Approach for Adaptive Anomaly Detection from Multi-Scenario Video Surveillance by Deepak Kumar Singh, Dibakar Raj Pant, Ganesh Gautam, Bhanu Shrestha

“…Video surveillance is widely used in different areas like roads, malls, education, industries, retail, parks, bus stands, and restaurants, each presenting distinct anomaly patterns that demand specialized detection strategies. …”
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Deep Learning–Based Enhanced Optimization for Automated Rice Plant Disease Detection and Classification by P. Preethi, R. Swathika, S. Kaliraj, R. Premkumar, J. Yogapriya

“…Specifically, a deep dense neural network (DNN) is employed for its capacity to capture intricate patterns in images and extreme learning machine (ELM) for classification. …”
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Arrhythmia detection with transfer learning architecture integrating the developed optimization algorithm and regularization method by Fatma Akalın, Pınar Dervişoğlu Çavdaroğlu, Mehmet Fatih Orhan

“…In addition, since the ECG patterns in pediatric patients are different from the ECG patterns in adults, physicians consider it a difficult and complex task. …”
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Electricity Theft Detection Using Rule-Based Machine Leaning (rML) Approach by Sheyda Bahrami, Erol Yumuk, Alper Kerem, Beytullah Topçu, Ahmetcan Kaya

“…Even though consumption-based models have been applied extensively to the detection of power theft, it can be difficult to reliably identify theft instances based only on patterns of usage. …”
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Video anomaly detection via cross-modal fusion and hyperbolic graph attention mechanism by JIANG Di, LAI Huicheng, WANG Liejun

“…Finally, a hyperbolic graph attention mechanism was incorporated to effectively capture the hierarchical relationships between normal and abnormal representations through the pattern separation property of hyperbolic space, thereby improving detection accuracy. …”
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Rapid detection of antibiotic resistance in Burkholderia pseudomallei using MALDI-TOF mass spectrometry by Nut Nithimongkolchai, Yothin Hinwan, Kanwara Trisakul, Lumyai Wonglakorn, Ploenchan Chetchotisakd, Auttawit Sirichoat, Arnone Nithichanon, Sorujsiri Chareonsudjai, Pisit Chareonsudjai, Jody Phelan, Taane G. Clark, Kiatichai Faksri

“…MALDI-TOF MS analysis revealed clustering patterns associated with resistance. A decision tree algorithm identified ten significant peaks that effectively distinguished resistant isolates. …”
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Paraphrase detection for Urdu language text using fine-tune BiLSTM framework by Muhammad Ali Aslam, Khairullah Khan, Wahab Khan, Sajid Ullah Khan, Abdullah Albanyan, Shabbab Ali Algamdi

“…Abstract Automated paraphrase detection is crucial for natural language processing (NL) applications like text summarization, plagiarism detection, and question-answering systems. …”
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Ransomware detection and family classification using fine-tuned BERT and RoBERTa models by Amjad Hussain, Ayesha Saadia, Faeiz M. Alserhani

“…By leveraging the dynamic analysis with API call sequences in a correct format, and training hyperparameter-optimized transformer learning-based models, the methodology efficiently captures behavioral patterns unique to ransomware. The research provides a scalable framework for integrating advanced detection mechanisms into real-world healthcare IoT systems, enhancing their resilience against cyber threats.…”
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Roadside LiDAR Vehicle Detection and Tracking Using Range and Intensity Background Subtraction by Tianya Zhang, Peter J. Jin

“…In this study, we developed the solution of roadside LiDAR object detection using a combination of two unsupervised learning algorithms. …”
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