AOAFS: A Malware Detection System Using an Improved Arithmetic Optimization Algorithm by Rafat Alshorman, Bilal H. Abed-alguni, Yaqeen E. Alqudah

“…This issue diminishes the efficacy of Machine Learning models used for malware detection. Feature Selection (FS) is an approach commonly used to reduce the number of features in a malware detection dataset to a smaller set of features to facilitate the ease of the Machine Learning process. …”
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VAE-WACGAN: An Improved Data Augmentation Method Based on VAEGAN for Intrusion Detection by Wuxin Tian, Yanping Shen, Na Guo, Jing Yuan, Yanqing Yang

“…To address the class imbalance issue in network intrusion detection, which degrades performance of intrusion detection models, this paper proposes a novel generative model called VAE-WACGAN to generate minority class samples and balance the dataset. …”
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Tomato ripeness detection method based on FasterNet block and attention mechanism by Ming Chen, Yixuan Xu, Wanxiang Qin, Yan Li, Jiyang Yu

“…In addition, the SimAM attention mechanism is introduced, enabling the model to intelligently focus on key features of the tomatoes, thereby improving its ability to recognize tomatoes at different maturity stages and enhancing detection accuracy. Furthermore, the generalized intersection over union loss function is employed to introduce a target box overlap metric, optimizing the object localization process and improving the precision of fruit positioning. …”
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A Survey on Android Malware Detection Techniques Using Supervised Machine Learning by Safa J. Altaha, Ahmed Aljughaiman, Sonia Gul

“…Machine learning (ML) plays a significant role in malware analysis and detection because it can process huge amounts of data, identify complex patterns, and adjust to changing threats. …”
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SURVEY AND PROPOSED METHOD TO DETECT ADVERSARIAL EXAMPLES USING AN ADVERSARIAL RETRAINING MODEL by Thanh Son Phan, Quang Hua Ta, Duy Trung Pham, Phi Ho Truong

“…This technique aims to enhance the robustness and performance of these models by subjecting them to adversarial scenarios during the training process. In this paper, we survey detection methods and propose a method to detect adversarial examples using YOLOv7, a commonly used intensive research model. …”
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Raspberry Pi-Based IoT System for Grouting Void Detection in Tunnel Construction by Weibin Luo, Junxing Zheng, Yu Miao, Lin Gao

“…This paper presents an IoT-based solution for detecting grouting voids in tunnel construction using the Raspberry Pi microcomputer. …”
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Tuberculosis detection with customized CNN and oversampling techniques: a deep learning approach by B. H. Shekar, Shazia Mannan

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Method of Credit Fraud Detection by Combining Sub-graph Selection and Neighborhood Filtering by TANG Xiaoyong, WANG Haodong

“…Credit fraud detection is a hot and difficult research topic in the field of financial fraud detection, especially fraud detection in the scenario of large-scale financial credit transactions. …”
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Towards a minimum universal features set for IoT DDoS attack detection by Osama Ebrahem, Salah Dowaji, Suhel Alhammoud

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Analysis of TDR Reflection Waveform for Detecting New Energy Power Cable Joint by SUN Tong, WANG Wei, WU Wei-kun, GONG Shi-ying, HE Yong, SHAN Chao

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An Improved Low-Cost Continuous Compaction Detection Method for the Construction of Asphalt Pavement by Tong Jia, Tiejun He, Zhendong Qian, Jian Lv, Kaixin Cao

“…For the monitoring of rolling process, an embedded-based detection system was designed. …”
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Tracing truth: dynamic temporal networks for multi-modal fake news detection by Jiaen Hu, Juan Zhang, Zichen Li

“…In response, This study proposes a multimodal approach to fake news detection—the dynamic temporal network (DTN) model. …”
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Retracted: Internet of Things Health Detection System in Steel Structure Construction Management by Qinglin Liu, Yongjiang Zhu, Xiongzhou Yuan, Jian Zhang, Rui Wu, Qianwen Dou, Song Liu

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POCT Detection of Pseudomonas aeruginosa by PGM and Application of Preventing Nosocomial Infection of Bronchoscopy by Tao Wen, Houqi Ning, Yinping Yang, Jinze Zhang

“…The magnetic nanoparticles (MNPs) were synthesized in a single step, followed by the optimization of the coating process with antibodies and invertase to produce the bifunctionalized IMIc. …”
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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

“…Additionally, the significantly smaller number of fraudulent users than benign users further complicates the detection process. To address these challenges, this paper proposes a Reinforced Cost-sensitive Graph Network (RCGN) for detecting fraud leaders in telecom fraud. …”
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Research on the Seed Respiration CO2 Detection System Based on TDLAS Technology by Lu Gao, Ying Zang, Guangwu Zhao, Hengnian Qi, Qizhe Tang, Qingshan Liu, Liangquan Jia

“…The respiration intensity curves and respiration rate change details show that the seed respiration CO2 detection system is more suitable for a small amount of seeds than nondispersive infrared (NDIR) CO2 sensor and gas chromatography in real-time monitoring of the breathing process.…”
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Global confidence degree based graph neural network for financial fraud detection by Jiaxun Liu, Yue Tian, Guanjun Liu

“…Graph Neural Networks (GNNs) are widely used in financial fraud detection due to their excellent ability on handling graph-structured financial data and modeling multilayer connections by aggregating information of neighbors. …”
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Distributed partition detection and recovery using UAV in wireless sensor and actor networks by Aditi Zear, VIRENDER RANGA

“…The requirements for the recovery process i.e., physical movement and communication are fulfilled by UAV. …”
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Research on detection methods of related substances and degradation products of the antitumor drug selpercatinib by Jingjing Xiang, Liangliang Cai, Qin Wang, Yonghong Zhu, Yong Han

“…BackgroundSelpercatinib, a selective RET kinase inhibitor, is approved for treating various cancers with RET gene mutations such as RET-rearranged thyroid cancer and non-small cell lung cancer. The presence of process-related and degradation impurities in its active pharmaceutical ingredient (API) can significantly affect its safety and effectiveness. …”
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Classification Model for Bot-IoT Attack Detection Using Correlation and Analysis of Variance by Firgiawan Faira, Dandy Pramana Hostiadi

“…This research focuses on detecting Bot-IoT activity using the Bot-IoT UNSW Canberra 2018 dataset. …”
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