Auto forensic detecting algorithms of malicious code fragment based on TensorFlow by Binglong LI, Jinlong TONG, Yu ZHANG, Yifeng SUN, Qingxian WANG, Chaowen CHANG

“…In order to auto detect the underlying malicious code fragments in complex，heterogeneous and massive evidence data about digital forensic investigation, a framework for malicious code fragment detecting algorithm based on TensorFlow was proposed by analyzing TensorFlow model and its characteristics.Back-propagation training algorithm was designed through the training progress of deep learning.The underlying binary feature pre-processing algorithm of malicious code fragment was discussed and proposed to address the problem about different devices and heterogeneous evidence sources from storage media and such as AFF forensic containers.An algorithm which used to generate data set about code fragments was designed and implemented.The experimental results show that the comprehensive evaluation index F₁of the method can reach 0.922, and compared with CloudStrike, Comodo, FireEye antivirus engines, the algorithm has obvious advantage in dealing with the underlying code fragment data from heterogeneous storage media.…”
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Aggregation-Induced Emissive Scintillators: A New Frontier for Radiation Detection and Imaging by Xinyi Li, Jiafu Yu, Yinghao Fan, Yuting Gao, Guangda Niu

“…Reviews the progress in AIE materials’ radiation response for efficient detection of X-rays, γ rays, neutrons, and other radiation types. …”
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Real Time Face-mask Detection with Arduino to Prevent COVID-19 Spreading by Saman M. Almufti, Ridwan B. Marqas, Zakiya A. Nayef, Tamara S. Mohamed

“… The rise of COVID-19 pandemic has had a lasting impact in many countries worldwide since 2019. Face-mask detection had been significant progress in the Image processing and deep learning fields studies. …”
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A Weakly Supervised Network for Coarse-to-Fine Change Detection in Hyperspectral Images by Yadong Zhao, Zhao Chen

“…In recent years, deep-learning based HSI-CD methods have made remarkable progress due to their powerful nonlinear feature learning capabilities, yet they face several challenges: mixed-pixel phenomenon affecting pixel-level detection accuracy; heterogeneous spatial scales of change targets where coarse-grained features fail to preserve fine-grained details; and dependence on high-quality labels. …”
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Audio Deepfake Detection: What Has Been Achieved and What Lies Ahead by Bowen Zhang, Hui Cui, Van Nguyen, Monica Whitty

“…It begins by exploring the foundational methods of audio deepfake generation, including text-to-speech (TTS) and voice conversion (VC), followed by a review of datasets driving progress in the field. The survey then delves into detection approaches, covering frontend feature extraction, backend classification models, and end-to-end systems. …”
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Deep learning and digital twin integration for structural damage detection in ancient pagodas by Sida Xu, Haonan Chen

“…Abstract In recent years, with the rise of digital twin technology in the field of artificial intelligence and the continuous advancement of hardware imaging equipment, significant progress has been made in the detection of structural damage in buildings and sculptures. …”
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A Narrative Review on Functionalized Nanoparticles for the Treatment and Early Detection of Hepatocellular Carcinoma by Meda Cosma, Teodora Mocan, Lavinia Ioana Sabau, Teodora Pop, Ofelia Mosteanu, Lucian Mocan

“…Due to their physicochemical properties, these nanoparticles can also carry contrast agents, enabling precise identification of tumor cells and contributing to the early diagnosis of hepatocellular carcinoma. (4) Conclusions: While significant progress has been made, challenges such as toxicity, cost, and regulatory hurdles remain.…”
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Determination of Optimal Dataset Characteristics for Improving YOLO Performance in Agricultural Object Detection by Jisu Song, Dongseok Kim, Eunji Jeong, Jaesung Park

“…Recent advances in artificial intelligence and computer vision have led to significant progress in the use of agricultural technologies for yield prediction, pest detection, and real-time monitoring of plant conditions. …”
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Deep Learning Techniques for Detecting Morphed Face Images: A Literature Review by Pedro Morais, Ines Domingues, Jorge Bernardino

“…Despite these challenges, deep learning techniques have made significant progress in improving Morph Attack Detection (MAD) systems. …”
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Normal-Only Anomaly Detection in Environmental Sensors in CPS: A Comprehensive Review by Yaa Takyiwaa Acquaah, Roy Kaushik

“…Anomaly detection is crucial for maintaining the reliability and security of environmental sensors in Cyber-Physical Systems (CPS). …”
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Biochemical and echocardiographic markers for the early detection of cardiotoxicity under monoclonal antibodies therapy by Ionela-Emilia Popovici, Angela Cozma, Olga Hilda Orasan, George Ciulei, Ana Maria Poenar, Cristina Buchman, Simina Tarmure, Sorina Secara, Adela Sitar-Taut, Teodora Alexescu, Andrada Lazar, Vasile Negrean, Lucia Maria Procopciuc

“…The progress made over the past years in the field of cancer therapy has led to a significant decrease in cancer mortality, but these therapies have many adverse effects, cardiovascular effects being among the most frequent ones. …”
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Rail squat detection using hybrid processing of axle box acceleration measurements by Reza Naseri, Brennan L. Gedney, Hossein Asgari, Dimitrios C. Rizos

“…Rail squat is the most common type of Rail Surface Spot Irregularity (RSSI) that comes into direct contact with the wheel surface and is distinguished for its relatively short length. As these defects progress within the rail, they compromise operational safety and accelerate wear on train and track components. …”
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Mechanisms for Securing Autonomous Shipping Services and Machine Learning Algorithms for Misbehaviour Detection by Marwan Haruna, Kaleb Gebremichael Gebremeskel, Martina Troscia, Alexandr Tardo, Paolo Pagano

“…Technological developments within the maritime sector are resulting in rapid progress that will see the commercial use of autonomous vessels, known as Maritime Autonomous Surface Ships (MASSs). …”
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Single-Molecule Detection of Optical Signals Using DNA-Based Plasmonic Nanostructures by Renjie Niu, Jintian Shao, Mingnan Wu, Chang Liu, Jie Chao

“…Single-molecule optical signal detection provides high sensitivity and specificity for the detection of biomolecules and chemical substances, which is of significant importance in fields such as biomedicine, environmental monitoring, and materials science. …”
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Toward In Vivo Cancer Detection: X-Ray Scattering on Thick Phantom Samples by Viacheslav Kubytskyi, Masroor Khonkhodzhaev, Aika Tanaka, Audrey Nguyen, Alexander Lazarev, Byron Aram, Keith Rogers, Lev Mourokh, Pavel Lazarev

“…However, these measurements were performed on small ex vivo samples, and to ensure the progress to in vivo diagnostics, the approach should be extended to larger tissues. …”
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Transportation Mode Detection Using Learning Methods and Self-Contained Sensors: Review by Ilhem Gharbi, Fadoua Taia-Alaoui, Hassen Fourati, Nicolas Vuillerme, Zebo Zhou

“…Reviewing the latest progress on TMD systems is important to inform readers about recent datasets used in detection, best practices for classification issues and the remaining challenges that still impact the detection performances. …”
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Recent Advances in Aggregation-Induced Emission (AIE) Fluorescent Sensors for Biomolecule Detection by Kavya S. Keremane, M. Gururaj Acharya, Praveen Naik, Chandi C. Malakar, Kai Wang, Bed Poudel

“…Notably, AIE-based fluorescent probes are emerging as attractive alternatives to traditional analytical methods owing to their low cost, fast detection, and high selectivity. Over the past two decades, considerable progress has been made in the rational design and development of AIE-active small-molecule fluorescent probes for detecting a wide variety of analytes, such as biologically relevant molecules, drug compounds, volatile organic compounds (VOCs), explosives, and contaminants associated with forensic and food safety analysis. …”
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Electricity theft detection in integrated energy systems considering multi-energy loads by Wenlong Liao, Dechang Yang, Leijiao Ge, Yixiong Jia, Zhe Yang

“…The significant progress has been made in electricity theft detection, but most classic works focus on electricity theft detection in residential environments, neglecting other locations such as hotels, industrial plants, and street lights. …”
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A comprehensive review on optical and electrochemical aptasensor for detection of fumonisin B1 by Jiayu Ma, Xiaodong Guo, Xiaodong Guo

“…Nucleic acid aptamers, generated via Systematic Evolution of Ligands by Exponential Enrichment (SELEX), have garnered significant attention as next-generation bioreceptors, demonstrating remarkable progress in food safety applications. Leveraging their high specificity and strong affinity for target molecules, aptamers have been successfully employed as alternatives to conventional methods for FB1 detection, leading to the development of diverse aptasensor platforms. …”
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An IoT Framework for the Detection of Lung Cancer Using a Decision Support System by Ahamd Habboush, Bassam Elzaghmouri, Binod Kumar Pattanayak, Pravat Kumar Rautaray

“… Cancer remains an ongoing global health challenge, necessitating the progress of innovative techniques for early detection and risk assessment. …”
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