Detecting behavioral changes associated with suicidal ideation on social media is essential yet complex. While machine learning and deep learning hold promise in this regard, current studies often lack generalizabilit...
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Recent Research in creating intelligent smart Closed Circuit Television (CCTV) surveillance systems that can counteract the rising levels of insecurity has increased dramatically as a result of the growing demand for ...
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ISBN:
(纸本)9798350384369
Recent Research in creating intelligent smart Closed Circuit Television (CCTV) surveillance systems that can counteract the rising levels of insecurity has increased dramatically as a result of the growing demand for video surveillance systems. However, the storage and processing capacity of analytical applications has been exceeded by the enormous volume of video data produced by these devices. By localizing data to the network's edges, this article suggests a smart surveillance system that exhibits high performance in terms of response time and bandwidth. In modern IoT era, the need for transforming the traditional system into smart surveillance system is high due to its demand for instant detection of anomalous occurrences by processing huge amount of video data on the go. Bringing the smartness into the system, makes it more automated and reliable. The challenging phases in making the system smart is storing and analyzing the video surveillance data since it calls for event recognition, visual interpretation, and the identification of relevant context. We employ sliding technique and adaptive contour based algorithms for detailed preprocessing layer that performs key frame extraction and background elimination respectively. And to address the issue of storage and instant processing, we also propose fog based smart surveillance framework that acts as the intermediator component between cloud and end users. The next major challenge is analyzing the incoming video data on the go. It can be addressed through semantic based algorithm for detecting the abnormal events. We propose an ontology based algorithm for detecting the unusual occurrences. Experiments are conducted on a real-time dataset to evaluate the suggested technique. The computed results demonstrate the superiority of the suggested fog based semantic analytics monitoring system over the traditional cloud-based monitoring solutions by attaining high prediction and accuracy rate coupled with low latency in
The increasing emergence of IoT in healthcare, industrial automation, manufacturing, infrastructure, business and the home undoubtedly provides more conveniences in different aspects of human life. Any IoT security an...
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Deep learning offers a promising methodology for the registration of prostate cancer images from histopathology to MRI. We explored how to effectively leverage key information from images to achieve improved end-to-en...
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Precision medicine is based on curing diseases based on a patient's genetic profile, lifestyle, and environmental factors. This method improves clinical trial success rates and speed up drug regulatory approval. P...
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The internet has become a part of every human ***,various devices that are connected through the internet are ***,the Industrial Internet of things(IIoT)is an evolutionary technology interconnecting various industries...
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The internet has become a part of every human ***,various devices that are connected through the internet are ***,the Industrial Internet of things(IIoT)is an evolutionary technology interconnecting various industries in digital platforms to facilitate their ***,IIoT is being used in various industrial fields such as logistics,manufacturing,metals and mining,gas and oil,transportation,aviation,and energy *** is mandatory that various industrial fields require highly reliable security and preventive measures against *** detection is defined as the detection in the network of security threats targeting privacy information and sensitive *** Detection Systems(IDS)have taken an important role in providing security in the field of computer *** of intrusion is completely based on the detection functions of the *** an IIoT network expands,it generates a huge volume of data that needs an IDS to detect intrusions and prevent network *** research works have been done for preventing network *** day,the challenges and risks associated with intrusion prevention are increasing while their solutions are not properly *** this regard,this paper proposes a training process and a wrapper-based feature selection With Direct Linear Discriminant Analysis LDA(WDLDA).The implemented WDLDA results in a rate of detection accuracy(DRA)of 97%and a false positive rate(FPR)of 11%using the Network Security Laboratory-Knowledge Discovery in Databases(NSL-KDD)dataset.
Hyper-relational facts, which consist of a primary triple (head entity, relation, tail entity) and auxiliary attribute-value pairs, are widely present in real-world Knowledge Graphs (KGs). Link Prediction on Hyper-rel...
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Payment channels support off-chain transactions by enhancing transaction speed and reducing fees in the main blockchain. However, the costs and complexity of the network increase as we increase the size of the network...
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As one of the most effective techniques for finding software vulnerabilities,fuzzing has become a hot topic in software *** feeds potentially syntactically or semantically malformed test data to a target program to mi...
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As one of the most effective techniques for finding software vulnerabilities,fuzzing has become a hot topic in software *** feeds potentially syntactically or semantically malformed test data to a target program to mine vulnerabilities and crash the *** recent years,considerable efforts have been dedicated by researchers and practitioners towards improving fuzzing,so there aremore and more methods and forms,whichmake it difficult to have a comprehensive understanding of the *** paper conducts a thorough survey of fuzzing,focusing on its general process,classification,common application scenarios,and some state-of-the-art techniques that have been introduced to improve its ***,this paper puts forward key research challenges and proposes possible future research directions that may provide new insights for researchers.
The ability to reflect on and correct failures is crucial for robotic systems to interact stably with real-life objects. Observing the generalization and reasoning capabilities of Multimodal Large Language Models (MLL...
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