The mobile cellular network provides internet connectivity for heterogeneous Internet of Things(IoT)*** cellular network consists of several towers installed at appropriate locations within a smart *** cellular towers...
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The mobile cellular network provides internet connectivity for heterogeneous Internet of Things(IoT)*** cellular network consists of several towers installed at appropriate locations within a smart *** cellular towers can be utilized for various tasks,such as e-healthcare systems,smart city surveillance,traffic monitoring,infrastructure surveillance,or sidewalk *** is a primary concern in data broadcasting,particularly authentication,because the strength of a cellular network’s signal is much higher frequency than the associated one,and their frequencies can sometimes be aligned,posing a significant *** a result,that requires attention,and without information authentication,such a barrier cannot be ***,we design a secure and efficient information authentication scheme for IoT-enabled devices tomitigate the flaws in the e-healthcare *** proposed protocol security shall check formally using the Real-or-Random(ROR)model,simulated using ProVerif2.03,and informally using pragmatic *** comparison,the performance phenomenon shall tackle by the already result available in the MIRACL cryptographic lab.
作者：
Petkar, Taniya
Faculty of Engineering and Technology Department of Computer Science And Medical Engineering Maharashtra Wardha442001 India
This paper presents a novel line-of-control (LoC) monitoring system that leverages the Internet of Things (IoT) to improve border security. The system creates a strong infrastructure for real-time monitoring throughou...
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Nowadays, high energy amount is being wasted by computing servers and personal electronic devices, which produce a high amount of carbon dioxide. Thus, it is required to decrease energy usage and pollution. Many appli...
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The cement-based materials have various void spaces, and water stays inside these spaces. If the structure of void spaces changes as curing progresses, the state of water inside void spaces also changes. Therefore, th...
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Convex clustering,turning clustering into a convex optimization problem,has drawn wide *** overcomes the shortcomings of traditional clustering methods such as K-means,Density-Based Spatial Clustring of Applications w...
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Convex clustering,turning clustering into a convex optimization problem,has drawn wide *** overcomes the shortcomings of traditional clustering methods such as K-means,Density-Based Spatial Clustring of Applications with Noise(DBSCAN)and hierarchical clustering that can easily fall into the local optimal ***,convex clustering is vulnerable to the occurrence of outlier features,as it uses the Frobenius norm to measure the distance between data points and their corresponding cluster centers and evaluate *** accurately identify outlier features,this paper decomposes data into a clustering structure component and a normalized component that captures outlier *** from existing convex clustering evaluating features with the exact measurement,the proposed model can overcome the vast difference in the magnitude of different features and the outlier features can be efficiently identified and *** solve the proposed model,we design an efficient algorithm and prove the global convergence of the *** on both synthetic datasets and UCI datasets demonstrate that the proposed method outperforms the compared approaches in convex clustering.
Solar flares are one of the strongest outbursts of solar activity,posing a serious threat to Earth’s critical infrastructure,such as communications,navigation,power,and ***,it is essential to accurately predict solar...
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Solar flares are one of the strongest outbursts of solar activity,posing a serious threat to Earth’s critical infrastructure,such as communications,navigation,power,and ***,it is essential to accurately predict solar flares in order to ensure the safety of human ***,the research focuses on two directions:first,identifying predictors with more physical information and higher prediction accuracy,and second,building flare prediction models that can effectively handle complex observational *** terms of flare observability and predictability,this paper analyses multiple dimensions of solar flare observability and evaluates the potential of observational parameters in *** flare prediction models,the paper focuses on data-driven models and physical models,with an emphasis on the advantages of deep learning techniques in dealing with complex and high-dimensional *** reviewing existing traditional machine learning,deep learning,and fusion methods,the key roles of these techniques in improving prediction accuracy and efficiency are *** prevailing challenges,this study discusses the main challenges currently faced in solar flare prediction,such as the complexity of flare samples,the multimodality of observational data,and the interpretability of *** conclusion summarizes these findings and proposes future research directions and potential technology advancement.
Border Gateway Protocol(BGP)is a standard inter-domain routing protocol for the Internet that conveys network layer reachability information and establishes routes to different *** BGP protocol exhibits security desig...
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Border Gateway Protocol(BGP)is a standard inter-domain routing protocol for the Internet that conveys network layer reachability information and establishes routes to different *** BGP protocol exhibits security design defects,such as an unconditional trust mechanism and the default acceptance of BGP route announcements from peers by BGP neighboring nodes,easily triggering prefix hijacking,path forgery,route leakage,and other BGP security ***,the traditional BGP security mechanism,relying on a public key infrastructure,faces issues like a single point of failure and a single point of *** decentralization,anti-tampering,and traceability advantages of blockchain offer new solution ideas for constructing secure and trusted inter-domain routing *** this paper,we summarize the characteristics of BGP protocol in detail,sort out the BGP security threats and their ***,we analyze the shortcomings of the traditional BGP security mechanism and comprehensively evaluate existing blockchain-based solutions to address the above problems and validate the reliability and effectiveness of blockchain-based BGP security methods in mitigating BGP security ***,we discuss the challenges posed by BGP security problems and outline prospects for future research.
作者：
Jiet, Moses MakueiKamble, AahashPuri, ChetanYesankar, PrajyotVerma, PrateekRewatkar, Rajendra
Faculty of Engineering and Technology Department of Computer Science & Design Maharashtra Wardha442001 India
Faculty of Engineering and Technology Department of Artificial Intelligence & Data Science Maharashtra Wardha442001 India
Faculty of Engineering and Technology Department of Artificial Intelligence & Machine Learning Maharashtra Wardha442001 India
Faculty of Engineering and Technology Department of Biomedical Engineering Maharashtra Wardha442001 India
This research focuses on the crucial role of the clustering technique in data mining, specifically in market forecasting and planning. The study presents a comprehensive report on utilizing the k-means clustering tech...
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Brain tumor is a global issue due to which several people suffer,and its early diagnosis can help in the treatment in a more efficient *** different types of brain tumors,including gliomas,meningiomas,pituitary tumors...
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Brain tumor is a global issue due to which several people suffer,and its early diagnosis can help in the treatment in a more efficient *** different types of brain tumors,including gliomas,meningiomas,pituitary tumors,as well as confirming the absence of tumors,poses a significant challenge using MRI *** approaches predominantly rely on traditional machine learning and basic deep learning methods for image *** methods often rely on manual feature extraction and basic convolutional neural networks(CNNs).The limitations include inadequate accuracy,poor generalization of new data,and limited ability to manage the high variability in MRI *** the EfficientNetB3 architecture,this study presents a groundbreaking approach in the computational engineering domain,enhancing MRI-based brain tumor *** approach highlights a major advancement in employing sophisticated machine learning techniques within computerscience and engineering,showcasing a highly accurate framework with significant potential for healthcare *** model achieves an outstanding 99%accuracy,exhibiting balanced precision,recall,and F1-scores across all tumor types,as detailed in the classification *** successful implementation demonstrates the model’s potential as an essential tool for diagnosing and classifying brain tumors,marking a notable improvement over current *** integration of such advanced computational techniques in medical diagnostics can significantly enhance accuracy and efficiency,paving the way for wider *** research highlights the revolutionary impact of deep learning technologies in improving diagnostic processes and patient outcomes in neuro-oncology.
In standard iris recognition systems,a cooperative imaging framework is employed that includes a light source with a near-infrared wavelength to reveal iris texture,look-and-stare constraints,and a close distance requ...
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In standard iris recognition systems,a cooperative imaging framework is employed that includes a light source with a near-infrared wavelength to reveal iris texture,look-and-stare constraints,and a close distance requirement to the capture *** these conditions are relaxed,the system’s performance significantly deteriorates due to segmentation and feature extraction ***,a novel segmentation algorithm is proposed to correctly detect the pupil and limbus boundaries of iris images captured in unconstrained ***,the algorithm scans the whole iris image in the Hue Saturation Value(HSV)color space for local maxima to detect the sclera *** image quality is then assessed by computing global features in red,green and blue(RGB)space,as noisy images have heterogeneous *** iris images are accordingly classified into seven categories based on their global RGB *** the classification process,the images are filtered,and adaptive thresholding is applied to enhance the global contrast and detect the outer iris ***,to characterize the pupil area,the algorithm scans the cropped outer ring region for local minima values to identify the darkest area in the iris *** experimental results show that our method outperforms existing segmentation techniques using the UBIRIS.v1 and v2 databases and achieved a segmentation accuracy of 99.32 on UBIRIS.v1 and an error rate of 1.59 on UBIRIS.v2.
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