This research aims to propose a practical framework designed for the automatic analysis of a product’s comprehensive functionality and security vulnerabilities,generating applicable guidelines based on real-world ***...
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This research aims to propose a practical framework designed for the automatic analysis of a product’s comprehensive functionality and security vulnerabilities,generating applicable guidelines based on real-world *** existing analysis of software security vulnerabilities often focuses on specific features or *** partial and arbitrary analysis of the security vulnerabilities makes it challenging to comprehend the overall security vulnerabilities of the *** key novelty lies in overcoming the constraints of partial *** proposed framework utilizes data from various sources to create a comprehensive functionality profile,facilitating the derivation of real-world security *** guidelines are dynamically generated by associating functional security vulnerabilities with the latest Common Vulnerabilities and Exposure(CVE)and Common Vulnerability Scoring System(CVSS)scores,resulting in automated guidelines tailored to each *** guidelines are not only practical but also applicable in real-world software,allowing for prioritized security *** proposed framework is applied to virtual private network(VPN)software,wherein a validated Level 2 data flow diagram is generated using the Spoofing,Tampering,Repudiation,Information Disclosure,Denial of Service,and Elevation of privilege(STRIDE)technique with references to various papers and examples from related *** analysis resulted in the identification of a total of 121 *** successful implementation and validation demonstrate the framework’s efficacy in generating customized guidelines for entire systems,subsystems,and selected modules.
Herein, we propose high-performance Ti/STO/n+-Si and Ag/STO/n+-Si write-once-read-many-times devices, where the resistance transition mechanisms are controlled by oxygen vacancies in the STO layer and metal atoms from...
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Android applications are becoming increasingly powerful in recent years. While their functionality is still of paramount importance to users, the energy efficiency of these applications is also gaining more and more a...
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Android applications are becoming increasingly powerful in recent years. While their functionality is still of paramount importance to users, the energy efficiency of these applications is also gaining more and more attention. Researchers have discovered various types of energy defects in Android applications, which could quickly drain the battery power of mobile devices. Such defects not only cause inconvenience to users, but also frustrate Android developers as diagnosing the energy inefficiency of a software product is a non-trivial task. In this work, we perform a literature review to understand the state of the art of energy inefficiency diagnosis for Android applications. We identified 55 research papers published in recent years and classified existing studies from four different perspectives, including power estimation method, hardware component, types of energy defects, and program analysis approach. We also did a cross-perspective analysis to summarize and compare our studied techniques. We hope that our review can help structure and unify the literature and shed light on future research, as well as drawing developers' attention to build energy-efficient Android applications.
Parallel Disassembly Sequence Planning (DSP) deals with obtaining the order of disassembling the product with multiple parts disassembling simultaneously. Existing studies derive the product’s disassembly order based...
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In the majority of Western nations including America, Australia and Europe, skin cancer is badly-behaved. Skin concealing, inadequacy of Sun-lights, climate, age, and inherited are major risk factors. Early identifica...
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In the 21st century, we can shop anytime and anywhere without leaving our comfort zones but there is still a noteworthy difference between offline and online shopping resulting high return rates especially in the appa...
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The foundation of the applicant selection process is the candidate eligibility criteria. All applications must go through some evaluation process to get selected for a job. Without the use of a machine learning algori...
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The rapid expansion of Internet of Things (IoT) devices and applications necessitates the need for more efficient computational and data management strategies. The Fog-enabled UAV-as-a-Service (FU-Serve) platform addr...
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The demand for cloud computing has increased manifold in the recent *** specifically,on-demand computing has seen a rapid rise as organizations rely mostly on cloud service providers for their day-to-day computing ***...
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The demand for cloud computing has increased manifold in the recent *** specifically,on-demand computing has seen a rapid rise as organizations rely mostly on cloud service providers for their day-to-day computing *** cloud service provider fulfills different user requirements using virtualization-where a single physical machine can host multiple *** virtualmachine potentially represents a different user environment such as operating system,programming environment,and ***,these cloud services use a large amount of electrical energy and produce greenhouse *** reduce the electricity cost and greenhouse gases,energy efficient algorithms must be *** specific area where energy efficient algorithms are required is virtual machine *** virtualmachine consolidation,the objective is to utilize the minimumpossible number of hosts to accommodate the required virtual machines,keeping in mind the service level agreement *** research work formulates the virtual machine migration as an online problem and develops optimal offline and online algorithms for the single host virtual machine migration problem under a service level agreement constraint for an over-utilized *** online algorithm is analyzed using a competitive analysis *** addition,an experimental analysis of the proposed algorithm on real-world data is conducted to showcase the improved performance of the proposed algorithm against the benchmark *** proposed online algorithm consumed 25%less energy and performed 43%fewer migrations than the benchmark algorithms.
The rapidly advancing Convolutional Neural Networks(CNNs)have brought about a paradigm shift in various computer vision tasks,while also garnering increasing interest and application in sensor-based Human Activity Rec...
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The rapidly advancing Convolutional Neural Networks(CNNs)have brought about a paradigm shift in various computer vision tasks,while also garnering increasing interest and application in sensor-based Human Activity Recognition(HAR)***,the significant computational demands and memory requirements hinder the practical deployment of deep networks in resource-constrained *** paper introduces a novel network pruning method based on the energy spectral density of data in the frequency domain,which reduces the model’s depth and accelerates activity *** traditional pruning methods that focus on the spatial domain and the importance of filters,this method converts sensor data,such as HAR data,to the frequency domain for *** emphasizes the low-frequency components by calculating their energy spectral density ***,filters that meet the predefined thresholds are retained,and redundant filters are removed,leading to a significant reduction in model size without compromising performance or incurring additional computational ***,the proposed algorithm’s effectiveness is empirically validated on a standard five-layer CNNs backbone *** computational feasibility and data sensitivity of the proposed scheme are thoroughly ***,the classification accuracy on three benchmark HAR datasets UCI-HAR,WISDM,and PAMAP2 reaches 96.20%,98.40%,and 92.38%,***,our strategy achieves a reduction in Floating Point Operations(FLOPs)by 90.73%,93.70%,and 90.74%,respectively,along with a corresponding decrease in memory consumption by 90.53%,93.43%,and 90.05%.
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