Increasingly, software needs to dynamically adapt its structure and behavior at runtime in response to changing conditions in the supporting computing, network infrastructure, and in the surrounding physical environme...
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ISBN:
(纸本)9780769543802
Increasingly, software needs to dynamically adapt its structure and behavior at runtime in response to changing conditions in the supporting computing, network infrastructure, and in the surrounding physical environments. By high complexity, adaptive programs are generally difficult to specify, verify, and validate. Assurance of high dependability of these programs is a great challenge. Efficiently and precisely specifying requirements and flexible model checking for adaptation are the key issues for developing dependably adaptive software. this paper introduces a formal model for adaptive programs which have different behavioral modes. We consider that adaptive programs have two behavioral level, functional behavior and adaptation. State machine is used to describe functional behavior in different modes and mode automata is proposed for adaptations. Specifications of adaptive programs are classified into three categories, local, adaptation and global properties from their different scope of dynamic adaptation. To specify and verify specifications on our model, We propose the Mode-extended Linear Temporal Logic (mLTL) and its model checking approach. mLTL extends Linear Temporal Logic (LTL) by adding mode related element and enables describing properties on different modes. Our formal model and mLTL formulae are translated to SMV language and verified in NuSMV model checker.
Image forgery is the alteration of a digital image to hide some of the important and useful information. Copy-move forgery (CMF) is one of the most difficult to detect because the copied part of the image has the same...
Image forgery is the alteration of a digital image to hide some of the important and useful information. Copy-move forgery (CMF) is one of the most difficult to detect because the copied part of the image has the same characteristics as the original image. Most of the existing datasets only highlight additional attacks in the copied part. Since there are no categories of duplication elements in the datasets, this research analyzed three categories of duplication elements in CMF which are animals, food and non-living things using DEFACTO and CoMo3Dataset. the analysis is performed on PatchMatch-based detection method and the results show that the method able to maintain at least 83% for all duplication elements in both DEFACTO and CoMo3Dataset. Furthermore, the method is able to detect a minimum 92% score for the food category in both datasets.
the software product line development goal is whole domain rather than a single software system, withthe results that effectively improved the software system development productivity and quality, shortened developme...
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E-wallet use has exploded, bringing in a new era of convenient and secure digital transactions;nevertheless, it has also led to a surge in fraudulent transactions. Using Recurrent Neural Networks (RNNs), this research...
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this paper describes testing framework that is capable of testing heterogeneous embedded systems. there are three key contributions. the first is the introduction of a new approach of embedded system testing. the seco...
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software requirements gathering from users, customers, and stakeholders is the very first and critical step in software development. Requirements are volatile due to change in needs, processes and technology. this mak...
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Intrusion Detection systems (IDS) play a crucial role in a comprehensive security framework for an organization by detection and response to security incidents, encompassing both network-based and host-based threats. ...
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Recently, recommendation models have gained popularity due to their effectiveness in improving customer satisfaction and deriving sales. However, current product recommendation models have a drawback: they lack person...
Recently, recommendation models have gained popularity due to their effectiveness in improving customer satisfaction and deriving sales. However, current product recommendation models have a drawback: they lack personalized and targeted advertisements for individual users. Consequently, the recommendations provided are random and not tailored to users' preferences. this limitation negatively impacts the system's ability to deliver relevant and personalized advertisements, leading to reduced user engagement and potentially lower conversion rates. Moreover, the absence of personalized advertisements can result in user dissatisfaction as they may receive recommendations that are irrelevant or not aligned withtheir interests and needs. To address these challenges, this study proposed a targeted product recommendation model using Deep Learning (DL) techniques in computer vision. the study utilizes the dataset of human images obtained from the Kaggle website, which includes details such as gender, class, and age. Findings of the study demonstrated a high level of accuracy in product recommendations, indicating the potential for significant improvements in addressing the issues. In conclusion, the proposed method achieves good accuracy in predicting the gender and age, and provides appropriate product recommendations based on these features.
A new type of exponential reaching law is proposed to address the problems of large overshoot and weak anti-interference ability of traditional exponential reaching law sliding mode control in permanent magnet synchro...
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the standard language is assessed, and the feelings transmitted by the individual are brought up. the purpose of sentiment analysis is to determine the polarity of a person's textual opinion. Most of the people us...
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