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Mutation testing is a practical approach for evaluating the quality of deep learning (DL) testing datasets. However, the enormous mutants during testing lead to significant testing overhead. Feature clustering is a conventional method that ...

• A method for reducing the quantity of mutants in deep learning.
• Aiming to ensure testing effectiveness and improve mutation testing efficiency.
• Conjunction with deep learning interpretability to analyze the features of the mutant.

Recently, tensor-based multi-view subspace clustering methods have shown promising results. Despite the impressive clustering performance, most clustering methods still face the following challenges: 1) the expensive computational burden caused by complex ...

The detection of latent tuberculosis infection (LTBI) is one of the vital means in controlling the spread of TB. The dynamical properties of a mathematical model with LTBI detectivity and exogenous reinfection are analyzed and their impacts on TB ...

With the widespread application of deep learning in software engineering, deep code models have played an important role in improving code quality and development efficiency, promoting the intelligence and industrialization of software ...

Deep neural networks (DNN) have been widely deployed in safety-critical domains, such as autonomous cars and healthcare, where error behaviors can lead to serious accidents, testing DNN is extremely important. Neuron coverage-guided fuzz ...

With the COVID-19 outbreak, health-related rumors have attracted significant attention from governments and global society. These rumors often mislead the public through multimedia, amplifying their negative impact and potentially manipulating ...

This paper studies a manufacturer’s selling channel structure choice in a supply chain wherein the firms may concern about consumer surplus. In addition, the retailer can make the demand-enhancement investment, the effect of which may spill over ...

• Manufacturer channel choice with dual-purpose firms and demand investment is studied.
• Mode R may arise as the equilibrium for dual-purpose firms under certain conditions.
• The manufacturer may abandon mode M when the retailer cares ...

Open-source software (OSS) greatly facilitates program development for developers. However, the high number of vulnerabilities in open-source software is a major concern, including in Golang, a relatively new programming language. In contrast to other ...

Backdoor attacks on deep neural networks (DNNs) using targeted universal adversarial perturbations (TUAPs) do not require training datasets and model tampering, and triggers based on TUAPs can make DNNs output any class the adversary wants. ...

• Backdoor attacks on DNN using targeted universal adversarial perturbations are stealthy.
• Sequential analysis and metamorphosis testing for backdoor detection.
• The backdoor detection success rate is up to 86.3%.
• More ...

Recent advances in artificial intelligence technology and perception components have promoted the rapid development of autonomous vehicles. However, as safety‐critical software, autonomous driving systems often make wrong judgments, seriously ...

We introduce MetaLiDAR, to alleviate the test oracle and test case generation problems of LiDAR‐based autonomous driving systems. MetaLiDAR utilizes carefully designed metamorphic relations and object‐level operation methods to automatically generate ...

Farmers are beginning to promote their agricultural products through e-commerce platform marketplaces beyond conventional retail modes. Platform financing based on this new retail model has gained popularity in e-commerce agricultural supply ...

• The effect of platform’s dual roles on supply chain’s operations management.
• The farmer’s financing preferences are deduced under the for-profit and socially responsible scenarios.
• The influence of social responsibility concern on ...

Intelligent condition identification is the development trend of transformer condition recognition, However, the existing intelligent condition recognition has the disadvantage of single model and low recognition accuracy. In order to overcome ...

Android API-related compatibility issues have become a severe problem and significant challenge for app developers due to the well-known Android fragmentation issues. To address this problem, many effective approaches such as app-based and API lifetime-...

This study examines firms’ product quality information disclosure incentives in a supply chain wherein an upstream manufacturer sells a national brand via a downstream retailer who also sells its own store brand. Two disclosure formats,...

• Both M-C disclosure and R-C disclosure formats are examined in a supply chain.
• ...

Online education brings more possibilities for personalized learning, in which identifying the cognitive state of learners is conducive to better providing learning services. Cognitive diagnosis is an effective measurement to assess the cognitive ...

Software defect prediction (SDP) is an important technology which is widely applied to improve software quality and reduce development costs. It is difficult to train the SDP model when software to be test only has limited historical data. Cross-project ...

According to the needs generated by the industry, there is an urgent need to investigate the flow vibration response law of the elastic tube bundle of heat exchangers subjected to the coupling effect of shell and tube domain at different inlet flow ...

This article aims at the discussion on the filling pressure on Natural Gas Permeability of CNG Type IV Gas Cylinder. During the test, the concentration of natural gas increases along with the time extension under whatever pressure. With the increase of ...

• We study the information sharing in an endogenous channel structure with spillovers.

This paper studies information sharing under an endogenous distribution channel structure, where the retailer has superior demand information over the manufacturer, who can conduct demand-enhancement investment that will spill over to ...