In order to improve the processing quality of traditional Chinese medicine rhubarb and control the processing process of rhubarb in real time, a programmable logic control system with Ethernet and Internet of things r...
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Compilers play a very important role in the development of software. More and more researchers are studying how to improve the reliability of compilers. An effective method is to test the compiler with equivalent prog...
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This research aims to determine whether Wi- Fi sensing, through Channel State Information (CSI), can identify the operational states of an NC milling machine without the need for contact sensors. The purpose is to eva...
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The conference on Program Analysis and software Testing is a special session under the workshop category which will be held in conjunction with ISEC-2023, Indian Institute of Information Technology, Allahabad Prayagra...
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This study examines how the introductory engineering course can engage students in learning Industry 4.0 concepts and enhance their digital technology skills through simulation-based design activities. The students us...
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This study examines how the introductory engineering course can engage students in learning Industry 4.0 concepts and enhance their digital technology skills through simulation-based design activities. The students used cloud-based design and simulation tools to resolve a system operation problem. They examined the motion of a digital model of a satellite under micro -gravity conditions and detected its instability (Dzhanibekov effect). Then, they redesigned the model and verified its motion stability through simulation. The experimental setup combined the cloud-based CAD platform Onshape and the simulation software Blender. The students' performances, understanding, and perceptions were evaluated using conventional research tools and the data analytics tools of Onshape. Findings showed that the students successfully performed the workshop assignment, correctly answered the questions about the factors that cause motion instability and appreciated the contribution of the workshop. The study demonstrated the potential of online simulation-based design practices for educating novice engineering students.
Function Point Analysis (FPA) is a well-established and widely used measure of software functional size. For more than 20 years, there have been several attempts to calculate function points on the basis of the object...
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Integrating machine learning (ML) into the official statisticians' toolset is gaining popularity as National Statistical Offices (NSOs) strive to improve their methodologies. This trend poses new challenges and im...
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ISBN:
(纸本)9798350376975;9798350376968
Integrating machine learning (ML) into the official statisticians' toolset is gaining popularity as National Statistical Offices (NSOs) strive to improve their methodologies. This trend poses new challenges and implications for incorporating innovative techniques that ensure the reliability of the official statistical production process. A comprehensive literature review was conducted using Scopus and Web of science databases to explore the contemporary applications of data science in official statistics. A total of 178 research articles were identified, focusing on areas such as big data, machine learning, and data quality. While the literature review revealed extensive proposals on utilizing alternative data and applying machine learning techniques to support official statistics production, it also identified research gaps in the post-training steps of the machine learning process. Areas requiring further investigation include machine learning operations in a production environment, data quality assurance, and governance.
The secret level of secret documents should be correctly labeled, especially when they are printed or copied from the company's internal network to mobile media. At this point, it is necessary to perform a consist...
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Injection vulnerabilities are among the most serious and dangerous security defects, as they can be exploited by attackers to inject malicious inputs and carry out cybercrimes. Timely fixing of injection vulnerabiliti...
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ISBN:
(纸本)9798350395693;9798350395686
Injection vulnerabilities are among the most serious and dangerous security defects, as they can be exploited by attackers to inject malicious inputs and carry out cybercrimes. Timely fixing of injection vulnerabilities is crucial. However, manual repairs of injection vulnerabilities often require specialized knowledge and are prone to errors, posing a challenge and a heavy burden on developers. In recent years, Automated Program Repair (APR) techniques have shown promising momentum in automatically fixing general defects. Yet, there has been no research on how APR techniques perform in repairing injection vulnerabilities. Therefore, in this paper, we conduct an empirical study. We first construct a benchmark for injection vulnerability repair and evaluate several representative state-of-the-art APR approaches on this benchmark. The results show that existing APR tools do not adequately support the repair of injection vulnerabilities. To investigate the underlying reasons, we compare the characteristics of patches for injection vulnerabilities and general defects, and explore whether the plastic surgery hypothesis widely used in APR still holds for injection vulnerabilities. The results reveal that fixing injection vulnerabilities is more complex than fixing general defects due to significant differences in the characteristics of their patches. Additionally, the support for the plastic surgery hypothesis is much lower in the context of injection vulnerability repair. We also analyzed developers' intentions when fixing injection vulnerabilities. Finally, we summarize the implications and point out potential research directions for injection vulnerability repair.
Nowadays, privacy data has widely stored and shared through the cloud storage services from numerous users and organizations. However, exist-ing cloud services are concentrating on improving the data storage amount an...
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