Tomato is one of the most popular crops worldwide. The success of a tomato crop is highly dependent on the health of the plants. Nutrient deficiency surveillance is typically conducted through visual inspections, whic...
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As industries continue to digitize at a rapid pace, the number of integrations, the connections between different digital systems, is increasing. As a consequence, integration management is becoming increasingly diffi...
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Image deblurring techniques that uses deep learning have shown great potential but due to low generalizability, noise immunity and the correlation among different pixels is not addressed in detail that results in unwa...
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Data has been quickly becoming as the fuel, the new oil, of growth and prosperity of companies in the modern age. With useful data and sufficient tools, companies have the ability to enhance their current products, pr...
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The development of the next generation of cellular networks, 5G-Advanced and 6G (5G-A/6G), offers higher speeds, sub-millisecond latency, and providing wider coverage, which are key to meeting the requirements of new ...
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Code reviews are an integral part of software development and have been recognized as a crucial practice for minimizing bugs and favouring higher code quality. They serve as an important checkpoint before committing c...
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ISBN:
(数字)9798331535100
ISBN:
(纸本)9798331535117
Code reviews are an integral part of software development and have been recognized as a crucial practice for minimizing bugs and favouring higher code quality. They serve as an important checkpoint before committing code and play an essential role in knowledge transfer between developers. However, code reviews can be time-consuming and can stale the development of large software projects. In a recent study, Guo et al. assessed how ChatGPT3.5 can help the code review process. They evaluated the effectiveness of ChatGPT in automating the code refinement tasks, where developers recommend small changes in the submitted code. While Guo et al.'s study showed promising results, proprietary models like ChatGPT pose risks to data privacy and incur extra costs for software projects. In this study, we explore alternatives to ChatGPT in code refinement tasks by including two open-source, smaller-scale large language models: CodeLlama and Llama 2 (7B parameters). Our results show that, if properly tuned, the Llama models, particularly CodeLlama, can achieve reasonable performance, often comparable to ChatGPT in auto-mated code refinement. However, not all code refinement tasks are equally successful: tasks that require changing existing code (e.g., refactoring) are more manageable for models to automate than tasks that demand new code. Our study highlights the potential of open-source models for code refinement, offering cost-effective, privacy-conscious solutions for real-world software development.
Rapid proliferation of aberrant neurons in brain tumors significantly damages organ function or causes death, endangering adult health. These tumors vary widely in terms of their locations, sizes, and textures. Findin...
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Service mobility in Multi-access Edge Computing (MEC) paradigm is necessary to provide ultra-Reliable Low Latency Communications for the erratically roaming MEC users. It involves relocation of containerized applicati...
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Early dementia detection is a crucial but challenging task in Bangladesh. Often, dementia is not recognized until it is too late to receive effective care. This results in part from a lack of knowledge about the illne...
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Collaboration between stakeholders is one of the current challenges facing cyberattacks in the avionics sector. Our goal is to propose ontologies as a viable solution to address this need among subsystems connecting h...
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ISBN:
(数字)9798350393095
ISBN:
(纸本)9798350393101
Collaboration between stakeholders is one of the current challenges facing cyberattacks in the avionics sector. Our goal is to propose ontologies as a viable solution to address this need among subsystems connecting heterogeneous providers, thereby contributing to the enhancement of system standardization and *** ARINC 429 bus standard raises concerns due to its lack of authentication, creating a plausible avenue for an adversary to engage in deceptive communication. We develop the ontology onto-by-429, created to provide avionics stakeholders with a comprehensive knowledge model of ARINC 429. It is combined with well-established ontologies such as NASA’s ATMONTO and MITRE D3FEND, bridging the domains of security, air traffic management (ATM), and ARINC 429. It results in a cross-disciplinary ontology known as *** the MITRE ATT&CK framework, we assess two distinct cyberattack scenarios, addressing concerns related to spoofing and denial-of-service (DoS) attacks. By giving a question to our Anomaly Explanation Engine (AEE) via a SPARQL request, its responses provide comprehensive anomaly explanations that facilitate error detection and establish a repository of traceable attack explanationOntology’s efficiency is evaluated using three simulated test cases: a rogue radiometer, a tampered Electronic Flight Bag (EFB), and a rogue autopilot. Our prototype is distinct from previous avionics attack taxonomies, establishes a knowledge base and employs the SAMOD agile methodology to build the *** logical rules pass consistency evaluations made by Pellet, a practical OWL-DL reasoner, during all three iteration processes. Three relevant competency questions, proposed by domain experts, are answered, providing anomaly elucidation to inform a pilot, a maintenance worker, or an Intrusion Detection Systems (IDS) developer of an attack, while offering cybersecurity countermeasure components and capabilities from MITRE D3FEND.
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