The authors believe that for society to continue improving, it needs to have a better waste classification system. This paper presents a computer vision model trained with a novel dataset comprising images of waste co...
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Underwater optical signal detection performance suffers from occlusion and turbidity in degraded environments. Due to complex underwater environment the high directionality of light beam and vibration transceiver inci...
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Requirements engineering (RE) is an essential part of softwareengineering (SE). As RE activities rely heavily on people, the success of RE is influenced by the human aspects of the team involved. In this research, we...
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ISBN:
(纸本)9798350326970
Requirements engineering (RE) is an essential part of softwareengineering (SE). As RE activities rely heavily on people, the success of RE is influenced by the human aspects of the team involved. In this research, we develop a prototype application, called Motive Metrics, to improve RE activities by allowing managers to track developers' personality and motivation and monitor their impact on developer performance and satisfaction. The tool takes the form of an extension to Jira and was developed through rapid prototyping. The effectiveness and usability of the tool were evaluated by student teams split into managers and team members. When evaluating Motive Metrics, 45.5% of participants rated 4 out of 5 for the application's effectiveness in capturing personalities, but only 9.1% of participants rated 4 out of 5 for capturing motivations. Motive Metrics is likely ineffective in monitoring satisfaction and performance, as 45% of participants rated 1 out of 5 in comfort in sharing their responses. Our evaluation results also show that Motive Metrics might not be beneficial in tracking the influence of motivation on the outcome but slightly more beneficial in tracking the influence of personality on RE task performance.
The proceedings contain 71 papers. The topics discussed include: performance optimization method for distributed storage system based on hybrid storage device;controllable text-to-image generation with enhanced text e...
The proceedings contain 71 papers. The topics discussed include: performance optimization method for distributed storage system based on hybrid storage device;controllable text-to-image generation with enhanced text encoder and edge-preserving embedding;research on database programming technology in computersoftwareengineering;a privacy-preserving scheme for JPEG image retrieval based on deep learning;web page design of automobile energy saving and emission reduction system based on neural network;DRTaint: a dynamic taint analysis framework supporting correlation analysis between data regions;research and design of distributed key-value storage system based on raft consensus algorithm;and research on key technologies of intelligent operation and maintenance of communication network.
Mobile applications are becoming increasingly used to achieve various computing needs. Hence, it is essential to guarantee quality of the applications. software testing has been the main activity for ensuring the qual...
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With the rapid advancement of artificial intelligence (AI) in various domains, the education sector is set for transformation. The potential of AI-driven tools in enhancing the learning experience, especially in progr...
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ISBN:
(纸本)9798400704987
With the rapid advancement of artificial intelligence (AI) in various domains, the education sector is set for transformation. The potential of AI-driven tools in enhancing the learning experience, especially in programming, is immense. However, the scientific evaluation of Large Language Models (LLMs) used in Automated Programming Assessment Systems (APASs) as an AI-Tutor remains largely unexplored. Therefore, there is a need to understand how students interact with such AI-Tutors and to analyze their experiences. In this paper, we conducted an exploratory case study by integrating the GPT-3.5-Turbo model as an AI-Tutor within the ALAS Artemis. Through a combination of empirical data collection and an exploratory survey, we identified different user types based on their interaction patterns with the AI-Tutor. Additionally, the findings highlight advantages, such as timely feedback and scalability. However, challenges like generic responses and students' concerns about a learning progress inhibition when using the AI-Tutor were also evident. This research adds to the discourse on AI's role in education.
Automatic production is closely linked with industrial robots. However, the precision of robot positioning significantly impacts the stability of the automation system. To address this issue, we establish an industria...
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Over the academic year 2022-23, we discussed the teaching of software performance engineering with more than a dozen faculty across North America and beyond. Our outreach was centered on research-focused faculty with ...
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ISBN:
(纸本)9798350364613;9798350364606
Over the academic year 2022-23, we discussed the teaching of software performance engineering with more than a dozen faculty across North America and beyond. Our outreach was centered on research-focused faculty with an existing interest in this course material. These discussions revealed an enthusiasm for making software pertimmance engineering a more prominent part of a curriculum for computer scientists and engineers. Here, we discuss how MIT's longstanding efforts in this area may serve as a launching point for community development of a software performance engineering curriculum, challenges in and solutions for providing the necessary infrastructure to universities, and future directions.
In this experience paper, we design, implement, and evaluate a new static type-error detection tool for Python. To build a practical tool, we first collected and analyzed 68 real-world type errors gathered from 20 ope...
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ISBN:
(数字)9798400712487
ISBN:
(纸本)9798400712487
In this experience paper, we design, implement, and evaluate a new static type-error detection tool for Python. To build a practical tool, we first collected and analyzed 68 real-world type errors gathered from 20 open-source projects. This empirical investigation revealed four key static-analysis features that are crucial for the effective detection of Python type errors in practice. Utilizing these insights, we present a tool called Pyinder, which can successfully detect 34 out of the 68 bugs, compared to existing type analysis tools that collectively detect only 16 bugs. We also discuss the remaining 34 bugs that Pyinder failed to detect, offering insights into future directions for Python type analysis tools. Lastly, we show that Pyinder can uncover previously unknown bugs in recent Python projects.
The role of medical image detection and segmentation in medical treatment is increasingly prominent. It provides users with timely and accurate diagnostic and therapeutic information, thereby improving the efficiency ...
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