In this paper, the authors introduce an innovative methodology for automating backend code optimization, triggered from the frontend of a web application and powered by advanced generative AI models. The proposed syst...
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ISBN:
(数字)9798331515799
ISBN:
(纸本)9798331515805
In this paper, the authors introduce an innovative methodology for automating backend code optimization, triggered from the frontend of a web application and powered by advanced generative AI models. The proposed system integrates the *** and Laravel frameworks, together with a PHP (Hypertext preprocessor) Parser and the OpenAI API (applicationprogramming interface), enabling dynamic, real-time optimization without necessitating system downtime. In contrast to conventional approaches that rely on offline environments or CI/CD (Continuous integration and continuous deployment) pipelines, this methodology facilitates continuous performance enhancement during active usage of web application. An experimental evaluation involving 20 functions within a Laravel application demonstrated a 70% optimization success rate, a 62.6% reduction in execution time and an 18.18% decrease in code lines. This approach preserves semantic consistency and provides reports to developers for further implementation. By reducing errors and enabling ongoing refinements, the work makes a significant contribution to the field of web application development.
In this paper, we present LYRICEL, an advanced AI-enhanced system that combines a rule-based decision-making mechanism, OpenAI's applicationprogramming interface (API), and additional external machine learning an...
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ISBN:
(数字)9798350368833
ISBN:
(纸本)9798350368840
In this paper, we present LYRICEL, an advanced AI-enhanced system that combines a rule-based decision-making mechanism, OpenAI's applicationprogramming interface (API), and additional external machine learning and analytical APIs to deliver song lyrics recommendations for an e-learning platform dedicated to Greek music and songs. This new component enhances MUSILYAN, a specialised software tool designed for musicological and lyrical analysis, by complementing it with GPT4o's capabilities. While ChatGPT excels in natural language understanding and generation, MUSILYAN provides structured semantic content management and thematic organization of lyrics. The integration of the two modules in LYRICEL, holds significant promise for enhancing the exploration and understanding of poetry and lyrics, offering a robust framework for enriching cultural heritage e-learning experiences.
E-Learning platforms became very common and popular nowadays. It also so frequent that some of the learners enrolled may not complete the course within the specified time. There comes a necessity to increase course co...
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ISBN:
(数字)9798331505790
ISBN:
(纸本)9798331505806
E-Learning platforms became very common and popular nowadays. It also so frequent that some of the learners enrolled may not complete the course within the specified time. There comes a necessity to increase course completion rate where the E-learning environment should be improved to boost the learning attitude of the learners by monitoring the learner’s attitude. The learners should be grouped based on similarity of their learning characteristics. A clustering and ranking system is created as a REST API (Representational State Transfer applicationprogramming Interface) service. This is integrated to an E-Learning solution. The service can take the preprocessed data of learner activity information as input and, next by using K-Prototypes clustering algorithm group or cluster all learners by their learning attitude based on the features, then give the category of learner attitude as response. Each data object is also ranked according to the closeness to the centroid within each cluster. The response generated by the service is taken by the E-Learning system, can now not only can identify the group of learners and but also each individual learner by their learning attitude thus involve in motivational activity. A scheduler is implemented to request the clustering and ranking API with data from E-Learning system at designated times. Using it the learner status at that instant can be obtained by the E-Learning system.
This paper presents an economical and reliable solution for LED control by utilizing the Bolt Wi-Fi module through a Bubble web app integrated with the Internet of Things (IoT), eliminating the need for programming sk...
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ISBN:
(数字)9798350381887
ISBN:
(纸本)9798350381894
This paper presents an economical and reliable solution for LED control by utilizing the Bolt Wi-Fi module through a Bubble web app integrated with the Internet of Things (IoT), eliminating the need for programming skills. Leveraging a User Interface (UI) builder, applicationprogramming Interface (API), and the Bolt Wi-Fi module ESP 8266MOD (ISM-2.4GHz, PA +25dBm, 802.11b/g/n) operating at 2.4 GHz frequency, LED control is achieved. The paper introduces a block control system for LED ON and LED OFF, allowing users to select appearance styles - a success button for LED ON and a danger button for LED OFF. Digital wire plugins are employed for both LED states, utilizing pin zero with a high status for LED ON and low for LED OFF.
Faced with the rapid development of social networks and the enormous business opportunities they contain, data mining and analysis based on social networks has become an inevitable trend. By utilizing various technolo...
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ISBN:
(数字)9798331528348
ISBN:
(纸本)9798331528355
Faced with the rapid development of social networks and the enormous business opportunities they contain, data mining and analysis based on social networks has become an inevitable trend. By utilizing various technologies such as Visual C++6.0 and Pajek, data collection and analysis were achieved. The user ID (Identification) was added to the Sina server and relevant user information was requested through the API (applicationprogramming Interface). Through the data analysis module, the stored data was processed appropriately for different research objects, and network analysis tools can be used to visually display certain results. Using this model, sentiment classification was performed on Weibo samples with existing labels, and the accuracy, recall and F1 value of manual labeling were evaluated. The positive accuracy was 0.85; recall was 0.82; F1 value was 0.84. This article helps to improve user experience and explore more user value.
Modeling and Simulation (M&S) plays a crucial role in the design and analysis of complex systems, with the Discrete EVent System specification (DEVS) formalism being a widely adopted mathematical framework. This p...
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ISBN:
(数字)9781713899310
ISBN:
(纸本)9798350350562
Modeling and Simulation (M&S) plays a crucial role in the design and analysis of complex systems, with the Discrete EVent System specification (DEVS) formalism being a widely adopted mathematical framework. This paper introduces xDEVS no_std, the first version of xDEVS written in the Rust programming language’s no_std environment. Rust’s features, including a data ownership mechanism, enable the development of high-performance, memory-safe simulations. xDEVS no_std focuses on Real-Time (RT) simulation for safety-critical embedded applications, leveraging Rust’s abstractions to simplify code sharing and cross-compilation. The paper outlines the implementation design and applicationprogramming Interface (API), which facilitates the creation of both atomic and coupled DEVS models. The RT simulator integrates with hardware, handling external interrupts and enabling interactions with the embedded system. A use case on a RISC-V microcontroller demonstrates xDEVS no_std’s capabilities, illustrating how it can effectively orchestrate tasks of Cyber-Physical System (CPS) on embedded platforms.
Personalized learning refers to a system of teaching and learning where the content, methods, and assessment are tailored to each learner's needs, capacities/skills/competencies, and pace. There is abundant litera...
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ISBN:
(数字)9798350376838
ISBN:
(纸本)9798350376845
Personalized learning refers to a system of teaching and learning where the content, methods, and assessment are tailored to each learner's needs, capacities/skills/competencies, and pace. There is abundant literature about personalized learning, describing its advantages, challenges, and approaches to implementing it. This study has explored the abundant literature and realized that while there are substantial proposed ways to achieve personalized learning, these proposals are not implemented into actionable products. This research aims to construct a Generative Artificial Intelligence (Gen AI) tutor that implements personalized learning and teaching in a higher education level course. The research methodology involved exploring literature to determine the requirements for personalized learning and designing a tutor system. The resultant system uses Custom GPT technology, applicationprogramming Interface (API), a repository for storing content, learners' profile information, and performance metrics. Out of the six components that make the proposed system, only the “Custom GPT” component has been implemented and tested on a course named “Applied Cryptography” in a postgraduate program. Though the preliminary results are promising, an effective assessment of the system will be made when the full implementation is completed. Further, issues related to ethics, scaling and integration with learning management systems should also be considered. Subsequent work to this study will focus on those issues.
Enterprise-level cloud databases pertinent to enterprises can be imported either through files or through an applicationprogramming Interface (API). Information that is stored in a document, before it can become an u...
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ISBN:
(数字)9798331505462
ISBN:
(纸本)9798331505479
Enterprise-level cloud databases pertinent to enterprises can be imported either through files or through an applicationprogramming Interface (API). Information that is stored in a document, before it can become an updated piece of data that is accessible in the database, must goes through a process. Some of the document processing covers actions such as, or are, business actions like; reading files, parsing input data, data validation, an API call, as well as the generation of a final report indicating records that have been imported from the document. Each time there is a new document to import; the previous procedures must be done all over again. To process the document various tools has to be used, for instance, AWS glue and Snaplogic are available in the market. These tools are predominantly used to integrate processes of data transfer between different applications and different data sources as well as to perform ETL or ELT depending on a specific scenario. Both the applications are nearly similar in having ETL and ELT facilities but the utilization of this type of application is different from one another depending on the client's requirement. This paper conducts the comparison between snaplogic and AWS glue based on all the relative characteristics such as the domain where it can be applied, flow, connector, difficulty level of using snaplogic and AWS glue and finally the major distinctions between the two platforms
N owadays, the emotion of every individual human is detected according to the user's facial expressions. The rapid growth of technologies in music information retrieval, personalized music recommendation systems r...
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ISBN:
(数字)9798331504960
ISBN:
(纸本)9798331504977
N owadays, the emotion of every individual human is detected according to the user's facial expressions. The rapid growth of technologies in music information retrieval, personalized music recommendation systems remain in the beginning stage only. However, the personalized music suggestions are common, but, recommending songs based on emotions remains a significant challenge. Hence, this research proposes a Deep Learning (DL) based Convolutional Recurrent Neural Network with Content-Based Filtering (CRNN-CBF) model to recommend personalized music based on emotion. At first, the data gathered from Facial Emotion Recognition 2013 (FER2013) dataset and the collected images are preprocessed by median filter, histogram equalization, and a wiener filter. Then, features are extracted by using Linear Binary Patterns (LBP) method and then classified using CRNN, categorizing images into seven distinct types of user emotions. Next, spotify applicationprogramming Interface (API) is employed to deliver playlists and finally, CBF is introduced to recommend personalized music according to user interests. From the results, the proposed CRNN-CBF model achieved outstanding results in accuracy 95.73%, precision 94.86%, and recall 96.78% when compared with existing model such as Emotion-Aware Music Recommendation System by using Deep Neural Network (EA-DNN).
APIs or application programming interfaces help distributed systems and microservices to expose their functionalities and serve as a means for communication among them. In contrast to a poorly designed API, a well-des...
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ISBN:
(数字)9798331504830
ISBN:
(纸本)9798331515621
APIs or application programming interfaces help distributed systems and microservices to expose their functionalities and serve as a means for communication among them. In contrast to a poorly designed API, a well-designed API is easy for users to understand and use. Thus, APIs with high-quality design are essential both for API providers and client developers. This paper aims to assess the linguistic design quality of APIs in distributed systems and microservices by automatically detecting good and poor design practices, commonly known as patterns and antipatterns, respectively. We rely on syntactic and semantic analyses for automatic assessment of the design quality of APIs using detection heuristics. Syntactic analysis involves analyzing the structure and syntax of the APIs, while semantic analysis involves analyzing API documentation, descriptions, and parameters. We achieved an overall accuracy of more than 93% in detecting patterns and antipatterns. Our detection results also suggest that antipatterns are prevalent in the APIs of distributed systems and microservices. Our findings will assist API developers in identifying poor design practices and improving the design quality of their APIs.
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