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检索条件"主题词=Application Programming Interfaces"

共 563 条记录，以下是21-30 订阅

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A Microservices Architecture Toolkit for Interconnected Science Ecosystems 24

A Microservices Architecture Toolkit for Interconnected Scie...

引用

Proceedings of the SC '24 Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis

作者： Michael J. Brim Lance Drane Marshall McDonnell Christian Engelmann Addi Malviya Thakur National Center for Computational Sciences Computer Science and Mathematics Division Oak Ridge National Laboratory Oak Ridge Tennessee U.S.A.

ISBN: (纸本)9798350355543

Microservices architecture is a promising approach for developing reusable scientific workflow capabilities for integrating diverse resources, such as experimental and observational instruments and advanced computational and data management systems, across many distributed organizations and facilities. In this paper, we describe how the INTERSECT Open Architecture leverages federated systems of microservices to construct interconnected science ecosystems, review how the INTERSECT software development kit eases microservice capability development, and demonstrate the use of such capabilities for deploying an example multi-facility INTERSECT ecosystem.

关键词： application programming interfaces

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Design and Implementation of a Smart Speech Interface using OCR and TTS APIs on ESP32-CAM

Design and Implementation of a Smart Speech Interface using ...

引用

Trends in Material Science and Inventive Materials (ICTMIM), International Conference on

作者： Imran Hussain S Mehul M S Mohana Sankaran S Department of Electronics and Communication Engineering Saveetha Engineering College Chennai India

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

Traditional TTS (TTS) systems are large, expensive, and inefficient, making them unsuitable for use by those competing in the eyeball challenge. These have limited portability and rely heavily on hardware for Optical Character Recognition (OCR) and TTS. The article describes a low-cost, lightweight solution based on the ESP32-CAM module, OCR, VoiceRSS, TTS, and application programming interfaces (API). An amplifier module uses OCR to turn the text acquired from images into high-quality speech. The benefits include portability, real-time computing, and decreased power usage. The test results were outstanding, with 98% precision for high-contrast text, 92% for low-contrast text, and 89% for small print. Furthermore, it achieved high voice intelligibility (9/10) and low average power consumption (0.72W). These results support the proposed system's potential as an effective and appropriate solution for assistive reading devices in a variety of settings.

关键词： Performance evaluation Power demand Text recognition Optical character recognition Lighting Text detection Speech recognition Robustness Text to speech application programming interfaces

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Generative Adversarial Network Based Real-Time Malware Detection in Cloud Environments

Generative Adversarial Network Based Real-Time Malware Detec...

引用

Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Srinivasa Rao Bittla Abothar Mahmood D. Kokila Ayesha Siddiqua Ajitha P R Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Al Diwaniyah Iraq Department of Artificial Intelligence & Data Science Excel Engineering College Namakkal India Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bengaluru India Department of Artificial Intelligence and Data Science Dhanalakshmi Srinivasan College of Engineering Technology Mamallapuram India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Recently, the rapid growth of cloud computing has created a vast attack surface for malware threats. The existing Support Vector Machine (SVM) accurately detected malwares although the dynamic nature of cloud environments led to high-dimensional data and class imbalance issues. Hence, this research proposes a Generative Adversarial Network (GAN) to address the class imbalance by creating synthetic malware samples. Initially, the input data is collected and fed into the analysis phase with Cuckoo Sandbox to generate malware behavior report in JavaScript Objective Notation (JSON) format. After that, Trend Micro Locality Sensitive Hashing (TLSH) is employed to measure the similarity among files and then the clustering phase groups the similar files as a cluster according to hash values. Further, the features are extracted from JSON format which contains information on application programming Interface (API) calls and their return codes. Then, the optimal features are selected using Chi-square to calculate the statistical independence on each feature and finally, GAN model is used to detect malware in cloud environments. From the results, the proposed GAN achieved better results in terms of accuracy (99.61%) when compared to existing Artificial Neural Network (ANN).

关键词： Support vector machines Cloud computing Codes Computer viruses Artificial neural networks Generative adversarial networks Feature extraction Malware Real-time systems application programming interfaces

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Mining Security Documentation Practices in OpenAPI Descriptions

Mining Security Documentation Practices in OpenAPI Descripti...

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Working IEEE/IFIP Conference on Software Architecture

作者： Diana Carolina Muñoz Hurtado Souhaila Serbout Cesare Pautasso Software Institute USI Lugano Switzerland

ISBN: (数字)9798331520908

ISBN: (纸本)9798331520915

Security is an integral requirement of any trustworthy software architecture, particularly critical for application programming interfaces (APIs). In this paper, we survey security documentation practices, specifically API security schemes related to authentication and authorization, by mining a large collection of OpenAPI descriptions retrieved from open-source GitHub repositories. Our study focuses on detecting existing security schemes and evaluating their prevalence and positioning within API descriptions. We distinguish whether security schemes are introduced locally (at the path or operation level) or globally (for the entire API). Our analysis highlights scenarios where security schemes are featured in APIs in different proportions over time, thus tracking whether the API documentation tends to include more (or less) security details as the API evolves.

关键词： Surveys Authorization Software architecture Authentication Documentation Security Data mining application programming interfaces Software development management

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In-Vehicle Artificial Intelligence Agent System with Local Large Language Models for Agent Selection and Vehicle Control

In-Vehicle Artificial Intelligence Agent System with Local L...

引用

International Conference on Computing, Networking and Communications (ICNC)

作者： Toru Furusawa Toyota Motor Corporation Tokyo Japan

ISBN: (数字)9798331520960

ISBN: (纸本)9798331520977

Voice User interfaces (VUIs) in vehicles enhance driver experience by enabling hands-free interaction with in-vehicle systems. However, the increasing complexity of these systems poses challenges for intuitive use, as drivers must remember numerous voice commands. Recent advancements in large language models (LLMs) offer opportunities to create more natural and flexible voice interactions. In this paper, we propose an in-vehicle Artificial Intelligence (AI) agent system that utilizes a local LLM for agent selection and vehicle control, eliminating the need for manual agent selection and dependency on internet connectivity for vehicle application programming Interface (API) execution. The system analyzes user speech content to automatically select appropriate AI agents and executes in-vehicle APIs using a local LLM capable of function calling. We implemented the system on an NVIDIA Jetson AGX Orin Developer Kit to simulate in-vehicle devices and evaluated its performance in terms of response time, accuracy of in-vehicle control API execution, and function calling success rate. Experimental results demonstrate that the proposed system achieves in-vehicle API execution with acceptable latency, improving usability and safety by enabling seamless and natural voice interactions without relying on internet connectivity.

关键词： Performance evaluation Large language models Manuals User interfaces Safety Time factors Usability application programming interfaces Vehicles Edge computing

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API-GEN: Accelerator Tool for Generation of REST APIs

API-GEN: Accelerator Tool for Generation of REST APIs

引用

IT Innovation and Knowledge Discovery (ITIKD), International Conference on

作者： Senthil Kumar T Jayapradha J Mardeni Bin Roslee Hajna Shaik Sanskriti Garg Chilakala Sudhamani Department of Computing Technologies SRM Institute of Science and Technology Kattankulathur India Faculty of Engineering Multimedia University Cyberjaya Malaysia

ISBN: (数字)9798350355468

ISBN: (纸本)9798350355475

application programming interfaces (APIs) are crucial for enabling seamless communication between software systems, allowing them to exchange data and perform tasks efficiently. They underpin essential operations across industries like e-Commerce, social media, and financial services. However, the traditional approach to API development is often labor-intensive, time-consuming, and prone to errors, diverting developers’ focus from innovation to repetitive coding tasks. This paper explores the concept and functionality of APIs, with a focus on automated API generation using JSON and class-based models. By automating this process, developers can streamline access to data from databases, significantly reducing manual effort while improving efficiency and accuracy. The study compares existing methods of API development with automated approaches, highlighting how automation can save time, minimize costs, and enhance the overall software development lifecycle. With its ability to simplify data integration and accelerate development, automated API generation represents a transformative solution for addressing the challenges of modern software systems, making the process faster, error-free, and more efficient.

关键词： Technological innovation Automation Databases Data integration Manuals Software systems Encoding application programming interfaces Software development management Python

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PowerShell Proxy-Aware Intercommunication and Manipulation

PowerShell Proxy-Aware Intercommunication and Manipulation

引用

International Symposium on Digital Forensic and Security (ISDFS)

作者： Jean Rosemond Dora Ladislav Hluchy dept. Institute of Informatics (UISAV) Slovak Academy of Sciences Bratislava Slovakia

ISBN: (数字)9798331509934

ISBN: (纸本)9798331509941

With the exponential expansion of attacks, organizations and enterprises nowadays, force their network communication through a proxy. This measure can assist security analysts to better control their environment, and monitor traffic. Likewise, attackers are interested in the manipulation techniques of the proxy concept, since they are aware of this protection. On the other hand, penetration testers (also known as, ethical attackers, or hackers) must ensure that their techniques (while generating payloads) can work through proxy to understand better steps that need to be mitigated. Additionally, they can always attempt to manipulate the proxy if possible [1], [2], along with any of its implemented monitors for this purpose. Usually, the PowerShell download cradles may not always be proxy-aware. However, the Meterpreter HTTP and HTTPS are [3]. A Meterpreter is a Metasploit attack payload that provides an interactive shell from which an attacker can proceed with his exploration of the target machine and run codes. Our focus will be based on strategies to talk to a proxy, i.e., we will need to use some modules which by default, are proxy-aware in the creation of our payloads [4]. We may still face some issues with some classes that are proxy-aware, since they may be reverted in future versions of Windows.

关键词： Visual BASIC Operating systems Organizations HTTP Security Protection Monitoring Standards Payloads application programming interfaces

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AutoGuard: Reporting Breaking Changes of REST APIs from Java Spring Boot Source Code

AutoGuard: Reporting Breaking Changes of REST APIs from Java...

引用

IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)

作者： Alexander Lercher Clemens Bauer Christian Macho Martin Pinzger Department of Informatics Systems University of Klagenfurt Klagenfurt Austria

ISBN: (数字)9798331535100

ISBN: (纸本)9798331535117

REpresentational State Transfer (REST) application programming interfaces (APIs) are widely used for the communication between loosely coupled web services. While the loose coupling allows services to evolve independently, it requires development teams to actively identify changes in their REST APIs to notify teams of affected services. If overlooked, changes can result in unexpected breaking changes that lead to failures in the affected service. In this paper, we present AutoGuard, our tool for automatically extracting and reporting breaking changes of REST APIs in services developed with the popular Java Spring Boot framework. AutoGuard consists of two components: the first component generates the OpenAPI descriptions of two versions of a REST API from the source code; the second component extracts and logs the differences between them and reports the API breaking changes. AutoGuard's static analysis does not require running a service to understand its REST API changes, enabling direct integration into the development process. We integrated AutoGuard into GitHub's and GitLab’ s contin-uous integration workflows, where it automatically generates the REST API change logs for pull and merge requests and reports any breaking changes. With this information, developers and code reviewers can make informed decisions on how to proceed with the requests. Video demonstration: https:/***/3qeWIVfMvWE Tool repository: https:/***/MSA-API-Management/AutoGuard

关键词： Java Web services Source coding Semantics Pipelines Static analysis Software Data models Representational state transfer application programming interfaces

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Intelligent Tutoring Systems Powered by Generative AI: Advancing Personalized Education and Overcoming Challenges

Intelligent Tutoring Systems Powered by Generative AI: Advan...

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Intelligent Systems and Computational Networks (ICISCN), International Conference on

作者： Balakrishnan P Anny Leema A Jothiaruna N Arun Kumar Sangaiah SCOPE Vellore Institue of Technology Vellore India SCSEAI Vellore Institue of Technology Bhobal India International Graduate School of AI National Yunlin University of Science and Technology Douliu Taiwan

ISBN: (数字)9798331529246

ISBN: (纸本)9798331529253

Brain signals analysis can be applied to students to identify their subject- or topic-specific struggles while they are listening to lecture videos. This re- search work proposes a threshold-based anomaly detection algorithm to identify the topics that cause students the most distress by analysing a dataset available at https://***/datasets/wanghaohan/confused-eeg/data. Firstly, it identifies the index and timestamp of distress data points of students’ brain signals, extracts the respective portion of transcribed textual content, given as prompt to ChatGPT or Bard via application programming interface (API) calls, get back the answers, and display it in a pop up window to the students. The proposed generative artificial intelligence (Gen AI)-powered intelligent tutoring system (ITS) captures almost 99% of confusion points and source confusion topic in brain signals as it uses context- aware algorithm thereby improving leaners’ clarity on the source confusion topic after reading the pop-up window content generated by Gen AI.

关键词： Generative AI Education Chatbots Indexes Signal analysis Intelligent systems Anomaly detection application programming interfaces Videos

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A Trustworthy Analysis Approach for Chatbots on Health Data: ChatGPT-4 Example

A Trustworthy Analysis Approach for Chatbots on Health Data:...

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International Scientific-Professional Conference on Information Technology (IT)

作者： Kübra Arslanoğlu Mehmet Karaköse The Department of Software Engineering The Faculty of Engineering The University of Firat Elazig The Department of Computer Engineering The Faculty of Engineering The University of Firat Elazig

ISBN: (数字)9798331517649

ISBN: (纸本)9798331517656

Considering the increasing and widespread use of chatbots, it is of great importance to provide methods and tools to address ethical concerns and to make users aware of various aspects of a chatbot, including non-functional features. The Generative Pre-Trained Transformer (GPT) is a state-of-the-art Natural Language Generation (NLG) model, enhanced by the latest version of GPT-4. This study evaluates the trustworthiness of the responses of three different chatbot models, BlenderBot with Hugging Face, ChatGPT-3.5 and ChatGPT-4, to 100 randomly selected medical questions. The accuracy and semantic similarity of the answers were measured by BLEU, ROUGE-1 and Cosine Similarity metrics, and response times were also recorded as an important performance factor. The results showed that GPT-4 exhibited superior performance, thus being able to produce more accurate and contextually reliable responses. However, the significantly longer response time of GPT-4 emerged as a disadvantage that may affect real-time utilisation. These findings provide an important reference for the effective use of GPT-4 in the context of health chatbots. The study contributes to the literature on improving the effectiveness of chatbots in healthcare by drawing attention to the importance of balancing speed, accuracy and trustworthiness, as well as the fact that the answers obtained are drawn with application programming Interface (API).

关键词： Accuracy Natural language generation Semantics Medical services Chatbots Transformers Real-time systems Time factors Reliability application programming interfaces

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