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检索条件"主题词=Application Programming Interfaces"

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Software Defined Radio for Time and Frequency applications: Example of Passive Monitoring of TWSTFT and other Timing Signals: (Invited Paper)

Software Defined Radio for Time and Frequency Applications: ...

引用

European Frequency and Time Forum (EFTF)

作者： J.-M Friedt FEMTO-ST Time & Frequency Besançon France

ISBN: (数字)9798350354270

ISBN: (纸本)9798350354287

Software Defined Radio (SDR) is a paradigm aimed at minimizing the contribution of hardware and maximizing the contribution of software when processing radiofrequency signals. While the concept is mostly used in the context of digital communication for agile systems flexible enough to adapt to unexpected conditions, accessing the raw samples right after the digitization of the radiofrequency wave provides opportunities for benefiting from information on the physical system before the signal has been processed. Not only does this access to the physical layer provide security, e.g. G NSS anti-spoofing and anti-jamming using null steering, but also the opportunity to finely recover timestamps in the context of time and frequency transfer. Free, opensource software is readily distributed for reproduction of the experiment at the Oscillator Instability Measurement Platform (OscIMP) Digital repository at https://***/oscimp/gr-satre for SATRE TWSTFT signal reception or https://***/oscimp/gnss-sdr-lpps/ for GNSS-controlled 1 PPS generation, and repetition of the measurements at remote sites, a core requirement of a scientific endeavor.

关键词： Radio frequency Time-frequency analysis Software maintenance Writing Digital communication Libraries Hardware Software measurement Software radio 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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DroidKey: A Practical Framework and Analysis Tool for API Key Security in Android applications

DroidKey: A Practical Framework and Analysis Tool for API Ke...

引用

International Research Conference on Smart Computing and Systems Engineering (SCSE)

作者： Kavindu Piyumantha Janaka Senanayake Keerthi Wijayasiriwardhane Dept. Industrial Management University of Kelaniya Dalugama Sri Lanka Dept. School of Computing Engineering and Technology Robert Gordon University Aberdeen United Kingdom

ISBN: (数字)9798331523268

ISBN: (纸本)9798331523275

The reliance on mobile applications has amplified concerns about application programming Interface (API) key security in Android platforms. Serving as essential authentication mechanisms, API keys ensure secure communication with external services. However, insecure practices like hardcoding expose keys to reverse engineering and unauthorized use. This research introduces the DroidKey Analysis Tool, designed to evaluate vulnerabilities and guide developers toward secure practices. The tool integrates a comprehensive framework encompassing six security domains. The methodology combines a systematic literature review, expert feedback, and validation through controlled experiments and real-world app evaluations. Results highlight the effectiveness of DroidKey, with secure implementations, such as those of the "Sample Mobile App," achieving significantly higher security scores than their insecure counterparts. Assessments of 10 real-world banking apps further reveal widespread vulnerabilities, underscoring the tool’s utility in addressing hardcoded keys and weak encryption. By leveraging industry-standard tools, the DroidKey Analysis Tool offers actionable insights to improve app security. Future enhancements, including real- time monitoring and expanded API key detection, are proposed to strengthen its functionality further. This research bridges the gap between theoretical security frameworks and practical applications, contributing to the advancement of Android app security.

关键词： Reverse engineering Systems engineering and theory Mobile security Mobile applications Encryption Security Protection Monitoring application programming interfaces Systematic literature review

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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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Monitoring Real-Time Fleet Emissions Through an Intelligent Fleet Management System

Monitoring Real-Time Fleet Emissions Through an Intelligent ...

引用

International Conference on Intelligent Transportation

作者： Hamidreza Abediasl Masoud Aliramezani Charles Robert Koch Mahdi Shahbakhti Department of Mechanical Engineering University of Alberta Edmonton Canada

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Monitoring fleet vehicle operation is a crucial aspect of fleet management systems, typically involving the analysis of GPS and/or on-board diagnostics (OBD) data from fleet vehicles. Given the increasing emphasis on environmental responsibility within fleet management, there is a growing demand for monitoring vehicle emissions. This study aims to integrate machine learning models for emission estimation into an intelligent fleet management system (IFMS) designed for light-duty vehicle fleets. These emission models are trained using real-driving data from fleet vehicles and have the capability to provide real-time emission estimates based on the OBD data of each vehicle. The developed IFMS is hardware-agnostic, allowing for wireless data collection, and enables the real-time reporting of fleet emissions, including CO 2 , CO, HC, and NOx.

关键词： Estimation Data collection Real-time systems Data models Monitoring Engines Load modeling Graphical user interfaces Global Positioning System application programming interfaces

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Violence Detection on Women using Generative AI

Violence Detection on Women using Generative AI

引用

Innovations in High Speed Communication and Signal Processing (IHCSP), International Conference on

作者： Aayush Shrivastava Nikhat Khan Paresh Tanna Amit Lathigara Computer Science Department IITM IES University Bhopal India Computer Science Department R K University Bhopal India

ISBN: (数字)9798350368949

ISBN: (纸本)9798350368956

Detection, prevention, and intervention strategies that rely on the application of state-of-the-art technology are required in that violence against women continues to threaten people from all walks of life. Through the applications of OpenAI's GPT models coupled with FastAPI for real-time deployment, this work comes to present an innovative solution in recognizing incidences of violence through Generative Artificial Intelligence. Through GPT's natural language capabilities, this system scans digital interactions for abusive language, harassment, and threats through social media and messaging platforms. Fast application programming interface (Fast API) is used by the system to give it scalability, real-time processing, and effective handling of concurrent requests so that it does not take too long in high-pressure situations. The technology is monitored and reports abusive behaviors through real-time alarm signals to the proper authorities or support services. Since it was trained on a wide variety of datasets, the model can both understand overt and subtle kinds of violence and thus be precise in identifying gender-based abuse that encompasses not only verbal manipulations but also psychological manipulations. This paper aims to deal with the ethical issues, problems, and possible impact of using a combination of GPT and FastAPI in relation to violence detection. The paper therefore underlines an integrated effort from AI developers, the legal frameworks, and social services to provide full mechanisms for protection.

关键词： Technological innovation Generative AI Social networking (online) Scalability Psychology Signal processing Real-time systems Protection Usability application programming interfaces

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Agile User-Centered Development of Mobile applications: A Systematic Literature Review

Agile User-Centered Development of Mobile Applications: A Sy...

引用

International Conference in Software Engineering Research and Innovation (CONISOFT)

作者： Alejandro Chacón Fernández Itzel Alessandra Reyes Flores Ana Luz Polo Estrella Facultad de Estadística e Informática Universidad Veracruzana Xalapa Veracruz México

ISBN: (数字)9798331532116

ISBN: (纸本)9798331532123

Given their nature, mobile applications require a high degree of usability, thus necessitating development processes which procure this quality attribute. Among such processes are those which integrate agile software development (ASD) with user-centered design (UCD), whose efficiency in creating more usable software has been proven in non-mobile software development projects. This study presents a systematic literature review with the aim of identifying the state of the art of agile-UCD Integration applied to mobile application development. A total of 32 studies were included, leading to the synthesis of frameworks used to integrate ASD with UCD, the UCD techniques involved in the process, the software tools used to design apps under agile-UCD, the challenges in adopting this approach as well as recommendations for their mitigation, and the benefits that both developers and users of mobile apps obtain when their software is developed with this approach.

关键词： Technological innovation Prevention and mitigation User centered design Agile software development Mobile communication Mobile applications Usability Software tools Software engineering application programming interfaces

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Generative AI for Personalized Learning Experiences in Education

Generative AI for Personalized Learning Experiences in Educa...

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International Conference on Computer and Communications Technologies (ICCCT)

作者： Swagata Sarkar Robin S Gokulrajan R Jitheshvar M Jeshvan Kudiyarasu Sri Sairam Engineering College

ISBN: (数字)9798331537579

ISBN: (纸本)9798331537586

When AI is used in schools, it should help kids to learn more. Individualized learning is an idea that has been around for a while, but you could not use it until not long ago. This research shows easy, cheap, and long-lasting ways to make learning tools. The teacher's learning goals for that class were used to make our tool. This tool can be used with a learning management system already set up at an engineering college. The lesson plans had three styles. For every question, there was more than one short answer and choice. There are three ways to get each lesson. Twenty software engineering students from a well-known European school helped test it in a small way. You can make this tool with a big language model and an application programming interface (API). All the participants participated in their own wish. These things were given to everyone in the class twice. They made a list of the things they used. They also cared about what people saw, thought, and felt, and they cared about these things over time. At school, it was also more important. People paid the most attention to the tests made immediately and looked like quizzes. Because it only looked at twenty kids, the study couldn't say what its results mean for all of them. The activation level for all tests was set to 0.5, and they were all done on the testing dataset.

关键词： Deep learning Measurement Learning management systems Generative AI Education Market research Data models application programming interfaces Testing Software engineering

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Anomaly Detection Employing a 5G Core Data Analytics Framework

Anomaly Detection Employing a 5G Core Data Analytics Framewo...

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IEEE International Conference on Cloud Networking (CLOUDNET)

作者： Júnia Maísa Oliveira Jônatan Almeida Erik De Britto e Silva Larissa Ferreira Rodrigues Moreira Rodrigo Moreira Flávio O. Silva Daniel F. Macedo José Marcos Nogueira Computer Science Department Universidade Federal de Minas Gerais Department of Electrical Electronic and Information Engineering University of Bologna Electrical Engineering Department Universidade Federal de Minas Gerais Institute of Exacts and Technological Sciences Federal University of Viçosa (UFV) Department of Informatics University of Minho (UMINHO)

ISBN: (数字)9798350376562

ISBN: (纸本)9798350376579

The Network Data Analytics Function (NWDAF) within the 5G core is not an inherent feature of open-source 5G cores, making its implementation necessary based on provider demands. However, for those seeking to integrate NWDAF into the core but lacking expertise in core architecture or application programming interface (API) integration, this task can be daunting, potentially resulting in the abandonment of data analytics implementation efforts. While the current version of NWDAF specifies certain use cases, it does not provide alternatives for developing new analytics scenarios. To fill this gap, this paper proposes a framework for 5G network data analytics designed to facilitate algorithmic modifications and the addition of new analytical contexts. The framework was developed considering the 3GPP technical specifications related to data analytics. Its evaluation was performed through a use case focused on cybersecurity anomaly detection applied to a 5G network core. The results demonstrated that the framework simplifies installation, increases flexibility for new algorithms, and integrates seamlessly into the 5G network core, effectively addressing previously identified shortcomings.

关键词： Analytical models Data analysis Machine learning algorithms 5G mobile communication Source coding Inspection 3GPP Computer security Anomaly detection application programming interfaces

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