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检索条件"丛书名=Lecture Notes in Networks and Systems"

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Comparative Analysis of Large Language Models in Source Code Analysis 1

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Erdogan, Huseyin Turan, Nezihe Turhan Onan, Aytug Izmir Katip Celebi Univ Inst Sci & Engn Dept Syst Engn TR-35620 Izmir Turkiye Izmir Katip Celebi Univ Fac Engn & Architecture Dept Engn Sci TR-35620 Izmir Turkiye Izmir Katip Celebi Univ Fac Engn & Architecture Dept Comp Engn TR-35620 Izmir Turkiye

ISBN: (数字)9783031700187

ISBN: (纸本)9783031700170;9783031700187

This article is a summary of a study focusing on Artificial Intelligence (AI) based source code analysis amidst the complexity of software development and rapidly evolving technological needs. The study evaluates analyses conducted to improve code quality, detect errors, and perform code optimization by examining the potential impacts of AI in software development processes. The time spent on research and experiments for detecting and resolving errors in the software development process has been a constant source of concern. In this context, the results of using unoptimized source code often lead to outputs that directly affect complex and maintenance costs. The topic has been extensively addressed in the literature as a comprehensive subject known as AI, Code Intelligence (CI), and Programming Language Processing (PLP) and has been the focus of various surveys and application studies. The article suggests that the use of AI could be a potential solution to increase efficiency and minimize errors in software development processes. In the study, two different AI tools, namely ChatGPT and Gemini, were used to address problem resolution. Two different models, GPT4 and Gemini, were included in the analysis process. JavaScript was the preferred language for obtaining source code, which was sourced from the GitHub platform.

关键词： Artificial Intelligence Source Code Analysis Source Code Improvement Source Code Optimization Source Code Quality Data Mining Deep Learning Machine Learning ChatGPT Gemini GPT4

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Invisible Presence Control System Through IoT Devices Network 16th

Invisible Presence Control System Through IoT Devices Networ...

引用

16th International Conference on Ubiquitous Computing and Ambient Intelligence

作者： Mora, Higinio Ramirez, Tamai Pujol, Francisco Llamas, Alejandro Sirvent Univ Alicante Dept Comp Sci & Technol Alicante Spain

ISBN: (纸本)9783031775703;9783031775710

This proposal consists of a system and a method of presence control without the need for any action on the part of the user. The system is able of detecting and registering users in an area. This action is performed transparently to the users so that the system does not require interaction by the users or any other operator to be detected. This system is ideal for time-stamping in an organization. This system has significant advantages over current systems, because the presence control does not require the intervention or the performance of specific actions of the agents involved to carry out the process of presence detection and registration. The system can be applied in work environments of any type and size, regardless of the number of workers to be registered and supervised. It provides up-to-date information on the real-time registration of the organization's workers. It is compatible with existing systems and can be deployed to complement or replace them.

关键词： presence control IoE application and services IoE enabling technologies Applications of hybrid sensor networks

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Federated Learning Approach Using Transfer Learning Architectures for Lung Cancer Detection

Federated Learning Approach Using Transfer Learning Architec...

引用

2024 International Conference on Computing, Communication, Cybersecurity and AI

作者： Choure, Purvi Prajapat, Shaligram Berwal, Krishan Devi Ahilya Vishwavidyalaya Int Inst Profess Studies Indore India

ISBN: (纸本)9783031744426;9783031744433

There have been many advancements in the field of medical imaging but even then, accurate cancer detection remains a challenge because of limited labelled data. In the research field, a lot of work is already done for this task, using pre-trained features from prominent architectures like VGG16, ResNet50, MobileNetV2, InceptionV3, and DensNet121. These approaches face the issue of privacy of patients' sensitive information and unnecessary latency of exchange of data from nodes to sever, so in this paper, we use Federated Learning that enables collaborative learning across geographically distributed medical institutions. Additionally, we implement differential privacy techniques to obscure the patients' identities which would further enhance privacy protection. This paper also presents the evaluation of effectiveness of different transfer learning architectures within the FL setting, comparing their performance with centralized learning and standalone transfer learning approaches. This work adds a new direction to cancer detection with improved privacy protection, leading to earlier intervention for cancer detection.

关键词： Deep Learning Transfer Learning Federated Learning Differential Privacy

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Agricultural Internet of Things (AIoTs) Threat Modeling Using STRIDE-LM 9th

Agricultural Internet of Things (AIoTs) Threat Modeling Usin...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Maodza, Brian du Toit, Jaco IIEMSA Independent Inst Educ Johannesburg South Africa Univ Johannesburg Johannesburg South Africa

ISBN: (纸本)9789819733019;9789819733026

To meet the ever-rising food requirements around the world and mitigate the effects of climate change and shortage of agricultural land, farmers are now adopting the Agricultural Internet of Things (AIoT) for intelligent agriculture, which helps to increase farm productivity. AIoT enables a data-driven agriculture model, enabling farmers to make informed decisions. The research paper will briefly discuss the application of AIoT in crop and livestock production. Components of AIoT architecture in crop and livestock production will be identified. Threats to AIoT were modeled using Spoofing, Tampering, Repudiation, Information Disclosure, Denial of service, and Elevation of Privilege Lateral Movement (STRIDE-LM). The research identified different threats to AIoT grouped into the different STRIDE_LM categories.

关键词： Threat modelling STRIDE-LM Agricultural Internet of Things Intelligent agriculture

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Prediction of Load Time in Web Services for Different Agent Locations and Browsers for Mobile Devices 1

引用

Computing Conference

作者： Wrzuszczak-Noga, Jolanta Wroclaw Univ Sci & Technol Fac Informat & Commun Technol Wybrzeze Wyspianskiego 27 PL-50370 Wroclaw Poland

ISBN: (数字)9783031622731

ISBN: (纸本)9783031622755;9783031622731;9783031622724

The paper concerns on the prediction of the load time of Internet resources, depending on the location of the client and the browser used for mobile devices (Android and IOS operating system). An experiment was performed using API ofWebPageTest to get and store real data from different agents located in four locations around the world. They monitor and store information about transferring data from 10 sites. The collected measurements were used for making prediction of load time using three different prediction algorithms: the Random Forest, SVM and Linear Regression. The quality assessment of prediction was tested and compared using metrics RMSE, MSE and MAE. Investigations can be applied and implemented in community networks, where time of network selection is important. Results can be also used for performing intelligent internet measurement (IoT), where more and more communication (transmission of data) takes places over mobile devices.

关键词： Mobile prediction Load time prediction Web performance

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Deep Learning for Medical Image Analysis 5th

Deep Learning for Medical Image Analysis

引用

5th International Conference on Communication and Intelligent systems (ICCIS)

作者： Panda, Saswat Parida, Sahul Kumar Khatri, Ripusudan Kaur, Rupinder Chandigarh Univ Dept Comp Sci Ludhiana Punjab India

ISBN: (纸本)9789819720811;9789819720828

Medical image analysis aims to enhance medical outcomes by using images of internal body parts for purposes such as research and diagnosis. The field has been transformed by deep learning, which has achieved remarkable results in tasks such as image alignment, partitioning, feature extraction, and categorization. The main factor for this shift is the advances in computing power and the emergence of deep neural networks. Deep learning is adept at finding hidden patterns in medical images and helps doctors make more precise diagnoses. They have shown their usefulness in tasks such as organ categorization, cancer detection, disease categorization, and computer-aided diagnosis. Various deep learning methods have been developed to analyze medical images for different diagnoses. In this article, we review the application of state-of-the-art deep learning techniques in medical image processing. We first survey the clinical trials that use neural networks. We then review popular pre-training models and discuss different integration methods that can enhance the performance of the neural network. Finally, we measure the performance indicators for the deep learning model and present the results.

关键词： Medical Images Diagnoses Network Cancer

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Embedding Inclusivity Design into the Data Science Curriculum

Embedding Inclusivity Design into the Data Science Curriculu...

引用

Intelligent systems Conference

作者： Campbell, Jacqueline Leeds Beckett Univ Leeds LS6 3QW W Yorkshire England

ISBN: (纸本)9783031663284;9783031663291

As big data, artificial intelligence (AI) and technology are infiltrating our lives at an exponential rate, challenges are being raised in term of the consequences, trust and bias of these advancements. This paper describes and evaluates the introduction of design thinking into the Data Science programmes. Curriculum was developed to highlight the issues of non-inclusive design, drawing on well received contemporary literature, research and using enquiry based learning to unpack the social and technical reasons for this. Students were introduced to ethical frameworks used to mitigate against design bias. Additionally, the university's strategy for Equality, Diversity and Inclusivity (EDI) was delivered as a contextualised workshop. The student experience was evaluated via a survey, concluding that the students had developed an appreciation for inclusivity both in terms of design thinking as team contribution.

关键词： Data science Technology Bias Enquiry based learning EDI

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Convolutional Neural Network-Based Efficient Dense Point Cloud Generation Using Unsigned Distance Fields 9th

Convolutional Neural Network-Based Efficient Dense Point Clo...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Basher, Abol Boutellier, Jani Univ Vaasa Sch Technol & Innovat Wolffintie 32 Vaasa 65200 Finland

ISBN: (纸本)9789819735556;9789819735563

Dense point cloud generation from a sparse or incomplete point cloud is a crucial and challenging problem in 3D computer vision and computer graphics. So far, the existing methods are either computationally too expensive, suffer from limited resolution, or both. In addition, some methods are strictly limited to watertight surfaces-another major obstacle for a number of applications. To address these issues, we propose a lightweight Convolutional Neural Network that learns and predicts the unsigned distance field for arbitrary 3D shapes for dense point cloud generation using the recently emerged concept of implicit function learning. Experiments demonstrate that the proposed architecture outperforms the state of the art by 7.8x less model parameters, 2.4x faster inference time and up to 24.8% improved generation quality compared to the state-of-the-art.

关键词： Point cloud Implicit representation CNN Unsigned distance field 3D reconstruction

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Non-fungible Tokens and Their Applications 1

引用

11st World Conference on Information systems and Technologies (WorldCIST)

作者： Patel, Jeet Fernandes, Delicia Jasani, Darshkumar Patel, Kunjal Rahim, Muhammad Abdul Basit Ur Calif State Univ Comp Engn & Comp Sci Long Beach CA 90840 USA

ISBN: (数字)9783031456510

ISBN: (纸本)9783031456503;9783031456510

We are moving toward digitization, and the word used most frequently while describing it is "money." This is backed up by "Bitcoins," a type of virtual currency that can be traded via Blockchain, a distributed ledger technology. Bitcoins are essentially extended sequences of code that have been changed to take on monetary value. However, Non-fungible tokens (NFTs) were created in late 2017 as a brand-new class of distinct and undivided blockchain-based currency. While fungible tokens have enabled new use cases, such as initial coin offerings, it is unclear if NFTs will be applicable. NFTs advance the reinvention of this infrastructure by enabling digital representations of physical assets. Because this technology is distributed and immutable, it is difficult to modify, replicate, or fake transactions. This study attempts to assist and educate the research community about this new disruptive technology and direct them in the correct steps for blockchain technology adoption.

关键词： Blockchain Tokenization Smart Contract Cryptocurrency Non-Fungible Token Applications

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Reviewing Learning Software Engineering Through Serious Game Development 1

引用

11st World Conference on Information systems and Technologies (WorldCIST)

作者： Kharbouch, Manal Alberto Garcia-Berna, Jose Carrillo de Gea, Juan Manuel Nicolas Ros, Joaquin Toval Alvarez, Jose Ambrosio Idri, Ali Luis Fernandez-Aleman, Jose Univ Murcia Fac Informat Dept Comp & Syst Software Engn Res Grp Murcia Spain Mohamed V Univ Rabat Dept Web & Mobile Engn ENSIAS Software Project Management Res Team Rabat Morocco

ISBN: (数字)9783031456459

ISBN: (纸本)9783031456442;9783031456459

Serious games (SGs) are known as games designed for educational purposes rather than mere entertainment. Although their integration into software engineering (SE) education is a relatively new trend, it is spreading gradually, and thus gaining growing attention in the academic field. In this paper, we first investigated how SGs' design and development have been used as a pedagogical approach in SE education. Second, we analyzed the perceived complexity and potential effectiveness of this approach from the literature. Last, we addressed its resulting challenges and opportunities in the realm of SE education. The search for studies was carried out in leading search resources namely, Science Direct, IEEE Xplore, ACM, Scopus, as well as Wiley resulting in a set of six selected studies. Our study's results show that the design and development of SGs could be used to further motivate students, improve their SE learning experience and make it more enjoyable, and promote the use of these SGs. Moreover, this pedagogical approach was considered effective for a holistic understanding of SE courses, and better knowledge and skills acquisition.

关键词： Serious Game Software Engineering Education

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