X

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    Comparative Analysis of Transfer Learning-Based CNN Approaches for Recognition of Traffic Signs in Autonomous Vehicles
    EDP Sciences ; 2023
    In:  E3S Web of Conferences Vol. 412 ( 2023), p. 01096-
    Details
    In: E3S Web of Conferences, EDP Sciences, Vol. 412 ( 2023), p. 01096-
    Abstract: Traffic signs recognition has a crucial role in enhancing the safety and efficienty of autonomous vehicles (AVs). This AVs can contribute to a cleaner and healthier environment by improving fuel efficiency, minimizing travel distances, and deacreasing air pollution. Many artificial intelligence (AI) approaches contribute to develop AVs. Therfore, Convolutional Neural Networks (CNNs) have shown remarkable performance in image classification tasks for AVs, inculding traffic signs recognition. However, training deep CNNs from scratch for traffic sign recognition requires a significant amount of labeled data, which can be time-consuming and ressource-intensive to obtain. Transfer Learning, a technique that leverages pre-trained models on large-scale datasets,offers a promising solution by enabling the transfer of learned feautres from one task to another. This paper presents a comprehensive comparative analysis of three popular transfer learning based CNN approaches, namely ResNet, VGGNet, and MobileNet,for the recognition of traffic signs in the context of AVs.
    Type of Medium: Online Resource
    ISSN: 2267-1242
    URL: Article
    DOI: 10.1051/e3sconf/202341201096
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 2755680-3
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 2
    Online Resource
    Online Resource
    Distributed storage optimization using multi-agent systems in Hadoop
    EDP Sciences ; 2023
    In:  E3S Web of Conferences Vol. 412 ( 2023), p. 01091-
    Details
    In: E3S Web of Conferences, EDP Sciences, Vol. 412 ( 2023), p. 01091-
    Abstract: Understanding data and extracting information from it are the main objectives of data science, especially when it comes to big data. To achieve these goals, it is necessary to collect and process massive data sets, arriving at the system in different formats at great velocity. The Big Data era has brought us new challenges in data storage and management, and existing state-ofthe-art data storage and processing tools are poised to meet the challenges while posing challenges to the next generation of data. Big Data storage optimization is essential for improving the overall efficiency of Big Data systems by maximizing the use of storage resources. It also reduces the energy consumption of Big Data systems, resulting in financial savings, environmental protection, and improved system performance. Hadoop provides a solution for storing and analysing large quantities of data. However, Hadoop can encounter storage management problems due to its distributed nature and the management of large volumes of data. In order to meet future challenges, the system needs to intelligently manage its storage system. The use of a multi-agent system presents a promising approach for efficiently managing hot and cold data in HDFS. These systems offer a flexible, distributed solution for solving complex problems. This work proposes an approach based on a multi-agent system capable of gathering information on data access activity in the HDFS cluster. Using this information, it classifies data according to its temperature (hot or cold) and makes decisions about data replication based on its classification. In addition, it compresses unused data to manage resources efficiently and reduce storage space usage.
    Type of Medium: Online Resource
    ISSN: 2267-1242
    URL: Article
    DOI: 10.1051/e3sconf/202341201091
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 2755680-3
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 3
    Online Resource
    Online Resource
    Comparative study of the Security Analysis of IoT systems using attack trees algorithm
    EDP Sciences ; 2023
    In:  E3S Web of Conferences Vol. 412 ( 2023), p. 01087-
    Details
    In: E3S Web of Conferences, EDP Sciences, Vol. 412 ( 2023), p. 01087-
    Abstract: The Internet of Things (IoT) is a rapidly evolving environment that allows users to use and control a wide variety of connected objects. The 20 billion IoT devices that will be employed by 2020 are only the top of the iceberg. According to IDC, the overall amount of connected devices will rise to 41.6 billion over the next five years, producing over 80 Zettabytes of data by 2025 which will impact environment severely. These connected environments increase the attack surface of a system since; the risks are multiplied by the number of connected devices. These devices are responsible for more or less critical tasks, and can therefore be the target of users malicious, in this paper we present a methodology to evaluate the security of IoT systems. We propose a way to represent IoT systems, coupled with attack trees in order to assess the chances of success of an attack on a given system.
    Type of Medium: Online Resource
    ISSN: 2267-1242
    URL: Article
    DOI: 10.1051/e3sconf/202341201087
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 2755680-3
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 4
    Online Resource
    Online Resource
    A Breast Cancer Detection Problem using various Machine Learning Techniques in the Context of Health Prediction System
    EDP Sciences ; 2023
    In:  E3S Web of Conferences Vol. 412 ( 2023), p. 01093-
    Details
    In: E3S Web of Conferences, EDP Sciences, Vol. 412 ( 2023), p. 01093-
    Abstract: Today, breast cancer is one of the most common diseases that can cause certain complications, sometimes worst-case scenario is death. Thus, there is an urgent need for a diagnosis tool that can help doctors detect the disease at an early stage and recommend the necessary lifestyle changes to stop the progression of the disease; the likelihood of developing cancer at a young age has also been greatly increased by environmental changes in our everyday lives. Machine learning is an urgent need today to enhance human effort and offer higher automation with fewer errors. In this article, a breast cancer detection and prediction system is developed based on machine learning models (SVM, NB, AdaBoost). The achieved accuracies of the developed models are as follows: SVM achieved an overall score of 98.82%, NB achieved an overall score of 97.71%, and finally, AdaBoost achieved an overall score of 97.71%.
    Type of Medium: Online Resource
    ISSN: 2267-1242
    URL: Article
    DOI: 10.1051/e3sconf/202341201093
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 2755680-3
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 5
    Online Resource
    Online Resource
    AODV-based Defense Mechanism for Mitigating Blackhole Attacks in MANET
    EDP Sciences ; 2023
    In:  E3S Web of Conferences Vol. 412 ( 2023), p. 01094-
    Details
    In: E3S Web of Conferences, EDP Sciences, Vol. 412 ( 2023), p. 01094-
    Abstract: Mobile Ad hoc Networks (MANETs) are decentralized and self-configuring networks composed of mobile devices that communicate without a fixed infrastructure. However, the open nature of MANETs makes them vulnerable to various security threats, including blackhole attacks, where malicious nodes attract and discard network traffic without forwarding it to its intended destination. Mitigating blackhole attacks is crucial to ensure the reliability and security of communication in MANETs. This paper focuses on the development and evaluation of AODV (Ad hoc On-Demand Distance Vector)-based defence mechanisms for effectively mitigating blackhole attacks in MANETs, while simultaneously addressing energy efficiency and environmental sustainability. AODV is a widely used routing protocol in MANETs due to its on-demand nature and low overhead. However, it lacks built-in security mechanisms, making it susceptible to attacks. We incorporate energyaware route selection, solar-powered routing, collaborative energy sharing, energy-efficient intrusion detection, green routing optimization, and energy harvesting from environmental sources. By considering energy consumption and environmental factors in the route selection process, our defense mechanism not only enhances the security of the network but also contributes to energy conservation and reduced environmental impact. To evaluate the effectiveness of the proposed defence mechanisms, extensive simulations and performance analyses are conducted using network simulation tools. Through simulation-based evaluations, we demonstrate the effectiveness of our approach in achieving robust blackhole attack mitigation while extending the network’s lifetime and minimizing its carbon footprint. Our research offers valuable insights into the development of energy-efficient and environmentally sustainable solutions for securing MANETs in the face of evolving security threats.
    Type of Medium: Online Resource
    ISSN: 2267-1242
    URL: Article
    DOI: 10.1051/e3sconf/202341201094
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 2755680-3
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 6
    Online Resource
    Online Resource
    Impact of E-learning on the environment and the optimization of the use of natural resources
    EDP Sciences ; 2023
    In:  E3S Web of Conferences Vol. 412 ( 2023), p. 01098-
    Details
    In: E3S Web of Conferences, EDP Sciences, Vol. 412 ( 2023), p. 01098-
    Abstract: Online education, also called e-learning, has several advantages in terms of environmental impact and optimization of resources. Over the past few years there has been a huge shift towards e-learning platforms as a place for learning and education. During these days of confinement due to the COVID19 virus, students, administrators, practitioners, administrators and others visited these platforms more than ever. E-learning allows learners to access courses and educational resources from anywhere, eliminating the need to physically travel to a learning location. That reduces fuel consumption and greenhouse gas emissions associated with travel. For That reason, That article proposes a reflection on the concept of e-learning or computerized learning environment with the aim of allowing the involvement of users in the preservation of the environment and the optimization of the use of natural resources. The learning environment is defined in that article as a real or virtual place bringing together one or more systems that interact with a common objective, which is learning. The use of Learning and not teaching with environment confirms the fact that knowledge is made by a community of learners more than by the transmission of knowledge from the teacher to the student. Meanwhile, the learning environment is computerized when some or all of the interactions between the subsystems are supported by computing resources. Indeed, the environment hosts several activities in addition to the tools and equipment necessary for their realization. The concept of an open environment offers an interesting avenue for that purpose. It should be noted that e-learning does not completely replace traditional forms of education, but complements and diversifies learning options. Adopting e-learning in education can bring significant benefits in terms of environmental impact and value for money, while providing more flexible and accessible learning opportunities.
    Type of Medium: Online Resource
    ISSN: 2267-1242
    URL: Article
    DOI: 10.1051/e3sconf/202341201098
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 2755680-3
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 7
    Online Resource
    Online Resource
    Erratum to: Impact of E-learning on the environment and the optimization of the use of natural resources
    EDP Sciences ; 2023
    In:  E3S Web of Conferences Vol. 412 ( 2023), p. 01112-
    Details
    In: E3S Web of Conferences, EDP Sciences, Vol. 412 ( 2023), p. 01112-
    Type of Medium: Online Resource
    ISSN: 2267-1242
    URL: Article
    DOI: 10.1051/e3sconf/202341201112
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 2755680-3
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 8
    Online Resource
    Online Resource
    Metaheuristics methods for The VRP in Home Health Care by minimizing fuel consumption for environmental gain
    EDP Sciences ; 2021
    In:  E3S Web of Conferences Vol. 234 ( 2021), p. 00094-
    Details
    In: E3S Web of Conferences, EDP Sciences, Vol. 234 ( 2021), p. 00094-
    Abstract: Nowadays, the international society began to see clearly the impact of neglecting the environmental aspect in our lives, especially the issue of global warming. This paper aims in the first degree to minimize the carbon emission by vehicles and in doing so help to reduce the pollution ratio that is increasing day by day. In the home care sector, a patient requires from a health structure offering home care services one or many services to be done at home. For this purpose a health staff is mobilized to provide these services and must be done optimally. Many papers dealing with this kind of problems are suggesting that the way to optimize the problem encountered efficiently is to use the resources put in place to minimize the total travelled distance, but in this perspective, the study prioritizes the reduction and minimizing the fuel consumption. To answer all this questions, an exploration and an investigation of the problems addressed in the literature is performed, after that a mathematical formulation of the problem and two metaheuristics methods are proposed to resolve this problem. In the end, a comparison of the results of the two methods is presented.
    Type of Medium: Online Resource
    ISSN: 2267-1242
    URL: Article
    DOI: 10.1051/e3sconf/202123400094
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2021
    detail.hit.zdb_id: 2755680-3
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 9
    Online Resource
    Online Resource
    DNA technology for big data storage and error detection solutions: Hamming code vs Cyclic Redundancy Check (CRC)
    EDP Sciences ; 2023
    In:  E3S Web of Conferences Vol. 412 ( 2023), p. 01090-
    Details
    In: E3S Web of Conferences, EDP Sciences, Vol. 412 ( 2023), p. 01090-
    Abstract: There is an increasing need for high-capacity, highdensity storage media that can retain data for a long time, due to the exponential development in the capacity of information generated. The durability and high information density of synthetic deoxyribonucleic acid (DNA) make it an attractive and promising medium for data storage. DNA data storage technology is expected to revolutionize data storage in the coming years, replacing various Big Data storage technologies. As a medium that addresses the need for high-latency, immutable information storage, DNA has several potential advantages. One of the key advantages of DNA storage is its extraordinary density. Theoretically, a gram of DNA can encode 455 exabytes, or 2 bits per nucleotide. Unlike other digital storage media, synthetic DNA enables large quantities of data to be stored in a biological medium. This reduces the need for traditional storage media such as hard disks, which consume energy and require materials such as plastic or metals, and also often leads to the generation of electronic waste when they become obsolete or damaged. Additionally, although DNA degrades over thousands of years under non-ideal conditions, it is generally readable. Furthermore, as DNA possesses natural reading and writing enzymes as part of its biological functions, it is expected to remain the standard for data retrieval in the foreseeable future. However, the high error rate poses a significant challenge for DNA-based information coding strategies. Currently, it is impossible to execute DNA strand synthesis, amplification, or sequencing errors-free. In order to utilize synthetic DNA as a storage medium for digital data, specialized systems and solutions for direct error detection and correction must be implemented. The goal of this paper is to introduce DNA storage technology, outline the benefits and added value of this approach, and present an experiment comparing the effectiveness of two error detection and correction codes (Hamming and CRC) used in the DNA data storage strategy.
    Type of Medium: Online Resource
    ISSN: 2267-1242
    URL: Article
    DOI: 10.1051/e3sconf/202341201090
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 2755680-3
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
  • 10
    Online Resource
    Online Resource
    Real-time GPS Tracking System for IoT-Enabled Connected Vehicles
    EDP Sciences ; 2023
    In:  E3S Web of Conferences Vol. 412 ( 2023), p. 01095-
    Details
    In: E3S Web of Conferences, EDP Sciences, Vol. 412 ( 2023), p. 01095-
    Abstract: This paper presents a real-time GPS tracking solution for connected vehicle networks, leveraging IoT, V2X communication, and VANET technologies. The system uses Arduino Uno R3, SIM800L, NEO6M GPS, Node.js, socket, and Firebase for seamless real-time GPS data collection, storage, and visualization. Users can access and monitor GPS data on a web interface. Integration of Node.js and sockets ensures efficient hardware-software communication, while Firebase enables realtime data storage and synchronization for resource management and tracking. The paper explores the system’s applications in dynamic routing for energy efficiency, eco-driving feedback, smart charging stations, environmental data collection, intelligent traffic management, and fleet emissions reduction. These applications highlight the system’s versatility, promoting energy efficiency and sustainability across industries. By incorporating IoT, VANET, and V2X communication, the system enables seamless connectivity and data exchange among vehicles, infrastructure, and the cloud, enhancing decision-making and system efficiency. Insights into system implementation, including IoT, VANET, and real-time GPS integration, are provided. The paper discusses transportation, logistics, and vehicule tracking as potential application domains, which hold promise for optimizing energy consumption. The presented solution offers an efficient, reliable platform for real-time GPS tracking in connected vehicle networks, harnessing IoT, VANET, and V2X communication for enhanced decisionmaking and sustainable transportation systems.
    Type of Medium: Online Resource
    ISSN: 2267-1242
    URL: Article
    DOI: 10.1051/e3sconf/202341201095
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 2755680-3
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Availability (electronic / print)
Nothing or not found what you are looking for? Please check your search query or use the Interlibrary Loan Search.
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages