Wireless Networking
The project entitled “COMPUTERIZED ENROLLMENT SYSTEM”. Every organization, whether big or small, has human resource challenges to overcome. Every organization has different employee management needs; therefore we design exclusive employee management systems that are adapted to your managerial requirements. This is designed to assist in strategic planning, and will help you ensure that your organization is equipped with the right level of human resources for your future goals.
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Computer Graphics is concerned with all aspects of producing pictures or images using a computer. We can create images that are indistinguishable from photographs of real objects. In other terms, Computer Graphics are the graphics created by the computers, and more generally, the representation and manipulation of image data by a computer. The development of computer graphics has been driven both by the needs of the user community and by advances in hardware and software.
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The term “graphical password” refers to a user authentication method where pictorial information is used for validation, instead of an alphanumerical password. This method poses many challenges, such as memo ability (which refers to how easy the password is to remember), usability, and security, since graphical passwords may tend to be visually simple and easily forged. Graphical passwords have become popular due to the proliferation of touch screen devices, in particular smart phones and tablets.
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Tourism receipts worldwide are not expected to recover to 2019 levels until 2023. In
the first half of this year, tourist arrivals fell globally by more than 65 percent, with a near halt
since April—compared with 8 percent during the global financial crisis and 17 percent amid
the SARS epidemic of 2003, according to ongoing IMF research on tourism in a post-pandemic
world. Because of pandemic we faces the different struggles specially the business closed.
that’s why country’s economy decrease, at first many company need to reduce their employee.
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This dataset used in the research paper "JamShield: A Machine Learning Detection System for Over-the-Air Jamming Attacks." The research was conducted by Ioannis Panitsas, Yagmur Yigit, Leandros Tassiulas, Leandros Maglaras, and Berk Canberk from Yale University and Edinburgh Napier University.
For any inquiries, please contact Ioannis Panitsas at ioannis.panitsas@yale.edu.
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The increasing prevalence of encrypted traffic in
modern networks poses significant challenges for network security,
particularly in detecting and classifying malicious activities
and application signatures. To overcome this issue, deep learning
has turned out to be a promising candidate owing to its ability
to learn complex data patterns. In this work, we present a
deep learning-based novel and robust framework for encrypted
traffic analysis (ETA) which leverages the power of Bidirectional
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In our research, we generate datasets utilizing two key statistical models: the Poisson Process Distribution and the Beta Distribution. These models are employed to simulate and analyze various aspects of Quality of Service (QoS) in Internet of Things (IoT) environments, with a particular emphasis on wireless communications. By leveraging these distributions, our study aims to optimize resource allocation, improve reliability, and ensure that QoS requirements are met in complex and dynamic wireless communication scenarios within IoT ecosystems.
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Intrusion detection in Unmanned Aerial Vehicle (UAV) networks is crucial for maintaining the security and integrity of autonomous operations. However, the effectiveness of intrusion detection systems (IDS) is often compromised by the scarcity and imbalance of available datasets, which limits the ability to train accurate and reliable machine learning models. To address these challenges, we present the "CTGAN-Enhanced Dataset for UAV Network Intrusion Detection", a meticulously curated and augmented dataset designed to improve the performance of IDS in UAV environments.
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The dataset accompanies the study titled “Rate Adaptation Algorithms in WLANs: A Comparative Analysis of Iwl-Mvm-Rs and Minstrel-HT Under Different Frame Error Causes.” This dataset contains simulation results that evaluate the performance of the Iwl-Mvm-Rs and Minstrel-HT Rate Adaptation Algorithms (RAAs) under varying frame error conditions, specifically low Signal-to-Noise Ratio (SNR) and collision-induced errors.
The data was generated using ns-3 simulations across four scenarios:
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This dataset consists of network packet traces collected in 2023 on the 5G infrastructure deployed at Chalmers University of Technology.
The dataset includes 1,912 pcap files, distributed across 8 folders. Each pcap file captures 1 minute of encrypted network traffic generated by one of the following 8 popular mobile applications:
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