This paper proposes a new algorithm called Dynamic Optimization of Energy and QoS in VANETs (DOEQ-VANET), designed to maximize the energy efficiency and Quality of Service (QoS) of the Vehicular Ad-hoc Networks (VANET...
详细信息
ISBN:
(数字)9798350354133
ISBN:
(纸本)9798350354140
This paper proposes a new algorithm called Dynamic Optimization of Energy and QoS in VANETs (DOEQ-VANET), designed to maximize the energy efficiency and Quality of Service (QoS) of the Vehicular Ad-hoc Networks (VANETs). Through exploiting the heterogeneity of Multiprocessor System-on-Chip (MPSoC) employing an approximate computation, DOEQ-VANET is capable of dynamically adjusting the computational accuracy for non-critical applications which results in energy conservation without the risk of propagating the misinformation. Task assignment and scheduling are continuously dynamically adjusted as they respond to network fluctuation, vehicle dynamics and energy availability. The simulation result and validation proved the power of the proposed algorithm, which would mark a large advancement toward more green and smart vehicular networks within the field of Intelligent Transport Systems (ITS). This algorithm is crucial for improving the sustainability and efficiency of future transportation systems.
Modern scientific applications are increasingly decomposable into individual functions that may be deployed across distributed and diverse cyberinfrastructure such as supercomputers, clouds, and accelerators. Such app...
详细信息
Low-latency and area-efficient forward error cor-rection is crucial in high-throughput communication scenarios, such as die-to-die connections. Using $t$ to denote error correction capability, we propose a low-laten...
详细信息
ISBN:
(数字)9798350354119
ISBN:
(纸本)9798350354126
Low-latency and area-efficient forward error cor-rection is crucial in high-throughput communication scenarios, such as die-to-die connections. Using
$t$
to denote error correction capability, we propose a low-latency t-unfolded simplified inverse-free Berlekamp- Massey (SiBM) decoder, which for
$t > 3$
offers a shorter critical path compared with area-efficient Peterson-based decoders. Synthesized in a 22-nm CMOS process, our unfolded SiBM decoders with
$t=4$
and 5 provide up to
$1.39\times$
higher throughput than their Peterson-based counterparts, at comparable area efficiencies.
Cervical Cancer (CC) is the fourth frequent dreadful cancers that prevails in women across the globe. Cervical cytology is being adopted as the standard technique for the screening of pre-cancerous stage and cancerous...
Cervical Cancer (CC) is the fourth frequent dreadful cancers that prevails in women across the globe. Cervical cytology is being adopted as the standard technique for the screening of pre-cancerous stage and cancerous lesions detection. For accurate segmentation in cervical cytology, the smear images play a crucial role in any Artificial Intelligence based computer Aided Diagnosis (CAD) method. This relies upon the precise segmentation of nucleus present in the cervical cytology smear images. The motive of this study deals with a systematic analysis of the various challenges that are encountered while segmenting the Cervical Cell Nucleus and the countermeasures that are incorporated to eliminate the misdiagnosis and missed diagnoses in the early stage of screening. With the motive of this, a systematic study of the published articles from the sources – Scopus, PubMed and Web of Science are analyzed and reviewed. The importance of this study is due to the intensity of the disease that still positions cervical cancer as a bothering disease that disrupts the life of about five lakh female population, every year across the world.
The rapid evolution of smart grids has necessitated the development of advanced computational techniques to ensure efficient and reliable power distribution. This paper introduces a novel approach to solving the Optim...
详细信息
Network Functions Virtualization has been a key enabler for the wide adoption of cloud-native functions for workloads. Well-established orchestration frameworks, such as Kubernetes, optimize network operation to meet ...
Network Functions Virtualization has been a key enabler for the wide adoption of cloud-native functions for workloads. Well-established orchestration frameworks, such as Kubernetes, optimize network operation to meet the networking requirements of deployed workloads, while providing a flexible API for fine-grained control throughout the lifecycle of the workload. As a result, these tools can be used effectively to provide access to distributed 5G experimental facilities, even across continents. However, resource clusters may belong to distinct administrative authorities; therefore, cluster integration must occur by exposing only the necessary information and services. In this paper, we suggest employing SUSE Rancher for managing multi-cluster Kubernetes deployments and utilize the Submariner framework in order to securely export services and establish connectivity across clusters. We evaluate the efficacy of such integrated framework and its various configurations over a high-speed networking fabric (up to 25 Gbps) connecting the various clusters and enabling 5G and beyond exnerimentation.
The Autonomous High Tension Transmission Line Inspection Robot is an innovative solution designed to revolutionize the maintenance and inspection processes associated with high-tension electrical transmission lines. H...
详细信息
The intelligent medical assistive system has emerged as a topic of considerable interest within the research community in recent years. The implementation of such a system has the potential to significantly reduce the...
详细信息
ISBN:
(数字)9798331521165
ISBN:
(纸本)9798331521172
The intelligent medical assistive system has emerged as a topic of considerable interest within the research community in recent years. The implementation of such a system has the potential to significantly reduce the workload of medical personnel while simultaneously enhancing the quality of medical treatment. The automated detection of endoscopic images through computer vision technology represents a significant aspect of the development of intelligent medical assistive systems. In this study, we propose the integration of artificial intelligence-based automated detection and measurement technology into a medical assistive system. The system is capable of detecting polyps in endoscopic images and measuring their sizes simultaneously, as well as calculating the distance to any region of interest in endoscopic images. The detection and measurement performance of the proposed system has been evaluated using self-collected real-world endoscopy images. To demonstrate the clinical unmet need that the proposed system addresses, it was deployed to an edge computing device and integrated with actual endoscopic equipment, which confirmed the effectiveness of the proposed system.
computer-aided diagnosis (CAD) systems stand out as potent aids for physicians in identifying the novel Coronavirus Disease 2019 (COVID-19) through medical imaging modalities. In this paper, we showcase the integratio...
详细信息
Phishing attacks are a major cybersecurity threat that resulted in over 1.2 million incidents in the first half of 2020. These attacks caused substantial financial losses and posed risks to individuals and organizatio...
详细信息
ISBN:
(数字)9798331534400
ISBN:
(纸本)9798331534417
Phishing attacks are a major cybersecurity threat that resulted in over 1.2 million incidents in the first half of 2020. These attacks caused substantial financial losses and posed risks to individuals and organizations. Being able to identify fraudulent websites is crucial in order to effectively address these potential risks. This study introduces a novel method for detecting phishing URLs by using word and character embeddings to capture complex URL patterns. We used a dataset of 80,000 URLs, including 50,000 legitimate ones and 30,000 phishing instances, and applied thorough preprocessing techniques. We utilized word embeddings in FastText to handle unseen words, with the added advantage of n-gram representations. Additionally, we captured character-level features through dense character embeddings. We trained several machine learning and deep learning models, and one model, the Convolutional Bidirectional LSTM (CBiLSTM), stood out with an accuracy of 99.01% and an F1-score of 99.08%. Furthermore, we made a thorough comparison with the most advanced techniques available, and our findings demonstrated clear superiority over previous research. This study presents an effective approach for classifying phishing URLs, providing a valuable tool to combat fraud and protect against identity theft, thereby helping to minimize the financial and emotional harm experienced by victims.
暂无评论