8,120 research outputs found

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Novel 129Xe Magnetic Resonance Imaging and Spectroscopy Measurements of Pulmonary Gas-Exchange

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    Gas-exchange is the primary function of the lungs and involves removing carbon dioxide from the body and exchanging it within the alveoli for inhaled oxygen. Several different pulmonary, cardiac and cardiovascular abnormalities have negative effects on pulmonary gas-exchange. Unfortunately, clinical tests do not always pinpoint the problem; sensitive and specific measurements are needed to probe the individual components participating in gas-exchange for a better understanding of pathophysiology, disease progression and response to therapy. In vivo Xenon-129 gas-exchange magnetic resonance imaging (129Xe gas-exchange MRI) has the potential to overcome these challenges. When participants inhale hyperpolarized 129Xe gas, it has different MR spectral properties as a gas, as it diffuses through the alveolar membrane and as it binds to red-blood-cells. 129Xe MR spectroscopy and imaging provides a way to tease out the different anatomic components of gas-exchange simultaneously and provides spatial information about where abnormalities may occur. In this thesis, I developed and applied 129Xe MR spectroscopy and imaging to measure gas-exchange in the lungs alongside other clinical and imaging measurements. I measured 129Xe gas-exchange in asymptomatic congenital heart disease and in prospective, controlled studies of long-COVID. I also developed mathematical tools to model 129Xe MR signals during acquisition and reconstruction. The insights gained from my work underscore the potential for 129Xe gas-exchange MRI biomarkers towards a better understanding of cardiopulmonary disease. My work also provides a way to generate a deeper imaging and physiologic understanding of gas-exchange in vivo in healthy participants and patients with chronic lung and heart disease

    Secure Routing Protocol To Mitigate Attacks By Using Blockchain Technology In Manet

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    MANET is a collection of mobile nodes that communicate through wireless networks as they move from one point to another. MANET is an infrastructure-less network with a changeable topology; as a result, it is very susceptible to attacks. MANET attack prevention represents a serious difficulty. Malicious network nodes are the source of network-based attacks. In a MANET, attacks can take various forms, and each one alters the network's operation in its unique way. In general, attacks can be separated into two categories: those that target the data traffic on a network and those that target the control traffic. This article explains the many sorts of assaults, their impact on MANET, and the MANET-based defence measures that are currently in place. The suggested SRA that employs blockchain technology (SRABC) protects MANET from attacks and authenticates nodes. The secure routing algorithm (SRA) proposed by blockchain technology safeguards control and data flow against threats. This is achieved by generating a Hash Function for every transaction. We will begin by discussing the security of the MANET. This article's second section explores the role of blockchain in MANET security. In the third section, the SRA is described in connection with blockchain. In the fourth phase, PDR and Throughput are utilised to conduct an SRA review using Blockchain employing PDR and Throughput. The results suggest that the proposed technique enhances MANET security while concurrently decreasing delay. The performance of the proposed technique is analysed and compared to the routing protocols Q-AODV and DSR.Comment: https://aircconline.com/ijcnc/V15N2/15223cnc07.pd

    Detecting Anomalous Microflows in IoT Volumetric Attacks via Dynamic Monitoring of MUD Activity

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    IoT networks are increasingly becoming target of sophisticated new cyber-attacks. Anomaly-based detection methods are promising in finding new attacks, but there are certain practical challenges like false-positive alarms, hard to explain, and difficult to scale cost-effectively. The IETF recent standard called Manufacturer Usage Description (MUD) seems promising to limit the attack surface on IoT devices by formally specifying their intended network behavior. In this paper, we use SDN to enforce and monitor the expected behaviors of each IoT device, and train one-class classifier models to detect volumetric attacks. Our specific contributions are fourfold. (1) We develop a multi-level inferencing model to dynamically detect anomalous patterns in network activity of MUD-compliant traffic flows via SDN telemetry, followed by packet inspection of anomalous flows. This provides enhanced fine-grained visibility into distributed and direct attacks, allowing us to precisely isolate volumetric attacks with microflow (5-tuple) resolution. (2) We collect traffic traces (benign and a variety of volumetric attacks) from network behavior of IoT devices in our lab, generate labeled datasets, and make them available to the public. (3) We prototype a full working system (modules are released as open-source), demonstrates its efficacy in detecting volumetric attacks on several consumer IoT devices with high accuracy while maintaining low false positives, and provides insights into cost and performance of our system. (4) We demonstrate how our models scale in environments with a large number of connected IoTs (with datasets collected from a network of IP cameras in our university campus) by considering various training strategies (per device unit versus per device type), and balancing the accuracy of prediction against the cost of models in terms of size and training time.Comment: 18 pages, 13 figure

    FedAVO: Improving Communication Efficiency in Federated Learning with African Vultures Optimizer

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    Federated Learning (FL), a distributed machine learning technique has recently experienced tremendous growth in popularity due to its emphasis on user data privacy. However, the distributed computations of FL can result in constrained communication and drawn-out learning processes, necessitating the client-server communication cost optimization. The ratio of chosen clients and the quantity of local training passes are two hyperparameters that have a significant impact on FL performance. Due to different training preferences across various applications, it can be difficult for FL practitioners to manually select such hyperparameters. In our research paper, we introduce FedAVO, a novel FL algorithm that enhances communication effectiveness by selecting the best hyperparameters leveraging the African Vulture Optimizer (AVO). Our research demonstrates that the communication costs associated with FL operations can be substantially reduced by adopting AVO for FL hyperparameter adjustment. Through extensive evaluations of FedAVO on benchmark datasets, we show that FedAVO achieves significant improvement in terms of model accuracy and communication round, particularly with realistic cases of Non-IID datasets. Our extensive evaluation of the FedAVO algorithm identifies the optimal hyperparameters that are appropriately fitted for the benchmark datasets, eventually increasing global model accuracy by 6% in comparison to the state-of-the-art FL algorithms (such as FedAvg, FedProx, FedPSO, etc.).Comment: 19 page

    A Secure and Distributed Architecture for Vehicular Cloud and Protocols for Privacy-preserving Message Dissemination in Vehicular Ad Hoc Networks

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    Given the enormous interest in self-driving cars, Vehicular Ad hoc NETworks (VANETs) are likely to be widely deployed in the near future. Cloud computing is also gaining widespread deployment. Marriage between cloud computing and VANETs would help solve many of the needs of drivers, law enforcement agencies, traffic management, etc. The contributions of this dissertation are summarized as follows: A Secure and Distributed Architecture for Vehicular Cloud: Ensuring security and privacy is an important issue in the vehicular cloud; if information exchanged between entities is modified by a malicious vehicle, serious consequences such as traffic congestion and accidents can occur. In addition, sensitive data could be lost, and human lives also could be in danger. Hence, messages sent by vehicles must be authenticated and securely delivered to vehicles in the appropriate regions. In this dissertation, we present a secure and distributed architecture for the vehicular cloud which uses the capabilities of vehicles to provide various services such as parking management, accident alert, traffic updates, cooperative driving, etc. Our architecture ensures the privacy of vehicles and supports secure message dissemination using the vehicular infrastructure. A Low-Overhead Message Authentication and Secure Message Dissemination Scheme for VANETs: Efficient, authenticated message dissemination in VANETs are important for the timely delivery of authentic messages to vehicles in appropriate regions in the VANET. Many of the approaches proposed in the literature use Road Side Units (RSUs) to collect events (such as accidents, weather conditions, etc.) observed by vehicles in its region, authenticate them, and disseminate them to vehicles in appropriate regions. However, as the number of messages received by RSUs increases in the network, the computation and communication overhead for RSUs related to message authentication and dissemination also increases. We address this issue and present a low-overhead message authentication and dissemination scheme in this dissertation. On-Board Hardware Implementation in VANET: Design and Experimental Evaluation: Information collected by On Board Units (OBUs) located in vehicles can help in avoiding congestion, provide useful information to drivers, etc. However, not all drivers on the roads can benefit from OBU implementation because OBU is currently not available in all car models. Therefore, in this dissertation, we designed and built a hardware implementation for OBU that allows the dissemination of messages in VANET. This OBU implementation is simple, efficient, and low-cost. In addition, we present an On-Board hardware implementation of Ad hoc On-Demand Distance Vector (AODV) routing protocol for VANETs. Privacy-preserving approach for collection and dissemination of messages in VANETs: Several existing schemes need to consider safety message collection in areas where the density of vehicles is low and roadside infrastructure is sparse. These areas could also have hazardous road conditions and may have poor connectivity. In this dissertation, we present an improved method for securely collecting and disseminating safety messages in such areas which preserves the privacy of vehicles. We propose installing fixed OBUs along the roadside of dangerous roads (i.e., roads that are likely to have more ice, accidents, etc., but have a low density of vehicles and roadside infrastructure) to help collect data about the surrounding environment. This would help vehicles to be notified about the events on such roads (such as ice, accidents, etc.).Furthermore, to enhance the privacy of vehicles, our scheme allows vehicles to change their pseudo IDs in all traffic conditions. Therefore, regardless of whether the number of vehicles is low in the RSU or Group Leader GL region, it would be hard for an attacker to know the actual number of vehicles in the RSU/GL region

    2023-2024 Boise State University Undergraduate Catalog

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    This catalog is primarily for and directed at students. However, it serves many audiences, such as high school counselors, academic advisors, and the public. In this catalog you will find an overview of Boise State University and information on admission, registration, grades, tuition and fees, financial aid, housing, student services, and other important policies and procedures. However, most of this catalog is devoted to describing the various programs and courses offered at Boise State

    ATR-FTIR Spectroscopy-Linked Chemometrics:A Novel Approach to the Analysis and Control of the Invasive Species Japanese Knotweed

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    Japanese knotweed (Reynoutria japonica), an invasive plant species, causes negative environmental and socio-economic impacts. A female clone in the United Kingdom, its extensive rhizome system enables rapid vegetative spread. Plasticity permits this species to occupy a broad geographic range and survive harsh abiotic conditions. It is notoriously difficult to control with traditional management strategies, which include repetitive herbicide application and costly carbon-intensive rhizome excavation. This problem is complicated by crossbreeding with the closely related species, Giant knotweed (Reynoutria sachalinensis), to give the more vigorous hybrid, Bohemian knotweed (Fallopia x Bohemica) which produces viable seed. These species, hybrids, and backcrosses form a morphologically similar complex known as Japanese knotweed ‘sensu lato’ and are often misidentified. The research herein explores the opportunities offered by advances in the application of attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy-linked chemometrics within plant sciences, for the identification and control of knotweed, to enhance our understanding of knotweed biology, and the potential of this technique. ATR-FTIR spectral profiles of Japanese knotweed leaf material and xylem sap samples, which include important biological absorptions due to lipids, proteins, carbohydrates, and nucleic acids, were used to: identify plants from different growing regions highlighting the plasticity of this clonal species; differentiate between related species and hybrids; and predict key physiological characteristics such as hormone concentrations and root water potential. Technical advances were made for the application of ATR-FTIR spectroscopy to plant science, including definition of the environmental factors that exert the most significant influence on spectral profiles, evaluation of sample preparation techniques, and identification of key wavenumbers for prediction of hormone concentrations and abiotic stress. The presented results cement the position of concatenated mid-infrared spectroscopy and machine learning as a powerful approach for the study of plant biology, extending its reach beyond the field of crop science to demonstrate a potential for the discrimination between and control of invasive plant species

    Blockchain Technology: Disruptor or Enhnancer to the Accounting and Auditing Profession

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    The unique features of blockchain technology (BCT) - peer-to-peer network, distribution ledger, consensus decision-making, transparency, immutability, auditability, and cryptographic security - coupled with the success enjoyed by Bitcoin and other cryptocurrencies have encouraged many to assume that the technology would revolutionise virtually all aspects of business. A growing body of scholarship suggests that BCT would disrupt the accounting and auditing fields by changing accounting practices, disintermediating auditors, and eliminating financial fraud. BCT disrupts audits (Lombard et al.,2021), reduces the role of audit firms (Yermack 2017), undermines accountants' roles with software developers and miners (Fortin & Pimentel 2022); eliminates many management functions, transforms businesses (Tapscott & Tapscott, 2017), facilitates a triple-entry accounting system (Cai, 2021), and prevents fraudulent transactions (Dai, et al., 2017; Rakshit et al., 2022). Despite these speculations, scholars have acknowledged that the application of BCT in the accounting and assurance industry is underexplored and many existing studies are said to lack engagement with practitioners (Dai & Vasarhelyi, 2017; Lombardi et al., 2021; Schmitz & Leoni, 2019). This study empirically explored whether BCT disrupts or enhances accounting and auditing fields. It also explored the relevance of audit in a BCT environment and the effectiveness of the BCT mechanism for fraud prevention and detection. The study further examined which technical skillsets accountants and auditors require in a BCT environment, and explored the incentives, barriers, and unintended consequences of the adoption of BCT in the accounting and auditing professions. The current COVID-19 environment was also investigated in terms of whether the pandemic has improved BCT adoption or not. A qualitative exploratory study used semi-structured interviews to engage practitioners from blockchain start-ups, IT experts, financial analysts, accountants, auditors, academics, organisational leaders, consultants, and editors who understood the technology. With the aid of NVIVO qualitative analysis software, the views of 44 participants from 13 countries: New Zealand, Australia, United States, United Kingdom, Canada, Germany, Italy, Ireland, Hong Kong, India, Pakistan, United Arab Emirates, and South Africa were analysed. The Technological, Organisational, and Environmental (TOE) framework with consequences of innovation context was adopted for this study. This expanded TOE framework was used as the theoretical lens to understand the disruption of BCT and its adoption in the accounting and auditing fields. Four clear patterns emerged. First, BCT is an emerging tool that accountants and auditors use mainly to analyse financial records because technology cannot disintermediate auditors from the financial system. Second, the technology can detect anomalies but cannot prevent financial fraud. Third, BCT has not been adopted by any organisation for financial reporting and accounting purposes, and accountants and auditors do not require new skillsets or an understanding of the BCT programming language to be able to operate in a BCT domain. Fourth, the advent of COVID-19 has not substantially enhanced the adoption of BCT. Additionally, this study highlights the incentives, barriers, and unintended consequences of adopting BCT as financial technology (FinTech). These findings shed light on important questions about BCT disrupting and disintermediating auditors, the extent of adoption in the accounting industry, preventing fraud and anomalies, and underscores the notion that blockchain, as an emerging technology, currently does not appear to be substantially disrupting the accounting and auditing profession. This study makes methodological, theoretical, and practical contributions. At the methodological level, the study adopted the social constructivist-interpretivism paradigm with an exploratory qualitative method to engage and understand BCT as a disruptive innovation in the accounting industry. The engagement with practitioners from diverse fields, professions, and different countries provides a distinctive and innovative contribution to methodological and practical knowledge. At the theoretical level, the findings contribute to the literature by offering an integrated conceptual TOE framework. The framework offers a reference for practitioners, academics and policymakers seeking to appraise comprehensive factors influencing BCT adoption and its likely unintended consequences. The findings suggest that, at present, no organisations are using BCT for financial reporting and accounting systems. This study contributes to practice by highlighting the differences between initial expectations and practical applications of what BCT can do in the accounting and auditing fields. The study could not find any empirical evidence that BCT will disrupt audits, eliminate the roles of auditors in a financial system, and prevent and detect financial fraud. Also, there was no significant evidence that accountants and auditors required higher-level skillsets and an understanding of BCT programming language to be able to use the technology. Future research should consider the implications of an external audit firm as a node in a BCT network on the internal audit functions. It is equally important to critically examine the relevance of including programming languages or codes in the curriculum of undergraduate accounting students. Future research could also empirically evaluate if a BCT-enabled triple-entry system could prevent financial statements and management fraud
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