1,462 research outputs found

    Undergraduate Catalog of Studies, 2023-2024

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    Graduate Catalog of Studies, 2023-2024

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    Undergraduate Catalog of Studies, 2023-2024

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    Graduate Catalog of Studies, 2023-2024

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    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Undergraduate Catalog of Studies, 2022-2023

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    Multi-objective resource optimization in space-aerial-ground-sea integrated networks

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    Space-air-ground-sea integrated (SAGSI) networks are envisioned to connect satellite, aerial, ground, and sea networks to provide connectivity everywhere and all the time in sixth-generation (6G) networks. However, the success of SAGSI networks is constrained by several challenges including resource optimization when the users have diverse requirements and applications. We present a comprehensive review of SAGSI networks from a resource optimization perspective. We discuss use case scenarios and possible applications of SAGSI networks. The resource optimization discussion considers the challenges associated with SAGSI networks. In our review, we categorized resource optimization techniques based on throughput and capacity maximization, delay minimization, energy consumption, task offloading, task scheduling, resource allocation or utilization, network operation cost, outage probability, and the average age of information, joint optimization (data rate difference, storage or caching, CPU cycle frequency), the overall performance of network and performance degradation, software-defined networking, and intelligent surveillance and relay communication. We then formulate a mathematical framework for maximizing energy efficiency, resource utilization, and user association. We optimize user association while satisfying the constraints of transmit power, data rate, and user association with priority. The binary decision variable is used to associate users with system resources. Since the decision variable is binary and constraints are linear, the formulated problem is a binary linear programming problem. Based on our formulated framework, we simulate and analyze the performance of three different algorithms (branch and bound algorithm, interior point method, and barrier simplex algorithm) and compare the results. Simulation results show that the branch and bound algorithm shows the best results, so this is our benchmark algorithm. The complexity of branch and bound increases exponentially as the number of users and stations increases in the SAGSI network. We got comparable results for the interior point method and barrier simplex algorithm to the benchmark algorithm with low complexity. Finally, we discuss future research directions and challenges of resource optimization in SAGSI networks

    Building Energy Modeling and Studies of Electric Power Distribution Systems with Distributed Energy Resources

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    There is significant opportunity for savings in energy and investment from improved performance of electric Power Distribution Systems (PDSs) through optimal planning and operation of conventional voltage-controlling devices. Novel multi-step model conversion and optimal capacitor planning (OCP) procedures are proposed for large-scale utility PDSs and are exemplified with an existing utility circuit of approximately 4,000 buses. Simulated optimal control and operation is achieved with a cluster-based approach that utilizes load-forecasting to minimize equipment degradation by intelligently dispersing device setting adjustments over time such that they remain most applicable. Improved performance may also be achieved through smart building technologies and Virtual Power Plant (VPP) control of increasingly more prevalent Distributed Energy Resources (DERs). The established simulation test bed for PDSs incorporates DERs to evaluate VPP implementations and an optimization process for control timing is proposed that minimizes targeted peak power and possible resulting increase in total daily energy. The advanced VPP controls incorporate the Consumer Technology Association (CTA) 2045 standard and EnergyStar performance characterizations to leverage HVAC systems as Generalized Energy Storage (GES) for load manipulation and to support the integration of demand-side generating DERs, such as local solar Photo-Voltaic (PV) systems

    Critical success factors for implementing blockchain technology in construction

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    In recent years, blockchain technology has attracted momentous attention in the construction industry. However, a state-of-the-art review of critical success factors (CSFs) for implementing blockchain technology in the construction industry is unexplored. In addition, there is no stage framework or a common set of CSFs for blockchain technology in the extant literature. Therefore, this review study aims to develop a stage framework and identify a common set of CSFs for successful blockchain technology implementation by analyzing published articles related to the studied domain. This review study adopted a systematic literature review and a science mapping approach to objectively identify a common set of CSFs, research gaps, and future research directions. Focusing on 78 journal articles retrieved from the Scopus database, influential journals, keywords, countries/regions, and documents in the domain of CSFs for blockchain technology in construction were analyzed. The results revealed that countries like China, USA, UK, and Australia have made the most contributions to this domain. Of the 22 CSFs, five main common sets for blockchain technology were (1) decentralized system (protocol), (2) transparency in data information for construction lifecycle processes, (3) ensuring data immutability, (4) increasing data security and reliability, and (5) providing full traceability of prefabrication. In the stage framework of CSFs for blockchain technology, some CSFs play an essential role throughout the entire construction life cycle processes (e.g., CSF#1 decentralized system and CSF#2 transparency in data information for construction life cycle processes). Four key research gaps and future research directions are proposed. They include (1) digital innovation, (2) smart contracts and information management, (3) intelligent construction, and (4) data analytics methods and techniques. Overall, the findings and checklist of CSFs for blockchain technology would be beneficial for successful exploration and practice in this field
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