The growing competition in the job market calls for a more in-depth comprehension of the factors that affect successful internship and job placement results in computer science education. This study provides a thoroug...
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In this paper, we introduce a nonparametric end-to-end method for probabilistic forecasting of distributed renewable generation outputs while including missing data imputation. Firstly, we employ a nonparametric proba...
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In a distributed system, job submission is permitted on any autonomous node, leading to varying rates of job arrival across nodes. The heterogeneous computational capacities of these autonomous systems can result in o...
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The proceedings contain 21 papers. The topics discussed include: effects of imperfections on quantum algorithms: a software engineering perspective;QIn: enabling formal methods to deal with quantum circuits;a testing ...
ISBN:
(纸本)9798350304794
The proceedings contain 21 papers. The topics discussed include: effects of imperfections on quantum algorithms: a software engineering perspective;QIn: enabling formal methods to deal with quantum circuits;a testing pipeline for quantum computing applications;LAWS: look around and warm-start natural gradient descent for quantum neural networks;parallelizing quantum simulation with decision diagrams;middleware for quantum: an orchestration of hybrid quantum-classical systems;agile practices for quantum software development: practitioners’ perspectives;iQuantum: a case for modeling and simulation of quantum computing environments;and effects of imperfections on quantum algorithms: a software engineering perspective.
Intelligent Transportation systems (ITS) are crucial for regulating public transportation, enhancing security, and addressing urban challenges. ITS offers smart guidance to mitigate traffic congestion, minimize enviro...
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6G networks will be massive, provide the ultimate experience, and applicable to diversified scenarios, achieving ubiquitous connections for all scenarios. Research needs to be car-ried out on the 6G network architectu...
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distributed control systems transform with the Industry 4.0 paradigm shift. A mesh-like, network-centric topology replaces the traditional controller-centered architecture, enforcing the interest of cloud-, fog-, and ...
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Alpine skiing is a popular winter sport, and several systems have been proposed to enhance training and improve efficiency. However, many existing systems rely on simulation-based environments, which suffer from drawb...
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ISBN:
(纸本)9798350374025;9798350374032
Alpine skiing is a popular winter sport, and several systems have been proposed to enhance training and improve efficiency. However, many existing systems rely on simulation-based environments, which suffer from drawbacks such as a gap between real skiing and the lack of body ownership. To address these limitations, we present ARpenSki, a novel augmented reality (AR) ski training system that employs a see-through head mounted display (HMD) to deliver augmented visual training cues that may be applied on real slopes. The proposed AR system provides a transparent view of the lower half of the field of vision, where we implemented three different AR-based direct and indirect postural visualization methods. We conducted an user study to investigate the influence of different visual cues in the AR environment. Our results indicate that a simple AR visualization of the user's spine (Figure 1.2) yields the most favorable training performance, surpassing conventional visualizations by 7% improvement in the user's posture. Building upon these promising findings, we further tested our system on real slopes and showed the potential of a real AR skiing application.
Reducing the energy consumption of the global IT industry requires one to understand and optimize the large software infrastructures the modern data economy relies on. Among them are the data stream processing systems...
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ISBN:
(纸本)9798350343946
Reducing the energy consumption of the global IT industry requires one to understand and optimize the large software infrastructures the modern data economy relies on. Among them are the data stream processing systems that are deployed in cloud data centers by companies, such as Twitter, to process billion of events per day in real time. However, studying the energy consumption of such infrastructures is difficult because they rely on a complex virtualized software ecosystem where attributing energy consumption to individual software components is a challenge, and because the space of possible configurations is large. We present GreenFlow, a principled methodology and tool designed to automate the deployment of energy measurement experiments for data stream processing systems in cloud environments. GreenFlow is designed to deliver reproducible results while remaining flexible enough to support a wide range of experiments. We illustrate its usage and show in particular that consolidating a DSP system in the smallest number of servers that are capable of processing it is an effective way to reduce energy consumption.
Edge computing, a distributedcomputing concept, brings data processing and storage closer to endpoints or edge devices. Caching methods are crucial in edge computing environments for optimizing performance and minimi...
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