Quantum computing is an emerging and promising technology that has overwhelming quantum advantages compared to its classical counterparts. Unit commitment (UC) is a critical issue in the power system, and it becomes m...
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Quantum computing is an emerging and promising technology that has overwhelming quantum advantages compared to its classical counterparts. Unit commitment (UC) is a critical issue in the power system, and it becomes more challenging with the integration of intermittent renewable energy. Therefore, this paper proposes an innovative decomposition and coordination optimization framework to accelerate the solution of UC, in which the interaction between an adiabatic quantum computer and a classical computer is designed to harness the immense computational power of quantum computers effectively. First, decomposition methods considering the requirements of quantum computers are introduced to decompose UC into smallscale models. Then, the paper presents a quadratic unconstrained binary optimization modeling method to transform UC problems into the form of quantum computing. Furthermore, due to the limitations of quantum computing resources, a reductive variable technique is proposed to reduce the number of slack variables in the optimization model and ensure that it remains feasible for quantum computers. Case studies conducted in test systems with a quantum annealing simulator and a real quantum annealing computer illustrate the feasibility and effectiveness of the method and demonstrate its potential in the era of quantum computing.
Application programming Interface (API) plays a vital role in Cloud computing. Improving API usability will help application programmers select and adapt the most suitable APIs for their specific needs. By adopting a ...
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ISBN:
(纸本)9783031762727;9783031762734
Application programming Interface (API) plays a vital role in Cloud computing. Improving API usability will help application programmers select and adapt the most suitable APIs for their specific needs. By adopting a general framework for usability measurement and analyzing questions and answers on Stack Overflow for YouTube APIs, we define three direct usability metrics: "team response time" to quantify learnability, "net upvote" to measure user satisfaction, and "downvote" to reflect usability problems. In addition, we identify six environmental factors that influence API usability by analyzing the question tags: language, library, browser, operating system, integrated development environment, and device. Our measurement and analysis provide an objective assessment of API usability and its environmental influencing factors.
The expanding hardware diversity in high performance computing adds enormous complexity to scientific software development. Developers who aim to write maintainable software have two options: 1) To use a so-called dat...
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ISBN:
(纸本)9783031506833;9783031506840
The expanding hardware diversity in high performance computing adds enormous complexity to scientific software development. Developers who aim to write maintainable software have two options: 1) To use a so-called data locality abstraction that handles portability internally, thereby, performance-productivity becomes a trade off. Such abstractions usually come in the form of libraries, domain-specific languages, and run-time systems. 2) To use generic programming where performance, productivity and portability are subject to software design. In the direction of the second, this work describes a design approach that allows the integration of low-level and verbose programming tools into high-level generic algorithms based on template meta-programming in C++. This enables the development of performance-portable applications targeting host-device computer architectures, such as CPUs and GPUs. With a suitable design in place, the extensibility of generic algorithms to new hardware becomes a well defined procedure that can be developed in isolation from other parts of the code. That allows scientific software to be maintainable and efficient in a period of diversifying hardware in HPC. As proof of concept, a finite-difference modelling algorithm for the acoustic wave equation is developed and benchmarked using roofline model analysis on Intel Xeon Gold 6248 CPU, Nvidia Tesla V100 GPU, and AMD MI100 GPU.
This paper presents a method for an efficient programming language identification technique which consists of selection of target categories and machine learning for unknown category. As software development scales ar...
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The Internet of Things (IoT) is a constantly expanding system connecting countless devices for seamless data collection and exchange. This has transformed decision-making with data-driven insights across different dom...
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The integration of generative AI tools into education has the potential to revolutionize learning experiences, particularly in computerscience. This paper explores the adoption and utilization of generative AI tools ...
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ISBN:
(纸本)9798400717819
The integration of generative AI tools into education has the potential to revolutionize learning experiences, particularly in computerscience. This paper explores the adoption and utilization of generative AI tools among computerscience students at the University of Applied sciences Campus Vienna in Austria through a comprehensive survey. The study aims to understand the extent to which AI tools like ChatGPT are integrated into students' academic routines, their perceptions of these tools, and the challenges and opportunities they present. The survey results indicate a high level of acceptance and frequent use of AI tools for tasks such as programming, exam preparation, and generating simplified explanations. However, concerns about the accuracy of AI-generated content and the potential impact on critical thinking skills were also highlighted. The findings underscore the need for clear institutional guidelines and ethical considerations in the use of AI tools in education. This paper contributes to the growing body of literature on AI in education and provides insights for educators and policymakers to enhance the responsible integration of AI technologies in computerscience curricula.
The premise for the development of the Advanced Placement (AP) computerscience Principles course was aimed at broadening participation in computing, as a high school level CS course. Since AP courses carry credibilit...
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ISBN:
(纸本)9798400706264
The premise for the development of the Advanced Placement (AP) computerscience Principles course was aimed at broadening participation in computing, as a high school level CS course. Since AP courses carry credibility with millions of students who take AP Exams as they are recognized with prospects of obtaining a college education, the hope was that the AP CS Principles course would lead to increased participation in AP CS Exams, especially with students historically excluded in CS including girls, Black, Hispanic, and Native American students, as well those with disabilities. The course raises opportunities and access to CS in higher education. The AP CS Principles curriculum framework is used in the development of the Exam which is significant in the creation college credit and placement policies. Nearly 1,300 colleges and universities have created policies providing students with opportunities to receive college credit or placement for scoring a 3 or higher on the AP CS Principles Exam [12]. The AP CS Principles curriculum framework is also used to define the learning outcomes for the course and stands as a pivotal tool in shaping high school CS education pathways to post-secondary introductory CS courses: It was designed to meet rigorous content requirements of an innovative first semester college-level introductory CS course. It exposes students to demanding expectations of building high levels of computational thinking skills and practical applications of programming that are valuable as they advance in their academics. It provides opportunities for students to connect fundamental programming concepts with important topics such as understanding the role of data in programming, and how data is processed and analyzed. AP CS Principles also recognizes the societal impacts of technology and teaches students about ethical considerations that may arise when analyzing bias in technological systems so that students develop a well-rounded perspective on technology's r
In recent years, load monitoring and analysis have played an increasingly important role in power system dispatch management. Although event-based non-intrusive load monitoring methods have made some progress in theor...
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ISBN:
(纸本)9798350386783;9798350386776
In recent years, load monitoring and analysis have played an increasingly important role in power system dispatch management. Although event-based non-intrusive load monitoring methods have made some progress in theory and practice, the increasing diversification and complexity of equipment types require enhanced recognition accuracy of existing methods. It is challenging to capture the power usage behavior of multi-state appliances. In this paper, a load matching method based on mixed-integer programming is proposed to assist in correcting the event detection identification results. This method involves constructing a matching matrix and solving it by considering event matching constraints, power matching constraints, and the number of matches constraints. The goal is to minimize the power error and the penalty terms associated with the number of matches constraints. Through arithmetic analysis of 546 real data in the public dataset PLAID, the method achieves an accuracy of 92.13%. This validates the effectiveness of mixed-integer programming modeling and demonstrates its potential as a supplementary tool for improving load identification results.
Recently,we demonstrated the success of a time-synchronized state estimator using deep neural networks(DNNs)for real-time unobservable distribution *** this paper,we provide analytical bounds on the performance of the...
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Recently,we demonstrated the success of a time-synchronized state estimator using deep neural networks(DNNs)for real-time unobservable distribution *** this paper,we provide analytical bounds on the performance of the state estimator as a function of perturbations in the input *** has already been shown that evaluating performance based only on the test dataset might not effectively indicate the ability of a trained DNN to handle input *** such,we analytically verify the robustness and trustworthiness of DNNs to input perturbations by treating them as mixed-integer linear programming(MILP)*** ability of batch normalization in addressing the scalability limitations of the MILP formulation is also *** framework is validated by performing time-synchronized distribution system state estimation for a modified IEEE 34-node system and a real-world large distribution system,both of which are incompletely observed by micro-phasor measurement units.
Despite the rapid growth of the ICT sector, there is a gap between it and STEM education, resulting in high dropout rates in computerscience and engineering programs. This has led to many vacancies in the ICT job mar...
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