This full paper addresses the concept of metanarrative in computing and engineering education: the presence of an overarching meta-narrative which provides a sense of integration and some degree of connection and cohe...
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ISBN:
(数字)9798350351507
ISBN:
(纸本)9798350363067
This full paper addresses the concept of metanarrative in computing and engineering education: the presence of an overarching meta-narrative which provides a sense of integration and some degree of connection and coherence to the elements under study. This meta-narrative should firstly provide a mechanism for discussing the fundamental entities under consideration, as well as the relationships between these and other, derived, concepts. Secondly, it should indicate what counts as valid knowledge, as well as legitimate ways of arriving at such knowledge. Thirdly, it should indicate how and where the concept of value arises in the content and practice of the subject. The meta-narrative should therefore provide a vehicle which encompasses the subject ontology, its epistemology and methodology, and its axiology (i.e., its ethics and aesthetics). In other words, the meta-narrative should provide a philosophy of that subject.
In this work, we present our experience on an NSF S-STEM grant that recruited and supported 39 talented and financially needy undergraduate students with potential to succeed in academic pursuits. There were 17 commun...
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ISBN:
(纸本)9781665458429
In this work, we present our experience on an NSF S-STEM grant that recruited and supported 39 talented and financially needy undergraduate students with potential to succeed in academic pursuits. There were 17 community college transfer students and 22 high school seniors recruited altogether. Among them were 11 Hispanic students and 13 female students. Despite the support of the scholarship, seven students could not continue in the program due to insufficient academic performance as they were working extra hours to pay for living expenses. In the Hispanic student group, it is found that their overall GPA went down near the end of the S-STEM program while other groups’ overall GPAs remained unaffected or improved. The female students were found to maintain a higher GPA than that of the male students. The overall GPA of the students recruited from high schools went down, and all the attritions were from the group of the recruits from high schools. In various support services, midterm mentoring was found to be helpful for students at risk and undergraduate research participation was found to be effective in seeking employment in leading industry by some students.
Economic and technological progress in the cloud are the main topics of this article. The essay examines the question of whether or not it makes financial sense to build software in the cloud, vs in-house. This resear...
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Electricity price forecasting plays a vital role inthe strategy decision making for almost all power marketparticipants. This article investigates statistical background andpotential relations between different power ...
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Electricity price forecasting plays a vital role inthe strategy decision making for almost all power marketparticipants. This article investigates statistical background andpotential relations between different power market products (***-ahead prices, intraday prices, etc.). Danish and Croatianpower markets are used for the purpose of the case studyto present the methods used in this article. First, Danish andCroatian power market structures are shortly explained to clarifythe context of the problem. The data collection and preprocessingmethods are described, followed by the core focus of the study:statistical analysis. In addition to the presented histograms ofrespective power market components, we examine interrelationships through statistical analysis, demonstrating significantcorrelations both numerically and graphically. Furthermore,price spreads are investigated as a logical next step of the noticedcorrelations. Our comparative analysis of Danish and Croatianmarket peculiarities reveals three key findings: i) statisticallysignificant relationships between specific market components,ii) distinct behavioral patterns among observed factors, and iii) anopen-access analytical tool with accompanying dataset for futureresearch. Finally, the findings of this article present to marketparticipants an efficient tool to adjust business strategies andincrease profit.
The attention mechanism has become a pivotal component in artificial intelligence, significantly enhancing the performance of deep learning applications. However, its quadratic computational complexity and intricate c...
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The attention mechanism has become a pivotal component in artificial intelligence, significantly enhancing the performance of deep learning applications. However, its quadratic computational complexity and intricate computations lead to substantial inefficiencies when processing long sequences. To address these challenges, we introduce Attar, a resistive random access memory(RRAM)-based in-memory accelerator designed to optimize attention mechanisms through software-hardware co-optimization. Attar leverages efficient Top-k pruning and quantization strategies to exploit the sparsity and redundancy of attention matrices, and incorporates an RRAM-based in-memory softmax engine by harnessing the versatility of the RRAM crossbar. Comprehensive evaluations demonstrate that Attar achieves a performance improvement of up to 4.88× and energy saving of 55.38% over previous computing-in-memory(CIM)-based accelerators across various models and datasets while maintaining comparable accuracy. This work underscores the potential of in-memory computing to enhance the efficiency of attention-based models without compromising their effectiveness.
Quantum circuit fidelity is a crucial metric for assessing the accuracy of quantum computation results and indicating the precision of quantum algorithm execution. The primary methods for assessing quantum circuit fid...
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Quantum circuit fidelity is a crucial metric for assessing the accuracy of quantum computation results and indicating the precision of quantum algorithm execution. The primary methods for assessing quantum circuit fidelity include direct fidelity estimation and mirror circuit fidelity estimation. The former is challenging to implement in practice, while the latter requires substantial classical computational resources and numerous experimental runs. In this paper, we propose a fidelity estimation method based on Layer Interleaved Randomized Benchmarking, which decomposes a complex quantum circuit into multiple sublayers. By independently evaluating the fidelity of each layer, one can comprehensively assess the performance of the entire quantum circuit. This layered evaluation strategy not only enhances accuracy but also effectively identifies and analyzes errors in specific quantum gates or qubits through independent layer evaluation. Simulation results demonstrate that the proposed method improves circuit fidelity by an average of 6.8% and 4.1% compared to Layer Randomized Benchmarking and Interleaved Randomized Benchmarking methods in a thermal relaxation noise environment, and by 40% compared to Layer RB in a bit-flip noise environment. Moreover, the method detects preset faulty quantum gates in circuits generated by the Munich Quantum Toolkit Benchmark, verifying the model’s validity and providing a new tool for faulty gate detection in quantum circuits.
The intricate sulfur redox chemistry involves multiple electron transfers and complicated phase *** have been previously explored to overcome the kinetic barrier in lithium-sulfur batteries(LSBs).This work contributes...
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The intricate sulfur redox chemistry involves multiple electron transfers and complicated phase *** have been previously explored to overcome the kinetic barrier in lithium-sulfur batteries(LSBs).This work contributes to closing the knowledge gap and examines electrocatalysis for enhancing LSB *** a strong chemical affinity for polysulfides,the electrocatalyst enables efficient adsorption and accelerated electron transfer *** cells with catalyzed cathodes exhibit improved rate capability and excellent stability over 500 cycles with 91.9%capacity retention at C/*** addition,cells were shown to perform at high rates up to 2C and at high sulfur loadings up to 6 mg cm^(-2).Various electrochemical,spectroscopic,and microscopic analyses provide insights into the mechanism for retaining high activity,coulombic efficiency,and *** work delves into crucial processes identifying pivotal reaction steps during the cycling process at commercially relevant areal capacities and rates.
This paper deals with reduction of losses in electric power distribution system through a dynamic reconfiguration case study of a grid in the city of Mostar,Bosnia and *** proposed solution is based on a nonlinear mod...
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This paper deals with reduction of losses in electric power distribution system through a dynamic reconfiguration case study of a grid in the city of Mostar,Bosnia and *** proposed solution is based on a nonlinear model predictive control algorithm which determines the optimal switching operations of the distribution *** goal of the control algorithm is to find the optimal radial network topology which minimizes cumulative active power losses and maximizes voltages across the network while simultaneously satisfying all system *** optimization results are validated through multiple simulations(using real power demand data collected for a few characteristic days during winter and summer)which demonstrate the efficiency and usefulness of the developed control algorithm in reducing the grid losses by up to 14%.
The massive integration of communication and information technology with the large-scale power grid has enhanced the efficiency, safety, and economical operation of cyber-physical systems. However, the open and divers...
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The massive integration of communication and information technology with the large-scale power grid has enhanced the efficiency, safety, and economical operation of cyber-physical systems. However, the open and diversified communication environment of the smart grid is exposed to cyber-attacks. Data integrity attacks that can bypass conventional security techniques have been considered critical threats to the operation of the grid. Current detection techniques cannot learn the dynamic and heterogeneous characteristics of the smart grid and are unable to deal with non-euclidean data types. To address the issue, we propose a novel Deep-Q-Network scheme empowered with a graph convolutional network (GCN) framework to detect data integrity attacks in cyber-physical systems. The simulation results show that the proposed framework is scalable and achieves higher detection accuracy, unlike other benchmark techniques.
As a result of its aggressive nature and late identification at advanced stages, lung cancer is one of the leading causes of cancer-related deaths. Lung cancer early diagnosis is a serious and difficult challenge that...
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