Deep neural networks are typically computationally expensive, thus, there is a strong motivation to develop less intensive models while maintaining performance. Distilling knowledge from a teacher network to a lightwe...
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Among the renewable energy conversion techniques, photovoltaic (PV) energy conversion is attractive due to its lifetime, less maintenance and easy conversion. PV technology directly converts sunlight into dc electrici...
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The important necessity for a severity grading system in conjunction with precise and effective identification of PCOS disease is addressed by this study. Using machine learning methods, we examine a large dataset tha...
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Positive tests (aka, happy path tests) cover the expected behavior of the program, while negative tests (aka, unhappy path tests) check the unexpected behavior. Ideally, test suites should have both positive and negat...
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ISBN:
(纸本)9798400706585
Positive tests (aka, happy path tests) cover the expected behavior of the program, while negative tests (aka, unhappy path tests) check the unexpected behavior. Ideally, test suites should have both positive and negative tests to better protect against regressions. In practice, unfortunately, we cannot easily identify whether a test is positive or negative. A better understanding of whether a test suite is more positive or negative is fundamental to assessing the overall test suite capability in testing expected and unexpected behaviors. In this paper, we propose test polarity, an automated approach to detect positive and negative tests. Our approach runs/monitors the test suite and collects runtime data about the application execution to classify the test methods as positive or negative. In a first evaluation, test polarity correctly classified 117 tests as as positive or negative. Finally, we provide a preliminary empirical study to analyze the test polarity of 2,054 test methods from 12 real-world test suites of the Python Standard Library. We find that most of the analyzed test methods are negative (88%) and a minority is positive (12%). However, there is a large variation per project: while some libraries have an equivalent number of positive and negative tests, others have mostly negative ones.
To ensure the stability of power grids, numerous load forecasting methods have continuously evolved. However, due to variations in factors like algorithm generalization capabilities and model complexity, their effecti...
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Although studies emphasized the effectiveness of analyzing data-flow coverage as opposed to branch coverage in the area of testing, there is still a lack of appropriate tools. We propose an approach to visualize data ...
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ISBN:
(纸本)9789897586477
Although studies emphasized the effectiveness of analyzing data-flow coverage as opposed to branch coverage in the area of testing, there is still a lack of appropriate tools. We propose an approach to visualize data flows of programs within code editors based on the Language Server Protocol (LSP). For this purpose, we define extensions of the LSP to increase usability in the given application. Furthermore, we present a prototype with implementations of a language server as well as the two language clients IntelliJ IDEA and Visual Studio Code. Moreover, we outline how the different components can interact effectively based on the LSP to enable the analysis and visualization of data-flows. We evaluate our prototype based on various benchmarks.
In software-Defined Networking (SDN), the positioning of controllers and the division of switches determine the upper limit of the network's responsiveness to network events. However, highly dynamic satellite netw...
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ISBN:
(纸本)9798350374377
In software-Defined Networking (SDN), the positioning of controllers and the division of switches determine the upper limit of the network's responsiveness to network events. However, highly dynamic satellite networks pose a significant challenge to the controller placement problem. The difficulty is to achieve efficient control over a long period of time with low overhead. Existing methods mostly perform computations independently and greedily in each time slot, leading to frequent changes in the controller placement and the control relationships between controllers and switches. In this paper, we present a comprehensive model to measure the control plane overhead. By defining migration overhead and anticipated overhead to ensure the continuity of control strategies, we formulate the controller placement problem in software-Defined Low Earth Orbit (LEO) satellite networks as an optimization problem. To tackle this issue, we draw inspiration from hierarchical clustering techniques and introduce a heuristic algorithm named Hierarchical Clustering-based Minimizing Overhead Algorithm (HCMOA). Evaluations of our simulation system show that HCMOA significantly outperforms relevant approaches in terms of control overhead and average response latency.
In this paper, we examine Crypto Jacking which is the significant threat to the world and how this threat is handled by the advanced technologies like Artificial Intelligence. Cryptocurrencies are based on blockchain,...
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With the freeze of 3GPP Release 15 protocols, the world has entered the 5G commercial era. In recent years, major communication companies and organizations have set up project groups for IMT-2030 to put forward propos...
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This paper introduces a low-cost, adaptable, and open-source system architecture for monitoring nutrient solution in hydroponic farming, specifically designed for small-scale farmers. The proposed architecture emphasi...
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