This study aims to involve students in Technopreneurship courses by utilizing the emarketplace as a marketing, sales and service medium for Micro, Small and Medium Enterprises (MSMEs). Where previously the lecture mat...
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Data integration and exchange are becoming more crucial with the increasing amount of distributed systems and ever-growing amounts of data. This need is also widely known in medical research and not yet comprehensivel...
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As use of data driven technologies spreads, software engineers are more often faced with the task of solving a business problem using data-driven methods such as machine learning (ML) algorithms. Deployment of ML with...
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ISBN:
(纸本)9781665452069
As use of data driven technologies spreads, software engineers are more often faced with the task of solving a business problem using data-driven methods such as machine learning (ML) algorithms. Deployment of ML within large software systems brings new challenges that are not addressed by standard engineering practices and as a result businesses observe high rate of ML deployment project failures. Data Oriented Architecture (DOA) is an emerging approach that can support data scientists and software developers when addressing such challenges. However, there is a lack of clarity about how DOA systems should be implemented in practice. This paper proposes to consider Flow-Based Programming (FBP) as a paradigm for creating DOA applications. We empirically evaluate FBP in the context of ML deployment on four applications that represent typical data science projects. We use Service Oriented Architecture (SOA) as a baseline for comparison. Evaluation is done with respect to different application domains, ML deployment stages, and code quality metrics. Results reveal that FBP is a suitable paradigm for data collection and data science tasks, and is able to simplify data collection and discovery when compared with SOA. We discuss the advantages of FBP as well as the gaps that need to be addressed to increase FBP adoption as a standard design paradigm for DOA. CCS CONCEPTS • Software and its engineering → Software design tradeoffs; • Computing methodologies → Machine learning.
Efficient machine learning techniques that need substantial equipment and power usage in its computation phase are computational models. stochastic computation has indeed been added and the solution a compromise betwe...
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The proceedings contain 25 papers. The special focus in this conference is on theory and practice of algorithms in (computer) systems. The topics include: A comparison of three algorithms for approximating the distanc...
ISBN:
(纸本)9783642197536
The proceedings contain 25 papers. The special focus in this conference is on theory and practice of algorithms in (computer) systems. The topics include: A comparison of three algorithms for approximating the distance distribution in real-world graphs;exploiting bounded signal flow for graph orientation based on cause–effect Pairs;on greedy and submodular matrices;MIP formulations for flowshop scheduling with limited buffers;a scenario-based approach for robust linear optimization;conflict propagation and component recursion for canonical labeling;3-hitting set on bounded degree hypergraphs: Upper and lower bounds on the kernel size;improved taxation rate for bin packing games;multi-channel assignment for communication in radio networks;managing power heterogeneity;computing strongly connected components in the streaming model;improved approximation algorithms for the max-edge coloring problem;new bounds for old algorithms: On the average-case behavior of classic single-source shortest-paths approaches;an approximative criterion for the potential of energetic reasoning;speed scaling for energy and performance with instantaneous parallelism;algorithms for scheduling with power control in wireless networks;the mathematics of mobility;speed scaling to manage temperature;alternative route graphs in road networks;robust line planning in case of multiple pools and disruptions;exact algorithms for intervalizing colored graphs;l(2,1)-labeling of unigraphs;energy-efficient due date scheduling.
Context-free path queries (CFPQ) extend the regular path queries (RPQ) by allowing context-free grammars to be used as constraints for paths. algorithms for CFPQ are actively developed, but J. Kuijpers et al. have rec...
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ISBN:
(纸本)9783030548315;9783030548322
Context-free path queries (CFPQ) extend the regular path queries (RPQ) by allowing context-free grammars to be used as constraints for paths. algorithms for CFPQ are actively developed, but J. Kuijpers et al. have recently concluded, that existing algorithms are not performant enough to be used in real-world applications. Thus the development of new algorithms for CFPQ is justified. In this paper, we provide a new CFPQ algorithm which is based on such linear algebra operations as Kronecker product and transitive closure and handles grammars presented as recursive state machines. Thus, the proposed algorithm can be implemented by using high-performance libraries and modern parallel hardware. Moreover, it avoids grammar growth which provides the possibility for queries optimization.
Introduction to computer Science is an introductory course for undergraduates majoring in computer science and technology, which plays an important role in the disciplinary teaching system. Using a mixed teaching meth...
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Object detection plays an important role in intelligent transportation systems, especially due to the rise of autonomous vehicles and smart traffic management. Although object detection techniques in traffic scenes ha...
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Object detection plays an important role in intelligent transportation systems, especially due to the rise of autonomous vehicles and smart traffic management. Although object detection techniques in traffic scenes have been studied for decades, it is still challenging in addressing long-tail problems under complex and extreme conditions. In this paper, we first introduce long-tail problems in object detection for intelligent transportation systems and investigate the usage of cross-domain approaches, which are widely leveraged in dealing with these problems. Then we describe a general parallel theory based framework for enhancing the effectiveness of computer vision tasks in complex scenes. Combining ACP methodology with cross-domain object detection, we propose a novel architecture to perform long-tail problems concerned object detection by simulating the real transportation scenes with rare situations. Artificial system is constructed to simulate and represent longtail situations, making it possible to collect and annotate specific and available diversified datasets. Computational experiments are built on Graph Convolutional Network (GCN) based cross-domain detection method to learn and evaluate vision models from limited real samples, then improve the performance of detection tasks in both artificial and real systems. Parallel execution can be used to optimize the whole architecture and supports the proposed work to be a routine practice of visual computing for intelligent transportation systems.
The rapid development of the Internet of Things (IoT) technologies has increased the number of connected devices with constrained resources. Therefore, there is an urgent need to develop secure, lightweight cryptograp...
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Saudi Arabia is experiencing depleting water level which ultimately leading to having reduced level of weed and crops farms. The ongoing practice of watering for all kind of weeds at farms is manual which is laborious...
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ISBN:
(纸本)9781665430418
Saudi Arabia is experiencing depleting water level which ultimately leading to having reduced level of weed and crops farms. The ongoing practice of watering for all kind of weeds at farms is manual which is laborious and slow besides waste of unregulated use of water. Therefore, there arises the need of automated water control, making the automated watering system as the viable option for precision weed control system. This paper has presented the development of real-time automated water sprinkle system for the target weeding area. The technique of wavelet frequency is developed as a software interface using MATLAB program detecting need of water sprinkling from the pictures of the leaves obtained. Software-based results are applied to hardware for real-time grass detection and classification based on shape and density due to reason that the leaves may be wide open, shrunk and leaves those with curved in features. The real-time system is capable of thus deciding the proportionate amount of water needed to be sprinkled over the weeds using a purposely developed hardware system. The system can detect areas where more, more or less water is needed, through a high-accuracy connected camera.
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