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关键词： Task analysis   Resource management   Technological innovation   Computational modeling   Big Data   Service computing   Computer science  

摘要： Presents corrections to author information for the above named paper.

关键词： “互联网+”   计算机科学技术   发展   趋势  

摘要： 随着社会经济的不断发展,众多行业领域对计算机的需求也不断攀升,由此促进了计算机产业技术的长足发展,其俨然成为人们生产生活中必不可少的一部分。近年来计算机领域涌现出大量的新型计算机科学技术,诸如互联网、大数据以及物联网等,以此重要反映了未来经济发展可能会以信息产业为主导。文章首先阐述了“互联网+”的内涵,其次介绍了“互联网+”下计算机科学技术的发展特征,以及“互联网+”下计算机科学技术的实际应用,最后探讨了“互联网+”下计算机科学技术的发展趋势,以期为相关人员研究提供一些借鉴。

关键词： 乌鳢   生态净养养殖   营养成分   氨基酸   质构特征   感官评价  

摘要： 目的为了比较生态净养和传统养殖的乌鳢营养品质。方法测定生态净养和传统池塘养殖2组乌鳢肌肉中蛋白质、脂肪、矿物质和氨基酸等营养成分,并通过生物特性、感官评价、风味物质测定比较其品质和营养价值。结果生态净养组肥满度(P<0.05)、水分、粗脂肪(P<0.01)、Fe、Cu、Zn、P等矿物元素均高于传统池塘组;2组均检测出17种氨基酸,生态净养组的必需氨基酸、鲜味氨基酸含量普遍高于传统池塘组;在穿刺模式下,生态净养组的硬度、弹性、破裂强度均高于传统池塘组,差异极显著(P<0.01);触碰模式中,生态净养组的硬度、咀嚼性、回复性高于传统池塘组,差异显著(P<0.05);生态净养组的挥发性气味物质与五点快感评价法也总体高于传统池塘组。结论生态净养组品质特性更佳,更符合消费者的需求,有良好市场前景。

关键词： Sensors   Indexes   Uncertainty   Data mining   Computational complexity   Computer science   Batteries   Imputation   multivariate   pattern mining  

摘要： Noise and missing data are intrinsic characteristics of real-world data, leading to uncertainty that negatively affects the quality of knowledge extracted from the data. The burden imposed by missing data is often severe in sensors that collect data from the physical world, where large gaps of missing data may occur when the system is temporarily off or disconnected. How can we reconstruct missing data for these periods? We introduce an accurate and efficient algorithm for missing data reconstruction (imputation), that is specifically designed to recover off-period segments of missing data. This algorithm, Ghost, searches the sequential dataset to find data segments that have a prior and posterior segment that matches those of the missing data. If there is a similar segment that also satisfies the constraint - such as location or time of day - then it is substituted for the missing data. A baseline approach results in quadratic computational complexity, therefore we introduce a caching approach that reduces the search space and improves the computational complexity to linear in the common case. Experimental evaluations on five real-world datasets show that our algorithm significantly outperforms four state-of-the-art algorithms with an average of 18 percent higher F-score.

关键词： Heuristic algorithms   Perturbation methods   Controllability   Biological systems   Computer science   Biological system modeling   Boolean networks   attractors   network control   decomposition  

摘要： We study the problem of computing a minimal subset of nodes of a given asynchronous Boolean network that need to be perturbed in a single-step to drive its dynamics from an initial state to a target steady state (or attractor), which we call the source-target control of Boolean networks. Due to the phenomenon of state-space explosion, a simple global approach that performs computations on the entire network may not scale well for large networks. We believe that efficient algorithms for such networks must exploit the structure of the networks together with their dynamics. Taking this view, we derive a decomposition-based solution to the minimal source-target control problem which can be significantly faster than the existing approaches on large networks. We then show that the solution can be further optimized if we take into account appropriate information about the source state. We apply our solutions to both real-life biological networks and randomly generated networks, demonstrating the efficiency and efficacy of our approach.

关键词： Special Issues And Sections   Data Visualization   Computer Science   Information Technology   Data Analysis  

摘要： The articles in this special section focus on data physicalization. The practice of representing data in physical form has existed for thousands of years, yet it has only become an area of investigation and exploration for scientists, designers, and artists much more recently.3 Advances in areas such as digital fabrication, actuated tangible interfaces, and shape-changing displays have spurred an emerging area of research now called Data Physicalization.1 This Special Issue of IEEE Computer Graphics and Applications presents four articles spanning a wide breadth of current data physicalization research, from theory to practice.

关键词： change   leadership   pharmacy   transformation  

关键词： 计算机科学与技术   应用现状   发展趋势  

摘要： 随着科学技术的不断进步,人类社会发生了天翻地覆的变化,各种新型工具层出不穷,其中对人类影响最大的莫过于计算机科学与技术的发明。自计算机技术发明以来,就以极高的普适性与改造性融入了各行各业,给各个行业带来无限的变革机会,同时也深入了人们生活的方方面面。计算机技术的应用给人类带来无限便利的同时,也极高地提高了人们生产工作的效率。而计算机技术自发明以来,也一直处于不断的升级与改造之中,未来计算机技术的发展必将给人类生活带来更大的帮助。因此文章从计算机科学与技术的应用现状出发,阐述了计算机技术能够快速应用发展的原因,分析了计算机科学与技术的未来发展方向,并对其外来的发展趋势进行预测,以期能够抓住时代发展的潮流与方向,紧跟时代的脚步,让计算机科学与技术更好地造福国民。

关键词： Trajectory   Query processing   Indexes   Measurement   Roads   Computer science   Compression algorithms   Reference trajectory   spatio-temporal trajectory   compression  

摘要： The pervasiveness of GPS-enabled devices and wireless communication technologies results in massive trajectory data, incurring expensive cost for storage, transmission, and query processing. To relieve this problem, in this paper we propose a novel framework for compressing trajectory data, REST (Reference-based Spatio-temporal trajectory compression), by which a raw trajectory is represented by concatenation of a series of historical (sub-)trajectories (called reference trajectories) that form the compressed trajectory within a given spatio-temporal deviation threshold. In order to construct a reference trajectory set that can most benefit the subsequent compression, we propose three kinds of techniques to select reference trajectories wisely from a large dataset such that the resulting reference set is more compact yet covering most footprints of trajectories in the area of interest. To address the computational issue caused by the large number of combinations of reference trajectories that may exist for resembling a given trajectory, we propose efficient greedy algorithms that run in the blink of an eye and dynamic programming algorithms that can achieve the optimal compression ratio. Compared to existing work on trajectory compression, our framework has few assumptions about data such as moving within a road network or moving with constant direction and speed, and better compression performance with fairly small spatio-temporal loss. In addition, by indexing the reference trajectories directly with an in-memory R-tree and building connections to the raw trajectories with inverted index, we develop an extremely efficient algorithm that can answer spatio-temporal range queries over trajectories in their compressed form. Extensive experiments on a real taxi trajectory dataset demonstrate the superiority of our framework over existing representative approaches in terms of both compression ratio and efficiency.