683 research outputs found

    A program-driven parallel machine simulation environment

    Get PDF
    [[abstract]]In recent years, it has been very popular to employ discrete-event simulation as a hardware architecture analytical tool to study distributed-memory multicomputers and shared-memory multiprocessors. After the hardware architecture prototype has been completed, a complete and detailed machine simulation environment can be utilized to evaluate the architecture's efficiency under real operating systems and application software. In this article, we discuss all the development and implementation of a program-executable Transputer network multicomputer as well as 80x86 series multiprocessors, and how they can be operated. On another level, owing to the extreme complexity of the simulated computer systems, parallel discrete-event simulation has also been used to shorten the time of running the simulation. In practice, this simulator can solve problems through a network connection with many workstations. Some of the workstations may be in charge of computing, while others can be responsible for the management of memory, thus making it simpler to establish a parallel machine simulation environment. In addition to providing an environment for programs to execute on it, such a simulator also calculates the time spent in running these programs, so as to evaluate the feasibility for these application programs to run on a hardware system.[[conferencetype]]國際[[conferencedate]]19981214~19981216[[conferencelocation]]Tainan, Taiwa

    A New Measure of Cluster Validity Using Line Symmetry

    Get PDF
    [[abstract]]Many real-world and man-made objects are symmetry, therefore, it is reasonable to assume that some kind of symmetry may exist in data clusters. In this paper a new cluster validity measure which adopts a non-metric distance measure based on the idea of "line symmetry" is presented. The proposed validity measure can be applied in finding the number of clusters of different geometrical structures. Several data sets are used to illustrate the performance of the proposed measure.[[notice]]補正完畢[[journaltype]]國外[[incitationindex]]SCI[[incitationindex]]EI[[ispeerreviewed]]Y[[booktype]]紙本[[booktype]]電子版[[countrycodes]]TW

    Tertiary Students’ Entrepreneurship Learning Socialization: Factor Analysis and Structural Equation

    Get PDF
    This study examines 728 tertiary students’ entrepreneurship learning socialization and its influencing factors to serve as a school reference for the development of internship and entrepreneurship education. The results show that students’ internship experience has a significant direct effect on entrepreneurship learning socialization, and entrepreneurship intention has a significant effect on entrepreneurship learning socialization through internship experience. The influence pattern and empirical data of entrepreneurship intention and internship experience on entrepreneurship learning socialization has a good fit. This paper gives an insight from Taiwan tertiary institutions about entrepreneurial learning socialization of students and contributions to them. We describe the development of the influencing factors, discuss its implications for entrepreneurship and internship education, and finally offer suggestions for further entrepreneurship education development

    Online platform for applying space–time scan statistics for prospectively detecting emerging hot spots of dengue fever

    Get PDF
    Abstract Background Cases of dengue fever have increased in areas of Southeast Asia in recent years. Taiwan hit a record-high 42,856 cases in 2015, with the majority in southern Tainan and Kaohsiung Cities. Leveraging spatial statistics and geo-visualization techniques, we aim to design an online analytical tool for local public health workers to prospectively identify ongoing hot spots of dengue fever weekly at the village level. Methods A total of 57,516 confirmed cases of dengue fever in 2014 and 2015 were obtained from the Taiwan Centers for Disease Control (TCDC). Incorporating demographic information as covariates with cumulative cases (365 days) in a discrete Poisson model, we iteratively applied space–time scan statistics by SaTScan software to detect the currently active cluster of dengue fever (reported as relative risk) in each village of Tainan and Kaohsiung every week. A village with a relative risk >1 and p value <0.05 was identified as a dengue-epidemic area. Assuming an ongoing transmission might continuously spread for two consecutive weeks, we estimated the sensitivity and specificity for detecting outbreaks by comparing the scan-based classification (dengue-epidemic vs. dengue-free village) with the true cumulative case numbers from the TCDC’s surveillance statistics. Results Among the 1648 villages in Tainan and Kaohsiung, the overall sensitivity for detecting outbreaks increases as case numbers grow in a total of 92 weekly simulations. The specificity for detecting outbreaks behaves inversely, compared to the sensitivity. On average, the mean sensitivity and specificity of 2-week hot spot detection were 0.615 and 0.891 respectively (p value <0.001) for the covariate adjustment model, as the maximum spatial and temporal windows were specified as 50% of the total population at risk and 28 days. Dengue-epidemic villages were visualized and explored in an interactive map. Conclusions We designed an online analytical tool for front-line public health workers to prospectively detect ongoing dengue fever transmission on a weekly basis at the village level by using the routine surveillance data

    Instant processing of large-scale image data with FACT, a real-time cell segmentation and tracking algorithm

    Get PDF
    Quantifying cellular characteristics from a large heterogeneous population is essential to identify rare, disease-driving cells. A recent development in the combination of high-throughput screening microscopy with single-cell profiling provides an unprecedented opportunity to decipher disease-driving phenotypes. Accurately and instantly processing large amounts of image data, however, remains a technical challenge when an analysis output is required minutes after data acquisition. Here, we present fast and accurate real-time cell tracking (FACT). FACT can segment ∼20,000 cells in an average of 2.5 s (1.9–93.5 times faster than the state of the art). It can export quantifiable features minutes after data acquisition (independent of the number of acquired image frames) with an average of 90%–96% precision. We apply FACT to identify directionally migrating glioblastoma cells with 96% precision and irregular cell lineages from a 24 h movie with an average F1 score of 0.91.</p

    School Organizational Innovative Indicators For Technical Universities And Institutes

    Get PDF
    This study aimed to construct the organizational innovation indicators of technical universities and institutes. This study held a group discussion and expert focus meeting and afterward, this study generalized seven facets of school organizational innovation: leadership innovation, administration innovation, student guidance and activity innovation, curriculum and instruction innovation, teacher professional development innovation, resource application innovation, and campus construction innovation. Then 25 criteria and 83 indices were developed
    corecore