教育訓練

研討會

  1. 巨量資料分析與江河運算課程訓練[Big Data Analytics and Stream Computing] 2014年04月15日至18日工程四館814室
    IBM TJ Watson Research Center Manager Dr. Shu-Ping Chang
    國立交通大學 電機系 王蒞君 教授
    國立交通大學 電機系 洪吉祥 博士

    本課程為IBM InfoSphere Streams平台之基本使用教學,搭配介紹課程及線上實作,除了讓學員們可以瞭解巨量資料的運算技術外,亦可輕鬆學會如何運用IBM InfoSphere Streams平台進行巨量資料分析方法之開發。

  2. Internet of Things and 5G 2015年07月13日至16日工程四館824室
    Dr. Ming-Jye Sheng

    The cloud is “descending” to the network edge and often diffused among the edge and client devices, in such Fog Networks supporting 5G and IoT, these devices are limited in global view of the network. We identify needs for effective RF surveillance and big data analytics and cross-layer cross-system visibility for several scenarios.

  3. 2015 Cloud Computing-Streams Processing Platform Workshop 2015年09月07日至11日工程四館814室
    國立交通大學 電機系 王蒞君 教授
    IBM TJ Watson Research Center Manager Dr. Shu-Ping Chang
    IBM TJ Watson Research Center Engineer Dr. Senthil Nathan

    本課程為IBM InfoSphere Streams平台之基本使用教學,搭配介紹課程及線上實作,除了讓學員們可以瞭解巨量資料的運算技術外,亦可輕鬆學會如何運用IBM InfoSphere Streams平台進行巨量資料分析方法之開發。

演講

  1. Intelligent Modelling of Big Data Systems 2015年08月05日工程五館220室
    國立交通大學 王啟旭 教授(IEEE Fellow)

    The Big Data Systems (BDSs) have been so popular since 2000. The purpose of this talk is not to illustrate BDSs, but to explore its kernel issue, i.e., the modelling of BDS. In the implementation of BDSs, the conventional mathematical techniques for data analysis have sometimes failed to perform the modelling of BDSs. It may due to the enormous amount of data, or the data structure behind the BDSs is beyond the imagination of classical people. To overcome this potential barrier, this talk will explore the modelling of BDSs by intelligent techniques. A very important finding about the capacity of Fuzzy Neural Networks (FNNs) will be explained first. This capacity issue with intelligent modelling has been actually applied to a real application of water monitoring system by remote sensing approach. This successful benchmark using intelligent modelling with capacity constraint for BDSs is a very positive sign in this research area. Further potential enhancements will be discussed also.