Han-Chieh Chao

Bio: Han-Chieh Chao is an academic researcher from National Dong Hwa University. The author has contributed to research in topics: Wireless sensor network & Wireless network. The author has an hindex of 46, co-authored 537 publications receiving 9269 citations. Previous affiliations of Han-Chieh Chao include Purdue University & National Ilan University.

Big data analytics: a survey

Abstract: The age of big data is now coming. But the traditional data analytics may not be able to handle such large quantities of data. The question that arises now is, how to develop a high performance platform to efficiently analyze big data and how to design an appropriate mining algorithm to find the useful things from big data. To deeply discuss this issue, this paper begins with a brief introduction to data analytics, followed by the discussions of big data analytics. Some important open issues and further research directions will also be presented for the next step of big data analytics.

Multimedia traffic security architecture for the internet of things

Abstract: An important challenge for supporting multimedia applications in the Internet of Things is the security heterogeneity of wired and wireless sensor and actuator networks. In this work, we design a new and efficient media-aware security framework for facilitating various multimedia applications in the Internet of Things. First, we present a novel multimedia traffic classification and analysis method for handling the heterogeneity of diverse applications. Then a media-aware traffic security architecture is proposed based on the given traffic classification to enable various multimedia services being available anywhere and anytime. Furthermore, we provide a design rule and strategy to achieve a good trade-off between a system?s flexibility and efficiency. To the best of our knowledge, this study is the first to provide general media-aware security architecture by jointly considering the characteristics of multimedia traffic, security service, and the Internet of Things.

A survey of black hole attacks in wireless mobile ad hoc networks

Abstract: The black hole attack is one of the well-known security threats in wireless mobile ad hoc networks. The intruders utilize the loophole to carry out their malicious behaviors because the route discovery process is necessary and inevitable. Many researchers have conducted different detection techniques to propose different types of detection schemes. In this paper, we survey the existing solutions and discuss the state-of-the-art routing methods. We not only classify these proposals into single black hole attack and collaborative black hole attack but also analyze the categories of these solutions and provide a comparison table. We expect to furnish more researchers with a detailed work in anticipation.

Pervasive, secure access to a hierarchical sensor-based healthcare monitoring architecture in wireless heterogeneous networks

Abstract: This study presents a healthcare monitoring architecture coupled with wearable sensor systems and an environmental sensor network for monitoring elderly or chronic patients in their residence. The wearable sensor system, built into a fabric belt, consists of various medical sensors that collect a timely set of physiological health indicators transmitted via low energy wireless communication to mobile computing devices. Three application scenarios are implemented using the proposed network architecture. The group-based data collection and data transmission using the ad hoc mode promote outpatient healthcare services for only one medical staff member assigned to a set of patients. Adaptive security issues for data transmission are performed based on different wireless capabilities. This study also presents a monitoring application prototype for capturing sensor data from wireless sensor nodes. The implemented schemes were verified as performing efficiently and rapidly in the proposed network architecture.

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Out of the Crisis

Abstract: According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.