Hsien-Tsung Chang

A cognitive adopted framework for IoT big-data management and knowledge discovery prospective

In future IoT big-data management and knowledge discovery for large scale industrial automation application, the importance of industrial internet is increasing day by day. Several diversified technologies such as IoT (Internet of Things), computational intelligence, machine type communication, big-data, and sensor technology can be incorporated together to improve the data management and knowledge discovery efficiency of large scale automation applications. So in this work, we need to propose a Cognitive Oriented IoT Big-data Framework (COIB-framework) along with implementation architecture, IoT big-data layering architecture, and data organization and knowledge exploration subsystem for effective data management and knowledge discovery that is well-suited with the large scale industrial automation applications. The discussion and analysis show that the proposed framework and architectures create a reasonable solution in implementing IoT big-data based smart industrial applications.

IoT Big-Data Centred Knowledge Granule Analytic and Cluster Framework for BI Applications: A Case Base Analysis

The current rapid growth of Internet of Things (IoT) in various commercial and non-commercial sectors has led to the deposition of large-scale IoT data, of which the time-critical analytic and clustering of knowledge granules represent highly thought-provoking application possibilities. The objective of the present work is to inspect the structural analysis and clustering of complex knowledge granules in an IoT big-data environment. In this work, we propose a knowledge granule analytic and clustering (KGAC) framework that explores and assembles knowledge granules from IoT big-data arrays for a business intelligence (BI) application. Our work implements neuro-fuzzy analytic architecture rather than a standard fuzzified approach to discover the complex knowledge granules. Furthermore, we implement an enhanced knowledge granule clustering (e-KGC) mechanism that is more elastic than previous techniques when assembling the tactical and explicit complex knowledge granules from IoT big-data arrays. The analysis and discussion presented here show that the proposed framework and mechanism can be implemented to extract knowledge granules from an IoT big-data array in such a way as to present knowledge of strategic value to executives and enable knowledge users to perform further BI actions.

A Cognitive Oriented Framework for IoT Big-data Management Prospective

The Internet-of-Things (IoT) environment continuously inspires any time-place-things connectivity of the smart objects in and around the universe. Day by day the rapid growth of enormous IoT objects and digital storage technology, lead to a large heterogeneous data depository, in which the IoT big-data are stored in the dissimilar database frameworks as a consequence of heterogeneous data sources. So due to large heterogeneous data sources, some incompatibilities like name, scale, structure, and level of abstraction are there in between the frameworks of IoT big-data that create threats to data management and knowledge discovery. So in this work, we need to propose a Cognitive Oriented IoT Big-data Framework (COIB-framework) along with implementation architecture, IoT big-data layering architecture, and a data organization framework for effective data management and knowledge discovery that cop-up with the large scale industrial automation applications. The discussion and analysis shows that the proposed framework and architectures creates a feasible solution in implementing IoT big-data based smart industrial applications.

A dynamic fitting room based on microsoft kinect and augmented reality technologies

In recent years, more and more researchers try to make Microsoft Kinect and Augmented Reality (AR) into real lives. In this paper, we try to utilize both Kinect and AR to build a dynamic fitting room. We can automatically measure the clothes size of a user in popular brands or different country standards. A user can utilize gesture to select cloths for fitting. Our proposed system will project the video dynamically of dressing selected clothes in accordance with the captured video from Kinect. This system can be utilized in clothing store, e-commerce of clothes shopping, and at your home when you are confusing choosing a clothes to wear. This can greatly reduce the time you fitting clothes.

Sharetouch: A system to enrich social network experiences for the elderly

Abstract The Sharetouch system is designed for raising users’ participation in community events. We put three subsystems into Sharetouch: (1) community pond, (2) Waterball interactive game, and (3) multimedia sharing. Sharetouch is based on an optical touch device designed by the Joyplux Company with an infrared LED and camera. This device can support multi-touch functions within a large display area. The software of Sharetouch was developed within XNA and .NET frameworks. We project the users as fish in our community pond. Sharetouch displays all the friends as fish when the users log into the system. Therefore, the number of fish equals the number of friends of the users. This design encourages users to make more friends to increase the number of fish. Waterball is a game that combines virtual images and real objects. The concept is based on the Nintendo Wii games, as players hold controllers (real objects) to play the games (virtual images). We also apply the concept of the cloud flash drive to multimedia sharing to avoid the trouble of carrying a real flash disk. This study employed the TAM measure to measure the validity of Sharetouch in this social platform. Our findings indicated that all proposed hypotheses had a positive and significant impact on the intention of older people to interact with Sharetouch. Unlike the computer-based system, Sharetouch is created as a user-friendly interface system. Sharetouch can enrich the users’ social network experiences through its hardware and software architectures.

Perceptions of a Specific Family Communication Application among Grandparents and Grandchildren: An Extension of the Technology Acceptance Model.

Many studies have noted that the use of social networks sites (SNSs) can enhance social interaction among the elderly and that the motivation for the elderly to use SNSs is to keep in contact with remote friends and family or the younger generation. Memotree is designed to promote intergenerational family communication. The system incorporates the Family Tree design concept and provides family communication mechanisms based on the Family Communication Scale. In addition, the system optimizes hardware and interface use to conform to the specific needs of older and substantially younger individuals. Regarding the impact of variables on SNS with respect to the interaction of usability variables in the construction of a cross-generational communication platform, we adopted the TAM model and Chung et al.’s suggestions to promote user acceptance of the proposed Memotree system. A total of 39 grandchildren and 39 grandparents met the criteria and were included in the study. The elderly and young respondents revealed substantial willingness to use and/or satisfaction with using the Memotree system. Empirical results indicate that technology affordances and perceived ease of use have a positive impact on perceived usefulness, while perceived ease of use is affected by technology affordances. Internet self-efficacy and perceived usefulness have a positive impact on the user’s behavioral intention toward the system. In addition, this study investigated age as a moderating variable in the model. The results indicate that grandchildren have a larger significant effect on the path between perceived usefulness and behavioral intention than grandparents. This study proposes a more complete framework for investigating the user’s behavioral intention and provides a more appropriate explanation of related services for cross-generational interaction with SNS services.

Scalable network file systems with load balancing and fault tolerance for web services

Abstract Because of the rapid growth of the World Wide Web and the popularization of smart phones, tablets and personal computers, the number of web service users is increasing rapidly. As a result, large web services require additional disk space, and the required disk space increases with the number of web service users. Therefore, it is important to design and implement a powerful network file system for large web service providers. In this paper, we present three design issues for scalable network file systems. We use a variable number of objects within a bucket to decrease internal fragmentation in small files. We also propose a free space and access load-balancing mechanism to balance overall loading on the bucket servers. Finally, we propose a mechanism for caching frequently accessed data to lower the total disk I/O. These proposed mechanisms can effectively improve scalable network file system performance for large web services.

A Topic Detection and Tracking System with TF-Density

In the past, news consumption took place predominantly via newspapers and were hard to track. Nowadays, the rapid growth of the Internet means that news are continually being shared and stored on a previously unimaginable scale. It is now possible to access several news stories on the same topic on a single web page. In this paper, we proposed a topic detection and tracking system with a new word measurement scheme named TF-Density. TF-Density is a new algorithm modified from the well-known TF-IWF and TF-IDF algorithms to provide a more precise and efficient method to recognize the important words in the text. Through our experiments, we demonstrated that our proposed topic detection and tracking system is capable of providing more precise and convenient result for the tracking of news by users.

Sharetouch: a multi-touch social platform for the elderly

The Sharetouch, which is a multi-touch social interaction system, aims to enable the elderly to engage the benefits of IT and enhance their social interaction among those older persons living in the community. Unlike most of the in-the-market digital devices, the Sharetouch attempts to merge the digital desktop and physical table into one, and has extra capabilities. Hence, a 52-inch large share-display system is developed for the purpose of accommodating multi-users simultaneously on a table surface shown in this paper.

Data-Centric Knowledge Discovery Strategy for a Safety-Critical Sensor Application

In an indoor safety-critical application, sensors and actuators are clustered together to accomplish critical actions within a limited time constraint. The cluster may be controlled by a dedicated programmed autonomous microcontroller device powered with electricity to perform in-network time critical functions, such as data collection, data processing, and knowledge production. In a data-centric sensor network, approximately 3–60% of the sensor data are faulty, and the data collected from the sensor environment are highly unstructured and ambiguous. Therefore, for safety-critical sensor applications, actuators must function intelligently within a hard time frame and have proper knowledge to perform their logical actions. This paper proposes a knowledge discovery strategy and an exploration algorithm for indoor safety-critical industrial applications. The application evidence and discussion validate that the proposed strategy and algorithm can be implemented for knowledge discovery within the operational framework.