Review on hygroscopic aging of cellulose fibres and their biocomposites

Big Data encompasses large volume of complex structured, semi-structured, and unstructured data, which is beyond the processing capabilities of conventional databases. The processing and analysis of Big Data now play a central role in decision making, forecasting, business analysis, product development, customer experience, and loyalty, to name but a few. In this paper, we examine the distinguishing characteristics of Big Data along the lines of the 3Vs: variety, volume, and velocity. Accordingly, the paper provides an insight into the main processing paradigms in relation to the 3Vs. It defines a lifecycle for Big Data processing and classifies various available tools and technologies in terms of the lifecycle phases of Big Data, which include data acquisition, data storage, data analysis, and data exploitation of the results. This paper is first of its kind that reviews and analyzes current trends and technologies in relation to the characteristics, evolution, and processing of Big Data. Copyright © 2014 John Wiley & Sons, Ltd.

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Emerging trends and technologies in big data processing

Good emotional health is one important point to improve quality of life. On the other hand, bad emotional health can lead to social or mental health problems. To cope with the bad emotional health caused by negative emotions in daily life, we design a healthcare system that focuses on emotional aspects and provides services to improve user emotions. To improve them, we need to recognize their current emotional states. Therefore, our system integrates emotion detection to suggest appropriate services and is designed as a web-based system. While users use the system, facial expressions and speech are detected and analyzed to determine their emotions. When negative emotions are detected, our system suggests that users take a break and provides appropriate services (including relaxation, amusement and excitement services) with augmented reality and Kinect to improve their emotional states. This paper focuses on feature extraction and the classification of emotion detection by facial expressions.

Emotional Healthcare System: Emotion Detection by Facial Expressions using Japanese Database

Cloud computing is changing the way industries and enterprises run their businesses. Cloud manufacturing is emerging as an approach to transform the traditional manufacturing business model, while helping the manufacturer to align production efficiency with its business strategy, and creating intelligent factory networks that enable collaboration across the whole enterprise. Many production planning and control (PPC) problems are essentially optimisation problems, where the objective is to develop a plan that meets the demand at minimum cost or maximum profit. Because the underlying optimisation problem will vary in the different business and operation phases, it is important to think about optimisation in a dynamic mechanism and in a number of interlinked sub-problems at the same time. Cloud manufacturing has the potential to offer decision support as a service and medium of communication in PPC. To solve these problems and produce collaboration across the supply chain, this paper provides an ove...

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Cloud manufacturing system for sheet metal processing

In this paper, a brief review and comparison of the engine waste heat recovery technologies have been made. These five technologies are electric turbocompounding systems (ETC), thermodynamic organic Rankine cycle (ORC), thermoelectric generators (TEG), hydrogen generation by using exhaust gas heat energy, and hybrid pneumatic power systems (HPPS). According to comparison results, the HPPS system can achieve the highest fuel economy improvement among the five technologies. Though there are their own benefits by utilizing these different technologies, their disadvantages prevent the application of these advanced technologies to different extent. Besides, a combined evaluation method consisting of grey relational analysis and analytic hierarchy process has been applied to assess the five new engine waste heat recovery technologies from the perspective of technical, economic, and environmental aspect. Based on the final results of the new evaluation method, the HPPS was found to be the most promising WHR technology for vehicle engines. But because of the emphasis on economic benefit, TEG was found to be more favorable for working conditions, like power plant and marine engine. What is more, as is shown in the sensibility analysis, the weighing of the environment relevant factors can prominently influence the comparison results between ETC and HPPS.

A review and selection of engine waste heat recovery technologies using analytic hierarchy process and grey relational analysis

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S.Bhavani D.Anuradha

Papers

Unit Based Fuzzy Expediting In Project Networks