The Third International Conference on Information Technology Convergence and Services (ITCS 2014)

The presence of information technology has become an intricate part of our life. Few would have realized in the early eighties that in the near future there will be multi-million dollar service based industries. The industrial revolution was successful because man knew how to work with machines. For the present knowledge age revolution to be successful it will depend on the wisdom inscribed in knowledge base articles. The absence of relevant knowledge base articles in self help portal of technical contact center causes high customer call volumes in service industry. This problem can cause staffing issues as well as loss of business credibility. That can further lead to staff attrition rate as well as business loss.

To resolve this issue we propose a framework. We have used statistical methods and computer programming language to quantify the various hypotheses central to developing the proposed framework. Web based questionnaire and interview are used to collect data for this research. In this research an interesting finding was the null hypotheses that Average call Handle Time (AHT) and Knowledge Base (KB) referral were not related to each other, and that is a contentious paradigm. This is reasoned to less data collected for research evaluation.

Finger Braille is one of the tactual communication methods utilized by deafblind individuals. Deafblind people who are skilled in Finger Braille can catch up with speech conversation and express various emotions by changing dotting strength and speed. In this paper, we designed the emotion teaching interface in order to express joy, sadness, anger and neutral for the Finger Braille emotion teaching system. We changed the previous background color (beige) of the teaching interface into 17 different colors. We also designed 8 kinds of dot patterns with different horizontal width and vertical length. The experiment to select the most suitable emotion teaching interfaces for joy, sadness, anger and neutral was conducted. The results showed that the dot patterns 6 (the wide and middle length pattern) or 1 (the small circle) with the lime, dark orange or yellow background colors are suitable for joy; the dot patterns 7 (the narrow and long pattern) or 4 (the narrow and middle length pattern) with the lavender, navy or blue background colors are suitable for sadness; the dot patterns 9 (the large circle) or 8 (the middle width and long pattern) with the red background color are suitable for anger; the dot pattern 5 (the middle circle) with the previous, honeydew, saddle brown or white background colors are suitable for neutral.

This article describes the design and development of a system for remote indoor 3D monitoring using an undetermined number of Microsoft ® Kinect sensors. In the proposed client-server system, the Kinect cameras can be connected to different computers, addressing this way the hardware limitation of one sensor per USB controller. The reason behind this limitation is the high bandwidth needed by the sensor, which becomes also an issue for the distributed system TCP/IP communications. Since traffic volume is too high, 3D data has to be compressed before it can be sent over the network. The solution consists in self-coding the Kinect data into RGB images and then using a standard multimedia codec to compress color maps. Information from different sources is collected into a central client computer, where point clouds are transformed to reconstruct the scene in 3D. An algorithm is proposed to conveniently merge the skeletons detected locally by each Kinect, so that monitoring of people is robust to self and inter-user occlusions. Final skeletons are labeled and trajectories of every joint can be saved for event reconstruction or further analysis.

The color satellite image compression technique by vector quantization can be improved either by acting directly on the step of constructing the dictionary or by acting on the quantization step of the input vectors. In this paper, an improvement of the second step has been proposed. The k-nearest neighbor algorithm was used on each axis separately. The three classifications, considered as three independent sources of information, are combined in the framework of the evidence theory. The best code vector is then selected, after the image is quantized, Huffman schemes compression is applied for encoding and decoding.

There are many ways to encode, represent, and compress satellite images. Today, with the huge technological advance, algorithms are used to perform many calculations to compress and decompress a satellite image. The future of the compression can take place only through mathematical algorithms, and the progress of mathematical research undoubtedly will lead to an advance in image and file compression. In this paper, we propose a hybrid DPCM-DCT predictive coding and discrete cosine transform DCT and, run-length encoding (RLE) for satellite image compression.

The need to transmit or store satellite images is growing rapidly with the development of modern communications and new imaging systems. The goal of compression is to facilitate the storage and transmission of large images on the ground with high compression ratios and minimum distortion. In this work, we present a new coding scheme for satellite images. At first, the image will be downloaded followed by a fast Fourier transform FFT. The result obtained after FFT processing undergoes a scalar quantization (SQ). The results obtained after the quantization phase are encoded using entropy encoding. This approach has been tested on satellite image and Lena picture. After decompression, the images were reconstructed faithfully and memory space required for storage has been reduced by more than 80%.

Protein can be represented by amino acid interaction network. This network is a graph whose vertices are the proteins amino acids and whose edges are the interactions between them. This interaction network is the first step of proteins three-dimensional structure prediction. In this paper we present a multi-objective evolutionary algorithm for interaction prediction and ant colony probabilistic optimization algorithm is used to confirm the interaction.

With the burst of social media in the 21st century, e-commerce underwent a paradigm shift with the manifestation of social commerce. Due to its tardy blooming, the term social commerce coined in the year 2005 is relatively researched less in the IS disciple despite an intense evolution. As a result, this paper aims to critically probe into existing and related work in the area of social commerce from the Information Systems perspective. The standard systematic literature review method employing a physical search of 6 journals and 9 proceedings were used in conducting the literature review. The comprehensively and explicitly conducted systematic literature review is valuable in bridging the social commerce gap and opens up novel directions to Information Systems scholars in this market segment.