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Journal of Telematics and Informatics

JTI
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Published by IAES Indonesia Section and Partners

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Core Subject : Science, Engineering,

Computer Science & IT Electrical & Electronics Engineering

Journal of Telematics and Informatics (e-ISSN: 2303-3703, p-ISSN: 2303-3711) is an interdisciplinary journal of original research and writing in the wide areas of telematics and informatics. The journal encompasses a variety of topics, including but not limited to: The technology of sending, receiving and storing information via telecommunication devices in conjunction with affecting control on remote objects; The integrated use of telecommunications and informatics; Global positioning system technology integrated with computers and mobile communications technology; The use of telematic systems within road vehicles, in which case the term vehicle telematics may be used; The structure, algorithms, behavior, and interactions of natural and artificial systems that store, process, access and communicate information; Develops its own conceptual and theoretical foundations and utilizes foundations developed in other fields; and The social, economic, political and cultural impacts and challenges of information technologies (advertising and the internet, alternative community networks, e-commerce, e-finance, eâ€“governance, globalization and security, green computing, ICT for sustainable development, ICT in healthcare and education, management and policymaking, mobile and wireless communications, peer-to-peer learning, regulation of digital technologies, social networking, special user groups, the 2.0 paradigm, the WWW, etc). The journal is a collaborative venture between Universitas Islam Sultan Agung (UNISSULA), Universitas Ahmad Dahlan (UAD) and Institute of Advanced Engineering and Science (IAES) Indonesia Section.

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Articles 5 Documents

Search results for , issue "Vol 2, No 2: September 2014" : 5 Documents clear

Application of MFFC and Edge Detection for Remote Driven Vehicles through Matlab T Ravi; K Pradeep Reddy; K Eepsita Saranya
Journal of Telematics and Informatics Vol 2, No 2: September 2014
Publisher : Universitas Islam Sultan Agung

Speech recognition is a rapidly emerging technology in Human Computer Interaction HCI. It has many applications as we use it from search engines to the device control it serves many areas we interact every day from dawn to dusk. Along with the uses we have many limitations in speech processing such as Language barrier, Accent and Noise, so to implement the speech processing we have many challenges. To enable the advantages of this speech processing most of the leading software companies like Apple, Microsoft and Google are continuously evolving their speech enabled applications. The speech processing eases the physically challenged people’s interaction with the devices and makes them productive. The Idea of the automatically driven cars is introduced by Google and Audi, but they are not acceptable in most of the cases because of lacking trust in current technology. Thus we here worked on the remote driven vehicle in a more secured method using the Mel Frequency cepstral Coefficient. The secure driving of the vehicle can be ensured by the remote driver. This technique is very rapid and more reliable for the speech detection thus the remote driver can use the MFCC and the video from the vehicle needed to be broadcasted to the remote driver that can be done an IP camera running on a data network. And the instructions can from the remote driver can be sent to the vehicle by an app created with python that connected to a micro controller. To minimize the limitations in the remote drive the vehicle must be enabled with automatic braking when obstacle approaches which can be done by the Ultrasonic sensors that do the distance estimation. The remote drivers usually have a very limited view of road they drive and they must get the precise edges of the road this can be achieved by processing the stream of images to calculate the edge in Matlab.

Significance of Weighted-Type Fractional Fourier Transform in FIR Filters P. Bobitha; P.V. Muralidhar
Journal of Telematics and Informatics Vol 2, No 2: September 2014
Publisher : Universitas Islam Sultan Agung

The desired frequency response of a filter is periodic in frequency and can be expanded in Fourier series. One possible way of obtaining FIR filter is to truncate the infinite Fourier series. But abrupt truncation of the Fourier series results in oscillation in the pass band and stop band. These oscillations are due to slow convergence of the Fourier series by the Gibb’s phenomenon. To reduce these oscillations the Fourier coefficients of the filter are modified by multiplying the infinite impulse response with a finite weighing sequence called a window. The Fourier transform (FT) of a window consists of a central lobe and side lobes. The central lobe contains most of the energy of the window. To get an FIR filter, the desired impulse response and window function are multiplied, which results to give finite length non-causal sequence. Since Fractional Fourier Transform (FrFT) is generalization of FT. Here an attempt is to implement filters using window by using Weighted Type Fractional Fourier Transform (WFrFt), differentiator and integrator using weighted FrFt is also present.

Facilitating Image and Document Retrieval Using Image Content and Querying Keyword M.R. Narasinga Rao; J. Srinija; P.Krishna Chaitanya; Y. Chanukya; T. Sabhareesh
Journal of Telematics and Informatics Vol 2, No 2: September 2014
Publisher : Universitas Islam Sultan Agung

Evolution of ubiquitous computing in the areas of personal computing technology has produced staggeringly large data It is difficult to search mainly the image data by understanding users objective only by keywords and phrases and this leads to uncertain outcomes. For producing these outcomes effectively, this paper introduces a new approach to the problem of image learning to enable search engines to learn about visual content over time based on user feedback through one click activity and images from a pool recovered by text based query are re-ranked depending on both visual and text based query. Content Based Image Retrieval (CBIR) techniques are used for accessing semantically-relevant images from an image data source depending on automatically-derived image functions for features like Geometric moments, Global histogram, Color Moments, Local histogram. Documents can also be retrieved using the text based query by the user.

Introducing Adaptive filters Based on Shadow Concept for Speech Processing M. Koteswara Rao; I.Santhi Prabha
Journal of Telematics and Informatics Vol 2, No 2: September 2014
Publisher : Universitas Islam Sultan Agung

This paper presents the new approach to introducing adaptive Filter with LMS Algorithm based on Shadow concept. Which is useful for the cancellation of the noise component overlap with Speech signal in the same frequency range, but fixed LMS algorithm produces minimum convergence rate and fixed steady state error. So we presents design, implementation and performance of adaptive FIR filter, based on Shadow concept, which produces minimum mean square error compare to fixed LMS, and we also obtains denoised Speech signal at output, and also we propose to calculate SNR values of Adaptive Filter with LMS algorithm with and without Shadow concept.

Provision of Relevant Results on web search Based on Browsing History G. Rama Krishna; G. Harika Priya; V. Sravani; Y. Sai Chandu; G. Sai Srikanth
Journal of Telematics and Informatics Vol 2, No 2: September 2014
Publisher : Universitas Islam Sultan Agung

Different users submit a query to a web search engine with different needs. The general type of search engines follows the "one size fits all" model which is not flexible to individual users resulting in too many answers for the query. In order to overcome this drawback, in this paper, we propose a framework for personalized web search which considers individual's interest introducing intelligence into the traditional web search and producing only relevant pages of user interest. This proposed method is simple and efficient which ensures quality suggestions as well as promises for effective and relevant information retrieval. The framework for personalized web search engine is based on user past browsing history. This context is then used to make the web search more personalized. The results are encouraging.

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