Jaypee Institute of Information Technology

About: Jaypee Institute of Information Technology is a education organization based out in Noida, Uttar Pradesh, India. It is known for research contribution in the topics: Computer science & Cluster analysis. The organization has 2136 authors who have published 3435 publications receiving 31458 citations. The organization is also known as: JIIT Noida.

Wavelet based Novel Technique for Signal Conditioning of Electro-Oculogram Signals

Abstract: In this paper, we present a novel and simple technique for signal conditioning of EOG signals which primarily involves denoising corrupted signals and post - processing for signal enhancement. Researches in the past have mainly focused on the EOG signals where the problem of removal of Ocular Artifacts from the Electroencephalogram was dealt. We present, from a new perspective, a scheme which essentially deals with enhancement of EOG Signals. The non-stationary and time-varying EOG signals are processed using methodologies anchored on multiresolution analyses and the Wavelet Transform theory. Coiflet wavelets are used for subsequent removal of noise from the (awgn) corrupted EOG signals using the concept of coefficient thresholding. SURE is used for threshold selection. Its performance, in terms of SNR, is compared with strategies suggested by Birge - Massart and Donoho and Johnstone. Haar based wavelets of higher orders are used for post-processing of EOG signals. A pronounced advantage of post - processing of signals is that it facilitates the estimation of time instants and durations of intentional eye gestures which mainly find application in the development of human - computer interface based devices.

A TENGRAM method based part-of-speech tagging of multi-category words in Hindi language

Abstract: In this paper, we have dealt on the problem of part-of-speech tagging of multi-category words which appear within the sentences of Hindi language. Firstly, a Hindi tagger is proposed which provides part-of-speech tags developed using grammar of Hindi language. For this purpose, Hindi Devanagari alphabets are used and their Hindi transliteration is done within the proposed tagger. Thereafter, a Rules' based TENGRAM method is described with an illustrative example, which guides to disambiguate multi-category words within sentences of Hindi corpus. The rules generated in TENGRAM are the result of computation of discernibility matrices, discernibility functions and reducts. These computations have been generated from decision tables which are based on theory of Rough sets. Basically, a discernibility matrix helps in cutting down indiscernible condition attributes; a discernibility function has rows corresponding to each column in the discernibility matrix which develops reducts; and the reducts provide a minimal subset of attributes which preserve indiscernibility relation of decision tables and hence they generate the decision rules.

A digital audio watermarking scheme using selective mid band DCT coefficients and energy threshold

Abstract: In this paper, two blind digital audio watermarking technique are proposed according to the payload requirement which uses discrete cosine transform (DCT). In our method the watermark is embedded into the selected mid band coefficients of the DCT transformed audio. The selected coefficients are middle band DCT coefficients which are modified and quantized through the average energy of the selected sub frame for watermark embedding. The mid band frequency components are selected through experiments such that the effect of mp3 compression and the common signal processing operation has a minimum effect on these coefficients. Original audio will not be required for extraction of the watermark. To adapt to the mp3 attack a preprocessing step is embedded which did an mp3 conversion of the audio and convert again the audio to the original format prior to embedding. Also embedding is done on the selected blocks which satisfies minimum energy threshold. Experiments show that our scheme produces imperceptible audios and the watermarked audio is robust against common signal processing attacks.

Temperature-dependent tuning of photonic band gaps for wavelength-selective switching applications

Abstract: Transmission characteristics of a thermally tunable optical filter system composed of two 1D silicon–air photonic crystals with different periods have been explored by transfer matrix method. The proposed structure is capable of separating and switching unique wavelength channel without interfering with others amongst 11 equally spaced wavelength channels. Each channel has full width at half maximum of 1 nm as per the wavelength-division multiplexing standards developed by the International Telecommunication Union specifying channel spacing between the adjacent channels in terms of wavelength for wavelength-selective switching applications. The refractive index of silicon is known to be dependent on both temperature and wavelength. Thus, any change in the operating temperature of both photonic crystals by same amount causes their photonic band gaps to alter simultaneously and significantly in such a way as to switch the wavelength-division multiplexing channels one by one as per requirement. The working of the proposed filter system is dependent only on tuning the photonic band gaps and is completely different from the conventional photonic crystals with defect.