DNA Sequence Representation methods

DNA sequence representation methods are used to denote a gene structure effectively and help in similarities/dissimilarities analysis of coding sequences. Many different kinds of representations have been proposed in the literature. They can be broadly classified into Numerical, Graphical, Geometrical and Hybrid representation methods. DNA structure and function analysis are made easy with graphical and geometrical representation methods since it gives visual representation of a DNA structure. In numerical method, numerical values are assigned to a sequence and digital signal processing methods are used to analyze the sequence. Hybrid approaches are also reported in the literature to analyze DNA sequences. This paper reviews the latest developments in DNA Sequence representation methods. We also present a taxonomy of various methods. A comparison of these methods where ever possible is also done

Development of Time - Frequency Techniques for Sonar Applications

Sonar signal processing comprises of a large number of signal processing algorithms for implementing functions such as Target Detection, Localisation, Classification, Tracking and Parameter estimation. Current implementations of these functions rely on conventional techniques largely based on Fourier Techniques, primarily meant for stationary signals. Interestingly enough, the signals received by the sonar sensors are often non-stationary and hence processing methods capable of handling the non-stationarity will definitely fare better than Fourier transform based methods.Time-frequency methods(TFMs) are known as one of the best DSP tools for nonstationary signal processing, with which one can analyze signals in time and frequency domains simultaneously. But, other than STFT, TFMs have been largely limited to academic research because of the complexity of the algorithms and the limitations of computing power. With the availability of fast processors, many applications of TFMs have been reported in the fields of speech and image processing and biomedical applications, but not many in sonar processing. A structured effort, to fill these lacunae by exploring the potential of TFMs in sonar applications, is the net outcome of this thesis. To this end, four TFMs have been explored in detail viz. Wavelet Transform, Fractional Fourier Transfonn, Wigner Ville Distribution and Ambiguity Function and their potential in implementing five major sonar functions has been demonstrated with very promising results. What has been conclusively brought out in this thesis, is that there is no "one best TFM" for all applications, but there is "one best TFM" for each application. Accordingly, the TFM has to be adapted and tailored in many ways in order to develop specific algorithms for each of the applications.

Studies on Minced Fish Technology

The quality of minced fish, as mentioned earlier depends largely on the type and quality of the raw material used, as well as on the processing methods employed. Moreover, fish mincing involves cutting up of tissues thereby increasing surface area to a great extent and releasing of enzymes and nutrients from the tissues. Due to these factors fish mince is relatively more prone to chemical. autolytic and microbial spoilage. Hence study of minced fish with these factors in focus is very important. Equally important is the availability, price and preference of the raw material vis-a-vis the end products and the storage period it passes through. In the present study. changes in the bacterial flora. both quantitative and qualitative of the dressed fish, viz. Nemipterus japonicas and mince from the same fish during freezing and frozen storage have been investigated in detail. The effect of a preservative. viz. . EZDTA on the bacteriological and shelf life characteristics of the minced fish has also been investigated. Attempts have also been made to develop various types of products from mince and to study their storage life.

Effect Of Raw Material Quality On The Shelf Life Of Frozen Stored Fish And Fishery Products

Frozen storage characteristics and shelflife vary considerably among species as well as within the species (Powrie, 1973; Fennema. 1973). This can be attributed to the variation in the composition of fish among various species. In certain species like sardines and mackerel. wide seasonal variation in chemical composition occur within the species. These variations affect the quality and shelflife. The nutritional level of water. spawning, method of catching, struggling etc. are found to have profound influence on the condition of the fresh fish. Soon after death the deteriorative changes in fish start due to autolysis and bacterial growth. The rate of these changes depends mainly on temperature. The handling methods have great influence on bacterial contamination. Thus the type oi'handling. temperature control. period of chill storage. processing methods. type of freezing, condition of frozen storage and period of storage affect the quality and shelflife Of the fisho In the present study extensive investigations were carried out on various factors affecting the quality of fish as well as their effect on the physical. chemical and sensory qualities of fish during frozen storage and the shelflife

“Effect of spice oleoresins in microbial decontamination and their potential application in quality stabilization of Tuna (Euthynnus affinis) during storage”

Unprocessed seafood harbor high number of bacteria, hence are more prone to spoilage. In this circumstance, the use of spice in fish for reduction of microorganism can play an important role in seafood processing. Many essential oils from herbs and spices are used widely in the food, health and personal care industries and are classified as GRAS (Generally regarded as safe) substances or are permitted food additives. A large number of these compounds have been the subject of extensive toxicological scrutiny. However, their principal function is to impart desirable flavours and aromas and not necessarily to act as antimicrobial agents. Given the high flavour and aroma impact to plant essential oils, the future for using these compound as food preservatives lies in the careful selection and evaluation of their efficacy at low concentrations but in combination with other chemical preservatives or preservation processes. For this reason they are worth of study alone or in combination with processing methods in order to establish if they could extend the shelf-life of foods. In this study, the effect of the spices, clove, turmeric, cardamom, oregano, rosemary and garlic in controlling the spoilage and pathogenic bacteria is investigated. Their effect on biogenic amine formation in tuna especially, histamine, as a result of bacterial control is also studied in detail. The contribution of spice oleoresin in the sensory and textural parameters is investigated using textural profile analysis and sensory panel. Finally, the potential of spices in quality stabilization and in increasing the shelf–life of tuna during frozen storage is analysed

Discrete wavelet transform de-noising in eukaryotic gene splicing

This paper compares the most common digital signal processing methods of exon prediction in eukaryotes, and also proposes a technique for noise suppression in exon prediction. The specimen used here which has relevance in medical research, has been taken from the public genomic database - GenBank.Here exon prediction has been done using the digital signal processing methods viz. binary method, EIIP (electron-ion interaction psuedopotential) method and filter methods. Under filter method two filter designs, and two approaches using these two designs have been tried. The discrete wavelet transform has been used for de-noising of the exon plots.Results of exon prediction based on the methods mentioned above, which give values closest to the ones found in the NCBI database are given here. The exon plot de-noised using discrete wavelet transform is also given.Alterations to the proven methods as done by the authors, improves performance of exon prediction algorithms. Also it has been proven that the discrete wavelet transform is an effective tool for de-noising which can be used with exon prediction algorithms

Characterization of Wastes from Natural Rubber and Rubber Wood Processing Industries and Their Utilization for Biomethanation

The research work which was carried out to characterization of wastes from natural rubber and rubber wood processing industries and their utilization for biomethanation. Environmental contamination is an inevitable consequence of human activity. The liquid and solid wastes from natural rubber based industries were: characterized and their use for the production of biogas investigated with a view to conserve conventional energy, and to mitigate environmental degradation.Rubber tree (flevea brasiliensis Muell. Arg.), is the most important commercial source of natural rubber and in india. Recently, pollution from the rubber processing factories has become very serious due to the introduction of modern methods and centralized group processing practices.The possibility of the use of spent slurry as organic manure is discussed.l0 percent level of PSD, the activity of cellulolytic, acid producing,proteolytic, lipolytic and methanogenic bacteria were more in the middle stage of methanogenesis.the liquid wastes from rubber processing used as diluents in combination with PSD, SPE promoted more biogas production with high methane content in the gas.The factors that favour methane production like TS, VS, cellulose and hemicellulose degradation were favoured in this treatment which led to higher methane biogenesis.The results further highlight ways and means to use agricultural wastes as alternative sources of energy.

Processing, procurement and marketing of pepper with particular reference to co-operative sector

The present Study is designed to gather, record and analyse data on history of pepper, pepper production, procurement and marketing with particular reference to Kerala. The main emphasis is given to study the'role of cooperative sector with regard to procurement and export efforts and also the services rendered by cooperative sector agencies under MARKETFED and NAFED to pepper trade. The scope of the Study covers the botany, methods of cultivation, fertilizer application, pest control management and other related aspects of pepper. Taking into consideration Kerala's supremacy in pepper cultivation and production, detailed study of its production, procurement, internal and export marketing with reference to Kerala has been given importance. As Kerala accounts for 96 per cent1 of the pepper cultivation and 94 per cent of the pepper production, the present study is entirely confined to Kerala

Studies on the treatment of effluents from natural rubber processing units

The present study was undertaken to evaluate the effectiveness of a few physico-chemical and biological methods for the treatment of effluents from natural rubber processing units. The overall objective of this study is to evaluate the effectiveness of certain physico-chemical and biological methods for the treatment of effluents from natural rubber processing units. survey of the chemical characteristics of the effluents discharged from rubber processing units showed that the effluents from latex concentration units were the most polluting

Development of solar air heaters & thermal energy storage system for drying applications in food processing industries

In the present work, the author has designed and developed all types of solar air heaters called porous and nonporous collectors. The developed solar air heaters were subjected to different air mass flow rates in order to standardize the flow per unit area of the collector. Much attention was given to investigate the performance of the solar air heaters fitted with baffles. The output obtained from the experiments on pilot models, helped the installation of solar air heating system for industrial drying applications also. Apart from these, various types of solar dryers, for small and medium scale drying applications, were also built up. The feasibility of ‘latent heat thermal energy storage system’ based on Phase Change Material was also undertaken. The application of solar greenhouse for drying industrial effluent was analyzed in the present study and a solar greenhouse was developed. The effectiveness of Computational Fluid Dynamics (CFD) in the field of solar air heaters was also analyzed. The thesis is divided into eight chapters.

Document Image Segmentation and Compression using Artificial Neural Networks and Evolutionary Methods

The work is intended to study the following important aspects of document image processing and develop new methods. (1) Segmentation ofdocument images using adaptive interval valued neuro-fuzzy method. (2) Improving the segmentation procedure using Simulated Annealing technique. (3) Development of optimized compression algorithms using Genetic Algorithm and parallel Genetic Algorithm (4) Feature extraction of document images (5) Development of IV fuzzy rules. This work also helps for feature extraction and foreground and background identification. The proposed work incorporates Evolutionary and hybrid methods for segmentation and compression of document images. A study of different neural networks used in image processing, the study of developments in the area of fuzzy logic etc is carried out in this work

Modified Block Adaptive Predictive Coder For Speech Processing

This thesis investigated the potential use of Linear Predictive Coding in speech communication applications. A Modified Block Adaptive Predictive Coder is developed, which reduces the computational burden and complexity without sacrificing the speech quality, as compared to the conventional adaptive predictive coding (APC) system. For this, changes in the evaluation methods have been evolved. This method is as different from the usual APC system in that the difference between the true and the predicted value is not transmitted. This allows the replacement of the high order predictor in the transmitter section of a predictive coding system, by a simple delay unit, which makes the transmitter quite simple. Also, the block length used in the processing of the speech signal is adjusted relative to the pitch period of the signal being processed rather than choosing a constant length as hitherto done by other researchers. The efficiency of the newly proposed coder has been supported with results of computer simulation using real speech data. Three methods for voiced/unvoiced/silent/transition classification have been presented. The first one is based on energy, zerocrossing rate and the periodicity of the waveform. The second method uses normalised correlation coefficient as the main parameter, while the third method utilizes a pitch-dependent correlation factor. The third algorithm which gives the minimum error probability has been chosen in a later chapter to design the modified coder The thesis also presents a comparazive study beh-cm the autocorrelation and the covariance methods used in the evaluaiicn of the predictor parameters. It has been proved that the azztocorrelation method is superior to the covariance method with respect to the filter stabf-it)‘ and also in an SNR sense, though the increase in gain is only small. The Modified Block Adaptive Coder applies a switching from pitch precitzion to spectrum prediction when the speech segment changes from a voiced or transition region to an unvoiced region. The experiments cont;-:ted in coding, transmission and simulation, used speech samples from .\£=_‘ajr2_1a:r1 and English phrases. Proposal for a speaker reecgnifion syste: and a phoneme identification system has also been outlized towards the end of the thesis.

" Nonlinear Signal Processing of Electroencephalogram .' Application in the Study of Neurodynamics. "

Interfacings of various subjects generate new field ofstudy and research that help in advancing human knowledge. One of the latest of such fields is Neurotechnology, which is an effective amalgamation of neuroscience, physics, biomedical engineering and computational methods. Neurotechnology provides a platform to interact physicist; neurologist and engineers to break methodology and terminology related barriers. Advancements in Computational capability, wider scope of applications in nonlinear dynamics and chaos in complex systems enhanced study of neurodynamics. However there is a need for an effective dialogue among physicists, neurologists and engineers. Application of computer based technology in the field of medicine through signal and image processing, creation of clinical databases for helping clinicians etc are widely acknowledged. Such synergic effects between widely separated disciplines may help in enhancing the effectiveness of existing diagnostic methods. One of the recent methods in this direction is analysis of electroencephalogram with the help of methods in nonlinear dynamics. This thesis is an effort to understand the functional aspects of human brain by studying electroencephalogram. The algorithms and other related methods developed in the present work can be interfaced with a digital EEG machine to unfold the information hidden in the signal. Ultimately this can be used as a diagnostic tool.

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.