Permutation Entropy Based Analysis of Complex Signals for Characterising Change in System Dynamics

Timely detection of sudden change in dynamics that adversely affect the performance of systems and quality of products has great scientific relevance. This work focuses on effective detection of dynamical changes of real time signals from mechanical as well as biological systems using a fast and robust technique of permutation entropy (PE). The results are used in detecting chatter onset in machine turning and identifying vocal disorders from speech signal.Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. Here we propose the use of permutation entropy (PE), to detect the dynamical changes in two non linear processes, turning under mechanical system and speech under biological system.Effectiveness of PE in detecting the change in dynamics in turning process from the time series generated with samples of audio and current signals is studied. Experiments are carried out on a lathe machine for sudden increase in depth of cut and continuous increase in depth of cut on mild steel work pieces keeping the speed and feed rate constant. The results are applied to detect chatter onset in machining. These results are verified using frequency spectra of the signals and the non linear measure, normalized coarse-grained information rate (NCIR).PE analysis is carried out to investigate the variation in surface texture caused by chatter on the machined work piece. Statistical parameter from the optical grey level intensity histogram of laser speckle pattern recorded using a charge coupled device (CCD) camera is used to generate the time series required for PE analysis. Standard optical roughness parameter is used to confirm the results.Application of PE in identifying the vocal disorders is studied from speech signal recorded using microphone. Here analysis is carried out using speech signals of subjects with different pathological conditions and normal subjects, and the results are used for identifying vocal disorders. Standard linear technique of FFT is used to substantiate thc results.The results of PE analysis in all three cases clearly indicate that this complexity measure is sensitive to change in regularity of a signal and hence can suitably be used for detection of dynamical changes in real world systems. This work establishes the application of the simple, inexpensive and fast algorithm of PE for the benefit of advanced manufacturing process as well as clinical diagnosis in vocal disorders.

‘Reliability Concepts in Quantile-based Analysis of Lifetime Data

Reliability analysis is a well established branch of statistics that deals with the statistical study of different aspects of lifetimes of a system of components. As we pointed out earlier that major part of the theory and applications in connection with reliability analysis were discussed based on the measures in terms of distribution function. In the beginning chapters of the thesis, we have described some attractive features of quantile functions and the relevance of its use in reliability analysis. Motivated by the works of Parzen (1979), Freimer et al. (1988) and Gilchrist (2000), who indicated the scope of quantile functions in reliability analysis and as a follow up of the systematic study in this connection by Nair and Sankaran (2009), in the present work we tried to extend their ideas to develop necessary theoretical framework for lifetime data analysis. In Chapter 1, we have given the relevance and scope of the study and a brief outline of the work we have carried out. Chapter 2 of this thesis is devoted to the presentation of various concepts and their brief reviews, which were useful for the discussions in the subsequent chapters .In the introduction of Chapter 4, we have pointed out the role of ageing concepts in reliability analysis and in identifying life distributions .In Chapter 6, we have studied the first two L-moments of residual life and their relevance in various applications of reliability analysis. We have shown that the first L-moment of residual function is equivalent to the vitality function, which have been widely discussed in the literature .In Chapter 7, we have defined percentile residual life in reversed time (RPRL) and derived its relationship with reversed hazard rate (RHR). We have discussed the characterization problem of RPRL and demonstrated with an example that the RPRL for given does not determine the distribution uniquely

A Quantile based analysis of income data

Dept. of Statistics, CUSAT

Analysis of System Signals Based on Cross Recurrence Method for System Dynamics Characterization

Natural systems are inherently non linear. Recurrent behaviours are typical of natural systems. Recurrence is a fundamental property of non linear dynamical systems which can be exploited to characterize the system behaviour effectively. Cross recurrence based analysis of sensor signals from non linear dynamical system is presented in this thesis. The mutual dependency among relatively independent components of a system is referred as coupling. The analysis is done for a mechanically coupled system specifically designed for conducting experiment. Further, cross recurrence method is extended to the actual machining process in a lathe to characterize the chatter during turning. The result is verified by permutation entropy method. Conventional linear methods or models are incapable of capturing the critical and strange behaviours associated with the dynamical process. Hence any effective feature extraction methodologies should invariably gather information thorough nonlinear time series analysis. The sensor signals from the dynamical system normally contain noise and non stationarity. In an effort to get over these two issues to the maximum possible extent, this work adopts the cross recurrence quantification analysis (CRQA) methodology since it is found to be robust against noise and stationarity in the signals. The study reveals that the CRQA is capable of characterizing even weak coupling among system signals. It also divulges the dependence of certain CRQA variables like percent determinism, percent recurrence and entropy to chatter unambiguously. The surrogate data test shows that the results obtained by CRQA are the true properties of the temporal evolution of the dynamics and contain a degree of deterministic structure. The results are verified using permutation entropy (PE) to detect the onset of chatter from the time series. The present study ascertains that this CRP based methodology is capable of recognizing the transition from regular cutting to the chatter cutting irrespective of the machining parameters or work piece material. The results establish this methodology to be feasible for detection of chatter in metal cutting operation in a lathe.

Standard of Living and Community Perception in the Community Based Ecotourism (CBET) Sites of Kerala: An Inter Zone Analysis

This study is an attempt to situate the quality of life and standard of living of local communities in ecotourism destinations inter alia their perception on forest conservation and the satisfaction level of the local community. 650 EDC/VSS members from Kerala demarcated into three zones constitute the data source. Four variables have been considered for evaluating the quality of life of the stakeholders of ecotourism sites, which is then funneled to the income-education spectrum for hypothesizing into the SLI framework. Zone-wise analysis of the community members working in tourism sector shows that the community members have benefited totally from tourism development in the region as they have got both employments as well as secured livelihood options. Most of the quality of life-indicators of the community in the eco-tourist centres show a promising position. The community perception does not show any negative impact on environment as well as on their local culture.

Analysis and Testing of a Novel Oadm Based on FBG and Machzehnder Interferometer

A novel optical add-drop multiplexer (OADM) based on the Mach-Zelauler interferometer (MZI) and the fiber Bragg grating (FBG) is proposed for the first tittle to the authors ' knowledge. In the structure, the Mach-Zehnder interferometer acts as an optical switch. The principle of the OADM is analyzed in this paper. The OADM can add/drop one of the multi-input channels or pass the channel directly by adjusting the difference of the two arms of the interferometer. The channel isolation is more than 20 dB

Dynamic mechanical analysis of binary and ternary polymer blends based on nylon copolymer/EPDM rubber and EPM grafted maleic anhydride compatibilizer

The dynamic mechanical properties such as storage modulus, loss modulus and damping properties of blends of nylon copolymer (PA6,66) with ethylene propylene diene (EPDM) rubber was investigated with special reference to the effect of blend ratio and compatibilisation over a temperature range –100°C to 150°C at different frequencies. The effect of change in the composition of the polymer blends on tanδ was studied to understand the extent of polymer miscibility and damping characteristics. The loss tangent curve of the blends exhibited two transition peaks, corresponding to the glass transition temperature (Tg) of individual components indicating incompatibility of the blend systems. The morphology of the blends has been examined by using scanning electron microscopy. The Arrhenius relationship was used to calculate the activation energy for the glass transition of the blends. Finally, attempts have been made to compare the experimental data with theoretical models.

Neural Network based studies on Spectroscopic Analysis and Image Processing

International School of Photonics, Cochin University of Science and Technology

Farm Programmes of Electronic Media: A Comparative Study of Audience Perception in Kerala

Farm communication and extension programs are vital part of the farm development attempts. Electronic media plays a major role in farm extension activities. Kerala, the consumer state, which was a complete agricultural state in pre-independence period, is the sprouting land of agricultural extension and publication activities in print media. Later AIR (All India Radio) farm programs and farm broadcasting of Doordarshan enriched the role of electronic media in farm extension activities. The media saturated southern state of India received this new electronic media farm communication revolution whole heartedly. However, after 1990, Kerala witnessed a flood of private T V channels and currently there are 24 channels in this regional language, named Malayalam. All major news and entertainment channels are broadcasting farm programs. Farm programs of AIR and Doordarshan, broadcasted in Malayalam language, have been well accepted to the farmers‘ in Kerala. However, post-independence period, witnessed the formation of Kerala state in Indian Union and the first ballot-elected communist Government started its administration. After the land reform bills, the state witnessed a gradual decrease in agricultural production. Even if it is not reflected much in the attitude and practices of farm community and farm broadcast of traditional electronic broadcasting, a change is observable after the post-liberalization era of India. Private Television channels, which were focused on entertainment value of programs, started broadcasting farm programs and the parameters of program production went through certain changes. In this situation, there is ample relevance for a study about the farm programs of electronic media in terms of a comparative study of audience perception. The study is limited in the state of Kerala as it is the most media saturated state in India. The study analyzes the rate, nature and scope of adoption of farming methods transmitted through electronic media (T.V. and Radio) in Malayalam language.All kinds of Farm programs including comprehensive program serials, success stories, seasonal cropping methods, experts opinion, been analyzed on the basis of the following objectives.  To find whether propagating new farm methods through farm programs in electronic media or the availability of adequate infrastructure and economic factors make a farmer to adopt a new farming method.  To find which electronic media has more influence on farmers to adopt agricultural programs.  To find which form of electronic media gets better feedback from farmers  To find out whether the programs of T.V. or Radio is more acceptable to farmers than the print media.  To find whether farmers gets the message through their preferred medium for the message. The researcher recorded opinions from a panel of agricultural officers, farm Information officers, agro extension researchers and experts. According to their opinions and guidelines, a pilot study is designed and conducted in Kanjikuzhy Panchayath, in Alappuzha district, Kerala. The Panchayath is selected by considering its ideal nature of being the sample for a social Science research. Besides, the nature of farming in the Panchayath, which devoid of the cultivation of cash crops also supported its sample value. As per the observations from the pilot study, researcher confirmed the Triangulation method as the methodology of research. The questionnaire survey, being the primary part contained 42 Questions with 6 independent and 32 dependent variables. The survey is conducted among 400 respondents in Idukki, Alappuzha and Pathanamthitta districts considering geographical differences and distribution of different types of crops. The response from a total of 360 respondents, 120 from each district, finally selected for tabulation and data analysis.The data analysis, based on percentage analysis, along with the results from focus group discussion among a selected group of 20 farmers, together produced the results as follows. Farmers, who are the audience of farm programs, have a very serious approach towards the medium. They are maintaining a critical point of view towards the content of the programs. Farmers are reasonably aware about the financial side of the programs and the monitory aspirations of both private and Government owned Television channels. Even though, the farmers are not aware on the technical terminology and jargons, they have ideas about success stories, program serials and they are even informed about channels are not maintaining an audience research section like AIR. Though the farmers accept Doordarshan as the credential source of farm information and methods, they are inclined to the entertainment value of programs too. They prefer to have more entertainment value for the programs of Doordarshan. Surprisingly, they have very solid suggestions on even about the shots which add entertainment value to the farm broadcasting methods of Doordarshan. Farmers are very much aware about the fact that media is just an instrument for inspiration and persuasion. They strongly believe that the source of information and new methods is agricultural research and an effective change happens only when there are adequate infrastructure and marketing facilities, along with the proper support from Government agricultural guideline and support systems like Krishi Bhavans. They strongly believe that media alone cannot create any magic in increasing agricultural production. Farmers are pointing out the lack of response to the feedback and queries of farmers on farming methods, as an evidence for the difference in levels of commitment of Government and private owned Television channels.Farmers are still perceiving AIR farm programs are far more committed to farmers and farming than any other electronic medium. However, they are seriously lacking Radio receivers with medium wave reception facility. Farmers perceive that the farming methods on new crops are more adoptable than the farming methods of traditional crops in both private and Government owned Television channels. There are multiple factors behind this observation from farmers. Farmers changed in terms of viewing habits and they prefer success stories, which are totally irrelevant and they even think that such stories encourage people to go for farming and they opined that such stories are good sources of inspiration. However, they are all very much sure about the importance and particular about the presence of entertainment factor even in farm programs. Farmers expect direct interaction of any expert of the new farming method to implement the method in their agriculture practices. Though introduction of a new idea in the T.V. is acceptable, farmers need the direct instruction of expert on field to start implementing the new farming practices Farmers still have an affinity towards print media reports and agricultural pages and they have complaints to print media on the removal of agricultural information pages from news papers. They prefer the reports in print media as it facilitates them to collect and refer articles when they need it. Farmers are having an eye of doubt about the credibility of farm programs by private T.V. channels. Even if they prefer private Television channels for listening and adopting new farming methods and other farm information, they scrutinize programs to know whether they are sponsored programs by agrochemical or agro-fertilizer manufacturer.

Mean Squared Residue Based Biclustering Algorithms for the Analysis of Gene Expression Data

Computational Biology is the research are that contributes to the analysis of biological data through the development of algorithms which will address significant research problems.The data from molecular biology includes DNA,RNA ,Protein and Gene expression data.Gene Expression Data provides the expression level of genes under different conditions.Gene expression is the process of transcribing the DNA sequence of a gene into mRNA sequences which in turn are later translated into proteins.The number of copies of mRNA produced is called the expression level of a gene.Gene expression data is organized in the form of a matrix. Rows in the matrix represent genes and columns in the matrix represent experimental conditions.Experimental conditions can be different tissue types or time points.Entries in the gene expression matrix are real values.Through the analysis of gene expression data it is possible to determine the behavioral patterns of genes such as similarity of their behavior,nature of their interaction,their respective contribution to the same pathways and so on. Similar expression patterns are exhibited by the genes participating in the same biological process.These patterns have immense relevance and application in bioinformatics and clinical research.Theses patterns are used in the medical domain for aid in more accurate diagnosis,prognosis,treatment planning.drug discovery and protein network analysis.To identify various patterns from gene expression data,data mining techniques are essential.Clustering is an important data mining technique for the analysis of gene expression data.To overcome the problems associated with clustering,biclustering is introduced.Biclustering refers to simultaneous clustering of both rows and columns of a data matrix. Clustering is a global whereas biclustering is a local model.Discovering local expression patterns is essential for identfying many genetic pathways that are not apparent otherwise.It is therefore necessary to move beyond the clustering paradigm towards developing approaches which are capable of discovering local patterns in gene expression data.A biclusters is a submatrix of the gene expression data matrix.The rows and columns in the submatrix need not be contiguous as in the gene expression data matrix.Biclusters are not disjoint.Computation of biclusters is costly because one will have to consider all the combinations of columans and rows in order to find out all the biclusters.The search space for the biclustering problem is 2 m+n where m and n are the number of genes and conditions respectively.Usually m+n is more than 3000.The biclustering problem is NP-hard.Biclustering is a powerful analytical tool for the biologist.The research reported in this thesis addresses the problem of biclustering.Ten algorithms are developed for the identification of coherent biclusters from gene expression data.All these algorithms are making use of a measure called mean squared residue to search for biclusters.The objective here is to identify the biclusters of maximum size with the mean squared residue lower than a given threshold. All these algorithms begin the search from tightly coregulated submatrices called the seeds.These seeds are generated by K-Means clustering algorithm.The algorithms developed can be classified as constraint based,greedy and metaheuristic.Constarint based algorithms uses one or more of the various constaints namely the MSR threshold and the MSR difference threshold.The greedy approach makes a locally optimal choice at each stage with the objective of finding the global optimum.In metaheuristic approaches particle Swarm Optimization(PSO) and variants of Greedy Randomized Adaptive Search Procedure(GRASP) are used for the identification of biclusters.These algorithms are implemented on the Yeast and Lymphoma datasets.Biologically relevant and statistically significant biclusters are identified by all these algorithms which are validated by Gene Ontology database.All these algorithms are compared with some other biclustering algorithms.Algorithms developed in this work overcome some of the problems associated with the already existing algorithms.With the help of some of the algorithms which are developed in this work biclusters with very high row variance,which is higher than the row variance of any other algorithm using mean squared residue, are identified from both Yeast and Lymphoma data sets.Such biclusters which make significant change in the expression level are highly relevant biologically.

“Urban Water Supply Management: A Study Of Centralised And Community Based Systems In Calicut City

Studies in urban water supply system are few in the state of Kerala. It is a little researched area. In the case of water pricing a number of studies are available. In Kerala state, exception to Jacob John’s study on “Economics of Public Water Supply System”, which is a case study of Trivandrum Water Supply System in 1997, no exhaustive research work has so far come out in this field. loreover no indepth research study has come up, so far, relating to household ater demand analysis and the distribution system of urban piped water supply. he proposed study is first of its kind, which focuses on the distributional and Iailability problems of piped water supply in an urban centre in Kerala state. Hence there is a felt need for enquiring into the sufficiency of )table water supplied to people in urban areas and the efficiency maintained in roviding the scarce resource and preventing its misuse by the consumers. It is in llS backdrop that this study was undertaken and its empirical part was conducted |Calicut city in the state of Kerala. Study is confined to the water supply system ithe city of Calicut

Development of a Fully Automated Image Analysis Method for High Density cDNA and array CGH Microarray Based Genomic Studies

In this thesis, different techniques for image analysis of high density microarrays have been investigated. Most of the existing image analysis techniques require prior knowledge of image specific parameters and direct user intervention for microarray image quantification. The objective of this research work was to develop of a fully automated image analysis method capable of accurately quantifying the intensity information from high density microarrays images. The method should be robust against noise and contaminations that commonly occur in different stages of microarray development.

Brain Tissue Classification from Multispectral MRI by Wavelet based Principal Component Analysis

In this paper, we propose a multispectral analysis system using wavelet based Principal Component Analysis (PCA), to improve the brain tissue classification from MRI images. Global transforms like PCA often neglects significant small abnormality details, while dealing with a massive amount of multispectral data. In order to resolve this issue, input dataset is expanded by detail coefficients from multisignal wavelet analysis. Then, PCA is applied on the new dataset to perform feature analysis. Finally, an unsupervised classification with Fuzzy C-Means clustering algorithm is used to measure the improvement in reproducibility and accuracy of the results. A detailed comparative analysis of classified tissues with those from conventional PCA is also carried out. Proposed method yielded good improvement in classification of small abnormalities with high sensitivity/accuracy values, 98.9/98.3, for clinical analysis. Experimental results from synthetic and clinical data recommend the new method as a promising approach in brain tissue analysis.

Wavelet based Independent Component Analysis for Multispectral Brain Tissue Classification

Multispectral analysis is a promising approach in tissue classification and abnormality detection from Magnetic Resonance (MR) images. But instability in accuracy and reproducibility of the classification results from conventional techniques keeps it far from clinical applications. Recent studies proposed Independent Component Analysis (ICA) as an effective method for source signals separation from multispectral MR data. However, it often fails to extract the local features like small abnormalities, especially from dependent real data. A multisignal wavelet analysis prior to ICA is proposed in this work to resolve these issues. Best de-correlated detail coefficients are combined with input images to give better classification results. Performance improvement of the proposed method over conventional ICA is effectively demonstrated by segmentation and classification using k-means clustering. Experimental results from synthetic and real data strongly confirm the positive effect of the new method with an improved Tanimoto index/Sensitivity values, 0.884/93.605, for reproduced small white matter lesions