16 resultados para statistical study
em Cochin University of Science
Resumo:
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
Resumo:
The study makes an attempt to examine the inter regional variations in Kerala in economic development with respect to the important indicators of development over the period 1971 to 2001. The study takes districts as the unit of analysis because this is an attempt to find out the status of districts in Kerala.The study proved that there exists inter district disparities in economic development measured in terms of different indices used for analysis.. statistical estimation of variation proves that there is high degree of variation in industrial sector followed by social and economic infrastructure. The composite index of industrial development shows that the highest index is 1.395 which is five times greater than that of the lowest index 0.273. More or less the same pattern of differences are noticed in most of the indicators of the development. A ranking of the district on the basis of the overall development indicators shows that Malappuram is the least developed district in Kerala. In case of almost all indicators of development Malappuram is lagging behind all other districts.
Resumo:
The standard models for statistical signal extraction assume that the signal and noise are generated by linear Gaussian processes. The optimum filter weights for those models are derived using the method of minimum mean square error. In the present work we study the properties of signal extraction models under the assumption that signal/noise are generated by symmetric stable processes. The optimum filter is obtained by the method of minimum dispersion. The performance of the new filter is compared with their Gaussian counterparts by simulation.
Resumo:
Information and communication technologies are the tools that underpin the emerging “Knowledge Society”. Exchange of information or knowledge between people and through networks of people has always taken place. But the ICT has radically changed the magnitude of this exchange, and thus factors such as timeliness of information and information dissemination patterns have become more important than ever.Since information and knowledge are so vital for the all round human development, libraries and institutions that manage these resources are indeed invaluable. So, the Library and Information Centres have a key role in the acquisition, processing, preservation and dissemination of information and knowledge. ln the modern context, library is providing service based on different types of documents such as manuscripts, printed, digital, etc. At the same time, acquisition, access, process, service etc. of these resources have become complicated now than ever before. The lCT made instrumental to extend libraries beyond the physical walls of a building and providing assistance in navigating and analyzing tremendous amounts of knowledge with a variety of digital tools. Thus, modern libraries are increasingly being re-defined as places to get unrestricted access to information in many formats and from many sources.The research was conducted in the university libraries in Kerala State, India. lt was identified that even though the information resources are flooding world over and several technologies have emerged to manage the situation for providing effective services to its clientele, most of the university libraries in Kerala were unable to exploit these technologies at maximum level. Though the libraries have automated many of their functions, wide gap prevails between the possible services and provided services. There are many good examples world over in the application of lCTs in libraries for the maximization of services and many such libraries have adopted the principles of reengineering and re-defining as a management strategy. Hence this study was targeted to look into how effectively adopted the modern lCTs in our libraries for maximizing the efficiency of operations and services and whether the principles of re-engineering and- redefining can be applied towards this.Data‘ was collected from library users, viz; student as well as faculty users; library ,professionals and university librarians, using structured questionnaires. This has been .supplemented by-observation of working of the libraries, discussions and interviews with the different types of users and staff, review of literature, etc. Personal observation of the organization set up, management practices, functions, facilities, resources, utilization of information resources and facilities by the users, etc. of the university libraries in Kerala have been made. Statistical techniques like percentage, mean, weighted mean, standard deviation, correlation, trend analysis, etc. have been used to analyse data.All the libraries could exploit only a very few possibilities of modern lCTs and hence they could not achieve effective Universal Bibliographic Control and desired efficiency and effectiveness in services. Because of this, the users as well as professionals are dissatisfied. Functional effectiveness in acquisition, access and process of information resources in various formats, development and maintenance of OPAC and WebOPAC, digital document delivery to remote users, Web based clearing of library counter services and resources, development of full-text databases, digital libraries and institutional repositories, consortia based operations for e-journals and databases, user education and information literacy, professional development with stress on lCTs, network administration and website maintenance, marketing of information, etc. are major areas need special attention to improve the situation. Finance, knowledge level on ICTs among library staff, professional dynamism and leadership, vision and support of the administrators and policy makers, prevailing educational set up and social environment in the state, etc. are some of the major hurdles in reaping the maximum possibilities of lCTs by the university libraries in Kerala. The principles of Business Process Re-engineering are found suitable to effectively apply to re-structure and redefine the operations and service system of the libraries. Most of the conventional departments or divisions prevailing in the university libraries were functioning as watertight compartments and their existing management system was more rigid to adopt the principles of change management. Hence, a thorough re-structuring of the divisions was indicated. Consortia based activities and pooling and sharing of information resources was advocated to meet the varied needs of the users in the main campuses and off campuses of the universities, affiliated colleges and remote stations. A uniform staff policy similar to that prevailing in CSIR, DRDO, ISRO, etc. has been proposed by the study not only in the university libraries in kerala but for the entire country.Restructuring of Lis education,integrated and Planned development of school,college,research and public library systems,etc.were also justified for reaping maximum benefits of the modern ICTs.
Resumo:
Learning Disability (LD) is a general term that describes specific kinds of learning problems. It is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. The learning disabled children are neither slow nor mentally retarded. This disorder can make it problematic for a child to learn as quickly or in the same way as some child who isn't affected by a learning disability. An affected child can have normal or above average intelligence. They may have difficulty paying attention, with reading or letter recognition, or with mathematics. It does not mean that children who have learning disabilities are less intelligent. In fact, many children who have learning disabilities are more intelligent than an average child. Learning disabilities vary from child to child. One child with LD may not have the same kind of learning problems as another child with LD. There is no cure for learning disabilities and they are life-long. However, children with LD can be high achievers and can be taught ways to get around the learning disability. In this research work, data mining using machine learning techniques are used to analyze the symptoms of LD, establish interrelationships between them and evaluate the relative importance of these symptoms. To increase the diagnostic accuracy of learning disability prediction, a knowledge based tool based on statistical machine learning or data mining techniques, with high accuracy,according to the knowledge obtained from the clinical information, is proposed. The basic idea of the developed knowledge based tool is to increase the accuracy of the learning disability assessment and reduce the time used for the same. Different statistical machine learning techniques in data mining are used in the study. Identifying the important parameters of LD prediction using the data mining techniques, identifying the hidden relationship between the symptoms of LD and estimating the relative significance of each symptoms of LD are also the parts of the objectives of this research work. The developed tool has many advantages compared to the traditional methods of using check lists in determination of learning disabilities. For improving the performance of various classifiers, we developed some preprocessing methods for the LD prediction system. A new system based on fuzzy and rough set models are also developed for LD prediction. Here also the importance of pre-processing is studied. A Graphical User Interface (GUI) is designed for developing an integrated knowledge based tool for prediction of LD as well as its degree. The designed tool stores the details of the children in the student database and retrieves their LD report as and when required. The present study undoubtedly proves the effectiveness of the tool developed based on various machine learning techniques. It also identifies the important parameters of LD and accurately predicts the learning disability in school age children. This thesis makes several major contributions in technical, general and social areas. The results are found very beneficial to the parents, teachers and the institutions. They are able to diagnose the child’s problem at an early stage and can go for the proper treatments/counseling at the correct time so as to avoid the academic and social losses.
Resumo:
Information communication technology (IC T) has invariably brought about fundamental changes in the way in which libraries gather. preserve and disseminate information. The study was carried out with an aim to estimate and compare the information seeking behaviour (ISB) of the academics of two prominent universities of Kerala in the context of advancements achieved through ICT. The study was motivated by the fast changing scenario of libraries with the proliferation of many high tech products and services. The main purpose of the study was to identify the chief source of information of the academics, and also to examine academics preference upon the form and format of information source. The study also tries to estimate the adequacy of the resources and services currently provided by the libraries.The questionnaire was the central instrument for data collection. An almost census method was adopted for data collection engaging various methods and tools for eliciting data.The total population of the study was 957, out of which questionnaire was distributed to 859 academics. 646 academics responded to the survey, of which 564 of them were sound responses. Data was coded and analysed using Statistical Package for Social Sciences (SPSS) software and also with the help of Microsofl Excel package. Various statistical techniques were engaged to analyse data. A paradigm shift is evident by the fact that academies push themselves towards information in internet i.e. they prefer electronic source to traditional source and the very shift is coupled itself with e-seeking of information. The study reveals that ISB of the academics is influenced priman'ly by personal factors and comparative analysis shows that the ISB ofthc academics is similar in both universities. The productivity of the academics was tested to dig up any relation with respect to their ISB, and it is found that productivity of the academics is extensively related with their ISB. Study also reveals that the users ofthe library are satisfied with the services provided but not with the sources and in conjunction, study also recommends ways and means to improve the existing library system.
Resumo:
The overall focus of the thesis involves the International trade and cochin port a historical and statistical analysis 1881-1980.Analysing the trend of exports and imports through cochin port during the course of the last hundred years .This analysis has brought to light some very pertinent facts which , in our opinion,deserve serious consideration of the policy makers,the partise involved in trade and those who are interested in the development of the cochin port.Our study is restricted to twelve commodities -ten commodities of exports and two commodities of imports.The study reveals that the commodities that were exported from cochin are subjected to fluctuations -some mild and others wild. The projections only indicate the potential and unless we are very cautious the chance will be taken away by our competitors .With reference to the development of the port in particular and the states economy in general we would like to make a suggestion .This suggestion relates to declaring cochin as a free port .This will go a long way in the develppment of the port and the state's economy.The sooner it is done the better for the port and the state.
Resumo:
Mathematical models are often used to describe physical realities. However, the physical realities are imprecise while the mathematical concepts are required to be precise and perfect. Even mathematicians like H. Poincare worried about this. He observed that mathematical models are over idealizations, for instance, he said that only in Mathematics, equality is a transitive relation. A first attempt to save this situation was perhaps given by K. Menger in 1951 by introducing the concept of statistical metric space in which the distance between points is a probability distribution on the set of nonnegative real numbers rather than a mere nonnegative real number. Other attempts were made by M.J. Frank, U. Hbhle, B. Schweizer, A. Sklar and others. An aspect in common to all these approaches is that they model impreciseness in a probabilistic manner. They are not able to deal with situations in which impreciseness is not apparently of a probabilistic nature. This thesis is confined to introducing and developing a theory of fuzzy semi inner product spaces.
Resumo:
Some investigations on the spectral and statistical characteristics of deep water waves are available for Indian waters. But practically no systematic investigation on the shallow water wave spectral and probabilistic characteristics is made for any part of the Indian coast except for a few restricted studies. Hence a comprehensive study of the shallow water wave climate and their spectral and statistical characteristics for a location (Alleppey) along the southwest coast of India is undertaken based on recorded data. The results of the investigation are presented in this thesis.The thesis comprises of seven chapters
Resumo:
The study is intended to estimate the existing rate of participation of women beneficiaries in the development programmes of different organisations in Kerala. It would enable one to understand whether participation is at the satisfactory level or not. Given the rate of participation, the major thrust of the analysis is on the impact of governmental and non-governmental organisations on the rate of participation. This is undertaken under the assumption that NGOs, due to their proximity to people and their needs, ensure better participation rates. Besides the organisational differences, the other major determinants of women participation such as their socio-economic characteristics, psychological make up, the nature of the programme etc. are also highlighted. 0 Since the ascribed status of women in society is inferior, the role of organisers, development personnel and local leaders is also pointed out. Thus the basic objective of the study is women participation and its determinants in the development programmes
Resumo:
Severe local storms, including tornadoes, damaging hail and wind gusts, frequently occur over the eastern and northeastern states of India during the pre-monsoon season (March-May). Forecasting thunderstorms is one of the most difficult tasks in weather prediction, due to their rather small spatial and temporal extension and the inherent non-linearity of their dynamics and physics. In this paper, sensitivity experiments are conducted with the WRF-NMM model to test the impact of convective parameterization schemes on simulating severe thunderstorms that occurred over Kolkata on 20 May 2006 and 21 May 2007 and validated the model results with observation. In addition, a simulation without convective parameterization scheme was performed for each case to determine if the model could simulate the convection explicitly. A statistical analysis based on mean absolute error, root mean square error and correlation coefficient is performed for comparisons between the simulated and observed data with different convective schemes. This study shows that the prediction of thunderstorm affected parameters is sensitive to convective schemes. The Grell-Devenyi cloud ensemble convective scheme is well simulated the thunderstorm activities in terms of time, intensity and the region of occurrence of the events as compared to other convective schemes and also explicit scheme
Resumo:
Low grade and High grade Gliomas are tumors that originate in the glial cells. The main challenge in brain tumor diagnosis is whether a tumor is benign or malignant, primary or metastatic and low or high grade. Based on the patient's MRI, a radiologist could not differentiate whether it is a low grade Glioma or a high grade Glioma. Because both of these are almost visually similar, autopsy confirms the diagnosis of low grade with high-grade and infiltrative features. In this paper, textural description of Grade I and grade III Glioma are extracted using First order statistics and Gray Level Co-occurance Matrix Method (GLCM). Textural features are extracted from 16X16 sub image of the segmented Region of Interest(ROI) .In the proposed method, first order statistical features such as contrast, Intensity , Entropy, Kurtosis and spectral energy and GLCM features extracted were showed promising results. The ranges of these first order statistics and GLCM based features extracted are highly discriminant between grade I and Grade III. In this study which gives statistical textural information of grade I and grade III Glioma which is very useful for further classification and analysis and thus assisting Radiologist in greater extent.
Resumo:
Econometrics is a young science. It developed during the twentieth century in the mid-1930’s, primarily after the World War II. Econometrics is the unification of statistical analysis, economic theory and mathematics. The history of econometrics can be traced to the use of statistical and mathematics analysis in economics. The most prominent contributions during the initial period can be seen in the works of Tinbergen and Frisch, and also that of Haavelmo in the 1940's through the mid 1950's. Right from the rudimentary application of statistics to economic data, like the use of laws of error through the development of least squares by Legendre, Laplace, and Gauss, the discipline of econometrics has later on witnessed the applied works done by Edge worth and Mitchell. A very significant mile stone in its evolution has been the work of Tinbergen, Frisch, and Haavelmo in their development of multiple regression and correlation analysis. They used these techniques to test different economic theories using time series data. In spite of the fact that some predictions based on econometric methodology might have gone wrong, the sound scientific nature of the discipline cannot be ignored by anyone. This is reflected in the economic rationale underlying any econometric model, statistical and mathematical reasoning for the various inferences drawn etc. The relevance of econometrics as an academic discipline assumes high significance in the above context. Because of the inter-disciplinary nature of econometrics (which is a unification of Economics, Statistics and Mathematics), the subject can be taught at all these broad areas, not-withstanding the fact that most often Economics students alone are offered this subject as those of other disciplines might not have adequate Economics background to understand the subject. In fact, even for technical courses (like Engineering), business management courses (like MBA), professional accountancy courses etc. econometrics is quite relevant. More relevant is the case of research students of various social sciences, commerce and management. In the ongoing scenario of globalization and economic deregulation, there is the need to give added thrust to the academic discipline of econometrics in higher education, across various social science streams, commerce, management, professional accountancy etc. Accordingly, the analytical ability of the students can be sharpened and their ability to look into the socio-economic problems with a mathematical approach can be improved, and enabling them to derive scientific inferences and solutions to such problems. The utmost significance of hands-own practical training on the use of computer-based econometric packages, especially at the post-graduate and research levels need to be pointed out here. Mere learning of the econometric methodology or the underlying theories alone would not have much practical utility for the students in their future career, whether in academics, industry, or in practice This paper seeks to trace the historical development of econometrics and study the current status of econometrics as an academic discipline in higher education. Besides, the paper looks into the problems faced by the teachers in teaching econometrics, and those of students in learning the subject including effective application of the methodology in real life situations. Accordingly, the paper offers some meaningful suggestions for effective teaching of econometrics in higher education
Resumo:
The distribution and accumulation of trace metals in the sediments of the Cochin estuary during the pre-monsoon, monsoon and post-monsoon periods were investigated. Sediment samples from 14 locations were collected and analysed for the metal contents (Mg, Cr, Mn, Fe, Co, Ni, Cu, Zn, Cd and Pb), organic carbon, total nitrogen, total sulphur and grain size. The data were processed using statistical tools like correlation, factor and cluster analysis. The study revealed an enrichment of Cd and Zn in the study area particularly at station 2, which is confirmed by enrichment factor, contamination factor and geoaccumulation index. The factor analysis revealed that the source of Cd and Zn may be same. The study indicated that the spatial variation for the metals like Mg, Cr, Fe, Co, Ni, Cu, Zn, Cd and Pb were predominant unlike Mn which shows a temporal variation. The strong association of trace metals with Fe and Mn hydroxides and oxides are prominent along the Cochin estuary. The anthropogenic inputs of industrial effluents mainly control the trace metals enrichment in the Cochin estuary
Resumo:
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.