Cost accountancy and cost control in hospitals

It is a fact that there now exists a sound framework of accounting theory to ascertain the working results and the investment status of hospitals. Yet, there is no system of accounting in practice to conduct its activities with utmost efficiency. No attempts have hitherto been made for the continuous improvement in the servics rendered by hospitals. Personal investments in hospitals have made the interaction of business to some extent.Planning, decision making and control assume increasing importance as hospitals grow in size and complexity. Moreover, wise and effective utilisation of resources should be ensured. The importance of cost cannot be overlooked in this context. Cost is the most effective factor in the determination of the prices of hospital services rendered. The important managerial functions have to rely heavily on accurate and timely cost information. More people can be provided with services if no services cost more than what is a must to provide the necessary level of care. The price paid for high cost technology for a few is no technology at all for the many. Hence no pains must be spared in ascertaining, presenting, controlling and reducing costs. An effective system of Cost Accountancy and Cost Control is imperative for the survival of hospitals in the intensely competitive conditions of today. The valuable objective of "better patient care" can be attained only if the management can make use of the various tools and techniques to ascertain, control and reduce each item of cost in hospitals. Constant efforts must be made by the management to continuously improve their services and bring down costs and prices of all hospital services. Cost Accountancy has made its impresssive impact on almost all the spheres of human activities. It is high time a comprehensive Cost Accountancy and Cost Control system be implemented in hospitals. The problem under study thus is the designing of a sound and full-fledged Cost Accountancy and Cost Control system that suits the requirements of hospitals. It is for the first time in India during the evolution of Cost Accountancy that a comprehensive cost system is tried in hospitals.

Computing median and antimedian sets in median graphs

The median (antimedian) set of a profile π = (u1, . . . , uk) of vertices of a graphG is the set of vertices x that minimize (maximize) the remoteness i d(x,ui ). Two algorithms for median graphs G of complexity O(nidim(G)) are designed, where n is the order and idim(G) the isometric dimension of G. The first algorithm computes median sets of profiles and will be in practice often faster than the other algorithm which in addition computes antimedian sets and remoteness functions and works in all partial cubes

Econometrics as an Academic Discipline in Higher Education: An Exploratory Study of the Need, Relevance and Significance

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

Model Diagnostics in the presence of measurement error

The problem of using information available from one variable X to make inferenceabout another Y is classical in many physical and social sciences. In statistics this isoften done via regression analysis where mean response is used to model the data. Onestipulates the model Y = µ(X) +ɛ. Here µ(X) is the mean response at the predictor variable value X = x, and ɛ = Y - µ(X) is the error. In classical regression analysis, both (X; Y ) are observable and one then proceeds to make inference about the mean response function µ(X). In practice there are numerous examples where X is not available, but a variable Z is observed which provides an estimate of X. As an example, consider the herbicidestudy of Rudemo, et al. [3] in which a nominal measured amount Z of herbicide was applied to a plant but the actual amount absorbed by the plant X is unobservable. As another example, from Wang [5], an epidemiologist studies the severity of a lung disease, Y , among the residents in a city in relation to the amount of certain air pollutants. The amount of the air pollutants Z can be measured at certain observation stations in the city, but the actual exposure of the residents to the pollutants, X, is unobservable and may vary randomly from the Z-values. In both cases X = Z+error: This is the so called Berkson measurement error model.In more classical measurement error model one observes an unbiased estimator W of X and stipulates the relation W = X + error: An example of this model occurs when assessing effect of nutrition X on a disease. Measuring nutrition intake precisely within 24 hours is almost impossible. There are many similar examples in agricultural or medical studies, see e.g., Carroll, Ruppert and Stefanski [1] and Fuller [2], , among others. In this talk we shall address the question of fitting a parametric model to the re-gression function µ(X) in the Berkson measurement error model: Y = µ(X) + ɛ; X = Z + η; where η and ɛ are random errors with E(ɛ) = 0, X and η are d-dimensional, and Z is the observable d-dimensional r.v.

New studies on the versatile roles of Polyaniline and its composites in polymer based optoelectronic and energy storage devices

From the early stages of the twentieth century, polyaniline (PANI), a well-known and extensively studied conducting polymer has captured the attention of scientific community owing to its interesting electrical and optical properties. Starting from its structural properties, to the currently pursued optical, electrical and electrochemical properties, extensive investigations on pure PANI and its composites are still much relevant to explore its potentialities to the maximum extent. The synthesis of highly crystalline PANI films with ordered structure and high electrical conductivity has not been pursued in depth yet. Recently, nanostructured PANI and the nanocomposites of PANI have attracted a great deal of research attention owing to the possibilities of applications in optical switching devices, optoelectronics and energy storage devices. The work presented in the thesis is centered around the realization of highly conducting and structurally ordered PANI and its composites for applications mainly in the areas of nonlinear optics and electrochemical energy storage. Out of the vast variety of application fields of PANI, these two areas are specifically selected for the present studies, because of the following observations. The non-linear optical properties and the energy storing properties of PANI depend quite sensitively on the extent of conjugation of the polymer structure, the type and concentration of the dopants added and the type and size of the nano particles selected for making the nanocomposites. The first phase of the work is devoted to the synthesis of highly ordered and conducting films of PANI doped with various dopants and the structural, morphological and electrical characterization followed by the synthesis of metal nanoparticles incorporated PANI samples and the detailed optical characterization in the linear and nonlinear regimes. The second phase of the work comprises the investigations on the prospects of PANI in realizing polymer based rechargeable lithium ion cells with the inherent structural flexibility of polymer systems and environmental safety and stability. Secondary battery systems have become an inevitable part of daily life. They can be found in most of the portable electronic gadgets and recently they have started powering automobiles, although the power generated is low. The efficient storage of electrical energy generated from solar cells is achieved by using suitable secondary battery systems. The development of rechargeable battery systems having excellent charge storage capacity, cyclability, environmental friendliness and flexibility has yet to be realized in practice. Rechargeable Li-ion cells employing cathode active materials like LiCoO2, LiMn2O4, LiFePO4 have got remarkable charge storage capacity with least charge leakage when not in use. However, material toxicity, chance of cell explosion and lack of effective cell recycling mechanism pose significant risk factors which are to be addressed seriously. These cells also lack flexibility in their design due to the structural characteristics of the electrode materials. Global research is directed towards identifying new class of electrode materials with less risk factors and better structural stability and flexibility. Polymer based electrode materials with inherent flexibility, stability and eco-friendliness can be a suitable choice. One of the prime drawbacks of polymer based cathode materials is the low electronic conductivity. Hence the real task with this class of materials is to get better electronic conductivity with good electrical storage capability. Electronic conductivity can be enhanced by using proper dopants. In the designing of rechargeable Li-ion cells with polymer based cathode active materials, the key issue is to identify the optimum lithiation of the polymer cathode which can ensure the highest electronic conductivity and specific charge capacity possible The development of conducting polymer based rechargeable Li-ion cells with high specific capacity and excellent cycling characteristics is a highly competitive area among research and development groups, worldwide. Polymer based rechargeable batteries are specifically attractive due to the environmentally benign nature and the possible constructional flexibility they offer. Among polymers having electrical transport properties suitable for rechargeable battery applications, polyaniline is the most favoured one due to its tunable electrical conducting properties and the availability of cost effective precursor materials for its synthesis. The performance of a battery depends significantly on the characteristics of its integral parts, the cathode, anode and the electrolyte, which in turn depend on the materials used. Many research groups are involved in developing new electrode and electrolyte materials to enhance the overall performance efficiency of the battery. Currently explored electrolytes for Li ion battery applications are in liquid or gel form, which makes well-defined sealing essential. The use of solid electrolytes eliminates the need for containment of liquid electrolytes, which will certainly simplify the cell design and improve the safety and durability. The other advantages of polymer electrolytes include dimensional stability, safety and the ability to prevent lithium dendrite formation. One of the ultimate aims of the present work is to realize all solid state, flexible and environment friendly Li-ion cells with high specific capacity and excellent cycling stability. Part of the present work is hence focused on identifying good polymer based solid electrolytes essential for realizing all solid state polymer based Li ion cells.The present work is an attempt to study the versatile roles of polyaniline in two different fields of technological applications like nonlinear optics and energy storage. Conducting form of doped PANI films with good extent of crystallinity have been realized using a level surface assisted casting method in addition to the generally employed technique of spin coating. Metal nanoparticles embedded PANI offers a rich source for nonlinear optical studies and hence gold and silver nanoparticles have been used for making the nanocomposites in bulk and thin film forms. These PANI nanocomposites are found to exhibit quite dominant third order optical non-linearity. The highlight of these studies is the observation of the interesting phenomenon of the switching between saturable absorption (SA) and reverse saturable absorption (RSA) in the films of Ag/PANI and Au/PANI nanocomposites, which offers prospects of applications in optical switching. The investigations on the energy storage prospects of PANI were carried out on Li enriched PANI which was used as the cathode active material for assembling rechargeable Li-ion cells. For Li enrichment or Li doping of PANI, n-Butyllithium (n-BuLi) in hexanes was used. The Li doping as well as the Li-ion cell assembling were carried out in an argon filled glove box. Coin cells were assembled with Li doped PANI with different doping concentrations, as the cathode, LiPF6 as the electrolyte and Li metal as the anode. These coin cells are found to show reasonably good specific capacity around 22mAh/g and excellent cycling stability and coulombic efficiency around 99%. To improve the specific capacity, composites of Li doped PANI with inorganic cathode active materials like LiFePO4 and LiMn2O4 were synthesized and coin cells were assembled as mentioned earlier to assess the electrochemical capability. The cells assembled using the composite cathodes are found to show significant enhancement in specific capacity to around 40mAh/g. One of the other interesting observations is the complete blocking of the adverse effects of Jahn-Teller distortion, when the composite cathode, PANI-LiMn2O4 is used for assembling the Li-ion cells. This distortion is generally observed, near room temperature, when LiMn2O4 is used as the cathode, which significantly reduces the cycling stability of the cells.

Design and Development of data mining models for the predictions of manpower placement in the technical Domain

Data mining is one of the hottest research areas nowadays as it has got wide variety of applications in common man’s life to make the world a better place to live. It is all about finding interesting hidden patterns in a huge history data base. As an example, from a sales data base, one can find an interesting pattern like “people who buy magazines tend to buy news papers also” using data mining. Now in the sales point of view the advantage is that one can place these things together in the shop to increase sales. In this research work, data mining is effectively applied to a domain called placement chance prediction, since taking wise career decision is so crucial for anybody for sure. In India technical manpower analysis is carried out by an organization named National Technical Manpower Information System (NTMIS), established in 1983-84 by India's Ministry of Education & Culture. The NTMIS comprises of a lead centre in the IAMR, New Delhi, and 21 nodal centres located at different parts of the country. The Kerala State Nodal Centre is located at Cochin University of Science and Technology. In Nodal Centre, they collect placement information by sending postal questionnaire to passed out students on a regular basis. From this raw data available in the nodal centre, a history data base was prepared. Each record in this data base includes entrance rank ranges, reservation, Sector, Sex, and a particular engineering. From each such combination of attributes from the history data base of student records, corresponding placement chances is computed and stored in the history data base. From this data, various popular data mining models are built and tested. These models can be used to predict the most suitable branch for a particular new student with one of the above combination of criteria. Also a detailed performance comparison of the various data mining models is done.This research work proposes to use a combination of data mining models namely a hybrid stacking ensemble for better predictions. A strategy to predict the overall absorption rate for various branches as well as the time it takes for all the students of a particular branch to get placed etc are also proposed. Finally, this research work puts forward a new data mining algorithm namely C 4.5 * stat for numeric data sets which has been proved to have competent accuracy over standard benchmarking data sets called UCI data sets. It also proposes an optimization strategy called parameter tuning to improve the standard C 4.5 algorithm. As a summary this research work passes through all four dimensions for a typical data mining research work, namely application to a domain, development of classifier models, optimization and ensemble methods.

ARMA modeling of time series based on rational approximation of spectral density function

This study is concerned with Autoregressive Moving Average (ARMA) models of time series. ARMA models form a subclass of the class of general linear models which represents stationary time series, a phenomenon encountered most often in practice by engineers, scientists and economists. It is always desirable to employ models which use parameters parsimoniously. Parsimony will be achieved by ARMA models because it has only finite number of parameters. Even though the discussion is primarily concerned with stationary time series, later we will take up the case of homogeneous non stationary time series which can be transformed to stationary time series. Time series models, obtained with the help of the present and past data is used for forecasting future values. Physical science as well as social science take benefits of forecasting models. The role of forecasting cuts across all fields of management-—finance, marketing, production, business economics, as also in signal process, communication engineering, chemical processes, electronics etc. This high applicability of time series is the motivation to this study.

Development of semiconductor metal oxide gas sensors for the detection of NO2 and H2S gases

One of the main challenges in the development of metal-oxide gas sensors is enhancement of selectivity to a particular gas. Currently, two general approaches exist for enhancing the selective properties of sensors. The first one is aimed at preparing a material that is specifically sensitive to one compound and has low or zero cross-sensitivity to other compounds that may be present in the working atmosphere. To do this, the optimal temperature, doping elements, and their concentrations are investigated. Nonetheless, it is usually very difficult to achieve an absolutely selective metal oxide gas sensor in practice. Another approach is based on the preparation of materials for discrimination between several analyte in a mixture. It is impossible to do this by using one sensor signal. Therefore, it is usually done either by modulation of sensor temperature or by using sensor arrays. The present work focus on the characterization of n-type semiconducting metal oxides like Tungsten oxide (WO3), Zinc Oxide (ZnO) and Indium oxide (In2O3) for the gas sensing purpose. For the purpose of gas sensing thick as well as thin films were fabricated. Two different gases, NO2 and H2S gases were selected in order to study the gas sensing behaviour of these metal oxides. To study the problem associated with selectivity the metal oxides were doped with metals and the gas sensing characteristics were investigated. The present thesis is entitled “Development of semiconductor metal oxide gas sensors for the detection of NO2 and H2S gases” and consists of six chapters.

Characterization of human and instrument related measurement errors

Measurement is the act or the result of a quantitative comparison between a given quantity and a quantity of the same kind chosen as a unit. It is generally agreed that all measurements contain errors. In a measuring system where both a measuring instrument and a human being taking the measurement using a preset process, the measurement error could be due to the instrument, the process or the human being involved. The first part of the study is devoted to understanding the human errors in measurement. For that, selected person related and selected work related factors that could affect measurement errors have been identified. Though these are well known, the exact extent of the error and the extent of effect of different factors on human errors in measurement are less reported. Characterization of human errors in measurement is done by conducting an experimental study using different subjects, where the factors were changed one at a time and the measurements made by them recorded. From the pre‐experiment survey research studies, it is observed that the respondents could not give the correct answers to questions related to the correct values [extent] of human related measurement errors. This confirmed the fears expressed regarding lack of knowledge about the extent of human related measurement errors among professionals associated with quality. But in postexperiment phase of survey study, it is observed that the answers regarding the extent of human related measurement errors has improved significantly since the answer choices were provided based on the experimental study. It is hoped that this work will help users of measurement in practice to better understand and manage the phenomena of human related errors in measurement.

" 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.

Service provider switching: a study on the switching process in retail banking

In a business environment that is characterized by intense competition, building customer loyalty has become a key area of focus for most financial institutions. The explosion of the services sector, changing customer demographics and deregulation and emergence of new technology in the financial services industry have had a critical impact on consumers’ financial services buying behaviour. The changes have forced banks to modify their service offerings to customers so as to ensure high levels of customer satisfaction and also high levels of customer retention. Banks have historically had difficulty distinguishing their products from one another because of their relative homogeneity; with increasing competition,the problem has only intensified with no coherent distinguishing theme. Rising wealth, product proliferation, regulatory changes and newer technologies are together making bank switching easier for customers. In order to remain competitive, it is important for banks to retain their customer base. The financial services sector is the foundation for any economy and plays the role of mobilization of resources and their allocation. The retail banking sector in India has emerged as one of the major drivers of the overall banking industry and has witnessed enormous growth. Switching behaviour has a negative impact on the banks’ market share and profitability as the costs of acquiring customers are much higher than the costs of retaining. When customers switch, the business loses the potential for additional profits from the customer the initial costs invested in the customer by the business get . The Objective of the thesis was to examine the relationship among triggers that customers experience, their perceptions of service quality, consumers’ commitment and behavioral intentions in the contemporary India retail banking context through the eyes of the customer. To understand customers’ perception of these aspects, data were collected from retail banking customers alone for the purpose of analysis, though the banks’ views were considered during the qualitative work carried out prior to the main study. No respondent who is an employee of a banking organization was considered for the final study to avoid the possibility of any bias that could affect the results adversely. The data for the study were collected from customers who have switched banks and from those who were non switchers. The study attempted to develop and validate a multidimensional construct of service quality for retail banking from the consumer’s perspective. A major conclusion from the empirical research was the confirmation of the multidimensional construct for perceived service quality in the banking context. Switching can be viewed as an optimization problem for customers; customers review the potential gains of switching to another service provider against the costs of leaving the service provider. As banks do not provide tangible products, their service quality is usually assessed through service provider’s relationship with customers. Thus, banks should pay attention towards their employees’ skills and knowledge; assessing customers’ needs and offering fast and efficient services.