AFLATOXICOSIS AND ITS AMELIORATION IN BLACK TIGER SHRIMP,PENAEUS MONODON FABRICIUS

The present study was undertaken to elucidate the nutritional and pathological changes associated with aflatoxin B1 toxicity in Penaeus monodon and to determine the efficacy of vitamins E and K, and Amrita Bindu, herbal mixture in ameliorating the toxicity of AFB1. The main objectives the study is to document the pathological and immunological changes in P.monodon fed with AFB1 incorporated diets and to delineate the histological and ultrastructural changes and determine the presence of AFB1 residue in the shrimp body, to evaluate the growth performance of feed efficiency in P. monodon post larvae fed AFB1 added diets, to assess the interactive effect of heavy metals like copper and cadmium at sub-lethal levels in P. monodon postlarve fed AFB1 added diets, to decipher the ameliorative action of Vitamins E & K and a spicy herbal mixture, Amrita Bindu on AFB1 in P.monodon sub-adults. The study has revealed that Aflatoxin B1 significantly affects protein, lipid and carbohydrate metabolism in the shrimp penaeus monodon. The remarkable effect was observed in the immune system, as AFB1 has elevatod the immune response during initial days of exposure and prolonged exposure to the toxin leads to weakening of the animal’s immunity. Aflatoxin B1 level above 50 ppb severely affected the growth and feed utilization which in turn reflects the damage caused to the hepatopancreas as evident from the histological and ultrastructural observations.

Compact Wideband Antenna for 2.4 GHz WLAN Applications

A novel compact wideband antenna for wireless local area network (WLAN) applications in the 2.4 GHz band are presented. The proposed low profile antenna of dimensions 15 x 14.5 x 1.6 mm offers 18.6% bandwidth and an average gain of~5 dBi. The antenna can be excited directly using a 50 coaxial probe

Compact Planar Multiband Antenna for GPS, DCS, 2.4/5.8 GHz WLAN Applications

A compact single –feed multiband planar antenna configuration Suitable for GPS, DCS. 2.4/5.8 GHz WLAN applications are presented. The antenna has dimensions 38 x 3 x 1.6 mm and offers good radiation and reflection characteristics in the above frequency bands. The antenna has a simple geometry and can be easily fed using a 50 coaxial probe

Compact amplifier integrated microstrip antenna

compact microstrip antenna integrated with an amplifier having an area reduction of 70%, compared to the standard circular microstrip patch antenna, is presented. The antenna also provides an enhanced gain of 10-dB more than its passive counter part. The measured 2:1 VSWR band width is -4% at 790 MHz, which is 2.5 times larger than that of the passive microstrip antenna

Compact Planar Multiband Antenna for GPS,DCS 2.4/5.8 GHz WLAN Applications

A compact single - feed muttiband planar antenna configuration suitable for GPS, DCS. 2.4/5.8 GHz WLAN applications is presented. The antenna has dimensions 38 x 3 x 1.6 mm and offers good radiation and reflection characteristics in the above frequency bands. The antenna has a simple geometry and can be easily fed using a 50 coaxial probe.

Compact Wideband Antenna for 2.4 GHz WLAN Applications

A novel compact wideband antenna for wireless local area network (WLAN) applications in the 2.4 GHz band is presented. The proposed low profile antenna of dimensions 15 x 14.5 x 1.6 mm offers 18.6% bandwidth and an average gain of -5 dBi. The antenna can be excited directly using a 50 coaxial probe

A Study of the impact of ISO 9001:2000 on Quality Management Practices in Selected Organisations in Kerala

The research work which was carried out to study the impact of ISO 9001: 2000, in selected organisations in Kerala, spread over various types of activities, such as fabrication of aero space hardware, glass ware, construction industries, health care units etc, encompassing, government and private enterprises, public sector undertakings, small and medium scale industries and research and development establishments. The ambience, work culture and collaboration prevalent in these organisations were varying on account of the environment in which they have been working. Fifty percent of the organizations selected for the study had obtained the ISO 900 I: 2000-certification since seven years or more. The process of study undertaken could invoke interest in the respondents, when a brief explanation on the purpose and need of the study was given to them prior to conducting the survey. There has been total cooperation from the management and the employees of all the organisations for the conduct of the study. Personal discussions were held with the senior management to draw their total support and involvement for the study.

Development and Analysis of a Compact Dual-Band Coplanar Antenna

The coplanar wave guide is an attractive device in microwave integrated circuits due to its uniplanar nature, ease of fabrication and low production cost. Several attempts are already done to explore the radiating modes in coplanar wave guide transmission lines. Usually coplanar wave guides are excited by an SMA connector with its centre conductor connected to the exact middle of the centre strip and the outer ground conductor to the two ground strips. The mode excited on it is purely a bound mode. The E-field distribution in the two slots are out of phase and there for cancels at the far field. This thesis addresses an attempt to excite an in phase E-field distribution in the two slots of the co planar wave guide by employing a feed asymmetry, in order to get radiation from the two large slot discontinuities of the coplanar waveguide. The omni directional distribution of the radiating energy can be achieved by widening the centre strip.The first part of the thesis deals with the investigations on the resonance phenomena of conventional coplanar waveguides at higher frequency bands. Then an offset fed open circuited coplanar waveguide supporting resonance/radiation phenomena is analyzed. Finally, a novel compact co planar antenna geometry with dual band characteristics, suitable for mobile terminal applications is designed and characterized using the inferences from the above study.

Analysis and Optimization of Machining Process Using Evolutionary Algorithms

To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.

Structural Characterization and Non-linear Optical Properties of Metal Complexes of Some Donor-Acceptor Substituted N-salicylidene-N' -aroylhydrazine Ligands

The present work deals with the complexation of Schiff bases of aroylhydrazines with various transition metal ions. The hydrazone systems selected for study have long 7I:-delocalized chain in the ligand molecule itself, which get intensified due to metal-to-ligand or ligand-to-metal charge transfer excitations upon coordination. Complexation with metal ions like copper, nickel, cobalt, manganese, iron, zinc and cadmium are tried. Various spectral techniques are employed for characterization. The structures of some complexes have been well established by single crystal X-ray diffraction studies. The nonIinaer optical studies of the ligands and complexes synthesized have been studied by hyper-Rayleigh scattering technique.The work is presented in seven chapters and the last one deals with summary and conclusion. One of the hydrazone system selected for study proved that it could give rise to polymeric metal complexes. Some of the copper, nickel, zinc and cadmium complexes showed non-linear optical activity. The NLO studies of manganese and iron showed negative result, may be due to the inversion centre of symmetry within the molecular lattice.

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

MQFD: A Model for Synergizing TPM and QFD

This thesis presents the methodology of linking Total Productive Maintenance (TPM) and Quality Function Deployment (QFD). The Synergic power ofTPM and QFD led to the formation of a new maintenance model named Maintenance Quality Function Deployment (MQFD). This model was found so powerful that, it could overcome the drawbacks of TPM, by taking care of customer voices. Those voices of customers are used to develop the house of quality. The outputs of house of quality, which are in the form of technical languages, are submitted to the top management for making strategic decisions. The technical languages, which are concerned with enhancing maintenance quality, are strategically directed by the top management towards their adoption of eight TPM pillars. The TPM characteristics developed through the development of eight pillars are fed into the production system, where their implementation is focused towards increasing the values of the maintenance quality parameters, namely overall equipment efficiency (GEE), mean time between failures (MTBF), mean time to repair (MTIR), performance quality, availability and mean down time (MDT). The outputs from production system are required to be reflected in the form of business values namely improved maintenance quality, increased profit, upgraded core competence, and enhanced goodwill. A unique feature of the MQFD model is that it is not necessary to change or dismantle the existing process ofdeveloping house ofquality and TPM projects, which may already be under practice in the company concerned. Thus, the MQFD model enables the tactical marriage between QFD and TPM.First, the literature was reviewed. The results of this review indicated that no activities had so far been reported on integrating QFD in TPM and vice versa. During the second phase, a survey was conducted in six companies in which TPM had been implemented. The objective of this survey was to locate any traces of QFD implementation in TPM programme being implemented in these companies. This survey results indicated that no effort on integrating QFD in TPM had been made in these companies. After completing these two phases of activities, the MQFD model was designed. The details of this work are presented in this research work. Followed by this, the explorative studies on implementing this MQFD model in real time environments were conducted. In addition to that, an empirical study was carried out to examine the receptivity of MQFD model among the practitioners and multifarious organizational cultures. Finally, a sensitivity analysis was conducted to find the hierarchy of various factors influencing MQFD in a company. Throughout the research work, the theory and practice of MQFD were juxtaposed by presenting and publishing papers among scholarly communities and conducting case studies in real time scenario.