Studies on magnetic monopole solutions of non-abelian gauge theories and related problems

In 1931 Dirac studied the motion of an electron in the field of a magnetic monopole and found that the quantization of electric charge can be explained by postulating the mere existence of a magnetic monopole. Since 1974 there has been a resurgence of interest in magnetic monopole due to the work of ‘t’ Hooft and Polyakov who independently observed that monopoles can exist as finite energy topologically stable solutions to certain spontaneously broken gauge theories. The thesis, “Studies on Magnetic Monopole Solutions of Non-abelian Gauge Theories and Related Problems”, reports a systematic investigation of classical solutions of non-abelian gauge theories with special emphasis on magnetic monopoles and dyons which possess both electric and magnetic charges. The formation of bound states of a dyon with fermions and bosons is also studied in detail. The thesis opens with an account of a new derivation of a relationship between the magnetic charge of a dyon and the topology of the gauge fields associated with it. Although this formula has been reported earlier in the literature, the present method has two distinct advantages. In the first place, it does not depend either on the mechanism of symmetry breaking or on the nature of the residual symmetry group. Secondly, the results can be generalized to finite temperature monopoles.

Stochastic processes and their applications semi-markov analysis of some inventory and queuing problems

This thesis analyses certain problems in Inventories and Queues. There are many situations in real-life where we encounter models as described in this thesis. It analyses in depth various models which can be applied to production, storag¢, telephone traffic, road traffic, economics, business administration, serving of customers, operations of particle counters and others. Certain models described here is not a complete representation of the true situation in all its complexity, but a simplified version amenable to analysis. While discussing the models, we show how a dependence structure can be suitably introduced in some problems of Inventories and Queues. Continuous review, single commodity inventory systems with Markov dependence structure introduced in the demand quantities, replenishment quantities and reordering levels are considered separately. Lead time is assumed to be zero in these models. An inventory model involving random lead time is also considered (Chapter-4). Further finite capacity single server queueing systems with single/bulk arrival, single/bulk services are also discussed. In some models the server is assumed to go on vacation (Chapters 7 and 8). In chapters 5 and 6 a sort of dependence is introduced in the service pattern in some queuing models.

Planning And Operation Problems Of Indian Major Ports With Special Emphasis On Cochin Port

Rapid changes in the technological environment of marine logistics and the increasing integration of waterborne, air and land transport systems have fostered a revolution in the design and operations of transport vehicles, cargo handling technology, and terminal facilities. This in turn has caused major changes in the functions of and uses of ports. From literature, it was found that these changes were very slow in case of Indian ports and the performances of port operations were poor when compared with similar ports in the same region. It was also found that a very few studies were conducted to identify the reasons for slow improvements in the performances of Indian major ports. In this thesis, an attempt is made to find out the operational problems of Indian major ports and to analyze the reasons for it. Some solutions have also been found out using management tools

Multi-objective assembly job shop scheduling using genetic algorithm and tabu search

Assembly job shop scheduling problem (AJSP) is one of the most complicated combinatorial optimization problem that involves simultaneously scheduling the processing and assembly operations of complex structured products. The problem becomes even more complicated if a combination of two or more optimization criteria is considered. This thesis addresses an assembly job shop scheduling problem with multiple objectives. The objectives considered are to simultaneously minimizing makespan and total tardiness. In this thesis, two approaches viz., weighted approach and Pareto approach are used for solving the problem. However, it is quite difficult to achieve an optimal solution to this problem with traditional optimization approaches owing to the high computational complexity. Two metaheuristic techniques namely, genetic algorithm and tabu search are investigated in this thesis for solving the multiobjective assembly job shop scheduling problems. Three algorithms based on the two metaheuristic techniques for weighted approach and Pareto approach are proposed for the multi-objective assembly job shop scheduling problem (MOAJSP). A new pairing mechanism is developed for crossover operation in genetic algorithm which leads to improved solutions and faster convergence. The performances of the proposed algorithms are evaluated through a set of test problems and the results are reported. The results reveal that the proposed algorithms based on weighted approach are feasible and effective for solving MOAJSP instances according to the weight assigned to each objective criterion and the proposed algorithms based on Pareto approach are capable of producing a number of good Pareto optimal scheduling plans for MOAJSP instances.

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.

Studies Using Computer Simulation Models to Solve Problems Related to Logistics Terminals

This thesis deals with the use of simulation as a problem-solving tool to solve a few logistic system related problems. More specifically it relates to studies on transport terminals. Transport terminals are key elements in the supply chains of industrial systems. One of the problems related to use of simulation is that of the multiplicity of models needed to study different problems. There is a need for development of methodologies related to conceptual modelling which will help reduce the number of models needed. Three different logistic terminal systems Viz. a railway yard, container terminal of apart and airport terminal were selected as cases for this study. The standard methodology for simulation development consisting of system study and data collection, conceptual model design, detailed model design and development, model verification and validation, experimentation, and analysis of results, reporting of finding were carried out. We found that models could be classified into tightly pre-scheduled, moderately pre-scheduled and unscheduled systems. Three types simulation models( called TYPE 1, TYPE 2 and TYPE 3) of various terminal operations were developed in the simulation package Extend. All models were of the type discrete-event simulation. Simulation models were successfully used to help solve strategic, tactical and operational problems related to three important logistic terminals as set in our objectives. From the point of contribution to conceptual modelling we have demonstrated that clubbing problems into operational, tactical and strategic and matching them with tightly pre-scheduled, moderately pre-scheduled and unscheduled systems is a good workable approach which reduces the number of models needed to study different terminal related problems.

An Alternative Approach To Computer System Security Monitoring And Enhancement Through System Call Sequence Analysis

Modern computer systems are plagued with stability and security problems: applications lose data, web servers are hacked, and systems crash under heavy load. Many of these problems or anomalies arise from rare program behavior caused by attacks or errors. A substantial percentage of the web-based attacks are due to buffer overflows. Many methods have been devised to detect and prevent anomalous situations that arise from buffer overflows. The current state-of-art of anomaly detection systems is relatively primitive and mainly depend on static code checking to take care of buffer overflow attacks. For protection, Stack Guards and I-leap Guards are also used in wide varieties.This dissertation proposes an anomaly detection system, based on frequencies of system calls in the system call trace. System call traces represented as frequency sequences are profiled using sequence sets. A sequence set is identified by the starting sequence and frequencies of specific system calls. The deviations of the current input sequence from the corresponding normal profile in the frequency pattern of system calls is computed and expressed as an anomaly score. A simple Bayesian model is used for an accurate detection.Experimental results are reported which show that frequency of system calls represented using sequence sets, captures the normal behavior of programs under normal conditions of usage. This captured behavior allows the system to detect anomalies with a low rate of false positives. Data are presented which show that Bayesian Network on frequency variations responds effectively to induced buffer overflows. It can also help administrators to detect deviations in program flow introduced due to errors.

Investment analysis of chemical projects and development of standerdised mathematical co-relation for cost estimation of pressure vessels in chemical industry

The present study is intended to provide a new scientific approach to the solution of the worlds cost engineering problems encountered in the chemical industries in our nation. The problem is that of cost estimation of equipments especially of pressure vessels when setting up chemical industries .The present study attempts to develop a model for such cost estimation. This in turn is hoped would go a long way to solve this and related problems in forecasting the cost of setting up chemical plants.

Studies on the ecology and productivity of saline lagoon

A perusal of the literature shows that most of the earlier works on the ecology and productivity from the Indian waters have been confined to the estuarine ecosystms and contiguous neritic and oceanic water bodies. Although some information is available on certain aspects of the envirornental parameters from the ‘coastal lagoon ecosystem‘, there is hardly any indepth study on the ecological and productivity problems from "derlict saline lagoonal environment" in India . In view of this, the researcher undertook a study on the subject "ecology and productivity“ of a typical “coastal saline lagoon"(Pilla;headan lagoon) situated along the southeast coast of India for a period of two years!-N11, 1982 to June, 1984) , and the results of the investigations are embodied in the present thesis entitled "studies on the ecology and productivity of saline lagoon‘.

Management of Traffic Control — A Computer Oriented Approach

Traffic Management system (TMS) comprises four major sub systems: The Network Database Management system for information to the passengers, Transit Facility Management System for service, planning, and scheduling vehicle and crews, Congestion Management System for traffic forecasting and planning, Safety Management System concerned with safety aspects of passengers and Environment. This work has opened a rather wide frame work of model structures for application on traffic. The facets of these theories are so wide that it seems impossible to present all necessary models in this work. However it could be deduced from the study that the best Traffic Management System is that whichis realistic in all aspects is easy to understand is easy to apply As it is practically difficult to device an ideal fool—proof model, the attempt here has been to make some progress-in that direction.

Fish Driven Bioturbation as a Viable Aquaculture Technology for Increasing Production and Improving Ecological Sustainability of Giant Tiger Shrimp Penaeus Monodon (FABRlClUS)

A general introduction to the problems faced in the shrimp culture due to waste formation and its consequent environmental hazards and production problems of Giant tiger shrimp, Penaeus monodon is highlighted by the author in this thesis. The objective of the present work was to assess the potential of brackish water finfish to improve bottom soil conditions and thereby increase the growth and production of Penaeus monodon. The salient findings of the present study are summarized in chapter 7. This is followed by the references cited in the thesis and list ofpublications originated from the present study.

Studies on the production management in the seafood processing industry in Kerala

Kerala was the pioneer in modern seafood processing and exporting. But now the industry is Iacingalot of problems due to low productivity and deterioration in the quality of the products. only about 17% of the installed freezing capacity in sea food processing industry was reported to be utilised during 1979-80. The price of the export commodities its decided by the buyers based on international supply and demand pattern and based on the strength and weakness of dollar/yen. The only way to increase the profitability of the processors is to reduce the cost of production to the possible extent. The individual processors find it difficult to continue in this field due to low productivity and quality problems. The main objectives of the research are to find out how the production is being managed in the seafood processing(freezing) 17industry in Kerala and the reasons for low productivity and poor quality of the products. The study includes a detailed analysis of Location of the factories. Layout Purchase, production and storage patterns. Production planning and scheduling. Work Measurement of the processing of important products. Quality Control and Inspection. Management Information System

Studies on Catalysis by Nano Titania Modified with Metals and Nonmetals

Semiconductor photocatalysis has received much attention during last three decades as a promising solution for both energy generation and environmental problems. Heterogeneous photocatalytic oxidation allows the degradation of organic compounds into carbon dioxide and water in the presence of a semiconductor catalyst and UV light source. The •OH radicals formed during the photocatalytic processes are powerful oxidizing agents and can mineralise a number of organic contaminants. Titanium dioxide (TiO2), due to its chemical stability, non-toxicity and low cost represents one of the most efficient photocatalyst. However, only the ultraviolet fraction of the solar radiation is active in the photoexcitation processes using pure TiO2 and although, TiO2 can treat a wide range of organic pollutants the effectiveness of the process for pollution abatement is still low. A more effective and efficient catalyst therefore must be formulated. Doping of TiO2 was considered with the aim of improving photocatalytic properties. In this study TiO2 catalyst was prepared using the sol-gel method. Metal and nonmetal doped TiO2 catalysts were prepared. The photoactivity of the catalyst was evaluated by the photodegradation of different dyes and pesticides in aqueous solution. High photocatalytic degradation of all the pollutants was observed with doped TiO2. Structural and optical properties of the catalysts were characterized using XRD, BET surface area, UV-Vis. DRS, CHNS analysis, SEM, EDX, TEM, XPS, FTIR and TG. All the catalysts showed the anatase phase. The presence of dopants shifts the absorption of TiO2 into the visible region indicating the possibility of using visible light for photocatalytic processes.

“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

Median graphs, the remoteness function, periphery transversals, and geodetic number two

A periphery transversal of a median graph G is introduced as a set of vertices that meets all the peripheral subgraphs of G. Using this concept, median graphs with geodetic number 2 are characterized in two ways. They are precisely the median graphs that contain a periphery transversal of order 2 as well as the median graphs for which there exists a profile such that the remoteness function is constant on G. Moreover, an algorithm is presented that decides in O(mlog n) time whether a given graph G with n vertices and m edges is a median graph with geodetic number 2. Several additional structural properties of the remoteness function on hypercubes and median graphs are obtained and some problems listed