High power N2 laser with a modified gas flow system and discharge geometry

A high power Nz laser of the double-Blumlein type having a modified gas flow system, electrode configuration, and discharge geometry with minimum inductance is described. By incorporating a triggere’d-pressurized spark gap switch, arc-free operation was achieved for a wide E/P range. The device gives a peak power in excess of 700 kW with a FWHM of 3 ns and an efficiency of 0.51%, which is remarkably high for a pulsed nitrogen laser system. The dependence of output power on parameters such as operating pressure, voltage, and repetition rate are discussed.

Low power optical phase conjugation in dyes embedded in polyvinyl alcohol films

Low power optical phase conjugation in polyvinyl alcohol films embedded with saturable dyes is reported. Phase conjugate reflectivity achieved is higher than that obtained in the case of similar gelatin films.

Studies on some generalizations of line graph and the power domination problem in graphs

Department of Mathematics, Cochin University of Science and Technology

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.

Theoretical study of the fluorinating power of SF6 to vanadocene

Màster Oficial en Química Teòrica i Computacional Curs: 2008-2009, Director: Juan J. Novoa Vide

Synthesis of Bio-Compatible SPION–based Aqueous Ferrofluids and Evaluation of RadioFrequency Power Loss for Magnetic Hyperthermia

Bio-compatible magnetic fluids having high saturation magnetization find immense applications in various biomedical fields. Aqueous ferrofluids of superparamagnetic iron oxide nanoparticles with narrow size distribution, high shelf life and good stability is realized by controlled chemical co-precipitation process. The crystal structure is verified by X-ray diffraction technique. Particle sizes are evaluated by employing Transmission electron microscopy. Room temperature and low-temperature magnetic measurements were carried out with Superconducting Quantum Interference Device. The fluid exhibits good magnetic response even at very high dilution (6.28 mg/cc). This is an advantage for biomedical applications, since only a small amount of iron is to be metabolised by body organs. Magnetic field induced transmission measurements carried out at photon energy of diode laser (670 nm) exhibited excellent linear dichroism. Based on the structural and magnetic measurements, the power loss for the magnetic nanoparticles under study is evaluated over a range of radiofrequencies.

Power Profile of Effective Managers: An Exploration among the Branch Managers of a Commercial Bank in Kerala

Managers are central to any fuction in a complex and developed society. Their talents are reckoned to be cardinal in developed economies and a basic yearning of all developing economies.In order to survive and produce results in a turbulent and transient environment, the task is to understand the nature of factors contributing to managerial effectiveness. This study is an attempt towards this core issue of the present from a different perspective. This study tries to focus attention on a group of managers functioning in the field of banking, a core sector in the country's economy. The gamut of economic activities in Kerala being predominantly service-oriented, importance of commercial banking is almost indisputable. Though economists would argue that the disproportionate development of service sector is anomalous when viewed against the hazy scenarios in the primary and secondary sectors of the state’s economy, the extent and pace of growth in the banking sector has had its dole meted out by ambitious and productive managers fiinctioning in the field. Researcher’s attempt here is to thresh the grain and chaff among bank managers in terms of their effectiveness and to account for the variations in the light of their ability to affect the thoughts and actions of their subordinates. To put it succinctly, the attempt herein is to explain the effectiveness of bank managers in the light of their ‘Power Profile’ taken to be comprising Power Differentials, Power Bases, their Visibility and Credibility in the organisation and, the Power Styles typically used by them for influencing subordinates.

The power of taxation under the indian constitution

The Power Of Taxation Under The lndian Constitution, the subject of the present thesis has a wide ambit covering the entire federal field end deep constitutional significance traversing many of the principles like pith and substance, colourability, severebility etc. However, considerations of time, space and areas already investigated have indicated that the present study may be confined to the fundamental constitutional limitations end the federal problem. Thus the effect of fundamental rights, the commerce clause, immunity of instrumentalitis and the principle limiting the power of legislative delegation on the power of taxation has been studied. The distribution of taxes between the Union and units of the Indian federation leans so much over to the former and that part of this study has been directed to discover what devices can help the units to gain economic viability

Evaluation of the Power Consumption of Routing Protocols for Wireless Sensor Networks

Sensor networks are one of the fastest growing areas in broad of a packet is in transit at any one time. In GBR, each node in the network can look at itsneighbors wireless ad hoc networking (? Eld. A sensor node, typically'hop count (depth) and use this to decide which node to forward contains signal-processing circuits, micro-controllers and a the packet on to. If the nodes' power level drops below a wireless transmitter/receiver antenna. Energy saving is one certain level it will increase the depth to discourage trafiE of the critical issue for sensor networks since most sensors are equipped with non-rechargeable batteries that have limitedlifetime. Routing schemes are used to transfer data collectedby sensor nodes to base stations. In the literature many routing protocols for wireless sensor networks are suggested. In this work, four routing protocols for wireless sensor networks viz Flooding, Gossiping, GBR and LEACH have been simulated using TinyOS and their power consumption is studied using PowerTOSSIM. A realization of these protocols has beencarried out using Mica2 Motes.

Channel Adaptive MAC Protocol with Traffic-Aware Distributed Power Management in Wireless Sensor Networks-Some Performance Issues

In Wireless Sensor Networks (WSN), neglecting the effects of varying channel quality can lead to an unnecessary wastage of precious battery resources and in turn can result in the rapid depletion of sensor energy and the partitioning of the network. Fairness is a critical issue when accessing a shared wireless channel and fair scheduling must be employed to provide the proper flow of information in a WSN. In this paper, we develop a channel adaptive MAC protocol with a traffic-aware dynamic power management algorithm for efficient packet scheduling and queuing in a sensor network, with time varying characteristics of the wireless channel also taken into consideration. The proposed protocol calculates a combined weight value based on the channel state and link quality. Then transmission is allowed only for those nodes with weights greater than a minimum quality threshold and nodes attempting to access the wireless medium with a low weight will be allowed to transmit only when their weight becomes high. This results in many poor quality nodes being deprived of transmission for a considerable amount of time. To avoid the buffer overflow and to achieve fairness for the poor quality nodes, we design a Load prediction algorithm. We also design a traffic aware dynamic power management scheme to minimize the energy consumption by continuously turning off the radio interface of all the unnecessary nodes that are not included in the routing path. By Simulation results, we show that our proposed protocol achieves a higher throughput and fairness besides reducing the delay

Evaluation of the Power Consumption of Routing Protocols for Wireless Sensor Networks

Sensor networks are one of the fastest growing areas in broad of a packet is in transit at any one time. In GBR, each node in the network can look at itsneighbors wireless ad hoc networking (? Eld. A sensor node, typically'hop count (depth) and use this to decide which node to forward contains signal-processing circuits, micro-controllers and a the packet on to. If the nodes' power level drops below a wireless transmitter/receiver antenna. Energy saving is one certain level it will increase the depth to discourage trafiE of the critical issue forfor sensor networks since most sensors are equipped with non-rechargeable batteries that have limited lifetime.

Evaluation of the Power Consumption of Routing Protocols for Wireless Sensor Networks

Sensor networks are one of the fastest growing areas in broadwireless ad hoc networking (?Eld. A sensor node, typically'contains signal-processing circuits, micro-controllers and awireless transmitter/receiver antenna. Energy saving is oneof the critical issue for sensor networks since most sensorsare equipped with non-rechargeable batteries that have limited lifetime.In thiswork, four routing protocols for wireless sensor networks vizFlooding, Gossiping, GBR and LEACH have been simulated using Tiny OS and their power consumption is studied usingcaorwreiredTOoSuStIuMs.ingAMirceaal2izMaotitoens.of these protocols has been carried out using mica 2 motes

A Numerically efficient power optimization scheme for coded OFDM systems in achieving minimum frame error rate

Coded OFDM is a transmission technique that is used in many practical communication systems. In a coded OFDM system, source data are coded, interleaved and multiplexed for transmission over many frequency sub-channels. In a conventional coded OFDM system, the transmission power of each subcarrier is the same regardless of the channel condition. However, some subcarrier can suffer deep fading with multi-paths and the power allocated to the faded subcarrier is likely to be wasted. In this paper, we compute the FER and BER bounds of a coded OFDM system given as convex functions for a given channel coder, inter-leaver and channel response. The power optimization is shown to be a convex optimization problem that can be solved numerically with great efficiency. With the proposed power optimization scheme, near-optimum power allocation for a given coded OFDM system and channel response to minimize FER or BER under a constant transmission power constraint is obtained