998 resultados para Legislative power.
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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.
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Department of Mathematics, Cochin University of Science and Technology
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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.
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Màster Oficial en Química Teòrica i Computacional Curs: 2008-2009, Director: Juan J. Novoa Vide
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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.
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This work is a study on ‘Legal Control of Fishing Industry in Kerala.Fishery and Fishery-related legislations are sought to be examined in the light of scientific opinion and judicial decisionsThis work is divided into five Part.The thrust of time Study is on the success of legislative measures in attempting to achieve socio-economic justice for the fishermen community.Fishing is more an avocation than an industry. It is basically the avocation of the artisanal or traditional fishermen who depend on it for their livelihood. As an ‘industry’, it is a generator of employment, income and wealth.The modern tendency in national legislations is to integrate legal proivisions relating to EEZ fisheries into the general fisheries legislation.Chartered fishing was introduced by the Central Government during 1977-78 to establish the abundance and distribution of fishery resources in Indian EEZ, for transfer of technology and for related purposes.Going by the provisions of Articles 61 and 62 of the U.N. Convention on the Law of the Sea, 1982, foreign fishing need be permitted in our EEZ area only if there is any surplus left after meeting our national requirements.Conservation of the renewable fishery resources should start with identification of the species, their habitats, feeding and breeding patterns, their classification and characteristics. Fishing patterns and their impact on different species and areas require to be examined and investigated.the Central Government, that the Kerala Marine Fishing Regulation Act, 1980 was passed.our traditional fishermen that our Governments in power in Kerala resorted to the appointment of Commissions after Commissions to enquire into the problems of resource management and conservation of the resources. The implementation of the recommendations of these Commissions is the need of the times.General infrastructure has increased to a certain extent in the fishery villages; but it is more the result of the development efforts of the State rather than due to increase in earnings from fishing. Fisherwomen ar e still unable to enjoy the status and role expected of them in the society and the family.Around 120 million people around the tuorld are economically dependent on fisheries. In developing countries like India, small-scale fishers are also the primary suppliers of fish, particularly for local consumption. A most important role of the fisheries sector is as a source of domestically produced food. Fish, as a food item, is a nutrient and it has great medicinal value.Consumers in our country face a dramatic rise in fish prices as our ‘fishing industry’ is linked with lucrative markets in industrial countries. Autonomy of States should be attempted to be maintained to the extent possible with the help and co-operation of the Centre. Regional co-operation of the coastal states interse and with the Centre should be attempted to be achieved under the leadership of the Centre in matters of regional concern. At time national level, a ifisheries management policy and plan should be framed in conformity with the national economic policies and plans as also keeping pace with the local and regional needs and priorities. Any such policy, plan and legislation should strive to achieve sustainability of the resources as well as support to the subsistence sector.
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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.
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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.
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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
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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.
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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
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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
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Manganites belonging to the series Gd1−xSrxMnO3 (x=0.3, 0.4 and 0.5) were prepared by wet solid-state reaction and their thermoelectric power was evaluated. Thermoelectric power measurements revealed a peak value at ∼40 K. All the samples exhibited a colossal thermopower at ∼40K and in that Gd0.5Sr0.5MnO3 exhibited a maximum value of ∼35mV/K, which is the largest reported for these class of materials at this temperature. Temperaturedependent magnetisation measurements showed that the samples exhibit a phase transition from paramagnetic to spin-glass–like state at these temperatures. Plausible mechanisms responsible for the observed colossal thermoelectric power in Gd-Sr manganites are discussed
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A simple and inexpensive power supply suitable for characteristics studies of a klystron is described. The circuit is a modified form of the high voltage adjustable power supply based on LM 317. This provides the necessary cavity and repeller voltages over a wide range, with good regulation. The system is protected aa- ainst short circuits and is ideallv suitable for laboratorv, ex.Deri ments with reflex klystrons.
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Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year