One of the most extensively investigated phenomena in hydraulic engineering is the hydraulic jump. Numerous investigators have studied it over the past century. Thus, stilling basins with hydraulic jump are remains as the most favorite choice of designers for energy dissipaters below spillways and outlets. A properly designed of hydraulic jump stilling basin can ensure 60–70% dissipation of energy in the basin itself. In this study, experiments are conducted to evaluate effects of a perforated sill with circular holes on the length of hydraulic jump and its position in a stilling basin.\nA series of perforated sills with different heights and ratio of ( is total area of circular holes and A is area of sill) were placed at three tailwater depth ratio ( ) along a stilling basin. The hydraulic characteristics of forced jump due to perforated sill were measured and compared with the classical hydraulic jump under variable discharges. Results of experiments confirmed significant effect of the perforated sill on dissipation of energy and reduction the length of basin. Also a new relationship was developed between the height of a perforated sill and length characteristic of stilling basin according to internal flow features.
The gum guggul, the resinous exudate secreted by the Commiphora mukul plant is shown to exert beneficial effects on human health through its antioxidant, anti-inflammatory, hypolidemic and anticancer properties. Besides a well-known risk factor for cardiovascular diseases, hypertension is one of the leading causes of liver and kidney diseases. It is unclear whether the guggul resin can ameliorate the liver and kidney functions affected by hypertension. In this study we tested this possibility in hypertensive male Wister rats. Rats were rendered hypertensive with the daily administration of cyclosporine A (25 mg/kg subcutaneously, diluted in 1 mL/kg olive oil) for 4 weeks followed by the oral treatment with aqueous extract of guggul resin (GRE) (200 mg/Kg/day) for 8 weeks. Compared to normotensive rats, cyclosporine A treated rats exhibited elevated blood pressure, altered lipid profile, increased serum levels of liver and kidney functional parameters including aspartate aminotransferase (AST), alanine aminotransferase (ALT), blood urea nitrogen (BUN), uric acid, creatinine, and renin, confirming the hypertensive state and its negative effects on liver and kidney functions.. Compared to untreated hypertensive rats, GRE treated hypertensive rats had significantly improved lipid profile and lowered blood pressure. GRE treatment significantly blunted the liver and kidney functional parameters within four weeks. The data suggest that guggul resin may help in not only attenuating the hypertension but also improving the liver and kidney functions hypertensive state.\nKey words: Commiphora mukul, hypertension, blood pressure, aspartate aminotransferase, creatinine.
Firms operating in servis sector must have a dynamic structure to be competitive in volatile business environment. Most of the employees in traditional retail service provider, in order to offer more services to customers, will be engaged in more powerful facilities. However, it is a fact that most of the staff has taken part in the sales and service responsibilities more intensively. The opportunities for customer service, service quality and sales revenue require understanding customer needs and competitors in a competitive environment as well as working staff for the provision of services that has a strategic role for performance evaluation. In this study, customer satisfaction competencies have been used by fuzzy ahp vikor method for performance evaluation in Turkish banking sector. This study illustrates the performance results of the banks based on ownership types and clarifies (i) the facilities of the state-owned banks suitable for their customer expactations (ii) privately-owned banks are in the second place (iii) foreign banks have weak performance results for the customer satisfaction based on negative financial outcomes, inconveniences in local countries (iv) finally, state-owned banks with their strong assets serve the customers in expected manner.
This paper presents space-time coding based analog network coding (STANC) for cooperative network under shadowed Rician fading environment. The performance of the proposed system is analyzed in terms of SER, STANC gain and ergodic capacity using both analytical expressions and Monte Carlo simulations. The SER for $M$-PSK modulated signals are derived by using Moment generating function (MGF) approach. The approximate closed-form expression of ergodic capacity presented using the derived mean and second moment for STANC based cooperative system. Rician shadowed model is used to address the effect of shadowing. The fading channel gains are computed using the path loss model $d_{xy}^{-\\beta }$, for $\\beta =3$ (suburban environment). Numerical results signify that all the approximated analytical expressions derived are very tight and can be effectively used for performance, gain and capacity analysis of the proposed STANC based system by randomly changing different parameters of interest and in any SNR region. The analysis illustrated that the STANC based system has significant performance improvement under path loss and shadowing effect as compared to the ANC based system due to the diversity combining.
We consider the recovery of high-dimensional sparse signals via L1-minimization under mutual incoherence condition, which was previously used for exact sparse signals recovery in the noiseless and noise case. Two well known L1-minimization methods, which are L1-minimization under the L2-constraint and the Dantzig selector, are studied. Using these two methods and a technical inequality, we give some results. To some extent, the results of this paper improve the existing results in the literature by tightening the error bounds. Moreover, our results are stated in the general setting of reconstructing an arbitrary signal.
Permanent magnet synchronous reluctance motors are attracting the industries due to its efficient operation and accurate speed control. Cogging torque is an undesirable characteristic of permanent magnet motors and is caused by the geometry of the motor. Generation of Cogging torque directly affects the starting capability, produces noise and mechanical vibration. Thus, minimizing cogging torque is important in improving the performance of permanent magnet motors. Various methods of reducing cogging torque are discussed and a better method of reducing the cogging torque is proposed. In this study, the possible arrangements for the magnet segments are simulated by Finite Element Method (FEM) and the cogging torques are analyzed. As a result various arrangements are compared in case of average torque and the optimum method is proposed. The results show a appreciable decrease in cogging torque.
This paper presents an image segmentation system that automatically segments brain magnetic resonance (MR) images. The approach is based on an unsupervised learning algorithm of the hybrid topology preserving map (HTPM). Cooccurrence matrix method is applied to the images to obtain texture information for distinguishing different tissues. Statistical information of the different tissues is extracted by applying spatial filtering to the coefficients of cooccurrence matrix. These features are used as input to the HTPM. HTPM is used to segment images in a competitive unsupervised approach. Results are evaluated using F1 Score and are compared with manually segmented images. Our system is having 0.82 F1 score and 96% accuracy. Quantitative comparisons of our system with the manually segmented images on real brain MR images using F1 Score demonstrates that our system shows better segmentation performance for the segmentation of brain tumor.
An Increasing number of current applications make huge volumes of very high dimensional data. In scientific databases, for example, it is common to assemble large sets of observations, represented by hundreds or even thousands of coordinates. Unfortunately the rate of data generation and growth significantly out performs our ability to explore and analyze it. Nevertheless, in order to extract knowledge from these datasets, need to access the original, hidden information. However, the size and dimensionality of these collections makes their processing and analysis impractical or even ineffective. Therefore scaling up knowledge discovery algorithms for data of both high dimensionality and cardinality has been recently identified as one of the major problems in data mining research. In parallel, the development of the internet as well as the appearance of novel applications, such as peer-to peer systems, has led to an unmatched distribution of available information. Data is distributed among network notes, making the cost of centralizing and subsequent processing excessive. Subsequently, distributed data mining and distributed knowledge discovery have also emerged as highly challenging tasks.
In this study, litigation risk factors were determined for accounting professional liability insurance and an artificial neural network was developed to determine the litigation risks. A training data set comprised of data from 201 policies was used to train an artificial neural network. The performance of the artificial neural network model was then assessed using a test data set comprised of data from 100 policies. In the research, a litigation risk estimation model was formed for liability insurance via an artificial neural network model. By comparing the litigation risks occurring in accounting professional liability insurance to those foreseen by the artificial neural network system, it was determined that the results were quite consistent. It was also determined that the realized results and the risks foreseen in the artificial neural network model provided data close to the real values and that the artificial neural network model could foresee the litigation risks in accounting professional liability insurance with a 99% success rate.
Coleus forskohlii is a botanical that has been used since ancient times in Hindu and Ayurvedic traditional medicine. The root portion of the plant has been traditionally used for medicinal purposes and contains the active constituent and forskolin. In this work, Experimental investigations of heat transfer, friction factor and thermal performance of hybrid model of plain tube collector type of solar dryer integrated with Bio-mass backup heater are analyzed. Experiments are carried out for plain tube method under natural circulation mode. Then the experimental Nusselt number and friction factors are compared and the predictions are made the deviations are found to fall within the acceptable limits of ± 7.95% and ± 13.65%. And also integrated system is to be evaluated using three methods like only solar dryer, only biomass dryer and Hybrid technique of solar dryer integrated with bio-mass dryer. Integrated model produced the better optimum results.
Software artifacts hold a relevant significance, both in the different sectors of the industry and also in the everyday lives of almost every person. The wide-spread use of mobile devices emphasized the importance of mobile application development. It has recently become one of the most significant areas in software industry. Alongside the increasing number of different target mobile platforms, the necessity for reliable and efficient applications is also growing rapidly. This paper introduces technology for multi-platform mobile application development. The approach utilizes the findings of our research team carried out during the last decade. There are four software areas we are actively researching, namely (i) mobile platforms, (ii) software modeling and model processing, (iii) distributed systems and cloud computing, and (iv) data technologies. Based on the realized results of these areas, the technology introduced by this paper provides a coherent methodology describing how to develop multi-platform mobile applications. The solution encompasses the model processing and cloud computing capabilities. As a result, it is possible to effectively develop energy efficient mobile applications for different mobile platforms. The paper emphasizes the role of research groups with multi-disciplinary software competence. These groups can achieve effective solutions for different problems in each software area.
A Mobile Ad hoc Network (MANET) consists of nodes that move arbitrarily and forms dynamic topologies. Node behaviour may exist depending on the nature of the infrastructure and hardly accessible battery-dependant energy. An incisive mobile node may effort to benefit from other nodes, but declines to share its own resources. Such mobile nodes are designated misbehaving or selfish nodes. These selfish nodes may strictly have an impact on the performance of network. Existing network protocols do not have the feature to perceive the malicious packet dropping attack. In this paper, a selfish aware routing protocol called Selfish Aware AODV (SAODV) is proposed to enhance the security of AODV routing protocol by detecting misbehaved nodes and avoid them in other transmissions. In SAODV protocol, improved 2 Acknowledgement (i2ACK) scheme is incorporated on the top of AODV protocol. The aim of i2ACK scheme is to overcome 2 ACK weaknesses in detecting malicious nodes and also improving 2ACK scheme. This paper also discusses the improvement of the 2ACK scheme which is used in existing SDSR protocol. The i2ACK extension mechanism scheme for SAODV routing protocol has been analyzed using network simulator Qualnet v4.5. Packet delivery ratio, routing overhead, end to end delay and the number of false alarms are used as metrics to compare the performance of SAODV with existing SDSR and STACK scheme.\nKeywords: MANET, routing, selfishness, packet dropping, acknowledgement, AODV
A new algorithm for determining optimal placement and sizing of multiple distributed generators is presented in this paper. Featuring a combination of voltage stability (VS) and particle swarm optimization (PSO) is the advantage of the technique. Overall algorithm is divided into two. Firstly, optimal DG locations are determined using power transfer stability index and secondly, the sizes are computed by PSO algorithm. The objectives of the optimization are to enhance the system voltage profile and minimize total power losses. The proposed algorithm was tested on IEEE 30 bus test system and the results revealed that optimal placement of multiple DG improved the system voltage stability.
Solar Chimney plays an important role in a wide range of application to improve cooling system efficiency such as drying process, and single and multi-story buildings ventilation against temperature rising. In this paper, predication of air velocity in Solar Chimney (SC) to improve photovoltaic (PV) system efficiency against rising in operating temperature using Neural-Fuzzy system (Anfis) )was proposed. First, a brief description of theoretical solar cooling chimney module and discusses the effect it’s parameter on the air flow velocity. Theoretical analysis used to generate learning data by using standard solar panels integrated with 40 SC modules with varying PV energy. Three ANFIS models with different input nodes representing the input layers is made 4 nodes height Hc, Width Wc, thickness tc and wall temperature Tsa and one output node represented by maximum air flow velocity. .The range of Sc simulation model were, Hc range 0.5m–3m and, Wc range 0.1m-0.5m, tc range 0.1m-0.5m, and Pressure difference between inlet and outlet increase from 0.5 to 5.3 KPa. Further the temperature drop in the photovoltaic panel is also estimated based on predicted air velocities. Simulation result shows the predicted air flow velocity inside solar chimney closely match with the analytical data.
In this paper, the new modification of Laplace decomposition method has been used to obtain solutions of the seventh order KdV equations. The numerical solutions are compared with the Adomian decomposition method (ADM) and the known analytical solutions. The results show that the method converges rapidly and approximates the exact solution very accurately using only few iterates of the recursive scheme.
This paper extends the dynamic capability perspective to the study of innovation that has been adopted by an eLearning company. Our structural equation modeling results, based on a sample of 249 eLearning companies, indicate that both the firm’s resource stock of alliance capability and external opportunity-recognizing integrative capabilities affect its eLearning innovation. The results revealed that both alliance capabilities and external opportunity-recognizing integrative capabilities had significant positive impact on eLearning innovation. Additionally, the results showed that external opportunity-recognizing integrative capabilities had a stronger impact on eLearning innovation than learning capacities did. Implications for companies and for researchers are reported.
The present work is aimed at automating the assessment of overall ground water quality through the application software using Water Quality Index (WQI) method. Ground water samples were collected from 35 bore-wells from either side of the Cooum river. The analysis focused on the determination of specific water quality parameters, viz pH, EC, TDS, Ca, Mg, Na, SO4, CO3, HCO3, Fe and Cl using standard procedures. The statistical analysis, like the mean and standard deviation of the obtained data were carried out. The water quality analysis of the collected samples revealed that the stated water quality parameters have not complied with the WHO standards, and about 46% of the collected water samples is not fit for drinking and domestic purposes. Present study recommends that top priority should be given for ground water quality management to make water for potable purpose.
House Money Effect and Risk Aversion Effect are among the emotional factors having an influence on the risk level perceived by the investors. The aim of this study is to determine whether 100 individual stock investors, operating at Istanbul Stock Exchange (ISE) during 2009 - 2011 period, were exposed to House Money Effect and Risk Aversion Effect or not. In the regression analyses performed using the real data belonging to 100 individual stock investors, it was detected that the profit and losses were influential on the next risky decisions of the investors, in case it was profit, this effect lasted longer, if the result was loss, this effect lasted shorter. Another important finding of the study was that as the amount of the profit or loss increased, its effect on the investor also increased.
An on-load tap-changer (OLTC) is an indispensable operating equipment for the regulation of power transformers in energy supplying networks. The importance of on-load tap-changers has steadily been increasing with the years. Today, almost all generator-type transformer and power transformers are equipped with on-load tap-changers. Not only is this similarly true for networks of all other industrial states, but also does the energy supply in developing countries more and more ask for regulated power transformers. It can generally be stated that an increase in the density and link of a network goes together wit an increase in the necessity for the regulationg transformer[1].\nIn this study; after giving a brief about the type of high speed resistor on-load tap-changers, the process of changing a tap-changer has been modeled in Matlab Simulink environment.In order to verify the simulation results, the process of changing a tap changer has been repeated in the labarotory by using Crouzet brand of PLC.The experimentel data has been transferred to PC through the Tektronix brand 4-channel digital oscilloscope. The data obtained here has verified the tap changer model. Then a new model has been created by combining the tap changer model and the power transformer.This model has been simulated again under balanced processing conditions in Matlab Simulank environment and current-voltage changes of a phase of the system which is during the transition are discussed.
The basic objective of this paper is to perform real time stereo matching algorithm for real time applications. Real time stereo matching is implemented through likelihood model. To increase and to improve the accuracy of disparity estimation a post processing is suggested. Initially stereo matching is implemented on the basis of rank transform. Using adaptive interaction among neighboring disparities, smoothness of disparity map and pixel wise energy function are defined. By combining the minimized joined energy function with the stereo matching, a model disparity is determined. Stereo images available from Internet are used for evaluation. The experiments with the proposed algorithm gives the clean and good estimated accuracy over 30 frames per second for 640x480 image and 60 disparity range. The proposed algorithm can be used for any 3D image display, depth based object extraction and 3D rendering.
Employee engagement is a critical aspect of organizational business success in today’s time. Motivated employee can surely bring innovative thoughts that may take the business to a higher level. Organizations float Employee Engagement Survey (ESS) on a regular basis to gauge the pulse of their employees so that business strategies can be realigned based upon the feedback shared by employees through ESS. Whole survey is divided into two parts with one addressing the structured replies from the employees and the other focuses on the feedback / suggestions given by employees in the form of unstructured data. A lot of business intelligence tools are available to analyze the outcome of such survey. These tools are licensed, proprietary ones and obviously costly. In this paper, authors suggest a very cost effective way to analysis such type of survey using Apache Hadoop, which is open source software. Map-Reduce (MR) is used to handle structured as well as unstructured data coming from the survey dataset.
The increasing demand of energy saving from society is the external force for the development of Permanent Magnet Brushless DC (PMBLDC) motor drives. It is however driven by a hard-switching pulse width modulation (PWM) inverter, which has low switching frequency, high switching loss, high electro-magnetic interference (EMI), high acoustic noise and low efficiency, etc. To solve these problems of the hard-switching inverter, many soft-switching inverters have been designed in the past. Unfortunately, high device voltage stress, large dc link voltage ripples, complex control scheme and so on are noticed in the soft-switching inverters. This paper introduces a fuzzy logic controller based soft-switching inverter using transformer, which can generate dc link voltage notches during chopping which minimize the drawbacks of soft-switching. Hence all switches work in zero-voltage switching condition. The experimental results show that the fuzzy logic controller renders a better transient response than the conventional proportional plus integral (PI) controller resulting in negligible overshoot, smaller settling time and rise time. Moreover the proposed controller provides low torque ripples and high starting torque. Both simulation and experimental results are presented to show the superiority of the proposed fuzzy logic controller based soft switching inverter.
Middleware provides reusable solution to regularly met problems like interoperability, security, heterogeneity. When networks are increasingly pervasive, middleware acts as a key building block for the growth of software systems. Heterogeneous services are composed and formed pervasive computing. A well-organized and interoperable communication system is the source of a pervasive environment. But the heterogeneity on network service levels met with a lot of constraints. To overcome the needs of more memory space and resources when number of services get increased, to build a component model with the service interface Markup Language-Interface Description Language(ML-IDL) for varied intra services wrapped in a single entity service component. To improve the services in mobile, web and desktop, an interface ML-IDL is used to build the components for the corresponding services in the software systems by keeping the components in some textual format. Then serialization/marshalling concept is used to render the appropriate service to the user based on the request arrives. The proposed Component Modeled Messaging Services(CMMS) is enabled with ML-IDL to combine related sub hierarchical components. The performance of CMMS model is estimated with multiple services in terms of time consumption rate for component invocation and memory size.
Construction industry is one of the major pillars of the economy in Malaysia. The more cross-boundary co-operation on economic activities implies heavier demands on new transportation and infrastructure developments. As the sustainability awareness rises globally, the construction industry is under increasing pressure to improve its efficiency of project delivery. The issue of sustainability continues to grow due to its relationship with overall Quality of Life in terms of economic, social and environmental of well-being. Therefore, satisfaction approach is needed in order to achieve sustainability in the construction so that the project expenditure will be within the allocated budget and given timeline. The sustainable developments are considered to be a means to improve the effectiveness of closing the final accounts. Final account in construction contracts is defined as the agreed statement of the amount of money to be paid at the end of a project contract by the owner to the contractor. Hence, the aim of this paper is to demonstrate the influence of final account closing satisfaction approach in achieving sustainability in the construction industry in Malaysia. This aim can be achieved via its objective in identifying the important attribute factors that can clearly distinguish between claims of the contractors and the employer. This paper can serve as a tool to achieve sustainability in construction projects through proper planning and understanding of strategies in term of value for money and other social considerations. Based on the results of the survey, this paper anticipates that pattern will emerge in form of the key performance indicators which measure project sustainability via final account closing satisfaction. The causal final account closing satisfaction, once identified, will be a useful piece of information to successfully implement a construction project. It is anticipated that the finding reported in this paper could assist the planning of future strategies and guidelines for the betterment of construction projects in Malaysia
Nowadays, Intrusion Detection Systems are facing a new challenge in dealing with big network data and have to operate in changing and adversarial network environments with diverse protocols, services, applications and so on. Existing approaches, such as the manual method using expert knowledge, will be inappropriate for IDSs. Machine learning, which is a field of study that gives computers the ability to learn without being explicitly programmed, is becoming more and more important for solving these challenges. This is because of the efficiency and effectiveness of the automatic learning algorithms, especially when the amount of network data is increasing rapidly. Three distinct machine learning algorithms are used in this work. They are Naïve Bayes for anomaly detection, Support Vector Machine for misuse detection and Fuzzy logic for final decision making.\n The drawback of the anomaly based intrusion detection in a wireless network is the high rate of false positive. This can be solved by a designing a machine learning based hybrid intrusion detection system by connecting a misuse detection module to the anomaly detection module. In this paper, we propose to develop a hybrid intrusion detection system for IEEE 802.11 networks, based on machine learning. In this Hybrid Intrusion Detection system, anomaly detection is performed using the Bayesian network technique and misuse detection is performed using the Support Vector Machine (SVM) technique. The overall decision of system is performed by the fuzzy logic. For anomaly detection using Bayesian network, each node has a monitoring agent and a classifier within it for its detection and a mobile agent for information collection. The anomaly is measured based on the naïve Bayesian technique. For misuse detection using SVM, all the data that lie within the hyper plane are considered to be normal whereas the data that lie outside the hyper plane are considered to be intrusive. The outputs of both anomaly detection and misuse detection modules are applied by the fuzzy decision rules to perform the final decision making.
Using Malaysia as a case study and in contrast to most studies that use aggregate models, this study employs a multi-sector computable general equilibrium model to provide perspectives on the sectorial aggregate adjustments of a sustained increase in petroleum products prices in the transport sector. Since transport is the main consumer of petroleum products in this country, the study highlights the transmission channels through which the rise in petroleum products’ prices affects the domestic economy. The simulation results suggest that the shock would have negative aggregate impacts, but would also encourage the reallocation of resources and would, therefore, induce inequality in sectorial adjustments. Furthermore, due to a decrease in total domestic output, total sales, total exports, and decrease in household consumption in the transport sectors, the shock was not beneficial for this sector as a whole. The non-citizen households have the highest decline in their consumption in these sectors. Finally, this shock leads to decline in energy consumption in the transport sectors.
A simple and efficient CBIR system with good retrieval accuracy is designed without using any intensive image processing feature extraction techniques. The unique indexed color histogram and wavelet decomposition based horizontal, vertical and diagonal image attributes (WH) serve as the main features for the retrieval system. Support vector machine (SVM) and decision tree (DT) is used for classification of these distinct image features to further improve the retrieval accuracy of the system. The performance of the proposed content based image classification and retrieval systems are evaluated with the standard SIMPLIcity dataset. The performance of the system is measured with precision as the metric. K-fold cross validation is used for validating the results. The proposed system performs obviously better than SIMPLIcity and all the other compared methods like FEI, FIRM and Simple Histogram.
Abstract\n\n\nHypodontiain the permanent dentition is a significant clinical challenge, particularly in the treatment of adolescent patients who are missing anterior teeth. They have severe aesthetic and psychological disorders and satisfying the aesthetic moment is the main motivation for treatment, but the goal in the management of hypodontia for the therapist is not only to improve the aesthetics but also to accomplish a good masticatory function with long lasting and predictable results.\nThe selection of an appropriate therapeutic option, needs multidisciplinary approach and team coordination, first during treatment planning and then for determining the most appropriate time and method for subsequent orthodontic, surgical and prosthetic treatment.\nThe aim of the authors is through the presentation of clinical material with hypodontia of the lateral incisors in maxilla and mandible,to show the need of multidisciplinary approach in the treatment of hypodontia using dental implants in the aesthetic region, and to emphasize the critical moments of the surgical aspects in order to achieve the best aesthetic and functional outcome.\nGood cooperation with the patients and their family is of particular importance, especially because of the long interval of orthodontic and surgical treatment until the final results are achieved.\n\n\nKey words: hypodontia, dental implants, surgical aspects, orthodontic therapy
Nowadays, in parallel with the advancing technology, automobiles that have substantially advanced technological properties are being manufactured. Intended uses of the automobiles have been changing in our days in contrast to 1960s when automobiles were only used for transportation. Consumers, in our day and age, expect profoundly different properties from an automobile. In this context, more than one criterion become effective on making decision on purchasing an automobile that has the required properties. In such a kind of decision problem, making use of multi criteria decision making methods will ease the solution of the problem and will enable the decision makers to make right decisions. \nIn this study, Fuzzy Analytic Network Process (Fuzzy ANP) method, one of the multi criteria decision making methods, was used in automobile purchasing decision making. Within the context of the study, some support was taken from the opinions of experts and from the results of similar studies in the determination of decision criteria. After determining decision criteria and alternatives, network structure of the automobile selection decision problem was formed, and by using fuzzy ANP method, optimal one was selected among three alternative automobiles that were in the same segment and were very approximate to each other in terms of their properties and prices.
Distributed database replication in the heterogeneous system is a very promising and challenging platform which is the compound of multi environment. Proper mechanism is significantly required in order to manage the complex heterogeneous data replication. This paper presents a new algorithm namely the Persistence Layer Synchronous Replication (PLSR) in order to manage the agent handling the replication. The main objective of this algorithm is to develop an adaptive persistence layer which consisted of reliable and smooth replication. It achieves faster time execution and cost minimization than that other replication processes. This algorithm also introduces a multi thread based persistence layer, which supports early binding and parallel connection to the servers. All the replication servers establish its connection through interfaces, which is furthermore, similar with the SOA (Service Oriented Architecture) and the structure is flexible enough to modify i.e.; adding and removing replication server. The performance has been compared with SQL Server in terms of transactional inserts and synchronization time. The result shows that PLSR performs outstandingly up to 83.2 % and 2.49% than that SQL server for transactional insert and time synchronization, respectively.
This paper presents an optimum long – term generation maintenance scheduling to enhance the grid reliability using Evolutionary Programming. Maintenance scheduling establishes the outage time scheduling of units in a particular time horizon. In a monopolistic power system, maintenance scheduling is being done upon the technical requirements of power plants and preserving the grid reliability. While in power system, technical viewpoints and system reliability are taken into consideration in maintenance scheduling with respect to the economical viewpoint. In this paper a genetic algorithm methodology for finding the optimum preventive maintenance scheduling of generating units in power system. The objective function is to maintain the units as earlier as possible. Varies constrains such as spinning reserve, duration of maintenance and maintenance crew are being taken into account. In case study, a 66 bus utility power system in India with twelve generating units and IEEE test system consist of 24 buses is used.
Multi Agent Systems have become a promising paradigm for developing distributed Applications. The inherent qualities of agent technology make it a perfect choice for many real world applications. However this usefulness can be undermined due to problems incurred by lack of fault tolerance and security in Multi Agent Based Applications. Distributed Systems are designed in such a way that it automatically recover from partial failures without seriously affecting the overall performance. In this paper we have proposed Smart Intelligent Fault Tolerant framework for Business Applications which provides fault tolerance (at both agent and system level) and security. An algorithm similar to the sliding window model ensures the agent level fault tolerance, while the system level fault tolerance has been provided by dynamic discovery of alternate paths. Different types of agents, work in collaborative manner to provide the desired system behavior by tolerating faults. The proposed framework is planned to be used in critical financial applications like Banking applications, E-commerce, Stock exchange etc. Therefore, information security being an important concern has also been catered for. Triple DES Algorithm is used for encryption / decryption and MD5 Algorithm is used for the integrity of the message. The proposed framework has been evaluated for financial transaction on an ATM machine and proposed framework yields improved transaction time and minimize the delays in transaction because of network faults.
This research paper compares the effect of temperature and irradiation over the Glass to Glass (G2G) and Glass to Tedlar (G2T) type PV panels. A G2G type panel is specially designed for the purpose of solar PVT system to improve the overall efficiency of the system. The effect of temperature and irradiation test was conducted in G2G and G2T type of PV panels. The real time test was conducted on December 2nd 2012 at Salem in the latitude and longitude of 11.574(N), 78.054(E) respectively. The 74W multicrystalline silicon solar panels were used for testing. The value of Open Circuit Voltage (Voc), Short Circuit Current (Isc), Maximum Power (Pmax), Maximum Voltage (Vmax), Maximum Current (Imax), Efficiency (η) and Fill Factor (FF) were calculated for varied temperatures and irradiation. The temperature and solar irradiation in different parts of the panels were measured. The effect of both temperature and irradiation on G2G and G2T were shown in the result. The efficiency and fill factor of the both panels were compared. The result showed that when the solar irradiation increased, then electrical output increased. The temperature also increased between 30.5˚C to 55.8˚C. At this temperature, the panel electrical efficiency was 14.82%. It was found that the electrical performance of the panel mainly depends on the irradiation and temperature. By reducing the temperature of the panel to 25˚C (STC), the efficiency of the PV panel increased more, at the same time the temperature absorbed from the panel is stored in water circulated on the panel. The hot water stored in insulated water tank that can be used for the domestic applications. On increasing the efficiency of the panel and retaining the heat, the overall efficiency of the panel could be improved
ABSTRACT\nTurkey signed European Charter of Local Self Government (E.C.L.G.) in 1988 by inscribing reservations on some of its articles. Not only do inscribing reservations on some articles prevent domination of local autonomy conditions in Turkey at its fullest but also some articles signed cannot be adopted due to effects of centralistic traditions for long years. In spite of constitutional amendments in 2004, 2005 and 2012 in Turkey, continuing problems are deficiencies in financial autonomy, problems occurring in methods implemented for accession and dismissal of local government organs and imbalances in delegations among central government and local government. The purpose of this study is to reveal implantation status of E.C.L.G., deficiencies in the Constitution pertaining to this issue and amendments required. To this end, concept of local autonomy will be dealt with and Turkish local government system will be evaluated and amendments required to be made in the Constitution will be tried to be defined. \nKeywords: European Charter of Local Self Governments, the Constitution, Local Government, Local Government, Financial Autonomy.
In order to assess the magnitude of suppressing capability of Calotropis procera Decne. on Parkinsonia aculeate L., the present study was conducted. The idea was quoted from the visual observation of the later as a desert weed of rare occurrence concomitant to the former in its communities. The investigation aims at elucidating the effect of organic mulching on the seed germination and growth of Parkinsonia. In a greenhouse potted experiment, Parkinsonia seeds were subjected to three mulch rates (1.5, 3 & 6 ton ha-1) of Calotropis Leaf Dry matter (CLD).The results showed that organic mulches significantly affected the final seed germination as well as the germination rate of Parkinsonia. Organic mulching also encouraged the R/S ratio (at bases of length), only at the mature vegetative stage. On bases of dry weight, R/S ratio was inhibited; particularly at the rates (1.5 & 6 ton ha-1) at the juvenile stage. There was a decrease of the leaves numbers of mulched plants compared to the non-mulched ones. The Parkinsonia leaf area and average dry weight decreased at the intermediate rate of 3 ton ha-1, especially at the juvenile stage. Specific leaf area (SLA) decreased at all mulch rates; particularly at juvenile stage.
