Search results for: Ignition delay time

Authors: L. Abdelmalek, M. Zerikat, M. Rahli

Abstract:

In this paper, we present a comparative study of the genetic algorithms and Hessian-s methods for optimal research of the active powers in an electric network of power. The objective function which is the performance index of production of electrical energy is minimized by satisfying the constraints of the equality type and inequality type initially by the Hessian-s methods and in the second time by the genetic Algorithms. The results found by the application of AG for the minimization of the electric production costs of power are very encouraging. The algorithms seem to be an effective technique to solve a great number of problems and which are in constant evolution. Nevertheless it should be specified that the traditional binary representation used for the genetic algorithms creates problems of optimization of management of the large-sized networks with high numerical precision.

Keywords: Genetic algorithm, Flow of optimum loadimpedances, Hessians method, Optimal distribution.

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Authors: S. D. Nedelcut, V. Proca, D. M. Purcaru

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At present, the tendency to implement the conditionbased maintenance (CBM), which allows the optimization of the expenses for equipment monitoring, is more and more evident; also, the transformer substations with remote monitoring are increasingly used. This paper reviews all the advantages of the on-line monitoring and presents an equipment for on-line monitoring of bushings, which is the own contribution of specialists who are the authors of this paper. The paper presents a study of the temperature field, using the finite element method. For carrying out this study, the 3D modelling of the above mentioned bushing was performed. The analysis study is done taking into account the extreme thermal stresses, focusing at the level of the first cooling wing section of the ceramic insulator. This fact enables to justify the tanδ variation in time, depending on the transformer loading and the environmental conditions. With a view to reducing the variation of dielectric losses in bushing insulation, the use of ferrofuids instead of mineral oils is proposed.

Keywords: Monitoring, dielectric losses, ferrofluids, bushing.

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Authors: Vita Levkane, Sandra Muizniece-Brasava, Lija Dukalska

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Experiments have been carried out at the Latvia University of Agriculture Department of Food Technology. The aim of this work was to assess the effect of sous vide packaging during the storage time of salad with meat in mayonnaise at different storage temperature. Samples were evaluated at 0, 1, 3, 7, 10, 15, 18, 25, 29, 42, and 52 storage days at the storage temperature of +4±0.5 ºC and +10±0.5 ºC. Experimentally the quality of the salad with meat in mayonnaise was characterized by measuring colour, pH and microbiological properties. The sous vide packaging was effective in protecting the product from physical, chemical, and microbial quality degradation. The sous vide packaging significantly reduces microbial growth at storage temperature of +4±0.5 ºC and +10±0.5 ºC. Moreover, it is possible to extend the product shelf life to 52 days even when stored at +10±0.5 ºC.

Keywords: salad with meat in mayonnaise, shelf life, sous videpackaging.

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Authors: Naiqin Feng, Fang Wang, Yuhui Qiu

Abstract:

A new approach to promote the generalization ability of neural networks is presented. It is based on the point of view of fuzzy theory. This approach is implemented through shrinking or magnifying the input vector, thereby reducing the difference between training set and testing set. It is called “shrinking-magnifying approach" (SMA). At the same time, a new algorithm; α-algorithm is presented to find out the appropriate shrinking-magnifying-factor (SMF) α and obtain better generalization ability of neural networks. Quite a few simulation experiments serve to study the effect of SMA and α-algorithm. The experiment results are discussed in detail, and the function principle of SMA is analyzed in theory. The results of experiments and analyses show that the new approach is not only simpler and easier, but also is very effective to many neural networks and many classification problems. In our experiments, the proportions promoting the generalization ability of neural networks have even reached 90%.

Keywords: Fuzzy theory, generalization, misclassification rate, neural network.

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Authors: Imen Ammari, Mourad Elloumi, Ala Eddine Barouni

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Visualizing “Courses – Pre – Required - Architecture" on the screen has proven to be useful and helpful for university actors and specially for students. In fact, these students can easily identify courses and their pre required, perceive the courses to follow in the future, and then can choose rapidly the appropriate course to register in. Given a set of courses and their prerequired, we present an algorithm for visualization a graph entitled “Courses-Pre-Required-Graph" that present courses and their prerequired in order to help students to recognize, lonely, what courses to take in the future and perceive the contain of all courses that they will study. Our algorithm using “Force Directed Placement" technique visualizes the “Courses-Pre-Required-Graph" in such way that courses are easily identifiable. The time complexity of our drawing algorithm is O (n2), where n is the number of courses in the “Courses-Pre-Required-Graph".

Keywords: Courses–Pre-Required-Architecture, Courses-Pre- Required-Graph, Courses-Pre-Required-Visualization, Force directed Placement, Resolution.

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Authors: Abhishek Swaroop, Awadhesh Kumar Singh

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The group mutual exclusion (GME) problem is a variant of the mutual exclusion problem. In the present paper a token-based group mutual exclusion algorithm, capable of handling transient faults, is proposed. The algorithm uses the concept of dynamic request sets. A time out mechanism is used to detect the token loss; also, a distributed scheme is used to regenerate the token. The worst case message complexity of the algorithm is n+1. The maximum concurrency and forum switch complexity of the algorithm are n and min (n, m) respectively, where n is the number of processes and m is the number of groups. The algorithm also satisfies another desirable property called smooth admission. The scheme can also be adapted to handle the extended group mutual exclusion problem.

Keywords: Dynamic request sets, Fault tolerance, Smoothadmission, Transient faults.

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Authors: F. Yildiz, S. Y. Oturanc

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Advances technology in the field of photogrammetry replaces analog cameras with reflection on aircraft GPS/IMU system with a digital aerial camera. In this system, when determining the position of the camera with the GPS, camera rotations are also determined by the IMU systems. All around the world, digital aerial cameras have been used for the photogrammetry applications in the last ten years. In this way, in terms of the work done in photogrammetry it is possible to use time effectively, costs to be reduced to a minimum level, the opportunity to make fast and accurate. Geo-referencing techniques that are the cornerstone of the GPS / INS systems, photogrammetric triangulation of images required for balancing (interior and exterior orientation) brings flexibility to the process. Also geo-referencing process; needed in the application of photogrammetry targets to help to reduce the number of ground control points. In this study, the use of direct and indirect georeferencing techniques on the accuracy of the points was investigated in the production of photogrammetric mapping.

Keywords: Photogrammetry, GPS/IMU Systems, Geo- Referencing.

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Authors: Mohammadreza Nezamirad, Azadeh Yazdi, Sepideh Amirahmadian, Nasim Sabetpour, Amirmasoud Hamedi

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In this study, the Reynolds-Stress-Navier-Stokes framework is utilized to investigate the flow inside the diesel injector nozzle. The flow is assumed to be multiphase as the formation of vapor by pressure drop is visualized. For pressure and velocity linkage, the coupled algorithm is used. Since the cavitation phenomenon inherently is unsteady, the quasi-steady approach is utilized for saving time and resources in the current study. Schnerr-Sauer cavitation model is used, which was capable of predicting flow behavior both at the initial and final steps of the cavitation process. Two different turbulent models were used in this study to clarify which one is more capable in predicting cavitation inception and super-cavitation. It was found that K-ε was more compatible with the Shnerr-Sauer cavitation model; therefore, the mentioned model is used for the rest of this study.

Keywords: CFD, RANS, cavitation, fuel, injector.

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Authors: R.S Pugazenthi, Andy C. McIntosh

Abstract:

Plasma Wind Tunnels (PWT) are extensively used for screening and qualification of re-entry Thermel Protection System (TPS) materials. Proper design of a supersonic diffuser for plasma wind tunnel is of importance for achieving good pressurerecovery (thereby reducing vacuum pumping requirement & run time costs) and isolating downstream stream fluctuations from propagating costs) and isolating downstream stream fluctuationnts the details of a rapid design methodology successfully employed for designing supersonic diffuser for high power (several megawatts)plasma wind tunnels and numerical performance analysis of a diffuser configuration designed for one megawatt power rated plasma wind tunnel(enthalpy ~ 30 MJ/kg) using FLUENT 6.3® solver for different diffuser operating sub-atmospheric back-pressures.

Keywords: Compressible flow, plasma wind tunnel, re-entry, supersonic diffuser

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Authors: Mayank Shakya, Soundra Pandian. K. K

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A linear feedback shift register (LFSR) is proposed which targets to reduce the power consumption from within. It reduces the power consumption during testing of a Circuit Under Test (CUT) at two stages. At first stage, Control Logic (CL) makes the clocks of the switching units of the register inactive for a time period when output from them is going to be same as previous one and thus reducing unnecessary switching of the flip-flops. And at second stage, the LFSR reorders the test vectors by interchanging the bit with its next and closest neighbor bit. It keeps fault coverage capacity of the vectors unchanged but reduces the Total Hamming Distance (THD) so that there is reduction in power while shifting operation.

Keywords: Linear Feedback Shift Register, Total Hamming Distance, Fault Coverage, Control Logic

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Authors: J. R. Wang, W.Y. Li, H.T. Lin, B.H. Lee, C. Shih, S.W. Chen

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In this research, the TRACE/PARCS model of  Lungmen ABWR has been developed for verification of ultimate  response guideline (URG) efficiency. This ultimate measure was  named as DIVing plan, abbreviated from system depressurization,  water injection and containment venting. The simulation initial  condition is 100% rated power/100% rated core flow. This research  focuses on the estimation of the time when the fuel might be damaged  with no water injection by using TRACE/PARCS first. Then, the  effect of the reactor core isolation system (RCIC), control  depressurization and ac-independent water addition system (ACIWA),  which can provide the injection with 950 gpm are also estimated for  the station blackout (SBO) transient.

 

Keywords: ABWR, TRACE, safety analysis, PARCS.

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Authors: Anton Stadler, Thorsten Ike

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In this paper, we present a video based smoke detection algorithm based on TVL1 optical flow estimation. The main part of the algorithm is an accumulating system for motion angles and upward motion speed of the flow field. We optimized the usage of TVL1 flow estimation for the detection of smoke with very low smoke density. Therefore, we use adapted flow parameters and estimate the flow field on difference images. We show in theory and in evaluation that this improves the performance of smoke detection significantly. We evaluate the smoke algorithm using videos with different smoke densities and different backgrounds. We show that smoke detection is very reliable in varying scenarios. Further we verify that our algorithm is very robust towards crowded scenes disturbance videos.

Keywords: Low density, optical flow, upward smoke motion, video based smoke detection.

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Authors: Hassan Masoumi, Ahad Salimi, Nazanin Barhemmat, Babak Gholami

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Artificial neural networks have gained a lot of interest as empirical models for their powerful representational capacity, multi input and output mapping characteristics. In fact, most feedforward networks with nonlinear nodal functions have been proved to be universal approximates. In this paper, we propose a new supervised method for color image classification based on selforganizing feature maps (SOFM). This algorithm is based on competitive learning. The method partitions the input space using self-organizing feature maps to introduce the concept of local neighborhoods. Our image classification system entered into RGB image. Experiments with simulated data showed that separability of classes increased when increasing training time. In additional, the result shows proposed algorithms are effective for color image classification.

Keywords: Classification, SOFM, neural network, RGB images.

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Authors: Phakhapong Thanitakul, Worawat Sa-ngiamvibool, Apinan Aurasopon, Saravuth Pothiya

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This paper presents an improved ant colony optimization (IACO) for solving the reliability redundancy allocation problem (RAP) in order to maximize system reliability. To improve the performance of ACO algorithm, two additional techniques, i.e. neighborhood search, and re-initialization process are presented. To show its efficiency and effectiveness, the proposed IACO is applied to solve three RAPs. Additionally, the results of the proposed IACO are compared with those of the conventional heuristic approaches i.e. genetic algorithm (GA), particle swarm optimization (PSO) and ant colony optimization (ACO). The experimental results show that the proposed IACO approach is comparatively capable of obtaining higher quality solution and faster computational time.

Keywords: Ant colony optimization, Heuristic algorithm, Mixed-integer nonlinear programming, Redundancy allocation problem, Reliability optimization.

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Authors: Mohammad Ghavami, Reza S. Dilmaghani

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This paper presents an adaptive framework for modelling financial markets using equity risk premiums, risk free rates and volatilities. The recorded economic factors are initially used to train four adaptive filters for a certain limited period of time in the past. Once the systems are trained, the adjusted coefficients are used for modelling and prediction of an important financial market index. Two different approaches based on least mean squares (LMS) and recursive least squares (RLS) algorithms are investigated. Performance analysis of each method in terms of the mean squared error (MSE) is presented and the results are discussed. Computer simulations carried out using recorded data show MSEs of 4% and 3.4% for the next month prediction using LMS and RLS adaptive algorithms, respectively. In terms of twelve months prediction, RLS method shows a better tendency estimation compared to the LMS algorithm.

Keywords: Prediction of financial markets, Adaptive methods, MSE, LSE.

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Authors: Amin Safari, Hossein Shayeghi

Abstract:

This paper presents a novel approach for tuning unified power flow controller (UPFC) based damping controller in order to enhance the damping of power system low frequency oscillations. The design problem of damping controller is formulated as an optimization problem according to the eigenvalue-based objective function which is solved using iteration particle swarm optimization (IPSO). The effectiveness of the proposed controller is demonstrated through eigenvalue analysis and nonlinear time-domain simulation studies under a wide range of loading conditions. The simulation study shows that the designed controller by IPSO performs better than CPSO in finding the solution. Moreover, the system performance analysis under different operating conditions show that the δE based controller is superior to the mB based controller.

Keywords: UPFC, Optimization Problem, Iteration ParticleSwarm Optimization, Damping Controller, Low FrequencyOscillations.

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Authors: Ali Abdrhman Ukasha

Abstract:

This paper presented two new efficient algorithms for contour approximation. The proposed algorithm is compared with Ramer (good quality), Triangle (faster) and Trapezoid (fastest) in this work; which are briefly described. Cartesian co-ordinates of an input contour are processed in such a manner that finally contours is presented by a set of selected vertices of the edge of the contour. In the paper the main idea of the analyzed procedures for contour compression is performed. For comparison, the mean square error and signal-to-noise ratio criterions are used. Computational time of analyzed methods is estimated depending on a number of numerical operations. Experimental results are obtained both in terms of image quality, compression ratios, and speed. The main advantages of the analyzed algorithm is small numbers of the arithmetic operations compared to the existing algorithms.

Keywords: Polygonal approximation, Ramer, Triangle and Trapezoid methods.

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Authors: Z.Farhadpour, Mohammad.R.Meybodi

Abstract:

A number of routing algorithms based on learning automata technique have been proposed for communication networks. How ever, there has been little work on the effects of variation of graph scarcity on the performance of these algorithms. In this paper, a comprehensive study is launched to investigate the performance of LASPA, the first learning automata based solution to the dynamic shortest path routing, across different graph structures with varying scarcities. The sensitivity of three main performance parameters of the algorithm, being average number of processed nodes, scanned edges and average time per update, to variation in graph scarcity is reported. Simulation results indicate that the LASPA algorithm can adapt well to the scarcity variation in graph structure and gives much better outputs than the existing dynamic and fixed algorithms in terms of performance criteria.

Keywords: Learning automata, routing, algorithm, sparse graph

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Authors: Noor Suhana Sulaiman, Rohani Abu Bakar, Norrozila Sulaiman

Abstract:

Intrusion Detection System is significant in network security. It detects and identifies intrusion behavior or intrusion attempts in a computer system by monitoring and analyzing the network packets in real time. In the recent year, intelligent algorithms applied in the intrusion detection system (IDS) have been an increasing concern with the rapid growth of the network security. IDS data deals with a huge amount of data which contains irrelevant and redundant features causing slow training and testing process, higher resource consumption as well as poor detection rate. Since the amount of audit data that an IDS needs to examine is very large even for a small network, classification by hand is impossible. Hence, the primary objective of this review is to review the techniques prior to classification process suit to IDS data.

Keywords: Intrusion Detection System, security, soft computing, classification.

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Authors: A. A. AlRasheed, A. Atkins, R. Campion

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This paper focuses on using knowledge management and visualisation concepts to improve the patients and hospitals employee’s workflow. Hospitals workflow is a complex and complicated process and poor patient flow can put both patients and a hospital’s reputation at risk, and can threaten the facility’s financial sustainability. Healthcare leaders are under increased pressure to reduce costs while maintaining or increasing patient care standards. In this paper, a framework is proposed to help improving patient experience, staff satisfaction, and operational efficiency across hospitals by using knowledge management based visualisation concepts. This framework is using real-time visibility to track and monitor location and status of patients, staff, rooms, and medical equipment.

Keywords: Knowledge management, visualisation, patients, hospitals, healthcare workers, workflow, improvements.

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Authors: Sumeet S. Nisale, Chandan J. Bharambe, Vidya N.More

Abstract:

We propose our genuine research of geometric moments which detects the mineral inadequacy in the frail groundnut plant. This plant is prone to many deficiencies as a result of the variance in the soil nutrients. By analyzing the leaves of the plant, we detect the visual symptoms that are not recognizable to the naked eyes. We have collected about 160 samples of leaves from the nearby fields. The images have been taken by keeping every leaf into a black box to avoid the external interference. For the first time, it has been possible to provide the farmer with the stages of deficiencies. This paper has applied the algorithms successfully to many other plants like Lady-s finger, Green Bean, Lablab Bean, Chilli and Tomato. But we submit the results of the groundnut predominantly. The accuracy of our algorithm and method is almost 93%. This will again pioneer a kind of green revolution in the field of agriculture and will be a boon to that field.

Keywords: Component image, geometric moments, average intensity, average affected area, black box

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Authors: Raluca-Ioana Horea-Şerban, Marinela Istrate

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The first part of the paper analyzes the dynamics of the total fertility rate both at the national and regional level, pointing out the regional disparities in the distribution of this indicator. At the same time, we also focus on the collapse of the number of live births, on the changes in the fertility rate by birth rank, as well as on the failure of acquiring the desired number of children. The second part of the study centres upon a survey applied to urban families with 3 and more than 3 offspring. The preliminary analysis highlights the fact that an increased fertility (more than 3rd rank) is triggered by the parents’ above the average material condition and superior education. The current situation of Romania, which is still passing through a period of relatively rapid demographic changes, marked by numerous convulsions, requires a new approach, in compliance with the recent interpretations appropriate to a new post-transitional demographic regime.

Keywords: Family size intention, fertility rate, regional disparities, third birth rank.

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Authors: B. I. Yun

Abstract:

A dual-reciprocity boundary element method is presented for the numerical solution of a class of axisymmetric elastodynamic problems. The domain integrals that arise in the integrodifferential formulation are converted to line integrals by using the dual-reciprocity method together suitably constructed interpolating functions. The second order time derivatives of the displacement in the governing partial differential equations are suppressed by using Laplace transformation. In the Laplace transform domain, the problem under consideration is eventually reduced to solving a system of linear algebraic equations. Once the linear algebraic equations are solved, the displacement and stress fields in the physical domain can be recovered by using a numerical technique for inverting Laplace transforms.

Keywords: Axisymmetric elasticity, boundary element method, dual-reciprocity method, Laplace transform.

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Authors: Jun-Oh Kim, Seol-Min Yang, Seok-Heum Baek, Sangmo Kang

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In this paper, the shape design process is briefly discussed emphasizing the use of topology optimization in the conceptual design stage. The basic idea is to view feasible domains for sensitivity region concepts. In this method, the main process consists of two steps: as the design moves further inside the feasible domain using Taguchi method, and thus becoming more successful topology optimization, the sensitivity region becomes larger. In designing a double-eccentric butterfly valve, related to hydrodynamic performance and disc structure, are discussed where the use of topology optimization has proven to dramatically improve an existing design and significantly decrease the development time of a shape design. Computational Fluid Dynamics (CFD) analysis results demonstrate the validity of this approach.

Keywords: Double-eccentric butterfly valve, CFD, Topology optimization

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Authors: A. P. Anvar, T. Dowling, T. Putland, A. M. Anvar, S.Grainger

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This paper presents the application of Intelligent Techniques to the various duties of Intelligent Condition Monitoring Systems (ICMS) for Unmanned Aerial Vehicle (UAV) Robots. These Systems are intended to support these Intelligent Robots in the event of a Fault occurrence. Neural Networks are used for Diagnosis, whilst Fuzzy Logic is intended for Prognosis and Remedy. The ultimate goals of ICMS are to save large losses in financial cost, time and data.

Keywords: Intelligent Techniques, Condition Monitoring Systems, ICMS, Robots, Fault, Unmanned Aerial Vehicle, UAV, Neural Networks, Diagnosis, Fuzzy Logic, Prognosis, Remedy.

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Authors: Mohammadi K., Ghalavand A., Aghaalikhani M., Eskandari M.

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In order to increase in chickpea quality and agroecosystem sustainability, field experiments were carried out in 2007 and 2008 growing seasons. In this research the effects of different organic, chemical and biological fertilizers were investigated on grain yield and quality of chickpea. Experimental units were arranged in split-split plots based on randomized complete blocks with three replications. The highest amounts of yield and yield components were obtained in G1×N5 interaction. Significant increasing of N, P, K, Fe and Mg content in leaves and grains emphasized on superiority of mentioned treatment because each one of these nutrients has an approved role in chlorophyll synthesis and photosynthesis ability of the crop. The combined application of compost, farmyard manure and chemical phosphorus (N5) had the best grain quality due to high protein, starch and total sugar contents, low crude fiber and reduced cooking time.

Keywords: Agroecosystem, sustainability, chickpea, naturalresources.

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Authors: Pavel Y. Tabakov, Kevin Duffy

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The present study presents a new approach to automatic data clustering and classification problems in large and complex databases and, at the same time, derives specific types of explicit rules describing each cluster. The method works well in both sparse and dense multidimensional data spaces. The members of the data space can be of the same nature or represent different classes. A number of N-dimensional ellipsoids are used for enclosing the data clouds. Due to the geometry of an ellipsoid and its free rotation in space the detection of clusters becomes very efficient. The method is based on genetic algorithms that are used for the optimization of location, orientation and geometric characteristics of the hyper-ellipsoids. The proposed approach can serve as a basis for the development of general knowledge systems for discovering hidden knowledge and unexpected patterns and rules in various large databases.

Keywords: Classification, clustering, data minig, genetic algorithms.

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Authors: S. N. Deepa, G. Sugumaran

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This paper proposes a new algebraic scheme to design a PID controller for higher order linear time invariant continuous systems. Modified PSO (MPSO) based model order formulation techniques have applied to obtain the effective formulated second order system. A controller is tuned to meet the desired performance specification by using pole-zero cancellation method. Proposed PID controller is attached with both higher order system and formulated second order system. The closed loop response is observed for stabilization process and compared with general PSO based formulated second order system. The proposed method is illustrated through numerical example from literature.

Keywords: Higher order systems, model order formulation, modified particle swarm optimization, PID controller, pole-zero cancellation.

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Authors: Rafael Jorge Menezes Santos, Ginalber Luiz de Oliveira Serra, Carlos César Teixeira Ferreira

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This paper proposes a methodology for analysis of the dynamic behavior of a robotic manipulator in continuous time. Initially this system (nonlinear system) will be decomposed into linear submodels and analyzed in the context of the Linear and Parameter Varying (LPV) Systems. The obtained linear submodels, which represent the local dynamic behavior of the robotic manipulator in some operating points were grouped in a Takagi-Sugeno fuzzy structure. The obtained fuzzy model was analyzed and validated through analog simulation, as universal approximator of the robotic manipulator.

Keywords: modeling of nonlinear dynamic systems, Takagi- Sugeno fuzzy model, Linear and Parameter Varying (LPV) System.

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Authors: Sibel Uzuner, Jale Acar

Abstract:

Pomegranate and pomegranate juices (PJs) have taken great attention for their health benefits in the last years. As there is an increasing concern about potential health benefits of ellagic acid, it is of great interest to evaluate alterations in ellagic acid concentration of commercial PJs. The purpose of this study is to analyze total phenolic, free and total ellagic acid content of six commercial PJs sold in Turkish markets using HPLC. The results showed that some commercial PJs had markedly high total phenolic and ellagic acid content. Total phenolic substances of commercial PJs range from 796.71 to 4608.91 mg GAE/l. Free amount of ellagic acid in commercial PJs range from 27.64 to 111.78 mg/l. Samples are hydrolyzed with concentrated HCl at 93oC for 2 and 24 hour and influences of temperature and time parameters on hydrolization were investigated. Thermal processing for pasteurization increased ellagic acid via ellagitannins hydrolysis.

Keywords: Ellagic acid, ellagitannin, pomegranate juice, total phenolic compounds

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