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A Comparative Analysis of the Performance of COSMO and WRF Models in Quantitative Rainfall Prediction

Year: 2018 Volume: 12 Issue: 2 130 - 138 Pages

Abstract: The Numerical weather prediction (NWP) models are considered powerful tools for guiding quantitative rainfall prediction. A couple of NWP models exist and are used at many operational weather prediction centers. This study considers two models namely the Consortium for Small–scale Modeling (COSMO) model and the Weather Research and Forecasting (WRF) model. It compares the models’ ability to predict rainfall over Uganda for the period 21st April 2013 to 10th May 2013 using the root mean square (RMSE) and the mean error (ME). In comparing the performance of the models, this study assesses their ability to predict light rainfall events and extreme rainfall events. All the experiments used the default parameterization configurations and with same horizontal resolution (7 Km). The results show that COSMO model had a tendency of largely predicting no rain which explained its under–prediction. The COSMO model (RMSE: 14.16; ME: -5.91) presented a significantly (p = 0.014) higher magnitude of error compared to the WRF model (RMSE: 11.86; ME: -1.09). However the COSMO model (RMSE: 3.85; ME: 1.39) performed significantly (p = 0.003) better than the WRF model (RMSE: 8.14; ME: 5.30) in simulating light rainfall events. All the models under–predicted extreme rainfall events with the COSMO model (RMSE: 43.63; ME: -39.58) presenting significantly higher error magnitudes than the WRF model (RMSE: 35.14; ME: -26.95). This study recommends additional diagnosis of the models’ treatment of deep convection over the tropics.

Comparative Quantitative Study on Learning Outcomes of Major Study Groups of an Information and Communication Technology Bachelor Educational Program

Year: 2017 Volume: 11 Issue: 3 670 - 674 Pages

Abstract: Higher Education system reforms, especially Finnish system of Universities of Applied Sciences in 2014 are discussed. The new steering model is based on major legislative changes, output-oriented funding and open information. The governmental steering reform, especially the financial model and the resulting institutional level responses, such as a curriculum reforms are discussed, focusing especially in engineering programs. The paper is motivated by management need to establish objective steering-related performance indicators and to apply them consistently across all educational programs. The close relationship to governmental steering and funding model imply that internally derived indicators can be directly applied. Metropolia University of Applied Sciences (MUAS) as a case institution is briefly introduced, focusing on engineering education in Information and Communications Technology (ICT), and its related programs. The reform forced consolidation of previously separate smaller programs into fewer units of student application. New curriculum ICT students have a common first year before they apply for a Major. A framework of parallel and longitudinal comparisons is introduced and used across Majors in two campuses. The new externally introduced performance criteria are applied internally on ICT Majors using data ex-ante and ex-post of program merger.  A comparative performance of the Majors after completion of joint first year is established, focusing on previously omitted Majors for completeness of analysis. Some new research questions resulting from transfer of Majors between campuses and quota setting are discussed. Practical orientation identifies best practices to share or targets needing most attention for improvement. This level of analysis is directly applicable at student group and teaching team level, where corrective actions are possible, when identified. The analysis is quantitative and the nature of the corrective actions are not discussed. Causal relationships and factor analysis are omitted, because campuses, their staff and various pedagogical implementation details contain still too many undetermined factors for our limited data. Such qualitative analysis is left for further research. Further study must, however, be guided by the relevance of the observations.

A Comparative Study of High Order Rotated Group Iterative Schemes on Helmholtz Equation

Year: 2016 Volume: 10 Issue: 10 486 - 491 Pages

Abstract: In this paper, we present a high order group explicit method in solving the two dimensional Helmholtz equation. The presented method is derived from a nine-point fourth order finite difference approximation formula obtained from a 45-degree rotation of the standard grid which makes it possible for the construction of iterative procedure with reduced complexity. The developed method will be compared with the existing group iterative schemes available in literature in terms of computational time, iteration counts, and computational complexity. The comparative performances of the methods will be discussed and reported.

Comparative Performance of Artificial Bee Colony Based Algorithms for Wind-Thermal Unit Commitment

Year: 2016 Volume: 10 Issue: 8 1087 - 1098 Pages

Abstract: This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Comparative Performance of Artificial Bee Colony Based Algorithms for Wind-Thermal Unit Commitment

Year: 2016 Volume: 10 Issue: 8 1024 - 1035 Pages

Abstract: This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Analysis of Time Delay Simulation in Networked Control System

Year: 2016 Volume: 10 Issue: 3 359 - 364 Pages

Abstract: The paper presents a PD controller for the Networked Control Systems (NCS) with delay. The major challenges in this networked control system (NCS) are the delay of the data transmission throughout the communication network. The comparative performance analysis is carried out for different delays network medium. In this paper, simulation is carried out on Ac servo motor control system using CAN Bus as communication network medium. The True Time toolbox of MATLAB is used for simulation to analyze the effect of different delays.

Comparative Performance Analysis of Fiber Delay Line Based Buffer Architectures for Contention Resolution in Optical WDM Networks

Year: 2016 Volume: 10 Issue: 1 19 - 22 Pages

Abstract: Wavelength Division Multiplexing (WDM) technology is the most promising technology for the proper utilization of huge raw bandwidth provided by an optical fiber. One of the key problems in implementing the all-optical WDM network is the packet contention. This problem can be solved by several different techniques. In time domain approach the packet contention can be reduced by incorporating Fiber Delay Lines (FDLs) as optical buffer in the switch architecture. Different types of buffering architectures are reported in literatures. In the present paper a comparative performance analysis of three most popular FDL architectures are presented in order to obtain the best contention resolution performance. The analysis is further extended to consider the effect of different fiber non-linearities on the network performance.

Comparative Performance Analysis of Nonlinearity Cancellation Techniques for MOS-C Realization in Integrator Circuits

Year: 2015 Volume: 9 Issue: 10 1207 - 1214 Pages

Abstract: In this paper, a comparative performance analysis of mostly used four nonlinearity cancellation techniques used to realize the passive resistor by MOS transistors, is presented. The comparison is done by using an integrator circuit which is employing sequentially Op-amp, OTRA and ICCII as active element. All of the circuits are implemented by MOS-C realization and simulated by PSPICE program using 0.35μm process TSMC MOSIS model parameters. With MOS-C realization, the circuits became electronically tunable and fully integrable which is very important in IC design. The output waveforms, frequency responses, THD analysis results and features of the nonlinearity cancellation techniques are also given.

GIC-Based Adsorbents for Wastewater Treatment through Adsorption and Electrochemical-Regeneration

Year: 2013 Volume: 7 Issue: 9 603 - 605 Pages

Abstract: Intercalation imparts interesting features to the host graphite material. Two different types of intercalated compounds called (GIC-bisulphate or Nyex 1000 and GIC-nitrate or Nyex 3000) were tested for their adsorption capacity and ability to undergo electrochemical regeneration. It was found that Nyex 3000 showed comparatively slow kinetics along with reduced adsorption capacity to one half for acid violet 17 as adsorbate. Acid violet 17 was selected as model organic pollutant for evaluating comparative performance of said adsorbents. Both adsorbent materials showed 100% regeneration efficiency as achieved by passing a charge of 36 C g-1 at a current density of 12 mA cm-2 and a treatment time of 60 min.  

An Attribute-Centre Based Decision Tree Classification Algorithm

Year: 2009 Volume: 3 Issue: 8 588 - 592 Pages

Abstract: Decision tree algorithms have very important place at classification model of data mining. In literature, algorithms use entropy concept or gini index to form the tree. The shape of the classes and their closeness to each other some of the factors that affect the performance of the algorithm. In this paper we introduce a new decision tree algorithm which employs data (attribute) folding method and variation of the class variables over the branches to be created. A comparative performance analysis has been held between the proposed algorithm and C4.5.

Analysis of Modified Heap Sort Algorithm on Different Environment

Year: 2008 Volume: 2 Issue: 6 1261 - 1263 Pages

Abstract: In field of Computer Science and Mathematics, sorting algorithm is an algorithm that puts elements of a list in a certain order i.e. ascending or descending. Sorting is perhaps the most widely studied problem in computer science and is frequently used as a benchmark of a system-s performance. This paper presented the comparative performance study of four sorting algorithms on different platform. For each machine, it is found that the algorithm depends upon the number of elements to be sorted. In addition, as expected, results show that the relative performance of the algorithms differed on the various machines. So, algorithm performance is dependent on data size and there exists impact of hardware also.

A Comparative Performance Evaluation Model of Mobile Agent Versus Remote Method Invocation for Information Retrieval

Year: 2007 Volume: 1 Issue: 3 519 - 524 Pages

Abstract: The development of distributed systems has been affected by the need to accommodate an increasing degree of flexibility, adaptability, and autonomy. The Mobile Agent technology is emerging as an alternative to build a smart generation of highly distributed systems. In this work, we investigate the performance aspect of agent-based technologies for information retrieval. We present a comparative performance evaluation model of Mobile Agents versus Remote Method Invocation by means of an analytical approach. We demonstrate the effectiveness of mobile agents for dynamic code deployment and remote data processing by reducing total latency and at the same time producing minimum network traffic. We argue that exploiting agent-based technologies significantly enhances the performance of distributed systems in the domain of information retrieval.

Comparative Performance and Microbial Community of Single-phase and Two-phase Anaerobic Systems Co-Digesting Cassava Pulpand Pig Manure

Year: 2010 Volume: 4 Issue: 2 157 - 162 Pages

Abstract: In this study, we illustrated the performance and microbial community of single- and two-phase systems anaerobically co-digesting cassava pulp and pig manure. The results showed that the volatile solid reduction and biogas productivity of two-phase CSTR were 66 ± 4% and 2000 ± 210 ml l-1 d-1, while those of singlephase CSTR were 59 ± 1% and 1670 ± 60 ml l-1 d-1, respectively. Codigestion in two-phase CSTR gave higher 12% solid degradation and 25% methane production than single-phase CSTR. Phylogenetic analysis of 16S rDNA clone library revealed that the Bacteroidetes were the most abundant group, followed by the Clostridia in singlephase CSTR. In hydrolysis/acidification reactor of two-phase system, the bacteria within the phylum Firmicutes, especially Clostridium, Eubacteriaceae and Lactobacillus were the dominant phylogenetic groups. Among the Archaea, Methanosaeta sp. was the exclusive predominant in both digesters while the relative abundance of Methanosaeta sp. and Methanospirillum hungatei differed between the two systems.

A Generic and Extensible Spidergon NoC

Year: 2007 Volume: 1 Issue: 7 1032 - 1037 Pages

Abstract: The Globally Asynchronous Locally Synchronous Network on Chip (GALS NoC) is the most efficient solution that provides low latency transfers and power efficient System on Chip (SoC) interconnect. This study presents a GALS and generic NoC architecture based on a configurable router. This router integrates a sophisticated dynamic arbiter, the wormhole routing technique and can be configured in a manner that allows it to be used in many possible NoC topologies such as Mesh 2-D, Tree and Polygon architectures. This makes it possible to improve the quality of service (QoS) required by the proposed NoC. A comparative performances study of the proposed NoC architecture, Tore architecture and of the most used Mesh 2D architecture is performed. This study shows that Spidergon architecture is characterised by the lower latency and the later saturation. It is also shown that no matter what the number of used links is raised; the Links×Diameter product permitted by the Spidergon architecture remains always the lower. The only limitation of this architecture comes from it-s over cost in term of silicon area.

Application of Soft Computing Methods for Economic Dispatch in Power Systems

Year: 2009 Volume: 3 Issue: 4 706 - 711 Pages

Abstract: Economic dispatch problem is an optimization problem where objective function is highly non linear, non-convex, non-differentiable and may have multiple local minima. Therefore, classical optimization methods may not converge or get trapped to any local minima. This paper presents a comparative study of four different evolutionary algorithms i.e. genetic algorithm, bacteria foraging optimization, ant colony optimization and particle swarm optimization for solving the economic dispatch problem. All the methods are tested on IEEE 30 bus test system. Simulation results are presented to show the comparative performance of these methods.

Prediction of Compressive Strength of SCC Containing Bottom Ash using Artificial Neural Networks

Year: 2011 Volume: 5 Issue: 5 722 - 727 Pages

Abstract: The paper presents a comparative performance of the models developed to predict 28 days compressive strengths using neural network techniques for data taken from literature (ANN-I) and data developed experimentally for SCC containing bottom ash as partial replacement of fine aggregates (ANN-II). The data used in the models are arranged in the format of six and eight input parameters that cover the contents of cement, sand, coarse aggregate, fly ash as partial replacement of cement, bottom ash as partial replacement of sand, water and water/powder ratio, superplasticizer dosage and an output parameter that is 28-days compressive strength and compressive strengths at 7 days, 28 days, 90 days and 365 days, respectively for ANN-I and ANN-II. The importance of different input parameters is also given for predicting the strengths at various ages using neural network. The model developed from literature data could be easily extended to the experimental data, with bottom ash as partial replacement of sand with some modifications.