Search results for: Multi criteria inventory classification models

Authors: Kholod M. Abualnaja

Abstract:

This paper consider the solution of the matrix differential models using quadratic, cubic, quartic, and quintic splines. Also using the Taylor’s and Picard’s matrix methods, one illustrative example is included.

Keywords: Matrix Splines, Cubic Splines, Quartic Splines.

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Authors: R. Suzana, T. Wardah, A.B. Sahol Hamid

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The use of radar in Quantitative Precipitation Estimation (QPE) for radar-rainfall measurement is significantly beneficial. Radar has advantages in terms of high spatial and temporal condition in rainfall measurement and also forecasting. In Malaysia, radar application in QPE is still new and needs to be explored. This paper focuses on the Z/R derivation works of radarrainfall estimation based on rainfall classification. The works developed new Z/R relationships for Klang River Basin in Selangor area for three different general classes of rain events, namely low (<10mm/hr), moderate (>10mm/hr, <30mm/hr) and heavy (>30mm/hr) and also on more specific rain types during monsoon seasons. Looking at the high potential of Doppler radar in QPE, the newly formulated Z/R equations will be useful in improving the measurement of rainfall for any hydrological application, especially for flood forecasting.

Keywords: Radar, Quantitative Precipitation Estimation, Z/R development, flood forecasting

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Authors: Prasanta Kundu, N.K. Kishore, A.K. Sinha

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Insulation used in transformer is mostly oil pressboard insulation. Insulation failure is one of the major causes of catastrophic failure of transformers. It is established that partial discharges (PD) cause insulation degradation and premature failure of insulation. Online monitoring of PDs can reduce the risk of catastrophic failure of transformers. There are different techniques of partial discharge measurement like, electrical, optical, acoustic, opto-acoustic and ultra high frequency (UHF). Being non invasive and non interference prone, acoustic emission technique is advantageous for online PD measurement. Acoustic detection of p.d. is based on the retrieval and analysis of mechanical or pressure signals produced by partial discharges. Partial discharges are classified according to the origin of discharges. Their effects on insulation deterioration are different for different types. This paper reports experimental results and analysis for classification of partial discharges using acoustic emission signal of laboratory simulated partial discharges in oil pressboard insulation system using three different electrode systems. Acoustic emission signal produced by PD are detected by sensors mounted on the experimental tank surface, stored on an oscilloscope and fed to computer for further analysis. The measured AE signals are analyzed using discrete wavelet transform analysis and wavelet packet analysis. Energy distribution in different frequency bands of discrete wavelet decomposed signal and wavelet packet decomposed signal is calculated. These analyses show a distinct feature useful for PD classification. Wavelet packet analysis can sort out any misclassification arising out of DWT in most cases.

Keywords: Acoustic emission, discrete wavelet transform, partial discharge, wavelet packet analysis.

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Authors: Reza Ghaemi , Md. Nasir Sulaiman , Hamidah Ibrahim , Norwati Mustapha

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The clustering ensembles combine multiple partitions generated by different clustering algorithms into a single clustering solution. Clustering ensembles have emerged as a prominent method for improving robustness, stability and accuracy of unsupervised classification solutions. So far, many contributions have been done to find consensus clustering. One of the major problems in clustering ensembles is the consensus function. In this paper, firstly, we introduce clustering ensembles, representation of multiple partitions, its challenges and present taxonomy of combination algorithms. Secondly, we describe consensus functions in clustering ensembles including Hypergraph partitioning, Voting approach, Mutual information, Co-association based functions and Finite mixture model, and next explain their advantages, disadvantages and computational complexity. Finally, we compare the characteristics of clustering ensembles algorithms such as computational complexity, robustness, simplicity and accuracy on different datasets in previous techniques.

Keywords: Clustering Ensembles, Combinational Algorithm, Consensus Function, Unsupervised Classification.

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Authors: Prasun Hajra, Ranjan Dasgupta

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Petri Net being one of the most useful graphical tools for modelling complex asynchronous systems, we have used Petri Net to model multi-track railway level crossing system. The roadway has been augmented with four half-size barriers. For better control, a three stage control mechanism has been introduced to ensure that no road-vehicle is trapped on the level crossing. Timed Petri Net is used to include the temporal nature of the signalling system. Safeness analysis has also been included in the discussion section.

Keywords: Modelling, Timed Petri Net, Railway Level Crossing, Safeness Condition.

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Authors: Henry J. Wattimanela, Udjianna S. Pasaribu, Nanang T. Puspito, Sapto W. Indratno

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Banda Sea Collision Zone (BSCZ) is the result of the interaction and convergence of Indo-Australian plate, Eurasian plate and Pacific plate. This location is located in eastern Indonesia. This zone has a very high seismic activity. In this research, we will calculate the rate (λ) and Mean Square Error (MSE). By this result, we will classification earthquakes distribution in the BSCZ with the point process approach. Chi-square is used to determine the type of earthquakes distribution in the sub region of BSCZ. The data used in this research is data of earthquakes with a magnitude ≥ 6 SR for the period 1964-2013 and sourced from BMKG Jakarta. This research is expected to contribute to the Moluccas Province and surrounding local governments in performing spatial plan document related to disaster management.

Keywords: Banda sea collision zone, earthquakes, mean square error, Poisson distribution, chi-square test.

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Authors: Norfadzila, S.W.A., Balakrishnan, V., A. Abrizah

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The purpose of this paper is to propose an integrated consumer health informatics utilization framework that can be used to gauge the online health information needs and usage patterns among Malaysian women. The proposed framework was developed based on four different theories/models: Use and Gratification Theory, Technology Acceptance 3 Model, Health Belief Model, and Multi-level Model of Information Seeking. The relevant constructs and research hypotheses are also presented in this paper. The framework will be tested in order for it to be used successfully to identify Malaysian women-s preferences of online health information resources and health information seeking activities.

Keywords: Consumer Health Informatics, Consumer Preferences, Information Needs and Usage Patterns, Online Health Information, Women Studies

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Authors: L. J. de Bessa Neto, V. S. Filho, J. V. Ferreira Nunes, G. C. Bergamo

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There are many situations in which human activities have significant effects on the environment. Damage to the ozone layer is one of them. The objective of this work is to use the Least Squares Method, considering the linear, exponential, logarithmic, power and polynomial models of the second degree, to analyze through the coefficient of determination (R²), which model best fits the behavior of the chlorodifluoromethane (HCFC-142b) in parts per trillion between 1992 and 2018, as well as estimates of future concentrations between 5 and 10 periods, i.e. the concentration of this pollutant in the years 2023 and 2028 in each of the adjustments. A total of 809 observations of the concentration of HCFC-142b in one of the monitoring stations of gases precursors of the deterioration of the ozone layer during the period of time studied were selected and, using these data, the statistical software Excel was used for make the scatter plots of each of the adjustment models. With the development of the present study, it was observed that the logarithmic fit was the model that best fit the data set, since besides having a significant R² its adjusted curve was compatible with the natural trend curve of the phenomenon.

Keywords: Chlorodifluoromethane (HCFC-142b), ozone (O3), least squares method, regression models.

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Authors: A. Amirov, O. Gerget, V. Kochegurov

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One of the main biomedical problem lies in detecting dependencies in semi structured data. Solution includes biomedical portal and algorithms (integral rating health criteria, multidimensional data visualization methods). Biomedical portal allows to process diagnostic and research data in parallel mode using Microsoft System Center 2012, Windows HPC Server cloud technologies. Service does not allow user to see internal calculations instead it provides practical interface. When data is sent for processing user may track status of task and will achieve results as soon as computation is completed. Service includes own algorithms and allows diagnosing and predicating medical cases. Approved methods are based on complex system entropy methods, algorithms for determining the energy patterns of development and trajectory models of biological systems and logical–probabilistic approach with the blurring of images.

Keywords: Biomedical portal, cloud computing, diagnostic and prognostic research, mathematical data analysis.

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Authors: M. A. Koroma, C. Zhan, A. F. Kamara, A. B. Sesay

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In this work we adopt a combination of Laplace transform and the decomposition method to find numerical solutions of a system of multi-pantograph equations. The procedure leads to a rapid convergence of the series to the exact solution after computing a few terms. The effectiveness of the method is demonstrated in some examples by obtaining the exact solution and in others by computing the absolute error which decreases as the number of terms of the series increases.

Keywords: Laplace decomposition, pantograph equations, exact solution, numerical solution, approximate solution.

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Authors: Filiz Ersoz, Taner Ersoz, Erkin Guler

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This paper addresses the issues and technique for textile industry using data mining techniques. Data mining has been applied to the stitching of garments products that were obtained from a textile company. Data mining techniques were applied to the data obtained from the CHAID algorithm, CART algorithm, Regression Analysis and, Artificial Neural Networks. Classification technique based analyses were used while data mining and decision model about the production per person and variables affecting about production were found by this method. In the study, the results show that as the daily working time increases, the production per person also decreases. In addition, the relationship between total daily working and production per person shows a negative result and the production per person show the highest and negative relationship.

Keywords: Data mining, textile production, decision trees, classification.

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Authors: Anamika Jain, A. S. Thoke, R. N. Patel

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This paper addresses the problems encountered by conventional distance relays when protecting double-circuit transmission lines. The problems arise principally as a result of the mutual coupling between the two circuits under different fault conditions; this mutual coupling is highly nonlinear in nature. An adaptive protection scheme is proposed for such lines based on application of artificial neural network (ANN). ANN has the ability to classify the nonlinear relationship between measured signals by identifying different patterns of the associated signals. One of the key points of the present work is that only current signals measured at local end have been used to detect and classify the faults in the double circuit transmission line with double end infeed. The adaptive protection scheme is tested under a specific fault type, but varying fault location, fault resistance, fault inception angle and with remote end infeed. An improved performance is experienced once the neural network is trained adequately, which performs precisely when faced with different system parameters and conditions. The entire test results clearly show that the fault is detected and classified within a quarter cycle; thus the proposed adaptive protection technique is well suited for double circuit transmission line fault detection & classification. Results of performance studies show that the proposed neural network-based module can improve the performance of conventional fault selection algorithms.

Keywords: Double circuit transmission line, Fault detection and classification, High impedance fault and Artificial Neural Network.

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Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Tae-Hyeon Oh, Dae-Gyu Park

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Automotive interior material consisting of several material layers has the sound-absorbing function. It is difficult to predict sound absorbing coefficient because of several material layers. So, many experimental tunings are required to achieve the target of sound absorption. Therefore, while the car interior materials are developed, so much time and money is spent. In this study, we present a method to predict the sound absorbing performance of the material with multi-layer using physical properties of each material. The properties are predicted by Foam-X software using the sound absorption coefficient data measured by impedance tube. Then, we will compare and analyze the predicted sound absorption coefficient with the data measured by scaled reverberation chamber and impedance tubes for a prototype. If the method is used instead of experimental tuning in the development of car interior material, the time and money can be saved, and then, the development effort can be reduced because it can be optimized by simulation.

Keywords: Multi-layer nonwoven, sound absorption coefficient, scaled reverberation chamber, impedance tubes.

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Authors: Thashmee Karunaratne, Henrik Böstrom

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Logic based methods for learning from structured data is limited w.r.t. handling large search spaces, preventing large-sized substructures from being considered by the resulting classifiers. A novel approach to learning from structured data is introduced that employs a structure transformation method, called finger printing, for addressing these limitations. The method, which generates features corresponding to arbitrarily complex substructures, is implemented in a system, called DIFFER. The method is demonstrated to perform comparably to an existing state-of-art method on some benchmark data sets without requiring restrictions on the search space. Furthermore, learning from the union of features generated by finger printing and the previous method outperforms learning from each individual set of features on all benchmark data sets, demonstrating the benefit of developing complementary, rather than competing, methods for structure classification.

Keywords: Machine learning, Structure classification, Propositionalization.

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Authors: Mak Kaboudan

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A multi-agent system is developed here to predict monthly details of the upcoming peak of the 24th solar magnetic cycle. While studies typically predict the timing and magnitude of cycle peaks using annual data, this one utilizes the unsmoothed monthly sunspot number instead. Monthly numbers display more pronounced fluctuations during periods of strong solar magnetic activity than the annual sunspot numbers. Because strong magnetic activities may cause significant economic damages, predicting monthly variations should provide different and perhaps helpful information for decision-making purposes. The multi-agent system developed here operates in two stages. In the first, it produces twelve predictions of the monthly numbers. In the second, it uses those predictions to deliver a final forecast. Acting as expert agents, genetic programming and neural networks produce the twelve fits and forecasts as well as the final forecast. According to the results obtained, the next peak is predicted to be 156 and is expected to occur in October 2011- with an average of 136 for that year.

Keywords: Computational techniques, discrete wavelet transformations, solar cycle prediction, sunspot numbers.

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Authors: Taeung Yoon, Youngpo Lee, Chonghan Song, Na Young Ha, Seokho Yoon

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Ren et al. presented an efficient carrier frequency offset (CFO) estimation method for orthogonal frequency division multiplexing (OFDM), which has an estimation range as large as the bandwidth of the OFDM signal and achieves high accuracy without any constraint on the structure of the training sequence. However, its detection probability of the integer frequency offset (IFO) rapidly varies according to the fractional frequency offset (FFO) change. In this paper, we first analyze the Ren-s method and define two criteria suitable for detection of IFO. Then, we propose a novel method for the IFO estimation based on the maximum-likelihood (ML) principle and the detection criteria defined in this paper. The simulation results demonstrate that the proposed method outperforms the Ren-s method in terms of the IFO detection probability irrespective of a value of the FFO.

Keywords: Orthogonal frequency division multiplexing, integer frequency offset, estimation, training symbol

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Authors: Volker Lange, Stephanie Moede, Christiane Auffermann

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From an economic standpoint the current and future road traffic situation in urban areas is a cost factor. Traffic jams and congestion prolong journey times and tie up resources in trucks and personnel. Many discussions about imposing charges or tolls for cities in Europe in order to reduce traffic congestion are currently in progress. Both of these effects lead – directly or indirectly - to additional costs for the urban distribution systems in retail companies. One approach towards improving the efficiency of retail distribution systems, and thus towards avoiding negative environmental factors in urban areas, is horizontal collaboration for deliveries to retail outlets – Urban Retail Logistics. This paper presents a classification system to help reveal where cooperation between retail companies is possible and makes sense for deliveries to retail outlets in urban areas.

Keywords: City Logistics, Horizontal Collaboration, Urban Freight Transport, Urban Retail Logistics.

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Authors: Belkacem Chikhaoui, Helene Pigot

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Cognitive models allow predicting some aspects of utility and usability of human machine interfaces (HMI), and simulating the interaction with these interfaces. The action of predicting is based on a task analysis, which investigates what a user is required to do in terms of actions and cognitive processes to achieve a task. Task analysis facilitates the understanding of the system-s functionalities. Cognitive models are part of the analytical approaches, that do not associate the users during the development process of the interface. This article presents a study about the evaluation of a human machine interaction with a contextual assistant-s interface using ACTR and GOMS cognitive models. The present work shows how these techniques may be applied in the evaluation of HMI, design and research by emphasizing firstly the task analysis and secondly the time execution of the task. In order to validate and support our results, an experimental study of user performance is conducted at the DOMUS laboratory, during the interaction with the contextual assistant-s interface. The results of our models show that the GOMS and ACT-R models give good and excellent predictions respectively of users performance at the task level, as well as the object level. Therefore, the simulated results are very close to the results obtained in the experimental study.

Keywords: HMI, interface evaluation, Analytical evaluation, cognitivemodeling, user modeling, user performance.

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Authors: Sitthichon Kanitthakun, Pinit Kumhom, Kosin Chamnongthai

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In quality control of freeze-dried durian, crispiness is a key quality index of the product. Generally, crispy testing has to be done by a destructive method. A nondestructive testing of the crispiness is required because the samples can be reused for other kinds of testing. This paper proposed a crispiness classification method of freeze-dried durians using fuzzy logic for decision making. The physical changes of a freeze-dried durian include the pores appearing in the images. Three physical features including (1) the diameters of pores, (2) the ratio of the pore area and the remaining area, and (3) the distribution of the pores are considered to contribute to the crispiness. The fuzzy logic is applied for making the decision. The experimental results comparing with food expert opinion showed that the accuracy of the proposed classification method is 83.33 percent.

Keywords: Durian, crispiness, freeze drying, pore, fuzzy logic.

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Authors: T. Penkova, A. Korobko, V. Nicheporchuk., L. Nozhenkova, A. Metus

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This paper presents an approach of on-line control of the state of technosphere and environment objects based on the integration of Data Warehouse, OLAP and Expert systems technologies. It looks at the structure and content of data warehouse that provides consolidation and storage of monitoring data. There is a description of OLAP-models that provide a multidimensional analysis of monitoring data and dynamic analysis of principal parameters of controlled objects. The authors suggest some criteria of emergency risk assessment using expert knowledge about danger levels. It is demonstrated now some of the proposed solutions could be adopted in territorial decision making support systems. Operational control allows authorities to detect threat, prevent natural and anthropogenic emergencies and ensure a comprehensive safety of territory.

Keywords: Decision making support systems, Emergency risk assessment, Natural and anthropogenic safety, On-line control, Territory.

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Authors: Mohammad Reza Sedighi, Behnam Nilforooshan Dardashti

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The high temperature degree and uniform Temperature Distribution (TD) on surface of cookware which contact with food are effective factors for improving cookware application. Additionally, the ability of pan material in retaining the heat and nonreactivity with foods are other significant properties. It is difficult for single material to meet a wide variety of demands such as superior thermal and chemical properties. Multi-Layer Plate (MLP) makes more regular TD. In this study the main objectives are to find the best structure (single or multi-layer) and materials to provide maximum temperature degree and uniform TD up side surface of pan. And also heat retaining of used metals with goal of improving the thermal quality of pan to economize the energy. To achieve this aim were employed Finite Element Method (FEM) for analyzing transient thermal behavior of applied materials. The analysis has been extended for different metals, we achieved the best temperature profile and heat retaining in Copper/ Stainless Steel MLP.

Keywords: Cookware, Energy optimization, Heat retaining, Laminated plate, Temperature distribution

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Authors: Min Kyung An

Abstract:

In Wireless Sensor Networks which consist of tiny wireless sensor nodes with limited battery power, one of the most fundamental applications is data aggregation which collects nearby environmental conditions and aggregates the data to a designated destination, called a sink node. Important issues concerning the data aggregation are time efficiency and energy consumption due to its limited energy, and therefore, the related problem, named Minimum Latency Aggregation Scheduling (MLAS), has been the focus of many researchers. Its objective is to compute the minimum latency schedule, that is, to compute a schedule with the minimum number of timeslots, such that the sink node can receive the aggregated data from all the other nodes without any collision or interference. For the problem, the two interference models, the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR), have been adopted with different power models, uniform-power and non-uniform power (with power control or without power control), and different antenna models, omni-directional antenna and directional antenna models. In this survey article, as the problem has proven to be NP-hard, we present and compare several state-of-the-art approximation algorithms in various models on the basis of latency as its performance measure.

Keywords: Data aggregation, convergecast, gathering, approximation, interference, omni-directional, directional.

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Authors: Ch. Antonopoulos, Th. Kapourniotis, V. Triantafillou

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Optimum communication and performance in Wireless Sensor Networks, constitute multi-facet challenges due to the specific networking characteristics as well as the scarce resource availability. Furthermore, it is becoming increasingly apparent that isolated layer based approaches often do not meet the demands posed by WSNs applications due to omission of critical inter-layer interactions and dependencies. As a counterpart, cross-layer is receiving high interest aiming to exploit these interactions and increase network performance. However, in order to clearly identify existing dependencies, comprehensive performance studies are required evaluating the effect of different critical network parameters on system level performance and behavior.This paper-s main objective is to address the need for multi-parametric performance evaluations considering critical network parameters using a well known network simulator, offering useful and practical conclusions and guidelines. The results reveal strong dependencies among considered parameters which can be utilized by and drive future research efforts, towards designing and implementing highly efficient protocols and architectures.

Keywords: Wireless sensor network, Communication Systems, cross-layer architectures, simulation based performance evaluation

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Authors: Samad Nejatian, Vahideh Rezaie, Vahid Asadpour

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This paper presents a novel approach for the design of microwave circuits using Adaptive Network Fuzzy Inference Optimizer (ANFIO). The method takes advantage of direct synthesis of subsections of the amplifier using very fast and accurate ANFIO models based on exact simulations using ADS. A mapping from course space to fine space known as space mapping is also used. The proposed synthesis approach takes into account the noise and scattering parameters due to parasitic elements to achieve optimal results. The overall ANFIO system is capable of designing different LNAs at different noise and scattering criteria. This approach offers significantly reduced time in the design of microwave amplifiers within the validity range of the ANFIO system. The method has been proven to work efficiently for a 2.4GHz LNA example. The S21 of 10.1 dB and noise figure (NF) of 2.7 dB achieved for ANFIO while S21 of 9.05 dB and NF of 2.6 dB achieved for ANN.

Keywords: fuzzy system, low noise amplifier, microwaveamplifier, space mapping

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Authors: N. Sopipan

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In this paper, we study the rainfall using a time series for weather stations in Nakhon Ratchasima province in Thailand by various statistical methods to enable us to analyse the behaviour of rainfall in the study areas. Time-series analysis is an important tool in modelling and forecasting rainfall. The ARIMA and Holt-Winter models were built on the basis of exponential smoothing. All the models proved to be adequate. Therefore it is possible to give information that can help decision makers establish strategies for the proper planning of agriculture, drainage systems and other water resource applications in Nakhon Ratchasima province. We obtained the best performance from forecasting with the ARIMA Model(1,0,1)(1,0,1)12.

Keywords: ARIMA Models, Exponential Smoothing, Holt- Winter model.

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Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

Abstract:

The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: Data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse.

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Authors: Kaveh Mohammad Cyrus, Shadi Sanagoo

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MABENA model is a complementary model in comparison with traditional models such as HCMS, CMS and etc. New factors, which have effects on preparation of strategic plans and their sequential order in MABENA model is the platform of presented road map in this paper.Study review shows, factors such as emerging new critical success factors for strategic planning, improvement of international strategic models, increasing the maturity of companies and emerging new needs leading to design a new model which can be responsible for new critical factors and solve the limitations of previous strategic management models. Preparation of strategic planning need more factors than introduced in traditional models. The needed factors includes determining future Critical Success Factors and competencies, defining key processes, determining the maturity of the processes, considering all aspects of the external environment etc. Description of aforementioned requirements, the outcomes and their order is developing and presenting the MABENA model-s road map in this paper. This study presents a road map for strategic planning of the Iranian organizations.

Keywords: Competitive Advantage, Process Maturity, StrategicPlanning, Strategic potential

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Authors: Mohammed Erritali

Abstract:

The growth in the volume of text data such as books and articles in libraries for centuries has imposed to establish effective mechanisms to locate them. Early techniques such as abstraction, indexing and the use of classification categories have marked the birth of a new field of research called "Information Retrieval". Information Retrieval (IR) can be defined as the task of defining models and systems whose purpose is to facilitate access to a set of documents in electronic form (corpus) to allow a user to find the relevant ones for him, that is to say, the contents which matches with the information needs of the user. This paper presents a new semantic indexing approach of a documentary corpus. The indexing process starts first by a term weighting phase to determine the importance of these terms in the documents. Then the use of a thesaurus like Wordnet allows moving to the conceptual level. Each candidate concept is evaluated by determining its level of representation of the document, that is to say, the importance of the concept in relation to other concepts of the document. Finally, the semantic index is constructed by attaching to each concept of the ontology, the documents of the corpus in which these concepts are found.

Keywords: Semantic, indexing, corpora, WordNet, ontology.

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Authors: Yoshinori Matsuura, Saori Iwanaga

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The Great East Japan Earthquake occurred at 14:46 on Friday, March 11, 2011. It was the most powerful known earthquake to have hit Japan. The earthquake triggered extremely destructive tsunami waves of up to 40.5 meters in height. We focus on the ship’s evacuation from tsunami. Then we analyze about ships evacuation from tsunami using multi-agent simulation and we want to prepare for a coming earthquake. We developed a simulation model of ships that set sail from the port in order to evacuate from the tsunami considering the ship carrying dangerous goods.

Keywords: Multi-agent simulation, Ship’s evacuation, Tsunami.

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Authors: Hany Alashwal, Safaai Deris, Razib M. Othman

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Predicting protein-protein interactions represent a key step in understanding proteins functions. This is due to the fact that proteins usually work in context of other proteins and rarely function alone. Machine learning techniques have been applied to predict protein-protein interactions. However, most of these techniques address this problem as a binary classification problem. Although it is easy to get a dataset of interacting proteins as positive examples, there are no experimentally confirmed non-interacting proteins to be considered as negative examples. Therefore, in this paper we solve this problem as a one-class classification problem using one-class support vector machines (SVM). Using only positive examples (interacting protein pairs) in training phase, the one-class SVM achieves accuracy of about 80%. These results imply that protein-protein interaction can be predicted using one-class classifier with comparable accuracy to the binary classifiers that use artificially constructed negative examples.

Keywords: Bioinformatics, Protein-protein interactions, One-Class Support Vector Machines

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