Search results for: Error classification

Authors: F. H. Abanda, B. Kamsu-Foguem, J. H. M. Tah

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Construction cost estimation is one of the most important aspects of construction project design. For generations, the process of cost estimating has been manual, time-consuming and error-prone. This has partly led to most cost estimates to be unclear and riddled with inaccuracies that at times lead to over- or underestimation of construction cost. The development of standard set of measurement rules that are understandable by all those involved in a construction project, have not totally solved the challenges. Emerging Building Information Modelling (BIM) technologies can exploit standard measurement methods to automate cost estimation process and improve accuracies. This requires standard measurement methods to be structured in ontological and machine readable format; so that BIM software packages can easily read them. Most standard measurement methods are still text-based in textbooks and require manual editing into tables or Spreadsheet during cost estimation. The aim of this study is to explore the development of an ontology based on New Rules of Measurement (NRM) commonly used in the UK for cost estimation. The methodology adopted is Methontology, one of the most widely used ontology engineering methodologies. The challenges in this exploratory study are also reported and recommendations for future studies proposed.

Keywords: BIM, Construction projects, Cost estimation, NRM, Ontology.

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Authors: Usman Qamar, Younus Javed

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Frequent pattern mining is the process of finding a pattern (a set of items, subsequences, substructures, etc.) that occurs frequently in a data set. It was proposed in the context of frequent itemsets and association rule mining. Frequent pattern mining is used to find inherent regularities in data. What products were often purchased together? Its applications include basket data analysis, cross-marketing, catalog design, sale campaign analysis, Web log (click stream) analysis, and DNA sequence analysis. However, one of the bottlenecks of frequent itemset mining is that as the data increase the amount of time and resources required to mining the data increases at an exponential rate. In this investigation a new algorithm is proposed which can be uses as a pre-processor for frequent itemset mining. FASTER (FeAture SelecTion using Entropy and Rough sets) is a hybrid pre-processor algorithm which utilizes entropy and roughsets to carry out record reduction and feature (attribute) selection respectively. FASTER for frequent itemset mining can produce a speed up of 3.1 times when compared to original algorithm while maintaining an accuracy of 71%.

Keywords: Rough-sets, Classification, Feature Selection, Entropy, Outliers, Frequent itemset mining.

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Authors: Daniela Ocipova, Zuzana Vranayova, Ondrej Sikula

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Safe drinking water is one of the biggest issues facing the planet this century. The primary aim of this paper is to present our research focused on theoretical and experimental analysis of potable water and in-building water distribution systems from the point of view of microbiological risk on the basis of confrontation between the theoretical analysis and synthesis of gathered information in conditions of the Slovak Republic. The presence of the bacteria Legionella in water systems, especially in hot water distribution system, represents in terms of health protection of inhabitants the crucial problem which cannot be overlooked. Legionella pneumophila discovery, its classification and its influence on installations inside buildings are relatively new. There are a lot of guidelines and regulations developed in many individual countries for the design, operation and maintenance for tap water systems to avoid the growth of bacteria Legionella pneumophila, but in Slovakia we don-t have any. The goal of this paper is to show the necessity of prevention and regulations for installations inside buildings verified by simulation methods.

Keywords: Legionella pneumophila, water temperature, distribution system, risk analysis, simulations.

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Authors: Ahmad Tariq Sheikh, Shahzad Amin Sheikh

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A new distance-adjusted approach is proposed in which static square contours are defined around an estimated symbol in a QAM constellation, which create regions that correspond to fixed step sizes and weighting factors. As a result, the equalizer tap adjustment consists of a linearly weighted sum of adaptation criteria that is scaled by a variable step size. This approach is the basis of two new algorithms: the Variable step size Square Contour Algorithm (VSCA) and the Variable step size Square Contour Decision-Directed Algorithm (VSDA). The proposed schemes are compared with existing blind equalization algorithms in the SCA family in terms of convergence speed, constellation eye opening and residual ISI suppression. Simulation results for 64-QAM signaling over empirically derived microwave radio channels confirm the efficacy of the proposed algorithms. An RTL implementation of the blind adaptive equalizer based on the proposed schemes is presented and the system is configured to operate in VSCA error signal mode, for square QAM signals up to 64-QAM.

Keywords: Adaptive filtering, Blind Equalization, Square Contour Algorithm.

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Authors: Dim En Nyaung, Thin Lai Lai Thein

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Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: Opinion Mining, Opinion Summarization, Sentiment Analysis, Text Mining.

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Authors: A. Shayeghi, H. Shayeghi, H. Eimani Kalasar

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In recent years, tuned mass damper (TMD) control systems for civil engineering structures have attracted considerable attention. This paper emphasizes on the application of particle swarm application (PSO) to design and optimize the parameters of the TMD control scheme for achieving the best results in the reduction of the building response under earthquake excitations. The Integral of the Time multiplied Absolute value of the Error (ITAE) based on relative displacement of all floors in the building is taken as a performance index of the optimization criterion. The problem of robustly TMD controller design is formatted as an optimization problem based on the ITAE performance index to be solved using the PSO technique which has a story ability to find the most optimistic results. An 11- story realistic building, located in the city of Rasht, Iran is considered as a test system to demonstrate effectiveness of the proposed method. The results analysis through the time-domain simulation and some performance indices reveals that the designed PSO based TMD controller has an excellent capability in reduction of the seismically excited example building.

Keywords: TMD, Particle Swarm Optimization, Tall Buildings, Structural Dynamics.

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Authors: Faten A. Dawood, Rahmita W. Rahmat, Suhaini B. Kadiman, Lili N. Abdullah, Mohd D. Zamrin

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Echocardiography imaging is one of the most common diagnostic tests that are widely used for assessing the abnormalities of the regional heart ventricle function. The main goal of the image enhancement task in 2D-echocardiography (2DE) is to solve two major anatomical structure problems; speckle noise and low quality. Therefore, speckle noise reduction is one of the important steps that used as a pre-processing to reduce the distortion effects in 2DE image segmentation. In this paper, we present the common filters that based on some form of low-pass spatial smoothing filters such as Mean, Gaussian, and Median. The Laplacian filter was used as a high-pass sharpening filter. A comparative analysis was presented to test the effectiveness of these filters after being applied to original 2DE images of 4-chamber and 2-chamber views. Three statistical quantity measures: root mean square error (RMSE), peak signal-to-ratio (PSNR) and signal-tonoise ratio (SNR) are used to evaluate the filter performance quantitatively on the output enhanced image.

Keywords: Gaussian operator, median filter, speckle texture, peak signal-to-ratio

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Authors: Pisit Boonsrimuang, Arjin Numsomran, Tawil Paungma, Hideo Kobayashi

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One of the disadvantages of using OFDM is the larger peak to averaged power ratio (PAPR) in its time domain signal. The larger PAPR signal would course the fatal degradation of bit error rate performance (BER) due to the inter-modulation noise in the nonlinear channel. This paper proposes an improved DSI (Dummy Sequence Insertion) method, which can achieve the better PAPR and BER performances. The feature of proposed method is to optimize the phase of each dummy sub-carrier so as to reduce the PAPR performance by changing all predetermined phase coefficients in the time domain signal, which is calculated for data sub-carriers and dummy sub-carriers separately. To achieve the better PAPR performance, this paper also proposes to employ the time-frequency domain swapping algorithm for fine adjustment of phase coefficient of the dummy subcarriers, which can achieve the less complexity of processing and achieves the better PAPR and BER performances than those for the conventional DSI method. This paper presents various computer simulation results to verify the effectiveness of proposed method as comparing with the conventional methods in the non-linear channel.

Keywords: OFDM, PAPR, dummy sub-carriers, non-linear

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Authors: Martin A. Smith, Xiaogang Chen

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This paper proposes new algorithms for the computeraided design and manufacture (CAD/CAM) of 3D woven multi-layer textile structures. Existing commercial CAD/CAM systems are often restricted to the design and manufacture of 2D weaves. Those CAD/CAM systems that do support the design and manufacture of 3D multi-layer weaves are often limited to manual editing of design paper grids on the computer display and weave retrieval from stored archives. This complex design activity is time-consuming, tedious and error-prone and requires considerable experience and skill of a technical weaver. Recent research reported in the literature has addressed some of the shortcomings of commercial 3D multi-layer weave CAD/CAM systems. However, earlier research results have shown the need for further work on weave specification, weave generation, yarn path editing and layer binding. Analysis of 3D multi-layer weaves in this research has led to the design and development of efficient and robust algorithms for the CAD/CAM of 3D woven multi-layer textile structures. The resulting algorithmically generated weave designs can be used as a basis for lifting plans that can be loaded onto looms equipped with electronic shedding mechanisms for the CAM of 3D woven multi-layer textile structures.

Keywords: CAD/CAM, Multi-layer, Textile, Weave.

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Authors: Elysia Barker, Jian Guo Zhou, Ling Qian, Steve Decent

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A method of modelling topography used in the simulation of riverbeds is proposed in this paper which removes the need for datapoints and measurements of a physical terrain. While complex scans of the contours of a surface can be achieved with other methods, this requires specialised tools which the proposed method overcomes by using fractional Brownian motion (FBM) as a basis to estimate the real surface within a 15% margin of error while attempting to optimise algorithmic efficiency. This removes the need for complex, expensive equipment and reduces resources spent modelling bed topography. This method also accounts for the change in topography over time due to erosion, sediment transport, and other external factors which could affect the topography of the ground by updating its parameters and generating a new bed. The lattice Boltzmann method (LBM) is used to simulate both stationary and steady flow cases in a side-by-side comparison over the generated bed topography using the proposed method, and a test case taken from an external source. The method, if successful, will be incorporated into the current LBM program used in the testing phase, which will allow an automatic generation of topography for the given situation in future research, removing the need for bed data to be specified.

Keywords: Bed topography, FBM, LBM, shallow water, simulations.

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Authors: Eduardo F. Arias, William Cooke III, Zhaofei Fan, William Kingery

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During the last decade Panicum virgatum, known as Switchgrass, has been broadly studied because of its remarkable attributes as a substitute pasture and as a functional biofuel source. The objective of this investigation was to establish soil suitability for Switchgrass in the State of Mississippi. A linear weighted additive model was developed to forecast soil suitability. Multicriteria analysis and Sensitivity analysis were utilized to adjust and optimize the model. The model was fit using seven years of field data associated with soils characteristics collected from Natural Resources Conservation System - United States Department of Agriculture (NRCS-USDA). The best model was selected by correlating calculated biomass yield with each model's soils-based output for Switchgrass suitability. Coefficient of determination (r2) was the decisive factor used to establish the 'best' soil suitability model. Coefficients associated with the 'best' model were implemented within a Geographic Information System (GIS) to create a map of relative soil suitability for Switchgrass in Mississippi. A Geodatabase associated with soil parameters was built and is available for future Geographic Information System use.

Keywords: Aptness, GIS, sensitivity analysis, switchgrass, soil.

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Authors: Wei Lei, Hui Chen, Lin Lu

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Microscopic emission and fuel consumption models have been widely recognized as an effective method to quantify real traffic emission and energy consumption when they are applied with microscopic traffic simulation models. This paper presents a framework for developing the Microscopic Emission (HC, CO, NOx, and CO2) and Fuel consumption (MEF) models for light-duty vehicles. The variable of composite acceleration is introduced into the MEF model with the purpose of capturing the effects of historical accelerations interacting with current speed on emission and fuel consumption. The MEF model is calibrated by multivariate least-squares method for two types of light-duty vehicle using on-board data collected in Beijing, China by a Portable Emission Measurement System (PEMS). The instantaneous validation results shows the MEF model performs better with lower Mean Absolute Percentage Error (MAPE) compared to other two models. Moreover, the aggregate validation results tells the MEF model produces reasonable estimations compared to actual measurements with prediction errors within 12%, 10%, 19%, and 9% for HC, CO, NOx emissions and fuel consumption, respectively.

Keywords: Emission, Fuel consumption, Light-duty vehicle, Microscopic, Modeling.

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Authors: H. Shareef, A. Mohamed, S. A. Khalid, Aziah Khamis

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This paper presents application artificial intelligent (AI) techniques, namely artificial neural network (ANN), adaptive neuro fuzzy interface system (ANFIS), to estimate the real power transfer between generators and loads. Since these AI techniques adopt supervised learning, it first uses modified nodal equation method (MNE) to determine real power contribution from each generator to loads. Then the results of MNE method and load flow information are utilized to estimate the power transfer using AI techniques. The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of both AI methods compared to that of the MNE method. The mean squared error of the estimate of ANN and ANFIS power transfer allocation methods are 1.19E-05 and 2.97E-05, respectively. Furthermore, when compared to MNE method, ANN and ANFIS methods computes generator contribution to loads within 20.99 and 39.37msec respectively whereas the MNE method took 360msec for the calculation of same real power transfer allocation. 

Keywords: Artificial intelligence, Power tracing, Artificial neural network, ANFIS, Power system deregulation.

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Authors: S. E. Oraby, A.M. Alaskari

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The stochastic nature of tool life using conventional discrete-wear data from experimental tests usually exists due to many individual and interacting parameters. It is a common practice in batch production to continually use the same tool to machine different parts, using disparate machining parameters. In such an environment, the optimal points at which tools have to be changed, while achieving minimum production cost and maximum production rate within the surface roughness specifications, have not been adequately studied. In the current study, two relevant aspects are investigated using coated and uncoated inserts in turning operations: (i) the accuracy of using machinability information, from fixed parameters testing procedures, when variable parameters situations are emerged, and (ii) the credibility of tool life machinability data from prior discrete testing procedures in a non-stop machining. A novel technique is proposed and verified to normalize the conventional fixed parameters machinability data to suit the cases when parameters have to be changed for the same tool. Also, an experimental investigation has been established to evaluate the error in the tool life assessment when machinability from discrete testing procedures is employed in uninterrupted practical machining.

Keywords: Machinability, tool life, tool wear, wear variability

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Authors: Hamed Afrasiab, Saeed Khodaygan

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Prediction of machining process capability in the design stage plays a key role to reach the precision design and manufacturing of mechanical products. Inaccuracies in machining process lead to errors in position and orientation of machined features on the part, and strongly affect the process capability in the final quality of the product. In this paper, an efficient systematic approach is given to investigate the machining errors to predict the manufacturing errors of the parts and capability prediction of corresponding machining processes. A mathematical formulation of fixture locators modeling is presented to establish the relationship between the part errors and the related sources. Based on this method, the final machining errors of the part can be accurately estimated by relating them to the combined dimensional and geometric tolerances of the workpiece – fixture system. This method is developed for uncertainty analysis based on the Worst Case and statistical approaches. The application of the presented method is illustrated through presenting an example and the computational results are compared with the Monte Carlo simulation results.

Keywords: Process capability, machining error, dimensional and geometrical tolerances, uncertainty analysis.

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Authors: N. H. Adenan, M. S. M. Noorani

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River flow prediction is an essential to ensure proper management of water resources can be optimally distribute water to consumers. This study presents an analysis and prediction by using nonlinear prediction method involving monthly river flow data in Tanjung Tualang from 1976 to 2006. Nonlinear prediction method involves the reconstruction of phase space and local linear approximation approach. The phase space reconstruction involves the reconstruction of one-dimensional (the observed 287 months of data) in a multidimensional phase space to reveal the dynamics of the system. Revenue of phase space reconstruction is used to predict the next 72 months. A comparison of prediction performance based on correlation coefficient (CC) and root mean square error (RMSE) have been employed to compare prediction performance for nonlinear prediction method, ARIMA and SVM. Prediction performance comparisons show the prediction results using nonlinear prediction method is better than ARIMA and SVM. Therefore, the result of this study could be used to develop an efficient water management system to optimize the allocation water resources.

Keywords: River flow, nonlinear prediction method, phase space, local linear approximation.

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Authors: Lokesh Tharani, R.P.Yadav

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This paper presents the results related to the interference reduction technique in multistage multiuser detector for asynchronous DS-CDMA system. To meet the real-time requirements for asynchronous multiuser detection, a bit streaming, cascade architecture is used. An asynchronous multiuser detection involves block-based computations and matrix inversions. The paper covers iterative-based suboptimal schemes that have been studied to decrease the computational complexity, eliminate the need for matrix inversions, decreases the execution time, reduces the memory requirements and uses joint estimation and detection process that gives better performance than the independent parameter estimation method. The stages of the iteration use cascaded and bits processed in a streaming fashion. The simulation has been carried out for asynchronous DS-CDMA system by varying one parameter, i.e., number of users. The simulation result exhibits that system gives optimum bit error rate (BER) at 3rd stage for 15-users.

Keywords: Multi-user detection (MUD), multiple accessinterference (MAI), near-far effect, decision feedback detector, successive interference cancellation detector (SIC) and parallelinterference cancellation (PIC) detector.

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Authors: Zhen Chen, Haitao Zhang, Weiyong Ying, Dingye Fang

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The direct synthesis process of dimethyl ether (DME) from syngas in slurry reactors is considered to be promising because of its advantages in caloric transfer. In this paper, the influences of operating conditions (temperature, pressure and weight hourly space velocity) on the conversion of CO, selectivity of DME and methanol were studied in a stirred autoclave over Cu-Zn-Al-Zr slurry catalyst, which is far more suitable to liquid phase dimethyl ether synthesis process than bifunctional catalyst commercially. A Langmuir- Hinshelwood mechanism type global kinetics model for liquid phase DME direct synthesis based on methanol synthesis models and a methanol dehydration model has been investigated by fitting our experimental data. The model parameters were estimated with MATLAB program based on general Genetic Algorithms and Levenberg-Marquardt method, which is suitably fitting experimental data and its reliability was verified by statistical test and residual error analysis.

Keywords: alcohol/ether fuel, Cu-Zn-Al-Zr slurry catalyst, global kinetics, slurry reactor

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Authors: Banashree N. P., Andhe Dharani, R. Vasanta, P. S. Satyanarayana

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The applications on numbers are across-the-board that there is much scope for study. The chic of writing numbers is diverse and comes in a variety of form, size and fonts. Identification of Indian languages scripts is challenging problems. In Optical Character Recognition [OCR], machine printed or handwritten characters/numerals are recognized. There are plentiful approaches that deal with problem of detection of numerals/character depending on the sort of feature extracted and different way of extracting them. This paper proposes a recognition scheme for handwritten Hindi (devnagiri) numerals; most admired one in Indian subcontinent our work focused on a technique in feature extraction i.e. Local-based approach, a method using 16-segment display concept, which is extracted from halftoned images & Binary images of isolated numerals. These feature vectors are fed to neural classifier model that has been trained to recognize a Hindi numeral. The archetype of system has been tested on varieties of image of numerals. Experimentation result shows that recognition rate of halftoned images is 98 % compared to binary images (95%).

Keywords: OCR, Halftoning, Neural classifier, 16-segmentdisplay concept.

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Authors: R. Karbalaei, A. Ghaffari, R. Kazemi, S. H. Tabatabaei

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An integrated vehicle dynamics control system is developed in this paper by a combination of active front steering (AFS) and direct yaw-moment control (DYC) based on fuzzy logic control. The control system has a hierarchical structure consisting of two layers. A fuzzy logic controller is used in the upper layer (yaw rate controller) to keep the yaw rate in its desired value. The yaw rate error and its rate of change are applied to the upper controlling layer as inputs, where the direct yaw moment control signal and the steering angle correction of the front wheels are the outputs. In the lower layer (fuzzy integrator), a fuzzy logic controller is designed based on the working region of the lateral tire forces. Depending on the directions of the lateral forces at the front wheels, a switching function is activated to adjust the scaling factor of the fuzzy logic controller. Using a nonlinear seven degrees of freedom vehicle model, the simulation results illustrate considerable improvements which are achieved in vehicle handling through the integrated AFS/DYC control system in comparison with the individual AFS or DYC controllers.

Keywords: Intelligent strategy, integrated control, fuzzy logic, AFS/DYC.

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Authors: Ying Shang, Chencheng Wang

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The wind field is the main driving factor for the spread of forest fires. For the simulation results of forest fire spread to be more accurate, it is necessary to obtain more detailed wind field data. Therefore, this paper studied the mountainous fine wind field simulation method coupled with WRF (Weather Research and Forecasting Model) and CFD (Computational Fluid Dynamics) to realize the numerical simulation of the wind field in a mountainous area with a scale of 30 m and a small measurement error. Local topographical changes have an important impact on the wind field. Based on the Rothermel fire spread model, a forest fire in Idaho in the western United States was simulated. The historical data proved that the simulation results had a good accuracy. They showed that the fire spread rate will decrease rapidly with time and then reach a steady state. After reaching a steady state, the fire spread growth area will not only be affected by the slope, but will also show a significant quadratic linear positive correlation with the wind speed change.

Keywords: Wind field, numerical simulation, forest fire spread, fire behavior model, complex terrain.

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Authors: S. M. Azad, H. Ghodsipour, F. Roshannafas

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In recent years ‘technology management and policymaking’ is one of the most important problems in management science. In this field, different generations of innovation and technology management are presented which the earliest one is Innovation System (IS) approach. In a general classification, innovation systems are divided in to 4 approaches: technical, sectoral, regional, and national. There are many researches in relation to each of these approaches in different academic fields. Every approach has some benefits. If two or more approaches hybrid, their benefits would be combined. In addition, according to the sectoral structure of the governance model in Iran, in many sectors, such as information technology, the combination of three other approaches with sectoral approach is essential. Hence, in this paper, combining two IS approaches (technical and sectoral) and using system dynamics, a generic model is presented for a sample of software industry. As a complimentary point, this article is introducing a new hybrid approach called Techno-Sectoral Innovation System. This TSIS model is accomplished by Changing concepts of the ‘functions’-which came from Technological IS literature- and using them into sectoral system as measurable indicators.

Keywords: Innovation system, technology, techno-sectoral system, functional indicators, system dynamics.

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Authors: Afshin Ahmadi Nadooshan, Ebrahim Shirani

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In this paper, the two-dimensional stagger grid interface pressure (SGIP) model has been generalized and presented into three-dimensional form. For this purpose, various models of surface tension force for interfacial flows have been investigated and compared with each other. The VOF method has been used for tracking the interface. To show the ability of the SGIP model for three-dimensional flows in comparison with other models, pressure contours, maximum spurious velocities, norm spurious flow velocities and pressure jump error for motionless drop of liquid and bubble of gas are calculated using different models. It has been pointed out that SGIP model in comparison with the CSF, CSS and PCIL models produces the least maximum and norm spurious velocities. Additionally, the new model produces more accurate results in calculating the pressure jumps across the interface for motionless drop of liquid and bubble of gas which is generated in surface tension force.

Keywords: Volume-of-Fluid; SGIP model; CSS model; CSF model; PCIL model; surface tension force; spurious currents.

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Authors: Panprapa Yongtrakul, Punyaphat Sirithanabadeekul, Pakjira Siriphan

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Background: The thread lift technique has become popular because it is less invasive, requires a shorter operation, less downtime, and results in fewer postoperative complications. The advantage of the technique is that the thread can be inserted under the skin without the need for long incisions. Currently, there are a lot of thread lift techniques with respect to the specific types of thread used on specific areas, such as the mid-face, lower face, or neck area. Objective: To review the thread lift technique for specific areas according to type of thread, patient selection, and how to match the most appropriate to the patient. Materials and Methods: A literature review technique was conducted by searching PubMed and MEDLINE, then compiled and summarized. Result: We have divided our protocols into two sections: Protocols for short suture, and protocols for long suture techniques. We also created 3D pictures for each technique to enhance understanding and application in a clinical setting. Conclusion: There are advantages and disadvantages to short suture and long suture techniques. The best outcome for each patient depends on appropriate patient selection and determining the most suitable technique for the defect and area of patient concern.

Keywords: Thread lift, thread lift method, thread lift technique, thread lift procedure, threading.

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Authors: V. Sudha, D. Sriram Kumar

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Orthogonal Frequency Division Multiplexing (OFDM) has been used in many advanced wireless communication systems due to its high spectral efficiency and robustness to frequency selective fading channels. However, the major concern with OFDM system is the high peak-to-average power ratio (PAPR) of the transmitted signal. Some of the popular techniques used for PAPR reduction in OFDM system are conventional partial transmit sequences (CPTS) and clipping. In this paper, a parallel combination/hybrid scheme of PAPR reduction using clipping and CPTS algorithms is proposed. The proposed method intelligently applies both the algorithms in order to reduce both PAPR as well as computational complexity. The proposed scheme slightly degrades bit error rate (BER) performance due to clipping operation and it can be reduced by selecting an appropriate value of the clipping ratio (CR). The simulation results show that the proposed algorithm achieves significant PAPR reduction with much reduced computational complexity.

Keywords: CCDF, OFDM, PAPR, PTS.

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Authors: Tea Poklepović, Zdravka Aljinović, Branka Marasović

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Due to the importance of yield curve and its estimation it is inevitable to have valid methods for yield curve forecasting in cases when there are scarce issues of securities and/or week trade on a secondary market. Therefore in this paper, after the estimation of weekly yield curves on Croatian financial market from October 2011 to August 2012 using Nelson-Siegel and Svensson models, yield curves are forecasted using Vector autoregressive model and Neural networks. In general, it can be concluded that both forecasting methods have good prediction abilities where forecasting of yield curves based on Nelson Siegel estimation model give better results in sense of lower Mean Squared Error than forecasting based on Svensson model Also, in this case Neural networks provide slightly better results. Finally, it can be concluded that most appropriate way of yield curve prediction is Neural networks using Nelson-Siegel estimation of yield curves.

Keywords: Nelson-Siegel model, Neural networks, Svensson model, Vector autoregressive model, Yield curve.

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Authors: Elnaz Lashgari, Emel Demircan

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Electromyography (EMG) is one of the most important interfaces between humans and robots for rehabilitation. Decoding this signal helps to recognize muscle activation and converts it into smooth motion for the robots. Detecting each muscle’s pattern during walking and running is vital for improving the quality of a patient’s life. In this study, EMG data from 10 muscles in 10 subjects at 4 different speeds were analyzed. EMG signals are nonlinear with high dimensionality. To deal with this challenge, we extracted some features in time-frequency domain and used manifold learning and Laplacian Eigenmaps algorithm to find the intrinsic features that represent data in low-dimensional space. We then used the Bayesian classifier to identify various patterns of EMG signals for different muscles across a range of running speeds. The best result for vastus medialis muscle corresponds to 97.87±0.69 for sensitivity and 88.37±0.79 for specificity with 97.07±0.29 accuracy using Bayesian classifier. The results of this study provide important insight into human movement and its application for robotics research.

Keywords: Electrocardiogram, manifold learning, Laplacian Eigenmaps, running pattern.

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Authors: Grzegorz Sierpiński, Ireneusz Celiński, Marcin Staniek

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The article discusses multimodal mobility in contemporary societies as a main planning and organization issue in the functioning of administrative bodies, a problem which really exists in the space of contemporary cities in terms of shaping modern transport systems. The article presents classification of available resources and initiatives undertaken for developing multimodal mobility. Solutions can be divided into three groups of measures – physical measures in the form of changes of the transport network infrastructure, organizational ones (including transport policy) and information measures. The latter ones include in particular direct support for people travelling in the transport network by providing information about ways of using available means of transport. A special measure contributing to this end is a trip planner. The article compares several selected planners. It includes a short description of the Green Travelling Project, which aims at developing a planner supporting environmentally friendly solutions in terms of transport network operation. The article summarizes preliminary findings of the project.

Keywords: Mobility, modal split, multimodal trip, multimodal platforms, sustainable transport.

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Authors: A. Shayeghi, H. Eimani Kalasar, H. Shayeghi

Abstract:

This paper emphasizes on the application of genetic algorithm (GA) to optimize the parameters of the TMD for achieving the best results in the reduction of the building response under earthquake excitations. The Integral of the Time multiplied Absolute value of the Error (ITAE) based on relative displacement of all floors in the building is taken as a performance index of the optimization criterion. The problem of robustly TMD controller design is formatted as an optimization problem based on the ITAE performance index to be solved using GA that has a story ability to find the most optimistic results. An 11–story realistic building, located in the city of Rasht, Iran is considered as a test system to demonstrate effectiveness of the proposed GA based TMD (GATMD) controller without specifying which mode should be controlled. The results of the proposed GATMD controller are compared with the uncontrolled structure through timedomain simulation and some performance indices. The results analysis reveals that the designed GA based TMD controller has an excellent capability in reduction of the seismically excited example building and the ITAE performance, that is so for remains as unknown, can be introduced a new criteria - method for structural dynamic design.

Keywords: Tuned Mass Damper, Genetic Algorithm, TallBuildings, Structural Dynamics.

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Authors: Arturo Aquino, Manuel Emilio Gegundez, Jose Manuel Bravo, Diego Marin

Abstract:

Retinal vascularity assessment plays an important role in diagnosis of ophthalmic pathologies. The employment of digital images for this purpose makes possible a computerized approach and has motivated development of many methods for automated vascular tree segmentation. Metrics based on contingency tables for binary classification have been widely used for evaluating performance of these algorithms and, concretely, the accuracy has been mostly used as measure of global performance in this topic. However, this metric shows very poor matching with human perception as well as other notable deficiencies. Here, a new similarity function for measuring quality of retinal vessel segmentations is proposed. This similarity function is based on characterizing the vascular tree as a connected structure with a measurable area and length. Tests made indicate that this new approach shows better behaviour than the current one does. Generalizing, this concept of measuring descriptive properties may be used for designing functions for measuring more successfully segmentation quality of other complex structures.

Keywords: Retinal vessel segmentation, quality assessment, performanceevaluation, similarity function.

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