Search results for: Absolute pitch
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 289

Search results for: Absolute pitch

79 Data Envelopment Analysis with Partially Perfect Objects

Authors: Alexander Y. Vaninsky

Abstract:

This paper presents a simplified version of Data Envelopment Analysis (DEA) - a conventional approach to evaluating the performance and ranking of competitive objects characterized by two groups of factors acting in opposite directions: inputs and outputs. DEA with a Perfect Object (DEA PO) augments the group of actual objects with a virtual Perfect Object - the one having greatest outputs and smallest inputs. It allows for obtaining an explicit analytical solution and making a step to an absolute efficiency. This paper develops this approach further and introduces a DEA model with Partially Perfect Objects. DEA PPO consecutively eliminates the smallest relative inputs or greatest relative outputs, and applies DEA PO to the reduced collections of indicators. The partial efficiency scores are combined to get the weighted efficiency score. The computational scheme remains simple, like that of DEA PO, but the advantage of the DEA PPO is taking into account all of the inputs and outputs for each actual object. Firm evaluation is considered as an example.

Keywords: Data Envelopment Analysis, Perfect object, Partially perfect object, Partial efficiency, Explicit solution, Simplified algorithm.

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78 Determine of Constant Coefficients to RelateTotal Dissolved Solids to Electrical Conductivity

Authors: M. Siosemarde, F. Kave, E. Pazira, H. Sedghi, S. J. Ghaderi

Abstract:

Salinity is a measure of the amount of salts in the water. Total Dissolved Solids (TDS) as salinity parameter are often determined using laborious and time consuming laboratory tests, but it may be more appropriate and economical to develop a method which uses a more simple soil salinity index. Because dissolved ions increase salinity as well as conductivity, the two measures are related. The aim of this research was determine of constant coefficients for predicting of Total Dissolved Solids (TDS) based on Electrical Conductivity (EC) with Statistics of Correlation coefficient, Root mean square error, Maximum error, Mean Bias error, Mean absolute error, Relative error and Coefficient of residual mass. For this purpose, two experimental areas (S1, S2) of Khuzestan province-IRAN were selected and four treatments with three replications by series of double rings were applied. The treatments were included 25cm, 50cm, 75cm and 100cm water application. The results showed the values 16.3 & 12.4 were the best constant coefficients for predicting of Total Dissolved Solids (TDS) based on EC in Pilot S1 and S2 with correlation coefficient 0.977 & 0.997 and 191.1 & 106.1 Root mean square errors (RMSE) respectively.

Keywords: constant coefficients, electrical conductivity, Khuzestan plain and total dissolved solids.

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77 Mathematical Modelling and Numerical Simulation of Maisotsenko Cycle

Authors: Rasikh Tariq, Fatima Z. Benarab

Abstract:

Evaporative coolers has a minimum potential to reach the wet-bulb temperature of intake air which is not enough to handle a large cooling load; therefore, it is not a feasible option to overcome cooling requirement of a building. The invention of Maisotsenko (M) cycle has led evaporative cooling technology to reach the sub-wet-bulb temperature of the intake air; therefore, it brings an innovation in evaporative cooling techniques. In this work, we developed a mathematical model of the Maisotsenko based air cooler by applying energy and mass balance laws on different air channels. The governing ordinary differential equations are discretized and simulated on MATLAB. The temperature and the humidity plots are shown in the simulation results. A parametric study is conducted by varying working air inlet conditions (temperature and humidity), inlet air velocity, geometric parameters and water temperature. The influence of these aforementioned parameters on the cooling effectiveness of the HMX is reported.  Results have shown that the effectiveness of the M-Cycle is increased by increasing the ambient temperature and decreasing absolute humidity. An air velocity of 0.5 m/sec and a channel height of 6-8mm is recommended.

Keywords: Renewable energy, indirect evaporative cooling, Maisotsenko cycle, HMX, mathematical model, numerical simulation.

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76 Collaboration in Palliative Care Networks in Urban and Rural Regions of Switzerland

Authors: R. Schweighoffer, N. Nagy, E. Reeves, B. Liebig

Abstract:

Due to aging populations, the need for seamless palliative care provision is of central interest for western societies. An essential aspect of palliative care delivery is the quality of collaboration amongst palliative care providers. Therefore, the current research is based on Bainbridge’s conceptual framework, which provides an outline for the evaluation of palliative care provision. This study is the first one to investigate the predictive validity of spatial distribution on the quantity of interaction amongst various palliative care providers. Furthermore, based on the familiarity principle, we examine whether the extent of collaboration influences the perceived quality of collaboration among palliative care providers in urban versus rural areas of Switzerland. Based on a population-representative survey of Swiss palliative care providers, the results of the current study show that professionals in densely populated areas report higher absolute numbers of interactions and are more satisfied with their collaborative practice. This indicates that palliative care providers who work in urban areas are better embedded into networks than their counterparts in more rural areas. The findings are especially important, considering that efficient collaboration is a prerequisite to achieve satisfactory patient outcomes. Conclusively, measures should be taken to foster collaboration in weakly interconnected palliative care networks.

Keywords: Collaboration, healthcare networks, palliative care, Switzerland.

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75 Studding of Number of Dataset on Precision of Estimated Saturated Hydraulic Conductivity

Authors: M. Siosemarde, M. Byzedi

Abstract:

Saturated hydraulic conductivity of Soil is an important property in processes involving water and solute flow in soils. Saturated hydraulic conductivity of soil is difficult to measure and can be highly variable, requiring a large number of replicate samples. In this study, 60 sets of soil samples were collected at Saqhez region of Kurdistan province-IRAN. The statistics such as Correlation Coefficient (R), Root Mean Square Error (RMSE), Mean Bias Error (MBE) and Mean Absolute Error (MAE) were used to evaluation the multiple linear regression models varied with number of dataset. In this study the multiple linear regression models were evaluated when only percentage of sand, silt, and clay content (SSC) were used as inputs, and when SSC and bulk density, Bd, (SSC+Bd) were used as inputs. The R, RMSE, MBE and MAE values of the 50 dataset for method (SSC), were calculated 0.925, 15.29, -1.03 and 12.51 and for method (SSC+Bd), were calculated 0.927, 15.28,-1.11 and 12.92, respectively, for relationship obtained from multiple linear regressions on data. Also the R, RMSE, MBE and MAE values of the 10 dataset for method (SSC), were calculated 0.725, 19.62, - 9.87 and 18.91 and for method (SSC+Bd), were calculated 0.618, 24.69, -17.37 and 22.16, respectively, which shows when number of dataset increase, precision of estimated saturated hydraulic conductivity, increases.

Keywords: dataset, precision, saturated hydraulic conductivity, soil and statistics.

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74 Assessment of the Biological Nitrogen Fixation in Soybean Sown in Different Types of Moroccan Soils

Authors: F. Z. Aliyat, B. Ben Messaoud, L. Nassiri, E. Bouiamrine, J. Ibijbijen

Abstract:

The present study aims to assess the biological nitrogen fixation in the soybean tested in different Moroccan soils combined with the rhizobial inoculation. These effects were evaluated by the plant growth mainly by the aerial biomass production, total nitrogen content and the proportion of the nitrogen fixed. This assessment clearly shows that the inoculation with bacteria increases the growth of soybean. Five different soils and a control (peat) were used. The rhizobial inoculation was performed by applying the peat that contained a mixture of 2 strains Sinorhizobium fredii HH103 and Bradyrhizobium. The biomass, the total nitrogen content and the proportion of nitrogen fixed were evaluated under different treatments. The essay was realized at the greenhouse the Faculty of Sciences, Moulay Ismail University. The soybean has shown a great response for the parameters assessed. Moreover, the best response was reported by the inoculated plants compared to non- inoculated and to the absolute control. Finally, good production and the best biological nitrogen fixation present an important ecological technology to improve the sustainable production of soybean and to ensure the increase of the fertility of soils.

Keywords: Biological nitrogen fixation, inoculation, rhizobium, soybean.

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73 Sustainability: An Ethical Approach Towards Project Business Success

Authors: G. S. Dangayach

Abstract:

For any country the project management has been a vital part for its development. The highly competitive business world has created tremendous pressure on the project managers to achieve success. The pressure is derived from survival and profit building in business organizations which compels the project managers to pursue unethical practices. As a result unethical activities in business projects can be found easily where situations or issues arise due to dubious business practice, high corruption, or absolute violation of the law. The recent spur on Commonwealth games to be organized in New Delhi indicates towards the same. It has been seen that the project managers mainly focus on cost, time, and quality rather than social impact and long term effects of the project. Surprisingly the literature as well as the practitioner-s perspective also does not identify the role of ethics in project success. This paper identifies ethics as the fourth most important dimension in the project based organizations. The paper predicts that the approach of considering ethics will result in sustainability of the project. It will increase satisfaction and loyalty of the customers as well as create harmony, trust, brotherhood, values and morality among the team members. This paper is conceptual in nature as inadequate literature exists linking the project success with an ethical approach.

Keywords: Ethics, Loyalty, Morality, Project success

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72 Analysis of Residual Strain and Stress Distributions in High Speed Milled Specimens using an Indentation Method

Authors: Felipe V. Díaz, Claudio A. Mammana, Armando P. M. Guidobono, Raúl E. Bolmaro

Abstract:

Through a proper analysis of residual strain and stress distributions obtained at the surface of high speed milled specimens of AA 6082–T6 aluminium alloy, the performance of an improved indentation method is evaluated. This method integrates a special device of indentation to a universal measuring machine. The mentioned device allows introducing elongated indents allowing to diminish the absolute error of measurement. It must be noted that the present method offers the great advantage of avoiding both the specific equipment and highly qualified personnel, and their inherent high costs. In this work, the cutting tool geometry and high speed parameters are selected to introduce reduced plastic damage. Through the variation of the depth of cut, the stability of the shapes adopted by the residual strain and stress distributions is evaluated. The results show that the strain and stress distributions remain unchanged, compressive and small. Moreover, these distributions reveal a similar asymmetry when the gradients corresponding to conventional and climb cutting zones are compared.

Keywords: Residual strain, residual stress, high speed milling, indentation methods, aluminium alloys.

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71 3-D Numerical Simulation of Scraped Surface Heat Exchanger with Helical Screw

Authors: Rabeb Triki, Hassene Djemel, Mounir Baccar

Abstract:

Surface scraping is a passive heat transfer enhancement technique that is directly used in scraped surface heat exchanger (SSHE). The scraping action prevents the accumulation of the product on the inner wall, which intensifies the heat transfer and avoids the formation of dead zones. SSHEs are widely used in industry for several applications such as crystallization, sterilization, freezing, gelatinization, and many other continuous processes. They are designed to deal with products that are viscous, sticky or that contain particulate matter. This research work presents a three-dimensional numerical simulation of the coupled thermal and hydrodynamic behavior within a SSHE which includes Archimedes’ screw instead of scraper blades. The finite volume Fluent 15.0 was used to solve continuity, momentum and energy equations using multiple reference frame formulation. The process fluid investigated under this study is the pure glycerin. Different geometrical parameters were studied in the case of steady, non-isothermal, laminar flow. In particular, attention is focused on the effect of the conicity of the rotor and the pitch of Archimedes’ screw on temperature and velocity distribution and heat transfer rate. Numerical investigations show that the increase of the number of turns in the screw from five to seven turns leads to amelioration of heat transfer coefficient, and the increase of the conicity of the rotor from 0.1 to 0.15 leads to an increase in the rate of heat transfer. Further studies should investigate the effect of different operating parameters (axial and rotational Reynolds number) on the hydrodynamic and thermal behavior of the SSHE.

Keywords: ANSYS-Fluent, hydrodynamic behavior, SSHE, thermal behavior.

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70 Impact of Changes in Excise Tax Rate for Strong Alcohol on Consumption and State Revenues in Latvia

Authors: A. Strateičuks, V. Kaže, R. Škapars

Abstract:

State tax revenues in most countries started to decrease during the recession. Government of Latvia decided to compensate the decline by increasing rates of several taxes including excise tax on strong alcohol. The total increase in 2009 constituted 42% and the rate increased from 896€ to 1 266€ for 100l of absolute alcohol. Since then this has had a negative impact on consumption volumes and the split between legal and illegal market. The legal alcohol sales decreased by almost 50% (by volume), consequentially having negative effect on the State revenues from VAT and excise tax. Estimated results for 2010 are indicating 54 million € decrease in VAT, excise tax and other taxes versus 2008 (excise tax -19 million €, VAT -30 million €, other taxes -5 million €). The paper aims to analyze impact of the increase in excise tax on consumption patterns, State revenues and competitiveness of the local companies to draw up proposals for the state authorities regarding more effective tax policies. The analysis reveals a relationship between excise tax rate, illegal alcohol market and State revenues. The results can be used to improve excise tax system and effectiveness in Latvia.

Keywords: State revenues, alcohol market, excise tax, competitiveness, consumption.

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69 A Propose of Personnel Assessment Method Including a Two-Way Assessment for Evaluating Evaluators and Employees

Authors: Shunsuke Saito, Kazuho Yoshimoto, Shunichi Ohmori, Sirawadee Arunyanart

Abstract:

In this paper, we suggest a mechanism of assessment that rater and Ratee (or employees) to convince. There are many problems exist in the personnel assessment. In particular, we were focusing on the three. (1) Raters are not sufficiently recognized assessment point. (2) Ratee are not convinced by the mechanism of assessment. (3) Raters (or Evaluators) and ratees have empathy. We suggest 1: Setting of "understanding of the assessment points." 2: Setting of "relative assessment ability." 3: Proposal of two-way assessment mechanism to solve these problems. As a prerequisite, it is assumed that there are multiple raters. This is because has been a growing importance of multi-faceted assessment. In this model, it determines the weight of each assessment point evaluators by the degree of understanding and assessment ability of raters and ratee. We used the ANP (Analytic Network Process) is a theory that an extension of the decision-making technique AHP (Analytic Hierarchy Process). ANP can be to address the problem of forming a network and assessment of Two-Way is possible. We apply this technique personnel assessment, the weights of rater of each point can be reasonably determined. We suggest absolute assessment for Two-Way assessment by ANP. We have verified that the consent of the two approaches is higher than conventional mechanism. Also, human resources consultant we got a comment about the application of the practice.

Keywords: Personnel assessment, ANP (analytic network process), two-way.

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68 Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) Parameters for Propane, Ethylene, and Hydrogen under Supercritical Conditions

Authors: Ilke Senol

Abstract:

Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) equation of state (EOS) is a modified SAFT EOS with three pure component specific parameters: segment number (m), diameter (σ) and energy (ε). These PC-SAFT parameters need to be determined for each component under the conditions of interest by fitting experimental data, such as vapor pressure, density or heat capacity. PC-SAFT parameters for propane, ethylene and hydrogen in supercritical region were successfully estimated by fitting experimental density data available in literature. The regressed PCSAFT parameters were compared with the literature values by means of estimating pure component density and calculating average absolute deviation between the estimated and experimental density values. PC-SAFT parameters available in literature especially for ethylene and hydrogen estimated density in supercritical region reasonably well. However, the regressed PC-SAFT parameters performed better in supercritical region than the PC-SAFT parameters from literature.

Keywords: Equation of state, perturbed-chain, PC-SAFT, super critical.

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67 Modelling an Investment Portfolio with Mandatory and Voluntary Contributions under M-CEV Model

Authors: Amadi Ugwulo Chinyere, Lewis D. Gbarayorks, Emem N. H. Inamete

Abstract:

In this paper, the mandatory contribution, additional voluntary contribution (AVC) and administrative charges are merged together to determine the optimal investment strategy (OIS) for a pension plan member (PPM) in a defined contribution (DC) pension scheme under the modified constant elasticity of variance (M-CEV) model. We assume that the voluntary contribution is a stochastic process and a portfolio consisting of one risk free asset and one risky asset modeled by the M-CEV model is considered. Also, a stochastic differential equation consisting of PPM’s monthly contributions, voluntary contributions and administrative charges is obtained. More so, an optimization problem in the form of Hamilton Jacobi Bellman equation which is a nonlinear partial differential equation is obtained. Using power transformation and change of variables method, an explicit solution of the OIS and the value function are obtained under constant absolute risk averse (CARA). Furthermore, numerical simulations on the impact of some sensitive parameters on OIS were discussed extensively. Finally, our result generalizes some existing result in the literature.

Keywords: DC pension fund, modified constant elasticity of variance, optimal investment strategies, voluntary contribution, administrative charges.

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66 Simulation of PM10 Source Apportionment at An Urban Site in Southern Taiwan by a Gaussian Trajectory Model

Authors: Chien-Lung Chen, Jeng-Lin Tsai, Feng-Chao Chung, Su-Ching Kuo, Kuo-Hsin Tseng, Pei-Hsuan Kuo, Li-Ying Hsieh, Ying I. Tsai

Abstract:

This study applied the Gaussian trajectory transfer-coefficient model (GTx) to simulate the particulate matter concentrations and the source apportionments at Nanzih Air Quality Monitoring Station in southern Taiwan from November 2007 to February 2008. The correlation coefficient between the observed and the calculated daily PM10 concentrations is 0.5 and the absolute bias of the PM10 concentrations is 24%. The simulated PM10 concentrations matched well with the observed data. Although the emission rate of PM10 was dominated by area sources (58%), the results of source apportionments indicated that the primary sources for PM10 at Nanzih Station were point sources (42%), area sources (20%) and then upwind boundary concentration (14%). The obvious difference of PM10 source apportionment between episode and non-episode days was upwind boundary concentrations which contributed to 20% and 11% PM10 sources, respectively. The gas-particle conversion of secondary aerosol and long range transport played crucial roles on the PM10 contribution to a receptor.

Keywords: back trajectory model, particulate matter, sourceapportionment

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65 Optimization of SAD Algorithm on VLIW DSP

Authors: Hui-Jae You, Sun-Tae Chung, Souhwan Jung

Abstract:

SAD (Sum of Absolute Difference) algorithm is heavily used in motion estimation which is computationally highly demanding process in motion picture encoding. To enhance the performance of motion picture encoding on a VLIW processor, an efficient implementation of SAD algorithm on the VLIW processor is essential. SAD algorithm is programmed as a nested loop with a conditional branch. In VLIW processors, loop is usually optimized by software pipelining, but researches on optimal scheduling of software pipelining for nested loops, especially nested loops with conditional branches are rare. In this paper, we propose an optimal scheduling and implementation of SAD algorithm with conditional branch on a VLIW DSP processor. The proposed optimal scheduling first transforms the nested loop with conditional branch into a single loop with conditional branch with consideration of full utilization of ILP capability of the VLIW processor and realization of earlier escape from the loop. Next, the proposed optimal scheduling applies a modulo scheduling technique developed for single loop. Based on this optimal scheduling strategy, optimal implementation of SAD algorithm on TMS320C67x, a VLIW DSP is presented. Through experiments on TMS320C6713 DSK, it is shown that H.263 encoder with the proposed SAD implementation performs better than other H.263 encoder with other SAD implementations, and that the code size of the optimal SAD implementation is small enough to be appropriate for embedded environments.

Keywords: Optimal implementation, SAD algorithm, VLIW, TMS320C6713.

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64 Influence of the Compression Force and Powder Particle Size on Some Physical Properties of Date Fruit (Phoenix dactylifera) Tablets

Authors: Djemaa Megdoud, Messaoud Boudaa, Fatima Ouamrane, Salem Benamara

Abstract:

In recent years, the compression of date (Phoenix dactylifera L.) fruit powders (DP) to obtain date tablets (DT) has been suggested as a promising form of valorization of non commercial valuable date fruit (DF) varieties. To further improve and characterize DT, the present study aims to investigate the influence of the DP particle size and compression force on some physical properties of DT. The results show that independently of particle size, the hardness (y) of tablets increases with the increase of the compression force (x) following a logarithmic law (y = a ln (bx) where a and b are the constants of model). Further, a full factorial design (FFD) at two levels, applied to investigate the erosion %, reveals that the effects of time and particle size are the same in absolute value and they are beyond the effect of the compression. Regarding the disintegration time, the obtained results also by means of a FFD show that the effect of the compression force exceeds 4 times that of the DP particle size. As final stage, the color parameters in the CIELab system of DT immediately after their obtaining are differently influenced by the size of the initial powder.

Keywords: Powder, valorization, tablets, date fruit (Phoenix dactylifera L.), hardness, erosion, disintegration time, color.

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63 Predicting the Impact of the Defect on the Overall Environment in Function Based Systems

Authors: Parvinder S. Sandhu, Urvashi Malhotra, E. Ardil

Abstract:

There is lot of work done in prediction of the fault proneness of the software systems. But, it is the severity of the faults that is more important than number of faults existing in the developed system as the major faults matters most for a developer and those major faults needs immediate attention. In this paper, we tried to predict the level of impact of the existing faults in software systems. Neuro-Fuzzy based predictor models is applied NASA-s public domain defect dataset coded in C programming language. As Correlation-based Feature Selection (CFS) evaluates the worth of a subset of attributes by considering the individual predictive ability of each feature along with the degree of redundancy between them. So, CFS is used for the selecting the best metrics that have highly correlated with level of severity of faults. The results are compared with the prediction results of Logistic Models (LMT) that was earlier quoted as the best technique in [17]. The results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The results show that Neuro-fuzzy based model provide a relatively better prediction accuracy as compared to other models and hence, can be used for the modeling of the level of impact of faults in function based systems.

Keywords: Software Metrics, Fuzzy, Neuro-Fuzzy, Software Faults, Accuracy, MAE, RMSE.

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62 Pension Plan Member’s Investment Strategies with Transaction Cost and Couple Risky Assets Modelled by the O-U Process

Authors: Udeme O. Ini, Edikan E. Akpanibah

Abstract:

This paper studies the optimal investment strategies for a plan member (PM) in a defined contribution (DC) pension scheme with transaction cost, taxes on invested funds and couple risky assets (stocks) under the Ornstein-Uhlenbeck (O-U) process. The PM’s portfolio is assumed to consist of a risk-free asset and two risky assets where the two risky assets are driven by the O-U process. The Legendre transformation and dual theory is use to transform the resultant optimal control problem which is a nonlinear partial differential equation (PDE) into linear PDE and the resultant linear PDE is then solved for the explicit solutions of the optimal investment strategies for PM exhibiting constant absolute risk aversion (CARA) using change of variable technique. Furthermore, theoretical analysis is used to study the influences of some sensitive parameters on the optimal investment strategies with observations that the optimal investment strategies for the two risky assets increase with increase in the dividend and decreases with increase in tax on the invested funds, risk averse coefficient, initial fund size and the transaction cost.

Keywords: Ornstein-Uhlenbeck process, portfolio management, Legendre transforms, CARA utility.

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61 An Assessment of the Hip Muscular Imbalance for Patients with Rheumatism

Authors: Anthony Bawa, Konstantinos Banitsas

Abstract:

Rheumatism is a muscular disorder that affects the muscles of the upper and lower limbs. This condition could potentially progress to impair the movement of patients. This study aims to investigate the hip muscular imbalance in patients with chronic rheumatism. A clinical trial involving a total of 15 participants, made up of 10 patients and five control subjects, took place in KATH Hospital between August and September. Participants recruited for the study were of age 54 ± 8 years, weight 65 ± 8 kg, and height 176 ± 8 cm. Muscle signals were recorded from the rectus femoris, and vastus lateralis on the right and left hip of participants. The parameters used in determining the hip muscular imbalances were the maximum voluntary contraction (MVC%), the mean difference, and hip muscle fatigue levels. The mean signals were compared using a t-test, and the metrics for muscle fatigue assessment were based on the root mean square (RMS), mean absolute value (MAV) and mean frequency (MEF), which were computed between the hip muscles of participants. The results indicated that there were significant imbalances in the muscle coactivity between the right and left hip muscles of patients. The patients’ MVC values were observed to be above 10% when compared with control subjects. Furthermore, the mean difference was seen to be higher with p > 0.002 among patients, which indicated clear differences in the hip muscle contraction activities. The findings indicate significant hip muscular imbalances for patients with rheumatism compared with control subjects. Information about the imbalances among patients will be useful for clinicians in designing therapeutic muscle-strengthening exercises.

Keywords: Muscular, imbalances, rheumatism, hip.

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60 Nonlinear Fuzzy Tracking Real-time-based Control of Drying Parameters

Authors: Marco Soares dos Santos, Camila Nicola Boeri, Jorge Augusto Ferreira, Fernando Neto da Silva

Abstract:

The highly nonlinear characteristics of drying processes have prompted researchers to seek new nonlinear control solutions. However, the relation between the implementation complexity, on-line processing complexity, reliability control structure and controller-s performance is not well established. The present paper proposes high performance nonlinear fuzzy controllers for a real-time operation of a drying machine, being developed under a consistent match between those issues. A PCI-6025E data acquisition device from National Instruments® was used, and the control system was fully designed with MATLAB® / SIMULINK language. Drying parameters, namely relative humidity and temperature, were controlled through MIMOs Hybrid Bang-bang+PI (BPI) and Four-dimensional Fuzzy Logic (FLC) real-time-based controllers to perform drying tests on biological materials. The performance of the drying strategies was compared through several criteria, which are reported without controllers- retuning. Controllers- performance analysis has showed much better performance of FLC than BPI controller. The absolute errors were lower than 8,85 % for Fuzzy Logic Controller, about three times lower than the experimental results with BPI control.

Keywords: Drying control, Fuzzy logic control, Intelligent temperature-humidity control.

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59 Study on the Effect of Bolt Locking Method on the Deformation of Bipolar Plate in PEMFC

Authors: Tao Chen, ShiHua Liu, JiWei Zhang

Abstract:

Assembly of the proton exchange membrane fuel cells (PEMFC) has a very important influence on its performance and efficiency. The various components of PEMFC stack are usually locked and fixed by bolts. Locking bolt will cause the deformation of the bipolar plate and the other components, which will affect directly the deformation degree of the integral parts of the PEMFC as well as the performance of PEMFC. This paper focuses on the object of three-cell stack of PEMFC. Finite element simulation is used to investigate the deformation of bipolar plate caused by quantity and layout of bolts, bolt locking pressure, and bolt locking sequence, etc. Finally, we made a conclusion that the optimal combination packaging scheme was adopted to assemble the fuel cell stack. The scheme was in use of 3.8 MPa locking pressure imposed on the fuel cell stack, type Ⅱ of four locking bolts and longitudinal locking method. The scheme was obtained by comparatively analyzing the overall displacement contour of PEMFC stack, absolute displacement curve of bipolar plate along the given three paths in the Z direction and the polarization curve of fuel cell. The research results are helpful for the fuel cell stack assembly.

Keywords: Bipolar plate, deformation, finite element simulation, fuel cell, locking bolt.

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58 Validation and Selection between Machine Learning Technique and Traditional Methods to Reduce Bullwhip Effects: a Data Mining Approach

Authors: Hamid R. S. Mojaveri, Seyed S. Mousavi, Mojtaba Heydar, Ahmad Aminian

Abstract:

The aim of this paper is to present a methodology in three steps to forecast supply chain demand. In first step, various data mining techniques are applied in order to prepare data for entering into forecasting models. In second step, the modeling step, an artificial neural network and support vector machine is presented after defining Mean Absolute Percentage Error index for measuring error. The structure of artificial neural network is selected based on previous researchers' results and in this article the accuracy of network is increased by using sensitivity analysis. The best forecast for classical forecasting methods (Moving Average, Exponential Smoothing, and Exponential Smoothing with Trend) is resulted based on prepared data and this forecast is compared with result of support vector machine and proposed artificial neural network. The results show that artificial neural network can forecast more precisely in comparison with other methods. Finally, forecasting methods' stability is analyzed by using raw data and even the effectiveness of clustering analysis is measured.

Keywords: Artificial Neural Networks (ANN), bullwhip effect, demand forecasting, Support Vector Machine (SVM).

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57 Forecasting 24-Hour Ahead Electricity Load Using Time Series Models

Authors: Ramin Vafadary, Maryam Khanbaghi

Abstract:

Forecasting electricity load is important for various purposes like planning, operation and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria namely, the Mean Absolute Error and Root Mean Square Error. The National Renewable Energy Laboratory (NREL) residential energy consumption data are used to train the models. The results of this study show that SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts we can improve the robustness of the models for 24 hour ahead electricity load forecasting.

Keywords: Bagging, Fbprophet, Holt-Winters, LSTM, Load Forecast, SARIMA, tensorflow probability, time series.

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56 Software Maintenance Severity Prediction for Object Oriented Systems

Authors: Parvinder S. Sandhu, Roma Jaswal, Sandeep Khimta, Shailendra Singh

Abstract:

As the majority of faults are found in a few of its modules so there is a need to investigate the modules that are affected severely as compared to other modules and proper maintenance need to be done in time especially for the critical applications. As, Neural networks, which have been already applied in software engineering applications to build reliability growth models predict the gross change or reusability metrics. Neural networks are non-linear sophisticated modeling techniques that are able to model complex functions. Neural network techniques are used when exact nature of input and outputs is not known. A key feature is that they learn the relationship between input and output through training. In this present work, various Neural Network Based techniques are explored and comparative analysis is performed for the prediction of level of need of maintenance by predicting level severity of faults present in NASA-s public domain defect dataset. The comparison of different algorithms is made on the basis of Mean Absolute Error, Root Mean Square Error and Accuracy Values. It is concluded that Generalized Regression Networks is the best algorithm for classification of the software components into different level of severity of impact of the faults. The algorithm can be used to develop model that can be used for identifying modules that are heavily affected by the faults.

Keywords: Neural Network, Software faults, Software Metric.

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55 Comparison of Different Discontinuous PWM Technique for Switching Losses Reduction in Modular Multilevel Converters

Authors: Kaumil B. Shah, Hina Chandwani

Abstract:

The modular multilevel converter (MMC) is one of the advanced topologies for medium and high-voltage applications. In high-power, high-voltage MMC, a large number of switching power devices are required. These switching power devices (IGBT) considerable switching losses. This paper analyzes the performance of different discontinuous pulse width modulation (DPWM) techniques and compares the results against a conventional carrier based pulse width modulation method, in order to reduce the switching losses of an MMC. The DPWM reference wave can be generated by adding the zero-sequence component to the original (sine) reference modulation signal. The result of the addition gives the reference signal of DPWM techniques. To minimize the switching losses of the MMC, the clamping period is controlled according to the absolute value of the output load current. No switching is generated in the clamping period so overall switching of the power device is reduced. The simulation result of the different DPWM techniques is compared with conventional carrier-based pulse-width modulation technique.

Keywords: Modular multilevel converter, discontinuous pulse width modulation, switching losses, zero-sequence voltage.

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54 An Efficient Architecture for Interleaved Modular Multiplication

Authors: Ahmad M. Abdel Fattah, Ayman M. Bahaa El-Din, Hossam M.A. Fahmy

Abstract:

Modular multiplication is the basic operation in most public key cryptosystems, such as RSA, DSA, ECC, and DH key exchange. Unfortunately, very large operands (in order of 1024 or 2048 bits) must be used to provide sufficient security strength. The use of such big numbers dramatically slows down the whole cipher system, especially when running on embedded processors. So far, customized hardware accelerators - developed on FPGAs or ASICs - were the best choice for accelerating modular multiplication in embedded environments. On the other hand, many algorithms have been developed to speed up such operations. Examples are the Montgomery modular multiplication and the interleaved modular multiplication algorithms. Combining both customized hardware with an efficient algorithm is expected to provide a much faster cipher system. This paper introduces an enhanced architecture for computing the modular multiplication of two large numbers X and Y modulo a given modulus M. The proposed design is compared with three previous architectures depending on carry save adders and look up tables. Look up tables should be loaded with a set of pre-computed values. Our proposed architecture uses the same carry save addition, but replaces both look up tables and pre-computations with an enhanced version of sign detection techniques. The proposed architecture supports higher frequencies than other architectures. It also has a better overall absolute time for a single operation.

Keywords: Montgomery multiplication, modular multiplication, efficient architecture, FPGA, RSA

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53 Estimation of Time -Varying Linear Regression with Unknown Time -Volatility via Continuous Generalization of the Akaike Information Criterion

Authors: Elena Ezhova, Vadim Mottl, Olga Krasotkina

Abstract:

The problem of estimating time-varying regression is inevitably concerned with the necessity to choose the appropriate level of model volatility - ranging from the full stationarity of instant regression models to their absolute independence of each other. In the stationary case the number of regression coefficients to be estimated equals that of regressors, whereas the absence of any smoothness assumptions augments the dimension of the unknown vector by the factor of the time-series length. The Akaike Information Criterion is a commonly adopted means of adjusting a model to the given data set within a succession of nested parametric model classes, but its crucial restriction is that the classes are rigidly defined by the growing integer-valued dimension of the unknown vector. To make the Kullback information maximization principle underlying the classical AIC applicable to the problem of time-varying regression estimation, we extend it onto a wider class of data models in which the dimension of the parameter is fixed, but the freedom of its values is softly constrained by a family of continuously nested a priori probability distributions.

Keywords: Time varying regression, time-volatility of regression coefficients, Akaike Information Criterion (AIC), Kullback information maximization principle.

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52 The Correlation of Total Phenol Content with Free Radicals Scavenging Activity and Effect of Ethanol Concentration in Extraction Process of Mangosteen Rind (Garcinia mangostana)

Authors: Ririn Lestari Sri Rahayu, Mustofa Ahda

Abstract:

The use of synthetic antioxidants often causes a negative effect on health and increases the incidence of carcinogenesis. Development of the natural antioxidants should be investigated. However, natural antioxidants have a low toxicity and are safe for human consumption. Ethanol extract of mangosteen rind (Garcinia mangostana) contains natural antioxidant compounds that have various pharmacological activities. Antioxidants from the ethanol extract of mangosteen rind have free radicals scavenging activities. The scavenging activity of ethanol extract of mangosteen rind was determined by DPPH method. The phenolic compound from the ethanol extract of mangosteen rind is determined with Folin-Ciocalteu method. The results showed that the absolute ethanol extract of mangosteen rind has IC50 of 40.072 ug/mL. The correlation of total phenols content with free radical scavenging activity has an equation y: 5.207x + 205.51 and determination value (R2) of 0.9329. Total phenols content from the ethanol extract of mangosteen rind has a good correlation with free radicals scavenging activity of DPPH.

Keywords: Antioxidant, Garcinia mangostana, inhibition concentration 50%, total phenolic compounds.

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51 Ab initio Study of Co2ZrGe and Co2NbB Full Heusler Compounds

Authors: Abada Ahmed, Hiadsi Said, Ouahrani Tarik, Amrani Bouhalouane, Amara Kadda

Abstract:

Using the first-principles full-potential linearized augmented plane wave plus local orbital (FP-LAPW+lo) method based on density functional theory (DFT), we have investigated the electronic structure and magnetism of full Heusler alloys Co2ZrGe and Co2NbB. These compounds are predicted to be half-metallic ferromagnets (HMFs) with a total magnetic moment of 2.000 B per formula unit, well consistent with the Slater-Pauling rule. Calculations show that both the alloys have an indirect band gaps, in the minority-spin channel of density of states (DOS), with values of 0.58 eV and 0.47 eV for Co2ZrGe and Co2NbB, respectively. Analysis of the DOS and magnetic moments indicates that their magnetism is mainly related to the d-d hybridization between the Co and Zr (or Nb) atoms. The half-metallicity is found to be relatively robust against volume changes. In addition, an atom inside molecule AIM formalism and an electron localization function ELF were also adopted to study the bonding properties of these compounds, building a bridge between their electronic and bonding behavior. As they have a good crystallographic compatibility with the lattice of semiconductors used industrially and negative calculated cohesive energies with considerable absolute values these two alloys could be promising magnetic materials in the spintronic field.

Keywords: Electronic properties, full Heusler alloys, halfmetallic ferromagnets, magnetic properties.

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50 Revised PLWAP Tree with Non-frequent Items for Mining Sequential Pattern

Authors: R. Vishnu Priya, A. Vadivel

Abstract:

Sequential pattern mining is a challenging task in data mining area with large applications. One among those applications is mining patterns from weblog. Recent times, weblog is highly dynamic and some of them may become absolute over time. In addition, users may frequently change the threshold value during the data mining process until acquiring required output or mining interesting rules. Some of the recently proposed algorithms for mining weblog, build the tree with two scans and always consume large time and space. In this paper, we build Revised PLWAP with Non-frequent Items (RePLNI-tree) with single scan for all items. While mining sequential patterns, the links related to the nonfrequent items are not considered. Hence, it is not required to delete or maintain the information of nodes while revising the tree for mining updated transactions. The algorithm supports both incremental and interactive mining. It is not required to re-compute the patterns each time, while weblog is updated or minimum support changed. The performance of the proposed tree is better, even the size of incremental database is more than 50% of existing one. For evaluation purpose, we have used the benchmark weblog dataset and found that the performance of proposed tree is encouraging compared to some of the recently proposed approaches.

Keywords: Sequential pattern mining, weblog, frequent and non-frequent items, incremental and interactive mining.

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