Search results for: misclassification rate
2792 The Classification Performance in Parametric and Nonparametric Discriminant Analysis for a Class- Unbalanced Data of Diabetes Risk Groups
Authors: Lily Ingsrisawang, Tasanee Nacharoen
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The problems arising from unbalanced data sets generally appear in real world applications. Due to unequal class distribution, many researchers have found that the performance of existing classifiers tends to be biased towards the majority class. The k-nearest neighbors’ nonparametric discriminant analysis is a method that was proposed for classifying unbalanced classes with good performance. In this study, the methods of discriminant analysis are of interest in investigating misclassification error rates for classimbalanced data of three diabetes risk groups. The purpose of this study was to compare the classification performance between parametric discriminant analysis and nonparametric discriminant analysis in a three-class classification of class-imbalanced data of diabetes risk groups. Data from a project maintaining healthy conditions for 599 employees of a government hospital in Bangkok were obtained for the classification problem. The employees were divided into three diabetes risk groups: non-risk (90%), risk (5%), and diabetic (5%). The original data including the variables of diabetes risk group, age, gender, blood glucose, and BMI were analyzed and bootstrapped for 50 and 100 samples, 599 observations per sample, for additional estimation of the misclassification error rate. Each data set was explored for the departure of multivariate normality and the equality of covariance matrices of the three risk groups. Both the original data and the bootstrap samples showed nonnormality and unequal covariance matrices. The parametric linear discriminant function, quadratic discriminant function, and the nonparametric k-nearest neighbors’ discriminant function were performed over 50 and 100 bootstrap samples and applied to the original data. Searching the optimal classification rule, the choices of prior probabilities were set up for both equal proportions (0.33: 0.33: 0.33) and unequal proportions of (0.90:0.05:0.05), (0.80: 0.10: 0.10) and (0.70, 0.15, 0.15). The results from 50 and 100 bootstrap samples indicated that the k-nearest neighbors approach when k=3 or k=4 and the defined prior probabilities of non-risk: risk: diabetic as 0.90: 0.05:0.05 or 0.80:0.10:0.10 gave the smallest error rate of misclassification. The k-nearest neighbors approach would be suggested for classifying a three-class-imbalanced data of diabetes risk groups.Keywords: Bootstrap, diabetes risk groups, error rate, k-nearest neighbors.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20082791 A New Face Recognition Method using PCA, LDA and Neural Network
Authors: A. Hossein Sahoolizadeh, B. Zargham Heidari, C. Hamid Dehghani
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In this paper, a new face recognition method based on PCA (principal Component Analysis), LDA (Linear Discriminant Analysis) and neural networks is proposed. This method consists of four steps: i) Preprocessing, ii) Dimension reduction using PCA, iii) feature extraction using LDA and iv) classification using neural network. Combination of PCA and LDA is used for improving the capability of LDA when a few samples of images are available and neural classifier is used to reduce number misclassification caused by not-linearly separable classes. The proposed method was tested on Yale face database. Experimental results on this database demonstrated the effectiveness of the proposed method for face recognition with less misclassification in comparison with previous methods.Keywords: Face recognition Principal component analysis, Linear discriminant analysis, Neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32132790 Voltage Problem Location Classification Using Performance of Least Squares Support Vector Machine LS-SVM and Learning Vector Quantization LVQ
Authors: Khaled Abduesslam. M, Mohammed Ali, Basher H Alsdai, Muhammad Nizam, Inayati
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This paper presents the voltage problem location classification using performance of Least Squares Support Vector Machine (LS-SVM) and Learning Vector Quantization (LVQ) in electrical power system for proper voltage problem location implemented by IEEE 39 bus New- England. The data was collected from the time domain simulation by using Power System Analysis Toolbox (PSAT). Outputs from simulation data such as voltage, phase angle, real power and reactive power were taken as input to estimate voltage stability at particular buses based on Power Transfer Stability Index (PTSI).The simulation data was carried out on the IEEE 39 bus test system by considering load bus increased on the system. To verify of the proposed LS-SVM its performance was compared to Learning Vector Quantization (LVQ). The results showed that LS-SVM is faster and better as compared to LVQ. The results also demonstrated that the LS-SVM was estimated by 0% misclassification whereas LVQ had 7.69% misclassification.
Keywords: IEEE 39 bus, Least Squares Support Vector Machine, Learning Vector Quantization, Voltage Collapse.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24052789 Novel Approach for Promoting the Generalization Ability of Neural Networks
Authors: Naiqin Feng, Fang Wang, Yuhui Qiu
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A new approach to promote the generalization ability of neural networks is presented. It is based on the point of view of fuzzy theory. This approach is implemented through shrinking or magnifying the input vector, thereby reducing the difference between training set and testing set. It is called “shrinking-magnifying approach" (SMA). At the same time, a new algorithm; α-algorithm is presented to find out the appropriate shrinking-magnifying-factor (SMF) α and obtain better generalization ability of neural networks. Quite a few simulation experiments serve to study the effect of SMA and α-algorithm. The experiment results are discussed in detail, and the function principle of SMA is analyzed in theory. The results of experiments and analyses show that the new approach is not only simpler and easier, but also is very effective to many neural networks and many classification problems. In our experiments, the proportions promoting the generalization ability of neural networks have even reached 90%.Keywords: Fuzzy theory, generalization, misclassification rate, neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15352788 Motor Imaginary Signal Classification Using Adaptive Recursive Bandpass Filter and Adaptive Autoregressive Models for Brain Machine Interface Designs
Authors: Vickneswaran Jeyabalan, Andrews Samraj, Loo Chu Kiong
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The noteworthy point in the advancement of Brain Machine Interface (BMI) research is the ability to accurately extract features of the brain signals and to classify them into targeted control action with the easiest procedures since the expected beneficiaries are of disabled. In this paper, a new feature extraction method using the combination of adaptive band pass filters and adaptive autoregressive (AAR) modelling is proposed and applied to the classification of right and left motor imagery signals extracted from the brain. The introduction of the adaptive bandpass filter improves the characterization process of the autocorrelation functions of the AAR models, as it enhances and strengthens the EEG signal, which is noisy and stochastic in nature. The experimental results on the Graz BCI data set have shown that by implementing the proposed feature extraction method, a LDA and SVM classifier outperforms other AAR approaches of the BCI 2003 competition in terms of the mutual information, the competition criterion, or misclassification rate.
Keywords: Adaptive autoregressive, adaptive bandpass filter, brain machine Interface, EEG, motor imaginary.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29012787 Early Warning System of Financial Distress Based On Credit Cycle Index
Authors: Bi-Huei Tsai
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Previous studies on financial distress prediction choose the conventional failing and non-failing dichotomy; however, the distressed extent differs substantially among different financial distress events. To solve the problem, “non-distressed”, “slightlydistressed” and “reorganization and bankruptcy” are used in our article to approximate the continuum of corporate financial health. This paper explains different financial distress events using the two-stage method. First, this investigation adopts firm-specific financial ratios, corporate governance and market factors to measure the probability of various financial distress events based on multinomial logit models. Specifically, the bootstrapping simulation is performed to examine the difference of estimated misclassifying cost (EMC). Second, this work further applies macroeconomic factors to establish the credit cycle index and determines the distressed cut-off indicator of the two-stage models using such index. Two different models, one-stage and two-stage prediction models are developed to forecast financial distress, and the results acquired from different models are compared with each other, and with the collected data. The findings show that the one-stage model has the lower misclassification error rate than the two-stage model. The one-stage model is more accurate than the two-stage model.
Keywords: Multinomial logit model, corporate governance, company failure, reorganization, bankruptcy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26802786 The Correlation of Economic Variables on Domestic Investment
Authors: Amirreza Attarzadeh
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This paper aims to investigate the relationship between economic variables, e.g., inflation rate, interest rate, trade openness and the growth rate of GDP, with domestic investment. The present study also draws on conceptual economy related theories to verify the negative effect of interest rates on domestic investment. However, trade openness and growth rate had a positive correlation, and the inflation rate may have a positive or negative impact on domestic investment.
Keywords: Inflation rate, growth rate of GDP, interest rate, trade openness, domestic investment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13952785 Analysis of Bit Error Rate Improvement in MFSK Communication Link
Authors: O. P. Sharma, V. Janyani, S. Sancheti
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Data rate, tolerable bit error rate or frame error rate and range & coverage are the key performance requirement of a communication link. In this paper performance of MFSK link is analyzed in terms of bit error rate, number of errors and total number of data processed. In the communication link model proposed, which is implemented using MATLAB block set, an improvement in BER is observed. Different parameters which effects and enables to keep BER low in M-ary communication system are also identified.Keywords: Additive White Gaussian Noise (AWGN), Bit Error Rate (BER), Frequency Shift Keying (FSK), Orthogonal Signaling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28892784 Hazard Rate Estimation of Temporal Point Process, Case Study: Earthquake Hazard Rate in Nusatenggara Region
Authors: Sunusi N., Kresna A. J., Islamiyati A., Raupong
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Hazard rate estimation is one of the important topics in forecasting earthquake occurrence. Forecasting earthquake occurrence is a part of the statistical seismology where the main subject is the point process. Generally, earthquake hazard rate is estimated based on the point process likelihood equation called the Hazard Rate Likelihood of Point Process (HRLPP). In this research, we have developed estimation method, that is hazard rate single decrement HRSD. This method was adapted from estimation method in actuarial studies. Here, one individual associated with an earthquake with inter event time is exponentially distributed. The information of epicenter and time of earthquake occurrence are used to estimate hazard rate. At the end, a case study of earthquake hazard rate will be given. Furthermore, we compare the hazard rate between HRLPP and HRSD method.Keywords: Earthquake forecast, Hazard Rate, Likelihood point process, Point process.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14952783 Research of Ring MEMS Rate Integrating Gyroscopes
Authors: Hui Liu, Haiyang Quan
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This paper To get the angle value with a MEMS rate gyroscope in some specific field, the usual method is to make an integral operation to the rate output, which will lead the error cumulating effect. So the rate gyro is not suitable. MEMS rate integrating gyroscope (MRIG) will solve this problem. A DSP system has been developed to implement the control arithmetic. The system can measure the angle of rotation directly by the control loops that make the sensor work in whole-angle mode. Modeling the system with MATLAB, desirable results of angle outputs are got, which prove the feasibility of the control arithmetic.Keywords: Rate gyroscope, Rate integrating gyroscope, Whole angle mode, MATLAB modeling, DSP control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32562782 Development of Sleep Quality Index Using Heart Rate
Authors: Dongjoo Kim, Chang-Sik Son, Won-Seok Kang
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Adequate sleep affects various parts of one’s overall physical and mental life. As one of the methods in determining the appropriate amount of sleep, this research presents a heart rate based sleep quality index. In order to evaluate sleep quality using the heart rate, sleep data from 280 subjects taken over one month are used. Their sleep data are categorized by a three-part heart rate range. After categorizing, some features are extracted, and the statistical significances are verified for these features. The results show that some features of this sleep quality index model have statistical significance. Thus, this heart rate based sleep quality index may be a useful discriminator of sleep.Keywords: Sleep, sleep quality, heart rate, statistical analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15042781 Synergistic Impacts and Optimization of Gas Flow Rate, Concentration of CO2, and Light Intensity on CO2 Biofixation in Wastewater Medium by Chlorella vulgaris
Authors: Ahmed Arkoazi, Hussein Znad, Ranjeet Utikar
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The synergistic impact and optimization of gas flow rate, concentration of CO2, and light intensity on CO2 biofixation rate were investigated using wastewater as a medium to cultivate Chlorella vulgaris under different conditions (gas flow rate 1-8 L/min), CO2 concentration (0.03-7%), and light intensity (150-400 µmol/m2.s)). Response Surface Methodology and Box-Behnken experimental Design were applied to find optimum values for gas flow rate, CO2 concentration, and light intensity. The optimum values of the three independent variables (gas flow rate, concentration of CO2, and light intensity) and desirability were 7.5 L/min, 3.5%, and 400 µmol/m2.s, and 0.904, respectively. The highest amount of biomass produced and CO2 biofixation rate at optimum conditions were 5.7 g/L, 1.23 gL-1d-1, respectively. The synergistic effect between gas flow rate and concentration of CO2, and between gas flow rate and light intensity was significant on the three responses, while the effect between CO2 concentration and light intensity was less significant on CO2 biofixation rate. The results of this study could be highly helpful when using microalgae for CO2 biofixation in wastewater treatment.
Keywords: Synergistic impact, optimization, CO2 biofixation, airlift reactor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7382780 The Rank-scaled Mutation Rate for Genetic Algorithms
Authors: Mike Sewell, Jagath Samarabandu, Ranga Rodrigo, Kenneth McIsaac
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A novel method of individual level adaptive mutation rate control called the rank-scaled mutation rate for genetic algorithms is introduced. The rank-scaled mutation rate controlled genetic algorithm varies the mutation parameters based on the rank of each individual within the population. Thereby the distribution of the fitness of the papulation is taken into consideration in forming the new mutation rates. The best fit mutate at the lowest rate and the least fit mutate at the highest rate. The complexity of the algorithm is of the order of an individual adaptation scheme and is lower than that of a self-adaptation scheme. The proposed algorithm is tested on two common problems, namely, numerical optimization of a function and the traveling salesman problem. The results show that the proposed algorithm outperforms both the fixed and deterministic mutation rate schemes. It is best suited for problems with several local optimum solutions without a high demand for excessive mutation rates.
Keywords: Genetic algorithms, mutation rate control, adaptive mutation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26692779 Impact of Exchange Rate on Macroeconomic Indicators
Authors: Aleksandre Ergeshidze
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The exchange rate is a pivotal pricing instrument that simultaneously impacts various components of the economy. Depreciation of nominal exchange rate is export promoting, which might be a desired export-led growth policy, and particularly critical to closing-down the widening current account imbalance. However, negative effects resulting from high dollarization and high share of imported intermediate inputs can outweigh positive effect. The aim of this research is to quantify impact of change in nominal exchange rate and test contractionary depreciation hypothesis on Georgian economy using structural and Bayesian vector autoregression. According to the acquired results, appreciation of nominal exchange rate is expected to decrease inflation, monetary policy rate, interest rate on domestic currency loans and economic growth in the medium run; however, impact on economic growth in the short run is statistically not significant.
Keywords: Bayesian vector autoregression, contractionary depreciation, dollarization, nominal exchange rate, structural vector autoregression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11782778 New Dynamic Constitutive Model for OFHC Copper Film
Authors: Jin Sung Kim, Hoon Huh
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The material properties of OFHC copper film was investigated with the High-Speed Material Micro Testing Machine (HSMMTM) at the high strain rates. The rate-dependent stress-strain curves from the experiment and the Johnson−Cook curve fitting showed large discrepancies as the plastic strain increases since the constitutive model implies no rate-dependent strain hardening effect. A new constitutive model was proposed in consideration of rate-dependent strain hardening effect. The strain rate hardening term in the new constitutive model consists of the strain rate sensitivity coefficients of the yield strength and strain hardening.
Keywords: Rate dependent material properties, Dynamic constitutive model, OFHC copper film, Strain rate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24182777 Exchange Rate Volatility, Its Determinants and Effects on the Manufacturing Sector in Nigeria
Authors: Chimaobi V. Okolo, Onyinye S. Ugwuanyi, Kenneth A. Okpala
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This study evaluated the effect of exchange rate volatility on the manufacturing sector of Nigeria. The flow and stock market theories of exchange rate determination was adopted considering macroeconomic determinants such as balance of trade, trade openness, and net international investment. Furthermore, the influence of changes in parallel exchange rate, official exchange rate and real effective exchange rate was modeled on the manufacturing sector output. Vector autoregression techniques and vector error correction mechanism were adopted to explore the macroeconomic determinants of exchange rate fluctuation in Nigeria and to examine the influence of exchange rate volatility on the manufacturing sector output in Nigeria. The exchange rate showed an unstable and volatile movement in Nigeria. Official exchange rate significantly impacted on the manufacturing sector of Nigeria and shock to previous manufacturing sector output caused 60.76% of the fluctuation in the manufacturing sector output in Nigeria. Trade balance, trade openness and net international investments did not significantly determine exchange rate in Nigeria. However, own shock accounted for about 95% of the variation of exchange rate fluctuation in the short-run and long-run. Among other macroeconomic variables, net international investment accounted for about 2.85% variation of the real effective exchange rate fluctuation in the short-run and in the long-run. Monetary authorities should maintain stability of the exchange rates through proper management so as to encourage local production and government should formulate and implement policies that will develop other sectors of the economy as this will widen the country’s revenue base, reduce our over reliance on oil sector for our foreign exchange earnings and in turn reduce the shocks on our domestic economy.
Keywords: Exchange rate volatility, exchange rate determinants, manufacturing sector, official exchange rate, parallel exchange rate, real effective exchange rate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19302776 A Bathtub Curve from Nonparametric Model
Authors: Eduardo C. Guardia, Jose W. M. Lima, Afonso H. M. Santos
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This paper presents a nonparametric method to obtain the hazard rate “Bathtub curve” for power system components. The model is a mixture of the three known phases of a component life, the decreasing failure rate (DFR), the constant failure rate (CFR) and the increasing failure rate (IFR) represented by three parametric Weibull models. The parameters are obtained from a simultaneous fitting process of the model to the Kernel nonparametric hazard rate curve. From the Weibull parameters and failure rate curves the useful lifetime and the characteristic lifetime were defined. To demonstrate the model the historic time-to-failure of distribution transformers were used as an example. The resulted “Bathtub curve” shows the failure rate for the equipment lifetime which can be applied in economic and replacement decision models.
Keywords: Bathtub curve, failure analysis, lifetime estimation, parameter estimation, Weibull distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22342775 Methods of Estimating the Equilibrium Real Effective Exchange Rate (REER)
Authors: Pavla Ruzickova, Petr Teply
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There are many debates now regarding undervalued and overvalued currencies currently traded on the world financial market. This paper contributes to these debates from a theoretical point of view. We present the three most commonly used methods of estimating the equilibrium real effective exchange rate (REER): macroeconomic balance approach, external sustainability approach and equilibrium real effective exchange rate approach in the reduced form. Moreover, we discuss key concepts of the calculation of the real exchange rate (RER) based on applied explanatory variables: nominal exchange rates, terms of trade and tradable and non-tradable goods. Last but not least, we discuss the three main driving forces behind real exchange rates movements which include terms of trade, relative productivity growth and the interest rate differential.Keywords: real exchange rate, real effective exchange rate, foreign exchange, terms of trade
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24892774 Effect of Dose Rate of Irradiation on Ultrastructure of Duodenal Mucosa
Authors: L. Labéjof, I. Mororó, P. Galle, G. Barbosa, M.I. Severo, A.H. de Oliveira
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Ultrastructure of duodenum mucosa of irradiated rat was studied versus dose rate of irradiation following exposure to gamma rays from 60-Cobalt source. The animals were whole body irradiated at two dose rates (1 Gy.mn-1 and 1 Gy.h-1) and three total doses (1, 2 or 4 Gy) for each dose rate. 24 or 48 h after irradiation, their small intestine was removed and samples of duodenum were processed for observations under a transmission electron microscopy. Samples of duodenum mucosa of control rats were processed in the same way. For the lower dose rate of 1 Gy.h-1, main lesions characteristic of apoptosis were detected within irradiated enterocytes at a total dose of 2 Gy and 24 h after exposure. Necrosis was noted in the samples, 48 h after exposition. For the higher dose rate of 1 Gy.mn-1, fewer changes were detected at all total doses 24 or 48 h irradiation. Thus, it was shown that the appearance of radiationinduced alterations varies not only with increasing total dose and post-irradiation time but especially with decreasing dose rate.Keywords: Dose rate, Radiation Inury, Apoptosis, SmallBowel
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19472773 A Comparison of Signal Processing Techniques for the Extraction of Breathing Rate from the Photoplethysmogram
Authors: Susannah G. Fleming Lionel Tarassenko
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The photoplethysmogram (PPG) is the pulsatile waveform produced by the pulse oximeter, which is widely used for monitoring arterial oxygen saturation in patients. Various methods for extracting the breathing rate from the PPG waveform have been compared using a consistent data set, and a novel technique using autoregressive modelling is presented. This novel technique is shown to outperform the existing techniques, with a mean error in breathing rate of 0.04 breaths per minute.Keywords: Autoregressive modelling, breathing rate, photoplethysmogram, pulse oximetry.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33182772 Automatic Facial Skin Segmentation Using Possibilistic C-Means Algorithm for Evaluation of Facial Surgeries
Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammadhossein Sedaaghi
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Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy CMeans (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic CMeans (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.
Keywords: Facial image, segmentation, PCM, FCM, skin error, facial surgery.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19902771 Using the Simple Fixed Rate Approach to Solve Economic Lot Scheduling Problem under the Basic Period Approach
Authors: Yu-Jen Chang, Yun Chen, Hei-Lam Wong
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The Economic Lot Scheduling Problem (ELSP) is a valuable mathematical model that can support decision-makers to make scheduling decisions. The basic period approach is effective for solving the ELSP. The assumption for applying the basic period approach is that a product must use its maximum production rate to be produced. However, a product can lower its production rate to reduce the average total cost when a facility has extra idle time. The past researches discussed how a product adjusts its production rate under the common cycle approach. To the best of our knowledge, no studies have addressed how a product lowers its production rate under the basic period approach. This research is the first paper to discuss this topic. The research develops a simple fixed rate approach that adjusts the production rate of a product under the basic period approach to solve the ELSP. Our numerical example shows our approach can find a better solution than the traditional basic period approach. Our mathematical model that applies the fixed rate approach under the basic period approach can serve as a reference for other related researches.Keywords: Economic Lot, Basic Period, Genetic Algorithm, Fixed Rate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19392770 The Impact of Exchange Rate Volatility on Real Total Export and Sub-Categories of Real Total Export of Malaysia
Authors: Wong Hock Tsen
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This study aims to investigate the impact of exchange rate volatility on real export in Malaysia. The moving standard deviation with order three (MSD(3)) is used for the measurement of exchange rate volatility. The conventional and partially asymmetric autoregressive distributed lag (ARDL) models are used in the estimations. This study finds exchange rate volatility to have significant impact on real total export and some sub-categories of real total export. Moreover, this study finds that the positive or negative exchange rate volatility tends to have positive or negative impact on real export. Exchange rate volatility can be harmful to export of Malaysia.
Keywords: Exchange rate volatility, autoregressive distributed lag, export, Malaysia.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11982769 On Speeding Up Support Vector Machines: Proximity Graphs Versus Random Sampling for Pre-Selection Condensation
Authors: Xiaohua Liu, Juan F. Beltran, Nishant Mohanchandra, Godfried T. Toussaint
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Support vector machines (SVMs) are considered to be the best machine learning algorithms for minimizing the predictive probability of misclassification. However, their drawback is that for large data sets the computation of the optimal decision boundary is a time consuming function of the size of the training set. Hence several methods have been proposed to speed up the SVM algorithm. Here three methods used to speed up the computation of the SVM classifiers are compared experimentally using a musical genre classification problem. The simplest method pre-selects a random sample of the data before the application of the SVM algorithm. Two additional methods use proximity graphs to pre-select data that are near the decision boundary. One uses k-Nearest Neighbor graphs and the other Relative Neighborhood Graphs to accomplish the task.Keywords: Machine learning, data mining, support vector machines, proximity graphs, relative-neighborhood graphs, k-nearestneighbor graphs, random sampling, training data condensation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19192768 Simulation of the Asphaltene Deposition Rate in a Wellbore Blockage via Computational Fluid Dynamics
Authors: Xiaodong Gao, Pingchuan Dong, Qichao Gao
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This work attempts to predict the deposition rate of asphaltene particles in blockage tube through CFD simulation. The Euler-Lagrange equation has been applied during the flow of crude oil and asphaltene particles. The net gravitational force, virtual mass, pressure gradient, Saffman lift, and drag forces are incorporated in the simulations process. Validation of CFD simulation results is compared to the benchmark experiments from the previous literature. Furthermore, the effects of blockage location, blockage length, and blockage thickness on deposition rate are also analyzed. The simulation results indicate that the maximum deposition rate of asphaltene occurs in the blocked tube section, and the greater the deposition thickness, the greater the deposition rate. Moreover, the deposition amount and maximum deposition rate along the length of the tube have the same trend. Results of this study are in the ability to better understand the deposition of asphaltene particles in production and help achieve to deal with the asphaltene challenges.
Keywords: Asphaltene deposition rate, blockage length, blockage thickness, blockage diameter, transient condition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4582767 A Study of Factors Affecting the Elapsed Time of Housing Renewal Project Implementation in Seoul
Authors: In Su Na, Gunwon Lee, Seiyong Kim
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This study analyzed the effect of area variables and economic variables on the length of each period of the project in order to analyze the effect of agreement rate on project implementation in housing renewal projects. In conclusion, as can be seen from these results, a low agreement rate may not translate into project promotion, and a higher agreement rate may not translate into project delay. The expectation of the policy is that the lower the agreement rate, the more projects would be promoted, but that is not the actual effect. From a policy consistency viewpoint, changing the agreement rate frequently, depending on the decision of the public, is not reasonable. The policy of using agreement rate as a necessary condition for project implementation should be reconsidered.Keywords: Area and Economic Variables, Elapsed time, Housing Renewal Project.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16242766 Optimal Policy for a Deteriorating Inventory Model with Finite Replenishment Rate and with Price Dependant Demand Rate and Cycle Length Dependant Price
Authors: Hamed Sabahno
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In this paper, an inventory model with finite and constant replenishment rate, price dependant demand rate, time value of money and inflation, finite time horizon, lead time and exponential deterioration rate and with the objective of maximizing the present worth of the total system profit is developed. Using a dynamic programming based solution algorithm, the optimal sequence of the cycles can be found and also different optimal selling prices, optimal order quantities and optimal maximum inventories can be obtained for the cycles with unequal lengths, which have never been done before for this model. Also, a numerical example is used to show accuracy of the solution procedure.Keywords: Deteriorating items, Dynamic programming, Finitereplenishment rate, Inventory control, Operation Research.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14032765 An Expectation of the Rate of Inflation According to Inflation-Unemployment Interaction in Croatia
Authors: Zdravka Aljinović, Snježana Pivac, Boško Šego
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According to the interaction of inflation and unemployment, expectation of the rate of inflation in Croatia is estimated. The interaction between inflation and unemployment is shown by model based on three first-order differential i.e. difference equations: Phillips relation, adaptive expectations equation and monetary-policy equation. The resulting equation is second order differential i.e. difference equation which describes the time path of inflation. The data of the rate of inflation and the rate of unemployment are used for parameters estimation. On the basis of the estimated time paths, the stability and convergence analysis is done for the rate of inflation.Keywords: Differencing, inflation, time path, unemployment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16142764 An Efficient Motion Recognition System Based on LMA Technique and a Discrete Hidden Markov Model
Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier
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Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.Keywords: Human Motion Recognition, Motion representation, Laban Movement Analysis, Discrete Hidden Markov Model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7282763 CFD Modeling of Reduction in NOX Emission Using HiTAC Technique
Authors: Abbas Khoshhal, Masoud Rahimi, Sayed Reza Shabanian, Ammar Abdulaziz Alsairafi
Abstract:
In the present study, the rate of NOx emission in a combustion chamber working in conventional combustion and High Temperature Air Combustion (HiTAC) system are examined using CFD modeling. The effect of peak temperature, combustion air temperature and oxygen concentration on NOx emission rate was undertaken. Results show that in a fixed oxygen concentration, increasing the preheated air temperature will increase the peak temperature and NOx emission rate. In addition, it was observed that the reduction of the oxygen concentration in the fixed preheated air temperature decreases the peak temperature and NOx emission rate. On the other hand, the results show that increase of preheated air temperature at various oxygen concentrations increases the NOx emission rate. However, the rate of increase in HiTAC conditions is quite lower than the conventional combustion. The modeling results show that the NOx emission rate in HiTAC combustion is 133% less than that of the conventional combustion.Keywords: CFD Modeling, HiTAC, NOx, Combustion.
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