Search results for: latin squares
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 234

Search results for: latin squares

234 Some Constructions of Non-Commutative Latin Squares of Order n

Authors: H. V. Chen, A. Y. M. Chin, S. Sharmini

Abstract:

Let n be an integer. We show the existence of at least three non-isomorphic non-commutative Latin squares of order n which are embeddable in groups when n ≥ 5 is odd. By using a similar construction for the case when n ≥ 4 is even, we show that certain non-commutative Latin squares of order n are not embeddable in groups.

Keywords: group, Latin square, embedding.

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233 Construction of Space-Filling Designs for Three Input Variables Computer Experiments

Authors: Kazeem A. Osuolale, Waheed B. Yahya, Babatunde L. Adeleke

Abstract:

Latin hypercube designs (LHDs) have been applied in many computer experiments among the space-filling designs found in the literature. A LHD can be randomly generated but a randomly chosen LHD may have bad properties and thus act poorly in estimation and prediction. There is a connection between Latin squares and orthogonal arrays (OAs). A Latin square of order s involves an arrangement of s symbols in s rows and s columns, such that every symbol occurs once in each row and once in each column and this exists for every non-negative integer s. In this paper, a computer program was written to construct orthogonal array-based Latin hypercube designs (OA-LHDs). Orthogonal arrays (OAs) were constructed from Latin square of order s and the OAs constructed were afterward used to construct the desired Latin hypercube designs for three input variables for use in computer experiments. The LHDs constructed have better space-filling properties and they can be used in computer experiments that involve only three input factors. MATLAB 2012a computer package (www.mathworks.com/) was used for the development of the program that constructs the designs.

Keywords: Computer Experiments, Latin Squares, Latin Hypercube Designs, Orthogonal Array, Space-filling Designs.

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232 Minimizing Examinee Collusion with a Latin- Square Treatment Structure

Authors: M. H. Omar

Abstract:

Cheating on standardized tests has been a major concern as it potentially minimizes measurement precision. One major way to reduce cheating by collusion is to administer multiple forms of a test. Even with this approach, potential collusion is still quite large. A Latin-square treatment structure for distributing multiple forms is proposed to further reduce the colluding potential. An index to measure the extent of colluding potential is also proposed. Finally, with a simple algorithm, the various Latin-squares were explored to find the best structure to keep the colluding potential to a minimum.

Keywords: Colluding pairs, Scale for Colluding Potential, Latin-Square Structure, Minimization of Cheating.

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231 Block Cipher Based on Randomly Generated Quasigroups

Authors: Deepthi Haridas, S Venkataraman, Geeta Varadan

Abstract:

Quasigroups are algebraic structures closely related to Latin squares which have many different applications. The construction of block cipher is based on quasigroup string transformation. This article describes a block cipher based Quasigroup of order 256, suitable for fast software encryption of messages written down in universal ASCII code. The novelty of this cipher lies on the fact that every time the cipher is invoked a new set of two randomly generated quasigroups are used which in turn is used to create a pair of quasigroup of dual operations. The cryptographic strength of the block cipher is examined by calculation of the xor-distribution tables. In this approach some algebraic operations allows quasigroups of huge order to be used without any requisite to be stored.

Keywords: quasigroups, latin squares, block cipher and quasigroup string transformations.

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230 Classification of the Latin Alphabet as Pattern on ARToolkit Markers for Augmented Reality Applications

Authors: Mohamed Badeche, Mohamed Benmohammed

Abstract:

augmented reality is a technique used to insert virtual objects in real scenes. One of the most used libraries in the area is the ARToolkit library. It is based on the recognition of the markers that are in the form of squares with a pattern inside. This pattern which is mostly textual is source of confusing. In this paper, we present the results of a classification of Latin characters as a pattern on the ARToolkit markers to know the most distinguishable among them.

Keywords: ARToolkit library, augmented reality, K-means, patterns

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229 Comparing Arabic and Latin Handwritten Digits Recognition Problems

Authors: Sherif Abdelazeem

Abstract:

A comparison between the performance of Latin and Arabic handwritten digits recognition problems is presented. The performance of ten different classifiers is tested on two similar Arabic and Latin handwritten digits databases. The analysis shows that Arabic handwritten digits recognition problem is easier than that of Latin digits. This is because the interclass difference in case of Latin digits is smaller than in Arabic digits and variances in writing Latin digits are larger. Consequently, weaker yet fast classifiers are expected to play more prominent role in Arabic handwritten digits recognition.

Keywords: Handwritten recognition, Arabic recognition, Digits recognition, Document recognition

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228 China's Strategic Aid Diplomacy to Foster Development of Latin America

Authors: Wanda Luen-Wun Siu, Xiaowen Zhang

Abstract:

This paper adopted a retrospective review of China’s assistance to Latin America from the 1950s to 2020. Findings suggested that China’s assistance to Latin America can be roughly divided into five stages: The 1950s to 1960s was the initial stage of China’s assistance to Latin America, mainly focusing on the establishment of diplomatic relations with Cuba and other Latin American countries. The strategy has a strong ideological basis. The 1980s were the stage of development of China's aid to Latin America, which was characterized by consolidating and expanding diplomatic space, emphasizing the spirit of cooperation of equality, mutual benefit, and common development. The 1990s to 2000s marked the further development of diplomatic relations with Latin American countries, plus domestic market-oriented reforms, emphasizing the importance of economic considerations, and less ideological orientation; and this period also witnessed more Chinese state-owned enterprises going out to invest in Latin America. 2010-2019 marked the further development of Latin American relations. This paper contributes to the literature of diplomacy and health assistance to Latin America and highlights the importance of foreign aid and health assistance in sealing bilateral diplomatic relations.

Keywords: Broad Spectrum Assistance, China, Latin America, bilateral relations.

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227 A Comparison of the Sum of Squares in Linear and Partial Linear Regression Models

Authors: Dursun Aydın

Abstract:

In this paper, estimation of the linear regression model is made by ordinary least squares method and the partially linear regression model is estimated by penalized least squares method using smoothing spline. Then, it is investigated that differences and similarity in the sum of squares related for linear regression and partial linear regression models (semi-parametric regression models). It is denoted that the sum of squares in linear regression is reduced to sum of squares in partial linear regression models. Furthermore, we indicated that various sums of squares in the linear regression are similar to different deviance statements in partial linear regression. In addition to, coefficient of the determination derived in linear regression model is easily generalized to coefficient of the determination of the partial linear regression model. For this aim, it is made two different applications. A simulated and a real data set are considered to prove the claim mentioned here. In this way, this study is supported with a simulation and a real data example.

Keywords: Partial Linear Regression Model, Linear RegressionModel, Residuals, Deviance, Smoothing Spline.

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226 Constitutionalisation and Judicial Protection of Social Rights - An Approach to Latin American Case

Authors: German Lopez Daza

Abstract:

Latin America is probably the region with greater social inequality, contrary to the amount of rights enshrined in their constitutions. In the last decade of the twentieth century, the area resulted in significant changes to democratization and constitutional changes. Through low-key public policy, political leaders activated participation in the culture of human rights. The struggle for social rights in Latin America has been a constant regulation. His consecration at the constitutional level has chained search application. The constitutionalization and judicial protection of these rights have been crucial in countries like Argentina, Venezuela, Peru and Colombia. This paper presents an analytical view on the constitutionalization of social rights in the Latin American context and its justiciability.

Keywords: Socials rights, public policy, justiciability, judicial protection, Latin America.

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225 Least Squares Method Identification of Corona Current-Voltage Characteristics and Electromagnetic Field in Electrostatic Precipitator

Authors: H. Nouri, I. E. Achouri, A. Grimes, H. Ait Said, M. Aissou, Y. Zebboudj

Abstract:

This paper aims to analysis the behavior of DC corona discharge in wire-to-plate electrostatic precipitators (ESP). Currentvoltage curves are particularly analyzed. Experimental results show that discharge current is strongly affected by the applied voltage. The proposed method of current identification is to use the method of least squares. Least squares problems that of into two categories: linear or ordinary least squares and non-linear least squares, depending on whether or not the residuals are linear in all unknowns. The linear least-squares problem occurs in statistical regression analysis; it has a closed-form solution. A closed-form solution (or closed form expression) is any formula that can be evaluated in a finite number of standard operations. The non-linear problem has no closed-form solution and is usually solved by iterative.

Keywords: Electrostatic precipitator, current-voltage characteristics, Least Squares method, electric field, magnetic field.

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224 An Adaptive Least-squares Mixed Finite Element Method for Pseudo-parabolic Integro-differential Equations

Authors: Zilong Feng, Hong Li, Yang Liu, Siriguleng He

Abstract:

In this article, an adaptive least-squares mixed finite element method is studied for pseudo-parabolic integro-differential equations. The solutions of least-squares mixed weak formulation and mixed finite element are proved. A posteriori error estimator is constructed based on the least-squares functional and the posteriori errors are obtained.

Keywords: Pseudo-parabolic integro-differential equation, least squares mixed finite element method, adaptive method, a posteriori error estimates.

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223 Wavelet Based Identification of Second Order Linear System

Authors: Sudipta Majumdar, Harish Parthasarathy

Abstract:

In this paper, a wavelet based method is proposed to identify the constant coefficients of a second order linear system and is compared with the least squares method. The proposed method shows improved accuracy of parameter estimation as compared to the least squares method. Additionally, it has the advantage of smaller data requirement and storage requirement as compared to the least squares method.

Keywords: Least squares method, linear system, system identification, wavelet transform.

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222 An Iterative Method for the Least-squares Symmetric Solution of AXB+CYD=F and its Application

Authors: Minghui Wang

Abstract:

Based on the classical algorithm LSQR for solving (unconstrained) LS problem, an iterative method is proposed for the least-squares like-minimum-norm symmetric solution of AXB+CYD=E. As the application of this algorithm, an iterative method for the least-squares like-minimum-norm biymmetric solution of AXB=E is also obtained. Numerical results are reported that show the efficiency of the proposed methods.

Keywords: Matrix equation, bisymmetric matrix, least squares problem, like-minimum norm, iterative algorithm.

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221 Order Reduction by Least-Squares Methods about General Point ''a''

Authors: Integral square error, Least-squares, Markovparameters, Moment matching, Order reduction.

Abstract:

The concept of order reduction by least-squares moment matching and generalised least-squares methods has been extended about a general point ?a?, to obtain the reduced order models for linear, time-invariant dynamic systems. Some heuristic criteria have been employed for selecting the linear shift point ?a?, based upon the means (arithmetic, harmonic and geometric) of real parts of the poles of high order system. It is shown that the resultant model depends critically on the choice of linear shift point ?a?. The validity of the criteria is illustrated by solving a numerical example and the results are compared with the other existing techniques.

Keywords: Integral square error, Least-squares, Markovparameters, Moment matching, Order reduction.

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220 Extended Least Squares LS–SVM

Authors: József Valyon, Gábor Horváth

Abstract:

Among neural models the Support Vector Machine (SVM) solutions are attracting increasing attention, mostly because they eliminate certain crucial questions involved by neural network construction. The main drawback of standard SVM is its high computational complexity, therefore recently a new technique, the Least Squares SVM (LS–SVM) has been introduced. In this paper we present an extended view of the Least Squares Support Vector Regression (LS–SVR), which enables us to develop new formulations and algorithms to this regression technique. Based on manipulating the linear equation set -which embodies all information about the regression in the learning process- some new methods are introduced to simplify the formulations, speed up the calculations and/or provide better results.

Keywords: Function estimation, Least–Squares Support VectorMachines, Regression, System Modeling

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219 Completion Latin Square for Wavelength Routing

Authors: Ali Habiboghli, Rouhollah Mostafaei, Vasif Nabiyev

Abstract:

Optical network uses a tool for routing called Latin router. These routers use particular algorithms for routing. For example, we can refer to LDF algorithm that uses backtracking (one of CSP methods) for problem solving. In this paper, we proposed new approached for completion routing table (DRA&CRA algorithm) and compare with pervious proposed ways and showed numbers of backtracking, blocking and run time for DRA algorithm less than LDF and CRA algorithm.

Keywords: Latin Router, Constraint Satisfaction Problem, Wavelength Routing.

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218 Relationship between Sums of Squares in Linear Regression and Semi-parametric Regression

Authors: Dursun Aydın, Bilgin Senel

Abstract:

In this paper, the sum of squares in linear regression is reduced to sum of squares in semi-parametric regression. We indicated that different sums of squares in the linear regression are similar to various deviance statements in semi-parametric regression. In addition to, coefficient of the determination derived in linear regression model is easily generalized to coefficient of the determination of the semi-parametric regression model. Then, it is made an application in order to support the theory of the linear regression and semi-parametric regression. In this way, study is supported with a simulated data example.

Keywords: Semi-parametric regression, Penalized LeastSquares, Residuals, Deviance, Smoothing Spline.

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217 Using of Latin Router for Routing Wavelength with Configuration Algorithm

Authors: A. Habiboghli, R. Mostafaei, M. R.Meybodi

Abstract:

Optical network uses a tool for routing which is called Latin router. These routers use particular algorithms for routing. In this paper, we present algorithm for configuration of optical network that is optimized regarding previous algorithm. We show that by decreasing the number of hops for source-destination in lightpath number of satisfied request is less. Also we had shown that more than single-hop lightpath relating single-hop lightpath is better.

Keywords: Latin Router, Constraint Satisfied, Wavelength, Optical Network

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216 Public Squares and Their Potential for Social Interactions: A Case Study of Historical Public Squares in Tehran

Authors: Asma Mehan

Abstract:

Under the thrust of technological changes, population growth and vehicular traffic, Iranian historical squares have lost their significance and they are no longer the main social nodes of the society. This research focuses on how historical public squares can inspire designers to enhance social interactions among citizens in Iranian urban context. Moreover, the recent master plan of Tehran demonstrates the lack of public spaces designed for the purpose of people’s social gatherings. For filling this gap, first the current situation of 7 selected primary historical public squares in Tehran including Sabze Meydan, Arg, Topkhaneh, Baherstan, Mokhber-al-dole, Rah Ahan and Hassan Abad have been compared. Later, the influencing elements on social interactions of the public squares such as subjective factors (human relationships and memories) and objective factors (natural and built environment) have been investigated. As a conclusion, some strategies are proposed for improving social interactions in historical public squares like; holding cultural, national, athletic and religious events, defining different and new functions in public squares’ surrounding, increasing pedestrian routs, reviving the collective memory, demonstrating the historical importance of square, eliminating visual obstacles across the square, organization the natural elements of the square, appropriate pavement for social activities. Finally, it is argued that the combination of all influencing factors which are: human interactions, natural elements and built environment criteria will lead to enhance the historical public squares’ potential for social interaction.

Keywords: Historical Square, Iranian Public Square, Social Interaction, Tehran.

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215 Short Time Identification of Feed Drive Systems using Nonlinear Least Squares Method

Authors: M.G.A. Nassef, Linghan Li, C. Schenck, B. Kuhfuss

Abstract:

Design and modeling of nonlinear systems require the knowledge of all inside acting parameters and effects. An empirical alternative is to identify the system-s transfer function from input and output data as a black box model. This paper presents a procedure using least squares algorithm for the identification of a feed drive system coefficients in time domain using a reduced model based on windowed input and output data. The command and response of the axis are first measured in the first 4 ms, and then least squares are applied to predict the transfer function coefficients for this displacement segment. From the identified coefficients, the next command response segments are estimated. The obtained results reveal a considerable potential of least squares method to identify the system-s time-based coefficients and predict accurately the command response as compared to measurements.

Keywords: feed drive systems, least squares algorithm, onlineparameter identification, short time window

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214 Recursive Least Squares Adaptive Filter a better ISI Compensator

Authors: O. P. Sharma, V. Janyani, S. Sancheti

Abstract:

Inter-symbol interference if not taken care off may cause severe error at the receiver and the detection of signal becomes difficult. An adaptive equalizer employing Recursive Least Squares algorithm can be a good compensation for the ISI problem. In this paper performance of communication link in presence of Least Mean Square and Recursive Least Squares equalizer algorithm is analyzed. A Model of communication system having Quadrature amplitude modulation and Rician fading channel is implemented using MATLAB communication block set. Bit error rate and number of errors is evaluated for RLS and LMS equalizer algorithm, due to change in Signal to Noise Ratio (SNR) and fading component gain in Rician fading Channel.

Keywords: Least mean square (LMS), Recursive least squares(RLS), Adaptive equalization, Bit error rate (BER), Rician fading channel, Quadrature Amplitude Modulation (QAM), Signal to noiseratio (SNR).

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213 Gauss-Seidel Iterative Methods for Rank Deficient Least Squares Problems

Authors: Davod Khojasteh Salkuyeh, Sayyed Hasan Azizi

Abstract:

We study the semiconvergence of Gauss-Seidel iterative methods for the least squares solution of minimal norm of rank deficient linear systems of equations. Necessary and sufficient conditions for the semiconvergence of the Gauss-Seidel iterative method are given. We also show that if the linear system of equations is consistent, then the proposed methods with a zero vector as an initial guess converge in one iteration. Some numerical results are given to illustrate the theoretical results.

Keywords: rank deficient least squares problems, AOR iterativemethod, Gauss-Seidel iterative method, semiconvergence.

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212 Online Estimation of Clutch Drag Torque in Wet Dual Clutch Transmission Based on Recursive Least Squares

Authors: Hongkui Li, Tongli Lu , Jianwu Zhang

Abstract:

This paper focuses on developing an estimation method of clutch drag torque in wet DCT. The modelling of clutch drag torque is investigated. As the main factor affecting the clutch drag torque, dynamic viscosity of oil is discussed. The paper proposes an estimation method of clutch drag torque based on recursive least squares by utilizing the dynamic equations of gear shifting synchronization process. The results demonstrate that the estimation method has good accuracy and efficiency.

Keywords: Clutch drag torque, wet DCT, dynamic viscosity, recursive least squares.

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211 Electric Load Forecasting Using Genetic Based Algorithm, Optimal Filter Estimator and Least Error Squares Technique: Comparative Study

Authors: Khaled M. EL-Naggar, Khaled A. AL-Rumaih

Abstract:

This paper presents performance comparison of three estimation techniques used for peak load forecasting in power systems. The three optimum estimation techniques are, genetic algorithms (GA), least error squares (LS) and, least absolute value filtering (LAVF). The problem is formulated as an estimation problem. Different forecasting models are considered. Actual recorded data is used to perform the study. The performance of the above three optimal estimation techniques is examined. Advantages of each algorithms are reported and discussed.

Keywords: Forecasting, Least error squares, Least absolute Value, Genetic algorithms

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210 A Study on the Least Squares Reduced Parameter Approximation of FIR Digital Filters

Authors: S. Seyedtabaii, E. Seyedtabaii

Abstract:

Rounding of coefficients is a common practice in hardware implementation of digital filters. Where some coefficients are very close to zero or one, as assumed in this paper, this rounding action also leads to some computation reduction. Furthermore, if the discarded coefficient is of high order, a reduced order filter is obtained, otherwise the order does not change but computation is reduced. In this paper, the Least Squares approximation to rounded (or discarded) coefficient FIR filter is investigated. The result also succinctly extended to general type of FIR filters.

Keywords: Digital filter, filter approximation, least squares, model order reduction.

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209 Variogram Fitting Based on the Wilcoxon Norm

Authors: Hazem Al-Mofleh, John Daniels, Joseph McKean

Abstract:

Within geostatistics research, effective estimation of the variogram points has been examined, particularly in developing robust alternatives. The parametric fit of these variogram points which eventually defines the kriging weights, however, has not received the same attention from a robust perspective. This paper proposes the use of the non-linear Wilcoxon norm over weighted non-linear least squares as a robust variogram fitting alternative. First, we introduce the concept of variogram estimation and fitting. Then, as an alternative to non-linear weighted least squares, we discuss the non-linear Wilcoxon estimator. Next, the robustness properties of the non-linear Wilcoxon are demonstrated using a contaminated spatial data set. Finally, under simulated conditions, increasing levels of contaminated spatial processes have their variograms points estimated and fit. In the fitting of these variogram points, both non-linear Weighted Least Squares and non-linear Wilcoxon fits are examined for efficiency. At all levels of contamination (including 0%), using a robust estimation and robust fitting procedure, the non-weighted Wilcoxon outperforms weighted Least Squares.

Keywords: Non-Linear Wilcoxon, robust estimation, Variogram estimation.

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208 Hybrid Artificial Bee Colony and Least Squares Method for Rule-Based Systems Learning

Authors: Ahcene Habbi, Yassine Boudouaoui

Abstract:

This paper deals with the problem of automatic rule generation for fuzzy systems design. The proposed approach is based on hybrid artificial bee colony (ABC) optimization and weighted least squares (LS) method and aims to find the structure and parameters of fuzzy systems simultaneously. More precisely, two ABC based fuzzy modeling strategies are presented and compared. The first strategy uses global optimization to learn fuzzy models, the second one hybridizes ABC and weighted least squares estimate method. The performances of the proposed ABC and ABC-LS fuzzy modeling strategies are evaluated on complex modeling problems and compared to other advanced modeling methods.

Keywords: Automatic design, learning, fuzzy rules, hybrid, swarm optimization.

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207 A Modified Genetic Based Technique for Solving the Power System State Estimation Problem

Authors: A. A. Hossam-Eldin, E. N. Abdallah, M. S. El-Nozahy

Abstract:

Power system state estimation is the process of calculating a reliable estimate of the power system state vector composed of bus voltages' angles and magnitudes from telemetered measurements on the system. This estimate of the state vector provides the description of the system necessary for the operation and security monitoring. Many methods are described in the literature for solving the state estimation problem, the most important of which are the classical weighted least squares method and the nondeterministic genetic based method; however both showed drawbacks. In this paper a modified version of the genetic algorithm power system state estimation is introduced, Sensitivity of the proposed algorithm to genetic operators is discussed, the algorithm is applied to case studies and finally it is compared with the classical weighted least squares method formulation.

Keywords: Genetic algorithms, ill-conditioning, state estimation, weighted least squares.

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206 Innovation Trends in Latin America Countries

Authors: José Carlos Rodríguez, Mario Gómez

Abstract:

This paper analyzes innovation trends in Latin America countries by means of the number of patent applications filed by residents and non residents during the period 1965 to 2012. Making use of patent data released by the World Intellectual Property Organization (WIPO), we search for the presence of multiple structural changes in patent application series in Argentina, Brazil Chile, and Mexico. These changes may suggest that firms’ innovative activity has been modified as a result of implementing a particular science, technology and innovation (STI) policy. Accordingly, the new regulations implemented in these countries during 1980s and 1990s have influenced their intellectual property regimes. The question conducting this research is thus how STI policies in these countries have affected their innovation activity? The results achieved in this research confirm the existence of multiple structural changes in the series of patent applications resulting from STI policies implemented in these countries.

Keywords: Econometric methods, innovation activity, Latin America countries, patents, science, technology and innovation (STI) policy.

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205 Short-Term Electric Load Forecasting Using Multiple Gaussian Process Models

Authors: Tomohiro Hachino, Hitoshi Takata, Seiji Fukushima, Yasutaka Igarashi

Abstract:

This paper presents a Gaussian process model-based short-term electric load forecasting. The Gaussian process model is a nonparametric model and the output of the model has Gaussian distribution with mean and variance. The multiple Gaussian process models as every hour ahead predictors are used to forecast future electric load demands up to 24 hours ahead in accordance with the direct forecasting approach. The separable least-squares approach that combines the linear least-squares method and genetic algorithm is applied to train these Gaussian process models. Simulation results are shown to demonstrate the effectiveness of the proposed electric load forecasting.

Keywords: Direct method, electric load forecasting, Gaussian process model, genetic algorithm, separable least-squares method.

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