Search results for: variable point spread function

Authors: Osama A. Omer, Amal Hamed

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Successful blind image Super-Resolution algorithms require the exact estimation of the Point Spread Function (PSF). In the absence of any prior information about the imagery system and the true image; this estimation is normally done by trial and error experimentation until an acceptable restored image quality is obtained. Multi-frame blind Super-Resolution algorithms often have disadvantages of slow convergence and sensitiveness to complex noises. This paper presents a Super-Resolution image reconstruction algorithm based on estimation of the PSF that yields the optimum restored image quality. The estimation of PSF is performed by the knife-edge method and it is implemented by measuring spreading of the edges in the reproduced HR image itself during the reconstruction process. The proposed image reconstruction approach is using L1 norm minimization and robust regularization based on a bilateral prior to deal with different data and noise models. A series of experiment results show that the proposed method can outperform other previous work robustly and efficiently.

Keywords: blind, PSF, super-resolution, knife-edge, blurring, bilateral, L1 norm

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Authors: Madhu Jain, Rakesh Kumar Meena

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This paper investigates a finite M/G/1 fault tolerant multi-component machining system. The system incorporates the features such as standby support, threshold recovery and imperfect coverage make the study closer to real time systems. The performance prediction of M/G/1 fault tolerant system is carried out using recursive approach by treating remaining service time as a supplementary variable. The numerical results are presented to illustrate the computational tractability of analytical results by taking three different service time distributions viz. exponential, 3-stage Erlang and deterministic. Moreover, the cost function is constructed to determine the optimal choice of system descriptors to upgrading the system.

Keywords: fault tolerant, machine repair, threshold recovery policy, imperfect coverage, supplementary variable technique

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Authors: Wenhao Lan, Ning Li, Qiang Tong

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To improve the registration accuracy of a source point cloud and template point cloud when the initial relative deflection angle is too large, a PointNetLK algorithm combined with an oriented bounding box (PointNetLK-OBB) is proposed. In this algorithm, the OBB of a 3D point cloud is used to represent the macro feature of source and template point clouds. Under the guidance of the iterative closest point algorithm, the OBB of the source and template point clouds is aligned, and a mirror symmetry effect is produced between them. According to the fitting degree of the source and template point clouds, the mirror symmetry plane is detected, and the optimal rotation and translation of the source point cloud is obtained to complete the 3D point cloud registration task. To verify the effectiveness of the proposed algorithm, a comparative experiment was performed using the publicly available ModelNet40 dataset. The experimental results demonstrate that, compared with PointNetLK, PointNetLK-OBB improves the registration accuracy of the source and template point clouds when the initial relative deflection angle is too large, and the sensitivity of the initial relative position between the source point cloud and template point cloud is reduced. The primary contribution of this paper is the use of PointNetLK to avoid the non-convex problem of traditional point cloud registration and leveraging the regularity of the OBB to avoid the local optimization problem in the PointNetLK context.

Keywords: mirror symmetry, oriented bounding box, point cloud registration, PointNetLK-OBB

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Authors: Priya Kedia, Kiranmoy Das

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There is a rich literature on variable selection in regression setting. However, most of these methods assume normality for the response variable under consideration for implementing the methodology and establishing the statistical properties of the estimates. In many real applications, the distribution for the response variable may be non-Gaussian, and one might be interested in finding the best subset of covariates at some predetermined quantile level. We develop dynamic Bayesian approach for variable selection in quantile regression framework. We use a zero-inflated mixture prior for the regression coefficients, and consider the asymmetric Laplace distribution for the response variable for modeling different quantiles of its distribution. An efficient Gibbs sampler is developed for our computation. Our proposed approach is assessed through extensive simulation studies, and real application of the proposed approach is also illustrated. We consider the data from health and retirement study conducted by the University of Michigan, and select the important predictors when the outcome of interest is out-of-pocket medical cost, which is considered as an important measure for financial risk. Our analysis finds important predictors at different quantiles of the outcome, and thus enhance our understanding on the effects of different predictors on the out-of-pocket medical cost.

Keywords: variable selection, quantile regression, Gibbs sampler, asymmetric Laplace distribution

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Authors: Yasmin Tantawi, Mary Beth Rosson

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In response to the dearth of information about emoji use for different purposes in different settings, this paper investigates the paralinguistic function of emojis within Twitter communication in the United States. To conduct this investigation, the Twitter feeds from 16 population centers spread throughout the United States were collected from the Twitter public API. One hundred tweets were collected from each population center, totaling to 1,600 tweets. Tweets containing emojis were next extracted using the “emot” Python package; these were then analyzed via the IBM Watson API Natural Language Understanding module to identify the topics discussed. A manual content analysis was then conducted to ascertain the paralinguistic and emotional features of the emojis used in these tweets. We present our characterization of emoji usage in Twitter and discuss implications for the design of Twitter and other text-based communication tools.

Keywords: computer-mediated communication, content analysis, paralinguistics, sociology

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Authors: Ehsan Motamedian

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Finding all optimal flux distributions of a metabolic model is an important challenge in systems biology. In this paper, a new algorithm is introduced to identify all alternate optimal solutions of a large scale metabolic network. The algorithm reduces the model to decrease computations for finding optimal solutions. The algorithm was implemented on the Escherichia coli metabolic model to find all optimal solutions for lactate and acetate production. There were more optimal flux distributions when acetate production was optimized. The model was reduced from 1076 to 80 variable fluxes for lactate while it was reduced to 91 variable fluxes for acetate. These 11 more variable fluxes resulted in about three times more optimal flux distributions. Variable fluxes were from 12 various metabolic pathways and most of them belonged to nucleotide salvage and extra cellular transport pathways.

Keywords: flux variability, metabolic network, mixed-integer linear programming, multiple optimal solutions

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Authors: Ofosuhene O. Apenteng, Noor Azina Ismail

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Recently tourism is a major foreign exchange earner in the World. In this paper, we propose the mathematical model to study the impact of tourists on the spread of HIV incidences using compartmental differential equation models. Simulation studies of reproduction number are used to demonstrate new insights on the spread of HIV disease. The periodogram analysis of a time series was used to determine the speed at which the disease is spread. The results indicate that with the persistent flow of tourism into a country, the disease status has increased the epidemic rate. The result suggests that the government must put more control on illegal prostitution, unprotected sexual activity as well as to emphasis on prevention policies that include the safe sexual activity through the campaign by the tourism board.

Keywords: HIV/AIDS, mathematical transmission modeling, tourists, stability, simulation

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Authors: Jing Zhang, Jie Chen

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In this paper, we deal with the optimal I/O point location in an automated parking system. In this system, the S/R machine (storage and retrieve machine) travels independently in vertical and horizontal directions. Based on the characteristics of the parking system and the basic principle of AS/RS system (Automated Storage and Retrieval System), we obtain the continuous model in units of time. For the single command cycle using the randomized storage policy, we calculate the probability density function for the system travel time and thus we develop the travel time model. And we confirm that the travel time model shows a good performance by comparing with discrete case. Finally in this part, we establish the optimal model by minimizing the expected travel time model and it is shown that the optimal location of the I/O point is located at the middle of the left-hand above corner.

Keywords: parking system, optimal location, response time, S/R machine

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Authors: Wu Sa, Zhang Qian, Li Qi, Wang Ye

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Currently in humidity tests having not put the Dew point temperature as a control parameter, this paper selects wet and dry bulb thermometer to measure the vapor pressure, and introduces several the saturation vapor pressure formulas easily calculated on the controller. Then establish the Dew point temperature calculation model to obtain the relationship between the Dew point temperature and vapor pressure. Finally check through the 100 groups of sample in the range of 0-100 ℃ from "Psychrometric handbook", find that the average error is small. This formula can be applied to calculate the Dew point temperature in the humidity test.

Keywords: dew point temperature, psychrometric handbook, saturation vapor pressure, wet and dry bulb thermometer

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Authors: Arvind Kumar, Manoj Kumar, Dattatraya H. Nagaraj, Amanpreet Singh, Jayanthi Prattapati

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The purpose of this paper is to study and compare two maximum power point tracking (MPPT) algorithms in a photovoltaic simulation system and also show a simulation study of maximum power point tracking (MPPT) for photovoltaic systems using perturb and observe algorithm and Incremental conductance algorithm. Maximum power point tracking (MPPT) plays an important role in photovoltaic systems because it maximize the power output from a PV system for a given set of conditions, and therefore maximize the array efficiency and minimize the overall system cost. Since the maximum power point (MPP) varies, based on the irradiation and cell temperature, appropriate algorithms must be utilized to track the (MPP) and maintain the operation of the system in it. MATLAB/Simulink is used to establish a model of photovoltaic system with (MPPT) function. This system is developed by combining the models established of solar PV module and DC-DC Boost converter. The system is simulated under different climate conditions. Simulation results show that the photovoltaic simulation system can track the maximum power point accurately.

Keywords: incremental conductance algorithm, perturb and observe algorithm, photovoltaic system, simulation results

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Authors: E. Popov, N. Yorino, Y. Zoka, Y. Sasaki, H. Sugihara

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This paper discusses the performance of critical trajectory method (CTrj) for power system transient stability analysis under various loading settings and heavy fault condition. The method obtains Controlling Unstable Equilibrium Point (CUEP) which is essential for estimation of power system stability margins. The CUEP is computed by applying the CTrjto the boundary controlling unstable equilibrium point (BCU) method. The Proposed method computes a trajectory on the stability boundary that starts from the exit point and reaches CUEP under certain assumptions. The robustness and effectiveness of the method are demonstrated via six power system models and five loading conditions. As benchmark is used conventional simulation method whereas the performance is compared with and BCU Shadowing method.

Keywords: power system, transient stability, critical trajectory method, energy function method

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Authors: Maryam Moosavi, Hadi Khatibzadeh

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The main purpose of this paper is to study the proximal point algorithm for quasi-nonexpansive mappings in Hadamard spaces. △-convergence and strong convergence of cyclic resolvents for a finite family of quasi-nonexpansive mappings one to a fixed point of the mappings are established

Keywords: Fixed point, Hadamard space, Proximal point algorithm, Quasi-nonexpansive sequence of mappings, Resolvent

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Authors: Nattapong Techarattanased

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The purposes of this research are to make comparisons in respect of the behaviors on the use of the services of metered taxi classified by the demographic factor and to study the influence of the recognition on service quality having the effect on usage behaviors of metered taxi services of consumers in Bangkok Metropolitan Areas. The samples used in this research are 400 metered taxi service users in Bangkok Metropolitan Areas and use a questionnaire as the tool for collecting the data. Analysis statistics is mean and multiple regression analysis. Results of the research revealed that the consumers recognize the overall quality of services in each aspect include tangible aspects of the service, responses to customers, assurance on the confidence, understanding and knowing of customers which is rated at the moderate level except the aspect of the assurance on the confidence and trustworthiness which are rated at a high level. For the result of a hypothetical test, it is found that the quality in providing the services on the aspect of the assurance given to the customers has the effect on the usage behaviors of metered taxi services and the aspect of the frequency on the use of the services per month which in this connection. Such variable can forecast at one point nine percent (1.9%). In addition, quality in providing the services and the aspect of the responses to customers have the effect on the behaviors on the use of metered taxi services on the aspect of the expenses on the use of services per month which in this connection, such variable can forecast at two point one percent (2.1%).

Keywords: consumer behavior, metered taxi service, satisfaction, service quality

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Authors: Hong-Ming Chen

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This work considers the resolution of the Hull and White interest rate model with the jump process. A deterministic process is adopted to model the random behavior of interest rate variation as deterministic perturbations, which is depending on the time t. The Brownian motion and jumps uncertainty are denoted as the integral functions piecewise constant function w(t) and point function θ(t). It shows that the interest rate function and the yield function of the Hull and White interest rate model with jump process can be obtained by solving a nonlinear semi-infinite programming problem. A relaxed cutting plane algorithm is then proposed for solving the resulting optimization problem. The method is calibrated for the U.S. treasury securities at 3-month data and is used to analyze several effects on interest rate prices, including interest rate variability, and the negative correlation between stock returns and interest rates. The numerical results illustrate that our approach essentially generates the yield functions with minimal fitting errors and small oscillation.

Keywords: optimization, interest rate model, jump process, deterministic

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Authors: Ishapathik Das

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The purpose of this article is to find a method of comparing designs for ordinal regression models using quantile dispersion graphs in the presence of linear predictor misspecification. The true relationship between response variable and the corresponding control variables are usually unknown. Experimenter assumes certain form of the linear predictor of the ordinal regression models. The assumed form of the linear predictor may not be correct always. Thus, the maximum likelihood estimates (MLE) of the unknown parameters of the model may be biased due to misspecification of the linear predictor. In this article, the uncertainty in the linear predictor is represented by an unknown function. An algorithm is provided to estimate the unknown function at the design points where observations are available. The unknown function is estimated at all points in the design region using multivariate parametric kriging. The comparison of the designs are based on a scalar valued function of the mean squared error of prediction (MSEP) matrix, which incorporates both variance and bias of the prediction caused by the misspecification in the linear predictor. The designs are compared using quantile dispersion graphs approach. The graphs also visually depict the robustness of the designs on the changes in the parameter values. Numerical examples are presented to illustrate the proposed methodology.

Keywords: model misspecification, multivariate kriging, multivariate logistic link, ordinal response models, quantile dispersion graphs

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Authors: Tamara Slišković, Tomislav Sekur

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This manuscript examines factors that affect demand and supply of the housing market in Croatia. The period from the beginning of this century, until 2008, was characterized by a strong expansion of construction, housing and real estate market in general. Demand for residential units was expanding, and this was supported by favorable lending conditions of banks. Indicators on the supply side, such as the number of newly built houses and the construction volume index were also increasing. Rapid growth of demand, along with the somewhat slower supply growth, led to the situation in which new apartments were sold before the completion of residential buildings. This resulted in a rise of housing price which was indication of a clear link between the housing prices with the supply and demand in the housing market. However, after 2008 general economic conditions in Croatia worsened and demand for housing has fallen dramatically, while supply descended at much slower pace. Given that there is a gap between supply and demand, it can be concluded that the housing market in Croatia is in imbalance. Such trend is accompanied by a relatively small decrease in housing price. The final result of such movements is the large number of unsold housing units at relatively high price levels. For this reason, it can be argued that housing prices are sticky and that, consequently, the price level in the aftermath of a crisis does not correspond to the discrepancy between supply and demand on the Croatian housing market. The degree of rigidity of the housing price can be determined by inclusion of the housing price as the explanatory variable in the housing demand function. Other independent variables are demographic variable (e.g. the number of households), the interest rate on housing loans, households' disposable income and rent. The equilibrium price is reached when the demand for housing equals its supply, and the speed of adjustment of actual prices to equilibrium prices reveals the extent to which the prices are rigid. The latter requires inclusion of the housing prices with time lag as an independent variable in estimating demand function. We also observe the supply side of the housing market, in order to explain to what extent housing prices explain the movement of new construction activity, and other variables that describe the supply. In this context, we test whether new construction on the Croatian market is dependent on current prices or prices with a time lag. Number of dwellings is used to approximate new construction (flow variable), while the housing prices (current or lagged), quantity of dwellings in the previous period (stock variable) and a series of costs related to new construction are independent variables. We conclude that the key reason for the imbalance in the Croatian housing market should be sought in the relative relationship of price elasticities of supply and demand.

Keywords: Croatian housing market, economic crisis, housing prices, supply imbalance, demand imbalance

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Authors: Lucy Novianti

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The purpose of this study is to determine the effect of corporate governance, ownership structure, and cash holdings on firm value, either direct or indirect through profitability as an intervening variable for non-financial companies listed on the Indonesia Stock Exchange during 2006 to 2014. Samples of 176 firms are chosen based on purposive sampling method. The results of this study conclude that profitability, the size of Audit Committee, audit quality, and cash flow have positive effects on firm value. This study also shows that the meeting frequency of the Board of Directors and free cash flow have negative effects on firm value. In addition, this study finds that the size of the Board of Directors, Independent Commissioner, and ownership structure do not have significant effects on firm value. In this study, the function of profitability as an intervening variable can only be done on the impact of the meeting frequency of the Board of Directors and cash flow on firm value. This study provides a reference for management in decision making concerning the application of corporate governance, cash holdings, and financial performance. Moreover, it can be used as additional information for investors in assessing the feasibility of an investment. Finally, it provides a suggestion for the government regarding the regulation of corporate governance.

Keywords: cash holdings, corporate governance, firm value, ownership structure, profitability

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Authors: Henni Mansour Abdelwaheb

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This study discusses the design of a bounded position/force feedback controller developed to ensure position and force tracking for bilateral teleoperation arms operating with variable delay, and actuator saturation. Also, an adaptive robust Radial Basis Function (RBF) neural network is used to estimate the environment torque. The parameters of the environment torque are then sent from the slave site to the master site as a non-power signal to avoid passivity problems. Moreover, a nonlinear function is applied to each controller term as a smooth saturation function, providing a bounded control signal and preserving the system’s actuators. Lastly, the Lyapunov approach demonstrates the global stability of the controlled system, and numerical experiment results further confirm the validity of the presented strategy.

Keywords: teleoperation manipulators system, time-varying delay, actuator saturation, adaptive robust rbf neural network approximation, uncertainties

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Authors: F. U. Rahman, R. Q. Zhang

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This work aims to develop a systematic numerical technique which can be easily extended to many-body problem. The Lippmann Schwinger equation (integral form of the Schrodinger wave equation) is solved for the nonrelativistic radial wave of hydrogen atom using iterative integration scheme. As the unknown wave function appears on both sides of the Lippmann Schwinger equation, therefore an approximate wave function is used in order to solve the equation. The Green’s function is obtained by the method of Laplace transform for the radial wave equation with excluded potential term. Using the Lippmann Schwinger equation, the product of approximate wave function, the Green’s function and the potential term is integrated iteratively. Finally, the wave function is normalized and plotted against the standard radial wave for comparison. The outcome wave function converges to the standard wave function with the increasing number of iteration. Results are verified for the first fifteen states of hydrogen atom. The method is efficient and consistent and can be applied to complex systems in future.

Keywords: Green’s function, hydrogen atom, Lippmann Schwinger equation, radial wave

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Authors: Amitha Puranik, V. S. Binu, Seena Biju

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Missing data is a common problem in spatial analysis especially at the aggregate level. Missing can either occur in covariate or in response variable or in both in a given location. Many missing data techniques are available to estimate the missing data values but not all of these methods can be applied on spatial data since the data are autocorrelated. Hence there is a need to develop a method that estimates the missing values in both response variable and covariates in spatial data by taking account of the spatial autocorrelation. The present study aims to develop a model to estimate the missing data points at the aggregate level in spatial data by accounting for (a) Spatial autocorrelation of the response variable (b) Spatial autocorrelation of covariates and (c) Correlation between covariates and the response variable. Estimating the missing values of spatial data requires a model that explicitly account for the spatial autocorrelation. The proposed model not only accounts for spatial autocorrelation but also utilizes the correlation that exists between covariates, within covariates and between a response variable and covariates. The precise estimation of the missing data points in spatial data will result in an increased precision of the estimated effects of independent variables on the response variable in spatial regression analysis.

Keywords: spatial regression, missing data estimation, spatial autocorrelation, simulation analysis

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Authors: Mohammad H. Ahmadi, Vahid Haghighatdoost

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Given a set of source locations for a group of friends, and a set of trip plans for each group member as a sequence of Categories-of-Interests (COIs) (e.g., restaurant), and finally a specific COI as a common destination that all group members will gather together, in Meeting Point Based on Trip Plans (MPTPs) queries our goal is to find a Point-of-Interest (POI) from different COIs, such that the aggregate travel distance for the group is minimized. In this work, we considered two cases for aggregate function as Sum and Max. For solving this query, we propose an efficient pruning technique for shrinking the search space. Our approach contains three steps. In the first step, it prunes the search space around the source locations. In the second step, it prunes the search space around the centroid of source locations. Finally, we compute the intersection of all pruned areas as the final refined search space. We prove that the POIs beyond the refined area cannot be part of optimal answer set. The paper also covers an extensive performance study of the proposed technique.

Keywords: meeting point, trip plans, road networks, spatial databases

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Authors: Nasser Mohamed Ramli, Mohamad Syafiq Mohamad

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Many types of controllers were applied on the continuous stirred tank reactor (CSTR) unit to control the temperature. In this research paper, Proportional-Integral-Derivative (PID) controller are compared with Fuzzy Logic controller for temperature control of CSTR. The control system for temperature non-isothermal of a CSTR will produce a stable response curve to its set point temperature. A mathematical model of a CSTR using the most general operating condition was developed through a set of differential equations into S-function using MATLAB. The reactor model and S-function are developed using m.file. After developing the S-function of CSTR model, User-Defined functions are used to link to SIMULINK file. Results that are obtained from simulation and temperature control were better when using Fuzzy logic control compared to PID control.

Keywords: CSTR, temperature, PID, fuzzy logic

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Authors: Michael Luc Andre, Célia Maintenant

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Theory of mind is a milestone in child development which allows children to understand that others could have different mental states than theirs. Understanding the developmental stages of theory of mind in children leaded researchers on two Connected research problems. In one hand, the link between executive function and theory of mind, and on the other hand, the relationship of theory of mind and syntax processing. These two lines of research involved a great literature, full of important results, despite certain level of disagreement between researchers. For a long time, these two research perspectives continue to grow up separately despite research conclusion suggesting that the three variables should implicate same developmental period. Indeed, our goal was to study the relation between theory of mind, executive function, and language via a unique research question. It supposed that between executive function and language, one of the two variables could play a critical role in the relationship between theory of mind and the other variable. Thus, 112 children aged between three and six years old were recruited for completing a receptive and an expressive vocabulary task, a syntax understanding task, a theory of mind task, and three executive function tasks (inhibition, cognitive flexibility and working memory). The results showed significant correlations between performance on theory of mind task and performance on executive function domain tasks, except for cognitive flexibility task. We also found significant correlations between success on theory of mind task and performance in all language tasks. Multiple regression analysis justified only syntax and general abilities of language as possible predictors of theory of mind performance in our preschool age children sample. The results were discussed in the perspective of a great role of language abilities in theory of mind development. We also discussed possible reasons that could explain the non-significance of executive domains in predicting theory of mind performance, and the meaning of our results for the literature.

Keywords: child development, executive function, general language, syntax, theory of mind

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Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

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In biomedical researches and randomized clinical trials, the most commonly interested outcomes are time-to-event so-called survival data. The importance of robust models in this context is to compare the effect of randomly controlled experimental groups that have a sense of causality. Causal estimation is the scientific concept of comparing the pragmatic effect of treatments conditional to the given covariates rather than assessing the simple association of response and predictors. Hence, the causal effect based semiparametric transformation model was proposed to estimate the effect of treatment with the presence of possibly time-varying covariates. Due to its high flexibility and robustness, the semiparametric transformation model which shall be applied in this paper has been given much more attention for estimation of a causal effect in modeling left-truncated and right censored survival data. Despite its wide applications and popularity in estimating unknown parameters, the maximum likelihood estimation technique is quite complex and burdensome in estimating unknown parameters and unspecified transformation function in the presence of possibly time-varying covariates. Thus, to ease the complexity we proposed the modified estimating equations. After intuitive estimation procedures, the consistency and asymptotic properties of the estimators were derived and the characteristics of the estimators in the finite sample performance of the proposed model were illustrated via simulation studies and Stanford heart transplant real data example. To sum up the study, the bias of covariates was adjusted via estimating the density function for truncation variable which was also incorporated in the model as a covariate in order to relax the independence assumption of failure time and truncation time. Moreover, the expectation-maximization (EM) algorithm was described for the estimation of iterative unknown parameters and unspecified transformation function. In addition, the causal effect was derived by the ratio of the cumulative hazard function of active and passive experiments after adjusting for bias raised in the model due to the truncation variable.

Keywords: causal estimation, EM algorithm, semiparametric transformation models, time-to-event outcomes, time-varying covariate

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Authors: Zhongzhi Hu, Jie Shen, Jiqiang Wang

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A high precision aeroengine model is needed when developing the engine control system. Compared with other main components, the axial compressor is the most challenging component to simulate. In this paper, a compressor map optimizing tool based on the introduction of a modifiable β function is developed for FWorks (FADEC Works). Three parameters (d density, f fitting coefficient, k₀ slope of the line β=0) are introduced to the β function to make it modifiable. The comparison of the traditional β function and the modifiable β function is carried out for a certain type of compressor. The interpolation errors show that both methods meet the modeling requirements, while the modifiable β function can predict compressor performance more accurately for some areas of the compressor map where the users are interested in.

Keywords: beta function, compressor map, interpolation error, map optimization tool

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Authors: Ramesh Chandra Patra, Ajay P. Gautam, Patitapaban Mohanty

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Headache disorders are one of the 10 most disabling conditions for men and women. Headache that originated from upper cervical spine and refereed to the one side of the head and/or face is known as cervicogenic headache (CH) which constitute15% to 20% among all the headaches. In our best knowledge manual therapy is often advocated for managing CH, but very little focus given on muscle system although it is a musculoskeletal disorder. In this study, 75 patients with CH were selected and divided into two groups Group A: Manual therapy and Group B: dry needling along with manual therapy group. Assessment was done using NPRS (0-10) for pain, wide spread pressure pain threshold using an algometer at the beginning and end of the study. There is a consistent reduction in pain and tenderness in both the group but significant improvement was shown in combined group. Outcome of the study has explored that the effectiveness of dry needling along with Mulligan is more beneficial in patients with cervicogenic headaches.

Keywords: cervicogenic headaches, dry needling, NPRS, pressure point threshold

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Authors: E. Tchandao Mangamana, V. Cariou, E. Vigneau, R. Glele Kakai, E. M. Qannari

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A new definition of a latent variable associated with a dataset makes it possible to propose variants of the PLS2 regression and the multi-block PLS (MB-PLS). We shall refer to these variants as Rd-PLS regression and Rd-MB-PLS respectively because they are inspired by both Redundancy analysis and PLS regression. Usually, a latent variable t associated with a dataset Z is defined as a linear combination of the variables of Z with the constraint that the length of the loading weights vector equals 1. Formally, t=Zw with ‖w‖=1. Denoting by Z' the transpose of Z, we define herein, a latent variable by t=ZZ’q with the constraint that the auxiliary variable q has a norm equal to 1. This new definition of a latent variable entails that, as previously, t is a linear combination of the variables in Z and, in addition, the loading vector w=Z’q is constrained to be a linear combination of the rows of Z. More importantly, t could be interpreted as a kind of projection of the auxiliary variable q onto the space generated by the variables in Z, since it is collinear to the first PLS1 component of q onto Z. Consider the situation in which we aim to predict a dataset Y from another dataset X. These two datasets relate to the same individuals and are assumed to be centered. Let us consider a latent variable u=YY’q to which we associate the variable t= XX’YY’q. Rd-PLS consists in seeking q (and therefore u and t) so that the covariance between t and u is maximum. The solution to this problem is straightforward and consists in setting q to the eigenvector of YY’XX’YY’ associated with the largest eigenvalue. For the determination of higher order components, we deflate X and Y with respect to the latent variable t. Extending Rd-PLS to the context of multi-block data is relatively easy. Starting from a latent variable u=YY’q, we consider its ‘projection’ on the space generated by the variables of each block Xk (k=1, ..., K) namely, tk= XkXk'YY’q. Thereafter, Rd-MB-PLS seeks q in order to maximize the average of the covariances of u with tk (k=1, ..., K). The solution to this problem is given by q, eigenvector of YY’XX’YY’, where X is the dataset obtained by horizontally merging datasets Xk (k=1, ..., K). For the determination of latent variables of order higher than 1, we use a deflation of Y and Xk with respect to the variable t= XX’YY’q. In the same vein, extending Rd-MB-PLS to the path modeling setting is straightforward. Methods are illustrated on the basis of case studies and performance of Rd-PLS and Rd-MB-PLS in terms of prediction is compared to that of PLS2 and MB-PLS.

Keywords: multiblock data analysis, partial least squares regression, path modeling, redundancy analysis

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Authors: Vipul M. Patel, Hemantkumar B. Mehta

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Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.

Keywords: ANN models, CLPHP, filling ratio, generalized regression, spread constant

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Authors: Ashwani Kumar Aggarwal

Abstract:

NIR Light is non-ionizing and can pass easily through living tissues such as breast without any harmful effects. Therefore, use of NIR light for imaging the biological tissue and to quantify its optical properties is a good choice over other invasive methods. Optical tomography involves two steps. One is the forward problem and the other is the reconstruction problem. The forward problem consists of finding the measurements of transmitted light through the tissue from source to detector, given the spatial distribution of absorption and scattering properties. The second step is the reconstruction problem. In X-ray tomography, there is standard method for reconstruction called filtered back projection method or the algebraic reconstruction methods. But this method cannot be applied as such, in optical tomography due to highly scattering nature of biological tissue. A hybrid algorithm for reconstruction has been implemented in this work which takes into account the highly scattered path taken by photons while back projecting the forward data obtained during Monte Carlo simulation. The reconstructed image suffers from blurring due to point spread function. This blurred reconstructed image has been enhanced using a digital filter which is optimal in mean square sense.

Keywords: least-squares optimization, filtering, tomography, laser interaction, light scattering

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Authors: Yasunori Kobori, Futoshi Fukaya, Takuya Arafune, Nobukazu Tsukiji, Nobukazu Takai, Haruo Kobayashi

Abstract:

This paper proposes an EMI spread spectrum technique to enable to set notch frequencies using pulse coding method for DC-DC switching converters of communication equipment. The notches in the spectrum of the switching pulses appear at the frequencies obtained from empirically derived equations with the proposed spread spectrum technique using the pulse coding methods, the PWM (Pulse Width Modulation) coding or the PCM (Pulse Cycle Modulation) coding. This technique would be useful for the switching converters in the communication equipment which receives standard radio waves, without being affected by noise from the switching converters. In our proposed technique, the notch frequencies in the spectrum depend on the pulse coding method. We have investigated this technique to apply to the switching converters and found that there is good relationship agreement between the notch frequencies and the empirical equations. The notch frequencies with the PWM coding is equal to the equation F=k/(WL-WS). With the PCM coding, that is equal to the equation F=k/(TL-TS).

Keywords: notch frequency, pulse coding, spread spectrum, switching converter

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