Image rectification is an essential part in most multi-view systems. It simplifies the stereo matching process by limiting the search path to horizontal and parallel lines. The main problem in conventional image rectification is complexity and mass computation load for calculation of calibration matrix, projection matrix and fundamental matrix. In this paper an efficient and confident method is presented to rectify stereo images based on the correspondence field (CF) that avoids the mentioned matrices. In general this algorithm is able to generate an image for any new camera position. Especially one can choose the new position in such a way that the virtual camera generates a rectified image. Both real and simulated stereo images are used to evaluate the proposed algorithm. SIFT algorithm is used to estimate how close is the generated image to original rectified one. Simulation results show the mean absolute error and standard deviation are about 0.25 and 0.26 pixels respectively and rectified image is independent of focal ratio.

Sentiment classification of opinions is a field of Natural Language Processing which has been considered in recent years by researchers due to popularity of Internet stores and the possibility of expressing opinions about sold goods or services. To train classifier models, we need labeled datasets, but as there are not rich labeled samples and as labeling is a difficult and time-consuming process, we must employ labeled samples of other domains. In this article, a new method for binary classification of opinions is proposed based on multi-domain transfer learning. The proposed method tries to adapt different domains by using Structural Correspondence Learning; and based on repetitive procedure of the boosting algorithm, a weight is assigned to classified samples of different domains and the class of each opinion is specified by merging these classifiers. Weighting the dataset samples to boost the process of classification based on the Adaboost algorithm and combining it with the Structural Corresponding Learning is the most important innovation of the current research. The Amazon dataset of four different domains, each one containing 1000 positive and 1000 negative opinions is used for training the proposed model. Accuracy measures of %89. 64, %93. 97, %92. 39 and %90. 17 are obtained for Electronics, DVD, Books and Kitchen domains, respectively. It illustrates that the proposed method is very effective compared with the similar methods.

This paper measures multidimensional poverty from 2004 to 2019. 13 ordinal categorical indicators in four dimensions of "economic welfare, " "housing, " "health, " and "education" are used and to determine the weight of the indicators, the method of multiple correspondence analysis (MAC) is used. Based on these weights, a composite poverty indicator is calculated. With five types of poverty lines, including union criterion, intersection criterion, 60% median, first three deciles, and the absolute poverty line, poverty indicators are obtained cross-sectionally and in time series by urban and rural areas. The results show that multidimensional poverty is higher in rural areas than in urban areas. The Compensating power of poverty is also higher in urban areas than in rural areas. This means that urban households can better compensate for deprivation in one dimension by another. In the 16 years under study, the poverty trend is a convex downward trend that has become almost horizontal in the last years. The study of poverty of the provinces also shows that the provinces of Sistan & Baluchestan and Mazandaran have the highest and lowest headcount ratio of the poverty, respectively.

Multiple Correspondence Analysis & Cluster Analysis (MCACA), firstly developed in this paper, extracts the main advantages of Multiple Correspondence Analysis and hierarchical cluster analysis, and unifies the R-and Q-mode cluster analysis of large data set. A systemic program to recognize the regional geochemical patterns is built up based on this method. With this program, the complex tasks for data interpretation can be achieved by simple processes, and important geochemical information can be displayed by a single diagram, i.e. the dendrogram. As a case study, the regional geochemical pattern recognition for Ashin sheet by scale of 1:100,000 in Isfahan province is introduced. The results show that many hidden geochemical patterns related to the lithologies, structures and etc. are revealed by the geochemical image, and that the main geochemical patterns are related with certain geological patterns. By finding contrasts between geochemical patterns and geological patterns, the MCACA results assist the geological mapping in this area. Stream sediment geochemical data obtained in Iran regional geochemical exploration provides useful information regarding geology and other factors, and the method described in this paper provides a new way to examine this type of resource.

In today’s extremely competitive markets it is crucial for companies to strategically position their brands, products and services relative to their competitors. With the emerging trend in internationalization of companies especially SME’s and the growing use of the Internet with this regard, great amount of attention has been turned to effective involvement of the Internet channel in the marketing mix of the companies. This has introduced a new term of market space (the Web) versus the traditional battleground of marketplace in which companies compete with each other. The growth of presence in the market space has been exponential, both in general and within specific industries.Thus bringing to attention the importance of Web presence and that it is crucial for companies to strategically regard competition in market space. It is important to understand that positioning on the Net is very different and requires its own set of strategies as part of the new marketing paradigm. This study goes towards addressing the need to understand and measure the nature of positioning of company Web sites on the Internet. The aim of the study is to introduce a statistical technique to compare the positioning of Web sites, in and across industries. With this regard a group of Web sites from the home appliances manufacturing industry was selected and the technique of correspondence analysis was applied to produce maps which can be studied and interpreted. The results indicated that either based on company strategies or accidentally, these Web sites are positioned differently and may follow or affect different marketing policies of their owners. At the end, the implications of this technique for management and how it can be used by new home appliance manufacturers or those who want to compare their sites with the ones of their competitors, in order to benchmark and/or revise their policies and strategies have been discussed.

Many tubular joints commonly found in offshore jacket structures are multi-planar. Investigating the effect of loaded out-of-plane braces on the values of the stress concentration factor (SCF) in offshore tubular joints has been the objective of numerous research works. However, due to the diversity of joint types and loading conditions, several quite important cases still exist that have not been studied thoroughly. Among them are internally ring-stiffened multi-planar XT-joints subjected to axial loading. In the present research, data extracted from the stress analysis of 81 finite element (FE) models, verified using experimental test results, was used to study the effects of geometrical parameters on the chord-side SCFs in multi-planar tubular XT-joints reinforced with internal ring stiffeners subjected to two types of axial loading. Parametric FE study was followed by a set of the nonlinear regression analyses to develop four new SCF parametric equations for the fatigue analysis and design of axially loaded multi-planar XT-joints reinforced with internal ring stiffeners.

I was asked to give a brief review of the black hole-string correspondence [1] as a warm-up for a longer SITP-group discussion of a recent paper by Chen, Maldacena, and Witten [2]. Here are my notes in written form.