With the significant growth of social media, individuals and organizations are increasingly using public opinion in these media to make their own decisions. The purpose of Sentiment Analysis is to automatically extract peoplechr('39')s emotions from these social networks. Social networks related to financial markets, including stock markets, have recently attracted the attention of many individuals and organizations. People on these social networks share their opinions and ideas about each share in the form of a post or tweet. In fact, sentiment analysis in this area is measuring peoplechr('39')s attitudes toward each share. One of the basic approaches in automatic analysis of emotions is lexicon-based methods. Most conventional lexicon is manually extracted, which is a very difficult and costly process. In this article, a new method for extracting a lexicon automatically in the field of stock social networks is proposed. A special feature of these networks is the availability of price information per share. Taking into account the price information of the share on the day of tweeting for that share, we extracted lexicon to improve the quality of opinion mining in these social networks. To evaluate the lexicon produced using the proposed method, we compared it with the Persian version of the SentiStrength lexicon, which is designed for general purpose. Experimental results show a 20% improvement in accuracy compared to the use of general lexicon.

Purpose: The purpose of this study is to present a cranifacial growth model using anthropometry based on changes observed in the human face.Materials and Methods: This cross sectional analytical study was conducted randomly on 45 pepole, with normal face patterns.Facial and cranial ratios were measured and compared. Data was analyzed by SPSS software. The regression line and the growth coefficient were determined for each Parameter. Finally, the mean values of these parameters were determined. Facial growth. pattern was drawn on the basis of on the growth parameters. A anthropometric ratios were obtained on the basis of facial landmark.Results: This research presents cranifacial growth model for young faces (2-18-years-old) using anthropometry based on changes observed in the human face that can be used as a method for growth parameters calculation.This model can also predict tailored face changes with the lapse of time.Conclusion: This model can be used for face recognition as well, on the other hand the results of this research can be used in medical professions such as maxillofacial surgery, growth and development studies, plastic surgery, bioengineering and non-medical fields such as shoe-making and eye glasses industries.

Proper positioning of the blank in the sheet metal forming dies is very important. An error in the initial positioning can lead to the production of a defective part. The number and location of positioning gauges are very effective in positioning the part correctly. In the manual and traditional design of dies for forming large sheet metal parts, two positioners are usually used to position the sheet at each edge, therefore eight gauges are used in the four directions of the sheet, some of which do not seem to be necessary. In the present study, by establishing a relationship between Catia and Abaqus softwares and with the help of optimization methods, an integrated software system has been created that is able to automatically perform finite element analyzes and make changes in the input file according to the output of each analysis and perform the next analysis. At each stage, for a specific arrangement of gauges, the amount of deviation of the sheet during placement and forming is examined, which should not be more than the allowable limit. Applying changes to the input parameters according to the optimization algorithm and performing subsequent analyzes will continue until the problem converges to the best answer that suggests the arrangement of the positioning levels. To compare the results of this system with the traditional design, two examples are presented. The results show that with a smaller number of gauges than the traditional method, the blank can be positioned correctly and accurately in the die.

Automatic image captioning is a challenging task in computer vision and aims to generate computer-understandable descriptions for images. Employing convolutional neural networks (CNN) has a key role in image caption generation. However, during the process of generating descriptions for an image, there are two major challenges for CNN, such as: they do not consider the relationships and spatial hierarchical structures between the objects in the image, and the lack of resistance against rotational changes of the images. In order to solve these challenges, this paper presents an improved capsule network to describe image content using natural language processing by considering the relations between the objects . A capsule contains a set of neurons that consider the parameters of the state of objects in the image, such as size, direction, scale, and relationships of objects to each other. These capsules have a special focus on extracting meaningful features for use in the process of generating relevant descriptions for a given set of images. Qualitative tests on the MS-COCO dataset using the capsule network and ELMo embedding technique have resulted in 2-5% improvement in the evaluated metrics compared to existing image captioning models.

Nuclear level density is one of the most important concepts in nuclear physics; basically, it is the key in dealing with nuclear statistical problems. This quantity plays an essential role in the statistical calculation of reactor physics, astrophysics, researches in the average energy of heavy-ion collision and calculations related to neutron evaporation and other applications. This quantity can be calculated analytically by the partition function method and saddle point conditions. Nuclear level density parameter is an important parameter in the calculation of nuclear level density. In this study, this parameter was calculated according to the way in which the limited size of nucleus, continuous states, layer effects, temperature dependence of effective mass related to frequency and momentum and the change of these effects with temperature were considered. To this end, improved Thomas-Fermi approximation as a function of temperature was used. Also, by using this approximation, for continuous effects in the zero temperature, the nuclear level density parameter was calculated as a function of the mass number.