The neoclassical growth MODEL is tested by use of panel DATA procedure in this research. In the econometric test, simoultanously time series and cross detection will be compared on the basis of panel DATA method through which their observed points increase and consequently the estimation efficiency will be increased. The examination of neoclassical growth theory has been done with reference to external & internal factors of 52 selected countries from 1960 to 2000. The independent variable of MODEL has been selected on the basis of the result of previous research which explains the result in three separate MODELs: developed countries, developing countries, and whole countries. These factors are such as: Gross National Products with lag of period, work force age, growth rate, education level, the change of capital accumulation and economic trade volum. The consequences of this research is that: neoclassical growth MODEL can explain the major part of economic growth of the countries with use of internal variables. Also with the use of panel procedure of fixed effect, we can see the fundamental differences and structure of the growth process for different countries; and show how the economic, and social conditions affect on the growth.

Face recognition from digital images is used for surveillance and authentication in cities, organizations, and personal devices. Internet of Things (IoT)-powered face recognition systems use multiple sensors and one or more servers to process DATA. All sensor DATA from initial methods was sent to the central server for processing, raising concerns about sensitive DATA disclosure. The main concern was that all DATA from all sectors that could contain confidential information was placed in a central server. Federated learning can solve this problem by using several local MODEL training servers for each region and a central aggregation server to form a global MODEL in IoT networks. This article presents a novel approach to optimize DATA transfer and convergence time in federated learning for a face recognition task using Non-dominated Sorting Genetic Algorithm II (NSGA II). The aim of the study is to balance the trade-off between training time and MODEL accuracy in a federated learning environment. The results demonstrate the effectiveness of the proposed approach in reducing DATA transfer and convergence time, leading to improved performance in face recognition accuracy. This research provides insights for researchers and practitioners to enhance the efficiency of federated learning in real-world applications.

Todays gamma knife radiosurgery is used widely for treatment of very small brain tumors. In order to investigate accuracy of dosimetry and treatment planning calculations, using Monte Carlo simulation with dedicated code named as beamnrc including non-CT DATA and CT DATA options is necessary. The aim of this study is choosing the best options in order to have an accurate tools based on their advantages and disadvantages. In this study, gamma knife unit 4C along with standard water equivalent phantom and EBT3 films were used to obtain dose distributions. Monte Carlo simulation was done with non-CT DATA and CT DATA options of the code and their resulting dose were compared. Comparison the calculated and measured dose distributions at X, Y and Z axis showed gamma value below 1 which verified Monte Carlo simulations. Also comparing the dose distributions from both non-CT DATA and CT DATA with each other implies that there is no significant difference between two methods. Based on the obtained results using non-CT DATA and CT DATA results in the same dose distribution. So for simplicity, using non CT DATA for regular phantom shapes is preferred.

Modern DATA storage and communication technology has created an opportunity to rethink the manner in which geosciences information is archived and presented. The Geosciences DATAbase must provide a mechanism to allow rapid access to up-to-date geosciences DATA in a form tailored to the needs of the user requesting the DATA. The DATA MODEL underlying this DATAbase must be flexible enough to encompass a wide range of earth science information, storing it in such a fashion that advances in Earth science do not obsolete the DATAbase. One of the major goals of a geosciences DATA MODEL is to simplify the process of generating derivative maps tailored to specific needs e. g. tectonic analysis, hazard assessment, mineral exploration. Such DATA may need to be based on information from many sources. Presently, in the derivative maps are usually compiled by manually extracting (i. e. tracing on paper) information from a number of printed maps, probably generated by different people with different motivations at different scales, and graphically combining the information (i. e. redrafting) into a single, derivative map. The goal of the geosciences conceptual DATA MODEL is to provide basic information from a variety of sources in a consistent, flexible, and searchable structure. In this research, regarding the importance of the maps in DATA interpretation of geosciences, geological maps is the base for the conceptual DATA MODELs. Using this base, required domains is defined. The MODEL outlined here provides a conceptual framework that could accommodate newly acquired field DATA or DATA mined from previously published sources into a common framework.

in the era of information, DATA which are worthwhile asset of human, organizations and enterprises have become such sophisticated that the conventional approaches and methods are not usable anymore, or not efficient at least. Such complexity which is known as the Big DATA problem is the affordable extraction of value from big DATA sets that we are encountered in many recent applications e.g., e-business, scientific research, monitoring, search engines, social networking, etc.. Big DATA complexities are instantiated by three major dimensions, high Volume, high Variety, and high Velocity (a.k.a.3Vs). The first and most essential step in DATA management (also for Big DATA management) is designing and employing a proper DATA MODEL, as the footstone of the other DATA management activities such as R& D of DB languages, DBMSs, tools, methods, algorithms, etc.. In this paper, a proper DATA MODEL for Big DATA is designed and proposed in which the properties required for Big DATA problem (i.e., to be integrated, complete, scalable, flexible, compatible, and efficient) are considered. As a DATA MODEL, DATA representation is designed and implicit integrity constraints are presented for the proposed HNG (Hyper Nested Graph) DATA MODEL. Experimental evaluation results show that the proposed DATA MODEL outperforms other currently used DATA MODELs such as the document-based, graph document-based, and graph- based DATA MODELs in terms of response time.

AbstractContext and purpose. The purpose of this research is to design a MODEL for the development of cultural and creative industries through economic tools and mechanisms and the integration of creative and cultural economy.Methodology/approach. In the current study, the qualitative method of grounded theory was used and the in-depth interview technique was used to collect information. The sampling method of the research was purposeful and snowball methods with theoretical saturation criteria and interviews with 20 experts in the field of creative and cultural industries. open, axial and selective coding processes was used to DATA analysis, and after that, the grounded theory emerging from the DATA was presented in the form of a story and visual MODEL, and based on them, definition and classification were carried out for the application of the development of creative and cultural industries. Findings and conclusions. The results have shown that training and empowerment of cultural and creative industries and culture building in the field of cultural and creative industries act as intervening conditions to encourage business owners to create cultural and creative jobs, and these three-dimensional conditions in interaction together have caused the development of cultural and creative industries and the dynamics of the economy and moving towards the creative economy, and the consequence of that is the creative ecosystem approach to economic benefits and economic profitability and cultural development.Originality/innovation. Previous researches have pointed out factors affecting cultural industries or creative industries separately and from different perspectives,