In this paper, the authors have focused on the stochastic analysis of an INTERNET DATA CENTER ((IDC)), which consists of a DATAbase main server connected to a redundant server. Observing the different possibilities of functioning of the system, analysis has been done to evaluate the various reliability characteristics of the system. The system can completely fail due to failure of redundant server before repair of DATAbase server, router failure and switch failure. The system can also fail completely due to a cooling failure or some natural calamity like earthquake, fire; etc. All the failure rates are assumed constant while the repairs follow two types of distributions namely general and Gumbel-Hougaard family copula.

The aim of this paper is to consider whether critical rationalism has any ideas which could usefully be applied to the INTERNET.  Today we tend to take the INTERNET for granted and it is easy to forget that it was only about two decades ago that it began to be used to any significant extent. Accordingly in section 1 of the paper, there is a brief consideration of the history of the INTERNET.  At first sight this makes it looks implausible that any of Popper’s ideas could be applicable to the INTERNET, since Popper died before the INTERNET came into general use.  However, section 2 argues that Popper’s theory of World 3 does apply very well to the INTERNET.  This application is significant because, as shown in section 3, it leads to the problem of misinformation, which is one of the most significant problems generated by the INTERNET.  In section 4 there is an attempt to solve this problem using ideas taken from Popper’s epistemology. It is argued that there should be changes in education designed to prepare students for the INTERNET age. Teaching in the INTERNET age should focus on presenting to the students not just the accepted theories but also the evidence on which they are based. An illustration of how this might be done is given by considering an example from science teaching, namely the teaching of Newtonian mechanics in the last years of school or first years of university.

In an electricity grid, imbalance between generation and load need be corrected within seconds so that frequency deviations will not threaten the stability and security. This is especially important for a low inertia microgrid operated in islanded mode, which is equipped with a limited number of synchronous generators in regulating frequency. To this end, for DATA CENTER microgrid with limited on-site generators and increased green energy, when isolated from the utility grid, frequency deviation due to generation-load imbalance could be potentially corrected by conventional generating units as well as DATA CENTER loads. Focusing on high PV penetrated DATA CENTER microgrid operated in islanded mode, this paper explores effective control strategies for DATA CENTER loads to participate in primary frequency response. By analyzing unique operational characteristics of traditional and PV generation units, uninterruptible power supply (UPS) units, and power consumption characteristics of IT components and cooling systems, the proposed load control strategy design effectively utilizes primary FR capabilities while not compromising DATA CENTER quality of service (QoS) requirements. Numerical simulations via MATLAB/Simulink illustrate effectiveness of the proposed load control strategy in enhancing renewable energy penetration without compromising the system stability and security, providing a viable solution for future green DATA CENTERs.

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.

Invasive ductal carcinoma ((IDC)) breast cancer is one of the most common types of breast cancer among women, with a relatively high mortality rate. Introducing new diagnostic methods to the medical field can lead to a reduction in mortality. One of these methods is statistical monitoring and social screening of people with high risk of (IDC) cancer. Accordingly, many variables involved in the (IDC) occurrence should be identified and valued and finally classified. These variables include genetic factors involved in the (IDC) occurrence, environmental and unknown parameters. Addressing each of the factors requires extensive research. However, in this study, it has been tried to use three effective factors in the (IDC) occurrence, which include age, HR/HER2 status, and race, to provide a statistical model of the (IDC) occurrence. This information is reported based on the research of the American Cancer Society for 5 different races, aged 20 to over 79 and with different HR/HER2 status. In this study, a statistical analysis has been done based on the age, HR/HER2 status, and race. To provide a visual presentation of statistical analysis, Koch curve has been used with Python software, which is the best curve to show the progress of (IDC) disease. The results showed that people in the age group of 60 to 69, with HR+/HER2- status and white race are the people with higher probability of (IDC). People in the age group of 20 to 39, with HR-/HER2+ status and with black race are less likely to develop (IDC). In the same way, people with characteristics between these two states can be ranked.

ISPs always confront a huge amount of their customer usage raw DATA. Since these DATA are too voluminous, DATA mining techniques can be useful to recognize hidden usage patterns of the users to develop relevant management strategies. But these patterns vary according to variable circumstances during a year. Therefore, in this paper, the usage patterns of INTERNET users are detected continuously during time line applying usage attributes of the users and association rules of mining technique within an incremental DATA mining framework. Raw DATA of an ISP is surveyed to describe the model. The results of the article show that the usage patterns of INTERNET users obtained from this DATA mining model can lead to the improvement of ISP services and the reduction of their costs.

Classifying customers using DATA mining algorithms enables banks to keep old customers loyality while attracting new ones. Using decision tree as a DATA mining technique, we can optimize customer classification provided that an appropriate decision tree is selected. In this article we have presented an appropriate model to classify customers who use INTERNET banking service. The model is developed based on CRISP- DM standard and we have used real DATA of Sina bank's INTERNET bank. In comparison with the other decision trees, ours is based on both optimization and accuracy factors that recognizes new potential INTERNET banking customers using a three level classification, which is low/medium and high. This is a practical, documentary-based research. Mining customer rules enables managers to make policies based on discovered patterns in order to have a better understanding of what customers really desire.