During the past two decades, internet has penetrated into people’s personal lives, significantly. People communicate with each other through internet facilities such as email services, social web pages, etc. Internet has influenced so much of our lives that many people get addicted and it has become a serious issue among different societies. In this study, we perform an empirical study to find the relationship of three issues of age, gender and employment status on internet addiction behavior. The survey selects 190 men and 160 women from a city of NajafAbad located in province of Esfahan, Iran and a questionnaire consists of 35 questions are distributed among them. The survey uses Chi-Square statistics to examine the effects of three mentioned factors and the results indicate that internet addiction is more among singles than married (Chi-Square=19.94). The survey also indicates that internet addition is more on men than women do (Chi-Square=6.64). However, our survey does not find any evidence to believe job employment has any impact on internet addiction.

The primary objective of this paper is to develop a comprehensive method to learn the effect of knowledge management (KM) practices on organizational performance. The balanced scorecard (BSC) is applied to materialize this comprehensiveness. In order to prevent research dispersion, the selective indicators in KM are oriented to some critical success factors influencing KM implementation. In addition, the mentioned effect is analyzed by path analysis using structural equation modeling (SEM). The results indicate that KM practices maintain some impacts on the overall performance. Finally, KM practices only influence learning and growth among dimensions of BSC, significantly. Likewise, data analysis states other significant impact among performance dimensions in terms of BSC model.

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Due to the increasing technological advances in all fields, a considerable amount of data has been collected to be processed for different purposes. Data mining is the process of determining and an-alyzing hidden information from different perspectives to obtain useful knowledge. Data mining can have many various applications, one of them is in medical diagnosis. Today, many diseases are regarded as dangerous and deadly. Heart disease, breast cancer, and diabetes are among the most dangerous ones. This paper investigates 168 articles associated with the implementation of data mining for diagnosing such diseases. The study concentrates on 85 selected papers which have received more attention between 1997 and 2018. All algorithms, data mining models, and evaluation methods are thoroughly reviewed with special consideration. The study attempts to determine the most efficient data mining methods used for medical diagnosing purposes. Also, one of the other significant results of this study is the detection of research gaps in the application of data mining in health care.

The project scheduling problem is both practically and theoretically of paramount importance. From the practical perspective, improvement of project scheduling as a critical part of project management process can lead to successful project completion and significantly decrease of the relevant costs. From the theoretical perspective, project scheduling is regarded as one of the in-teresting optimization issues, which has attracted the attention of many researchers in the area of operations research. Therefore, the project scheduling issue has been significantly evaluated over time and has been developed from various aspects. In this research, the topics related to Re-source-Constrained Project Scheduling Problem (RCPSP) are reviewed, recent developments in this field are evaluated, and the results are presented for future studies. In this regard, first, the standard problem of RCPSP is expressed and related developments are presented from four as-pects of resources, characteristics of activities, type of objective functions, and availability level of information. Following that, details about 216 articles conducted on RCPSP during 1980-2017 are expressed. At the end, in line with the statistics obtained from the evaluation of previ-ous articles, suggestions are made for the future studies in order to help the development of new issues in this area.

The condensation of several aromatic/heteroaromatic aldehydes with 2-aminothiophenol under melt reaction conditions afforded 2-arylbenzothiazoles under solvent-free conditions. The major advantages of the present method are high yields, short reaction times, and eco-friendly conditions.

An ionic liquid 1-Butyl-3-methylimidazoliumchloride[BMIm]Cl/sodium hydroxide system, was employed as a catalyst for the fast and one-pot crossed aldol-condensation of various aromatic aldehydes and cyclic ketones, to produce a variety of substituted ?,? & apos; -bis(benzylidene)-cycloalkanones under neat conditions. This process is simple, efficient and environmentally benign and proceeds in high yield and short reaction times. The ionic liquid can be recycled for subsequent reactions without any appreciable loss of efficiency.

Business trades among individuals, companies, firms, enterprises, and governments are rapidly expelled from their traditional mode, which were mainly based on paper-based exchange, and are geared towards trading through information-based systems. E-commerce has opened up a new field in terms of speed, efficiency, cost savings, and the exploitation of fleeting opportunities. This paper evaluates different authentication methods for online banking in Parsian Bank, which is one of the biggest private banks in Iran. The study designs a questionnaire and distributes it among some experts to find cause and effect factors based on a multi-criteria decision making technique named Decision Making Trial And Evaluation Laboratory (DEMATEL). The study evaluates 12 criteria and divides them into two groups of cause and effect. “Use of mobile systems in authenti-cation methods”, “Authentication with fingerprint and smart card”, “Authentication with bank card and password”, and “Authentication with digital signatures and passwords” are considered as the causative group, while “Authentication with a bank card”, “Biometric authentication and disposable codes” and “Authentication with digital signature” are among the effective group.

An efficient and simple synthesis of some 2-amino-3-cyano-4H-pyran derivatives was developed by the one-pot and three-component reaction of aldehydes, ethyl acetoacetate, and malononitrile in the presence of ammonia as catalyst at room temperature. The reaction is rapid and clean, and gives the products in high yields.

In this research, the influences of modal properties of a micro cubic satellite on equivalent static loads (due to combination of quasi-static and dynamic loads during launch time) have been studied. The study shows that the magnitude of equivalent static loads can be affected by satellite effective modes and effective mass distribution along natural frequencies. Besides, when to distinct launchers with different dynamic environments candidate for launch, analytical results illustrate that sometimes the equivalent static combined load value can be higher for the launcher with smaller quasi-static loads. This phenomenon is due to effective modal mass distribution of the satellite. Consequently, a higher combined load may be occurred during launch for smaller quasi-static conditions. Furthermore, in separation phase of satellite from the launcher, the satellite modal parameters influence the magnitude of applied shock load in both axial (launch) and lateral directions, importantly. Thus the present study yields reliable input values for separation shock test which considers dynamic properties of the satellite in comparison with some standards and launcher manuals, suggest a rough estimation of shock load, neglecting the satellite structure dynamic behavior.

Clustering is absolutely useful information to explore data structures and has been employed in many places. It organizes a set of objects into similar groups called clusters, and the objects within one cluster are both highly similar and dissimilar with the objects in other clusters. The K-mean, C-mean, Fuzzy C-mean and Kernel K-mean algorithms are the most popular clustering algorithms for their easy implementation and fast work, but in some cases we cannot use these algorithms. Regarding this, in this paper, a hybrid model for customer clustering is presented that is applicable in five banks of Fars Province, Shiraz, Iran. In this way, the fuzzy relation among customers is defined by using their features described in linguistic and quantitative variables. As follows, the customers of banks are grouped according to K-mean, C-mean, Fuzzy C-mean and Kernel K-mean algorithms and the proposed Fuzzy Relation Clustering (FRC) algorithm. The aim of this paper is to show how to choose the best clustering algorithms based on density-based clustering and present a new clustering algorithm for both crisp and fuzzy variables. Finally, we apply the proposed approach to five datasets of customer's segmentation in banks. The result of the FCR shows the accuracy and high performance of FRC compared other clustering methods.