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.

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.

These days cyberattack is a serious criminal offense and it is a hotly debated issue moreover. A man-in-the-middle-attack is a kind of cyberattack where an unapproved outsider enters into an online correspondence between two users, remains escaped the two parties. The malware that is in the middle-attack often monitors and changes individual/classified information that was just real-ized by the two users. A man-in-the-middle-attack as a protocol is subjected to an outsider inside the system, which can access, read and change secret information without keeping any tress of manipulation. This issue is intense, and most of the cryptographic systems without having a decent authentication security are threatened to be hacked by the malware named ‘men-in-the-middle-attack’ (MITM/MIM). This paper essentially includes the view of understanding the term of ‘men-in-the-middle-attack’; the current work is mainly emphasized to accumulate related da-ta/information in a single article so that it can be a reference to conduct research further on this topic at college/undergraduate level. This paper likewise audits most cited research and survey articles on ‘man-in-the-middle-attack’ recorded on 'Google Scholar'. The motivation behind this paper is to help the readers for understanding and familiarizing the topic 'man-in-the-middle attack'.

One of the primary concerns in most financial institutions to have an appropriate method for ranking customers. Bank customers are the primary sources of creating income and the success of banking industry depends on how to select good customers for allocation of loans. This paper uses Decision Tree, K-nearest neighbor (KNN), Support Vector Machine (SVM), Naive Bayes, and Logistic Regression for data categorization to estimate credit ranking of bank customers in one of major banks in Middle East. The results indicate that Logistic Regression was considered as the best method for ranking customers with the precision of 76.17% while Decision Tree was considered as the weakest technique with the precision of 73.30%.

Magnetic abrasives are important parts of Magnetic Assisted Abrasive Finishing (MAF). Magnetic abrasives are prepared by many processes, but sintering is the one of the best processes to prepare magnetic abrasives. The objective of this paper is to optimize the sintering process parameters. To do that, Response Surface Methodology (RSM) is used for the optimization of process parameters, Abrasive concentration in ferromagnetic particles (AC)%, Compacting Pressure (CP) N/mm2 and Sintering Time(ST)min. To check the performance of magnetic abrasives Percentage Improvement in Surface finish (PISF) is considered as a response variable. Optimization and prediction are executed through RSM and Central Composite Design (CCD) is used to conduct the experiments. The optimized values of process parameters obtained are AC (19.29%), ST (15min) and CP (6.9 N/mm2) and also predicted values for the response variable are obtained.

A new flexible and adjustable model which is based on an Intuitionistic Fuzzy TOPSIS model with an exponential-related function and intuitionistic fuzzy entropy method has been presented and apply in this study. For supporting designers in determining design stakeholders’ preferences when finding the best compromise between new concepts design during early product develop-ment phase. The main advantage of the new model is that it is flexible and adjustable and affords the design stakeholders the option to a change of action in the event they receive new information or reason not to continue with a particular design or product. Finally, it uses both subjective and objective weights methods for the evaluation of the design concepts criteria, which makes the proposed model more realistic and more practical. The model has been applied for the design concept evaluation of seven forklift trucks with the view to improving the reliability of the machine.

Flexibility has been cited as a key factor to enhance the performance of flexible manufacturing sys-tem (FMS). The main aim of this paper is to rank the flexibility of FMS. The ranking decisions are complex in the manufacturing field to analyze a number of alternatives based on a set of some attributes. In this research, two MADM methods i.e. MOORA (i.e. multi-objective optimization on the basis of ratio analysis) and weighted Euclidean distance based approach (WEDBA) are used for ranking of flexibility in FMS for new part development. MOORA approach can give de-cision with or without considering relative importance of attributes i.e. attribute weights. While in WEDBA, integrated attribute weights are used for evaluation which included the subjective and objective weights of attributes. Objective weights are calculated by entropy method and subjective weights are calculated by analytic hierarchy process. MOORA is applied in two ways i.e. ratio based and reference point analysis. Ranking of fifteen flexibility of FMS done on the basis fifteen variables which effect flexibility of FMS. The results of MOORA and WEDBA approach shows that product flexibility has the top most flexibility in fifteen flexibilities and programme flexibility has the least impact in fifteen flexibilities.

This paper presents the application of the new method in the process of making the decisions on the scooters selection. The Fuzzy AHP method was used to obtain the weight coefficients of criteria, on the basis of which the alternatives were evaluated. The selection of criteria for evaluating scooters was based on an analysis of available manufacturer website. The evaluation and selection of scooters was carried out using a new multi-criteria decision making (MCDM) method. The present study tries to identify the attributes like kerb weight, mileage, top speed, fuel tank capacity and price playing prominent role in the buying behavior of the working women while purchasing scooters. Fuzzy-AHP method has been used to obtain the relative weights of the criteria, on the basis of which the alternatives are evaluated using new MCDM. The TOPSIS and MABAC methods were tested under the same conditions. The stability of the result obtained by this method is established through a sensitivity analysis.

This paper presents the application of the new method in the process of making the decisions on the scooters selection. The Fuzzy AHP method was used to obtain the weight coefficients of criteria, on the basis of which the alternatives were evaluated. The selection of criteria for evaluating scooters was based on an analysis of available manufacturer website. The evaluation and selection of scooters was carried out using a new multi-criteria decision making (MCDM) method. The present study tries to identify the attributes like kerb weight, mileage, top speed, fuel tank capacity and price playing prominent role in the buying behavior of the working women while purchasing scooters. Fuzzy-AHP method has been used to obtain the relative weights of the criteria, on the basis of which the alternatives are evaluated using new MCDM. The TOPSIS and MABAC methods were tested under the same conditions. The stability of the result obtained by this method is established through a sensitivity analysis.