Fuzzy-rough set models and fuzzy-rough data reduction

Rough set theory is a powerful tool to analysis the information systems. Fuzzy rough set is introduced as a fuzzy generalization of rough sets. This paper reviewed the most important contributions to the rough set theory, fuzzy rough set theory and their applications. In many real world situations, some of the attribute values for an object may be in the set-valued form. In this paper, to handle this problem, we present a more general approach to the fuzzification of rough sets. Specially, we define a broad family of fuzzy rough sets. This paper presents a new development for the rough set theory by incorporating the classical rough set theory and the interval-valued fuzzy sets. The proposed methods are illustrated by an numerical example on the real case

Named entity recognition using a new fuzzy support vector machine.

Recognizing and extracting exact name entities, like Persons, Locations, Organizations, Dates and Times are very useful to mining information from electronics resources and text. Learning to extract these types of data is called Named Entity Recognition(NER) task. Proper named entity recognition and extraction is important to solve most problems in hot research area such as Question Answering and Summarization Systems, Information Retrieval and Information Extraction, Machine Translation, Video Annotation, Semantic Web Search and Bioinformatics, especially Gene identification, proteins and DNAs names. Nowadays more researchers use three type of approaches namely, Rule-base NER, Machine Learning-base NER and Hybrid NER to identify names. Machine learning method is more famous and applicable than others, because it’s more portable and domain independent. Some of the Machine learning algorithms used in NER methods are, support vector machine(SVM), Hidden Markov Model, Maximum Entropy Model (MEM) and Decision Tree. In this paper, we review these methods and compare them based on precision in recognition and also portability using the Message Understanding Conference(MUC) named entity definition and its standard data set to find their strength and weakness of each these methods. We have improved the precision in NER from text using the new proposed method that calls FSVM for NER. In our method we have employed Support Vector Machine as one of the best machine learning algorithm for classification and we contribute a new fuzzy membership function thus removing the Support Vector Machine’s weakness points in NER precision and multi classification. The design of our method is a kind of One-Against-All multi classification technique to solve the traditional binary classifier in SVM

The role of advertising through social networks to promote brand equity

Social networks are online gathering places for people who would like to share their interests and activities. In this context, advertising through social networks is one of the most important topics in the field of marketing and brand that has been considered only in few studies. This study examines the impact of advertising on brand equity through social networks in the beverage industry (PepsiCo). This research study was to survey and collect data from the a standard questionnaire. PepsiCo brand, which is a well known beverage industry worldwide is selected for the proposed study of this paper. Thus, all customers of Pepsi products in city of Tehran are considered as statistical research community and a sample size of 385 people is selected for the proposed study. In order to analyze the data, we use structural equations method and certified factor analysis. The results of our survey indicate that advertisement on social networks has a positive impact in this industry. Based on the results of our survey, we realize that there are some positive relationship between social network advertisement and quality perception, brand loyalty, brand awareness and brand association when the level of significance is one percent

The Impact of Coronavirus on the Ecosystem of Rationality

The recent pandemic is a reminder of several important lessons from Popper's philosophy. My aim in this paper is to address some of these lessons. By making use of Popper's theory of three worlds, I explain how coronavirus has a far-reaching impact on the ecosystem of rationality, and how the viruses that threaten humans could also be a threat to the whole life on Earth. Applying the epistemological distinction between science and technology, I go on to explain the pivotal role of science in preventing further crises. This, I argue, is done by putting technology in the sphere of rationality; through both criticizing technologies and inspiring the invention of clean technologies, and also technologies that serve us as alerting systems. I shall argue that critical rationalism helps us to understand the ‘pandemic problem situation’ in a more informed manner and thus helps us to find out about the vulnerable points of our ecosystem of rationality in a more efficient way. In the latter part of the paper, I shall develop the thesis that while during the recent pandemic, science did it best to warn us about its dangers, the policy-makers, who are technologists of a sort, in many countries did not take those warnings seriously. Even when the crisis turned into a global catastrophe, the three types of technologies (health-care, lock-down, and diagnosis and treatment) were not fully efficient in controlling the pandemic. Drawing on Popper’s ideas I shall argue that in the face of the current emergency, our best chance to improve our situation is to apply the method of piecemeal social engineering to alleviate people’s suffering

The relationship between spiritual intelligence and self-management in patients with diabetes

BACKGROUND: Type 1 diabetes is one of the most common chronic diseases in children. Metabolic control and following diet therapy in teenagers with type 1 diabetes are weaker than children before the adolescence stage. One of the most important factors influencing self-management seems to be spiritual intelligence. The aim of this study was to investigate the relationship between spiritual intelligence and self-management in patients with diabetes.METHODS: The population of this descriptive cross-sectional study consisted of all adolescents with type 1 diabetes referring to the clinic of Tohid Hospital in Sanandaj, Iran, which were 194 people. Data were collected by interview and using a questionnaire. Sampling method was available or simple sampling. The collected data were analyzed using descriptive statistics and SPSS software.RESULTS: The majority of people were in the middle period of adolescence. More than half (88.5%) of them had a moderate and good economic situation and the majority of them (62.5%) had a history of diabetes in the family. Most of the people (56.5%) had an average duration of diabetes. More than half of the subjects were the first and second children of the family.CONCLUSION: The results showed that self-management increased with increasing spiritual intelligence of individuals, and with decreasing spiritual intelligence, self-management decreased; in other words, there was a positive and significant correlation between spiritual intelligence and self-management.

BUCKLING ASSESSMENT OF IMPERFECT CYLINDRICAL SHELLS UNDER AXIAL LOADS USING A GEP TECHNIQUE

Determination of buckling behavior of shell structures has long been identified as a challenging task. This is largely because the buckling behavior is masked by local large deformations, which occur once the critical load is reached. This research proposes a novel technique to accurately predict the buckling load of imperfect cylindrical shells using gene expression programming (GEP), which is an evolutionary artificial intelligence method. An existing experimental data bank was employed for training and testing the program, and the obtained buckling load of shell structures were accordingly verified. From the results, it is concluded that GEP is a promising and reliable method to determine the buckling load of shell structures subjected to axial compression

Philosophical Relationship of Humanities and Technology

The purpose of this paper is to shed some light on the Philosophical relationship between humanities and technology. It will be explained that most disciplines in humanities are Janus-faced: they are part science/knowledge and part technology. The thesis of the paper is that the relationship between the technological aspect of humanities and other technologies is positive and synergetic, while the relationship between their scientific aspect and technologies is almost entirely critical and negative. The argument of the paper is not that the scientific aspect of humanities has nothing positive to offer to the development of technologies, but rather to clarify the nature of this assistance. It is also hoped that the paper’s analysis could help to explain how the scientific aspect of humanities can partake in the process of rationalisation of the development of technology