Text documents clustering using data mining techniques

Increasing progress in numerous research fields and information technologies, led to an increase in the publication of research papers. Therefore, researchers take a lot of time to find interesting research papers that are close to their field of specialization. Consequently, in this paper we have proposed documents classification approach that can cluster the text documents of research papers into the meaningful categories in which contain a similar scientific field. Our presented approach based on essential focus and scopes of the target categories, where each of these categories includes many topics. Accordingly, we extract word tokens from these topics that relate to a specific category, separately. The frequency of word tokens in documents impacts on weight of document that calculated by using a numerical statistic of term frequency-inverse document frequency (TF-IDF). The proposed approach uses title, abstract, and keywords of the paper, in addition to the categories topics to perform the classification process. Subsequently, documents are classified and clustered into the primary categories based on the highest measure of cosine similarity between category weight and documents weights

Comparison of Naïve bayes classifier with back propagation neural network classifier based on f - folds feature extraction algorithm for ball bearing fault diagnostic system

This paper is intended to compare the Naïve bayes classifier for ball bearing fault diagnostic system with the back propagation neural network based on the f-folds feature extraction algorithm. The f-folds feature extraction algorithm has been used with different number of folders and clusters. The two classifiers have shown similar classification accuracies. The Naive bayes classifier has not shown any case of false negative or false positive classification. However, the back propagation neural network classifier has shown many cases of false positive and false negative classifications

Multiplex polymerase chain reaction identification of Candida species colonized sputum of patients suffering from various respiratory tract disorders in Duhok, Iraq

Background: Candida species are part of the body normal flora. Under certain conditions, these opportunistic microorganisms may lead to infection. The purpose of this study was to identify Candida species isolated from sputum from patients suffering from respiratory tract disorders.Methods: A total of 59 sputum samples taken from patients attending Azadi hospital at Duhok province, Kurdistan Region/Iraq. For primary isolation, sputum samples were cultured on sabouraud dextrose agar (SDA). Suspected colonies of Candida isolates were then sub cultured on chromogenic Candida agar for presumptive identification. Genomic DNA extraction was performed using a genomic DNA extraction kit. For rapid identification of Candida spp, specific primers based on the genomic sequence of DNA topoisomerase 11 of C. albicans, C. parapsilosis I, C. parapsilosis II, C. guilliermondi, C. dubliniensis, C. krusei, C. kefyr and C. glabrata, C. tropicalis I, C. tropicalis II, C. lusitaniae were used. The Multiplex PCR products were separated by electrophoresis in 1.5% agarose gel, visualized by staining with ethidium bromide, and photographed.Results: Three Candida species namely C. albicans, C. glabrata and C. tropicalis were differentiated by their colour produced on Chromogenic Candida agar. PCR with the primer mixes yielded 4 different sized of PCR products corresponding to C. albicans, C. glabrata, C. Keyfer and C. tropicalis II, C. glabrata was the most common species (33.33%), followed by C. albicans (16.66%). The highest rate of isolation of Candida species was between the ages of 36 to 45.Conclusion: This study concluded that phenotypic characteristics on selective agar medium such as chromogenic Candida agar are useful for presumptive identification of Candiada spp with the support of molecular method such as multiplex PCR.

Identification of Candida spp. isolated from vaginal swab by phenotypic methods and multiplex PCR in Duhok, Iraq

Background: Candida species are the second most common cause of vulvovaginitis worldwide. The purpose of this study was to identify the species of vaginal Candida isolates by using phenotypic and Multiplex PCR techniques.  Methods: 91 isolates from patients admitted to Azadi hospital and Maternity hospital in Duhok city were collected. The vaginal swab specimens were inoculated on Sabouraud dextrose agar. Colonies were then sub cultured on Chromogenic Candida agar. Genomic DNA extraction was performed using a Genomic DNA Extraction kit. For rapid identification of Candida spp., specific primers based on the genomic sequence of DNA topoisomerase 11 of C. albicans, C. parapsilosis I, C. parapsilosis II, C. guilliermondi, C. dubliniensis, C. krusei, C. kefyr and C. glabrata, C. tropicalis I, C. tropicalis II, C. lusitaniae were used. The multiplex PCR products were separated by electrophoresis in 1.5% agarose gel, visualized by staining with ethidium bromide, and photographed.  Results: 4 Candida species, namely C. albicans, C. glabrata, C. krusei and C. tropicalis were distinguished by Chromogenic Candida agar on the basis of colony colour and morphology. PCR with the primer mixes yielded 7 different sized of PCR products corresponding to C. albicans, C. guilliermondii, C. dubliniensis, C. glabrata, C. kefyr, C. krusei and C. tropicalis II. The analysis revealed C. glabrata and C. albicans were the most common species isolated with the percentage 40% and 30% respectively.Conclusions: This study concluded that phenotypic characteristics on selective agar medium such as chromogenic candida agar are useful for presumptive identification of Candiada spp. with the support of molecular method such as multiplex PCR.  

Expert material selection for manufacturing of green biocomposites

The innovation in material science reveals more materials day by day and the material database grows exponentially. The conventional material selection systems fail to handle this large material database. The explosion all over the world is increasingly using the computing power to solve complex problems. Accordingly, it is applied in the field of engineering to obtain an optimum solution. The Expert System is a computer application that emulates the decision-making ability of a human expert for a specific task. This chapter presents a brief perception of implementing the expert systems for material selection of green bio composites. Due to the increasing ecological problem the synthetic materials are being reduced in the manufacturing industry and replaced by so called “bio composite” materials. The bio composites have different fibre orientations, matrices and constitutions would result in diverse characteristics in physical, mechanical, thermal and environmental properties. These dissimilar attributes of bio composites would increase the challenges for the material selection process. Hence, few case studies with automotive interior components are discussed for better understanding and to show the implementation of the expert system for the material selection of green bio composites. The result shows that these expert system has dramatically advanced the material selection to enforce green technology and sustainability in manufacturing and design

Implementation of the expert decision system for environmental assessment in composite materials selection for automotive components

Conventional materials selection system was replaced with sophisticated software tools by rapid changing technology. The growing environmental concerns and regulations widely among the industry, especially in automobiles, force us to explore the natural fiber materials as a replacement for synthetic materials which is in common use. As a result of extensive research and development, new natural fiber reinforced composite materials are emerging and the database of materials growing exponentially. The decision of selecting optimized materials was complicated, as it involves diversified choice of materials, coupled with various influencing criteria for the selection process. To abstain from deciding inappropriate materials, the technology of expert system software tools can help us in the appropriate materials selection. The objective of this research was to explore the implementation of Analytical Hierarchy Process (AHP) using the expert choice software tool for deciding optimum natural fiber reinforced composite materials by considering main criteria and sub-criteria in the hierarchical model. The final judgement was performed with different scenarios of sensitivity analysis, giving priority to the environmental factors and sustainability. The result shows that the natural fiber composite material hemp and polypropylene gained the higher rank in the selection process and almost compliant with the requirements of industrial product design specification and can be recommended to automotive component manufacturers to enforce green technology

A review on polyurethane and its composites

In the recent years, the research about polyurethane (PU) composites (thermoplastic, thermoset, biobased polyurethane with synthetic fibers (glass, aramid and carbon) and natural fibers used as reinforcement of polymers has been increased due to their biodegradability, lightness, reduced cost and favorable mechanical properties. Unique mechanical, thermal, and chemical properties of Polyurethanes (thermoset/thermoplastic) can be designed by the reaction of various polyhydric compounds (polyols) and polyisocyanates which is derived from the formation of cross-linked polyurethanes. One of the challenges that researchers face today is to achieve satisfactory interfacial bonding which will result in products with better mechanical and thermal properties. Composites having better mechanical and thermal properties could find more industrial applications and consequently would have greater commercial acceptance. However, this is difficult due to the hydrophilicity of the fibers and the hydrophobicity of polymers such as polyurethane. In this review paper, comprehensive review about PU and its polymer composites were presented with concentrating on the effect of the different kinds of natural and synthetic fibers on the PU based polymer composites products. We also discussed the effect of chemical treatments of natural fibers on improvement of interfacial bonding between natural fiber and polyurethane matrix for development of advanced materials with better mechanical and thermal properties

Determinants of College and University Choice for High-School Students in Qatar

Drawing on existing research, this paper investigates various predictors of high school students’ college and university choice decisions in Qatar. Based on a 2015 survey of 1,427 participants, this study utilized exploratory factor analysis to identify variables that affect student choice of higher educational institutions (HEI). Three factors were extracted from the analysis, revealing the following aspects of the academic experience as important when choosing a HEI: quality of education, cultural values, and the cost of education. To further the understanding of the relevance of these factors for different student demographics, we employed ordinal logistic regression to test whether several independent variables (student’s gender, nationality, parental education, and parental occupation) act as significant predictors of the three extracted dimensions (dependent variables). The analysis revealed that, indeed, demographic characteristics significantly predict, to varying degrees, all three factors affecting student’s HEI choice. Discussion on postulated reasons behind the recorded relationships will follow, along with implications and recommendations for further study and research. Findings of this study will help HEIs in Qatar and the broader region to position themselves more effectively, and develop targeted strategies that attract a diverse student population

Java based expert system for selection of natural fibre composite materials

Many research papers are published in the field of materials selection for manufacturing process and design of polymer composite materials. However, least consideration has been given for material selection of natural fibre composites. Intensive research carried out to use natural fibres as alternative materials for petrochemical based synthetic materials to enforce green technology in manufacturing engineering. There are several algorithm and methods are being proposed by various researchers in this field. Computer oriented materials selection and knowledge-based expert systems are the prevailing approach in materials selection. In this paper, we develop a technology for the materials selection system using Java based expert system. The weighted-range method (WRM) was implemented to identify the range value and to scrutinise the candidate materials. The expert system performance tested with automotive component as case study with high, medium and low precision criteria and the result sets generated by the expert system comply with industrial benchmark

Microplastic Contaminants in the Sediment of the East Coast of Saudi Arabia

Microplastic contamination in the sediment of the east coast of Saudi Arabia was not addressed by any study. The objective of this study is to obtain the first measurement of microplastic abundance at four different beaches on the east coast of Saudi Arabia (Khafji, Jubial, Dammam, and Salwa). Sediment samples were collected from both high tide and low tide zone. A total of 586 microplastic particles were collected from all the sites with an average particle size of 1.55 ± 0.94 mm. The majority of microplastic particles (77%) were less than 2 mm in size. Microplastic abundance ranged from 5.5 ± 1.55 to 21.2 ± 0.68 particle/kg (51.1 ± 14.71 to 152.8 ± 21.32 particle/m2) in low tide region, and from 6.3 ± 4.05 to 16.5 ± 4.98 particle/kg (50.6 ± 31.21 to 204.5 ± 64.15 particle/m2) in high tide region. The most dominant colors were transparent (34%) and blue (30%), while the fiber was the most common shape (96%). Polyethylene terephthalates were the common polymer type of fibers, while polyethylene and high-density polyethylene were common in fragments and filaments