Question categorization and classification using grammar based approach

Question-answering has become one of the most popular information retrieval applications. Despite that most question-answering systems try to improve the user experience and the technology used in finding relevant results, many difficulties are still faced because of the continuous increase in the amount of web content. Questions Classification (QC) plays an important role in question-answering systems, with one of the major tasks in the enhancement of the classification process being the identification of questions types. A broad range of QC approaches has been proposed with the aim of helping to find a solution for the classification problems; most of these are approaches based on bag-of-words or dictionaries. In this research, we present an analysis of the different type of questions based on their grammatical structure. We identify different patterns and use machine learning algorithms to classify them. A framework is proposed for question classification using a grammar-based approach (GQCC) which exploits the structure of the questions. Our findings indicate that using syntactic categories related to different domain-specific types of Common Nouns, Numeral Numbers and Proper Nouns enable the machine learning algorithms to better differentiate between different question types. The paper presents a wide range of experiments the results show that the GQCC using J48 classifier has outperformed other classification methods with 90.1% accuracy.     

Electrical power free, low dead volume, pressure-driven pumping for microfluidic applications

This paper presents a simple-to-construct, low dead volume pump capable of generating a wide range of positive and negative pressures for microfluidic applications. The pump generates pressure or vacuum by changing the volume of air confined inside a syringe and is able to generate pressures between -95 and +300 kPa with a resolution as high as 1 Pa. Different from syringe pumps and electrokinetic pumping, which are capable of controlling flow rates only, our pump can be used to generate constant flow rates or constant pressures, which are required for certain applications such as the aspiration of biological cells for biophysical characterization. Compared to syringe pumps, the new pump has almost zero dead volume and does not exhibit pulsatile flows. Additionally, the system does not require electrical power and is cost effective (～$100). To demonstrate the capabilities of the pump, we used it to aspirate osteoblasts (MC3T3-E1 cells) and to determine Young's modulus of the cells, to generate a concentration gradient, and to produce variable-sized droplets in microchannels using hydrodynamic focusing.     

Effectiveness of antigraffiti treatments in connection with penetration depth determined by different techniques

The elimination of spray paint using traditional (chemical and mechanical) methods inevitably entails altering surface characteristics. Hence, the impact and deterioration caused by graffiti in heritage buildings and monuments have led to the development and application of preventive systems in the form of antigraffiti coatings (which prevent paint from seeping into the pores of the surface material and facilitate cleaning). The effectiveness of two of these treatments, a commercial product (fluoroalkyl siloxane, protectosil, marketed by Degussa) and a hybrid organic-inorganic material (Ormosil), was evaluated in five construction materials (limestone, granite, cement mortar, lime mortar and brick), in terms of their penetration into the substrate. A number of techniques were used to determine the penetration depth (SEM/EDX, micro-Raman and LIBS), because a comparative analysis showed that none was universally valid for all types of treatments. The results show that the presence of the coating on the surface of less porous materials only ensures effective cleaning when the surface is fairly smooth. In granite, for instance, the CF₃ terminals in the fluorinated treatment hinder spray paint bonding more effectively than Ormosil, but not efficiently enough to ensure complete removal of the paint from granite surfaces.     

Management of inclusive education in Oman: A framework for Action

Inclusive education (IE) and the special education services related to it are relatively new in Oman. Efforts to manage special/inclusive education face many challenges due to a number of culturally rooted factors. Further, empirical research on IE in Oman is scarce and there is a need to advance IE discourse based on empirically validated perspectives. This article examines how IE is managed in schools from the perspective of school leaders in order to develop a framework for action. The author conducted a preliminary qualitative inquiry into how IE is understood and managed in Key stage 1 schools in Oman. The inquiry was based on a focus group interview with a cohort of 25 school leaders who were completing a two year bachelor in educational administration, an endorsement‐like programme at Sultan Qaboos University. Findings showed a number of challenges and tensions between theory and practice, highlighted by school leaders. These challenges and tensions were analysed in order to map out strengths and difficulties. A three level prism shaped framework for action was developed based on the analysis. The framework for action could potentially serve to guide policy‐ and decision‐makers, researchers, practitioners, and is advocated to develop a model of best practice for the successful implementation and management of IE in Oman.     

Developing a road performance index using a Bayesian belief network model

There is a high demand to develop and incorporate decision support tools, by the transportation sectors and other concerned agencies, to improve their infrastructure assets management under shrinking budgets and increasing demands. This paper develops a proof-of-concept Bayesian belief network (BBN) model to rank roads in a network system based on several key performance indicators (KPI) using a probabilistic framework. For a given road network, the proposed tool is capable of ranking or prioritizing the segment of roads for high level management objectives. To demonstrate the application of the proposed model, various scenarios are elaborated and discussed in detail. Finally, the sensitivity analysis is carried out to evaluate the effects of different KPIs.     

A multilevel model for effects of social capital and knowledge sharing in knowledge-intensive work teams

Although it is a widely held belief that social capital facilitates knowledge sharing among individuals, there is little research that has deeply investigated the impacts of social capital at different levels on an individual's knowledge sharing behavior. To address this research gap, this study combines a multilevel approach and an optimal network configuration view to investigate the multilevel effects of social capital on individuals’ knowledge sharing in knowledge intensive work teams. This study makes a distinction between the social capital at the team-level and that of social capital at the individual level to examine their cross-level and direct effects on an individual's sharing of explicit and tacit knowledge. A survey involving 343 participants in 47 knowledge-intensive teams was conducted for testing the multilevel model. The results reveal that social capital at both levels jointly influences an individual's explicit and tacit knowledge sharing. Further, when individuals possess a moderate betweenness centrality and the whole team holds a moderate network density, team members’ knowledge sharing can be maximized. These findings offer a more comprehensive and precise understanding of the multilevel impacts of social capital on team members’ knowledge sharing behavior, thus contributing to the social capital theory, as well as knowledge management research and practices.