ASSESSMENT AND ASSURANCE OF SERVICE QUALITY IN PEDIATRIC HEALTHCARE IN QATAR

The purpose of this study was quality assessment and quality assurance in pediatric services of public and private hospitals in Qatar. The purpose of quality assessment was to identify gaps in the delivered services; while quality assurance process was carried out to ensure no future gaps in quality occur. The objectives were achieved using a modified SERVQUAL scale and Fuzzy-Quality Function Deployment (Fuzzy- QFD) approach. Data from 179 participants who visit public/private hospitals in Qatar was analyzed to find the gaps between expectations and perceptions. The results of the SERVQUAL study indicates negative quality gaps for all the service quality dimensions. The inference that can be drawn from this result is that, in general, the people are dissatisfied by the pediatric healthcare services offered by the public/ private hospitals in Qatar. Thus, the managers in these hospitals should work towards improving the quality of their services, in particular, the responsiveness and empathy dimensions. The output of the SERVQUAL study was then utilized to model those variables that are important in assuring service quality. This was achieved using Fuzzy-QFD model which demonstrates that there is a set of variables that should be accorded prime importance by the hospitals administrators’ to assure quality in pediatric services

A framework to manage uncertainties in cloud manufacturing environment

This research project aims to develop a framework to manage uncertainty in cloud manufacturing for small and medium enterprises (SMEs). The framework includes a cloud manufacturing taxonomy; guidance to deal with uncertainty in cloud manufacturing, by providing a process to identify uncertainties; a detailed step-by-step approach to managing the uncertainties; a list of uncertainties; and response strategies to security and privacy uncertainties in cloud manufacturing. Additionally, an online assessment tool has been developed to implement the uncertainty management framework into a real life context. To fulfil the aim and objectives of the research, a comprehensive literature review was performed in order to understand the research aspects. Next, an uncertainty management technique was applied to identify, assess, and control uncertainties in cloud manufacturing. Two well-known approaches were used in the evaluation of the uncertainties in this research: Simple Multi-Attribute Rating Technique (SMART) to prioritise uncertainties; and a fuzzy rule-based system to quantify security and privacy uncertainties. Finally, the framework was embedded into an online assessment tool and validated through expert opinion and case studies. Results from this research are useful for both academia and industry in understanding aspects of cloud manufacturing. The main contribution is a framework that offers new insights for decisions makers on how to deal with uncertainty at adoption and implementation stages of cloud manufacturing. The research also introduced a novel cloud manufacturing taxonomy, a list of uncertainty factors, an assessment process to prioritise uncertainties and quantify security and privacy related uncertainties, and a knowledge base for providing recommendations and solutions

Manufacturing Quality Function Deployment: Literature Review and Future Trends

A comprehensive review of the Quality Function Deployment (QFD) literature is made using extensive survey as a methodology. The most important results of the study are: (i) QFD modelling and applications are one-sided; prioritisation of technical attributes only maximise customer satisfaction without considering cost incurred (ii) we are still missing considerable knowledge about neural networks for predicting improvement measures in customer satisfaction (iii) further exploration of the subsequent phases (process planning and production planning) of QFD is needed (iv) more decision support systems are needed to automate QFD (v) feedbacks from customers are not accounted for in current studies

An Approach for e-inclusion: Bringing illiterates and disabled people into play

In emergent economies, the continued process of digitalizing the ICTs, summed up with some sociocultural particularies and porvety, contributes to cleave the society into two groups: the connected and the increasingly more disconnected or socially excluded. However, efforts to effectively narrow this kind of divide transcends the provision of access to web and other digital networks, mainly if the attention is focused on people with disabilities and lack of literacy. For these social groups, accessibility and intelligibility are the key barriers to e-society. A manner to mitigate then is the objective of an ongoing research project in which we are engaged and that comprises the elaboration and application of a methodology for developing solutions to e-inclusion in Brazil. This paper presents the central aspects of such an appoach, focusing on some activities which go beyond the connectivity provision and may help the most “excludeds” in bridging the divide.En las economías emergentes, el continuo proceso de digitalización de las TICs, en adición a algunas particularidades socioculturales y la pobreza, contribuye a dividir la sociedad en dos grupos: los conectados y los cada vez más desconectados o socialmente excluidos. Sin embargo, esfuerzos para efectivamente estrechar esta división trasciende la provisión de acceso a la web y otras redes digitales, principalmente si la atención está enfocada a personas con discapacidades y analfabetismo. Para estos grupos sociales, la accesibilidad e inteligibilidad son barreras para el ingreso a una sociedad electrónica. Una manera de mitigar este problema es teniendo como objetivo una investigación de avanzada, la cual tenga un compromiso y contacto con la elaboración y aplicación de una metodología para el desarrollo de soluciones y de inclusión electrónica en Brasil. Este trabajo presenta los aspectos centrales de tal aproximación, enfoscándose en algunas actividades que van más allá de la conectividad, provisión y una posibilidad de conectar a los excluidos de éste sistemaIn emergent economies, the continued process of digitalizing the ICTs, summed up with some sociocultural particularies and porvety, contributes to cleave the society into two groups: the connected and the increasingly more disconnected or socially excluded. However, efforts to effectively narrow this kind of divide transcends the provision of access to web and other digital networks, mainly if the attention is focused on people with disabilities and lack of literacy. For these social groups, accessibility and intelligibility are the key barriers to e-society. A manner to mitigate then is the objective of an ongoing research project in which we are engaged and that comprises the elaboration and application of a methodology for developing solutions to e-inclusion in Brazil. This paper presents the central aspects of such an appoach, focusing on some activities which go beyond the connectivity provision and may help the most “excludeds” in bridging the divide

Past, present and future of information and knowledge sharing in the construction industry: Towards semantic service-based e-construction

The paper reviews product data technology initiatives in the construction sector and provides a synthesis of related ICT industry needs. A comparison between (a) the data centric characteristics of Product Data Technology (PDT) and (b) ontology with a focus on semantics, is given, highlighting the pros and cons of each approach. The paper advocates the migration from data-centric application integration to ontology-based business process support, and proposes inter-enterprise collaboration architectures and frameworks based on semantic services, underpinned by ontology-based knowledge structures. The paper discusses the main reasons behind the low industry take up of product data technology, and proposes a preliminary roadmap for the wide industry diffusion of the proposed approach. In this respect, the paper stresses the value of adopting alliance-based modes of operation

That Movie was so Hilarious NE!' The Development of Japanese Interactional Particles NE, YO, and YONE in L2 Classroom Instruction.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2017

Metadiscourse analysis of digital interpersonal interactions in academic settings in Turkey

Rapid technological advances, efficiency and easy access have firmly established emailing as a vital medium of communication in the last decades. Nowadays, all around the world, particularly in educational settings, the medium is one of the most widely used modes of interaction between students and university lecturers. Despite their important role in academic life, very little is known about the metadiscursive characteristics of these e-messages and as far as the author is aware there is no study that has examined metadiscourse in request emails in Turkish. This study aims to contribute to filling in this gap by focusing on the following two research questions: (i) How many and what type of interpersonal metadiscourse markers are used in request emails sent by students to their lecturers? (ii) Where are they placed and how are they combined with other elements in the text? In order to answer these questions a corpus of unsolicited request e-mails in Turkish was compiled. The data collection started in January 2010 and continued until March 2018. A total of 353 request emails sent from university students to their lecturers were collected. The data were first transcribed in CLAN CHILDES format and analysed using the interpersonal model. The metadiscourse categories that aimed to involve readers in the email were identified and classified. Next, their places in the text were determined and described in detail. Findings of the study show that request emails include a wide array of multifunctional interpersonal metadiscourse markers which are intricately combined and employed by the writers to reach their aims. The results also showed that there is a close relation between the “weight of the request” and number of the interpersonal metadiscourse markers in request mails

Multi modal multi-semantic image retrieval

PhDThe rapid growth in the volume of visual information, e.g. image, and video can overwhelm users’ ability to find and access the specific visual information of interest to them. In recent years, ontology knowledge-based (KB) image information retrieval techniques have been adopted into in order to attempt to extract knowledge from these images, enhancing the retrieval performance. A KB framework is presented to promote semi-automatic annotation and semantic image retrieval using multimodal cues (visual features and text captions). In addition, a hierarchical structure for the KB allows metadata to be shared that supports multi-semantics (polysemy) for concepts. The framework builds up an effective knowledge base pertaining to a domain specific image collection, e.g. sports, and is able to disambiguate and assign high level semantics to ‘unannotated’ images. Local feature analysis of visual content, namely using Scale Invariant Feature Transform (SIFT) descriptors, have been deployed in the ‘Bag of Visual Words’ model (BVW) as an effective method to represent visual content information and to enhance its classification and retrieval. Local features are more useful than global features, e.g. colour, shape or texture, as they are invariant to image scale, orientation and camera angle. An innovative approach is proposed for the representation, annotation and retrieval of visual content using a hybrid technique based upon the use of an unstructured visual word and upon a (structured) hierarchical ontology KB model. The structural model facilitates the disambiguation of unstructured visual words and a more effective classification of visual content, compared to a vector space model, through exploiting local conceptual structures and their relationships. The key contributions of this framework in using local features for image representation include: first, a method to generate visual words using the semantic local adaptive clustering (SLAC) algorithm which takes term weight and spatial locations of keypoints into account. Consequently, the semantic information is preserved. Second a technique is used to detect the domain specific ‘non-informative visual words’ which are ineffective at representing the content of visual data and degrade its categorisation ability. Third, a method to combine an ontology model with xi a visual word model to resolve synonym (visual heterogeneity) and polysemy problems, is proposed. The experimental results show that this approach can discover semantically meaningful visual content descriptions and recognise specific events, e.g., sports events, depicted in images efficiently. Since discovering the semantics of an image is an extremely challenging problem, one promising approach to enhance visual content interpretation is to use any associated textual information that accompanies an image, as a cue to predict the meaning of an image, by transforming this textual information into a structured annotation for an image e.g. using XML, RDF, OWL or MPEG-7. Although, text and image are distinct types of information representation and modality, there are some strong, invariant, implicit, connections between images and any accompanying text information. Semantic analysis of image captions can be used by image retrieval systems to retrieve selected images more precisely. To do this, a Natural Language Processing (NLP) is exploited firstly in order to extract concepts from image captions. Next, an ontology-based knowledge model is deployed in order to resolve natural language ambiguities. To deal with the accompanying text information, two methods to extract knowledge from textual information have been proposed. First, metadata can be extracted automatically from text captions and restructured with respect to a semantic model. Second, the use of LSI in relation to a domain-specific ontology-based knowledge model enables the combined framework to tolerate ambiguities and variations (incompleteness) of metadata. The use of the ontology-based knowledge model allows the system to find indirectly relevant concepts in image captions and thus leverage these to represent the semantics of images at a higher level. Experimental results show that the proposed framework significantly enhances image retrieval and leads to narrowing of the semantic gap between lower level machinederived and higher level human-understandable conceptualisation