Qatar Foundation Annual Research Forum Volume 2012 Issue 1

There is an increasing need for improved environmental compliance, while reducing the time and cost of compliance checking (CC). This research offers a new approach for automated environmental CC. The approach utilizes semantic modeling and natural language processing (NLP) techniques. Semantic modeling aims at offering the level of knowledge representation and reasoning that is needed to process applicable environmental regulations and check compliance of construction plans to the rules that are prescribed by those regulations. NLP techniques will facilitate text analysis and processing for achieving human-like extraction and formalization of rules and information. The approach is intended to automatically detect non-compliance instances and provide a rich analysis of the non-compliance such as which regulation was violated, reason for violation, possible consequences of violation. To achieve such deep levels of text processing and automated reasoning, three algorithms are developed and combined into one computational platform: (1) a machine-learning-based text classification algorithm to classify relevant text (in documents such as environmental regulations), (2) a hybrid syntactic-semantic, utilizing grammatical and meaning-descriptive features of the text, information extraction algorithm to facilitate text processing for extraction and formalization of rules and information, and (3) a logic-based algorithm for compliance reasoning. Automated analysis will be facilitated by a semantic model for environmental knowledge representation and reasoning. The algorithms will be implemented in a proof-of-concept prototype software for automated environmental CC, and will be tested and validated using real-life-based test case scenarios. This research will transform the way we conceptualize and formally reason about complex regulatory schemes and associated CC processes, and will advance the research in the areas of deep NLP and deep semantic reasoning. The results of this research will also transform the way construction professionals and government regulators (e.g. environmental protection agencies) check the compliance of construction projects with environmental regulations and green practices. The ultimate goals of this research, in terms of benefits to the society, are: (1) increasing environmental compliance in construction, thereby protecting human health and the environment, (2) promoting compliance with non-regulatory green construction practices, thereby supporting green and sustainable construction, and (3) reducing the time and cost of environmental CC.^{2 2} This material is based upon work supported by the National Science Foundation under Grant No. 1201170. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.

Clustering is an important data mining technique that groups similar data records. In this research, the problem of clustering categorical (or transactional) data is studied. An algorithm for clustering transactional data, called F-Tree (frequent tree), is proposed, and a new similarity measure function, called PWO (probability of the weights of overlapped items), is introduced. Then, a framework to detect the best similarity value for different datasets is developed. Based on the items' frequencies in transactions, the F-Tree algorithm first generates small but highly pure clusters. It then merges similar clusters using the PWO similarity measure function, which depends on the probability of weights of overlapped items. One advantage of PWO is that it outputs the percentage of similarity between items; this is a clearer and more accurate measure of similarity than other similarity measures. Our experimental evaluation on real categorical datasets such as (Mushrooms, KrVskp, Congressional Voting, Soybean-Large, Soybean-Small, Hepatitis, Zoo, Lenses, and Adult-Stretch) shows that: Firstly, F-Tree is effective in finding rare or interesting clusters, and produces clusters with higher purity than LargeItem, WCD and CLOPE. Secondly, PWO is more effective in measuring the similarity between categorical data than LargeItem and CLOPE. Thirdly, clustering using the similarity measure PWO with pre-defined number of clusters results in separate classes with a good purity of average 80% coverage of real classes. Fourthly, the overlap estimator perfectly estimates the value of the overlap threshold using a small sample of dataset of around 5%. Finally, it is seen that the process of merging pure and small clusters increases the purity of resulted clusters as well as reduces time of clustering better than the process of generating clusters directly from the dataset then refining clusters. Based on the items' frequencies in transactions, The F-Tree algorithm first generates small but highly pure clusters. It then merges similar clusters using the PWO similarity measure function, which depends on the probability of weights of overlapped items. One advantage of PWO is that it outputs the percentage of similarity between items; this is a clearer and more accurate measure of similarity than other similarity measures. Our experimental evaluation on real categorical datasets such as "Mushrooms, KrVskp, Congressional Voting, Soybean-Large, Soybean-Small, Hepatitis, Zoo, Lenses, and Adult-Stretch" shows that: Firstly, F-Tree is effective in finding rare or interesting clusters, and produces clusters with higher purity than LargeItem, WCD and CLOPE. Secondly, PWO is more effective in measuring the similarity between categorical data than LargeItem and CLOPE. Thirdly, Clustering using the similarity measure PWO with pre-defined number of clusters results in separate classes with a good purity of average 80% coverage of real classes. Fourthly, the overlap estimator perfectly estimates the value of the overlap threshold using a small sample of dataset of around 5 percent. Finally, It is seen that the process of merging pure and small clusters increases the purity of resulted clusters as well as reduces time of clustering better than the process of generating clusters directly from the dataset then refining clusters.

I. Background Articulatory modeling is used to incorporate speech production information into automatic speech recognition (ASR) systems. It is believed that solutions to the problems of co-articulation, pronunciation variations, and other speaking style related phenomena rest in how accurately we capture the production process. II. Objective In this work we present a novel approach for speech recognition that incorporates knowledge of the speech production process. We discuss our contribution on going from a purely statistical speech recognizer to one that is motivated by the physical generative process of speech. III. Methods We follow an analysis-by-synthesis approach. Firstly, we attribute a physical meaning to the inner states of the recognition system pertaining to the configurations the human vocal tract takes over time. We utilize a geometric model of the vocal tract, adapt it to our speakers, and derive realistic vocal tract shapes from electromagnetic articulograph (EMA) measurements in the MOCHA database. Secondly, we synthesize speech from the vocal tract configurations using a physiologically-motivated articulatory synthesis model of speech generation. Thirdly, the observation probability of the Hidden Markov Model (HMM), which is used for phone classification, is a function of the distortion between the speech synthesized from the vocal tract configurations and the real speech. The output of each state in the HMM is based on a mixture of density functions. Each density models the distribution of the distortion at the output of each vocal tract configuration. During training, we initialize the model parameters using ground-truth articulatory knowledge. During testing, only the acoustic data is used. IV. Results and conclusion We present phone classification results using our novel dynamic articulatory model and following our adaptation procedure. The table below shows phone error rates (PER) for a female and a male speaker. We use a three-state HMM with different observation densities and initialization techniques. We combine the probabilities of the baseline topology with the new ones. Our novel framework provides a 10.9% relative reduction in phone error rate over our baseline which uses MFCC features. This is achieved using the distortion features with linear discriminant analysis (LDA) and cepstral mean normalization (CMN). We conclude that incorporating articulatory knowledge in the combined statistical framework we devised contributes to lowering the error rates in speech recognition. Features (dimension) Topology Observation Prob / Initialization Female PER Male PER Both PER Improvement Baseline Features MFCC + CMN (13) 3S-128M-HMM Gaussian/VQ 61.6% 55.9% 58.8% Distortion Features (1024) (Prob. Combination with MFCC, α = 0.2) 3S-1024M-HMM Exponential/Flat Sparsity = 21% 57.6% 53.7% 55.7% 5.3% Distortion Features (1024) (Prob. Combination with MFCC, α = 0.2) 3S-1024M-HMM Exponential/EMA Sparsity = 51% 58.3% 53.9% 56.1% 4.6% Adapted Distortion Features (1024) (Prob. Combination with MFCC, α = 0.25) 3S-1024M-HMM Exponential/EMA Sparsity = 51% 58.4% 53.1% 55.7% 5.3% Distortion Features + LDA + CMN (20) (Prob. Combination with MFCC, α = 0.6) 3S-128M-HMM Gaussian/VQ Sparsity = 0% 54.9% 49.8% 52.4% 10.9%

Spermidine/spermine-N1-acetyltransferase (SSAT) is a highly inducible and tightly controlled enzyme that is the rate-limiting step for polyamine catabolism. Because polyamines increase in dividing cells, SSAT has long been a target for cancer drug discovery. We have shown that the ability to enhance SSAT activity is a useful tool for cancer research, perhaps especially so for prostate cancer since the polyamine pathway is particularly active in this organ. SSAT can be induced by small molecules, including the biogenic polyamines themselves, which activate the negative feedback mechanism used to remove excess levels of these polyamines. SSAT activity is known to be affected by many mechanisms and good evidence indicates that translation control is important. We recently found that SSAT translation control involves a stem loop at the beginning of the open reading frame (ORF) and an upstream ORF 5' to the initiating methionine. A nucleolin isoform suppresses translation by binding to and stabilizing a 5' stem loop of SSAT mRNA but this repression is released when increased polyamines activate nucleolin autocatalysis; i.e., this is a negative feedback system. The current study is designed to exploit these exciting results with the overall goal to identify drug candidates with high potency and desirable physical properties to take forward into pre-clinical development. Here we report the development and validation of a luciferase-based reporter system for the identification of compounds that are able to promote the translation of SSAT. The translational de-repression sensor system, which uses HEK293T cells transformed with a construct composed of SSAT mRNA modified to lack uORF function, is mutated to overcome repression and is linked at the 3' end with luciferase. As a proof of principle of the utility of the SSAT translation sensor, we screened 2 libraries, the Redox library consisting of antioxidants (84 compounds) and the FDA Approved Drug library (1,200 compounds). Untreated cells were used as the negative control, and cells treated with 10 µM DENSPM (N1, N11-diethylnorspermine) were the positive control. Twelve compounds were identified from these libraries that activate SSAT translation by at least 35% more than the basal expression. We conclude that an SSAT translational control-based high throughput screening sensor can lead to the identification of novel pharmacophores that are able to prevention and/or treat prostate cancer.

This study examines the practice of arranged marriage with close relatives in Qatar. A survey was conducted on 521 young males and females to identify weather youth attitudes towards marriage selection have changed and to what extent their attitudes are influenced by the traditional standards of the arranged marriage which is associated with kinship system. The study also reviewed many previous studies about marriage in the region, dating back to the last century, and compared them with the results of more recent studies and the current study. The study findings showed that the practice of this form of consanguineous marriage is common in the region, and remains common, in spite of the rapid modernization and urbanization of the region. The perseverance of these practices challenges some of the fundamental assumptions about the correlation between modernization and social change. From a practical standpoint, the perseverance of these consanguineous marriage practices also represents a significant risk to the societies in question, as endogamous marriage practices within a tribe result in high levels of congenital disorders. This study suggests the cultural foundation of these practices, and recommends that programs seeking to remedy these problems take aim at their social and cultural roots.

A web-based application designed for the iPad which focuses on buildings designed for Doha across the decades.  Over the years, some of the greatest architects of their respective eras have designed buildings for Doha. These buildings were preceded by the local vernacular architecture, of which a few notable examples remain. Each of these buildings responds, in its own way, to the local climate and culture. More than any other single artifact, a building represents a culture's values and aspirations, socioeconomic conditions and construction techniques. Buildings project these attributes outward and become a means for a city or a nation to transmit its identity to others. It is not by accident that postcards of buildings are so common; an image of the city as represented by its architecture is disseminated outward across the globe.  These digital postcards represent a curated selection of noteworthy buildings that were designed for Doha. They range in time, location, use, style and built status. These categories allow for different means of sorting the information: into different eras (pre-oil, independence, realignment, or expansion), by architectural language or style (vernacular, modern, postmodern or contemporary); and by its current condition (built, demolished, unrealized or renovated). Part of an ongoing research project on the physical growth of Doha over time, 4dDoha: Buildings is an educational web-based application that focuses on the city's architecture throughout its history. Combining research, graphic design and interaction design, the iPad app allows users to sift through the data via a series of filters, while recording the users' choices on a projected map. Created by Carnegie Mellon School of Architecture faculty Kelly Hutzell and Rami el Samahy with research associates Adam Himes, Spencer Gregson and Kristina Ricco. Generous support provided by Carnegie Mellon Qatar and Qatar Foundation. Concept and software design by over,under, inc.

Background & Objectives: This presentation reports on the findings of a Qatar National Research Fund-sponsored study that is the first of its kind in the Gulf. Through a survey, the study examines the demographics, cost, migration arrangements, and the living and working conditions of low-income migrant workers in Qatar. Although much has been written about the problems and challenges of migrant workers in the Gulf, these quantitative data are the first of their kind in the larger area of migration studies in the Gulf. Our presentation seeks to provide an overview of the findings, with more in-depth discussion of the findings that complement and challenge our ethnographically-derived findings to date. Methods: Utilizing a sampling frame derived from utility records, we constructed a random sample of 1,189 low-income transnational labor migrants in Qatar's worker accommodations and other migrant dwellings. The administered survey explores the problems and challenges labor migrants oftentimes encounter in the Gulf States, with topical sections exploring labor brokerage, wages, housing, health, migrant finances, and living and working conditions in general. Results: The findings suggest that while labor migrants in Qatar face a similar regime of structures, practices, and challenges, there is significant variation within the total population of low-income labor migrants, with nationality and ethnicity playing the most significant role in shaping the migrant experience. For example, basic salaries for low-income workers from the Philippines and Egypt were substantially higher than the lowest earning nationalities. Arab low-income migrants also work fewer days per week, live in slightly less crowded conditions, and, unlike their South Asian counterparts, report no problems with salary withholding. Conclusions: Although our findings generally confirm the conclusions others have produced via small-scale, anecdotal, or non-representative samples in regard to the general characteristics of the population and the challenges they face, we also present several surprising findings that challenge conventional knowledge about labor migration in Qatar and the GCC at large.

This study reports on the development and large-scale validation of the "Assessing Arabic Speaking Students' Attitudes toward Science Survey" (ASSASS). The study is part of a larger project funded by the Qatar Foundation and aimed at identifying factors that impact precollege (grades 3 through 12) Qatari students' interest in, and attitudes toward, science. The development was primarily motivated by the fact that no instruments have been specifically designed and systematically validated for use with Arabic speaking students. Additionally, most extant instruments were developed for use with a specific grade or school level, and many lacked grounding in a robust theoretical framework. ASSASS was grounded in the most recent revision of the theories of reasoned action and planned behavior (TRABP). A 10-member international panel of science educators and education researchers reviewed an initial pool of 74, 5-point Likert scale items for alignment with TRABP. A revised pool of 60 items was piloted with a purposively selected sample of 396 grade 3 through 12 students in Qatar. Survey administration was followed by individual interviews with a 10% random sample of the students to ensure that ASSASS items were comprehensible to, and meaningful from the perspective of, students. Exploratory factor analysis (EFA) of pilot data resulted in the deletion of 14 items, which had poor loadings on an initial six-factor model for the instrument. Next, the resulting 46-item version of ASSASS was administered to a nationally representative sample of 2,778 grade 3 through 12 students in Qatar. Again, survey administration was followed by individual interviews with a 3% randomly selected sample of respondents to help triangulate assertions derived from quantitative data. EFA followed by confirmatory factor analysis (CFA) resulted in a robust model showing a very good fit, with a Root Mean Square Error of Approximation (RMSEA) at .042 (among many other robust statistical indicators). The model included a single global factor ("attitudes toward science") plus four orthogonal residual factors (a sub-set of the six factors identified in the pilot study). These factors were: intention to pursue or engage in science, negative outlook toward science, perceptions of school science, and perceived utility of science.

Infrastructure assets and services, such as water, energy, transport and telecommunications, play a vital role in promoting economic prosperity, political stability and human development. However, throughout the Muslim world, the availability of infrastructure services is poor due to the combination of growing populations, rapid urbanization, and historic underinvestment in infrastructure. These factors as well as the constant need for technological advancements put extreme pressures on public budgets, many of which are already constrained. Huge investment in infrastructure is needed through a consorted effort between the public and private sector. In Qatar alone, the pipeline of infrastructure projects is estimated at over $70 billion up to 2030. Among the most important sources of financing in the Muslim world is Islamic finance. However, data suggests that Islamic finance and capital market activity in infrastructure projects (excluding real estate) has been relatively limited. The objective of this paper is to highlight the importance of Islamic finance in infrastructure projects, to investigate the current state of Islamic infrastructure finance within the Gulf Cooperation Council (GCC) region, and to suggest ways of overcoming the challenges that Islamic and infrastructure finance face. The paper begins with a review of the economic literature on the importance of infrastructure to economic development, poverty alleviation, entrepreneurship and trade. The paper argues that there is a natural theoretical and ideological link between Islamic finance and infrastructure finance. Sources of financing infrastructure projects are then analyzed, and the mechanics of Islamic project financing are explained. The Islamic infrastructure finance market in the Gulf Cooperation Council countries is then surveyed. Case studies of past projects are then presented drawing attention to four areas: (1) structure of Islamic finance products for infrastructure financing; (2) challenges facing the use of Islamic finance; (3) potential development of new products; and (4) implications for policy-makers. The information presented in this research will provide useful lessons for GCC member countries on a subject that is given scarce attention to by academia.

Background: The groundbreaking activities that were enabled and facilitated by an NPRP research grant (Islamic Medical and Scientific Ethics, NPRP No. 08-783-6-017) to build a comprehensive collection of scholarly resources on Islamic bioethics have transformed the original proposal and slowly succeeded in creating a research culture that brought local, regional, and international attention to the project and its resources as an important hub for Islamic bioethics research. These activities include: development of a multilingual collection, which is catalogued, indexed, and maintained by the project team; development of an information retrieval system that enables fast and accurate searching capabilities of the stored bibliographic information; supporting collaborative initiatives with local, regional, and international stakeholders; envisioning further research opportunities that expand the scope of the project beyond bibliographic research into topical research projects and comprehensive reference works, which inspired another three-year research proposal to compile the world's first Encyclopedia of Islamic Bioethics and which has been accepted and awarded at the QNRF's Fifth Cycle in May 2012 (NPRP No. 5-1390-6-043) . These efforts have recently culminated in the successful organization of an international conference on Islamic bioethics, which brought together some of the most prominent experts of Islamic bioethics both in the West and in the Muslim world, which was held in June 2012 in Doha. Objectives: The presentation aims to show the different dimensions of the Islamic bioethics research project with a special focus on the important aspects that ensure smooth and effective transition from one level of the research process to another. More particularly, the presentation seeks to highlight the importance of maintaining a long-term vision, which inspires short-term and periodical objectives. Methods: the presentation will address these dimensions of the project: - Planning and revision - Bibliographic component - Research component - Workflow and team-building component - Dissemination and outreach component Results and Conclusions: The presentation will share the most important results that the project achieved in the first phase as well as preparations for the following phase with a special focus on the challenges that the project team encountered as well as the important lessons gained in the process.