Qatar Foundation Annual Research Forum Volume 2013 Issue 1

Increasing attention has recently been drawn in the human-computer interaction community towards the design and development of accessible computer applications for children and youth with developmental or cognitive impairments. Due to better healthcare and assistive technology, the quality of life for children with intellectual disability (ID) has evidently been improved. Many children with ID often have cognitive disabilities, along with overweight problems due to lack of physical activity. This paper introduces an edutainment system specifically designed to help these children have an enhanced and enjoyable learning process, and addresses the need for integrating physical activity into their daily lives. These games are developed with the following pedagogical model in mind: A combination of Mayer's Cognitive Theory of Multimedia Learning with a mild implementation of Skinner's Operant Condition, incorporated with physical activity as part of the learning process. The system proposed consists of a padded floor mat that consists of sixteen square tiles supported by sensors, which are used to interact with a number of software games specifically designed to suit the mental needs of children with ID. The games consist of multimedia technology with a tangible user interface. The edutainment system consists of three games, each with three difficulty levels meant to suit specific needs of different children. The system aims at enhancing the learning, coordination and memorization skills of the children with ID while involving them into physical activities, thus offering both mental and physical benefits. The edutainment system was tested on 100 children with different IDs, half of which have Down syndrome (DS. The children pertain to three disability levels; mildly, moderately and severely disabled. The obtained results depict a high increase in the learning process as the children became more proactive in the classrooms. Assessment methodology took into account the following constraints; disability type, disability level, gender, scoring, timing, motivation, coordination, acceptance levels and relative performance. The following groups, when compared with other groups, achieved best results in terms of scores and coordination: children with DS, mildly disabled children and females. In contrast to children with other IDs, moderately and severely disabled children, and males performed with lower scores and coordination levels, but all the above mentioned groups exhibited high motivation levels. Rejection rate was found to be very low, at 3% of children refusing to participate. When children repeated the games, 92% were noted to achieve significantly higher results. The edutainment is developed with the following aims: helping children with ID have an enhanced cognitive experience, allowing them a learning environment where they can interact with the game and exert physical activities, ensuring a proactive role for all in the classroom, boosting motivation, coordination and memory levels. Results proved that the system had very positive effects on the children, in terms of cognition and motivational levels. Instructors also expressed willingness to incorporate the edutainment system into the classroom on a daily basis, as a complementary tool to conventional learning.

With the decline in physical activities among young people, it is essential to monitor their physical activity and ensure their calorie expenditure is within the range necessary to lead a healthy life style. For many children and young adults, video gaming is one favorable venue for physical activities. A new flavor of video games on popular platforms, such as Wii and Xbox, aim to improve the health of young adults through competing in games which require players to perform various physical activities. These popular platforms detect the user movements, and through an avatar in the game, players can be part of the game activities, such as boxing, playing tennis, dancing, avoiding obstacles, etc. Early studies used self-administered questionnaires or interviews to collect data about the patient's activities. These self-reporting methods ask participants to report their activities on hourly, daily, or weekly basis. But self-reporting techniques suffer from a number of limitations, such as inconvenience in entering data, poor compliance, and inaccuracy due to bias or poor memory. Reporting activities is a sensitive task for overweight/obese individuals with research evidence showing that they tend overestimate the calories they burn. Having a tool to help estimate calories consumption is therefore becoming essential to manage obesity and over-weight issues. We propose providing a calories expenditure estimation service. This service would augment the treatment provided by an obesity clinic or a personal trainer for obese children. Our energy expenditure estimation system consists of two main components: activity recognition and calories estimation. Activity recognition systems have three main components: low-level sensing module to gather sensor data, feature selection module to process raw sensor data and select the features necessary to recognize activities, and a classification module to infer the activity from the captured features. Using the activity type, we can estimate the calories consumption using existing models on energy expenditure developed on the gold standard of respiratory gases measurements. We choose Kinetic as our test platform. The natural user interface in Kinect is the low-level sensing module providing skeleton tracking data. The skeleton positions will be the raw input to our activity recognition module. From this raw data, we define the features that help the classifier, such as the speed of the hands and legs, body orientation, and rate of change in the vertical and horizontal position. These are some features that can be quantified and passed periodically (e.g., every 5 seconds) to the classifier to distinguish between different activities. Other important features might need more processing, such as the standard deviation, the difference between peaks (in periodic activities), and the distribution of skeleton positions. We also plan to build an index for the calories expenditure for game activities using the medical gold standard of oxygen consumption, CO2. Game activities, such as playing tennis, running, and boxing are different from the same real world activities in terms of enegy concumption and it would be useful to quantify the difference in order to answer the question of whether these “health” games are useful for weight loss.

We describe an assistive technology for improved literacy among the Deaf and Hard of Hearing, that is cost-wise and accessible to deaf individuals and their families/service providers (e.g., educators), businesses which employ them or list them as customers and healthcare professionals. The technology functions as (1) A real-time translation system between Moroccan Sign Language (a visual-gestural language) and standard written Arabic. Moroccan Sign Language (MSL) is a visual/gestural language that is distinct from spoken Moroccan Arabic and Modern Standrad Arabic (SA) and has no text representation. In this context, we describe some challenges in SA-to-MSL machine translation. In Arabic, word structure is not built linearly as is the case in concatenative morphological systems, which results in a large space of of morphological variation. The language has a large degree of ambiguity in word senses, and further ambiguity attributable to a writing system that omits diacritics. (e.g. short vowels, consonant doubling, inflection marks). The lack of diacritics coupled with word order flexibility are causes of ambiguity in the syntactic structure of Arabic. The problem is compounded when translating into a visual/gestural language that has far fewer signs than words of the source language. In this presentation, we show how Natural language processing tools are integrated into the system, the architecture of the system and provide a demo of several input examples with different levels of complexity. Our Moroccan Sign Language database has currently 2000 Graphic signs and their corresponding video clips. The database extension is an ongoing process task that is done in collaboration with MSL interpreters, deaf signers and educators in Deaf schools in different regions in Morocco. (2) Instructional tool: Deaf school children, in general, have poor reading skills. It is easier for them to understand text represented in sign language than in print. Several works have demonstrated that a combination of sign language and spoken/written language can significantly improve literacy and comprehension (Singleton, Supalla, Litchfield, & Schley, 1998; Prinz, Kuntz, & Strong, 1997; Ramsey & Padden, 1998). While many assistive technologies have been created for the blind, such as hand-held scanners and screen readers, there are only a few products targeting poor readers who are deaf. An example of such technology is the iCommunicator™ which translates in real time: speech to text, speech/typed text to videos of signs, and speech/typed text to computer generated voice. This tool, however, does not generate text from scans and display them with sign graphic supports that a teacher can print, edit, and use to support reading. It also does not capture screen text. We show a set of tools aiming at improving literacy among the Deaf and Hard-of-Hearing. Our tools offer a variety of input and ouput options, including scanning, screen text transfer, sign graphics and video clips. The technology we have developed is useful to teachers, educators, Health care professionals, speech/language pathologists, etc. who have a need to support understanding of Arabic text with Moroccan Sign Language signs for purposes of literacy improvement, curriculum enhancement, or communication in emergency situations.

The study of complex multi-faceted scientific questions demand innovative computing solutions—solutions that transcend beyond the management of big data to dedicated semantics-enabled, services-driven infrastructures that can effectively aggregate, filter, process, analyze, visualize and share the cumulative scientific efforts and insights of the research community. From a technical standpoint, E-Science purports technology-enabled collaborative research platforms to (i) collect, store and share multi-modal data collected from different geographic sites, (ii) perform complex simulations and experiments using sophisticated simulation models; (iii) design complex experiments by integrating data and models and executing them as per the experiment workflow; (iv) visualize high-dimensional simulation results; and (v) aggregate and share the scientific results (Fig 1). Taking a knowledge management approach, we have developed an innovative E-Science platform— termed Platform for Ocean Knowledge Management (POKM)—that is built using innovative web-enabled services, services-oriented architecture, semantic web, workflow management and data visualization technologies. POKM offers a suite of E-Science services that allow oceanographic researchers to (a) handle large volumes of ocean and marine life data; (b) access, share, integrate and operationalize the data and simulation models; (c) visualization of data and simulation results; (d) multi-site collaborations in joint scientific research experiments; and (e) form a broad, virtual community of national and international researchers, marine resource managers, policy makers and climate change specialists. (Fig 2) The functional objective of our E-Science infrastructure is to establish an online scientific experimentation platform that supports an assortment of data/knowledge access and processing tools to allow a group of scientists to collaborate and conduct complex experiments by sharing data, models, knowledge, computing resources and expertise. Our E-Science approach is to complement data-driven approaches with domain-specific knowledge-centric models in order to establish causal, associative and taxonomic relations between (a) raw data and modeled observations; (b) observations and their causes; and (c) causes and theoretical models. This is achieved by taking a unique knowledge management approach, whereby we have exploited semantic web technologies to semantically describe the data, scientific models, knowledge artifacts and web services. The use of semantic web technologies provides a mechanism for the selection and integration of problem-specific data from large repositories. To define the functional aspects of the e-science services we have developed a services ontology that provides a semantic description of knowledge-centric e-science services. POKM is modeled along a services-oriented architecture that exposes a range of task-specific web services accessible through a web portal. The POKM architecture features five layers—Presentation Layer, Collaboration Layer, Service Composition Layer, Service Layer and Ontology Layer (Fig 3). POKM is applied to the domain of oceanography to understand our changing eco-system and its impact on marine life. POKM helps researchers investigate (a) changes in marine animal movement on time scales of days to decades; (b) coastal flooding due to changes in certain ocean parameters; (c) density of fish colonies and stocks; and (d) time-varying physical characteristics of the oceans (Fig 4 & 5). In this paper, we present the technical architecture and functional description of POKM, highlighting the various technical innovations and their applications to E-Science.

In this work, we develop a spontaneous large vocabulary speech recognition system for Qatari Arabic (QA). A major problem with dialectal Arabic speech recognition is due to the sparsity of speech resources. So, we propose an Automatic Speech Recognition (ASR) framework to jointly use Modern Standard Arabic (MSA) data and QA data to improve acoustic and language modeling by orthographic normalization, cross-dialectal phone mapping, data sharing, and acoustic model adaptation. A wide-band speech corpus has been developed for QA. The corpus consists of 15 hours speech data collected from different TV series and talk-show programs. The corpus was manually segmented and transcribed. A QA tri-gram language model (LM) was linearly interpolated with a large MSA LM in order to decrease Out-Of-Vocabulary (OOV) rate and to improve perplexity. The vocabulary consists of 21K words extracted from the QA training set with additional 256K MSA vocabulary. The acoustic model (AM) was trained with a data pool of QA data and additional 60 hours of MSA data. In order to boost the contribution of QA data, Maximum-A-Posteriori (MAP) adaptation was applied on the resulted AM using only the QA data, effectively increasing the weight of dialectal acoustic features in the final cross-lingual model. All trainings were performed with Maximum Mutual Information Estimation (MMIE) and with Speaker Adaptive Training (SAT) applied on top of MMIE. Our proposed approach achieves more than 16% relative reduction in WER on QA testing set compared to a baseline system trained with only QA data. This work was funded by a grant from the Qatar National Research Fund under its National Priorities Research Program (NPRP) award number NPRP 09-410-1-069. Reported experimental work was performed at Qatar University in collaboration with University of Illinois.

In embedded real-time communication and multimedia processing applications, the manipulation of large amounts of data has a major effect on both power consumption and performance of the system. Due to the significant amount of data transfers between the processing units and the large and energy consuming off-chip memories, these applications are often called data-dominated or data-intensive. Providing sufficient bandwidth to sustain fast and energy-efficient program execution is a challenge for system designers: due to the growing gap of speed between processors and memories, the performance of the whole VLSI system will mainly depend on the memory subsystem, when memory is unable to provide data and instructions at the pace required by the processor. This effect is, sometimes, referred in the literature as the memory wall problem. At system level, the power cost can be reduced by introducing an optimized custom memory hierarchy that exploits the temporal data locality. Hierarchical memory organizations reduce energy consumption by exploiting the non-uniformity of memory accesses: the reduction can be achieved by assigning the frequently-accessed data to low hierarchy levels, a problem being how to optimally assign the data to the memory layers. This hierarchical assignment diminishes the dynamic energy consumption of the memory subsystem - which expands due to memory accesses. Moreover, it diminishes the static energy consumption as well, since this decreases monotonically with the memory size. Moreover, within a given memory hierarchy level, power can be reduced by memory banking - whose principle is to divide the address space in several smaller blocks, and to map these blocks to physical memory banks that can be independently enabled and disabled. Memory partitioning is also a performance-oriented optimization strategy, because of the reduced latency due to accessing smaller memory blocks. Arbitrarily fine partitioning is prevented since an excessively large number of small banks is area inefficient, imposing a severe wiring overhead -- which increases communication power and decreases performance. This presentation will introduce an electronic design automation (EDA) methodology for the design of hierarchical memory architectures in embedded data-intensive applications, mainly in the area of multidimensional signal processing. The input of this memory management framework is the behavioral specifications of the applications, that are assumed to be procedural and affine. Figure 1 shows an illustrative example of behavioral specification with 6 nested loops. This framework employs a formal model operating with integral polyhedra, using techniques specific to the data-dependence analysis employed in modern compilers. Different from previous works, three optimization problems - the data assignment to the memory layers (on-chip scratch-pad memory and off-chip DRAM), the mapping of multidimensional signals to the physical memories, and the banking of the on-chip memory (see Figure 2) - are addressed in a consistent way, based on the same formal model. The main design target is the reduction of the static and dynamic energy consumption in the memory subsystem, but the same formal model and algorithmic principles can be applied for the reduction of the overall time of access to memories, or combinations of these design goals.

Line and word segmentation is a key-step in any document image analysis system. It can be used for instance in handwriting recognition when separating words before their recognition. Line segmentation can also serve as a prior step before extracting the geometric characteristics of lines which are unique to each writer. Text line and word segmentation is not an easy task because of the following problems: 1) text lines do not all have the same direction in the handwritten text; 2) text lines are not always horizontal which makes their separation more difficult; 3) characters may overlap between successive text lines; 4) it is often confusing to distinguish between inter and intra word distances. In our method, line segmentation is done by using a smoothed version of the handwritten document which makes it possible to detect the main line components using a subsequent thresholding algorithm. The connected components of the resulting image are then assigned to a separate label which represents a line component. Then, each text region which intersects only with one line component is assigned to the same label of that line component. The Voronoi diagram of the image thus obtained is then computed in order to label the remaining text pixels. Word segmentation is performed by computing a generalized Chamfer distance in which the horizontal distance is slightly favored. This distance is subsequently smoothed in order to reflect the distances between word components and neglect the distance to dots and diacritics. Word segmentation is then performed by thresholding the distance thus obtained. The threshold depends on the characteristics of the handwriting. We have therefore computed several features in order to predict it, including: the sum of maximum distances within each line component, the number of connected components within the document and the average width and height of lines. The optimal threshold is then obtained by training a linear regression of those features on a training set of about 100 documents. This method achieved the best performance on the ICFHR Handwriting Segmentation Contest dataset reaching a matching score of 97.4% on line segmentation and 91% on word segmentation. The method has also been tested on the QUWI Arabic dataset reaching 97.1% on line segmentation and 49.6% on word segmentation. The relatively low performance of word segmentation in Arabic script is due to the fact that words are very close to each other with respect to English script. The proposed method tackles most of the problems of line and word segmentation and achieves high segmentation results. It can however be improved by combining it with a handwriting recognizer which will eliminates words which are not recognized.

Attenuators are extensively employed as an amplitude control circuit in communication and radar systems. Flatness, attenuation range, and bandwidth are typical specifications for attenuators. Most attenuators in previous studies rely on the basic topologies of the Pi-, T-, and distributed attenuators. The performance of the Pi- and T-attenuators, however, is affected substantially by the switch performance of transistors, and it is hard to obtain optimum flatness, attenuation range, and bandwidth with these attenuators. The conventional distributed attenuator also demands a large chip area for large attenuation ranges. We report the design of a new microwave/millimeter-wave CMOS attenuator. A design method is proposed and implemented in the attenuator to improve its flatness, attenuation range, and bandwidth. It is recognized that the Pi- and T-attenuators at a certain attenuation state inherently has the insertion-loss slope increasing as the frequency is increased. This response is owing to the off-capacitance of the series transistors. On the other hand, the distributed attenuators can be designed to have the opposite insertion-loss slope by shortening the transmission lines. The reason is that short transmission lines causes the center frequency be shifted higher. The proposed design method utilizes the two opposite insertion-loss slopes and is implemented for the Pi-, T-and distributed attenuators in a cascade connection. Over 10-67 GHz, the measured results exhibit attenuation flatness of 6.8 dB and attenuation range of 32-42 dB.

We propose a multimedia-based learning system to teach children with intellectual disabilities (ID) basic concepts in Science, Math and daily living tasks. The tutorials' pedagogical development is based on Mayer's Cognitive Learning Model combined with Skinner's Behaviorist Operant Conditioning Model. Two types of Arabic tutorials are proposed: (1) Statically generated tutorials, which are pre-designed by special needs instructors, and developed by animation experts. (2) Dynamically generated tutorials, which are developed using natural language processing and ontology building. Dynamic tutorials are generated by processing Arabic text, and using machine learning to query the Google engine and generate multimedia elements, which are automatically updated into an ontology system and are hence used to construct a customized tutorial. Both types of tutorials have shown considerable improvements in the learning process and allowed children with ID to enhance their cognitive skills and become more motivated and proactive in the classroom.

This paper presents a robust real-time vision framework that detects and tracks vehicles from stationary traffic cameras with certain regions of interest. The framework enables intelligent transportation and road safety applications such as road-occupancy characterization, congestion detection, traffic flow computation, and pedestrian tracking. It consists of three main modules:1) detection, 2) tracking, and 3) data association. To this end, vehicles are first detected using Haar-like features. In the second phase, a light-weight appearance-based model is built using random projections to keep track of the detected vehicles. The data association module fuses new detections and existing targets for accurate tracking. The practical value of the proposed framework is demonstrated with evaluation involving several real-world experiments and variety of challenges.

We will present an overview and in-progress report of a QNRF-sponsored project for research in the effects of using program visualization in teaching and learning computational thinking. Computers and computing have made possible incredible leaps of innovation and imagination in solving critical problems such as finding a cure for diseases, predicting a hurricane's path, or landing a spaceship on the moon. The modern economic conditions of countries around the world are increasingly related to their ability to adapt to the digital revolution. This, in turn, drives the need for educated individuals who can bring the power of computing-supported problem solving to an increasingly expanded field of career paths. It is no longer sufficient to wait until students are in college to introduce computational thinking. All of today's students will go on to live in a world that is heavily influenced by computing, and many of these students will work in fields that involve or are influenced by computing. They must begin to work with algorithmic problem solving and computational methods and tools in K-12. Many courses taught in K-12 (for example, math and science) teach problem solving and logical thinking skills. Computational thinking embodies these skills and brings them to bear on problems in other fields and on problems that lie at the intersection of these fields. In the same way that learning to read opens a gateway to learning a multitude of knowledge, learning to program opens a gateway to learning all things computational. Alice is a programming environment designed to enable novice programmers in creating 3-D virtual worlds, including animations and games. In Alice, 3-D models of objects (e.g., people, animals and vehicles) populate a virtual world and students use a drag and drop editor to manipulate the movement and activities of these objects. Alice for the Middle East - "Alice ME" is a research project funded by Qatar National Research Fund (QNRF) under their National Priorities Research Program (NPRP) that aims to modify the well-known Alice introductory programming software to be internationally and culturally relevant for the Middle East. In this project, we are working on developing new 3D models that provide animation objects encountered in daily lives (animals, buildings, clothing, vehicles, etc.) as well as artifacts that reflect and respect the heritage of Qatari culture. The new models will provide characters and images that enable students to create animations that tell the stories of local culture, thereby supporting the QNV 2030 aspiration for maintaining a balance between modernizations and preserving traditions. We are also working with local schools to develop an ICT curriculum centered on using Alice to help students learn computational thinking. We are also designing workshops to train teachers in using Alice and delivering this curriculum.

Translation of named entities (NEs) is important for NLP applications such as Machine Translation (MT) and Cross-lingual Information Retrieval. For MT, named entities are major subset of the out-of-vocabulary terms. Due to their diversity, they cannot always be found in parallel corpora, dictionaries or gazetteers. Thus, state-of-the-art MT systems need to handle NEs in specific ways: (i) direct translation which results in missing many out of vocabulary terms and (ii) blind transliteration of out of vocabulary terms which does not necessarily contribute to translation adequacy and may actually create noisy contexts for the language model and the decoder. For example, in the sentence "Dudley North visits North London", the MT system is expected to transliterate "North" in the former case, and translate "North" in the latter. In this work, we present a classification-based framework, that enables MT system to automate the decision of translation vs. transliteration for different categories of NEs. We model the decision as a binary classification at the token level: each token within a named-entity gets a decision label to be translated or transliterated. Training the classifier requires a set of NEs with token-level decision labels. For this purpose, we automatically construct a set of bilingual lexicon of NEs paired with the translation/transliteration decisions from two different domains: We heuristically extract and label parallel NEs from a large word aligned news parallel corpus and we use a lexicon of bilingual NEs collected from Arabic and Wikipedia titles. Then, we designed a procedure to clean up the noisy Arabic NE spans by part-of-speech verification, and heuristically filtering impossible items (e.g. verbs). For training, the data is automatically annotated using a variant of edit distance measuring the similarity between an English word and its Arabic transliteration. For test set, we manually reviewed the labels and fixed the incorrect ones. As part of our project, this bilingual corpus of named entities has been released to the research community. Using Support Vector Machines, we trained the classifier using a set of token-based, contextual and semantic features of the NEs. We evaluated our classifier both in the limited news and diverse Wikipedia domains, and achieved promising accuracy of 89.1%. To study the utility of using our classifier on an English to Arabic statistical MT system, we deployed it as a pre-translation component to the MT system. We automatically located the NEs in the source language sentences and used the classifier to find those which should be transliterated. For such terms, we offer the transliterated form as an option to the decoder. The impact of adding the classifier to the SMT pipeline resulted in a major reduction of out of vocabulary terms and a modest improvement of the BLEU score. This research is supported by the Qatar National Research Fund (a member of the Qatar Foundation) through grants NPRP-09-1140-1-177 and YSREP-1-018-1-004. The statements made herein are solely the responsibility of the authors.

There are many cities where urbanization occurs at a faster rate than that of communication infrastructure deployment. Mobile users with sophisticated devices are often dissatisfied with this lag in infrastructure deployment; their Internet connection is via opportunistic open Access Points for short durations, or via weak, unreliable, and costly 3G connections. With increased demands on network infrastructure, we believe that opportunistic networking, where user mobility is exploited to increase capacity and augment Internet reachability, can play an active role as a complimentary technology to improve user experience, particularly with delay insensitive data. Opportunistic forwarding solutions were mainly designed using a set of assumptions that have grown in complexity, rendering them unusable outside their intended environment. Figure 1 categorizes sample state-of-the-art opportunistic forwarding solutions based on their assumption complexity. Most of these solutions however are not designed for large scale urban environments. In this work, we believe to be the first to exploit the space syntax paradigm to better guide forwarding decisions in large scale urban environments. Space syntax, initially proposed in the field of architecture to model natural mobility patterns by analyzing spacial configurations, offers a set of measurable metrics that quantify the effect of road maps and architectural configurations on natural movement. By interacting with the pre-built static environment, space syntax predicts natural movement patterns in a given area. Our goal is to leverage space syntax concepts to create efficient opportunistic forwarding distributed solutions for large scale urban environments. We address two communication themes: (1) Mobile-to-Infrastructure: We propose a set of space syntax based algorithms that adapt to a spectrum of simplistic assumptions in urban environments. As depicted in Figure 1, our goal is to gain performance improvement across the spectrum, within each assumption category, when compared to other state-of-the-art solutions. We adopt a data driven approach to evaluate the space syntax based forwarding algorithms we propose, within each of three assumption categories, based on large scale mobility traces capturing vehicle mobility. Overall, our results show that our space syntax based algorithms perform more efficiently within each assumption category. (2) Infrastructure-to-Mobile: We propose a new algorithm, Select&Spray, which leverages space syntax, and enables data transfers to mobile destinations reached directly through the infrastructure or opportunistically via other nodes. This architecture consists of: (i) a select engine that identifies a subset of directly connected nodes with a higher probability to forward messages to destinations, and (ii) a spray engine residing on mobile devices that guide the opportunistic dissemination of messages towards destination devices. We evaluate our algorithm using several mobility traces. Our results show that Select&Spray is more efficient in guiding messages towards their destinations. It helps extend the reach in data dissemination to more than 20% of the interested destinations within very short delays, and successfully reaches almost 90% of the destinations in less than 5 minutes.

The use of more effective processing tools such as advanced video codecs in wireless sensor networks (WSNs) has enabled widespread adoption of video-based WSNs for monitoring and surveillance applications. Considering that in video-based WSN applications large amounts of energy resources are required for both compression and transmission of video content, optimizing the energy consumption is of paramount importance. There is a trade-off between the encoding complexity and compression performance in the sense that high compression efficiency comes at the expense of increased encoding complexity. On the other hand, there is a direct relationship between coding complexity and energy consumption. Since the nodes in a video sensor network (VSN) share the same wireless medium, there is also an issue with fairness of bandwidth allocation per each node. Nevertheless, the fairness of resource allocation (encoding and transmission energy) for nodes placed at different locations in VSNs has a significant effect on energy consumption. In our study, our objective is to maximize the lifetime of the network by reducing the consumption of the node with the maximum energy usage. Our research focuses on VSNs with linear topology where the nth node relays its data through the nth-1 node, and the node closest to the sink relays information from all the other nodes. In our approach, we analyze the relation between the fairness of nodes' resource allocation, video quality and VSNs' energy consumption to propose an algorithm for adjusting the coding parameters and fairness ratio of each node such that energy consumption is balanced. Our results show that by allocating higher fairness ratios to the closest nodes to the sink, we reduce the maximum energy consumption and achieve a more balanced energy usuge. For instance, in the case of a VSN with six nodes, by allocating the fairness ratios between 0.17 to 0.3 to the closer nodes to the sink, the maximum energy consumption is reduced by 11.28%, with standard deviation of nodes' energy consumption (STDen) of 0.09W compared to 0.25W achieved by the maximum fairness scheme.

Quantifying the Cybersecurity of Cloud Computing as a Mean Failure Cost

This work focuses on developing a contextual spellchecker to improve the correctness of input queries to a multi-lingual, cross-cultural robot receptionist system. Queries that have fewer misspellings will improve the robot's ability to answer them and in turn improve the effectiveness of the human-robot interaction. We focus on developing an n-gram model based contextual spell-checker to correct misspellings and increase the query-hit rate of the robot. Our test bed is a bi-lingual, cross-cultural robot receptionist, Hala, deployed at the Carnegie Mellon University in Qatar's reception area. Hala can accept typed input queries in Arabic and English and speak responses in both languages as she interacts with users. All input queries to Hala are logged. These logs allow the study of multi-lingual aspects, the influence of socio-cultural norms and the nature of human-robot interaction within a multicultural, yet primarily ethnic Arab, setting. A recent statistical analysis has shown that 26.3% of Hala's queries are missed. The missed queries are due to either Hala not having the required answer in the knowledge base or due to misspellings. We have measured that 50% are due to misspellings. We designed, developed and assessed a custom spellchecker based on an n-gram model. We focused our efforts on a spellchecker for the English mode of Hala. We trained our system on our existing language corpus consisting of valid input queries making the spellchecker more specific to Hala. Finally, we adjusted the n in the n-gram model and evaluated the correctness of the spellchecker in the context of Hala. Our system makes use of the Hunspell, which is an engine that uses algorithm based on n-gram similarity, rule and dictionary based pronunciation data and morphological analysis. Misspelled words are passed through the Hunspell spellchecker and the output is a list of possible words. Utilizing the list of words, we apply our n-gram model algorithm to find which word is best suited in a particular context. The model calculates the conditional probability P(w|s) of a word w given the previous sequence of words s, that is, predicting the next word based on the preceding n-1 words. To assess the effectiveness of our system, we evaluate it using 5 different cases of misspelled word location. The table below lists our results, correct indicates when the sentence is correctly spellchecked and incorrect when the sentences did not change after passing through the spellchecker, or the sentences included transliterated Arabic, or were incorrectly spellchecked which resulted in loss of semantics. Refer to table. We observed that context makes the spellchecking of a sentence more sensible resulting in a higher hit rate in Hala's knowledge base. For case 5, despite having more context than the previous cases, the hit rate is lower. This is because other sources of errors were introduced such as user making use of SMS languages or mixture of English and Arabic. In our future work we would like to tackle the above-mentioned problems and also work on a Part-of-Speech tagging system that would help in correcting real-word mistakes.

Abstract This study began focused on the use of traditional knowledge in promoting sustainable development in crisis conditions. Presented the question: How have successful community- level sustainable development efforts undertaken under crisis conditions drawn upon indigenous knowledge to achieve positive outcomes? The study is a cross case analysis. The three cases addressed in this study have explained some of the ways that indigenous knowledge has played significant positive roles in promoting sustainable development for communities living under crisis conditions in Palestine. Indigenous knowledge community based patterns indicated significant focus on strengths of local culture, social cohesion, the integration process, and special advantages for policy implementation from the community level as key components of sustainable development in crisis conditions. This study especially focuses on efforts to implement sustainable development in crisis conditions. As the World Commission on Environment and Development, better known as the Brundtland Commission, explained in its seminal report (1987), the core problem for sustainable development is the need to integrate social development, economic development, and environmental protection to ensure “development that meet the needs of the present without compromising the ability of the future generations to meet their own needs” (World Commission on Environment and Development 1987, p. 8). And as that report and subsequent studies indicate, too often the social development dimension of the living triangle has been ignored or dramatically undervalued as those involved in development have concentrated on economic development and to some extent environmental protection (World Commission on Environment and Development 1987). In addition to the important ongoing problem of lack of focus on social aspects, sustainable development is particularly important and especially challenging in crisis conditions that include war, terrorism, and civil disorder and their aftermath. This research specifically considers the challenges of sustainable development in the Palestinian context with sensitivity to the need for the integration of all three elements of the living triangle and with concern for the special challenges presented by efforts to achieve sustainable development in crisis conditions. The study contributes to theory by analyzing common elements from the case studies and providing a set of testable propositions, grounded in those successful experiences that can be a starting point for building theory. Practically, the study has generated lessons that sustainable development policy implementers and decision makers can learn from when addressing sustainable development in different crisis conditions contexts such as the aftermath of what is called the “Arab Spring” contexts.

Qatar's rich Arabic heritage is not only captured in its buildings, artworks and stories, but also in the living memory of its people. Historians and ethnographers work to capture these stories by interviewing people in “oral history” projects, typically one by one. This is, naturally, a slow process, which can only record selected highlights of a people's rich memory. We here introduce a digital infrastructure that enables crowd-sourcing and distribution of Qatar's oral history. The goal is to inspire people to actively participate in shaping their country's historic record. People in Qatar as well as those living overseas will be stimulated to participate, thus weaving a rich heritage tapestry available electronically to Qataris and tourists alike. Each user will have our software installed as an app on their smartphone. While they are moving though their environs, users are prompted to create audio recording using our app. As in an interview with an ethnographer, they are guided through a set of questions, one at a time. The person acting as the Oral Historian creates the dynamically configurable script of questions and further defines time limits for each answer. If a response is brief, the app prompts for more detail, if a response is overly lengthy, the app prompts for closure on that question. Our software automatically captures some basic metadata: the time, GPS location, and length of the recording. It can further prompt for semi-structured metadata from its user, such as descriptions of their surroundings and the period to which the recording refers. Users are also prompted to upload any photos, documents, or videos that might relate to their audio contribution. At the end of a recording, a user is asked if they wish to provide personal data, e.g., name and age. The system does not automatically use registration account details as a user might be accompanied by another person who contributes to the oral history recording. These captured oral histories are grouped into collections and curated by an Oral Historian to prevent misuse and ensure quality. They may additionally decide to periodically publish a new set of questions to the registered users, for example to enrich particular topic areas in the collection. The end user software is available as a smartphone app, whereas the interface for the historian is server-based for ease of use. The underlying infrastructure uses the Open Source digital library system Greenstone, which has a pedigree of two decades (www.greenstone.org). It is sponsored by UNESCO as part of its "Information for All" programme, and its user interface has been translated into over 50 languages. Recent developments enable mobile phone operation and multimedia content. Greenstone therefore provides an ideal platform to deliver this integrated, mobile infrastructure for crowd-sourcing oral history information. The captured oral histories and any accompanying multimedia artefacts are sent to a central library where Greenstone's content management tools are available to the curating Oral Historian. The items are thus integrated into an evolving, public collection that are available to mobile and web users alike.

Language and culture are bound together. In Arabic, courtesy expressions play an important role. Consequently, a learner should be aware of them in order to fully master the Arabic language. The current research studies the compliment responses in Colloquial Arabic and their use when teaching Arabic as a foreign language. The speech act of complimenting was chosen because of the important role it plays in human communication. Compliments strengthen solidarity between the speakers and are an explicit reflection of cultural values. The first part of the study was a comparative ethnographic study on compliment responses in peninsular Spanish and in Lebanese Arabic. 72 selected members of a Lebanese and a Spanish social network participated in the research. The independent variables were: origin, age and gender. In both social networks, parallel communicative situations were created. The participants were linked by kinship or friendship and paid a compliment on the same topic. Secret recordings were used in order to register these communicative interactions and create a corpus formed with natural conversations. Compliment response sequences were analysed following a taxonomy created by the researcher for the specific study of the Spanish and Lebanese corpora. In the Lebanese corpus, formulaic expressions and invocations against the 'evil eye' were used. In Arabic and Islamic societies, it is believed that a compliment could attract the 'evil eye' if it is not accompanied by expressions invoking God's protection. In the Spanish corpus, both long and detailed explanations were frequently used. In the second part of the research, a corpus of courtesy expressions in colloquial Arabic is being built. The corpus of the current research could serve for future studies in the field of Arabic dialectology and sociolinguistics as it is the first one to include all the different Arabic dialects. The researcher will study the relationship between language and culture in Arabic societies. Participants of the second part of research are female Arab University students with an advance proficiency level of English and French. The independent variable is origin. Muted videos are the instrument to collect the data for this study. Three different videos for compliments about physical appearance, belongings and skills were recorded in Beirut and Bahrain. Students are requested to recreate the dialogue between the characters in Colloquial Arabic. The compliment response sequence is collected through this instrument because it enhances the students' creative freedom. The objectives of the study are: - Building a corpus of courtesy expressions in colloquial Arabic and conducting a comparative analysis of the formulaic responses to compliments in all Arabic dialects. - Studying if courtesy expressions are included in textbooks for teaching Arabic as a foreign language and if they are currently taught in Institutions and Universities. The results of the present research have some pedagogical implications. Courtesy expressions in spoken Arabic are essential and therefore should be introduced in the language classroom through real language examples. Developing the pragmatic competence plays an important role in teaching foreign languages and it helps Arabic learners to become intercultural speakers.

This presentation provides systematic evidence on an emergent debate about a Muslim woman's dress and her perceived credibility as a witness in a court context. The objective of this research is to understand how Muslim women's dress impacts their perceived credibility. The issue of testifying in western courts while wearing either a head veil (hijab) or a face veil (niqab) has been strongly contested on the grounds that physically seeing the witness's face helps observers judge her credibility (e.g., R. v. N.S., 2010). Canada's Supreme Court (N.S. v. Her Majesty the Queen, et al., 2012) ruled that judges will disallow the niqab "whenever the effect of wearing it would impede an evaluation of the witness's credibility." In 2010, an Australian judge ruled that a Muslim woman must remove her full veil while giving evidence before a jury. In 2007, the UK guidance on victims also indicated that the niqab may affect the quality of evidence given in the court room. All of those decisions and opinions run contrary to systematic research. Psychological studies suggest that nonverbal cues are not only poor indicators of veracity, but that they are the least useful indicators of deception (e.g., DePaulo et al., 2003, Vrij, 2008). This presentation discusses results of a research project that examined Muslim women's credibility. Using a quasi-experimental design, three groups of Muslim women lied or told the truth while testifying about a mock crime: 1) women without any coverings (safirat), 2) women wearing hijab (muhjabat) and 3) women wearing niqab (munaqabat). Videos of these women were then shown to audiences who assessed the credibilityof the witnesses. The research further explored the witness's general perceptions of being an eyewitness within the court system, and to what extent (if any) their dress impacted their perceptions. The presentation fits within the Social Sciences, Arts and Humanities thematic pillar of Qatar's National Research Strategy. It more particularly fits within two of the grand challenges: Managing Transition to a Diversified Knowledge- based Society: Build a knowledge-based society by emphasizing a robust research culture, and Holistic and Systematic Assessment of the Rapidly Changing Environment: Foster motivation, scholarship, and prosperity among Qatari nationals and expatriates along with cultural accommodations that are in-sync with modern practice.

Geolocated video represents an opportunity for innovation in journalism and media. Reported here are the results of a proof-of-concept research project demonstrating and assessing the process of creating geolocated video in journalism and media. Geolocated refers to tagging video or other media content with geographic location information, usually obtained from GPS data. Geolocation is a growing feature of news and media content. It is being used increasingly in photographs and social media, including Twitter posts. Geolocation in video is a relatively new application. Employing a proof-of-concept method, this project demonstrates how geolocated video (using Kinomap technology) serves several purposes in news and media (see Figure 1). First, geolocation allows the content to be automatically uploaded to Google Earth or other mapping software available online. This enables others anywhere to access that content by location. It is an aspect of Big Data, in that it permits mapping or other analysis of geolocated content. Such analysis can reveal a variety of insights about the production of media content. Second, geolocation, in concert with other digital watermarking, provides a useful tool to authenticate video. Geolocation in a digital watermark is a valuable tool to help establish the veracity of video or other content. Geolocation can help document when and where video produced by users or freelancers or even professionally employed reporters covering a sensitive story was captured. Reporters (or lay-citizens) providing smartphone video of an event can use geolocation to help establish time, date and location. Third, geolocation supports freelance media practitioners in protecting copyright or intellectual property rights by helping provide a strong digital watermark that includes their identity and the precise time, date and location the video was captured. Fourth, geolocated video represents an opportunity for a new approach to storytelling including in digital maps. Geolocated videos have been produced and made available on Google Earth. Viewing can occur immersively with mobile or wearable devices (e.g., augmented reality, Google Glass). This project aligns with three of the Qatar Research Grand Challenges. First, it supports Culture, Arts, Heritage, Media and Language within the Arabic Context, providing a medium to foster investment in the nation's legacy in Arabic arts, design, architecture, and cultural programs. Second, it supports Holistic and Systematic Assessment of the Rapidly Changing Environment, exploring the roles of communication (e.g., education, journalism, traditional and social media channels) in fostering awareness of social issues. Third, it supports Sustainable Urbanization-Doha as a smart city, demonstrating a state-of-the-art communications technology especially effective and efficient in facilitating location-based communications challenges and needs.

This presentation draws on data from a four-year longitudinal study of undergraduate literacy development at an English-medium university in Qatar. While previous studies have documented literacy development at the primary and secondary school levels (Christie & Derewianka, 2010, Coffin, 2006) and much has been researched about the nature of writing genres at the graduate and professional levels (Hyland, 2009, Swales, 1990, 2004), there is a limited body of research on writing at the undergraduate level (Ravelli & Ellis, 2005). The limited work at this level has been either largely qualitative (Leki, 2007, Sternglass, 1997) or primarily text-based (Byrnes, 2010, Colombi, 2002, Nessi, 2009, 2011, North, 2005, Woodward-Kron, 2002, 2005, 2008). Recently, drawing on systemic functional linguistics (SFL) and genre pedagogy, the work of Dreyfus (2013), and Humphrey and Hao (2013) has begun to shed light on the nature of disciplinary writing and writing development at the undergraduate level. However, there is much to learn about the nature of undergraduate writing. This study aims to contribute to this area by examining faculty expectations, student trajectories, and development from a text-based and ethnographic approach. This presentation reports on different trajectories of academic literacy development by presenting four case studies of multilingual students at an English-medium university in the Middle East. While there have been several studies that have looked at the developmental literacy trajectories of undergraduate students (Leki, 2007, Sternglass, 1997, Zamel, 2004) using case studies, they have not closely and systematically examined writing development from a text-based approach. This paper aims to contribute to the growing interest in understanding the nature of undergraduate writing, especially among multilingual students, by using detailed case studies and analysis of student writing longitudinally. The presenters will describe the college experiences of four students and present longitudinal analysis of their writing over four years in the disciplines of business administration and information systems. The findings suggest that students enter the university with differing pre-college experiences that shape their college experiences and impact their rate of development. While personal, social, and academic development is documented in all cases, there are differences between those who came in with a strong academic background in English and those that had limited experiences with English academic reading and writing. Using the tools of Systemic Functional Linguistics (Halliday, 1984), the text analysis of student writing shows development as their writing progressively becomes more academic (with increasing use of nominalizations and abstractions), analytical (with increasing use of evaluations), and better organized, with differences among the four case studies. Overall, the findings suggest that while weaker students do improve their literacy skills while in college, many still graduate with inconsistencies and infelicities in their writing. Documenting the literacy development of university students in Qatar is pivotal as Qatar continues to invest in English-medium education to build its human capital. This project aims to generate insights for curricular planning and assessment in Qatar and a basis for research on academic literacy development that will be of interest to scholars internationally.

Universal surveys—such as the World Values Survey—seek to promote generalizability across contexts. But what if two different cultures interpret and respond to a general question in two different ways (e.g., King et al. 2004)? Using this methodological conundrum as a starting point, over the past year I have a led a research team of four faculty and twelve students—drawn from Northwestern University in Qatar, Qatar University, and Georgetown University in Qatar—in creating, translating, and analyzing a context-sensitive survey of the Qatari population, funded through a Qatar National Research Fund UREP (Undergraduate Research Experience Program) grant. The survey was conducted by Qatar University's Social and Economic Survey Research Institute (SESRI) from January 15 to February 3 for a total of 798 Qatari respondents, making it a professional and valuable addition to the literature. Further, we were able to insert many questions that had never previously been asked of the population, including ones spanning the relative importance of tradition versus modern symbolism, specific opinions on the national education reforms, personal versus state priorities, satisfaction with particular welfare benefits offered by the state, and measures of religiosity. Both the process of creating a contextualized survey for the Qatari population—including what could and could not be asked, and how sensitive concepts were translated—as well as the fascinating results, which have opened up new avenues of research into the sociopolitical transformations of the Qatari people, are well worth presenting to the community and receiving feedback. Even more importantly, the insights gained from how we contextualized the survey can be applied to improve the current state of social science survey research in Qatar. The explosion of survey research in Qatar—pioneered by the Qatar Statistics Authority and Qatar University's SESRI, and recently joined by the multinational surveys of the World Values Survey, Harris Polling, Zogby's, and the Arab Barometer—demonstrates the need for questions that are contextually and culturally sensitive and ensure full understanding of the Qatari population. The ability to present my work to the Qatar Foundation Annual Research Conference will provide valuable feedback and networking opportunities with likeminded professionals, researchers, and community members in my quest to continue this collaborate and important research effort. Citation: King, Gary, Christopher Murray, Joshua Salomon, and Ajay Tandon. 2004. “Enhancing the Validity and Cross-Cultural Comparability of Measurement in Survey Research.” American Political Science Review 98 (1): 191-207.

The Qatar National Vision aims at “transforming Qatar into an advanced country by 2030, capable of sustaining its own development and providing for a high standard of living for all of its people for generations to come”. The grand challenge of Human Capacity Development aims to develop sustainable talent for Qatar's knowledge economy in order to meet the needs for a high-quality workforce. In order for Qatar to achieve its 2030 National Vision and become an advanced country by 2030, it has to train its citizens to function in a globalized and competitive world. Important skills for Qatari to function in the 21st century are communication and use of emerging technologies skills. This presentation will propose a training model to develop the Qatar workforce for the 21st century using emerging learning technologies. The training model was based on a mobile learning research project funded by the Qatar Foundation through the Qatar National Research Fund. The project is a collaborative research project with Qatar University, Qatar Petroleum, Qatar Wireless Innovation Centre, and Athabasca University, Canada. The project developed and implemented training lessons on Communication Skills for the oil and gas industry using mobile technology to deliver the training. The workers were employed at Qatar Petroleum and completed the training as part of their professional development to improve their English communication skills. Results from the project showed that workers performance improved after they completed the training and they reported that use of mobile technology to deliver the training provides flexibility for learning on the job. They suggested that the training should be more interactive and game-like. This is important since today's young workers are comfortable using mobile technologies and they need to be motivated to learn using the mobile technologies. The proposed Qatar National Training Model (QNTM) (Figure 1) is based on the mobile learning research project funded by the Qatar Foundation through the Qatar National Research Fund. In the QNTM, the learner/trainee/worker is at the center of the learning since the goal of training is to provide the knowledge and skills to improve workers' performance on the job. The design of the training must follow good learning design principles including preparing the learner for the training, providing activities for the learners to complete to improve their knowledge and skills, allowing learners to practice to improve their performance, certifying learners based on their performance, and providing opportunities for learners to transfer what they learn to the job environment. The delivery of the training should be flexible using a blended approach that includes face-to-face, hands-on, E-learning, mobile learning, and online learning. A variety of learning strategies such as practice with feedback, tutorials, simulations, games, and problem solving can be used depending on the learning outcomes to be achieved. The proposed Qatar National Training Model will allow for learner-centered training, lifelong learning, just-in-time learning, learning in context, developing skills required for 21st century learning, and interaction between learners and between learners and the trainer using social media.