Arabic Spelling Correction using Supervised Learning

In this work, we address the problem of spelling correction in the Arabic language utilizing the new corpus provided by QALB (Qatar Arabic Language Bank) project which is an annotated corpus of sentences with errors and their corrections. The corpus contains edit, add before, split, merge, add after, move and other error types. We are concerned with the first four error types as they contribute more than 90% of the spelling errors in the corpus. The proposed system has many models to address each error type on its own and then integrating all the models to provide an efficient and robust system that achieves an overall recall of 0.59, precision of 0.58 and F1 score of 0.58 including all the error types on the development set. Our system participated in the QALB 2014 shared task "Automatic Arabic Error Correction" and achieved an F1 score of 0.6, earning the sixth place out of nine participants.Comment: System description paper that is submitted in the EMNLP 2014 conference shared task "Automatic Arabic Error Correction" (Mohit et al., 2014) in the Arabic NLP workshop. 6 page

Map++: A Crowd-sensing System for Automatic Map Semantics Identification

Digital maps have become a part of our daily life with a number of commercial and free map services. These services have still a huge potential for enhancement with rich semantic information to support a large class of mapping applications. In this paper, we present Map++, a system that leverages standard cell-phone sensors in a crowdsensing approach to automatically enrich digital maps with different road semantics like tunnels, bumps, bridges, footbridges, crosswalks, road capacity, among others. Our analysis shows that cell-phones sensors with humans in vehicles or walking get affected by the different road features, which can be mined to extend the features of both free and commercial mapping services. We present the design and implementation of Map++ and evaluate it in a large city. Our evaluation shows that we can detect the different semantics accurately with at most 3% false positive rate and 6% false negative rate for both vehicle and pedestrian-based features. Moreover, we show that Map++ has a small energy footprint on the cell-phones, highlighting its promise as a ubiquitous digital maps enriching service.Comment: Published in the Eleventh Annual IEEE International Conference on Sensing, Communication, and Networking (IEEE SECON 2014

Heat transfer enhancement downstream of vortex generators on a flat plate

This investigation was conducted in order to better understand the augmentation of forced convective heat transfer when a single row of counter-rotating vortex blades is attached to a flat surface. The major emphasis of the work is to study the way in which vortex generators augment the heat transfer coefficient of an initially-laminar boundary layer over a flat, constant-heat-flux surface exposed to favorable free-stream pressure gradients. Particular emphasis is placed on the relationship between the geometry of vortex generators and the augmentation of local and overall heat transfer coefficients. The behavior of the boundary layer downstream of vortex generators is partially explored;This dissertation includes results of an experimental investigation that indicates the amount of heat transfer enhancement depends on the vortex blade height and arrangement on the plate surface. The local enhancement of heat transfer coefficient was increased up to 300% over that for a plain flat plate mainly because of high turbulence produced over the region adjacent to the plate surface, resulting in increased mixing of the slower fluid near the plate surface with the free stream. A set of guidelines for the design of more efficient surface with vortex generators was proposed

It's the Human that Matters: Accurate User Orientation Estimation for Mobile Computing Applications

Ubiquity of Internet-connected and sensor-equipped portable devices sparked a new set of mobile computing applications that leverage the proliferating sensing capabilities of smart-phones. For many of these applications, accurate estimation of the user heading, as compared to the phone heading, is of paramount importance. This is of special importance for many crowd-sensing applications, where the phone can be carried in arbitrary positions and orientations relative to the user body. Current state-of-the-art focus mainly on estimating the phone orientation, require the phone to be placed in a particular position, require user intervention, and/or do not work accurately indoors; which limits their ubiquitous usability in different applications. In this paper we present Humaine, a novel system to reliably and accurately estimate the user orientation relative to the Earth coordinate system. Humaine requires no prior-configuration nor user intervention and works accurately indoors and outdoors for arbitrary cell phone positions and orientations relative to the user body. The system applies statistical analysis techniques to the inertial sensors widely available on today's cell phones to estimate both the phone and user orientation. Implementation of the system on different Android devices with 170 experiments performed at different indoor and outdoor testbeds shows that Humaine significantly outperforms the state-of-the-art in diverse scenarios, achieving a median accuracy of $15^\circ$ averaged over a wide variety of phone positions. This is $558\%$ better than the-state-of-the-art. The accuracy is bounded by the error in the inertial sensors readings and can be enhanced with more accurate sensors and sensor fusion.Comment: Accepted for publication in the 11th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (Mobiquitous 2014

Ultrasound Prediction of the Mode of Delivery in the Second Stage of Labor Using the Fetal Head-Symphysis Distance

OBJECTIVE: To evaluate whether the fetal head-symphysis distance measured by three-dimensional transperineal ultrasound during the active second stage predicts operative delivery. DESIGN: Prospective observational study. SETTING: University hospital, Bologna, Italy. POPULATION: Seventy-one nulliparous women at term in active second stage of labor. METHODS: We acquired a series of sonographic volumes at the beginning of the active second stage (T1) and every 20 min thereafter (T2, T3, T4, T5, T6) until delivery. All volumes were retrospectively analyzed and head-symphysis distance was measured for each acquisition. We compared head-symphysis distance between women with spontaneous vaginal delivery and those with operative delivery. Receiver operator characteristic curves were constructed to estimate the accuracy of head-symphysis distance in the prediction of operative delivery. Logistic regression was used to identify independent variables associated with operative delivery. MAIN OUTCOME MEASURES: Operative delivery (vacuum or cesarean). RESULTS: Of the women included, 81.7% had a spontaneous vaginal delivery and 18.3% underwent operative delivery. Women with spontaneous vaginal delivery had shorter head-symphysis distance than women in the operative delivery group at T1 (p < 0.001), T2 (p < 0.001) and T3 (p = 0.025), whereas no significant differences were recorded thereafter. Receiver operator characteristic curves revealed accuracy values of 81.0%, 87.9% and 77.6% in the prediction of operative delivery at T1, T2 and T3, respectively. At multivariate logistic regression head-symphysis distance and epidural analgesia were the only independent predictors of operative delivery among ultrasonographic, maternal and intrapartum variables. CONCLUSIONS: Ultrasonographic measurement of head-symphysis distance in the second stage of labor can be used to predict operative delivery