Tweet2Vec: Learning Tweet Embeddings Using Character-level CNN-LSTM Encoder-Decoder

We present Tweet2Vec, a novel method for generating general-purpose vector representation of tweets. The model learns tweet embeddings using character-level CNN-LSTM encoder-decoder. We trained our model on 3 million, randomly selected English-language tweets. The model was evaluated using two methods: tweet semantic similarity and tweet sentiment categorization, outperforming the previous state-of-the-art in both tasks. The evaluations demonstrate the power of the tweet embeddings generated by our model for various tweet categorization tasks. The vector representations generated by our model are generic, and hence can be applied to a variety of tasks. Though the model presented in this paper is trained on English-language tweets, the method presented can be used to learn tweet embeddings for different languages.Comment: SIGIR 2016, July 17-21, 2016, Pisa. Proceedings of SIGIR 2016. Pisa, Italy (2016

Index of Potential Contamination for Intestinal Schistosomiasis among School Children of Raya Alamata District, Northern Ethiopia

Effective and sustainable control of Schistosomamansoni infection requires identifying subpopulations that are at risk of infection. A cross-sectional epidemiological survey was conducted in children of four primary schools in Raya Alamata District of Ethiopia to determine the prevalence and intensity of infection, and index of potential contamination of intestinal schistosomiasis. Fecal samples of 500 (266 males and 234 females) subjects aged 6-19 years were processed using Kato Katz thick smear field technique. Questionnaire survey was also deployedto assess associated risk factors among infected children. Out of the examined children, 101(20.2%) were infected by S. mansoni. The prevalence of infection differed significantly among the age groups (÷2= 6.93; P<0.05). High prevalence of infection was observed among children of 10-14 years old. Intensity of S. mansoni infection was low, only 3.96% had heavy infection intensity. Children of 10-14 years age have high infection intensity than any age group (÷2= 12.5; P<0.05). Index of potential contamination value showed that to a great extent children of 10-14 years were responsible to contaminate the environment with the bulk of S. mansoni eggs and for the transmission and maintenance of the disease in the area. Swimming habit (AOR= 3.66; P<0.05), frequency of water contact (AOR= 8.15; P<0.05) and treatment history (AOR 2.1; CI 1.3-3.3, P= 0.002) were the potential associated risk factors for S. mansoni infection. Schistosomamansoni infection did not show any significant association with gender, household water source, bathing and family occupation. Intestinal schistosomiasis is a public health problem, and to a great extent children of 10-14 years age group were responsible in the transmission and maintenance of the infection.Key words: Ethiopia Infection prevalence, Schistosomiasis, IPC, Tigray

Unsupervised, Efficient and Semantic Expertise Retrieval

We introduce an unsupervised discriminative model for the task of retrieving experts in online document collections. We exclusively employ textual evidence and avoid explicit feature engineering by learning distributed word representations in an unsupervised way. We compare our model to state-of-the-art unsupervised statistical vector space and probabilistic generative approaches. Our proposed log-linear model achieves the retrieval performance levels of state-of-the-art document-centric methods with the low inference cost of so-called profile-centric approaches. It yields a statistically significant improved ranking over vector space and generative models in most cases, matching the performance of supervised methods on various benchmarks. That is, by using solely text we can do as well as methods that work with external evidence and/or relevance feedback. A contrastive analysis of rankings produced by discriminative and generative approaches shows that they have complementary strengths due to the ability of the unsupervised discriminative model to perform semantic matching.Comment: WWW2016, Proceedings of the 25th International Conference on World Wide Web. 201

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Performance of Wind Pump Prototype

A wind pump prototype with 3.6 m rotor diameter, 19 m hub height above ground and 0.22 mm reciprocating pump stroke has been developed at the Department of Mechanical Engineering, Mekelle University. The prototype was designed and manufactured locally. Theoretical model based on combined efficiency of the rotor and the reciprocating pump was used to estimate the performance of the wind pump. One year wind speed data collected at 10 m height was extrapolated to the wind pump hub height using wind shear coefficient. The model assumed balanced rotor power and reciprocating pump, hence did not consider the effect of pump size. The theoretical model estimated the average daily discharge to be around 50 m3 and 30 m3 at 8 m and 12 m head, respectively. The prototype was tested with the same pump stroke but two different size pumps at two different heads. The pumps were with internal diameter of 55 and 70 mm and the test heads were at 8 and 12 m. Measurement of the flow rate, rotational speed and wind speed were made every 10 minutes during the test period. The data collected were analyzed to find the performance of the wind pump at the two test heads and two pump sizes. The flow rate data was plotted against binned wind speed data to determine the linear fit function. The linear fit function was then used to estimate the flow rate at any wind speed. With the 55 mm pump the measured average daily discharge was 20 and 19 m3 at 8 m and 12 m head, respectively. With the 70 mm pump the measured average daily discharge was 41 m3 and 30 m3 at 8 m and 12 m head, respectively.Keywords: Wind pump, Windmill, Performance testing, Pump efficiency, Pump discharge, Ethiopia