Temporal Localization of Fine-Grained Actions in Videos by Domain Transfer from Web Images

We address the problem of fine-grained action localization from temporally untrimmed web videos. We assume that only weak video-level annotations are available for training. The goal is to use these weak labels to identify temporal segments corresponding to the actions, and learn models that generalize to unconstrained web videos. We find that web images queried by action names serve as well-localized highlights for many actions, but are noisily labeled. To solve this problem, we propose a simple yet effective method that takes weak video labels and noisy image labels as input, and generates localized action frames as output. This is achieved by cross-domain transfer between video frames and web images, using pre-trained deep convolutional neural networks. We then use the localized action frames to train action recognition models with long short-term memory networks. We collect a fine-grained sports action data set FGA-240 of more than 130,000 YouTube videos. It has 240 fine-grained actions under 85 sports activities. Convincing results are shown on the FGA-240 data set, as well as the THUMOS 2014 localization data set with untrimmed training videos.Comment: Camera ready version for ACM Multimedia 201

Trends and Correlates of Breast Cancer Screening among Florida Women: Analysis of 2001 and 2008 BRFSS Data

This study examined trends and correlates of breast cancer screening among women aged ≥40 years old by race/ethnicity using the 2001 and 2008 Florida Behavioral Risk Factor Surveillance System (BRFSS). Breast cancer screening was measured using both mammography and clinical breast examination (CBE). The total sample size was 10,386, with 4,938 women in the 2001 BRFSS and 5,448 in 2008. Significant disparities in breast cancer screening by race/ethnicity were found both in 2001 and 2008, with Hispanics having the lowest screening participation, compared to non-Hispanic whites and non-Hispanic Blacks. In 2008, non-Hispanic Black women had the highest percentage of timely mammography, CBE, and both mammography and CBE combined than non- Hispanic white and Hispanic women. Not having health insurance was a strong predictor of non-screening across all racial/ethnic groups. Whereas age, being married, and having a college education or higher were negatively correlated with lack of timely breast cancer screening among non-Hispanic Whites, poor health status was positively associated with lack of timely screening. Among Hispanics, the variables of having some college education or college degree or higher were positively associated with lack of CBE and with mammography and CBE. Our findings suggest that both an expansion of health insurance coverage as well as the timely promotion of screening across education and racial/ethnic segments may be important for breast cancer prevention

Productive and reproductive performance of local cows under farmer’s management in central Tigray, Ethiopia

The study was conducted on 408 indigenous cows maintained under farmer’s management in eight districts of central Tigray, Ethiopia. A total of 208 small-scale dairy farm owners were randomly selected and interviewed with structured questionnaire to obtain information on the productive and reproductive performance of indigenous cows. The results of the study showed that the mean age at first calving (AFC) was 43.3 ±2.7 months, number of services per conception (NSC) was 2.7±0.5, days open (DO) was 201.47±61.21 days, calving interval (CI) was 468.33±71.42 days, lactation length (LL) was 206.17±32.33 days, lactation milk yield (LMY) was 414.65±53.69 litres for indigenous cows. The estimated value for productive and reproductive traits had higher than normal range in indigenous cows. This calls for a planned technical and institutional intervention for improved support services for appropriate breeding programs, improved cows and adequate veterinary health services. Key words: Productive and Reproductive Performance, Local Cows

Learning from Partially Annotated Data: Example-aware Creation of Gap-filling Exercises for Language Learning

Since performing exercises (including, e.g., practice tests) forms a crucial component of learning, and creating such exercises requires non-trivial effort from the teacher. There is a great value in automatic exercise generation in digital tools in education. In this paper, we particularly focus on automatic creation of gapfilling exercises for language learning, specifically grammar exercises. Since providing any annotation in this domain requires human expert effort, we aim to avoid it entirely and explore the task of converting existing texts into new gap-filling exercises, purely based on an example exercise, without explicit instruction or detailed annotation of the intended grammar topics. We contribute (i) a novel neural network architecture specifically designed for aforementioned gap-filling exercise generation task, and (ii) a real-world benchmark dataset for French grammar. We show that our model for this French grammar gap-filling exercise generation outperforms a competitive baseline classifier by 8% in F1 percentage points, achieving an average F1 score of 82%. Our model implementation and the dataset are made publicly available to foster future research, thus offering a standardized evaluation and baseline solution of the proposed partially annotated data prediction task in grammar exercise creation.Comment: 12 pages, Accepted in the 18th Workshop on Innovative Use of NLP for Building Educational Application

A multianalytical approach to investigate stone biodeterioration at a UNESCO world heritage site: the volcanic rock-hewn churches of Lalibela, Northern Ethiopia.

A multianalytical approach combining Optical Microscopy (OM), Backscattered Variable Pressure Scanning Electron Microscopy + Energy Dispersive X-ray Spectroscopy (VP-BSEM + EDS), Powder X-ray Diffractometry (PXRD), Raman Spectroscopy, and Microbiological techniques has been applied to characterize decay products and processes occurring at the surface of two rockhewn churches (Bete Gyorgis and Bete Amanuel) at the UNESCO’s World Heritage site of Lalibela, Northern Ethiopia. The two churches were carved into volcanic scoria deposits of basaltic composition. In their geological history, the Lalibela volcanic rocks underwent late to post-magmatic hydrothermal alteration together with partial laterization and are therefore characterized by a decay-prone highly vesicular microtexture with late stage to post-magmatic precipitation of secondary mineral phases (calcite–zeolite–smectite). The main objective of the study was to gain a better insight into the weathering products and mechanisms affecting the surface of the stone monuments and to assess the relative contribution of natural “geological” weathering processes versus biological/salt attack in stone decay at this unique heritage site. Results indicate that while the main cause of bulk rock deterioration and structural failure could be related to the stone inherited “geological” features, biological attack by micro- (bacteria) and/or macro- (lichens) organisms is currently responsible for severe stone surface physical and chemical weathering leading to significant weakening of the stone texture and to material loss at the surface of the churches walls. A prompt and careful removal of the biological patinas with the correct biocidal treatment is therefore recommended

A multianalytical approach to investigate stone biodeterioration at a UNESCO world heritage site: the volcanic rock-hewn churches of Lalibela, Northern Ethiopia.

A multianalytical approach combining Optical Microscopy (OM), Backscattered Variable Pressure Scanning Electron Microscopy + Energy Dispersive X-ray Spectroscopy (VP-BSEM + EDS), Powder X-ray Diffractometry (PXRD), Raman Spectroscopy, and Microbiological techniques has been applied to characterize decay products and processes occurring at the surface of two rockhewn churches (Bete Gyorgis and Bete Amanuel) at the UNESCO’s World Heritage site of Lalibela, Northern Ethiopia. The two churches were carved into volcanic scoria deposits of basaltic composition. In their geological history, the Lalibela volcanic rocks underwent late to post-magmatic hydrothermal alteration together with partial laterization and are therefore characterized by a decay-prone highly vesicular microtexture with late stage to post-magmatic precipitation of secondary mineral phases (calcite–zeolite–smectite). The main objective of the study was to gain a better insight into the weathering products and mechanisms affecting the surface of the stone monuments and to assess the relative contribution of natural “geological” weathering processes versus biological/salt attack in stone decay at this unique heritage site. Results indicate that while the main cause of bulk rock deterioration and structural failure could be related to the stone inherited “geological” features, biological attack by micro- (bacteria) and/or macro- (lichens) organisms is currently responsible for severe stone surface physical and chemical weathering leading to significant weakening of the stone texture and to material loss at the surface of the churches walls. A prompt and careful removal of the biological patinas with the correct biocidal treatment is therefore recommended

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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

Integrated morbidity mapping of lymphatic filariasis and podoconiosis cases in 20 co-endemic districts of Ethiopia

Background: Lymphatic filariasis (LF) and podoconiosis are neglected tropical diseases (NTDs) that pose a significant physical, social and economic burden to endemic communities. Patients affected by the clinical conditions of LF (lymphoedema and hydrocoele) and podoconiosis (lymphoedema) need access to morbidity management and disability prevention (MMDP) services. Clear estimates of the number and location of these patients are essential to the efficient and equitable implementation of MMDP services for both diseases. Methodology/Principle findings: A community-based cross-sectional study was conducted in Ethiopia using the Health Extension Worker (HEW) network to identify all cases of lymphoedema and hydrocoele in 20 woredas (districts) co-endemic for LF and podoconiosis. A total of 612 trained HEWs and 40 supervisors from 20 districts identified 26,123 cases of clinical morbidity. Of these, 24,908 (95.3%) reported cases had leg lymphoedema only, 751 (2.9%) had hydrocoele, 387 (1.5%) had both leg lymphoedema and hydrocoele, and 77 (0.3%) cases had breast lymphoedema. Of those reporting leg lymphoedema, 89.3% reported bilateral lymphoedema. Older age groups were more likely to have a severe stage of disease, have bilateral lymphoedema and to have experienced an acute attack in the last six months. Conclusions/Significance: This study represents the first community-wide, integrated clinical case mapping of both LF and podoconiosis in Ethiopia. It highlights the high number of cases, particularly of leg lymphoedema that could be attributed to either of these diseases. This key clinical information will assist and guide the allocation of resources to where they are needed most