Browsing by Subject "Patterns"

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    Cow mortality in Midwest dairy herds
    (2013-03) Shahid, Muhammad Qamer
    On-farm dairy cow mortality is becoming a significant issue in the US dairy industry. A rise in on-farm mortality among cows indicates compromised cow welfare and also causes economic losses, including value of animal, its replacement cost, the loss of milk production and the extra labor used for its carcass disposal. Recently published studied showed increasing trends in dairy cow mortality in the US and in other countries. Mortality is the primary reason of cows leaving the herd. Various herd and cow level factors have been associated to the rise in mortality over the last couple of decades. The aim of the current study was to describe the mortality patterns among cows in Midwest dairy herds and to identify the cow and herd level risk factors for on farm mortality. Approximately 5.9 million lactation records for cows from 10 Midwest states that calved between January 2006 and December 2010 were analyzed. Herd level mortality rate increased over time, and was higher in larger herds, herds with lower milk yield, and herds with less annual culling. Cow level mortality rate was higher in early lactation, in older cows, in winter and summer. Also, mortality was the main reason of cows leaving the herds in our study. The survival analysis indicated that the hazards of mortality were higher in cows with higher fat to protein ratio, higher fat%, lower milk protein %, higher 1st test day somatic cell score, higher milk urea nitrogen, cows with male calves, cows carrying multiple calves, and increased calving difficulty score. Cow mortality was higher in herds with increased percentage of still births, herds with higher somatic cell score and increased herd calving interval, and larger herds. Cows with higher 1st test day milk yield and in herds with higher milk yield had lower mortality hazards. The results of current study indicate that first test day records especially those indicative of negative energy balance in cows could be helpful to identify animals at high risk of mortality. It was also noted that higher milk yield did not seem to have harmful effects on mortality. In addition, the association between herd level factors and mortality indicated that management quality could be an important factor in lowering on-farm mortality thereby improving cow welfare.
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    Hypernym Discovery over WordNet and English Corpora - using Hearst Patterns and Word Embeddings
    (2018-07) Vallabhajosyula, Manikya Swathi
    Languages evolve over time. With new technical innovations, new terms get created and new senses are added to existing words. Dictionaries like WordNet which act as a database for English vocabulary should be updated with these new concepts. WordNet organizes these concepts in sets of synonyms and interlinks them by using semantic relations. Many Natural Language Processing applications like Machine Translation and Word Sense Disambiguation rely on WordNet for their functionality. WordNet was last updated in 2006. If WordNet is not updated with new vocabulary, the performance of applications which rely on WordNet would drop. The objective of our research is to automatically update WordNet with the new senses by using resources like online dictionaries and text corpora available over the internet. We use the ISA hierarchy structure of WordNet to insert new senses. In an ISA hierarchy, the concepts higher in a hierarchy (called hypernyms) are more abstract representations of the concepts lower in hierarchy (called hyponyms). To improve the coverage of our solution, we rely on two complementary techniques - traditional pattern matching and modern vector space models - to extract candidate hypernym from WordNet for a new sense. Our system was ranked 4 among the systems that participated in for this SemEval task SemEval 2016 Task 14 Semantic Taxonomy Enrichment. We also evaluate our system by participating in the task SemEval 2018 Task 09 Hypernym Discovery. In this task, we apply our system to the huge UMBC WebBase text corpus to extract candidate hypernyms for a given input term. Our system was ranked 3 among the systems which find hypernyms for Concepts.