In the rapidly evolving domain of computerscience education, fostering deep engagement and sustained motivation among students remains a challenge. This study introduces the Answers platform, a pioneering online lear...
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Named entity recognition is a field of NLP that aims to detect and extract relevant information from unstructured text documents. However, some Ethiopian languages were getting started in different research fields. On...
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ISBN:
(数字)9798331542559
ISBN:
(纸本)9798331542566
Named entity recognition is a field of NLP that aims to detect and extract relevant information from unstructured text documents. However, some Ethiopian languages were getting started in different research fields. One of the languages spoken in Ethiopia is called Awingi language has a rich morphology and it is highly lacking in computational linguistic tools. There is some NER research done in Ethiopian language using different approaches and classification techniques, but since there was a lack of study conducted on NER for the Awingi language. This study aims to design a named entity recognition model for the Awngi Language using a deep learning approach with word2vect word embedding techniques. The data collected from AMICO Hiber Awiꬼgi program was posted on social media pages, Awngi Language and Literature Department of Injibara University, and Awi Zone Educational and Training Department. Therefore, the study uses a newly tagged dataset with 37,133 tokens. Presently, researchers focused on discovering four main named entities such as persons, locations, Dates, and organizations from unstructured Awiꬼgi text by using the three algorithms namely convolutional neural networks, long short-term memory, and bi-directional long-short-term memory. For the feature engineering task, Word2vec and one-hot encoding are utilized. To identify the best-performing model, the researchers have conducted several experiments. Over other algorithms, the Bi-LSTM algorithm before sampling and word embedding performed better results, i.e 95.4%, 92.4%, 95.3%, and 91.2% Accuracy, precision, recall, and f1-score, respectively, and after sampling and word embedding it performed with 99.4%, 97.3%, 99.2%, and 97.2% Accuracy, precision, recall, and f1-score, respectively.
Avian influenza viruses (AIVs) pose a growing global health threat, particularly in low- and middle-income countries (LMICs), where limited surveillance capacity and under-resourced healthcare systems hinder timely de...
Avian influenza viruses (AIVs) pose a growing global health threat, particularly in low- and middle-income countries (LMICs), where limited surveillance capacity and under-resourced healthcare systems hinder timely detection and response. Migratory birds play a significant role in the transboundary spread of AIVs, yet data from key regions along migratory flyways remain sparse. To address these surveillance gaps, we conducted a study between December 2021 and February 2023 using fresh bird guano collected across 10 countries in the Global South. Here, we show that remote, uninhabited regions in previously unsampled areas harbor a high diversity of AIV strains, with H5N1 emerging as the most prevalent. Some of these H5N1 samples also carry mutations that may make them less responsive to the antiviral drug oseltamivir. Our findings documented the presence of AIVs in several underrepresented regions and highlighted critical transmission hotspots where viral evolution may be accelerating. These results underscore the urgent need for geographically targeted surveillance to detect emerging variants, inform public health interventions, and reduce the risk of zoonotic spillover.
THe initiation of a Programming Preparation Course for enhancing students' preparation in a C++ programming course and their level of confidence in mastering the basics of computer programming is discussed. The co...
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THe initiation of a Programming Preparation Course for enhancing students' preparation in a C++ programming course and their level of confidence in mastering the basics of computer programming is discussed. The course is a collaborative effort of faculty in the College of engineering and the computerscience Department. The topics used to introduce the fundamentals of programming include variables, loops and input, and function calls. The instructor team that has developed thsi course has the potential of increasing student retention in the programming course during the spring semester.
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