This research aims to develop a sentiment analysis system specifically designed for the Amharic l... more This research aims to develop a sentiment analysis system specifically designed for the Amharic language. The study employs four deep learning algorithms to achieve this goal: Convolutional Neural Network (CNN), Bidirectional Long Short-Term Memory (BiLSTM), Gated Recurrent Unit (GRU), and a combination of CNN and BiLSTM. The CNN algorithm is utilized for its effectiveness in extracting relevant features from the input data. By applying filters and pooling operations, the CNN can identify important patterns and structures within the Amharic text. The BiLSTM algorithm is chosen for its ability to process sequential information by considering both past and future contexts. It incorporates a memory cell that enables the model to retain important information and understand the dependencies between different parts of the text. Additionally, the GRU algorithm is employed as it offers similar capabilities to BiLSTM but with fewer computational requirements. This allows for more efficient p...
Objective: To develop document summarization for the Afaan Oromo language based on the query ente... more Objective: To develop document summarization for the Afaan Oromo language based on the query entered by the user(s). Methods: This study follows the design science analysis technique as a result of its considerations of thoughtful, intellectual, and ingenious activity throughout problem-solving and the creation of knowledge. The developed query-based framework has used the TF-IDF term weight methodology. Development tools such as HornMorpho are employed for morphological analysis; whereas, Natural Language Processing Toolkit is employed for the text process. The system has experimented on the various extraction rates of 10%, 20%, and 30%. The result's evaluated exploitation recall, precision, and F-measure for objective analysis; whereas, subjective analysis has been evaluated by language consultants. Findings: The results of the evaluations showed that the proposed system registered f-measure of 90%, 91% and 93% at a summary extraction rate of 10%, 20%, and 30% respectively. The informativeness and coherence of the proposed system also registered its best performance summary of 51.67%, 56.67 % and 54.17% average score on five scale measures at an extraction rate of 10%, 20%, and 30% respectively when both methods were used together. Novelty: By using a morphological analysis tool the performance of the system is improved from 80.67% to 91.3% F-measure when we compare it with the previous work even supposing there's still a requirement to conduct additional analysis to enhance the Afaan Oromo text summarization.
Image processing technology is a popular practical technology in the field of computer science.
... more Image processing technology is a popular practical technology in the field of computer science. It has important research in analysing, recognizing, identifying, and predicting the images using a variety of platform with algorithms.This is aimed at the analysis of algorithms of image processing in the cloud platform.Several algorithms are very high to use image processing and computing technique. Here a selection of state-of-art is applied to test image processing execution and timing factor using different strategies and platforms. Among them, the dataset structure and performance of the system can choose a verification algorithm to achieve the final operation. Based on the structure of a real-time image processing system based on SOPC technology is built and the corresponding functional receiving unit is designed for real-time image storage, editing, viewing, and analysing. Studies have shown that the image processing system based on cloud computing has increased the speed of image data processing by 12.7%. Compared with another platformespecially in the case of segmentation and enhancement of the image. This analysis has advantages in image compression and image restoration on a cloud platform.
International Journal of Advanced Computer Science and Applications, 2021
This study has implemented a rule-based approach on grammar checkers by integrating a spell-check... more This study has implemented a rule-based approach on grammar checkers by integrating a spell-checker with a morphological analyzer to improve the Afaan Oromo grammar checker. A corpus containing about 300,000 words has been prepared to be used for spell-checker. About 300 grammar rules are constructed to detect the grammar error within the Afaan Oromo text and to suggest the possible grammar correction. The developed frameworks have experimented on the document having pairs of 100 correct and incorrect sentences. The experimental result for checking the spelling errors has scored 73% of recall, 76% precision, and 75% of F-measure. The score for suggesting the correct spelling is 78% of recall, 62% precision, and 70% precision F-measure while the evaluation result for detecting the grammar errors has 47% recall, 90% precision and 68% f-measure score. For suggesting the possible correct grammar on the detected error, the system has scored 61% recall, 71% precision and 66% f-measure. Th...
This research aims to develop a sentiment analysis system specifically designed for the Amharic l... more This research aims to develop a sentiment analysis system specifically designed for the Amharic language. The study employs four deep learning algorithms to achieve this goal: Convolutional Neural Network (CNN), Bidirectional Long Short-Term Memory (BiLSTM), Gated Recurrent Unit (GRU), and a combination of CNN and BiLSTM. The CNN algorithm is utilized for its effectiveness in extracting relevant features from the input data. By applying filters and pooling operations, the CNN can identify important patterns and structures within the Amharic text. The BiLSTM algorithm is chosen for its ability to process sequential information by considering both past and future contexts. It incorporates a memory cell that enables the model to retain important information and understand the dependencies between different parts of the text. Additionally, the GRU algorithm is employed as it offers similar capabilities to BiLSTM but with fewer computational requirements. This allows for more efficient p...
Objective: To develop document summarization for the Afaan Oromo language based on the query ente... more Objective: To develop document summarization for the Afaan Oromo language based on the query entered by the user(s). Methods: This study follows the design science analysis technique as a result of its considerations of thoughtful, intellectual, and ingenious activity throughout problem-solving and the creation of knowledge. The developed query-based framework has used the TF-IDF term weight methodology. Development tools such as HornMorpho are employed for morphological analysis; whereas, Natural Language Processing Toolkit is employed for the text process. The system has experimented on the various extraction rates of 10%, 20%, and 30%. The result's evaluated exploitation recall, precision, and F-measure for objective analysis; whereas, subjective analysis has been evaluated by language consultants. Findings: The results of the evaluations showed that the proposed system registered f-measure of 90%, 91% and 93% at a summary extraction rate of 10%, 20%, and 30% respectively. The informativeness and coherence of the proposed system also registered its best performance summary of 51.67%, 56.67 % and 54.17% average score on five scale measures at an extraction rate of 10%, 20%, and 30% respectively when both methods were used together. Novelty: By using a morphological analysis tool the performance of the system is improved from 80.67% to 91.3% F-measure when we compare it with the previous work even supposing there's still a requirement to conduct additional analysis to enhance the Afaan Oromo text summarization.
Image processing technology is a popular practical technology in the field of computer science.
... more Image processing technology is a popular practical technology in the field of computer science. It has important research in analysing, recognizing, identifying, and predicting the images using a variety of platform with algorithms.This is aimed at the analysis of algorithms of image processing in the cloud platform.Several algorithms are very high to use image processing and computing technique. Here a selection of state-of-art is applied to test image processing execution and timing factor using different strategies and platforms. Among them, the dataset structure and performance of the system can choose a verification algorithm to achieve the final operation. Based on the structure of a real-time image processing system based on SOPC technology is built and the corresponding functional receiving unit is designed for real-time image storage, editing, viewing, and analysing. Studies have shown that the image processing system based on cloud computing has increased the speed of image data processing by 12.7%. Compared with another platformespecially in the case of segmentation and enhancement of the image. This analysis has advantages in image compression and image restoration on a cloud platform.
International Journal of Advanced Computer Science and Applications, 2021
This study has implemented a rule-based approach on grammar checkers by integrating a spell-check... more This study has implemented a rule-based approach on grammar checkers by integrating a spell-checker with a morphological analyzer to improve the Afaan Oromo grammar checker. A corpus containing about 300,000 words has been prepared to be used for spell-checker. About 300 grammar rules are constructed to detect the grammar error within the Afaan Oromo text and to suggest the possible grammar correction. The developed frameworks have experimented on the document having pairs of 100 correct and incorrect sentences. The experimental result for checking the spelling errors has scored 73% of recall, 76% precision, and 75% of F-measure. The score for suggesting the correct spelling is 78% of recall, 62% precision, and 70% precision F-measure while the evaluation result for detecting the grammar errors has 47% recall, 90% precision and 68% f-measure score. For suggesting the possible correct grammar on the detected error, the system has scored 61% recall, 71% precision and 66% f-measure. Th...
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Papers by Jemal Abate
It has important research in analysing, recognizing, identifying, and predicting the images using a variety of
platform with algorithms.This is aimed at the analysis of algorithms of image processing in the cloud
platform.Several algorithms are very high to use image processing and computing technique. Here a selection of
state-of-art is applied to test image processing execution and timing factor using different strategies and
platforms. Among them, the dataset structure and performance of the system can choose a verification
algorithm to achieve the final operation. Based on the structure of a real-time image processing system based on
SOPC technology is built and the corresponding functional receiving unit is designed for real-time image
storage, editing, viewing, and analysing. Studies have shown that the image processing system based on cloud
computing has increased the speed of image data processing by 12.7%. Compared with another
platformespecially in the case of segmentation and enhancement of the image. This analysis has advantages in
image compression and image restoration on a cloud platform.
It has important research in analysing, recognizing, identifying, and predicting the images using a variety of
platform with algorithms.This is aimed at the analysis of algorithms of image processing in the cloud
platform.Several algorithms are very high to use image processing and computing technique. Here a selection of
state-of-art is applied to test image processing execution and timing factor using different strategies and
platforms. Among them, the dataset structure and performance of the system can choose a verification
algorithm to achieve the final operation. Based on the structure of a real-time image processing system based on
SOPC technology is built and the corresponding functional receiving unit is designed for real-time image
storage, editing, viewing, and analysing. Studies have shown that the image processing system based on cloud
computing has increased the speed of image data processing by 12.7%. Compared with another
platformespecially in the case of segmentation and enhancement of the image. This analysis has advantages in
image compression and image restoration on a cloud platform.