Mohd Amin Mohd Yunus

Semantic query for Quran documents results

The query-based on the result is less relevant documents results. In this study, a query has been improved in order to retrieve more relevant documents across language boundaries, a mechanism for query translation with semantic which is applied on as semantic query (SQ). Therefore, this study is conducted with the purposes to investigate semantic approach against the queries and vice versa. Furthermore, it is also conducted to investigate the performance query based on total retrieve and relevant. The retrieval however, included the irrelevant documents because of the translation polysemy. Results from the experiments suggest that semantic approach is most important process in cross language information retrieval (CLIR). It also found that semantic approach contributes to better performance in retrieving more relevant and related Quran document results.

Visualizing Quran documents results by stemming semantic speech query

The information visualization results are retrieving lack of information to meet users speech query even though there is presenting information and results in visualization. Hence, in this study, visualization of retrieving relevant documents through cross language information retrieval (CLIR) system needs to across language boundaries, a mechanism for query translation with semantic and stemmers are required well-known as stemming semantic query (SSQ). Therefore, this study is conducted with the purposes to investigate visualization approach against the queries and vice versa using SpaceTree. Furthermore, it is also conducted to investigate the performance of visualization to present normal listing results. The retrieval results however, focus on how SpaceTree is beneficial to represent them in a good manner. Results from the experiments suggest that SpaceTree is most friendly to display results to the users in CLIR. It also found that semantic approach with stemmers contributes to better performance in visualizing more relevant and related Quran document results.

Semantic query with stemmer for Quran documents results

The query-based on the result is lack of limited relevant documents in retrieval results. Therefore, query performance is considered to retrieve more relevant documents across language boundaries by applying semantic and stemmers which are more significant as stemming semantic query (SSQ). Therefore, this study is conducted with the purposes to investigate the integration semantic and stemmers approach against the queries and vice versa. Furthermore, it is also conducted to investigate the performance query based on total retrieve and relevant. The retrieval however, included the irrelevant documents because of the translation polysemy. Results from the experiments suggest that SSQ is most important process in cross language information retrieval (CLIR). It also found that semantic approach with stemmers contributes to better performance in retrieving more relevant and related Quran document results.

Semantic speech query via stemmer for Quran documents results

Speech recognition has provided limited converted speech into text as query for cross language information retrieval (CLIR). Therefore, in this study, speech recognition to be integrated with cross language information retrieval system to investigate the Quran system results performance using semantic and stemmers as stemming semantic spoken query (SSSQ). The query however is based on the speech to be input and converted into text. Therefore, this study is conducted with the purposes to investigate the integration speech, semantic and stemmers approach against the queries and vice versa. Furthermore, it is also conducted to investigate the performance query based on total retrieve and relevant. The retrieval however, included the irrelevant documents because of the translation polysemy. Results from the experiments suggest that SSSQ is most important process in CLIR. It also found that semantic speech approach with stemmers contributes to better approach in using speech instead of keyboard to investigate its performance for Quran document results.

Encryption function on artificial neural network

AbstractSix algorithms that design secrecy keys are used for digital image encryption. The privacy keys generated by stream cipher generators were tested for their randomness applying five tests of randomness. The images generated by applying each algorithm were tested for their regularity and residual intelligibility. The histograms for images ciphered by stream cipher schemes all have approximately flat histogram less information as compared to one-dimensional ciphering algorithms and threshold generator-based image ciphering scheme. Furthermore, the stream cipher schemes were effectively applied to the colored images of 256-color levels of true-color images (24 bit). In this paper, we try to decrypt automatically using artificial neural network by decryption through multilayer perceptron and radial basis function; networks were tested using the interface by calculating the error rates of decrypted images.