• International Journal of Computer Science & Network Security
• /
• v.21 no.5
• /
• pp.84-89
• /
• 2021

Medical tests are very important part of the health monitoring process. It is performed for various reasons like diagnosing diseases, determining medications effectiveness, etc. Due to that, patients should be able to read and understand the available online tests and results in order to take proper decisions regarding their health condition. In fact, people are varying in their educational level and health backgrounds that make providing such information in an easily readable format by the majority of people considered as a challenge in the health domain since ever. This paper describes the MTReadable corpus which constructed for evaluating the readability of online medical tests. It covered 32 basic periodic check-up tests with over 36k words. These tests information are annotated and labelled based on three readability levels which are easy, neutral and difficult by three non-specialists native Arabic speakers. This paper contributes to enriching the Arabic health research community with an investigation of the level of readability of online medical tests and to be a baseline for further complex health online reports and information.

• International Journal of Computer Science & Network Security
• /
• v.22 no.8
• /
• pp.175-186
• /
• 2022

This research article develops an Arabic books' recommendation system, which is based on the content similarity that assists users to search for the right book and predict the appropriate and suitable books pertaining to their literary style. In fact, the system directs its users toward books, which can meet their needs from a large dataset of Information. Further, this system makes its predictions based on a set of data that is gathered from different books and converts it to vectors by using the TF-IDF system. After that, the recommendation algorithms such as the cosine similarity, the sequence matcher similarity, and the semantic similarity aggregate data to produce an efficient and effective recommendation. This approach is advantageous in recommending previously unrated books to users with unique interests. It is found to be proven from the obtained results that the results of the cosine similarity of the full content of books, the results of the sequence matcher similarity of Arabic titles of the books, and the results of the semantic similarity of English titles of the books are the best obtained results, and extremely close to the average of the result related to the human assigned/annotated similarity. Flask web application is developed with a simple interface to show the recommended Arabic books by using cosine similarity, sequence matcher similarity, and semantic similarity algorithms with all experiments that are conducted.

• International Journal of Computer Science & Network Security
• /
• v.22 no.11
• /
• pp.319-323
• /
• 2022

Handwritten text recognition is one of the active research areas nowadays. The progress in this field differs in every language. For example, the progress in Arabic handwritten text recognition is still insignificant and needs more attentions and efforts. One of the most important fields in this is Arabic handwritten manuscript text recognition which focuses in extracting text from historical manuscripts. For eons, ancients used manuscripts to write everything. Nowadays, there are millions of manuscripts all around the world. There are two main challenges in dealing with these manuscripts. The first one is that they are at the risk of damage since they are written in primitive materials, the second challenge is due to the difference in writing styles, hence most people are unable to read these manuscripts easily. Therefore, we discuss in this study different papers that are related to this important research field.

• International Journal of Computer Science & Network Security
• /
• v.23 no.8
• /
• pp.9-16
• /
• 2023

Speech can actively elicit feelings and attitudes by using words. It is important for researchers to identify the emotional content contained in speech signals as well as the sort of emotion that resulted from the speech that was made. In this study, we studied the emotion recognition system using a database in Arabic, especially in the Saudi dialect, the database is from a YouTube channel called Telfaz11, The four emotions that were examined were anger, happiness, sadness, and neutral. In our experiments, we extracted features from audio signals, such as Mel Frequency Cepstral Coefficient (MFCC) and Zero-Crossing Rate (ZCR), then we classified emotions using many classification algorithms such as machine learning algorithms (Support Vector Machine (SVM) and K-Nearest Neighbor (KNN)) and deep learning algorithms such as (Convolution Neural Network (CNN) and Long Short-Term Memory (LSTM)). Our Experiments showed that the MFCC feature extraction method and CNN model obtained the best accuracy result with 95%, proving the effectiveness of this classification system in recognizing Arabic spoken emotions.

• SUVANNABHUMI
• /
• v.10 no.1
• /
• pp.35-61
• /
• 2018

This paper explores the influence of Arab culture on the culture of Bugis-Makassar, the two major ethnic groups in South Sulawesi, Indonesia, particularly after their Islamization in the early 17^th century. The paper argues that since then, the on-going process of Islamization in the region has also brought a continuous flow of ideas and cultural practices from Mecca to Indonesia by means of the hajj pilgrims, Arab traders, and the establishment of Islamic educational institutions that emphasized the teaching and use of Arabic language in education. These factors, among others, have facilitated a cultural inflow which enabled cultural practices borne of West Asia (Middle East) to be integrated into local customs and beliefs. The paper particularly depicts the most observable forms of Arabic cultural integration, acculturation, and assimilation into the Bugis-Makassar culture such as the use of Arabic in Islamic schools and religious sermons; the Arab-style dressing by religious scholars, teachers, and students; the wearing of the hijab (head cover) by women; and the change of people's names from local into Arabic. By utilizing the historical and anthropological approach, this paper investigates this dynamic process of adaptation and integration of a foreign culture that first came through the Islamization of a local culture, exploring the role of an Islamic missionary and educational institutions in mediating and maintaining such cultural integration processes.

• Journal of Food Hygiene and Safety
• /
• v.16 no.3
• /
• pp.227-231
• /
• 2001

Basic materials for various making gangjung, various concentration 0∼25.0%(w/v) of coating agent and 0∼20.0% of substitutional materials carried out an experiment in sensory evaluation, expansion rate and hardness of substitutional materials. The results are as follows: 1. Added coating agent far improvement of decreasing aroma, arabic gum and dextrin significant from 20.0% to 25.0% compared with others. A good results flavor strength score and hedonic score of added 20.0% arabic gum are highest. 2. Expansion rate is caused by substitutional waxy rice, expansion rate decreased above 20.0% as tapioca above 5.0%, rice above 10.0%, brown waxy rice and wheat flour 15.0%. 3. After firing gangjung of substitutional materials, hardness increase concentration of substitutional materials. Therefore substitutional materials added to tapioca below 5.0%, rice and wheat flour 10.0%, brown waxy rice 15.0% is thought of good.

• Cross-Cultural Studies
• /
• v.27
• /
• pp.7-29
• /
• 2012

This study was aimed to analyze - focusing on the thesis of Younes - the pronunciation error occuring mostly for Arabian speakers to learn French pronunciation for Arabians and to suggest the effective study plan to improve such errors and provide the effective studying method. The first part is on how the Arabic and French pronunciation system are distinguished, especially by comparing and analyzing the system of graphemes and phonemes, with which we focused on the fact that Arabian is a language centralized on consonants, while French is a verb-centered language. In the second part, we mainly discussed the cause and the types of errors occurring when Arabic speakers study French pronunciation. As of the category of mistakes, we separated them into consonants and verbs. We assumed the possible method which can be used in learning, focusing on /b/, /v/, /p/, /b/ - in case of non-verbs and consonants - and /y/, /ø/, - in case of verbs - which don't exist in Arabic pronunciation system. One of the troubles the professors in Arabian culture have in teaching French to native learners is how to solve the problem on a phonetic basis regarding speaking and reading ability, which belong to verbal skill, among the critical factors of foreign language education, which are listening, speaking, reading, and writing skills. In fact, the problems occuring in learning foreign language are had by not only Arabian learners but also general groups of people who learn the foreign language, the pronunciation system of which is distinctly distinguished from their mother tongue. The important fact professors should recognize regarding study of pronunciation is that they should encourage the learners to reach the acceptable level in proper communication rather than push them to have the same ability as the native speakers, Even though it cannot be said that the methods suggested in this study have absolute influence in reducing errors when learning French pronunciation system, I hope it can be at least a small help.

• Proceedings of the KIEE Conference
• /
• 1991.07a
• /
• pp.900-904
• /
• 1991

In this paper, our study for the recognition of Hand-written Korean characters, Arabic numbers and alphabets by neural netwoks. This System extracts feature of character by using the MESH feature point of handwritten character, Arabic numbers and alphabets. To reduce the input image data, features are extracted from each input images. A MLP(multi-layer perceptron) with one hidden layer was trained with a modified BEP(back error propagation) algorithm. This method extracts feature sets of the characters directly from the scanner and can enhance computation speed without using the special preprocesses such as size normalization, smoothing, and thinning.

• Proceedings of the KSPS conference
• /
• 1996.10a
• /
• pp.206-206
• /
• 1996

Previous studies of American English(e.g. Sussman 1991, 1993, 1994) CVC coarticulation with initial consonants representing the labial, alveolar, and velar showed a linear relationship that fits to data points formed by plotting onsets of F2 transition along the y-axis and their corresponding midvowel points along the x-axis. The present study extends the locus equation metric to include the following places of articulation:uvular, pharyngeal, laryngeal, and emphatics. The question of interest is to determine if locus equation could serve as phonetic descriptor for the place of articulation in Arabic. Five male native speakers of Colloquial Egyptian Arabic(CEA) read a list of 204 CVC and CVCC words, containing eight different places of articulation and eight vowels. Average of formant patterns(Fl,F2,F3) onsets, midpoints, and offsets were calculated, using wide band spectrograms obtained by means of the kay spectrograph model(7029), and plotted as locus equations. A summary of the acoustic properties of the place of articulation of CEA will be presented in the frames of bVC and CVb. Strong linear regression relationships were found for every place of articulation.

• Journal of Information Processing Systems
• /
• v.11 no.1
• /
• pp.22-38
• /
• 2015

While Modern Standard Arabic is the formal spoken and written language of the Arab world; dialects are the major communication mode for everyday life. Therefore, identifying a speaker's dialect is critical in the Arabic-speaking world for speech processing tasks, such as automatic speech recognition or identification. In this paper, we examine two approaches that reduce the Universal Background Model (UBM) in the automatic dialect identification system across the five following Arabic Maghreb dialects: Moroccan, Tunisian, and 3 dialects of the western (Oranian), central (Algiersian), and eastern (Constantinian) regions of Algeria. We applied our approaches to the Maghreb dialect detection domain that contains a collection of 10-second utterances and we compared the performance precision gained against the dialect samples from a baseline GMM-UBM system and the ones from our own improved GMM-UBM system that uses a Reduced UBM algorithm. Our experiments show that our approaches significantly improve identification performance over purely acoustic features with an identification rate of 80.49%.