• International Journal of Computer Science & Network Security
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• 제23권6호
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• pp.1-12
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• 2023

With the rapid increase of user generated data on digital platforms, the task of categorizing and classifying theses huge data has become difficult. Topic modeling is an unsupervised machine learning technique that can be used to get a summary from a large collection of documents. Topic modeling has been widely used in English content, yet the application of topic modeling in Arabic language is limited. Therefore, the aim of this paper is to provide a systematic review of the application of topic modeling algorithms in Arabic content. Using a well-known and trusted databases including ScienceDirect, IEEE Xplore, Springer Link, and Google Scholar. Considering the publication date from 2012 to 2022, we got 60 papers. After refining the papers based on predefined criteria, we resulted in 32 papers. Our result show that unfortunately the application of topic modeling techniques in Arabic content is limited.

• 한국식품저장유통학회지
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• 제12권6호
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• pp.572-577
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• 2005

표고버섯 과립의 품질 특성에 결합제가 미치는 영향을 조사하기 위하여, 버섯분말에 결합제로 corn starch, lactose, gelatin, gum arabic 및 dextrin(DE=23)을 각각 첨가하고 버섯열수추출액으로 반죽하여 압출과립을 제조한 다음 과립의 이화학적 특성을 측정하였다. 과립의 용해도는 gum arabic >gelatin>lactose, dextrin>corn starch 첨가구 순이었다. L값은 corn starch lactose>gelatin, gum arabic, dextrin 첨가구 순이었고, a값은 결합제종류에 따라 큰 차이를 보이지 않았고, b값은 lactose, corn starch>gelatin, gum arabic>dextrin 첨가구 순이었다. 점도는 gelatia corn starch>gum arabic, dextrin, lactose 첨가구 순이었고, 흡습성은 gelatin>lactose>corn starch>dextrin>gum arabic 순이었다. pH는 결합제의 종류에 따라서 큰 차이를 보이지 않았으며, 총당 함량은 gum arabic>lactose, dertrin>corn starch, gelatin 순이었고, 단백질 함량은 gelatin 첨가구에서 가장 높게 나타났다. 이상의 결과로 볼 때 표고버섯 과립의 용해도 증가와 흡습성 저하를 위한 결합제로gum arabic이 보다 효과적인 것으로 확인되었다.

• International Journal of Computer Science & Network Security
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• 제22권11호
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• pp.331-337
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• 2022

Smart learning is augmented with digital, context-aware, and adaptable technologies to encourage students to learn better and faster. To ensure that digital learning is successful and that implementation is efficient, it is critical that the dimensions of digital learning are arranged correctly and that interactions between the various elements are merged in an efficient and optimal manner. This paper builds and discusses a basic framework for smart learning in the digital age, aimed to improve students' abilities and performance in learning. The proposed framework consists of five dimensions: Teacher, Technology, Learner, Digital content, and Evaluation. The Teacher and Learner dimensions operate on two levels: (a) an abstract level to fit in knowledge and skills or interpersonal characteristics and (b) a concrete level in the form of digital devices used by teachers and learners. Moreover, this paper proposes asynchronous online course delivery model. An Arabic smart learning platform has been developed, based on these smart learning core dimensions and the asynchronous online course delivery model, because despite the official status of this language in many countries, there is a lack of Arabic platforms to teach Arabic. Moreover, many non-native Arabic speakers around the world have expressed an interest in learning it. The Arabic digital platform consists of over 70 lessons classified into three competence levels: beginner, intermediate, and advanced, delivered by Arabic experts and Arabic linguists from various Arab countries. The five dimensions are described for the Arabic platform in this paper. Learner dimension is the Arabic and non-Arabic speakers, Teacher dimension is Arabic experts and Arabic linguistics, Technology dimension consists of technology for Arabic platform that includes web design, cloud computing, big data, etc. The digital contents dimension consists of web-based video, records, etc. The evaluation dimension consists of Teachers rating, comments, and surveys.

• International Journal of Computer Science & Network Security
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• 제22권8호
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• pp.175-186
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• 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.

• Asian Pacific Journal of Cancer Prevention
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• 제17권5호
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• pp.2619-2624
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• 2016

Background: Cancer is a worldwide health problem. Arabic countries are also concerned and the burden linked to the pain related to cancer is dsiquieting. The aim of this study is to set the panel of valid tools for assessing the multiple dimensions of pain in arabic speaking countries. Materials and Methods: A systematic review on PubMed, Scopus, and Science Direct databases was conducted using as key words cancer, pain and arabic speaking population. The content of 51 articles was studied and nine articles were retained for their relevance for the issue. Results: We founf eight different questionnaires. MSAS-Leb, EORTC-C30, EORTC-BR23, MDASI, FLIC, and COOP/WONCA are dedicated to physical and psychological dimensions of pain. BPI is centered on direct items for measuring pain accurately. ABQ-II is the unique tool focusing on barriers to cancer pain control. All tools are confirmed valid and reliable in the context studied for assessing pain and disconfort linked to cancer. Conclusions: This panel of questionnaires covers all relevant aims for assessing pain in diferent arabic speaking countries with the recommendation of a cultural adaptation to local arabic languages.

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.155-162
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• 2021

The expansion of the world wide web has led to a huge amount of user generated content over different forums and social media platforms, these rich data resources offer the opportunity to reflect, and track changing public sentiments and help to develop proactive reactions strategies for decision and policy makers. Analysis of public emotions and opinions towards events and sentimental trends can help to address unforeseen areas of public concerns. The need of developing systems to analyze these sentiments and the topics behind them has emerged tremendously. While most existing works reported in the literature have been carried out in English, this paper, in contrast, aims to review recent research works in Arabic language in the field of thematic sentiment analysis and which techniques they have utilized to accomplish this task. The findings show that the prevailing techniques in Arabic topic-based sentiment analysis are based on traditional approaches and machine learning methods. In addition, it has been found that considerably limited recent studies have utilized deep learning approaches to build high performance models.

• 약학회지
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• 제28권4호
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• pp.223-229
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• 1984

Microcapsules of indomethacin were prepared by the complex coacervation technique using gelatin-gum arabic as the wall-forming material. The effects of varying drug-to-matrix ratios and formalization time, and hydroxy propyl cellulose (HPC) added on the release of drug from microcapsules were studied. As the amount of wall-forming material increased, the drug content in the microcapsules decreased and the release of drug from microcapsules was retarded. The drug content was lower in the HPC added microcapsules than that in the microcapsules was retarded. The drug content was lower in the HPC added microcapsules than that in the microcapsules without HPC and the microcapsules with 1:4 drug-to-matrix ratio showed the slowest release. The release rate of the drug from microcapsules with 1:2 drug-to-matrix was delayed according to the increase of formalization time and the microcapsules formalized for 24hr showed ratio the most retardation.

• International Journal of Computer Science & Network Security
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• 제24권8호
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• pp.61-71
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• 2024

The dynamic nature of Online Social Networks (OSNs), especially on platforms like Twitter, presents challenges in identifying and responding to community attacks, particularly within Arabic content. The proposed integrated system addresses these challenges by achieving 91% accuracy in detecting real-time community event attacks while efficiently managing computational costs. This is accomplished through the use of specialized integrated approach clustering to detect both major and minor attacks. Additionally, the system leverages clustering algorithms, temporal modules, and social network graphs to identify events, map communities, and analyze online dynamics. An extensive parameter sensitivity analysis was conducted to fine-tune the algorithm, and the system's effectiveness was validated using a benchmark dataset, demonstrating substantial improvements in event detection.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.9-16
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• 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.

• 한국식품과학회지
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• 제41권6호
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• pp.657-661
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• 2009

해조칼슘을 습식분쇄한 초미세액상칼슘을 분무건조하여 부형제 종류에 따른 분말칼슘의 품질특성을 알아보고자 gum arabic, cyclodextrin, Na-caseinate를 첨가하여 품질특성을 비교하였다. 분무건조한 초미세분말칼슘의 수분함량은 2% 내외의 안정한 분말을 얻을 수 있었고, 색도는 원료인 해조칼슘보다 L값은 높았으며, b값은 감소하는 것으로 나타났다. 입자크기는 당류의 부형제 첨가로 초미세 크기로 분쇄되는 것을 확인할 수 있었으며, gum arabic을 첨가하여 제조한 초미세액상칼슘을 분무건조한 분말이 식초와 pH에 대한 용해도에서 가장 우수한 것으로 나타났다. 칼슘함량은 해조칼슘분말이 28%의 칼슘함량을 나타내었고, 부형제를 달리하여 제조한 초미세액상칼슘을 분무건조한 분말은 27% 내외로 비슷한 칼슘함량을 나타내어, 습식분쇄나 분무건조 공정에서 칼슘의 손실은 없는 것으로 나타났다. 흡습에 대한 안정성실험에서는 해조칼슘분말이 흡습에 안정하였으며, gum arabic을 첨가하여 분무건조한 분말이 흡습이 많이 발생하였다. 전자주사 현미경 관찰을 통하여 습식분쇄로 입자크기가 작아지는 것을 확인할 수 있었고, gum arabic을 사용하여 얻은 초미세칼슘분말이 단백질계나 사용하지 않았을 때보다 더 균일한 입자분포를 보였다. 따라서 습식분쇄한 초미세액상칼슘을 분말화하여 용해성등 품질특성이 개선됨을 확인하였으며 습식분쇄기술과 분무건조법을 식품가공기술로 활용할 수 있는 가능성을 확보하였다.