Online handwriting Arabic recognition system using k-nearest neighbors classifier and DCT features

With advances in machine learning techniques, handwriting recognition systems have gained a great deal of importance. Lately, the increasing popularity of handheld computers, digital notebooks, and smartphones give the field of online handwriting recognition more interest. In this paper, we propose an enhanced method for the recognition of Arabic handwriting words using a directions-based segmentation technique and discrete cosine transform (DCT) coefficients as structural features. The main contribution of this research was combining a total of 18 structural features which were extracted by DCT coefficients and using the k-nearest neighbors (KNN) classifier to classify the segmented characters based on the extracted features. A dataset is used to validate the proposed method consisting of 2500 words in total. The obtained average 99.10% accuracy in recognition of handwritten characters shows that the proposed approach, through its multiple phases, is efficient in separating, distinguishing, and classifying Arabic handwritten characters using the KNN classifier. The availability of an online dataset of Arabic handwriting words is the main issue in this field. However, the dataset used will be available for research via the website

Recognition techniques for online Arabic handwriting recognition systems

Online recognition of Arabic handwritten text has been an on-going research problem for many years. Generally, online text recognition field has been gaining more interest lately due to the increasing popularity of hand-held computers, digital notebooks and advanced cellular phones. However, different techniques have been used to build several online handwritten recognition systems for Arabic text, such as Neural Networks, Hidden Markov Model, Template Matching and others. Most of the researches on online text recognition have divided the recognition system into these three main phases which are preprocessing phase, feature extraction phase and recognition phase which considers as the most important phase and the heart of the whole system. This paper presents and compares techniques that have been used to recognize the Arabic handwriting scripts in online recognition systems. Those techniques attempt to recognize Arabic handwritten words, characters, digits or strokes. The structure and strategy of those reviewed techniques are explained in this article. The strengths and weaknesses of using these techniques will also be discussed

Sentiment analysis for Malay language: systematic literature review

Recent research and developments in Sentiment Analysis (SA) have simplified sentiment detection and classification from textual content. The related domains for these studies are diverse and comprise fields such as tourism, costumer review, finance, software engineering, speech conversation, social media content, news and so on. SA research and developments field have been done on various languages such as Chinese and English language. However, SA research on other languages such as Malay language is still scarce. Thus, there is a need for constructing SA research specifically for Malay language. To understand trends and to support practitioners and researchers with comprehension information with regard to SA for Malay language, this study exhibit to review published articles on SA for Malay language. From five online databases including ACM, Emerald insight, IEEE Xplore, Science Direct, and Scopus, 2433 scientific articles were obtained. Moreover, through the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Statement, 10 articles have been chosen for the review process. Those articles have been reviewed depend on a few categories consisting of the aim of the study, SA classification techniques, as well as the domain and source of content. As a result, the conducted systematic literature review shed some light about the starting point to research in term of SA for Malay language

Malay Online Virtual Integrated Corpus (MOVIC): a systematic review

The development of the various Malay corpora have given the opportunities to many researchers to explore their usage in diverse contexts. However, the corpora were distributed in various locations, and for the ease of access for users, a system called Malay Online Virtual Integrated Corpus (MOVIC) is proposed. This paper focuses on applying the systematic literature review (SLR) on the Malay corpus research to find out the recent development in the area. From the initial search, 3231 articles were extracted from five online databases, such as, IEEE Xplore, Scopus, ProQuest, Springer Link, and ACM. After several rounds of filtering, 11 papers were selected for review

Digital hacking and cyber-attacks: cyber security from Islamic perspective

As the number of devices connected to the Internet increase and the amount of data available online grow, the cyber-attacks will keep increasing in number and their severity. For Malaysia specifically, as of the second quarter of 2022, a total of 44.2 million accounts have been breached putting the security, privacy, and confidentiality of the account owners’ data in danger. Cyber hacking can become a strong power which can be harmful if the necessary skills are learned without ethical standards. On the other hand, learning the skills for ethical hacking became a necessity to protect digital systems, discover vulnerabilities and mitigate them. An Islamic approach to cyber security issues is presented in this paper. As Islam is a revealed religion from Allah SWT to be guidance to the Muslims in all matters, we can derive many ethical standards in any field following the holy Quran and the Sunnah of the Prophet (Peace be upon him)

Studying the Reduction Techniques for Mining Engineering Datasets

Over the world, companies often have huge datasets as data warehouses collection. The enormous size could make difficulty to analyze the data. The main reason, the complexity of data in terms of number of attributes and number of cases. To overcome this problem could be done by using a sufficient number of attributes and cases before mining this dataset. In Data Mining field, several methods could be used to reduce the attributes number and similar cases. This paper presents a study to test three reduction methods on engineering domain using five datasets. The three methods are: Genetic Algorithm (GA), Principal Component Analysis (PCA), and Johnson technique. The five datasets where obtained from UCI machine learning archive. The study examines which reduction method can be proper for datasets in Engineering field. It can be done by identifying the three reduction methods ranking based on percentage accuracy and number of selected attributes

A Proposed Model for E-learning Adaptability Measurement During COVID-19 Pandemic Using Data Mining Techniques

E-learning became the main medium of education in the world for the past two years. COVID-19 virus has pushed all the universities and academic institutions to utilize and activate E-learning platforms and systems. The sudden and urgent transformation from the regular traditional learning system to E-learning system has involved many challenges and limitations. Therefore, the need to evaluate and enhance the current E-learning mechanism in Iraq became very urgent and critical need. The target level was students at higher education institutes which include university students in Basra city. The data collected based on students’ evaluation and opinions about E-learning based on their interaction and usage during two years under COVID-19 spread era. This research involved applying data mining techniques to sample dataset and utilizing the obtained results as feedback for a proposed model suggested by the authors to measure adaptability. The proposed model is derived from the idea of the Technology Acceptance Model (TAM) with focus on the positivity as the main factor to measure adaptability. The results of the research showed approximate adaptation level of 52% which is very close compared to the actual situation in real life which involve limitations and challenges faced by Iraqi students

انظمة التعرف الضوئي على الكتابة اليدوية بواسطة شاشات اللمس: التحديات والحلول

تعد لوحات المفاتيح من وسائل الإدخال الأساسية لأجهزة الحاسوب الشخصية وأجهزة الهواتف النقالة. ومع ذلك، لم تعد لوحات المفاتيح الطريقة الوحيدة لإدخال البيانات إلى أجهزة الحاسوب والهواتف لعدة أسباب. من هذه الأسباب حجم الأجهزة الإلكترونية وطبيعة عملها والحاجة لاستخدام شاشات ذات أحجام أكبر نسبياً. ومن ناحية أخرى، أدى ظهور الشاشات القابلة للمس والكتابة إلى استخدام الشاشة كجهاز إدخال وإخراج في آن واحد. حيث يتم استخدام لوحات مفاتيح رسومية داخل حيز الشاشة ويتم التعامل معها بلمس الشاشة على الازرار الافتراضية للوحة. كذلك تم استخدام هذه الشاشات لكتابة النصوص مباشرة إلى هذه الأجهزة سواءً باستخدام الاصبع او باستخدام قلم خاص للكتابة. ومن هذا المنطلق ظهرت الحاجة إلى معالجة النصوص المدخلة آنيا لكي يتم تمييزها من قبل نظام الجهاز الألكتروني. تسلط هذه الورقة الضوء على التحديات والمشاكل التي قد تحدث عند الكتابة على الشاشات القابلة للمس. وتوضح هذه الورقة التقنيات المستخدمة للتغلب على هذه المشكلات

Applications of Data Mining in Mitigating Fire Accidents Based on Association Rules

Due to the increased rate of fire accidents which cause many damages and losses to people souls, material, and property in Basra city. The necessity of analyzing and mining the data of the fire accidents became an urgent need to find a solution. The need increased for a solution that helps to mitigate and reduce the number of accidents. In this paper, data mining techniques and applications including data preprocessing, data cleaning, and data exploration have been applied. Data mining applications is performed to analyze and discover the hidden knowledge in ten years of data (fire accidents happened from 2010 – 2019) which is approximately 20k record of accidents. These data mining techniques along with the association rules algorithm is applied on the dataset. The applied approach and techniques resulted in discovering the patterns and the nature of the fire accidents in Basra city. It also helped to reach to recommendations and resolutions for mitigating the fire accidents and its occurrence rate