{"title":"A COMPARATIVE STUDY OF DIFFERENT SEARCH AND INDEXING TOOLS FOR BIG DATA","authors":"A. Oussous, Fatima-Zahra Benjelloun","doi":"10.5455/jjcit.71-1637097759","DOIUrl":"https://doi.org/10.5455/jjcit.71-1637097759","url":null,"abstract":"","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70820593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Raya Jaradat, F. Shahroury, H. Ahmad, I. Abuishmais
{"title":"DESIGN METHODOLOGY FOR NARROW-BAND LOW NOISE AMPLIFIER USING CMOS 0.18 µm TECHNOLOGY","authors":"Raya Jaradat, F. Shahroury, H. Ahmad, I. Abuishmais","doi":"10.5455/jjcit.71-1637577305","DOIUrl":"https://doi.org/10.5455/jjcit.71-1637577305","url":null,"abstract":"","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"20 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70820633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Rat Swarm Optimizer for Data Clustering","authors":"Ibrahim Zebiri, D. Zeghida, M. Redjimi","doi":"10.5455/jjcit.71-1652735477","DOIUrl":"https://doi.org/10.5455/jjcit.71-1652735477","url":null,"abstract":"Rat Swarm Optimization (RSO) is one of the newest swarm intelligence optimization algorithms that is inspired from the behaviors of chasing and fighting of rats in nature. In this paper we will apply the RSO to one of the most challenging problems, which is data clustering. The search capability of RSO is used here to find the best clusters centers. The proposed algorithm RSO for clustering (RSOC) is tested on several benchmarks and compared to some other optimization algorithms for data clustering including some wellknown and powerful algorithms such as Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) and other recent such as the Hybridization of Krill Herd Algorithm and harmony search (H-KHA), hybrid Harris Hawks Optimization with differential evolution (H-HHO), and Multi-Verse Optimizer (MVO). Results are validated through a bunch of measures: homogeneity, completeness, v-measure, purity, and error rate. The computational results are encouraging, Where they demonstrate the effectiveness of RSOC over other techniques.","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70820893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A NOVEL TRUE REAL-TIME SPATIOTEMPORAL DATA STREAM PROCESSING FRAMEWORK","authors":"Ature Angbera, H. Chan","doi":"10.5455/jjcit.71-1646838830","DOIUrl":"https://doi.org/10.5455/jjcit.71-1646838830","url":null,"abstract":"The ability to interpret spatiotemporal data streams in real-time is critical for a range of systems. However, processing vast amounts of spatiotemporal data out of several sources, such as online traffic, social platforms, sensor networks, and other sources, is a considerable challenge. The major goal of this study is to create a framework for processing and analyzing spatiotemporal data from multiple sources with irregular shapes so that researchers can focus on data analysis instead of worrying about the data sources' structure. We introduced a novel spatiotemporal data paradigm for true-real-time stream processing, which enables high-speed and low-latency real-time data processing, with these considerations in mind. A comparison of two state-of-the-art real-time process architectures was offered, as well as a full review of the various open-source technologies for real-time data stream processing, and their system topologies were also presented. Hence, this study proposed a brand-new framework that integrates Apache Kafka for spatiotemporal data ingestion, Apache flink for true real-time processing of spatiotemporal stream data, as well as machine learning for real-time predictions, and Apache Cassandra at the storage layer for distributed storage in real-time. The proposed framework was compared with others from the literature using the following features: Scalability (Sc), prediction tools (PT), data analytics (DA), multiple event types (MET), data storage (DS), Real-time (Rt), and performance evaluation (PE) stream processing (SP), and our proposed framework provided the ability to handle all of this task.","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70821220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"TOWARD DEVELOPING AN INTELLIGENT PERSONAL ASSISTANT FOR TUNISIAN ARABIC","authors":"Inès Zribi, Lamia Hadrich Belguith","doi":"10.5455/jjcit.71-1652434864","DOIUrl":"https://doi.org/10.5455/jjcit.71-1652434864","url":null,"abstract":"Intelligent systems powered by Artificial Intelligence techniques have been massively proposed to help humans in various tasks. The intelligent personal assistant (IPA) is one of these smart systems. In this paper, we present an attempt to create an IPA, that interacts with users via Tunisian Arabic (TA), (the colloquial form used in Tunisia). We propose and explore a simple-to-implement method for building the principal components of a TA IPA. We apply Deep learning techniques: CNN [1], RNN encoder-decoder [2] and end-to-end approaches for creating IPA speech components (Speech Recognition and Speech Synthesis). In addition, we explore the availability and free dialog platform for understanding and generating the suitable response in TA for a request. For this proposal, we create and use TA transcripts for generating the corresponding models. Evaluation results are acceptable for the first attempt.","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70821301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"MELANOMA SKIN LESION CLASSIFICATION USING IMPROVED EFFICIENTNETB3","authors":"Saumya Salian, D. Sawarkar","doi":"10.5455/jjcit.71-1636005929","DOIUrl":"https://doi.org/10.5455/jjcit.71-1636005929","url":null,"abstract":"","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70820528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Mekki, Inès Zribi, M. Ellouze, Lamia Hadrich Belguith
{"title":"COTA 2.0: an Automatic Corrector of Tunisian Arabic Social Media Texts","authors":"A. Mekki, Inès Zribi, M. Ellouze, Lamia Hadrich Belguith","doi":"10.5455/jjcit.71-1655499240","DOIUrl":"https://doi.org/10.5455/jjcit.71-1655499240","url":null,"abstract":"In written text, orthographic noise is a common concern for NLP, especially when operating social network comments and raw documents. This is mainly due to its orthographic conventions and morphological ambiguity. We propose to automatically normalize the social media dialect corpora by following CODA-TUN, the Conventional Orthography for Tunisian Arabic (TA). The existing system developed for TA <<COTA Orthography 1.0>> is not able to handle all forms of TA. Therefore, we propose to extend its rules and lexicons to address the peculiarities of social media dialect. In certain words, the COTA Orthography 1.0 system provides the user with several correction possibilities. Therefore, in the new version, we incorporated a trigram language model to automatically select the right correction. Our results show that the system can reduce transcription errors by 95.72%.","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70820996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"AN IN-DEPTH VISION TO HARDWARE DESIGN SECURITY VULNERABILITIES","authors":"Zainab Younis, Basim Mahmood","doi":"10.5455/jjcit.71-1635517841","DOIUrl":"https://doi.org/10.5455/jjcit.71-1635517841","url":null,"abstract":"","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70820490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A NEW ADAPTED CANNY FILTER FOR EDGE DETECTION IN RANGE IMAGES","authors":"Mohamed Cheribet, S. Mazouzi","doi":"10.5455/jjcit.71-1620428305","DOIUrl":"https://doi.org/10.5455/jjcit.71-1620428305","url":null,"abstract":"","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70820304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. Singhal, Vaishali Ganganwar, M. Yadav, Asha Chauhan, Mahender Jakhar, Kareena Sharma
{"title":"COMPARATIVE STUDY OF MACHINE LEARNING AND DEEP LEARNING ALGORITHM FOR FACE RECOGNITION","authors":"N. Singhal, Vaishali Ganganwar, M. Yadav, Asha Chauhan, Mahender Jakhar, Kareena Sharma","doi":"10.5455/jjcit.71-1624859356","DOIUrl":"https://doi.org/10.5455/jjcit.71-1624859356","url":null,"abstract":"","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"116 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70820834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}