International Journal of Intelligent Computing and Information Sciences最新文献_第6页

AUGMENTED REALITY IN TECHNOLOGY-ENHANCED LEARNING: SYSTEMATIC REVIEW 2011-2021 技术增强学习中的增强现实:系统回顾2011-2021

International Journal of Intelligent Computing and Information Sciences Pub Date : 2022-01-18 DOI: 10.21608/ijicis.2022.97513.1121

R. Tolba, T. Elarif, Zaki Taha

{"title":"AUGMENTED REALITY IN TECHNOLOGY-ENHANCED LEARNING: SYSTEMATIC REVIEW 2011-2021","authors":"R. Tolba, T. Elarif, Zaki Taha","doi":"10.21608/ijicis.2022.97513.1121","DOIUrl":"https://doi.org/10.21608/ijicis.2022.97513.1121","url":null,"abstract":"With the raise of COVID-19 pandemic in 2020, the traditional teaching-learning process became inefficient. Technology-Enhanced Learning (TEL) research has increasingly focused on emergent technologies such as Augmented Reality (AR). It became one of the technologies that has received great attention and interest in the last decade. In this paper, we conducted a systematic review that describes the current state of using AR as a learning tool. Taking into consideration the needs of all students including those with a disability, in different levels of education. It is done through the analysis of the following factors: AR in learning system, AR in levels of education and categories of educational AR applications. A total of 103 studies between 2011 and 2021 were analyzed through searching in four interdisciplinary databases: Springer, IEEE Xplore, ResearchGate, and Google Scholar. This analysis helped to see in which direction AR systems for education are heading and how it will be designed to fit the students’ needs and improve their learning. Further research and development will make AR a more promising learning tool.","PeriodicalId":244591,"journal":{"name":"International Journal of Intelligent Computing and Information Sciences","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127387647","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}

引用次数: 1

IMAGE RETRIEVAL USING BLENDING OF EXTENDED FEATURE COMPONENTS 混合扩展特征组件的图像检索

International Journal of Intelligent Computing and Information Sciences Pub Date : 2022-01-18 DOI: 10.21608/ijicis.2022.105794.1140

Hewayda M. Lotfy

{"title":"IMAGE RETRIEVAL USING BLENDING OF EXTENDED FEATURE COMPONENTS","authors":"Hewayda M. Lotfy","doi":"10.21608/ijicis.2022.105794.1140","DOIUrl":"https://doi.org/10.21608/ijicis.2022.105794.1140","url":null,"abstract":"Receiving the most relevant images from image databases is a challenging and critical issue in many applications. Texture is a substantial feature of an image which depicts the spatial behavior of gray-levels in any given neighborhood. Color features uses a variety of color systems and are meaningful to differentiate image segments. Presently, many of the favorable methods for image content description use local descriptors as their starting point with several conducts. The content in an image may appear in some feature descriptor's components more accurately than other components. This paper presents an innovative idea for local image retrieval using a new methodology for feature extraction welding named Blend of Extended Features’ Components (BoEFC). The paper shows that an image's content may be described individually by the feature descriptor's components or collectively through the Extended Feature Components (EFC). Retrieval options are attempted using a selection method of Feature Components then the relevant results are collected and ordered according to newly adapted feature similarity measures. The experiments were performed using a general-purpose image database which itself represent a challenge and the INRIA Holiday image database. The experiments was performed by varying the EFCs to compute recall, precision and draw the Precision-Recall (PR) curves which showed increased recall and precision with some components. In addition, calculating mAP and mAR showed increased performance due to the BoEFC blending process.","PeriodicalId":244591,"journal":{"name":"International Journal of Intelligent Computing and Information Sciences","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124977499","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}

引用次数: 0

SMART Hospital Management Systems Based on Internet of Things: Challenges, Intelligent Solutions and Functional Requirements 基于物联网的智慧医院管理系统:挑战、智能解决方案与功能需求

International Journal of Intelligent Computing and Information Sciences Pub Date : 2021-11-24 DOI: 10.21608/ijicis.2021.82144.1107

Dalia Rizk, H. Hosny, Sayed ElHorbety, Abdel-Badeeh M. Salem

{"title":"SMART Hospital Management Systems Based on Internet of Things: Challenges, Intelligent Solutions and Functional Requirements","authors":"Dalia Rizk, H. Hosny, Sayed ElHorbety, Abdel-Badeeh M. Salem","doi":"10.21608/ijicis.2021.82144.1107","DOIUrl":"https://doi.org/10.21608/ijicis.2021.82144.1107","url":null,"abstract":"Nowadays, Internet of Things (IoT) is invading almost all sectors of life since it is based on connecting living or non-living things together through computer technology. It is responsible for connecting physical objects together through the internet. Healthcare and hospitals are one of the most important sectors that require a lot of attention to transfer their old form of documentation into SMART management systems. It is essential to analyze health data in order to increase the quality of patient’s care. Egypt being a development country is starting to substitute its old governmental systems into electronic SMART technology. IoT devices produce different types of data and transfer them to the cloud computing for storage and analysis. The benefits of using IoT in collecting, transferring, and analyzing patients’ data for the hospitals are attracting a lot of researchers. Therefore, the arrangement of smarter and more money saving healthcare services are becoming highly required. Security and privacy, device communication, and data collection and management are some of the challenges that face the IoT technology especially when used with hospital’s data. Accordingly, a proposed reference model for making SMART hospital management system is under construction in order to achieve the best performance. The model is taking into consideration both the functional and non-functional requirements of the different participants involved in the hospital management system. International Journal of Intelligent Computing and Information Sciences https://ijicis.journals.ekb.eg/ 2 D. k. A. A. Rizk et al.","PeriodicalId":244591,"journal":{"name":"International Journal of Intelligent Computing and Information Sciences","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126396004","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}

引用次数: 4

A Threshold-based Technique to Cluster Ransomware Infected Medical Records on the Internet of Medical Things 基于阈值的医疗物联网病历勒索病毒聚类技术

International Journal of Intelligent Computing and Information Sciences Pub Date : 2021-11-17 DOI: 10.21608/ijicis.2021.79289.1100

Randa ELGawish, M. Hashem, R. Elgohary, Mohamed Abu-Rizka

{"title":"A Threshold-based Technique to Cluster Ransomware Infected Medical Records on the Internet of Medical Things","authors":"Randa ELGawish, M. Hashem, R. Elgohary, Mohamed Abu-Rizka","doi":"10.21608/ijicis.2021.79289.1100","DOIUrl":"https://doi.org/10.21608/ijicis.2021.79289.1100","url":null,"abstract":"Ransomware attacks have led many healthcare hospitals to migrate back to their traditional methods of monitoring patients using pen and paper instead of using implantable medical devices remotely. Studying the behaviour of payload ransomware on an approved actual healthcare dataset obtained from ICU and correctly clustering them into normal and malicious records after manifestation is the primary focus of this study. The features decided were upon the possibility of being captured remotely and their frequency of occurrences. Data transformation was included, to handle the encrypted values and perform data normalization, prior to the clustering process. Unsupervised machine learning gained a lot of attention in the cybersecurity domain for its efficiency and capability of clustering tuples into malicious and benign categories. However, on the internet of medical things (IoMT), due to the constraints of the interconnected nodes, clustering of malicious activities became highly challenging and demanded to secure the infrastructure. This work used unsupervised machine learning techniques of k-means, DBscan, and mean shift compared to a threshold-based method which outperformed them with a precision of 100%. The performance metrics used in this work are; precision, recall and f1 score.","PeriodicalId":244591,"journal":{"name":"International Journal of Intelligent Computing and Information Sciences","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133433989","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}

引用次数: 0

Image colorization using Scaled-YOLOv4 detector 使用Scaled-YOLOv4检测器进行图像着色

International Journal of Intelligent Computing and Information Sciences Pub Date : 2021-11-01 DOI: 10.21608/ijicis.2021.92207.1118

Mennatullah Hesham, H. Khaled, H. Faheem

引用次数: 3

A Location Prediction Methods: state of art A位置预测方法:最新技术

International Journal of Intelligent Computing and Information Sciences Pub Date : 2021-11-01 DOI: 10.21608/ijicis.2021.84159.1111

aml Ismaiel, Walaa K. Gad, T. Mostafa, N. Badr

引用次数: 0

MOBILE CROWDSENSING FRAMEWORK FOR ROAD SURFACE QUALITY DETECTION. 面向路面质量检测的移动众测框架。

International Journal of Intelligent Computing and Information Sciences Pub Date : 2021-11-01 DOI: 10.21608/ijicis.2021.91569.1119

Karim Emara, Aya El-Kady, E. Shaaban, M. ElEliemy

{"title":"MOBILE CROWDSENSING FRAMEWORK FOR ROAD SURFACE QUALITY DETECTION.","authors":"Karim Emara, Aya El-Kady, E. Shaaban, M. ElEliemy","doi":"10.21608/ijicis.2021.91569.1119","DOIUrl":"https://doi.org/10.21608/ijicis.2021.91569.1119","url":null,"abstract":"Received 20218-24; Revised 2021-9-30; Accepted 2021-10-7 Abstract— Smartphones became ubiquitous and are used by so many people, at least to know the driving directions to their destination. Smartphones come with rich embedded sensors (e.g., GPS, accelerometer, and camera) as well as built-in radios (e.g., Bluetooth, Wi-Fi, and Cellular), which both enable users to gather data and distribute it among people at any time or location. These features have come up with the mobile crowdsensing (MCS) development which can be used in a wide range of applications. In this paper, we introduce a complete mobile crowdsensing framework for road surface condition detection. Various modules have been addressed such as task management, data fusion, reputation scoring, incentive awarding, security, and privacy, as well as discussing popular techniques and algorithms utilized in the proposed MCS framework modules. A prototype of the crowd sensing application is designed which is related to our framework. The proposed framework considers the data quality and trustiness between the users and the server as well.","PeriodicalId":244591,"journal":{"name":"International Journal of Intelligent Computing and Information Sciences","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130156039","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}

引用次数: 0

A Review of Leveraging Blockchain based Framework Landscape in Healthcare Systems 在医疗保健系统中利用基于区块链的框架景观的综述

International Journal of Intelligent Computing and Information Sciences Pub Date : 2021-10-08 DOI: 10.21608/ijicis.2021.75531.1095

Mohammed Elghoul

引用次数: 3

Integrating Hexagonal Image Processing with Evidential Probabilistic Supervised Classification Technique to Improve Image Retrieval Systems 结合六边形图像处理与证据概率监督分类技术改进图像检索系统

International Journal of Intelligent Computing and Information Sciences Pub Date : 2021-10-08 DOI: 10.21608/ijicis.2021.83987.1110

A. Amin

{"title":"Integrating Hexagonal Image Processing with Evidential Probabilistic Supervised Classification Technique to Improve Image Retrieval Systems","authors":"A. Amin","doi":"10.21608/ijicis.2021.83987.1110","DOIUrl":"https://doi.org/10.21608/ijicis.2021.83987.1110","url":null,"abstract":"This paper presents a suggested approach to treat a major issue in images classification namely uncertainty. Uncertainty in image classification means some pixels within each cluster are more or less likely to actually belong to this cluster. So, techniques have been used in this paper to deal with the pixels that do not belong to specific regions, helping to raise image retrieval performance. This was done by merging one of the artificial intelligence techniques, which is image processing, with one of the statistical techniques for probability, which is evidential probabilistic. In such contexts, it may be advantageous to resort to two branches: hexagonal image processing based on partial down-sampling of the image resolution in both directions by half using weighted average performance then shifting the remaining pixels in alternate rows. The other is an evidential theory which is rich and flexible formalisms for representing and manipulating uncertain information. Both hexagonal image processing and evidential theory are used to obtain high accuracy in images classification. The hierarchical nature of the hexagonal image processing addressing scheme is exploited to extract features from the image efficiently.","PeriodicalId":244591,"journal":{"name":"International Journal of Intelligent Computing and Information Sciences","volume":"368 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120868228","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}

引用次数: 1

Comparative Study for Anomaly Detection in Crowded Scenes 拥挤场景中异常检测的比较研究

International Journal of Intelligent Computing and Information Sciences Pub Date : 2021-10-08 DOI: 10.21608/ijicis.2021.84588.1112

Mohamed Abdelghafour, Maryam ElBery, Zaki Taha

引用次数: 4