International Journal of Computer and Information Technology(2279-0764)最新文献_第2页

An Intelligent Approach to Automatic Query Formation from Plain Text using Artificial Intelligence 一种基于人工智能的纯文本自动查询生成方法

International Journal of Computer and Information Technology(2279-0764) Pub Date : 2022-08-21 DOI: 10.24203/ijcit.v11i3.284

Mohd Akbar, Mohd Shahid Hussain, Mohd Suaib

{"title":"An Intelligent Approach to Automatic Query Formation from Plain Text using Artificial Intelligence","authors":"Mohd Akbar, Mohd Shahid Hussain, Mohd Suaib","doi":"10.24203/ijcit.v11i3.284","DOIUrl":"https://doi.org/10.24203/ijcit.v11i3.284","url":null,"abstract":"Man have always been, inherently, curious creatures. They ask questions in order to satiate their insatiable curiosity. For example, kids ask questions to learn more from their teachers, teachers ask questions to assist themselves to evaluate student performance, and we all ask questions in our daily lives. Numerous learning exchanges, ranging from one-on-one tutoring sessions to thorough exams, as well as real-life debates, rely heavily on questions. One notable fact is that, due to their inconsistency in particular contexts, humans are often inept at asking appropriate questions. It has been discovered that most people have difficulty identifying their own knowledge gaps. This becomes our primary motivator for automating question generation in the hopes that the benefits of an automated Question Generation (QG) system will help humans achieve their useful inquiry needs. QG and Information Extraction (IE) have become two major issues for language processing communities, and QG has recently become an important component of learning environments, systems, and information seeking systems, among other applications. The Text-to-Question generation job has piqued the interest of the Natural Language Processing (NLP), Natural Language Generation (NLG), Intelligent Tutoring System (ITS), and Information Retrieval (IR) groups as a possible option for the shared task. A text is submitted to a QG system in the Text-to-Question generation task. Its purpose would be to create a series of questions for which the text has answers (such as a word, a set of words, a single sentence, a text, a set of texts, a stretch of conversational dialogue, an inadequate query, and so on).","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122447233","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

Comparative Analysis of the Performance of Single Sign-On Authentication Systems with OpenID and OAuth Protocols OpenID和OAuth单点登录认证系统性能比较分析

International Journal of Computer and Information Technology(2279-0764) Pub Date : 2022-08-21 DOI: 10.24203/ijcit.v11i3.277

T. Waluyo, Sutarman

{"title":"Comparative Analysis of the Performance of Single Sign-On Authentication Systems with OpenID and OAuth Protocols","authors":"T. Waluyo, Sutarman","doi":"10.24203/ijcit.v11i3.277","DOIUrl":"https://doi.org/10.24203/ijcit.v11i3.277","url":null,"abstract":"A vast number of people use the internet on a regular basis. The growing number of users will inadvertently bring new issues for both users and administrators as user managers. Users forget their user accounts and passwords when they have too many accounts to surf the internet. Web-based application services at University of Technology Yogyakarta include the Academic Information System (SIA) and E-Learning without exception. Both have the same issue: figuring out how to establish an authentication mechanism that will prevent users from forgetting their accounts on the system. The goal of this research is to create a prototype using Single Sign On (SSO) and compare the performance of the two SSO protocols utilized, OpenID and OAuth. The Explicate Problem, Define Requirements, Design and Develop Artifact, Demonstrate Artifact, Evaluate Artifact, and Communication processes are all part of this study. The results of prototype testing are obtained by attempting to log in using an academic service system account, and users are not required to login/authenticate again while accessing the e-learning page. Performance studies on both protocols revealed that the highest number of users who could login to the system at the same time was 1230 (OpenID) and 1219 (OAuth). In comparison to the OpenID protocol, the OAuth protocol is more consistent in terms of average response time for handling user requests. A greater specification is also required to suit the demands of additional users.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128885071","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

A Cloud-based Framework for Quality Assurance and Enhancement as a Service (QAEaaS) for Universities with Blended Learning Approach 采用混合学习方法的大学质量保证和增强即服务(QAEaaS)的基于云的框架

International Journal of Computer and Information Technology(2279-0764) Pub Date : 2022-08-21 DOI: 10.24203/ijcit.v11i3.228

Ehsan Ahmad, A. Alammary

引用次数: 0

Comparison of A* Algorithm and Greedy Best Search in Searching Fifteen Puzzle Solution A*算法与贪心最优搜索在寻十五解中的比较

International Journal of Computer and Information Technology(2279-0764) Pub Date : 2022-08-21 DOI: 10.24203/ijcit.v11i3.242

Charisma T. Setyobudhi

引用次数: 0

Drone Tracking with Drone using Deep Learning 无人机跟踪与无人机使用深度学习

International Journal of Computer and Information Technology(2279-0764) Pub Date : 2022-08-21 DOI: 10.24203/ijcit.v11i3.238

Ziya Tan, Mehmet Karaköse, Elif Özet

{"title":"Drone Tracking with Drone using Deep Learning","authors":"Ziya Tan, Mehmet Karaköse, Elif Özet","doi":"10.24203/ijcit.v11i3.238","DOIUrl":"https://doi.org/10.24203/ijcit.v11i3.238","url":null,"abstract":"With the development of technology, studies in fields such as artificial intelligence, computer vision and deep learning are increasing day by day. In line with these developments, object tracking and object detection studies have spread over wide areas. In this article, a study is presented by simulating two different drones, a leader and a follower drone, accompanied by deep learning algorithms. Within the scope of this study, it is aimed to perform a drone tracking with drone in an autonomous way. Two different approaches are developed and tested in the simulator environment within the scope of drone tracking. The first of these approaches is to enable the leader drone to detect the target drone by using object-tracking algorithms. YOLOv5 deep learning algorithm is preferred for object detection. A data set of approximately 2500 images was created for training the YOLOv5 algorithm. The Yolov5 object detection algorithm, which was trained with the created data set, reached a success rate of approximately 93% as a result of the training. As the second approach, the object-tracking algorithm we developed is used. Trainings were carried out in the simulator created in the Matlab environment. The results are presented in detail in the following sections. In this article, some artificial neural networks and some object tracking methods used in the literature are explained.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116914919","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

Analysis of Deep-Fake Technology Impacting Digital World Credibility: A Comprehensive Literature Review 深度造假技术对数字世界可信度的影响分析:综合文献综述

International Journal of Computer and Information Technology(2279-0764) Pub Date : 2022-06-21 DOI: 10.24203/ijcit.v11i2.282

M. Akbar, Mohd. Suaib, Mohd Shahid Hussain

引用次数: 0

ENMSJ : An Efficiency Filtering Technique using Bitmap Vectors for n-way Joins in Wireless Sensor Networks 基于位图向量的无线传感器网络n向连接高效滤波技术

International Journal of Computer and Information Technology(2279-0764) Pub Date : 2022-06-11 DOI: 10.24203/ijcit.v11i2.180

Boubekeur Djail

引用次数: 0

A Protection Layer over MapReduce Framework for Big Data Privacy 基于MapReduce框架的大数据隐私保护层

International Journal of Computer and Information Technology(2279-0764) Pub Date : 2022-06-11 DOI: 10.24203/ijcit.v11i2.263

Hidayath Ali Baig

{"title":"A Protection Layer over MapReduce Framework for Big Data Privacy","authors":"Hidayath Ali Baig","doi":"10.24203/ijcit.v11i2.263","DOIUrl":"https://doi.org/10.24203/ijcit.v11i2.263","url":null,"abstract":"In many organizations, big data analytics has become a trend in gathering valuable data insights. The framework MapReduce, which is generally used for this purpose, has been accepted by most organizations for its exceptional characteristics. However, because of the availability of significant processing resources, dispersed privacy-sensitive details can be collected quickly, increasing the widespread privacy concerns. This article reviews some of the existing research articles on the MapReduce framework's privacy issues and proposes an additional layer of privacy protection over the adopted framework. The data is split into bits and processed in the clouds, and two other steps are taken. Hadoop splits the file into bits of a smaller scale. The task tracker then allocates these bits to several mappers. First, the data is split up into key-value pairs, and the intermediate data sets are generated. The efficiency of the suggested approach may then be effectively interpreted. Overall, the proposed method provides improved scalability. The following figures compare execution time with relation to file size and the number of partitions. As privacy protection technique is used, the loss of data content can be appropriately handled. It has been demonstrated that MRPL outperforms current methods in terms of CPU optimization, memory usage, and reduced information loss. Research reveals that the suggested strategy creates significant advantages for Big Data by enhancing privacy and protection. MRPL can considerably solve the privacy issues in Big Data.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114373195","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 Discrete Mathematical Model of the Variable State of the Pandemic 流行病变量状态的离散数学模型

International Journal of Computer and Information Technology(2279-0764) Pub Date : 2022-06-11 DOI: 10.24203/ijcit.v11i2.210

A. Bardavelidze, J. Sztrik, Khatuna Bradvelidze, I. Basheleishvili

引用次数: 0

Feature Extraction using Histogram of Oriented Gradients for Image Classification in Maize Leaf Diseases 面向梯度直方图特征提取用于玉米叶片病害图像分类

International Journal of Computer and Information Technology(2279-0764) Pub Date : 2022-06-11 DOI: 10.24203/ijcit.v11i2.204

Vincent Mbandu Ochango, Geoffrey Mariga Wambugu, John Gichuki Ndia

引用次数: 0