2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)最新文献_第5页

Review Study of the Impact of Artificial Intelligence on Cyber Security 人工智能对网络安全的影响研究综述

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10099788

Moaiad Ahmed Khder, Samer Shorman, Dana Anwar Showaiter, A. Zowayed, Sara Isa Zowayed

引用次数: 1

Designing of Intrusion Detection System Using an Ensemble of Artificial Neural Network and Honey Badger Optimization Algorithm 基于人工神经网络和蜜獾优化算法的入侵检测系统设计

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10100161

R. Chinnasamy, Malliga Subramanian, N. Sengupta

引用次数: 0

Visual Paragraph Generation: Review 视觉段落生成:回顾

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10099830

K. Almohsen

引用次数: 0

Predicting Acute Respiratory Failure Using Fuzzy Classifier 应用模糊分类器预测急性呼吸衰竭

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10099746

Fatema Khalaf, Subhashini S. Baskaran

引用次数: 0

Parallel Self Organizing Neural Network (PSONN) Prediction of Water Saturation in Carbonate Reservoirs 并行自组织神经网络(PSONN)预测碳酸盐岩储层含水饱和度

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10099865

G. Hamada, Abdelrageeb Al Gathe, Abbas Al Khudafi

{"title":"Parallel Self Organizing Neural Network (PSONN) Prediction of Water Saturation in Carbonate Reservoirs","authors":"G. Hamada, Abdelrageeb Al Gathe, Abbas Al Khudafi","doi":"10.1109/ITIKD56332.2023.10099865","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10099865","url":null,"abstract":"Carbonate reservoir rocks are considered heterogeneous and it is due to complex pores pattern caused by different diagenetic factors that are modifying the microstructures and matrix system. parameters and finally leading to significant petrophysical heterogeneity and anisotropy. Water saturation determination in carbonate reservoirs is crucial parameter to determine initial reserve of given an oil field. Water saturation determination using electrical measurements is based on Archie's formula. Consequently, accuracy of Archie's formula parameters affects seriously water saturation values. Determination of Archie's parameters (a, m and n) is proceeded by three techniques conventional, CAPE and 3-D. This work introduces the hybrid system of parallel self-organizing neural network (PSONN) targeting an accepted value of Archie's parameters and consequently reliable water saturation values. This work focuses on calculation of water saturation using Archie's formula. Different determination techniques of Archie's parameters such as conventional technique, CAPE technique and 3-D technique have been tested and then water saturation was calculated using Archie's formula with the calculated parameters (a, m and n). This study introduced parallel self-organizing neural network (PSONN) algorithm predict Archie's parameters and determination of water saturation. Results have shown that predicted Arche's parameters (a, m and n) are highly accepted with statistical analysis lower statistical error and higher correlation coefficient than conventional determination techniques. The developed PSONN algorithm used big number of measurement points from core plugs of carbonate reservoir rocks. PSONN algorithm provided reliable water saturation values. We believe that PSONN can improve or may replace the conventional techniques to determine Archie's parameters and determination of reserve estimate in carbonate reservoirs.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124569826","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

Propose a Recommender System to Dynamically Align Higher Education Curriculums With 4IR Market Needs 提出一个推荐系统，使高等教育课程与4IR市场需求动态匹配

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10099924

Z. Hasan, Subhashini S. Baskaran

{"title":"Propose a Recommender System to Dynamically Align Higher Education Curriculums With 4IR Market Needs","authors":"Z. Hasan, Subhashini S. Baskaran","doi":"10.1109/ITIKD56332.2023.10099924","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10099924","url":null,"abstract":"The Fourth Industrial Revolution (4IR) era leads to significant economic shifts due to technological advancement. The changes introduced by 4IR raise concern about its impact on employment due to jobs automation, or lack of workforce equipped with the required skills. It is essential to reshape the curriculums according to 4IR requirements to mitigate unemployment risks. The objective of this paper is to automatically identify the rapidly changing 4IR jobs skills and identify the gap between curriculums and modern industry jobs as well. In addition, the proposed solution has the capability of delivering efficient gap analysis recommendations that could be used in the curriculum enhancement decision-making process. The proposed recommender system clusters jobs based on K-Means and TF-IDF algorithms and then identifies the similarity and dissimilarity by utilizing the Cosine Similarity algorithm. The solution utilizes the algorithm's result to construct gap analysis recommendations that curriculum developers can use to align curriculums with 4IR requirements. The results of the classification report indicated that the system was effectively capable of clustering jobs based on skills similarity and identifying the 4IR gap.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128647360","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

Resistant to Technology and Digital Banking Behavior Among Jakarta's Generation Z 雅加达Z世代对科技的抵制和数字银行行为

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10099594

Michael Christian, Henilia Yulita, Y. Yuniarto, Suryo Wibowo, E. Indriyarti, S. Sunarno

{"title":"Resistant to Technology and Digital Banking Behavior Among Jakarta's Generation Z","authors":"Michael Christian, Henilia Yulita, Y. Yuniarto, Suryo Wibowo, E. Indriyarti, S. Sunarno","doi":"10.1109/ITIKD56332.2023.10099594","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10099594","url":null,"abstract":"When sophisticated technology is integrated into digital banking services with the goal of providing customers with an easy, fast, safe, and enjoyable experience, then details about customer behavior when receiving services are based on this sophisticated technology. Therefore, the goal of this study is to investigate how ease of use, usefulness, security, and self-efficacy affect resistance to technology or behavior when using digital banks among Jakarta's generation Z. In this quantitative study, partial least-square structural equation modeling (PLS-SEM) is used. Specifically, SmartPLS 3.0 is used to analyze the data collected from 157 participants. According to the findings of this study, participants consider the factor of resistance to digital banking technology to be more important than the impact on usage behavior. Issues related to security are also an important factor for customers when using technology such as digital banking services. Notably, the limitation of this research is that it does not use aspects of the technology used in each digital banking service. Furthermore, comparing users from different generations can help to improve the findings of this study.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129684916","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

Hybrid Deep Learning for Channel Estimation and Power Assignment for MISO-NOMA System 基于混合深度学习的MISO-NOMA系统信道估计与功率分配

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10099781

Mohamed Gaballa, M. Abbod, Sadeq Alnasur

{"title":"Hybrid Deep Learning for Channel Estimation and Power Assignment for MISO-NOMA System","authors":"Mohamed Gaballa, M. Abbod, Sadeq Alnasur","doi":"10.1109/ITIKD56332.2023.10099781","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10099781","url":null,"abstract":"In this paper, the influence of Deep Neural Network (DNN) in predicting both the channel parameters and the power factors for users in a Power Domain Multi-Input Single-Output Non-Orthogonal Multiple Access (MISO-NOMA) system is inspected. In channel prediction based Deep Learning (DL) approach, we integrate the Long Short Term Memory (LSTM) learning network into NOMA system in order that LSTM can be utilized to predict the channel coefficients. Additionally, in Deep Learning based power estimation method, we introduce an algorithm based on Convolutional Neural Network (CNN) to predict and allocate the power factor for each user in MISO-NOMA cell. DNN is trained online using channel statistics in order to approximate the channel coefficients and allocate the power factors for each user, so that these parameters can be utilized by the receiver to recover the desired data. Besides, this paper introduce a framework where channel prediction based on LSTM layer and power approximation based on CNN can be jointly employed for multiuser detection in MISO-NOMA. In this work, Power factors are optimized analytically based on maximizing the sum-rate of users to derive the optimum power factors. Simulation outcomes for distinct metrics have verified the dominance of the channel estimation and power predication based DNN over standard approaches.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132984767","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

Welcome Message from the Conference Chair 会议主席致欢迎辞

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/itikd56332.2023.10100107

Wasan Shakir Awad

引用次数: 0

The Impact of Data Augmentation on Sentiment Analysis of Translated Textual Data 数据扩充对翻译文本数据情感分析的影响

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10099851

Thuraya Omran, B. Sharef, C. Grosan, Yongming Li

引用次数: 1