2022 International Conference on Business Analytics for Technology and Security (ICBATS)最新文献_第3页

Expert Systems and Neural Networks and their Impact on the Relevance of Financial Information in the Jordanian Commercial Banks 专家系统和神经网络及其对约旦商业银行金融信息相关性的影响

2022 International Conference on Business Analytics for Technology and Security (ICBATS) Pub Date : 2022-02-16 DOI: 10.1109/ICBATS54253.2022.9759047

Ghazi M. Qasaimeh, Anwar Al-Gasaymeh, T. Kaddumi, Qais Kilani

{"title":"Expert Systems and Neural Networks and their Impact on the Relevance of Financial Information in the Jordanian Commercial Banks","authors":"Ghazi M. Qasaimeh, Anwar Al-Gasaymeh, T. Kaddumi, Qais Kilani","doi":"10.1109/ICBATS54253.2022.9759047","DOIUrl":"https://doi.org/10.1109/ICBATS54253.2022.9759047","url":null,"abstract":"The current study aims to discern the impact of expert systems and neural network on the Jordanian commercial banks. In achieving the objective, the study employed descriptive analytical approach and the population consisted of the 13 Jordanian commercial banks listed at Amman Stock Exchange-ASE. The primary data were obtained by using a questionnaire with 188 samples distributed to a group of accountants, internal auditors, and programmers, who constitute the study sample. The results unveiled that there is an impact of the application of expert systems and neural networks on the relevance of financial information in Jordanian commercial banks. It also revealed that there is a high level of relevance of financial information in Jordanian commercial banks. Accordingly, the study recommended the need for banks to keep pace with the progress and development taking place in connection to the process and environment of expertise systems by providing modern and developed devices to run various programs and expert systems. It also recommended that, Jordanian commercial banks need to rely more on advanced systems to operate neural network technology more efficiently.","PeriodicalId":289224,"journal":{"name":"2022 International Conference on Business Analytics for Technology and Security (ICBATS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130830363","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: 7

Vocabulary Taught Via Mobile Application Gamification: Receptive, Productive and Long-Term Usability of Words Taught Using Quizlet and Quizlet Live 通过移动应用程序游戏化教授的词汇:使用Quizlet和Quizlet Live教授的词汇的接受性，生产性和长期可用性

2022 International Conference on Business Analytics for Technology and Security (ICBATS) Pub Date : 2022-02-16 DOI: 10.1109/ICBATS54253.2022.9759019

John Senior

引用次数: 0

Improve the security for voice cryptography in the RSA algorithm 提高了RSA算法中语音加密的安全性

2022 International Conference on Business Analytics for Technology and Security (ICBATS) Pub Date : 2022-02-16 DOI: 10.1109/ICBATS54253.2022.9759016

Sara Al-Ghamdi, Hala Al-Sharari

引用次数: 0

Analysis of Anomaly Detection of Diabetes Using Decision Tree Classifier and an Innovative Back Propagation Algorithm using Fit as a Parameter 基于决策树分类器和以拟合为参数的创新反向传播算法的糖尿病异常检测分析

2022 International Conference on Business Analytics for Technology and Security (ICBATS) Pub Date : 2022-02-16 DOI: 10.1109/ICBATS54253.2022.9759012

Aluru Pradeepik, R. Sabitha

{"title":"Analysis of Anomaly Detection of Diabetes Using Decision Tree Classifier and an Innovative Back Propagation Algorithm using Fit as a Parameter","authors":"Aluru Pradeepik, R. Sabitha","doi":"10.1109/ICBATS54253.2022.9759012","DOIUrl":"https://doi.org/10.1109/ICBATS54253.2022.9759012","url":null,"abstract":"Aim: The work aims to evaluate the accuracy and precision in the analysis of Anomaly detection of diabetes using Decision tree and Backpropagation classification algorithm. Materials and Methods: Back Propagation Classification is applied on a Pima Indian diabetes dataset that consist of 769 records. A machine learning techniques for earlier prediction of diabetes disease which compares Decision tree and Back Propagation Classification algorithms has been proposed and developed. The sample size was measured as 27 per group using Glower. Sample size was calculated using clincalc analysis, with alpha and beta values 0.07 and 0.5, 95% confidence, pretest power 80% and enrolment ratio 1. The accuracy and precision of the classifiers was evaluated and recorded. Results: The accuracy was maximum in predicting diabetes usingBack propagation (77.29%) with minimum mean error when compared with Decision tree classifier (70.09%). There is a significant difference of 0.05 between the classifiers. Conclusion: The study proves that Back Propagation exhibits better accuracy than Decision tree classifier in predicting diabetes.","PeriodicalId":289224,"journal":{"name":"2022 International Conference on Business Analytics for Technology and Security (ICBATS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122593948","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

Machine Learning Optimization using Bat Algorithm to Classify Sentiment of Twitter Users 基于Bat算法的推特用户情感分类机器学习优化

2022 International Conference on Business Analytics for Technology and Security (ICBATS) Pub Date : 2022-02-16 DOI: 10.1109/ICBATS54253.2022.9759029

Ema Utami, Suwanto Raharjo, Omar Muhammad Altoumi Alsyaibani, Candra Adipradana

{"title":"Machine Learning Optimization using Bat Algorithm to Classify Sentiment of Twitter Users","authors":"Ema Utami, Suwanto Raharjo, Omar Muhammad Altoumi Alsyaibani, Candra Adipradana","doi":"10.1109/ICBATS54253.2022.9759029","DOIUrl":"https://doi.org/10.1109/ICBATS54253.2022.9759029","url":null,"abstract":"Social-media is a very effective communication media in today’s digital era. Twitter is one of them which widely used by Internet users. Huge number of tweets has encouraged research in the field of text mining, especially in sentiment analysis. Most of sentiment analysis researches which mined data in Bahasa used TF-IDF to assign weight on every word in corpus. This traditional method resulted low accuracy when tested using machine learning methods. In this study, instead of using TF-IDF, we implemented Bat Algorithm to weight every word in corpus. We tested this on Naïve Bayes, Decision Tree and K-NN methods. The result of this study shows that Naïve Bayes, Decision Tree and K-NN methods which classified data weighted using TF-IDF reached accuracy 33.58%, 32.82% and 33.61%, respectively. Afterwards, words in corpus were weighted using Bat Algorithm and tested using the same methods. The test result shows that Naïve Bayes, Decision Tree and K-NN methods reached 39.01%, 76.63% and 66.15% in respectively. It can be inferred that Bat Algorithm usage for weighting words in corpus improves machine learning algorithms to classify sentiment of Twitter users. Moreover, it can be identified that the biggest improvement occurred in Decision Tree algorithm which increased 43.81% accuracy. On the other hand, improvement in Naïve Bayes algorithm is still minor compared to other machine learning algorithms.","PeriodicalId":289224,"journal":{"name":"2022 International Conference on Business Analytics for Technology and Security (ICBATS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122623369","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 Novel Approach to Estimation Precision and Recall for Star Rating Online Customers Based on Negative Hotel Reviews using Multinomial Naive Bayes over Multischeme Classifier 基于多方案分类器的多项朴素贝叶斯估计酒店差评的精度和召回率

2022 International Conference on Business Analytics for Technology and Security (ICBATS) Pub Date : 2022-02-16 DOI: 10.1109/ICBATS54253.2022.9759081

S. Shajahan, T. Poovizhi

引用次数: 0

Fuzzy System For Covid-19 Disease Detection 新型冠状病毒病模糊检测系统

2022 International Conference on Business Analytics for Technology and Security (ICBATS) Pub Date : 2022-02-16 DOI: 10.1109/ICBATS54253.2022.9759014

A. Rehman, Hafiz Muhammad Haroon, J. Malik, Afia Saeed, Asad Ali, Karamath Ateeq

引用次数: 0

Application of Computational Intelligence and Machine Learning to Conventional Operational Research Methods 计算智能和机器学习在传统运筹学方法中的应用

2022 International Conference on Business Analytics for Technology and Security (ICBATS) Pub Date : 2022-02-16 DOI: 10.1109/ICBATS54253.2022.9759033

Atif Ali, Raed A. Said, H. Rizwan, Khurram Shehzad, I. Naz

引用次数: 5

Smart Waste Management and Classification System for Smart Cities using Deep Learning 基于深度学习的智慧城市智能废物管理和分类系统

2022 International Conference on Business Analytics for Technology and Security (ICBATS) Pub Date : 2022-02-16 DOI: 10.1109/ICBATS54253.2022.9759087

M Zahid Hasan, Muhammad Adnan Khan, Ghassan F. Issa, Ayesha Atta, Alimardani Akram, M. Hassan

{"title":"Smart Waste Management and Classification System for Smart Cities using Deep Learning","authors":"M Zahid Hasan, Muhammad Adnan Khan, Ghassan F. Issa, Ayesha Atta, Alimardani Akram, M. Hassan","doi":"10.1109/ICBATS54253.2022.9759087","DOIUrl":"https://doi.org/10.1109/ICBATS54253.2022.9759087","url":null,"abstract":"For modern city environments to be renewable and clean, waste management and recycling are essential. Solid waste management, disposal, and recycling are issues in many Pakistani cities, particularly Karachi and Lahore. The combination of the IoTs and deep learning offers a modular technique to data categorization and real-time examining. This article illustrates a capable “Smart trash management and categorization system” based on the “internet of things (IoT)” and DL. The article provides an architectural idea for a microchips-based garbage bin that uses numerous measuring instruments to connect with the method to gather wastes as quickly as possible. The “Internet of Things (IoT)” is used in the suggested data monitoring solution to offer real-time data control. In addition, in this smart waste management and categorization scheme, a waste classification model based on convolutional neural networks was deployed. This waste classification technique will be used to sort rubbish into several categories at the waste-collecting plant to increase recycling. This proposed system offers complete trash management and recycling solution in smart cities, from waste collection to waste management and classification.","PeriodicalId":289224,"journal":{"name":"2022 International Conference on Business Analytics for Technology and Security (ICBATS)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115743115","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: 43

Conceptual Framework for Adversarial Thinking Adoption in Experiential Learning Model for Robotics Learning 机器人学习体验学习模型中对抗性思维应用的概念框架

2022 International Conference on Business Analytics for Technology and Security (ICBATS) Pub Date : 2022-02-16 DOI: 10.1109/ICBATS54253.2022.9758998

Noridayu Adnan, Siti Hendon Sheikh Abdullah, R. Yusof, Noor Faridatul Ainun Zainal

{"title":"Conceptual Framework for Adversarial Thinking Adoption in Experiential Learning Model for Robotics Learning","authors":"Noridayu Adnan, Siti Hendon Sheikh Abdullah, R. Yusof, Noor Faridatul Ainun Zainal","doi":"10.1109/ICBATS54253.2022.9758998","DOIUrl":"https://doi.org/10.1109/ICBATS54253.2022.9758998","url":null,"abstract":"In this high-technological era, cybersecurity is well-known due to various cybercrimes that happen from time to time. Adversarial thinking, which can be explained as one ability of strategic thinking commonly applied by the hacker, needs to be disclosed to society as one of cybersecurity awareness. Therefore, this study highlights the usage of adversarial thinking in education by adopting the adversarial thinking elements in the experiential learning model. The conceptual framework of adopting adversarial thinking has been developed by using the Matsuo-Nagata learning model 2020. The Matsuo-Nagata learning model has only been applied in the training programs; therefore, to apply the current learning model to the education and cybersecurity field, a new learning model has been revised and adopted with the adversarial thinking aspect. Robotic learning has been chosen as the learning tool for the revised experiential learning model. This study involves three elements of adversarial thinking: analytical, creative, and practical. By analyzing the previous study and the survey results from the expert, the findings show that adversarial thinking is suitable and essential to be adopted in the experiential learning model.","PeriodicalId":289224,"journal":{"name":"2022 International Conference on Business Analytics for Technology and Security (ICBATS)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115755031","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