2022 IEEE World AI IoT Congress (AIIoT)最新文献_第7页

Lung cancer prediction model using ensemble learning techniques and a systematic review analysis 肺癌预测模型使用集成学习技术和系统回顾分析

2022 IEEE World AI IoT Congress (AIIoT) Pub Date : 2022-06-06 DOI: 10.1109/aiiot54504.2022.9817326

M. Mamun, Afia Farjana, Miraz Al Mamun, Md Salim Ahammed

{"title":"Lung cancer prediction model using ensemble learning techniques and a systematic review analysis","authors":"M. Mamun, Afia Farjana, Miraz Al Mamun, Md Salim Ahammed","doi":"10.1109/aiiot54504.2022.9817326","DOIUrl":"https://doi.org/10.1109/aiiot54504.2022.9817326","url":null,"abstract":"Lung cancers are malignant lung tumors resulting from uncontrolled growth of lung cells that metastasizes to other parts of the body and can cause death. Although lung cancer cannot be prevented, the risk of cancer development can be lowered. Early detection of lung cancer is essential for patient survival, and machine learning-based prediction models have potential use in predicting lung cancer. Ensemble techniques are compelling and powerful techniques in Machine Learning to improve the prediction accuracy as classifiers. This paper reviewed some research articles on lung cancer prediction models that used machine learning and ensemble learning techniques. Furthermore, we added our newly developed ensemble learning techniques to this paper which was developed based on a survey dataset of 309 people with or without lung cancer by oversampling SMOTE method. The ensemble techniques we used are XGBoost, LightGBM, Bagging, and AdaBoost by k-fold 10 cross-validation method and the attributes our lung cancer prediction models used are age, smoking, yellow fingers, anxiety, peer pressure, chronic disease, fatigue, allergy, wheezing, alcohol, coughing, shortness of breath, swallowing difficulty, and chest pain. Results: According to our analysis, the XGBoost technique performed better than other ensemble techniques and achieved an accuracy of 94.42 %, precision of 95.66%, recall of 94.46%, and AUC of 98.14%, respectively.","PeriodicalId":409264,"journal":{"name":"2022 IEEE World AI IoT Congress (AIIoT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123127870","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: 22

Detecting Amazon Bot Reviewers Using Unsupervised and Supervised Learning 使用无监督和监督学习检测亚马逊机器人评论者

2022 IEEE World AI IoT Congress (AIIoT) Pub Date : 2022-06-06 DOI: 10.1109/aiiot54504.2022.9817207

Brandon Wood, Khaled Slhoub

引用次数: 1

Analysis of Various Vulnerabilities in the Raspbian Operating System and Solutions Raspbian操作系统各种漏洞分析及解决方案

2022 IEEE World AI IoT Congress (AIIoT) Pub Date : 2022-06-06 DOI: 10.1109/aiiot54504.2022.9817202

Christopher Le, Alvaro Martin Grande, AJ Carmine, J. Thompson, Tauheed Khan Mohd

引用次数: 1

A Review of Human Immune Inspired Algorithms for Intrusion Detection Systems 基于人体免疫的入侵检测算法综述

2022 IEEE World AI IoT Congress (AIIoT) Pub Date : 2022-06-06 DOI: 10.1109/aiiot54504.2022.9817213

Chukwuemeka Duru, J. Ladeji-Osias, K. Wandji, Otily Toutsop, Rachida Kone

{"title":"A Review of Human Immune Inspired Algorithms for Intrusion Detection Systems","authors":"Chukwuemeka Duru, J. Ladeji-Osias, K. Wandji, Otily Toutsop, Rachida Kone","doi":"10.1109/aiiot54504.2022.9817213","DOIUrl":"https://doi.org/10.1109/aiiot54504.2022.9817213","url":null,"abstract":"Security and trust of Information Systems are critical in its design as they directly influence users' view and acceptance of such systems. Security can be said to be a contextual and dynamic term as there has not been a holistic, universal, and eternal security measure to date. Recent years have seen a lot of confidential and sensitive information being sent, received, and analyzed on the Internet, and a plethora of investigations on ways of developing comprehensive security solutions like encryptions, pattern recognition, and anomaly detection. This work reviews the human inspired algorithms that are particularly employed in pattern recognition and anomaly detection problems. The work discusses the components of the immune system that inspired the artificial Immune System (AIS) based algorithms for pattern and intrusion detection (IDS) problems. A detailed comparison is made between negative selection, clonal selection, and dendritic cell algorithms (danger theory) which are the three major AIS algorithms. AIS is ubiquitous in computer and information security because it is based on the theories developed through years of study and understanding of the human immune system by immunologist. The strengths and weaknesses of these algorithms are also discussed, and possible improvement suggested.","PeriodicalId":409264,"journal":{"name":"2022 IEEE World AI IoT Congress (AIIoT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130141739","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

Cloud Computing Security and Future 云计算安全与未来

2022 IEEE World AI IoT Congress (AIIoT) Pub Date : 2022-06-06 DOI: 10.1109/aiiot54504.2022.9817186

Patrick Kopacz, M. Chowdhury

引用次数: 0

Data Quality Management Improvement: Case Studi PT BPI 数据质量管理改进:案例研究PT BPI

2022 IEEE World AI IoT Congress (AIIoT) Pub Date : 2022-06-06 DOI: 10.1109/aiiot54504.2022.9817195

Nandang Sunandar, A. Hidayanto

{"title":"Data Quality Management Improvement: Case Studi PT BPI","authors":"Nandang Sunandar, A. Hidayanto","doi":"10.1109/aiiot54504.2022.9817195","DOIUrl":"https://doi.org/10.1109/aiiot54504.2022.9817195","url":null,"abstract":"Data quality is closely related to the quality of information. Low data quality leads to inaccurate information and leads to a decrease in business performance. PT BPI as a company that serves the management of local government financial data needs to control and maintain data quality to remain good. The quality of the data produced is very important to note. This needs to be done to maintain the credibility and capability of PT BPI. This scientific writing aims to provide recommendations for improving data quality management. This scientific writing uses qualitative methods with document studies and several interview sessions. The models used in this scientific writing are Data Quality Management Maturity from Loshin and Data Management Body of Knowledge (DMBOK). The results of measuring the maturity level of data quality management at PT BPI using the D'Lhosin model shows that the organization is still at level one. This indicates that PT BPI does not yet have adequate and thorough basic knowledge about data quality management. PT BPI cannot meet the eight measurement characteristics at level two. Based on the resulting maturity measurement to reach level two, the writer made recommendations from eight unmet characteristics based on DMBOK.","PeriodicalId":409264,"journal":{"name":"2022 IEEE World AI IoT Congress (AIIoT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125501732","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

Proof-of-Concept for a Granular Incident Management Information Sharing Scheme 一种粒度事件管理信息共享方案的概念验证

2022 IEEE World AI IoT Congress (AIIoT) Pub Date : 2022-06-06 DOI: 10.1109/aiiot54504.2022.9817254

Outi-Marja Latvala, Ivo Emanuilov, Tatu Niskanen, Pia Raitio, J. Salonen, Diogo Santos, K. Yordanova

引用次数: 0

Day ahead Power Demand Forecasting for Hybrid Power at the Edge 边缘混合动力的日前电力需求预测

2022 IEEE World AI IoT Congress (AIIoT) Pub Date : 2022-06-06 DOI: 10.1109/aiiot54504.2022.9817155

Calum McCormack, Christopher Wallace, P. Barrie, G. Morison

引用次数: 0

Shift-Invariant Structure-Imposed Convolutional Neural Networks for Direction of Arrival Estimation 基于移位不变结构的卷积神经网络到达方向估计

2022 IEEE World AI IoT Congress (AIIoT) Pub Date : 2022-06-06 DOI: 10.1109/aiiot54504.2022.9817278

K. Adhikari

引用次数: 7

Measurement of Similarity Between Requirement Elicitation and Requirement Specification Using Text Pre-Processing in the Cinemaloka Application 在Cinemaloka应用中使用文本预处理测量需求引出和需求说明之间的相似性

2022 IEEE World AI IoT Congress (AIIoT) Pub Date : 2022-06-06 DOI: 10.1109/aiiot54504.2022.9817193

Junifar Adam Pamungkas, Y. Priyadi, M. J. Alibasa

{"title":"Measurement of Similarity Between Requirement Elicitation and Requirement Specification Using Text Pre-Processing in the Cinemaloka Application","authors":"Junifar Adam Pamungkas, Y. Priyadi, M. J. Alibasa","doi":"10.1109/aiiot54504.2022.9817193","DOIUrl":"https://doi.org/10.1109/aiiot54504.2022.9817193","url":null,"abstract":"There are differences in perceptions between Clients and Developers regarding software requirements specifications therefore, research is needed to determine the perceived similarity between software requirements specifications and requirements elicitation results. The SRS document used in this study is called the Cinemaloka application. This document contains business processes and Requirements Specifications related to website-based cinema ticket reservations. This study aims to measure the suitability of perceptions between developers and clients regarding the specification of software requirements that will be or are being built. There are methods that are combined in this research, namely: determining the similarity of the requirement specification with the elicitation of requirements, analyzing the text contained in the elicitation results, Text Pre-processing, and validation through Gwet's AC1. The results of the measurement of the similarity between the elicitation of requirements and the requirement specification carried out in this study resulted in a match between the applications made and the wishes of potential users/clients. Through stages such as CountVectorizer, PorterStemmer, and Cosine Similarity, resulting in a match of 0.717144. Kappa Score from Gwet's AC1 formula using Python is -0.2222, which means “Less than Chance-agreement,” while the Kappa Score value using a questionnaire filled out by the Expert is 0.5378, which means “Moderate Aggregation.”.","PeriodicalId":409264,"journal":{"name":"2022 IEEE World AI IoT Congress (AIIoT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120956812","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: 6