2022 International Conference on Engineering and Emerging Technologies (ICEET)最新文献_第9页

A Predictive Model for R0 (SARS-COV2) R0 (SARS-COV2)的预测模型

2022 International Conference on Engineering and Emerging Technologies (ICEET) Pub Date : 2022-10-27 DOI: 10.1109/ICEET56468.2022.10007418

Yasmany Fernández-Fernández, S. Allende-Alonso, Ridelio Miranda-Pérez, Gemayqzel Bouza-Allende, Elia N. Cabrera-Álvarez

引用次数: 0

Utilizing Monte Carlo Simulation to Determine Value at Risk in the Wireless Telecommunications Industry 利用蒙特卡罗模拟来确定无线通信行业的风险价值

2022 International Conference on Engineering and Emerging Technologies (ICEET) Pub Date : 2022-10-27 DOI: 10.1109/ICEET56468.2022.10007118

D. H. Syahchari, A. Hapsari

{"title":"Utilizing Monte Carlo Simulation to Determine Value at Risk in the Wireless Telecommunications Industry","authors":"D. H. Syahchari, A. Hapsari","doi":"10.1109/ICEET56468.2022.10007118","DOIUrl":"https://doi.org/10.1109/ICEET56468.2022.10007118","url":null,"abstract":"This study aims to calculate the Value at Risk (VaR) in the stock portfolio using the Monte Carlo simulation method. Value at risk (VaR) is a widely used measure of the risk of loss in a particular portfolio of financial assets. The result of this study is to determine the maximum loss that investors in the portfolio can receive. The experiment was used 500 times to describe the risk. The stock portfolio comes from the Wireless Telecommunication Sector on the Indonesian Stock Exchange, namely PT Smartfren Telecom Tbk (FREN), PT Indosat Tbk (ISAT), and PT XL Axiata Tbk. (EXCL) PT. Telkom Indonesia Tbk (TLKM), The assumption of the calculation of the VaR is based on a capital investment of IDR 200,000,000 in each share. According to the analysis, the results show negative results, which may cause investors losses by investing in the five stocks. The VaR value generated by FREN is+0.3434 maximum loss of IDR (686,709.01); ISAT VaR+0.3732 maximum loss of IDR (746,484.6S); EXCL with a VaR of +0.1731 with a total loss of IDR (346,230.10), TLKM with a VaR of +0.111 with a maximum loss of (222,106.53).","PeriodicalId":241355,"journal":{"name":"2022 International Conference on Engineering and Emerging Technologies (ICEET)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115249559","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

Robust Texture Analysis via Optimal Mass Transport: Application to Medical Images Classification 基于最优质量传递的鲁棒纹理分析:在医学图像分类中的应用

2022 International Conference on Engineering and Emerging Technologies (ICEET) Pub Date : 2022-10-27 DOI: 10.1109/ICEET56468.2022.10007100

Z. Belkhatir, A. Iyer, J. Mathews, Maryam Pouryahya, S. Nadeem, J. Deasy, A. Apte, A. Tannenbaum

{"title":"Robust Texture Analysis via Optimal Mass Transport: Application to Medical Images Classification","authors":"Z. Belkhatir, A. Iyer, J. Mathews, Maryam Pouryahya, S. Nadeem, J. Deasy, A. Apte, A. Tannenbaum","doi":"10.1109/ICEET56468.2022.10007100","DOIUrl":"https://doi.org/10.1109/ICEET56468.2022.10007100","url":null,"abstract":"The emerging field of radiomics, which consists of transforming standard-of-care images into quantifiable scalar statistics, endeavors to reveal the information hidden in these macroscopic images. This field of research has found different applications ranging from phenotyping and tumor classification to outcome prediction and treatment planning. Texture analysis, which often consists of reducing spatial texture matrices to summary scalar features, has been shown to be important in many of the later applications. However, as pointed out in many studies, some of the derived texture statistics are strongly correlated and tend to contribute redundant information; and are also sensitive to the parameters used in their computation, e.g., the number of gray intensity levels. In the present study, we propose new set of spatial texture features that consider texture matrices in general, with an emphasis here on gray-level co-occurrence matrix (GLCM), as non-parametric multivariate objects. The proposed modeling approach avoids evaluating redundant and strongly correlated features and also prevents the feature processing steps. Then, via the Wasserstein distance from optimal mass transport theory, we propose to compare these spatial objects to identify computerized tomography slices with dental artifacts in head and neck cancer. We demonstrate the robustness of the proposed classification approach with respect to the GLCM extraction parameters and the size of the training set. Comparisons with the random forest classifier, which is constructed on scalar texture features, demonstrate the efficiency and robustness of the proposed algorithm.","PeriodicalId":241355,"journal":{"name":"2022 International Conference on Engineering and Emerging Technologies (ICEET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115655655","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

An Empirical Study of Models and APPs Design of the Adoption Ease of Mobile Payments 移动支付普及度模型与app设计实证研究

2022 International Conference on Engineering and Emerging Technologies (ICEET) Pub Date : 2022-10-27 DOI: 10.1109/ICEET56468.2022.10007374

M. W. Rana, Sufang Zhang, Iqra Hamid

{"title":"An Empirical Study of Models and APPs Design of the Adoption Ease of Mobile Payments","authors":"M. W. Rana, Sufang Zhang, Iqra Hamid","doi":"10.1109/ICEET56468.2022.10007374","DOIUrl":"https://doi.org/10.1109/ICEET56468.2022.10007374","url":null,"abstract":"For many people, mobile phones have become more than just communication devices; they’ve become an integral part of their daily lives. Mobile phone users in Pakistan outnumber those with bank accounts by a wide margin. The purpose of this research is to examine how efficiently people are in adoption of Mobile Payment APPs (MPAPPs). The practice of Theory of Acceptance Model has been applied in this context of embracing Mobile Payment APPs. Two of the most popular mobile payment APPs (JazzCash and Easy-Paisa) in Pakistan have been selected for the analysis. Features of the applications have been experimentally analyzed in the context of technology efficiency and users friendly while, eight of the APPs users have also been interviewed to investigate app performance and efficiency. MPAPPs contain a lot of technological problems that are not user-friendly, according to the findings. It has been found that consumers are less likely to transition to new technologies due to speed of transaction, security and unaware about the use of money transfer mobile apps that’s why consumers are paying or receiving money through shopkeepers’ points rather than performing the transaction themselves through their phones.","PeriodicalId":241355,"journal":{"name":"2022 International Conference on Engineering and Emerging Technologies (ICEET)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124823380","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

Machine Learning Classifiers Based on HoG Features Extracted from Locomotive Neutral Section Images 基于机车中性截面图像HoG特征提取的机器学习分类器

2022 International Conference on Engineering and Emerging Technologies (ICEET) Pub Date : 2022-10-27 DOI: 10.1109/ICEET56468.2022.10007093

Christopher Thembinkosi Mcineka, N. Pillay

{"title":"Machine Learning Classifiers Based on HoG Features Extracted from Locomotive Neutral Section Images","authors":"Christopher Thembinkosi Mcineka, N. Pillay","doi":"10.1109/ICEET56468.2022.10007093","DOIUrl":"https://doi.org/10.1109/ICEET56468.2022.10007093","url":null,"abstract":"This paper presents a comparative study on machine learning algorithms for neutral section image classification. The classifiers are trained by employing the Histogram of Oriented Gradient features that are extracted from the neutral section dataset [1]. A neutral section is a phase break that is used on the Transnet freight rail system to separate the single-phase supply from the 25kV three-phase overhead traction supply. The 25kV is a stepped-down voltage from an 8SkV three-phase supply coming from the national grid. While the main purpose of the neutral section is to separate phase voltages, electric locomotives can traverse through these phases by switching On and Off. This auto-switching is possible through induction magnets installed in between the rails and with magnet detection sensors installed underneath the locomotives. However, a computer vision model has been developed, trained, and tested with a neutral section dataset containing images having open and close markers [1]. This paper, therefore, utilises this dataset to provide performance comparison on several machine learning classification algorithms viz. Decision Tree, Discriminant Analysis, Support Vector Machine, K-Nearest Neighbors, Ensemble, Naïve Bayes, and Convolutional Neural Network. A confusion matrix, F1-measure and computation time are employed to measure the performance of each classifier. The MATLAB Classification Learner application was used to obtain the results. The results show that the Linear Support Vector Machine performs best when considering performance and prediction speed. The Linear Support Vector Machine achieved a training accuracy of 93.40% with a test accuracy reaching 94% at a prediction speed of 75 objects per second (computation time).","PeriodicalId":241355,"journal":{"name":"2022 International Conference on Engineering and Emerging Technologies (ICEET)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124668834","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

Implementation of an Intelligent Parking System 智能停车系统的实现

2022 International Conference on Engineering and Emerging Technologies (ICEET) Pub Date : 2022-10-27 DOI: 10.1109/ICEET56468.2022.10007136

J. Arshad, Chaudhry Ahmed Ijaz, Adnan Yousaf, Sania Habib, Ateeq ur Rehman, Huzafa Abid, R. M. Asif

引用次数: 0

A Global Trend of The Smart Home Research: A Bibliometric Analysis 智能家居研究的全球趋势:文献计量分析

2022 International Conference on Engineering and Emerging Technologies (ICEET) Pub Date : 2022-10-27 DOI: 10.1109/ICEET56468.2022.10007252

D. H. Syahchari, H. Saroso

{"title":"A Global Trend of The Smart Home Research: A Bibliometric Analysis","authors":"D. H. Syahchari, H. Saroso","doi":"10.1109/ICEET56468.2022.10007252","DOIUrl":"https://doi.org/10.1109/ICEET56468.2022.10007252","url":null,"abstract":"Smart Home research started in 2000. Since then, Smart Home has attracted the attention of many researchers, and several studies have been conducted. This study aims to chart Smart Home research trends using bibliometric analyses from all years up to the publication date indexed in Scopus. We use keywords related to Smart Home in the Scopus database. Analysis techniques that use parameters include the year of publication, Scopus quartile range, year of publication, type of publication, journal publication, the publication of the most frequently cited maps, and density display mapping. The results show that the Q1 journal dominated since the first Smart Home publication in 2000 and peaked in 2013. The journal article type is the most commonly published compared to research conferences and other publications. Journal publications show the majority of IEEE transactions in consumer electronics. Three Smart Home publications have been cited more than 1563 times. This study also found that the words ‘smart home’, ‘technology,’ and ‘management’ are widely used by researchers. For future research, you should use keywords like ‘smart home energy management,’ ‘smart home environment,’ ‘sensor,’ ‘electric vehicle,’ and ‘smart home technology.’","PeriodicalId":241355,"journal":{"name":"2022 International Conference on Engineering and Emerging Technologies (ICEET)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116488475","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

Waste reduction in production for plasma cutting process by applying the MES system 应用MES系统减少等离子切割生产过程中的废弃物

2022 International Conference on Engineering and Emerging Technologies (ICEET) Pub Date : 2022-10-27 DOI: 10.1109/ICEET56468.2022.10007119

Khwanchanok Pimpetch, J. Srithorn

{"title":"Waste reduction in production for plasma cutting process by applying the MES system","authors":"Khwanchanok Pimpetch, J. Srithorn","doi":"10.1109/ICEET56468.2022.10007119","DOIUrl":"https://doi.org/10.1109/ICEET56468.2022.10007119","url":null,"abstract":"This research aims to improve the plasma cutting process to increase the efficiency of the process by applying the MES system (Manufacturing Execution Systems). This study focused on increasing efficiency in the plasma cutting process for supporting future customers’ needs, reducing the cost of waste in the plasma cutting process, and creating a more standardized production process. The MES system directly linked pc and PLC (Programmable Logic Controller) to increase operational efficiency. The system allows auto-input of all parameters needed for the plasma cutting process through the connection. Furthermore, this system enables the robot to receive the cutting program command based on the customer’s command data in the MES Server by creating conditions from the Kepware application. The experimental results show that improvement by the application of the MES system can reduce the production time by %07.55. The amount of waste caused by the plasma cutting process due to cutting errors by %100. Furthermore, it allows the company to reduce the cost of repairing time and reduce the cost of producing new parts to replace the scrap.","PeriodicalId":241355,"journal":{"name":"2022 International Conference on Engineering and Emerging Technologies (ICEET)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121767145","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

Bounded Issues on a Class of Integral Equations with Weakly Singular Kernels 一类弱奇异核积分方程的有界问题

2022 International Conference on Engineering and Emerging Technologies (ICEET) Pub Date : 2022-10-27 DOI: 10.1109/ICEET56468.2022.10007179

Shihchung Chiang

引用次数: 0

Comparative Study of Binary Classifiers for Reducing False Negative Detection of Melanoma in Skin Lesions 二分类器减少皮肤病变中黑色素瘤假阴性检测的比较研究

2022 International Conference on Engineering and Emerging Technologies (ICEET) Pub Date : 2022-10-27 DOI: 10.1109/ICEET56468.2022.10007359

Amith Jooravan, S. Reddy, N. Pillay

{"title":"Comparative Study of Binary Classifiers for Reducing False Negative Detection of Melanoma in Skin Lesions","authors":"Amith Jooravan, S. Reddy, N. Pillay","doi":"10.1109/ICEET56468.2022.10007359","DOIUrl":"https://doi.org/10.1109/ICEET56468.2022.10007359","url":null,"abstract":"Reliable and accurate classification of a skin lesion is essential to the early diagnosis of skin cancer, especially melanoma. Traditional classification methods require performing a biopsy on the lesion. The overlap of benign and malignant clinical features may lead to incorrect melanoma diagnosis and/or excising an excessive number of benign lesions. This paper focuses on the use of machine learning to aid physicians with the non-invasive classification methodology of skin lesions, whilst prioritising the minimization of false negative classification. The clinical features used are based on the ABCD rule, representing the asymmetry, border, colour and diameter of the lesion. The dermoscopic images chosen are of melanoma lesions less than 0,76mm in thickness which corresponds to the early stages of cancer. The investigated classification methods include K-Nearest neighbours (KNN), Naïve Bayes and linear support vector machine. (LSVM). This research proposes the use of a LSVM machine learning algorithm to classify a skin lesion as being either melanoma or non-melanoma with the lowest false negative rate of the investigated classification. Classification accuracy of 85% and a false negative rate of 5% is achieved.","PeriodicalId":241355,"journal":{"name":"2022 International Conference on Engineering and Emerging Technologies (ICEET)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127146419","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