2020 8th International Conference on Intelligent and Advanced Systems (ICIAS)最新文献_第2页

Classification of Diabetes Mellitus using Ensemble Algorithms 用集成算法对糖尿病进行分类

2020 8th International Conference on Intelligent and Advanced Systems (ICIAS) Pub Date : 2021-07-13 DOI: 10.1109/ICIAS49414.2021.9642508

Noor Azmiya Bt Sirajun Noor, I. Elamvazuthi, N. Yahya

{"title":"Classification of Diabetes Mellitus using Ensemble Algorithms","authors":"Noor Azmiya Bt Sirajun Noor, I. Elamvazuthi, N. Yahya","doi":"10.1109/ICIAS49414.2021.9642508","DOIUrl":"https://doi.org/10.1109/ICIAS49414.2021.9642508","url":null,"abstract":"Diabetes Mellitus (DM) is one of the most prevalent diseases in the world today which is associated by having high glucose levels in the body either due to inadequate production of insulin or the body cell’s not responding towards the produced insulin. Data mining and machine learning techniques can be extremely useful in classification of DM considering the need to have a shift from current traditional methods which use sharp needles to draw blood towards a non - invasive method. The objective of this study is to perform DM classification using various machine learning algorithms. In this paper, individual classifiers such as Support Vector Machine, Naïve Bayes, Bayes Net, Decision Stump, k - Nearest Neighbors, Logistic Regression, Multilayer Perceptron and Decision Tree are experimented. Apart from that, ensemble methods such as bagging, boosting, hybrid classifier using combinations of Random Forest with other base classifiers and ensemble algorithm which is the Random Forest has also been studied. Proposed DM classification model is chosen based on an optimized model reflected by their accuracy and performance of the model. In this research, it was found that performance of ensemble method using hybrid classifier of Random Forest - Bayes Net model has proven to be the best DM classification model with an accuracy of 83.91% and AUC of 0.904 using the Pima Indian Diabetes Dataset (PIDD).","PeriodicalId":212635,"journal":{"name":"2020 8th International Conference on Intelligent and Advanced Systems (ICIAS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128756559","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: 2

Design Analysis of Energy Harvester: The Impact of Speed of Motion and Mass of Device 能量采集器设计分析:运动速度和装置质量的影响

2020 8th International Conference on Intelligent and Advanced Systems (ICIAS) Pub Date : 2021-07-13 DOI: 10.1109/ICIAS49414.2021.9642631

N. Gurusamy, I. Elamvazuthi, N. Yahya

引用次数: 0

Modeling of Scattering the Electromagnetic Pulses by High Voltage Converters 高压变换器电磁脉冲散射的建模

2020 8th International Conference on Intelligent and Advanced Systems (ICIAS) Pub Date : 2021-07-13 DOI: 10.1109/ICIAS49414.2021.9642587

R. Kannan, Sundar Ramakrishnan, K. Porkumaran, Srinivasan Prabakar, R. Karthikeyan

引用次数: 0

Design and Simulation of MEMS Electrostatic Resonator for Ammonia Gas Detection Based on SOIMUMPs 基于SOIMUMPs的微机电系统氨气体检测静电谐振器的设计与仿真

2020 8th International Conference on Intelligent and Advanced Systems (ICIAS) Pub Date : 2021-07-13 DOI: 10.1109/ICIAS49414.2021.9642706

Saeed S. Ba Hashwan, M. H. M. Md Khir, Y. Al-Douri, A. Yousif, H. Ramza, S. Arjo

{"title":"Design and Simulation of MEMS Electrostatic Resonator for Ammonia Gas Detection Based on SOIMUMPs","authors":"Saeed S. Ba Hashwan, M. H. M. Md Khir, Y. Al-Douri, A. Yousif, H. Ramza, S. Arjo","doi":"10.1109/ICIAS49414.2021.9642706","DOIUrl":"https://doi.org/10.1109/ICIAS49414.2021.9642706","url":null,"abstract":"The analytical modeling, design, and simulation of micromachined MEMS resonator for ammonia gas detection is presented in this paper. The MEMS resonator is designed to be vibrated electrostatically using interdigitated comb fingers. The demonstrated device is designed to be capable to carry micro-ring resonator and vibrated in-plane laterally to enhance the sensitivity of the gas detection. This MEMS resonator working principle is based on the changes in the output signal wavelength due to the change in the effective refractive index introduced by the ammonia gas. The resonant frequency of the actuator and the pull-in voltage have been calculated theoretically and found to be 11.15 kHz and 79.7 V respectively. The design and simulation of the micromachined micro-resonator has been carried out using CoventorWare software. Furthermore, the mathematically modeled results were verified using the finite element analysis software and the result shows a good agreement within 1.06% error between the modeled and simulated frequencies where the modeled and the simulated frequencies are found to be 11.15 kHz and 11.27 kHz respectively.","PeriodicalId":212635,"journal":{"name":"2020 8th International Conference on Intelligent and Advanced Systems (ICIAS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122726392","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 Hybridized Pre-Processing Method for Detecting Tuberculosis using Deep Learning 一种基于深度学习的肺结核检测混合预处理方法

2020 8th International Conference on Intelligent and Advanced Systems (ICIAS) Pub Date : 2021-07-13 DOI: 10.1109/ICIAS49414.2021.9642622

A. Elashmawy, I. Elamvazuthi, Syed Saad Azhar Ali, Elango Natarajan, S. Paramasivam

引用次数: 0

Blood Pressure Measuring Device for Hypertension Monitoring Based on Internet of Things with E-KTP Authentication 基于E-KTP认证的物联网高血压监测血压测量装置

2020 8th International Conference on Intelligent and Advanced Systems (ICIAS) Pub Date : 2021-07-13 DOI: 10.1109/ICIAS49414.2021.9642538

Muhammad Kirana Baiduri, D. Perdana, S. Sussi

引用次数: 0

Condition based maintenance for generator and transformer system 发电机和变压器系统的状态维护

2020 8th International Conference on Intelligent and Advanced Systems (ICIAS) Pub Date : 2021-07-13 DOI: 10.1109/ICIAS49414.2021.9642563

Kalaimany Arumuggam, A. D. Saliang, M. Fuad, M. Yusof Abu Bakar, Adrian Buayeh Tadam, M. Naim

引用次数: 0

A Comparative Study on Performance of Drop Casted and Inkjet Printed Humidity Sensor 水滴浇铸与喷墨印刷湿度传感器性能的比较研究

2020 8th International Conference on Intelligent and Advanced Systems (ICIAS) Pub Date : 2021-07-13 DOI: 10.1109/ICIAS49414.2021.9642625

Q. J. Liew, H. F. Hawari, L. H. Wah, M. Khir, S. Sulaiman

{"title":"A Comparative Study on Performance of Drop Casted and Inkjet Printed Humidity Sensor","authors":"Q. J. Liew, H. F. Hawari, L. H. Wah, M. Khir, S. Sulaiman","doi":"10.1109/ICIAS49414.2021.9642625","DOIUrl":"https://doi.org/10.1109/ICIAS49414.2021.9642625","url":null,"abstract":"In this study, flexible inkjet-printed capacitive humidity sensors were developed using Fujifilm Dimatix 2850 printer. The interdigitated electrodes (IDE) of the sensors were printed with the commercial silver nano-particles ink (AgNPs ink) on the polyethylene terephthalate (PET). To develop the sensing material on the humidity sensors, two methodologies were investigated. The former was a drop-cast method while the latter was an inkjet-printing method. Both utilized graphene oxide (GO) as the sensing material mixed with polyacrylic acid (PAA). The results in capacitance were obtained from experiments conducted in the humidity range from 30 % RH to 80 % RH. It was found that the former to be more suitable working in humidity range of 30 % RH up to 70% RH while the latter more suitable working in humidity range of 30 % RH up to 60% RH. The methodology using the drop-casted method presented higher sensitivity 9.766 pF/% RH compared to the inkjet printing method which was 0.441 pF/% RH. The sensors also exhibited good stabilities during short-term and long-term stability tests under predefined humidity and temperature.","PeriodicalId":212635,"journal":{"name":"2020 8th International Conference on Intelligent and Advanced Systems (ICIAS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127680846","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

Fault Classification and Location in Three-Phase Transmission Lines Using Wavelet-based Machine Learning 基于小波机器学习的三相输电线路故障分类与定位

2020 8th International Conference on Intelligent and Advanced Systems (ICIAS) Pub Date : 2021-07-13 DOI: 10.1109/ICIAS49414.2021.9642641

Chew Kia Yuan Zerahny, L. Yun, W. Raymond, K. Mei

{"title":"Fault Classification and Location in Three-Phase Transmission Lines Using Wavelet-based Machine Learning","authors":"Chew Kia Yuan Zerahny, L. Yun, W. Raymond, K. Mei","doi":"10.1109/ICIAS49414.2021.9642641","DOIUrl":"https://doi.org/10.1109/ICIAS49414.2021.9642641","url":null,"abstract":"A long transmission line was simulated to collect fault data from one end of the line, which makes it a cost-efficient approach. Using Discrete Wavelet Transform (DWT), the essential characteristics of the fault type and its location can be extracted. Twelve types of mother wavelets with decomposition levels up to level 9 were compared and Haar wavelet was found to be most suitable. The resulting output was used as features to train several machine learning models for location and classification of faults. Fault estimation was carried out using the features extracted. By relying on the fault estimation, the search area for the fault can be reduced, thus decreasing the time needed to locate the actual fault. The artificial neural network (ANN) performed very well for fault classification having up to 100% accuracy. Another ANN was used for fault zone location and the accuracy obtained was 95.9%. Other machine learning models perform slightly poorer than ANN but had acceptable accuracy for fault location and classification. The results obtained considered single-phase to ground, two-phase, two-phase to ground and three-phase to ground faults. The faults occurred at various fault inception angles. The faults also included low and high fault impedances. The results indicate that this approach managed to detect and locate the fault zone with reasonable accuracy on a long transmission line model using data measured from one end only.","PeriodicalId":212635,"journal":{"name":"2020 8th International Conference on Intelligent and Advanced Systems (ICIAS)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115951119","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

New Technique for Tracking the Global Peaks of PV System under Partial Shaded Conditions 部分荫蔽条件下光伏系统全局峰值跟踪新技术

2020 8th International Conference on Intelligent and Advanced Systems (ICIAS) Pub Date : 2021-07-13 DOI: 10.1109/ICIAS49414.2021.9642637

A. E. Ibrahim, N. M. Nor, M. Romlie, K. Hasan

{"title":"New Technique for Tracking the Global Peaks of PV System under Partial Shaded Conditions","authors":"A. E. Ibrahim, N. M. Nor, M. Romlie, K. Hasan","doi":"10.1109/ICIAS49414.2021.9642637","DOIUrl":"https://doi.org/10.1109/ICIAS49414.2021.9642637","url":null,"abstract":"Partial Shaded Condition (PSC) is a process of non-optimal power capture in PV systems; this phenomenon occurs when one or more PV solar cells are shaded by external factors. It generates one global peak and many local peaks in the Power voltage curve. Thus, it makes a sudden change in cell irradiance and leads to non-optimal power capture in PV systems. In this work, a novel MPPT technique was proposed to solve the problem of tracking speed and accuracy in the shaded PV systems. FLC and GA-FLC with Power Scanning Technique (PST) algorithms were designed, developed and simulated using MATLAB/Simulink. The performance of FLC and GAFLC with PST was figured out under varied operating conditions. Proposed FLC tracked the PV power under PSC in 0. 4s with 92% accuracy, meanwhile, GA-FLC with PST achieved 0. 4s as tracking speed with 99% accuracy using Buck converter. Proposed GA-FLC with PST showed high capability in terms of tracking speed and accuracy compared to MPPT techniques. Finally, the dynamic performance of GA-FLC with the PST algorithm was compared to other techniques reported in the works of literature. Improved tracking speed and accuracy were obtained compared to other methods. For future work, experimental work in terms of tracking speed and accuracy should be carried out to validate the performance of the proposed algorithm.","PeriodicalId":212635,"journal":{"name":"2020 8th International Conference on Intelligent and Advanced Systems (ICIAS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125915277","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