2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)最新文献

{"title":"Comparative Study of PID Controllers for Time-Varying of Steam Distillation Process","authors":"H. Shariff, Mohd Hezri Fazalul Rahiman, R. Adnan, Mohd Hezri Marzaki, M. Tajjudin, M. H. A. Jalil","doi":"10.1109/I2CACIS52118.2021.9495874","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495874","url":null,"abstract":"The steam distillation technique is the earliest technique to extract the essential oil from botanical raw material. Until today, the technique are still relevant and popular among the industrial practitioners due to low manufacturing cost, green environment and higher yield produced. In order to extract the oils, the botanical raw material placed inside the distillation tank which is above the water level. The steam are produced by boiling the water inside the distillation tank. Then, the botanical raw material is heated by the steam and breaking the gland. In order to produce the best quality of essential oils, the con-trolling of steam temperature is important. The disclosure of extracted raw material to the high degree of steam temperature is expose to risk which degradation of essential oils produced. To ensure the process is able to produce the high quality of essential oils; the process dynamic must be regulated by capable controller. In addition, the controller also need to have capability to capture and control dynamic behavior of the system. In this studies, the Small-Medium Scale Steam Distillation System is developed and controlled by PID controller to regulate the temperature at desired setpoint. The development of PID are tuned by the Cohen-Coon, Chchen-Reswicks and Hrones and AMIGO which the controller performance are evaluated based on step test, set point change test and error matrices.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126049982","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}

{"title":"Design and Development of Energy Harvesting Ramp Through Brushed DC Generator Using Gear System","authors":"Jessie R. Balbin, Edward James A. Joves, Mico C. Parreno, E. Chua, Daniel R. Ranque","doi":"10.1109/I2CACIS52118.2021.9495896","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495896","url":null,"abstract":"In the recent years, obtaining a sustainable form of energy to power various autonomous wireless and portable devices is increasingly becoming a matter of concern & various alternate sources of energy have been explored. Energy harvesting technology may be considered as the ultimate solution to replace batteries and provide a long-term power supply for portable devices. The aim of this project is to design and construct a ramp that harvests the kinetic energy from vehicular impacts. The design consists of six stages which include gear mechanism, dc generator, boost converter, transistor circuit, battery level indicator and inverter. The designed prototype is functional, durable, economical, and feasible using affordable components that are readily available in the market.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126669097","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}

{"title":"Variance Component Estimation Dilemma in Cadastral Network Adjustment","authors":"M. A. Abbas, N. M. Hashim, Akram Zulkifli, S. Sulaiman, M. A. Mustafar, Tengku Afrizal Tengku Ali","doi":"10.1109/I2CACIS52118.2021.9495848","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495848","url":null,"abstract":"Land record that preserve the positional accuracy is an absolute objective in cadastral implementation. To achieve that, Department of Surveying and Mapping Malaysia (DSMM) has taken drastic decision by transforming the adjustment procedure from traditional approach (i.e. Bowditch) to the most rigorous procedure (i.e. least square adjustment). However, homogenous precisions as stated in DSMM circular are not align with fundamental principle of least square adjustment (LSA). In LSA implementation, there is a knowledge known as stochastic modeling used to derive the realistic variance. With determination to verify the significance of the realistic variance, this study has designed two assessments which focus on positional errors and sensitivity towards outliers. The artificial errors have been introduced in cadastral dataset, both homogenous and realistic variance were exploited in LSA computation. Through positional accuracy examination, minor advantage has been demonstrated by the outcomes of realistic variance. The conclusion can be made when homogenous variances manage to passed the global test but failed to identify the outliers (artificial errors) in the dataset. To preserve the positional accuracy of land record, realistic variance is a crucial requirement in cadastral network adjustment.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115617915","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}

{"title":"Classification of Oil Palm Fruit Ripeness Using Artificial Neural Network","authors":"Tan Hong, Fazida Hanim Hashim, Thinal Raj, A. B. Huddin","doi":"10.1109/I2CACIS52118.2021.9495857","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495857","url":null,"abstract":"Oil extraction rate (OER) and quality of oil palm can be improved by precisely and accurately classifying the ripeness of oil palm before harvesting. This paper focuses on the development of an artificial neural network (ANN) model for classification of oil palm fruit ripeness using Raman spectra features. In this study, the oil palm fruitlets are from the dura x pisifera (DxP) progenies, harvested from the oil palm plantation of National University of Malaysia (UKM) managed by Khazanah-UKM. A total of 50 samples from unripe, over ripe and ripe fruitlets were collected according to the standard of Malaysia Palm Oil Board (MPOB). Raman spectra for each sample are collected from benchtop Confocal Raman spectrometer. The spectral features for each sample are extracted using pre-processing techniques and used as predictors to train the ANN model. Samples are divided into training set and test set using 50:50 holdout method. The developed model achieves 95.48% prediction accuracy. The accuracy and robustness of the neural network can be improved by increasing the number of samples used in the training.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"134 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131030515","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}

{"title":"Toward a Novel Design for Mechanical Ventilator System to Support Novel Coronavirus (Covid-19) Infected Patients Using IoT Based Technology","authors":"M. N. Mohammed, Halim Syamsudin, M. Abdelgnei, Dharshini Subramaniam, Mohamad Amirul Aznil Mohd Taib, N. Hashim., S. Al-Zubaidi, E. Yusuf","doi":"10.1109/I2CACIS52118.2021.9495900","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495900","url":null,"abstract":"Recent pandemic of Covid-19 has diffused and become concern to the world. The disease is contagious and infected many people within short time. The Covid-19 has infected more than 100 million of reported cases according to the WHO with more than 2 million deaths. Many symptoms found in infectee of Covid-19 such as fever, dry cough, etc. One of the symptoms, shortness of breath, is found in 18.6% of infectee. Part of people infected by COVID-19 suffered from acute difficulty in breathing which need a help from ventilator for breathing. The ventilator plays important role in saving the Covid-19 patients. Ventilator can aid the patient to breath easily and supporting the lungs by letting in the sufficient air while encountering the hard breathing. In developed area, the ventilator is limited while the demand during pandemic gets increased. This paper proposes a low-cost prototype of ventilator for Covid-19 patient which integrated with IoT. The technology supports the clinicians to monitor the patient condition by letting the ventilator and the phone or tablet to be connected and exchange information.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128909730","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}

{"title":"Energy- and Spectral- Efficient Optimization in Cloud RAN based on Dueling Double Deep Q-Network","authors":"Amjad Iqbal, Mau-Luen Tham, Yoong Choon Chang","doi":"10.1109/I2CACIS52118.2021.9495912","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495912","url":null,"abstract":"Cloud radio access network (CRAN) has gained considerable attention for the upcoming cellular network that can offload the mobile data traffic and reduce energy consumption by deploying intelligent distributed multiple remote radio units (RRHs). However, it is still very challenging to achieve an optimal global strategy to maximize the performance of energy efficiency (EE) and spectral efficiency (SE) simultaneously due to non-convex and combinatorial features. Deep reinforcement learning (DRL)-based framework becomes an imperative solution to jointly maximize the EE-SE performance and guarantee the user quality of service (QoS) demands in downlink CRAN. Furthermore, in order to deal with the large state-action space problem, we leverage dueling double deep Q-network (D3QN) to achieve the nearly optimal control strategy. In the end, extensive simulation results demonstrate the effectiveness of the proposed D3QN method over the conventional-DRL methods.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126485815","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}

{"title":"Predicting University's Students Performance Based on Machine Learning Techniques","authors":"D. M. Ahmed, A. Abdulazeez, D. Zeebaree, F. Y. Ahmed","doi":"10.1109/I2CACIS52118.2021.9495862","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495862","url":null,"abstract":"Machine learning algorithms have been used in many fields, like economics, medicine, etc. Education data mining is one of the areas concerned with exploring patterns of data in an educational environment. One of the most important uses is to predict students' performance to improve the existing educational situation. It can be considered as one of the data mining sciences. The ability to predict in advance in many areas has many benefits. In the case of learning, it enables us to know students' levels in advance and identify students who need special attention. This paper proposes using the algorithm (GBDT) which is a machine learning technology used for regression, classification, and ranking tasks, and is part of the Boosting method family to predict university students' performance in final exams. It compares the proposed system's performance with selected machine learning algorithms (Support vector machine, Logistic Regression, Naive Bayes, Gradient Boosted Trees).","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123340604","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}

{"title":"An Optimal Phasor Measurement Unit (PMU) Placement Algorithm with (N-1) Contingency Using Integer Linear Programming (ILP)","authors":"Aaron Kyle Monton, Vanessa Larioza, M. Pacis","doi":"10.1109/I2CACIS52118.2021.9495901","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495901","url":null,"abstract":"Obtaining a good Phasor Measurement Unit (PMU) placement equates with having to deal with less power system demands. It allows the monitoring and maintenance of the network at high precision. In this paper, the researchers formed an algorithm wherein an output of where the PMU should be placed to obtain a complete observable network along with the ranking and screening of all N-1 Contingency is obtained through presenting different cases of IEEE buses largely for IEEE-6, IEEE-9, IEEE-14, and IEEE-30 bus system. This allows that evaluation of the severity of each outage that might occur on a given network. Also, the researchers made use of Gauss-Seidel Method for the algorithm’s load flow and Voltage-Reactive Performance Index in determining the severity of each outage while, the utilization of Integer Linear Programming was used on determining the proper PMU Placement.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124658159","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}

{"title":"Optimal Directional Overcurrent Relay Settings Using Automated Interval Coordination Matrix Algorithm","authors":"J. P. Félix, K. G. Gonong, E. J. Macadaeg, M. Pacis, G. Magwili, K. K. Quiao","doi":"10.1109/I2CACIS52118.2021.9495904","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495904","url":null,"abstract":"Protective relays on any power system network must always operate correctly with minimum operating time to clear a fault. Until now, manual computations and curve-fitting techniques are still being used to coordinate relays on complex electrical grids. To eliminate these methods, this paper provides a time-efficient algorithm that can determine the optimal directional overcurrent relay settings of any power system network by automating the formulation of its Interval Coordination Matrix. The algorithm was first tested by validating the optimal relay settings of the 3 cases of the IEEE 14 Bus System from a previous study. The proposed algorithm reduced the time of simulation by 77.399%. Then, the researchers were also able to acquire the optimal relay settings on all the 642 fault cases of the 46-Bus Sub-Transmission Network. The result of this study provides a proof of time-efficient algorithm that can replace the manual methods in evaluating the settings of protection relays.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115388468","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}

{"title":"Evaluation of the Effects of Using Different Blade Material in the Performance of an Icewind Turbine","authors":"Marison C. Angeles, Bonaobra Paolo Luis V. Bonaobra, Dave Carlo S. Matibag, Marc Daniel N. Molina, Ricky D. Umali, M. Manuel, Jennifer C. Dela Cruz, Roderick C. Tud","doi":"10.1109/I2CACIS52118.2021.9495906","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495906","url":null,"abstract":"A problem that the world faces, especially third world countries is the scarcity and expensiveness of electricity specifically the use of fossil fuel and its surging price. The world faces an era that is slowly degrading its atmosphere and where the carbon emissions are at its all-time high. The solution with renewable energy is not getting cheap to be able to apply these sources into poor rural areas. Icewind turbine is an example of how effective it is but the cost is too high. The focus of the study is to make a design that is cost efficient, can be installed anywhere, and able to supply power to rural roads and areas for adequate lighting. Icewind turbines are types of Vertical Axis Wind Turbines (VAWT) whose blades utilize a Savonius VAWT design. Icewind turbines are already applied in the country Iceland for telecom towers and residential applications such as homes, cabins, and farms. It is also applied in a bus stop located in Reykjavik Iceland as a power hub for Wi-Fi and charging. According to researchers, Icewind turbine is 28.4% more efficient than the typical Savonius Vertical Axis Wind turbine. This research aims to compare the effects of an Icewind Turbine using different materials namely; aluminum, 3D printer filament; Polyethylene terephthalate Glycol (PETG), and stainless steel by fabricating the blades. Using these materials, the researchers gathered data that will determine the best suitable material to fabricate the turbine design that will yield the best performance output and efficiency under the same conditions in three different situations. The materials gave different interpretation in regard to the situation they are under; stiffness and weight made a huge difference on its outcome. The results depended on what type of situation the turbine is. Nevertheless, aluminum blades are the most suitable and most ideal on any given environment.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129302966","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}