Pub Date : 2021-06-26DOI: 10.1109/I2CACIS52118.2021.9495887
M. Alomari, Ismail Ahmed Al-Qasem Al-Hadi, M. Yusoff, I. Sulaiman
A survey by Malaysian Communication and Multimedia Commission (MCMC) has shown that Internet users in Malaysia has increased up to 88.7% in year 2020 compared to 76.9% in year 2016 which is quite high increase in percentage. The pervasive use of smartphones and computers nowadays as well as the availability of high-speed Internet access has brought a new way of promoting products. E-commerce is a buy and sell system that can be accessed globally around the world. This system can provide efficient strategies for promoting products and services. It is widely agreed that even small enhancements in promotion techniques can increase the profitability of any e-commerce system. In this paper, a research has been conducted to study methods to enhance product promotion among Malaysians. The study investigates through a survey the factors affecting users’ WTP (willing-to-pay) during performing e-commerce transaction as well as factors what attract/repel them more. To achieve the study aim, a group of 385 respondents throughout Malaysia have been involved in this research through questionnaire study. Detailed analysis has been introduced to clarify the results. The study has identified the top e-commerce platforms that are used by Malaysians to execute product promotion. The results show that promotion through e-commerce platforms could increase profitability and help businesses to expand rapidly. This is due to the fast market penetration of online promoting compared to conventional one.
{"title":"A Survey on Product Promotion via E-commerce Platforms - Case Study in Malaysia","authors":"M. Alomari, Ismail Ahmed Al-Qasem Al-Hadi, M. Yusoff, I. Sulaiman","doi":"10.1109/I2CACIS52118.2021.9495887","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495887","url":null,"abstract":"A survey by Malaysian Communication and Multimedia Commission (MCMC) has shown that Internet users in Malaysia has increased up to 88.7% in year 2020 compared to 76.9% in year 2016 which is quite high increase in percentage. The pervasive use of smartphones and computers nowadays as well as the availability of high-speed Internet access has brought a new way of promoting products. E-commerce is a buy and sell system that can be accessed globally around the world. This system can provide efficient strategies for promoting products and services. It is widely agreed that even small enhancements in promotion techniques can increase the profitability of any e-commerce system. In this paper, a research has been conducted to study methods to enhance product promotion among Malaysians. The study investigates through a survey the factors affecting users’ WTP (willing-to-pay) during performing e-commerce transaction as well as factors what attract/repel them more. To achieve the study aim, a group of 385 respondents throughout Malaysia have been involved in this research through questionnaire study. Detailed analysis has been introduced to clarify the results. The study has identified the top e-commerce platforms that are used by Malaysians to execute product promotion. The results show that promotion through e-commerce platforms could increase profitability and help businesses to expand rapidly. This is due to the fast market penetration of online promoting compared to conventional one.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129816446","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}
Pub Date : 2021-06-26DOI: 10.1109/I2CACIS52118.2021.9495872
Christian Dale B. Comprado, Justin A. Diño, Francis Rafael P. Mateo, Paul Michael H. Salazar, M. Manuel, Jennifer C. Dela Cruz, Marvin S. Verdadero
The Additive Manufacturing industry and its continuous rise are both promising and problematic at the same time because of the waste produced. In this study, the researchers fabricated a modified filament extruder based on the "Precious Plastic" project by Dave Hakkens. This study serves two purposes, to lessen the costs involved with procuring 3-D printing filament to use and to reduce the environmental impact of plastic waste such as failed 3-D prints. The testing involves the variation of nozzles, extrusion temperatures, and motor speed with key results: 190℃ and 10rpm setup yielded the filament closest to the targeted value by having a mean diameter of 1.7490mm; motor speed and its interaction with temperature are significant to the determination of filament diameter; and in terms of tolerance, the filaments produced from testing is within the ± 0.05 range with 95% confidence level. For future testing, the inclusion of physical properties such as strength and flexibility can provide a concrete basis for selecting optimal settings and determining the quality of filament produced.
{"title":"Fabrication, Testing and Statistical Analysis of a Project-Based Single-Screw Filament Extruder","authors":"Christian Dale B. Comprado, Justin A. Diño, Francis Rafael P. Mateo, Paul Michael H. Salazar, M. Manuel, Jennifer C. Dela Cruz, Marvin S. Verdadero","doi":"10.1109/I2CACIS52118.2021.9495872","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495872","url":null,"abstract":"The Additive Manufacturing industry and its continuous rise are both promising and problematic at the same time because of the waste produced. In this study, the researchers fabricated a modified filament extruder based on the \"Precious Plastic\" project by Dave Hakkens. This study serves two purposes, to lessen the costs involved with procuring 3-D printing filament to use and to reduce the environmental impact of plastic waste such as failed 3-D prints. The testing involves the variation of nozzles, extrusion temperatures, and motor speed with key results: 190℃ and 10rpm setup yielded the filament closest to the targeted value by having a mean diameter of 1.7490mm; motor speed and its interaction with temperature are significant to the determination of filament diameter; and in terms of tolerance, the filaments produced from testing is within the ± 0.05 range with 95% confidence level. For future testing, the inclusion of physical properties such as strength and flexibility can provide a concrete basis for selecting optimal settings and determining the quality of filament produced.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129838118","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}
Pub Date : 2021-06-26DOI: 10.1109/I2CACIS52118.2021.9495864
Toya Acharya, Ishan Khatri, A. Annamalai, M. Chouikha
The exponential rise in internet technologies and allied applications encompass a significantly large number of networked devices have alarmed academia-industries to achieve more effective and robust security solutions. Undeniably, digitization has led to revolution globally; however, the security threats, breaches, and subsequent losses indicate the need for a robust cybersecurity solution. Unlike classical intrusion detection systems (IDS), network IDS (NIDS) has been becoming more challenging due to continuous changes in attack-patterns and anomaly behavior. As solution data-driven machine learning methods have exhibited better by learning over network traffic information and detecting anomalies; however, its generalization over a network with both known and unknown patterns remains questionable. Moreover, most of the classical approaches fail to address the key issues of class-imbalance, level-of-significance centric feature selection, normalization and over-fitting problems resulting in different performance by varied machine learning models. In this paper, a novel and robust heterogeneous ensemble machine learning model is developed to detect anomalies in NIDS. The proposed model first applies sub-sampling to alleviate the class-imbalance problem of NIDS datasets. Subsequently, performing normalization using the Min-Max algorithm, it mapped the input data in the range of 0 to 1, thus alleviating overfitting and convergence. The feature reduction is used to reduce the features; it retained the most suitable features without imposing computational overheads, often in meta-heuristic-based approaches. Finally, the proposed NIDS solution designed a Heterogeneous ensemble learning model with J48, k-NN, SVM, Bagging, AdaBoost, and RF algorithms as base-classifier to perform two-class as well as multi-class classification over feature-selected NSL-KDD, KDD99, and UNSW-NB-15 datasets. Performance assessment in terms of true-positive rate, false positive rate and AUC revealed that the proposed NIDS model exhibited better performance than the standalone classifiers and superior to other existing anomaly detection methods.
{"title":"Efficacy of Heterogeneous Ensemble Assisted Machine Learning Model for Binary and Multi-Class Network Intrusion Detection","authors":"Toya Acharya, Ishan Khatri, A. Annamalai, M. Chouikha","doi":"10.1109/I2CACIS52118.2021.9495864","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495864","url":null,"abstract":"The exponential rise in internet technologies and allied applications encompass a significantly large number of networked devices have alarmed academia-industries to achieve more effective and robust security solutions. Undeniably, digitization has led to revolution globally; however, the security threats, breaches, and subsequent losses indicate the need for a robust cybersecurity solution. Unlike classical intrusion detection systems (IDS), network IDS (NIDS) has been becoming more challenging due to continuous changes in attack-patterns and anomaly behavior. As solution data-driven machine learning methods have exhibited better by learning over network traffic information and detecting anomalies; however, its generalization over a network with both known and unknown patterns remains questionable. Moreover, most of the classical approaches fail to address the key issues of class-imbalance, level-of-significance centric feature selection, normalization and over-fitting problems resulting in different performance by varied machine learning models. In this paper, a novel and robust heterogeneous ensemble machine learning model is developed to detect anomalies in NIDS. The proposed model first applies sub-sampling to alleviate the class-imbalance problem of NIDS datasets. Subsequently, performing normalization using the Min-Max algorithm, it mapped the input data in the range of 0 to 1, thus alleviating overfitting and convergence. The feature reduction is used to reduce the features; it retained the most suitable features without imposing computational overheads, often in meta-heuristic-based approaches. Finally, the proposed NIDS solution designed a Heterogeneous ensemble learning model with J48, k-NN, SVM, Bagging, AdaBoost, and RF algorithms as base-classifier to perform two-class as well as multi-class classification over feature-selected NSL-KDD, KDD99, and UNSW-NB-15 datasets. Performance assessment in terms of true-positive rate, false positive rate and AUC revealed that the proposed NIDS model exhibited better performance than the standalone classifiers and superior to other existing anomaly detection methods.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114023815","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}
Pub Date : 2021-06-26DOI: 10.1109/I2CACIS52118.2021.9495852
Mohd Rizman Sultan Mohd, J. Johari, F. Ruslan, Noorfadzli Abdul Razak, Salmiah Ahmad, A. S. Mohd Shah
The radiant energy from the sun is defined as solar radiation. It had been discovered as a renewable energy which can provide electricity supplies using a photovoltaic system. Before developing the system, a preliminary test must be carried out to perform the analysis of solar energy potential in that specific area. This preliminary test is known as a modeling technique. The technique will use the related parameters as an input to predict the solar radiation value. Since there are multiple parameters used for solar radiation prediction model development, there had been multiple attempts on using only certain parameters to produce predictions for solar radiation value. This paper will review and further analyzed several works presented by the previous studies on developing solar radiation prediction models using various parameters with their results. With the findings, the implementation of the Neural Network Autoregressive Model with Exogenous Input (NNARX) on solar radiation prediction carried out for the different input parameter configurations. Based on the results, it shows that the solar radiation prediction model development using more input parameters produced the best prediction performance with the R2 value of 0.9329.
{"title":"Analysis on Parameter Effect for Solar Radiation Prediction Modeling using NNARX","authors":"Mohd Rizman Sultan Mohd, J. Johari, F. Ruslan, Noorfadzli Abdul Razak, Salmiah Ahmad, A. S. Mohd Shah","doi":"10.1109/I2CACIS52118.2021.9495852","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495852","url":null,"abstract":"The radiant energy from the sun is defined as solar radiation. It had been discovered as a renewable energy which can provide electricity supplies using a photovoltaic system. Before developing the system, a preliminary test must be carried out to perform the analysis of solar energy potential in that specific area. This preliminary test is known as a modeling technique. The technique will use the related parameters as an input to predict the solar radiation value. Since there are multiple parameters used for solar radiation prediction model development, there had been multiple attempts on using only certain parameters to produce predictions for solar radiation value. This paper will review and further analyzed several works presented by the previous studies on developing solar radiation prediction models using various parameters with their results. With the findings, the implementation of the Neural Network Autoregressive Model with Exogenous Input (NNARX) on solar radiation prediction carried out for the different input parameter configurations. Based on the results, it shows that the solar radiation prediction model development using more input parameters produced the best prediction performance with the R2 value of 0.9329.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115134582","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}
Pub Date : 2021-06-26DOI: 10.1109/I2CACIS52118.2021.9495875
Nor Syafikah Pezol, M. Rahiman, R. Adnan, M. Tajjudin
This paper presents a study on temperature control of steam temperature using steam distillation plant for essential oils extraction process. The steam temperature was controlled in a certain range to preserve the quality of essential oils. However, this study is focusing on evaluating the effect of parameter change in the process while maintaining the desired temperature. Two controllers were proposed in this study which are the First generation of CRONE (CRONE-1) and Fractional order PID using FOMCON (FOPID-FOMCON) controllers. Both controllers are robust because they inherit the iso-damping property from the fractional-order terms. Evaluations and comparison of both controllers were done by simulation where the time constant will be varied within 10%.
{"title":"Comparison of the CRONE-1 and FOPID Controllers for Steam Temperature Control of the Essential Oil Extraction Process","authors":"Nor Syafikah Pezol, M. Rahiman, R. Adnan, M. Tajjudin","doi":"10.1109/I2CACIS52118.2021.9495875","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495875","url":null,"abstract":"This paper presents a study on temperature control of steam temperature using steam distillation plant for essential oils extraction process. The steam temperature was controlled in a certain range to preserve the quality of essential oils. However, this study is focusing on evaluating the effect of parameter change in the process while maintaining the desired temperature. Two controllers were proposed in this study which are the First generation of CRONE (CRONE-1) and Fractional order PID using FOMCON (FOPID-FOMCON) controllers. Both controllers are robust because they inherit the iso-damping property from the fractional-order terms. Evaluations and comparison of both controllers were done by simulation where the time constant will be varied within 10%.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116458939","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}
Pub Date : 2021-06-26DOI: 10.1109/I2CACIS52118.2021.9495879
Z. Lim, Neo Yong Quan
In this paper, we present a six-degree of freedom (DOF) robotic arm that can be directly controlled by brainwaves, also known as electroencephalogram (EEG) signals. The EEG signals are acquired using an open-source device known as OpenBCI Ultracortex Mark IV Headset. In this research, inverse kinematics is implemented to simplify the controlling method of the robotic into 8 commands for the end-effector: forward, backward, upward, downward, left, right, open and close. A deep learning method namely convolutional neural network (CNN) which constructed using Python programming language is used to classify the EEG signals into 8 mental commands. The recall rate and precision of the 8 mental command classification using the CNN model in this research are up to 91.9% and 92%. The average inference time for the system is 1.5 seconds. Hence, this research offers a breakthrough technology that allows disabled persons for example paralyzed patients and upper limbs amputees to control a robotic arm to handle their daily life tasks.
在本文中，我们提出了一种可以通过脑电波(也称为脑电图(EEG)信号)直接控制的六自由度机械臂。脑电图信号是使用开源设备获取的，该设备被称为OpenBCI ultrortex Mark IV耳机。在本研究中，采用逆运动学的方法，将机器人的控制方法简化为末端执行器的8个命令:向前、向后、向上、向下、左、右、打开和关闭。利用Python编程语言构建卷积神经网络(convolutional neural network, CNN)作为深度学习方法，将EEG信号分类为8个心理指令。本研究中使用CNN模型对8个心理命令分类的查全率和查准率分别达到91.9%和92%。系统的平均推理时间为1.5秒。因此，这项研究提供了一项突破性的技术，可以让瘫痪患者和上肢截肢者等残疾人控制机械臂来处理他们的日常生活任务。
{"title":"Convolutional Neural Network Based Electroencephalogram Controlled Robotic Arm","authors":"Z. Lim, Neo Yong Quan","doi":"10.1109/I2CACIS52118.2021.9495879","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495879","url":null,"abstract":"In this paper, we present a six-degree of freedom (DOF) robotic arm that can be directly controlled by brainwaves, also known as electroencephalogram (EEG) signals. The EEG signals are acquired using an open-source device known as OpenBCI Ultracortex Mark IV Headset. In this research, inverse kinematics is implemented to simplify the controlling method of the robotic into 8 commands for the end-effector: forward, backward, upward, downward, left, right, open and close. A deep learning method namely convolutional neural network (CNN) which constructed using Python programming language is used to classify the EEG signals into 8 mental commands. The recall rate and precision of the 8 mental command classification using the CNN model in this research are up to 91.9% and 92%. The average inference time for the system is 1.5 seconds. Hence, this research offers a breakthrough technology that allows disabled persons for example paralyzed patients and upper limbs amputees to control a robotic arm to handle their daily life tasks.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126183458","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}
Pub Date : 2021-06-26DOI: 10.1109/I2CACIS52118.2021.9495892
Nurul Aida Noor Aidee, M. Johar, M. H. Alkawaz, Asif Iqbal Hajamydeen, Mohammed Sabbih Hamoud Al-Tamimi
A Smart Contract is an agreement in the form of computer code that is made between two individuals. In a blockchain environment, smart contracts executed and stored in a shared ledger that are not modifiable. Ethereum is one of the major platforms used for smart contracts, where solidity basically is a high-level programming language used in the Ethereum to build smart contracts. Recent vulnerabilities found by the coders were not updated in analysis tool (SmartCheck) and therefore incapable of detecting vulnerabilities. No definitions of patterns were existing to detect these vulnerabilities. This paper focuses on the improvement of the Smartcheck analysis method to convert the source code of solidity into an intermediate representation based on XML and verifies this against the XPath patterns. Moreover, the latest vulnerabilities were listed to create new patterns to detect such vulnerabilities. The proposed method was evaluated with real world datasets and the results were compared with similar tools.
{"title":"Vulnerability Assessment on Ethereum Based Smart Contract Applications","authors":"Nurul Aida Noor Aidee, M. Johar, M. H. Alkawaz, Asif Iqbal Hajamydeen, Mohammed Sabbih Hamoud Al-Tamimi","doi":"10.1109/I2CACIS52118.2021.9495892","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495892","url":null,"abstract":"A Smart Contract is an agreement in the form of computer code that is made between two individuals. In a blockchain environment, smart contracts executed and stored in a shared ledger that are not modifiable. Ethereum is one of the major platforms used for smart contracts, where solidity basically is a high-level programming language used in the Ethereum to build smart contracts. Recent vulnerabilities found by the coders were not updated in analysis tool (SmartCheck) and therefore incapable of detecting vulnerabilities. No definitions of patterns were existing to detect these vulnerabilities. This paper focuses on the improvement of the Smartcheck analysis method to convert the source code of solidity into an intermediate representation based on XML and verifies this against the XPath patterns. Moreover, the latest vulnerabilities were listed to create new patterns to detect such vulnerabilities. The proposed method was evaluated with real world datasets and the results were compared with similar tools.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129498483","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}
Pub Date : 2021-06-26DOI: 10.1109/I2CACIS52118.2021.9495853
H. Abdulrazzak, N. Tan, Nurul Asyikin Mohd Radzi
The dedicated vehicular ad-hoc network (VANET) is a communication model as vehicles can communicate with other vehicles directly or via fixed nodes called Roadside Units (RSU). It has become necessary to find supporting protocols for RSU to increase their efficiency, and thus increase the efficiency of the network. Since these nodes are distributed on the roads, it is important to find appropriate ways to distribute them to increase data transfer and reduce their energy consumption. In this paper, a zigzag distribution method is proposed and a mathematical model of Right Side–Left Side (RS-LS) is used to reduce the energy consumption of RSU and compare it with the main chain protocol. Two different cases were taken, Case-1-is for low density with 20 vehicles and Case-2-is for high density with 40 vehicles. The proposed method succeeded in saving energy and reduce the consumption in both cases, by 60% and 44%, respectively.
{"title":"Minimizing Energy Consumption in Roadside Unit of Zigzag Distribution Based on RS-LS Technique","authors":"H. Abdulrazzak, N. Tan, Nurul Asyikin Mohd Radzi","doi":"10.1109/I2CACIS52118.2021.9495853","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495853","url":null,"abstract":"The dedicated vehicular ad-hoc network (VANET) is a communication model as vehicles can communicate with other vehicles directly or via fixed nodes called Roadside Units (RSU). It has become necessary to find supporting protocols for RSU to increase their efficiency, and thus increase the efficiency of the network. Since these nodes are distributed on the roads, it is important to find appropriate ways to distribute them to increase data transfer and reduce their energy consumption. In this paper, a zigzag distribution method is proposed and a mathematical model of Right Side–Left Side (RS-LS) is used to reduce the energy consumption of RSU and compare it with the main chain protocol. Two different cases were taken, Case-1-is for low density with 20 vehicles and Case-2-is for high density with 40 vehicles. The proposed method succeeded in saving energy and reduce the consumption in both cases, by 60% and 44%, respectively.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129865644","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}
Pub Date : 2021-06-26DOI: 10.1109/i2cacis52118.2021.9495868
{"title":"[I2CACIS 2021 Front cover]","authors":"","doi":"10.1109/i2cacis52118.2021.9495868","DOIUrl":"https://doi.org/10.1109/i2cacis52118.2021.9495868","url":null,"abstract":"","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120857564","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}
Pub Date : 2021-06-26DOI: 10.1109/I2CACIS52118.2021.9495854
Jessie R. Balbin, Marianne M. Sejera, Vernadette B. Borcena, Bebeth Jean B. Olivar, Albert Elli G. Paragas
Using ultrasonography recommends Antenatal care in improving maternal and fetal outcomes, especially in breeding programs. However, some veterinary clinics and farms in rural and remote areas cannot invest in ultrasound devices, given that these machines are costly. This study developed a low-cost wireless Doppler ultrasound device for remote fetal assessment by utilizing a Doppler module. The developed device will assess the fetal status, estimated gestational age, and estimated parturition through the fetal heart rate reading. It was tested to 40 samples, comprising 20 dogs and 20 cats, with a 95% accuracy rate than the Veterinarian's assessment.
{"title":"Wireless Cloud-based Scan Conversion through a Single Element Transducer for Fetal Heart Rate Assessment using Doppler Ultrasonography with Mobile Application","authors":"Jessie R. Balbin, Marianne M. Sejera, Vernadette B. Borcena, Bebeth Jean B. Olivar, Albert Elli G. Paragas","doi":"10.1109/I2CACIS52118.2021.9495854","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495854","url":null,"abstract":"Using ultrasonography recommends Antenatal care in improving maternal and fetal outcomes, especially in breeding programs. However, some veterinary clinics and farms in rural and remote areas cannot invest in ultrasound devices, given that these machines are costly. This study developed a low-cost wireless Doppler ultrasound device for remote fetal assessment by utilizing a Doppler module. The developed device will assess the fetal status, estimated gestational age, and estimated parturition through the fetal heart rate reading. It was tested to 40 samples, comprising 20 dogs and 20 cats, with a 95% accuracy rate than the Veterinarian's assessment.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115633541","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}
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