{"title":"Forecasting the annual carbon dioxide emissions of Malaysia using Lasso-GMDH neural network-based","authors":"A. Shabri","doi":"10.1109/iscaie54458.2022.9794541","DOIUrl":"https://doi.org/10.1109/iscaie54458.2022.9794541","url":null,"abstract":"In this study, it was intended to develop an accurate forecasting model for the annually CO2 emission of Malaysia in the short-term. For this purpose, the Group Method of Data Handling (GMDH) model as one of the Neural Networks (NNs) was utilized to structure a nonlinear time-series based forecasting model. In order to improve GMDH prediction accuracy, this paper highlights the drawbacks of using the least square method to solve model parameters and attempts to use the Lasso method (Lasso-GMDH). A case study with the proposed model was carried out for one-year-ahead forecasting of CO2 emissions data during the years 2000-2016. Three different models: grey model GM(1,N), artificial neural network (ANN) and GMDH models were investigated to model the Co2 emission forecast. The comparison revealed that Lasso-GMDH model has the highest general performance for forecasting the annually CO2 emission of Malaysia.","PeriodicalId":395670,"journal":{"name":"2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115949851","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}
Ashik Adnan, G. M. Mahbubur Rahman, M. M. Hossain, Mahfuza Sultana Mim, Md. Khalilur Rahman
{"title":"A Deep Learning Based Autonomous Electric Vehicle on Unstructured Road Conditions","authors":"Ashik Adnan, G. M. Mahbubur Rahman, M. M. Hossain, Mahfuza Sultana Mim, Md. Khalilur Rahman","doi":"10.1109/iscaie54458.2022.9794498","DOIUrl":"https://doi.org/10.1109/iscaie54458.2022.9794498","url":null,"abstract":"Autonomous driving vehicles are too known as driver-less cars which is one of the foremost astounding advances of the twenty-first century, anticipated to be driver-less, effective, and crash dodging ideal urban cars of the future. Autonomous cars actually sense the environment, navigate and fulfill human transportation capabilities without any human inclusion. Cameras, radar, lidar, GPS, and navigational pathways help this type of vehicle detect its surroundings. Even when the conditions alter, advanced control systems interpret sensory data to maintain their locations. Autonomous vehicles are on their way to completely replacing the world’s transportation system. To reach this goal automobile industries have begun working in this zone to realize the potential and unravel the challenges as of now. A few companies have also started their trail. It will aid in reducing traffic, reducing pollution, avoiding maximum accidents, saving time, conserving energy, and improving human safety. As a result, with the aim and vision of eradicating these challenges from our country, we are focusing on an independent car that will assist us in saving ourselves from the daily revelations we generally confront on the road. Besides, it is high time we began working in Bangladesh on a driver-less vehicle","PeriodicalId":395670,"journal":{"name":"2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130654020","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":"Final Year Project Allocation System Techniques: A Systematic Literature Review","authors":"Nik Intan Syahiddatul Ilani Jailani, Al-Fahim Mubarak Ali, Syahrulanuar Ngah","doi":"10.1109/iscaie54458.2022.9794501","DOIUrl":"https://doi.org/10.1109/iscaie54458.2022.9794501","url":null,"abstract":"Undergraduate students require to undertake the Final Year Project (FYP) for the completion of their studies. The allocation of FYP can be fundamental for students to be allocated to the project based on their interest with supervisors that expertise in their project field. However, the usual practice for the FYP allocation process is done manually by the FYP Coordinator. In this paper, few studies have been made on existing FYP allocation systems. Besides, we also focus on allocation techniques to provide the best decision which satisfied both lecturer and student preferences and lesser the workload of the FYP Coordinator. The existing FYP System which includes subject allocation and implemented the allocation techniques were highlighted and presented. The efficiency of the system is identified through the highest project allocation accuracy and shows the best FYP system and allocation technique. Therefore, this paper focused on a systematic literature review (SLR) from a previous study regarding the existing Final Year Project Allocation System and allocation techniques.","PeriodicalId":395670,"journal":{"name":"2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131140818","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}
N. J, R. Sam, N. H. Abdul Wahab, N. Sunar, M. A. Ahsan, Keng Yinn Wong
{"title":"Development of Smart Home Automation System Based on PLC","authors":"N. J, R. Sam, N. H. Abdul Wahab, N. Sunar, M. A. Ahsan, Keng Yinn Wong","doi":"10.1109/iscaie54458.2022.9794550","DOIUrl":"https://doi.org/10.1109/iscaie54458.2022.9794550","url":null,"abstract":"Using a Programmable Logic Controller (PLC), this paper proposes an implementation of a smart home system. The program of smart job scheduling is an energy-efficient home system. The machine is operated automatically, is energy-efficient, and creates a more relaxed and simpler environment for life. It also increases the safety of the house. In addition to this, the central control unit manages and controls several operations, including control of the main entrance and garage, control of electrical connections, and security control system using PLC and relays with a regulated schedule. The core software for PLC is built using a CX-Programmer. CX-Programmer is used to create a ladder diagram that capable of processing, sequencing, scheduling, and reading instructions. CX-Designer is used to provide Human Machine Interface (HMI). The activities can be performed exactly according to the schedule defined by user demand.","PeriodicalId":395670,"journal":{"name":"2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131114149","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}
I'zzul Labiqah Mohamad Azmi, M. Kassim, N. Sulaiman, Suhaili Beeran Kutty, M. Yusoff
{"title":"Interactive Remote Robot for Pediatric Patients","authors":"I'zzul Labiqah Mohamad Azmi, M. Kassim, N. Sulaiman, Suhaili Beeran Kutty, M. Yusoff","doi":"10.1109/iscaie54458.2022.9794499","DOIUrl":"https://doi.org/10.1109/iscaie54458.2022.9794499","url":null,"abstract":"Pediatric patients are defined based on the age of 21 years old or younger during the time of diagnosis or treatment. Patients that are traumatized by the unfortunate incident do not have a companion in the ward once admitted. Medical procedures may become invasive that could cause distress for the patients causing them to develop stress and anxiety before the upcoming procedure. The research has developed and tested an interactive robot to assist pediatric patients to undergo medical procedures. Speech recognition and body gestures was built in the robot to interact with the patients. The humanoid robot is programmed to maintain receiving responses from samples of pediatric patients with Artificial Intelligence (AI) which acted as social skills such as giving feedback and giving mutual gaze while communicating. An Arduino microcontroller was built into the robot to control the movements of the robot via a Bluetooth module. DC motors are used for robot movements that are connected to motor drivers due to the extra power supply required to operate. AI was created for communication skills with patients. The result presents an analysis of the communication performance of the robot and AI. The robot movement was presented, and AI answers communication was listed. Research has presented its significance in that the robot helps and assisted patients to entertain and interact with pediatric patients during hospital stay which motivates and cheer them.","PeriodicalId":395670,"journal":{"name":"2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130481206","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}
K. K. Mohd Shariff, A. Ali, S. A. Enche Ab Rahim, Zuhani Khan Ismail
{"title":"Wet Road Detection Using CNN With Transfer Learning","authors":"K. K. Mohd Shariff, A. Ali, S. A. Enche Ab Rahim, Zuhani Khan Ismail","doi":"10.1109/iscaie54458.2022.9794528","DOIUrl":"https://doi.org/10.1109/iscaie54458.2022.9794528","url":null,"abstract":"There is an increasing need to detect wet road surfaces automatically considering many accidents and traffic problems that occur in wet weather. Road condition detection based on acoustic signals has gained more attention in recent years due to its low implementation cost. However, current deep learning methods for wet surface detection rely on supervised audio measurements. Furthermore, they require a large amount of training data. Recent advancements in convolutional neural networks (CNNs) have made it possible for transferring trained CNN from one dataset to another. In this study, we aim to evaluate the capabilities of pre-trained CNN models to detect wet road surfaces. Results show that transfer learning was able to discriminate between dry and wet road surfaces with an accuracy of more than 80%. Additionally, we also provide performance comparisons for the three trained models.","PeriodicalId":395670,"journal":{"name":"2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127039022","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}
Fadhilah Aman, Thunesver Puvanen Thiran, Khairul Huda Yusof, N. M. Sapari
{"title":"IoT Gas Leakage Detection, Alert, and Gas Concentration Reduction System","authors":"Fadhilah Aman, Thunesver Puvanen Thiran, Khairul Huda Yusof, N. M. Sapari","doi":"10.1109/iscaie54458.2022.9794559","DOIUrl":"https://doi.org/10.1109/iscaie54458.2022.9794559","url":null,"abstract":"LPG is a common industrial and household item, which is extremely flammable. Many accidents have occurred because of LPG leaking, whose causes range from improper installation to the usage of faulty gas cylinders. Serious accidents that cause bodily harms or even fatalities can be avoided if the leakage is detected early before it initiates huge fires and causes damage to the surrounding where the LPG container is installed. This study proposes and develops an improved design of a system which detects LPG leakage, such as methane, butane, or any other petroleum-based gaseous liquid. Combining the gas leakage detection system with an IoT system shall provide mechanism to instantly contain the severity of LPG leakage and send instant alerts. In this system, an MQ-6 sensor and NodeMCU with ESP8266 WIFI module are used to detect gas presence, in which a relay will turn on to activate an exhaust fan to instantly reduce gas concentration whilst sending alert notification to user via an app. The information will then be transmitted over the internet to a database, in which the information will be accessible via an app configured specifically for the accessibility by the user.","PeriodicalId":395670,"journal":{"name":"2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126467196","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":"Investigation on Battery Supercapacitor Hybrid Energy Storage Performance based on Frequency Separation Strategy for Electric Vehicle Drive System","authors":"Z. Rasin, Nur Afiqah Md Raif, Lochana Palraju","doi":"10.1109/iscaie54458.2022.9794539","DOIUrl":"https://doi.org/10.1109/iscaie54458.2022.9794539","url":null,"abstract":"Currently, applying hybrid energy storage for electric vehicle is inevitable as there is no single energy storage device can satisfactorily fulfill its operational power demand. High energy density of the battery, combined with the high power density of supercapacitor contributes towards not only a longer travel distance but also a good drive response during transient operation e.g. acceleration or regenerative braking. The frequency separation based energy management is among the strategy available to realize energy division between the two energy storage device. This work focuses to investigate how the strategy affects the state of charge performance of the battery under various condition of driving cycles. The design, configuration and simulation of the electrical drive system is carried out with Matlab/Simulation software. The investigation results indicate that the battery current stress is significantly reduced by using the frequency separation strategy, but it does not significantly help to improve the state of charge performance of the battery over the period of the driving cycle.","PeriodicalId":395670,"journal":{"name":"2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132909767","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}
M. H. Alkawaz, Stephanie Joanne Steven, Omar Farook Mohammad, Md Gapar Md Johar
{"title":"Identification and Analysis of Phishing Website based on Machine Learning Methods","authors":"M. H. Alkawaz, Stephanie Joanne Steven, Omar Farook Mohammad, Md Gapar Md Johar","doi":"10.1109/iscaie54458.2022.9794467","DOIUrl":"https://doi.org/10.1109/iscaie54458.2022.9794467","url":null,"abstract":"People are increasingly sharing their details online as internet usage grows. Therefore, fraudsters have access to a massive amount of information and financial activities. The attackers create web pages that seem like reputable sites and transmit the malevolent content to victims to get them to provide subtle information. Prevailing phishing security measures are inadequate for detecting new phishing assaults. To accomplish this aim, objective to meet for this research is to analyses and compare phishing website and legitimate by analyzing the data collected from open-source platforms through a survey. Another objective for this research is to propose a method to detect fake sites using Decision Tree and Random Forest approaches. Microsoft Form has been utilized to carry out the survey with 30 participants. Majority of the participants have poor awareness and phishing attack and does not obverse the features of interface before accessing the search browser. With the data collection, this survey supports the purpose of identifying the best phishing website detection where Decision Tree and Random Forest were trained and tested. In achieving high number of feature importance detection and accuracy rate, the result demonstrates that Random Forest has the best performance in phishing website detection compared to Decision Tree.","PeriodicalId":395670,"journal":{"name":"2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"331 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133843106","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":"Procedure Enhancement for PDF Output Workflow Conformity","authors":"M. Y. Masod, Aezzaddin Aisyah Zainuddin","doi":"10.1109/iscaie54458.2022.9794464","DOIUrl":"https://doi.org/10.1109/iscaie54458.2022.9794464","url":null,"abstract":"Applications and parameters of Raster Image Processor enable a significant influence on the final print output in a sophisticated digital prepress system. Concerns regarding the PDF workflow systems’ compatibility with PDF/X continue to exist. The capability and reliability of RIPs in conforming to PDF/X-4 specifications in digital prepress workflow systems are questionable. The majority of output workflow systems were installed with outdated settings of PDF/X-4 standard (ISO 15930-9:2010). The goal of this research is to provide a test procedure for assessing the conformity of PDF output workflow by proposing the application of the Ghent Workgroup’s Output Suite 5.0. (GOS5).","PeriodicalId":395670,"journal":{"name":"2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128121788","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}