{"title":"MFCC Feature Selection for Infant Cry Classification","authors":"Natlada Meephiw, P. Leesutthipornchai","doi":"10.1109/ICSEC56337.2022.10049328","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049328","url":null,"abstract":"The infant calls for attention by crying. The crying comes from many reasons (e.g., attention, hunger, need to change wet diapers). The infant crying sounds seem too similar and difficult to classify by humans. This paper applies Mel Frequency Cepstral Coefficients (MFCC) for the feature extraction process. Various number of MFCC-feature are investigated and compared to obtain a suitable factor for classification techniques. Simple and well-known classification techniques (decision tree, naive Bayes, and support vector machine) are selected to classify the infant cry sounds. The support vector machine has highest performance metrics in both term of accuracy and F1score that are 70% and 71% respectively. Those are obtained from 11 features of MFCC. From the experimental results, MFCC:11 is suitable for infant crying sounds.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114322563","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":"Utilizing the Internet of Things technology to control oyster mushrooms","authors":"Pipop Maneejamnong, Natawut Payakkhin, Sancha Panpaeng","doi":"10.1109/ICSEC56337.2022.10049316","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049316","url":null,"abstract":"The objectives of this research were 1) Examine Internet of Things technologies for water spray and ventilation fan control in mushroom farms. 2) Develop tools and systems that enable users to monitor temperature, record it, and manage the amount of humidity in the House by adjusting humidity levels. These studies have selected NodeMCU ESP8266 and Arduino MEGA, AM2315, and KC-TH-280 modules for measuring digital temperature and humidity capture for load management of different electrical appliances. They utilized the application to switch on and off air humidity, drip irrigation, and water spraying automatically or manually to capture data acquired from a cloud system and demonstrate value to the Blynk System through mobile phones 3 meters wide, 6 meters long, and 3 meters high House. The investigation revealed that the sensor device readings measured and analyzed for on-off accuracy while the application was running were correct. There are 50 consecutive operations involving human control and automation. Through the application, the user controls the on/off state of the water pump and the operation of the ventilation fan. The water pump is active around 94% or 47 times. The quantity of pumps is disabled. The ventilation fan was turned off 49 times, or 98%, and the fan was turned off 48 times, or 96%, while testing the equipment’s functionality with the humidity and temperature settings. The mushroom house was heated to 30-35 degrees Celsius and humidified to a relative humidity of 65-75 percent. This technique was an effective tool for managing mushroom farm equipment.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114796812","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}
Noranand Apichanapong, Nalina Phisanbut, P. Piamsa-nga
{"title":"Leaf identification using learning machines for seedling distribution in Thailand","authors":"Noranand Apichanapong, Nalina Phisanbut, P. Piamsa-nga","doi":"10.1109/ICSEC56337.2022.10049376","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049376","url":null,"abstract":"Despite being an essential natural resource, the forest cover in Thailand has been continuously declining as a result of population growth and industrial expansion. In an attempt to reverse the situation, the Thai government has drawn up a plan with an aim to increase the forest area to 40% of the country, and part of the promotion plans is free seedling distribution.However, although the seedlings can be visually classified, it requires solid botanical expertise. In this research, we propose to use machine learning to classify seedlings by leaf images. Eight traditional learning machines and four deep learning models are investigated. An image dataset of eight highly distributed seedlings’ leaves is built from seedlings provided by the Royal Forest Department of Thailand. The results show that SVM and DenseNet201 perform best for traditional and deep learning machines.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"177 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116895204","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 a Robust Fractional order TID Controller for Congestion Avoidance in TCP/AQM system","authors":"Layla H. Abood, I. Ali, B. K. Oleiwi","doi":"10.1109/ICSEC56337.2022.10049311","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049311","url":null,"abstract":"The most important problem that effect on data flow efficiency in network systems the congestion problem, to obtain a stable behavior in TCP/AQM systems, an active queue management (AQM) is adopted for solving congestion and guarantee regular path for communicate in these network. In this paper uses a Matlab program to simulate a robust Fractional Order Tilt Integral Derivative (FOTID) controller for controlling the AQM system, Snake Optimization Algorithm (SOA) is suggested to obtain the controller variables and uses the Integral Time Absolute Error (ITAE) function to adjust system response by eliminating system error. The transient analysis is utilized for the proposed controller and two classical types of controller (PI&PID) to see the superior performance of FOTID proposed controller and then applies robustness analysis to the proposed controller in two step the first step is varying the desired queue length to different values(200,300,400) packet and the second step is by varying the link capacity to ±20% from its original value; in the two test done the controller faces these variations efficiently and return the system response to a stable and robust desired value.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130617858","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}
S. Glomglome, Watanyou Damrongphokaphan, Kittisak Phormraksa, Korntawat Witchuvanit
{"title":"Industrial IoT Edge Computing Platform for Real-Time Monitoring","authors":"S. Glomglome, Watanyou Damrongphokaphan, Kittisak Phormraksa, Korntawat Witchuvanit","doi":"10.1109/ICSEC56337.2022.10049372","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049372","url":null,"abstract":"This research’s goal is to develop an industrial IoT edge computing platform for Industrial IoT 4.0 that are currently in the process of transitioning from legacy systems to adopting IoT system. Due to connecting and collecting data from each machine part is still a problem of transition from the old system, this is the origin of this research. The system consists of a Remote Terminal Unit (RTU) which collect data from machines with sensors and an Edge Computing Device used to collect data from RTUs via MQTT Protocol. The system also has an IoT platform that processes incoming data for storing in the database and displays on the Web Application in real time and in retrospect and can also alert to Line Notify according to the conditions predefined by the user. Based on the benchmark test, an edge computing device can concurrently handle RTU connections up to 800 connections.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130574078","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":"Rugby Goal Kick Prediction Using OpenPose Coordinates and LSTM","authors":"Mondheera Pituxcoosuvarn, Yohei Murakami","doi":"10.1109/ICSEC56337.2022.10049358","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049358","url":null,"abstract":"The goal kick is the most delicate play in rugby. To train athletes, giving accurate instructions is difficult because each player’s form is different. Furthermore, in Japan, rugby goal posts are only installed in a few areas, so athletes who do not have access to a goal post have limited possibilities to perform practical kicks, and goal kick practice is insufficient. As a result, we used Long Short-Term Memory (LSTM) to create a goal prediction model from goal-kick videos to provide the player with feedback. We also attempted to determine which parts of the body are crucial criteria for scoring. This paper addresses only goal kicks/conversion kicks and penalty goal kicks made from stationary locations, not kicks made while the ball was in play such as the drop-kick. According to the findings, the model built using domain expertise was just as precise as the model built using all joint data. This result proved that the right knee and ankle of the kicking leg, as well as the positions of the right eye and shoulder, are crucial elements in determining a successful kick.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134088971","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}
Rachet Thipards, Narongrit Yotanak, Metha Tasakorn, R. Sakulpong, Akkachai Phuphanin, S. Kaewarsa, Ura Khongklew, Aornpanita Jaratthanaworapat, Nithiroth Ponrsuwanacharoen
{"title":"Smart Street Lighting Control for Electrical Power on Saving by IoT","authors":"Rachet Thipards, Narongrit Yotanak, Metha Tasakorn, R. Sakulpong, Akkachai Phuphanin, S. Kaewarsa, Ura Khongklew, Aornpanita Jaratthanaworapat, Nithiroth Ponrsuwanacharoen","doi":"10.1109/ICSEC56337.2022.10049363","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049363","url":null,"abstract":"The purpose of the smart street light control for saving electricity via the Internet of Things (IoT) is the use of LED luminaires that are regulated through operating time via a motion sensor Passive Infrared Detector (PIR) controller and Smart lighting towers also include PM 2.5 sensors, IP cameras and a Wi-Fi system controlled by a microcontroller. The result of energy savings is 64%, pollution display (PM 2.5) is in the range of 17-20 mg/m3, and life safety is enhanced by surveillance through IP Camera, the IoT system. It can be as many benefits as smart homes, smart farms, smart offices and smart electricity by analyzing the deep learning and machine learning approaches of the future.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132975146","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":"Self-Regulated Learning Styles in Hybrid Learning Using Educational Data Mining Analysis","authors":"Pratya Nuankaew, Patchara Nasa-Ngium, W. Nuankaew","doi":"10.1109/ICSEC56337.2022.10049322","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049322","url":null,"abstract":"Online learning requires a learning style consistent with learners’ behavior and performance. Therefore, this research has the significant goal of studying learning behaviors which accurate online learning management, with three main objectives: 1) to investigate the context of students’ self-regulated learning styles in hybrid learning situations, 2) to study clusters of learners formed by self-regulated learning styles in hybrid learning situations, and 3) to evaluate the appropriate cluster from self-regulated learning styles in hybrid learning situations. The data collected were 44 students from the School of Information and Communication Technology, University of Phayao, who received a hybrid learning approach during the 2022 academic year. The research tool applied machine learning principles, used unsupervised learning techniques to cluster learners’ appropriate learning behaviors, and elbow assessment techniques were used to determine the number of clusters appropriately consistent with the self-regulated learning styles. The results showed that learners who used the online learning approach had lower learning achievements than those who used the onsite learning approach in the course 221101[5] Fundamental Information Technology in Business. In addition, the study found a significant difference in the learning achievement of the two groups of students. Therefore, this research is a tool for designing learner groups consistent with learners’ behavior and potential in science and technology issues based on the self-regulated learning styles in hybrid learning situations.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115224636","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":"The Optimized Proportion for Beef Cattle Feed using Sequential Least Squares Programming","authors":"Khomkris Mathiang, Kulwarun Warunsin, Phuwitson Phumsaranakhom","doi":"10.1109/ICSEC56337.2022.10049370","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049370","url":null,"abstract":"Producing premium beef cattle requires a good quality roughage and feed containing nutritional value appropriate to the age of the cattle. One strategy for producing high-quality beef cattle is smart nutrition management in the feed of fattening. Optimal feed ration for beef cattle is a challenging task under the multiple constrains. Therefore, this research aims to compare the efficiency of 4 optimal methods: SLSQP, COBYLA, Simplex, and Primal-Dual via the 10 beef cattle feed formulas. Using a database from the Bureau of Animal Nutrition Development, Department of Livestock Development, by comparing the accuracy and processing time. According to the experimental findings, all strategies produced answers that were equally accurate. However, the time required to process SLSQP is minimal, followed by the Simplex and Primal-Dual. Due to the iteration loop exceeding our limit, COBYLA is negligees.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121250658","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":"A Comparison of the Instructor-Trainee Dance Dataset Using Cosine similarity, Euclidean distance, and Angular difference","authors":"Thanawat Srikaewsiew, Khatadet Khianchainat, Atima Tharatipyakul, Suporn Pongnumkul, Sarunya Kanjanawattana","doi":"10.1109/ICSEC56337.2022.10049368","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049368","url":null,"abstract":"The COVID-19 outbreak has restricted most outdoor activities, leads to increasing interest in exercise at home with online trainers. One issue of online exercise technology is the safety since improper motion might result in injury. As a basis to prevent improper motion, methods for evaluating the motion similarity between an instructor and a trainee are essential. Cosine similarity, Angular difference, and Euclidean distance are three general ways for the motion evaluation. This study aimed to determine the most effective way for analyzing the similarity of human motion on the dataset of instructor-led dances. We first experimented with the data to find the appropriate cut-off value for classifying posture into two classes based on the similarity score. Confusion matrix, precision, recall, F1-score, accuracy of the results were then used to compare the efficiency. We discovered that Cosine similarity had the highest accuracy, 82.77 percent at cut-off 93.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130150860","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}