2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)最新文献

{"title":"Implementation of PRBS & RGS Perturbation Input Signals on Steam Temperature: Model Estimation and PID Control","authors":"Amzar Haziq Azman Nasir, N. Hambali, M. Rahiman","doi":"10.1109/CSPA57446.2023.10087748","DOIUrl":"https://doi.org/10.1109/CSPA57446.2023.10087748","url":null,"abstract":"Recent studies have conducted modelling using both linear and nonlinear approach to approximate the model of distillation column. This study presents the nonlinear modelling using Nonlinear Auto Regressive with Exogenous Input (NARX) model using Pseudorandom Binary Sequence (PRBS) and Random Gaussian Signal (RGS) perturbation input signals and PID control for distillation’s column temperature. System identification tools has been used for the NARX modelling estimation. The PID controllers with Ziegler Nichols (ZN) and Takahashi tuning methods were designed using MATLAB Simulink toolbox to regulate the steam temperature of Steam Distillation Pilot Plant (SDPP). The best model was evaluated based on high percentage of fitness and low value of mean square error (MSE) and final prediction error (FPE) while the selection of the best PID controller was determined based on the control performance such as rise time, settling time and percentage of overshoot. The RGS input signal with sixth number of orders was chosen as the best NARX model estimation because of highest percentage of best fit and lowest value of MSE and FPE from others model. Takahashi tuning method with PRBS input signal had delivered the best control performance with the fastest rise time of 880. 0209s, settling times of 5.1097x103 s and the lowest percentage of overshoot of 5.0134%. This controller was then chosen to undergo the fine-tuning method, which produced an excellent result with the elimination of system overshoot and a fast response time.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"176 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120888353","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":"Performance Analysis of Secure MQTT Communication Protocol","authors":"Muhammad Zulhamizan Ahmad, Alisa Rafiqah Adenan, M. S. Rohmad, Y. M. Yussoff","doi":"10.1109/CSPA57446.2023.10087603","DOIUrl":"https://doi.org/10.1109/CSPA57446.2023.10087603","url":null,"abstract":"Nowadays the growth of IoT is rapid and the MQTT protocol has become widely used in IoT communication. MQTT protocol does not come with strong security features except the username and password authentication. However, without TLS, the username and password are not good enough to secure communication. Therefore, the security and efficiency of MQTT protocol are the core basic issue. This paper discusses a method to secure the MQTT protocol via TLS and analysis of the performance. Using TLS in MQTT will encrypt the message transported from MQTT client to the server. The packet was analyzed using Wireshark, it showed that applying TLS into MQTT will encrypt the message in the network traffic. In a nutshell, security in MQTT protocol is important as MQTT has become a de facto standard for IoT.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"255 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121135607","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 Real-Time Monitoring of Air Quality Using IOT-Based Environment System","authors":"H. Hashim, Muhamad Hazwan, P. Saad, Z. Harun","doi":"10.1109/CSPA57446.2023.10087557","DOIUrl":"https://doi.org/10.1109/CSPA57446.2023.10087557","url":null,"abstract":"Air quality is important in human daily life. It is good if we can monitor and control our environment’s air quality in real time. Therefore, this project allows users to monitor the air quality in their desired environment from a smartphone using an IoT system. The aim of the project was to monitor the environment by measuring the humidity, temperature, and air of surroundings by using low-cost sensors such as humidity sensor (DHTII), temperature sensor (LM35), and gas sensor (MQ135) which have been analyzed and studied. The project used Arduino Uno R3 and a Wi-Fi module (ESP8266) to obtain input data from sensors and the output data were displayed on a smartphone. All sensors and Wi-Fi modules were connected to the Arduino Uno R3. The Wi-Fi module was used to transmit data to the Blynk cloud and can be accessed through a smartphone via the Blynk application. The end-users can monitor the results through their Blynk application. The application showed the desired data which are the temperature, humidity, and air quality. The experiment data was collected from two places which are the city and the suburb. The collected data was taken indoors and outdoors in the two places. The results show that the air quality in the city is above 300 PPM which can be considered as high especially outdoors. It can be concluded that there are many of pollution in the city that led to a high reading of air quality.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133367040","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":"Detection of White Stem Borer Disease in Coffee Plantation using Autonomous Multi Terrain Robot","authors":"Likhitha Sindhu Geddam, Ananya Mungara, Kiriti Kapavari, Karthikeya Jayarama, S. Tripathi","doi":"10.1109/CSPA57446.2023.10087558","DOIUrl":"https://doi.org/10.1109/CSPA57446.2023.10087558","url":null,"abstract":"A number of nations’ economies rely heavily on the production of coffee. The coffee plant has experienced significant damage as a result of a White Stem Borer (WSB) bug. The WSB bores into the coffee stem and stays buried there until the plant fully falls. As it is challenging to diagnose the disease in the early stages of its infestation, this disease greatly distresses coffee growers. In order to find a way to prevent the significant yield loss, we built on a dataset of WSB-infected stems, identified 3 distinct features to classify infected coffee stems and distinguish them from healthy stems, and then trained YoloV5 deep learning model. We developed a model using augmented images from the existing image data after dividing it into training and testing sets. mAP, precision, and recall of 81.9, 89.7 and 73.8 percentages respectively were obtained, which would increase substantially with larger data size. The proposed method of utilising the bark’s characteristics for early detection of stem borer disease has not been explored so far. The image processing pipeline implemented is accompanied by the simulation of Arabica Coffee plantationlike environments. The simulations focus on the Jackal UGV as it is an ideal robot for the use case of autonomous deployment in mapping and navigation of the plantations. Functionalities such as Elevation Mapping, State Estimation and Localisation have been incorporated in tandem so that data captured by use of a depth camera can be used efficiently for operation.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129305740","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":"Prediction of Ultraviolet Corrosion Levels of High Density Polyethylene Using Artificial Intelligence","authors":"Jeongwon Seo, Geumbi Park, Minju Kim, Jae-Hyeong Joo, Jinhwan Koh","doi":"10.1109/CSPA57446.2023.10087881","DOIUrl":"https://doi.org/10.1109/CSPA57446.2023.10087881","url":null,"abstract":"Currently, as the intensity of ultraviolet rays increases due to the severe global warming problem, it is difficult to make materials that exclude ultraviolet rays. As a result, high-density polyethylene (HDPE) is a non-toxic ecofriendly plastic with no environmental hormones detected and has been found to have excellent strength and less damage to ultraviolet rays, and interest in eco-friendly ship technology is increasing. This research predicted damage to high-density polyethylene by adding a carbon black sample, which is a UV stabilizer, to HDPE using a long-lasting UV-A lamp because it requires a lot of time due to the presence or absence of ultraviolet limitation. Since it takes a lot of time and money to check the corrosion of the material using ultraviolet rays, research was conducted using artificial intelligence to solve this problem, and as a result, it was confirmed that the degree of corrosion of HDPE according to the irradiation time can be predicted with 90% accuracy.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116139612","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":"Production and Capacity Planning as well as Inventory and Distribution Control in Snack Packaging Companies Using Open Source ERP Simulation","authors":"Vanessa Angelica Budiono, L. Gozali, I. W. Sukania","doi":"10.1109/CSPA57446.2023.10087652","DOIUrl":"https://doi.org/10.1109/CSPA57446.2023.10087652","url":null,"abstract":"PT. XYZ is a company that produces cardboard packaging. The product that is most in demand by customers is snack packaging. Snack packaging products have an erratic demand that affects the production process and ordering of raw materials. Therefore, companies need a more effective improvement proposal design starting from forecasting, inventory, distribution, production planning, and ERP simulation. The data needed to start the research are the raw materials used, data on demand for snack packaging products for the past 1 year, lead times for raw materials, machines used, and other data. Data processing begins with forecasting using the Double Moving Average, Single Moving Average, Weight Moving Average, Double Exponential Smoothing, Single Exponential Smoothing, Cyclic, Linear Regression, and decomposition methods followed by validation and verification of forecasting methods Mean Absolute Deviation, Mean Square Error, Mean Absolute Percent Error, and Standard Error of Estimate. Forecasting results that have been verified are followed by aggregate planning, Rough Cut Capacity Planning with Capacity Planning using Overall Factors, Bill of Labour Approach, Resource Profile Approach, safety stock methods, Material Requirement Planning with the Least Unit Cost, Lot for Lot, Silver Meal, Economic Order Quantity, Period Order Quantity, Capacity Requirement Planning, Distribution Requirement Planning, and Enterprise Resource Planning methods. The proper forecasting method used is the decomposition method which has the least error compared to PT. XYZ methods. The calculation of mixed aggregate planning (overtime and shifts) is the right method because it costs the least total cost, namely ${$}$ 34023.54. The results of Capacity Requirement Planning and Rough-Cut Capacity Planning calculations do not indicate a lack of capacity to meet the demand for the Master Production Schedule. The proper Material Requirement Planning method is the Period Order Quantity lotsizing method with a 47.6% savings compared to PT. XYZ. Proper distribution planning using the Distribution Requirement Planning method with a savings of 36.3% compared to PT. XYZ methods.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121813999","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":"Manufacturing Execution System of Bluetooth Speaker Pen Holder Assembly Line based on Genetic Algorithm","authors":"Yang Qiuping, Alexander A. Hernandez","doi":"10.1109/CSPA57446.2023.10087378","DOIUrl":"https://doi.org/10.1109/CSPA57446.2023.10087378","url":null,"abstract":"In view of the problems existing in the production line of a Bluetooth speaker pen holder in an enterprise, such as unreasonable planning organization, the low utilization efficiency of equipment resources, long production cycle, and so on, MES system is proposed to carry out information transformation on it. According to the actual needs of production, the functional module of MES was built to realize the comprehensive monitoring and management of ‘‘people, raw materials, equipment, and environment’’ involved in production. Meanwhile, for the most difficult production scheduling problem in MES system, the minimum completion time of orders was taken as the optimization goal, and the genetic algorithm was used to construct and optimize the production schedule. The scheduling effect is simulated by Matlab, the results show that compared with manual scheduling, the optimized scheduling algorithm proposed in this paper can reduce the scheduling time, shorten the production cycle, and increase the production efficiency by 10% or more, and the larger the order volume, the more obvious the advantages, which provides conditions for the mass production of Bluetooth speaker pen holder.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116642901","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":"LSTM-based Forecasting using Policy Stringency and Time-varying Parameters of the SIR Model for COVID-19","authors":"Pavodi Maniamfu, K. Kameyama","doi":"10.1109/CSPA57446.2023.10087773","DOIUrl":"https://doi.org/10.1109/CSPA57446.2023.10087773","url":null,"abstract":"Accurate forecasting of the number of infections is an important task that can allow health care decision makers to allocate medical resources efficiently during a pandemic. Two approaches have been combined, a stochastic model by Vega et al. for modelling infectious disease and Long Short-Term Memory using COVID-19 data and government’s policies. In the proposed model, LSTM functions as a nonlinear adaptive filter to modify the outputs of the SIR model for more accurate forecasts one to four weeks in the future. Our model outperforms most models among the CDC models using the United States data. We also applied the model on the Canadian data from two provinces, Saskatchewan and Ontario where it performs with a low mean absolute percentage error.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130164287","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":"Sensing the Presence of Benzotriazole Passivator in Thermally Aged Corrosive Transformer Insulating Oil Using UV-Vis Spectroscopy","authors":"Nur Izyan Husnina Zulkefli, M. S. A. Khiar, S. Ghani","doi":"10.1109/CSPA57446.2023.10087719","DOIUrl":"https://doi.org/10.1109/CSPA57446.2023.10087719","url":null,"abstract":"This paper introduces UV-vis spectroscopy as a potential technique for sensing benzotriazole passivator content in thermally aged transformer insulating oils. The progression of benzotriazole is tracked employing the changes in transmittance value at 500 nm wavelength, which is measured using UV-vis spectroscopy. The results show that the change of transmittance value at 500 nm wavelength is a function of the level of passivator compounds (i.e., in ppm).","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127485974","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":"CNN Model Compression by Merit-Based Distillation","authors":"Takumi Morikawa, K. Kameyama","doi":"10.1109/CSPA57446.2023.10087390","DOIUrl":"https://doi.org/10.1109/CSPA57446.2023.10087390","url":null,"abstract":"Deep learning has advanced dramatically in recent years, and especially large convolutional neural networks (CNNs) have shown outstanding performance in a wide variety of tasks. However, such large-scale CNNs may not be able to be utilized in practice because they require a lot of computational resources. Therefore, there is a need to realize a CNN in a small model that has high performance similar to the large CNN. One method to solve these problems is Distillation, which uses a model of large scale and high performance as the teacher and a small model as the student model, and performs model compression by transferring the knowledge of the teacher model to the student model. However, in distillation, even when the teacher model incorrectly guesses the training input, the student model learns to mimic the teacher. This can prevent the student model from learning better. In this paper, we propose Meritbased Distillation, in which the accuracy of the teacher model’s output determines the degree to which the student model mimics the teacher model’s output, thereby preventing the student to learn undesired mappings. In the experiment, the effect of the Merit-based Distillation is evaluated. Consequently, the proposed method outperforms the improvements in the generalization by the student models trained by other known methods.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131312569","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}