2023 15th International Conference on Computer and Automation Engineering (ICCAE)最新文献

{"title":"Artificial Intelligence Based Real-Time Skin Cancer Detection","authors":"T. Kumar, I. N. Himanshu","doi":"10.1109/ICCAE56788.2023.10111099","DOIUrl":"https://doi.org/10.1109/ICCAE56788.2023.10111099","url":null,"abstract":"Skin cancer emerge as the one of the most dangerous kinds of cancer occurred to human beings. Early detection of skin cancer is curable and necessary treatment can save the patient’s life. There are several types of skin cancer diseases with each having respective characteristics. The traditional way of detecting skin lesion include ABCDET technique which is widely used by the doctors. However manual detection of skin lesion fails in the current era with rapidly increasing skin cancer cases world-wide. Automatic detection of skin lesion is needed to perform the detection faster and minimize the diagnostic errors, lowering the overhead on the doctors. With the advent of different machine learning and deep learning techniques, an intelligent system can be developed to identify the skin lesions accurately. Neural networks are such a deep learning models used for the extraction and classification of skin lesion features. This paper presents a comparative analysis of skin lesion classification using CNN and Random Forest classifiers and real-time simulation of skin cancer detection. The dataset considered is HAM10000 dataset which provides a wide range of images of seven different types of skin lesions. Followed by image preprocessing for denoising and artifacts removal, image segmentation is done using Active Contours Without Edges (ACWE) and feature extraction is done using ABCDT technique where the textural analysis is implemented using Gray Level Co-Occurrence Matrix (GLCM) and Fractal Dimension texture analysis (FDTA). The accuracy with CNN classification is obtained to be 91.97% and that of Random Forest classification is 89.82%. The real-time simulation for skin cancer detection using trained models is performed and CNN model performed well than Random Forest classifier.","PeriodicalId":406112,"journal":{"name":"2023 15th International Conference on Computer and Automation Engineering (ICCAE)","volume":"32 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":"113971732","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":"ICCAE 2023 Cover Page","authors":"","doi":"10.1109/iccae56788.2023.10111386","DOIUrl":"https://doi.org/10.1109/iccae56788.2023.10111386","url":null,"abstract":"","PeriodicalId":406112,"journal":{"name":"2023 15th International Conference on Computer and Automation Engineering (ICCAE)","volume":"68 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":"122023462","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":"Model for Verifying the Reliability of Candidate Data Based on Blockchain Technology","authors":"Thu Nguyen, K. Vo, Thu-Thuy Ta, Tu-Anh Nguyen-Hoang, N. Dinh","doi":"10.1109/ICCAE56788.2023.10111120","DOIUrl":"https://doi.org/10.1109/ICCAE56788.2023.10111120","url":null,"abstract":"Big data is one of the most prominent technologies today and is applied in different areas of society. Big data is all information, collected from different sources and continuously updated over time. Therefore, big data has many challenges that make it difficult to apply in practice. One of the challenges that many researchers care about and find solutions to overcome is to ensure the reliability of the data. Meanwhile, blockchain technology emerges with a transparent, immutable, and secure data storage solution. Therefore, we focus on researching and developing a solution to verify the reliability of data based on blockchain technology. We analyze candidate data provided from multiple sources and find solutions to verify the reliability of this data to meet the urgent needs of employers looking for high quality human resources. Currently, on the internet, many systems provide an environment for information exchange between candidates and employers. However, it is difficult to verify the reliability of this information. Therefore, recruiters spend a lot of time checking the reliability of data provided by candidates. In this paper, we propose a model for verifying the reliability of candidate data based on blockchain technology (VRCD-BT). The system built according to this model can become an effective bridge between candidates and employers. Highly reliable candidate data creates many opportunities for candidates and employers to easily collaborate and grow. Thereby, contributing to the development of a sustainable economy operated by high-quality human resources.","PeriodicalId":406112,"journal":{"name":"2023 15th International Conference on Computer and Automation Engineering (ICCAE)","volume":"165 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":"127197961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An RFID-Assisted Smart Livestock and Poultry Farming System on the Cloud","authors":"Bin-hai Wu, Jiaqi Li, Qingsong Liu, K. Du","doi":"10.1109/ICCAE56788.2023.10111202","DOIUrl":"https://doi.org/10.1109/ICCAE56788.2023.10111202","url":null,"abstract":"Green and healthy food is being favored by consumers. In this paper, we design a radiofrequency identification (RFID)-based smart farming Internet of Things (IoT) system on the cloud, which provides an integrated automated information management platform for livestock and poultry farms. The system realizes the functions of video surveillance, environmental monitoring, management, environmental control and automatic feeding, manure treatment, disease diagnosis, and traceability. Utilization of this system ensures healthy animal farming and food safety, improves the quality and yield of animal farms, and thus bring considerable economic benefits to the farmers.","PeriodicalId":406112,"journal":{"name":"2023 15th International Conference on Computer and Automation Engineering (ICCAE)","volume":"9 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":"121311813","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":"Gender Classification for a Day-Old Gallus Gallus Domesticus Using Image Processing","authors":"M. A. Latina, Joseph Bryan G. Ibarra, Kean Nicole M. Sta. Ana, Allan Adrian C. Tinio, Mark Jay G. Berboso","doi":"10.1109/ICCAE56788.2023.10111111","DOIUrl":"https://doi.org/10.1109/ICCAE56788.2023.10111111","url":null,"abstract":"In the poultry business, pullets have the vital role in their species which make them valuable than cockerels. In order to sort them, hatcheries hire chick feather sexers. Nowadays, different countries are in need of chick sexers but the shortage in sexers are due to low income of farmers. In order to provide a solution to this shortage, the researchers have come up with a device that can classify a newly-hatched day-old chick’s gender based on its wing's feather pattern. The study used an image processing algorithm to determine the edges of the shaft and compare it with reference images. The study tested and evaluated the system using a sample group of day-old chicks and compared the result with a chick gender classifier and the chick’s actual gender when its physical characteristics started to show.","PeriodicalId":406112,"journal":{"name":"2023 15th International Conference on Computer and Automation Engineering (ICCAE)","volume":"93 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":"116193990","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 Black Sigatoka Disease on Banana Leaves Using ShuffleNet V2 CNN Architecture in Comparison to SVM and KNN Techniques","authors":"A. Yumang, Jonathan M. Baguisi, Baird Rouan S. Buenaventura, C. Paglinawan","doi":"10.1109/ICCAE56788.2023.10111367","DOIUrl":"https://doi.org/10.1109/ICCAE56788.2023.10111367","url":null,"abstract":"In this paper, the Shufflenet V2 Convolutional Neural Network Architecture is used to detect Black Sigatoka Disease in banana leaves. This architecture is used to compare its results in terms of accuracy, sensitivity, and specificity with different algorithms that also have been applied to the same scenario. Shufflenet V2 CNN is compared to the Support Vector Machine and K-nearest Neighbor in this case. Image classification has been a helpful tool. Its application detects anomalies and physical manifestations in different cases, such as agriculture and biomedical. Image classification uses different algorithms for its process, and each varies in performance. Thus, this study is made to see the percentage differences in this specific application. The CNN model is trained first by feeding it with data of healthy and Black Sigatoka infected banana leaf images in raw and augmented forms. The trained model is then deployed to a Raspberry Pi device prototype, wherein leaf samples are used as test data. The results of this test garnered 95% accuracy, 96.67% sensitivity, and 93.33% specificity. This ShuffleNet V2 CNN trained model's results are compared to the results of both algorithms, SVM and KNN.","PeriodicalId":406112,"journal":{"name":"2023 15th International Conference on Computer and Automation Engineering (ICCAE)","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":"130344635","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":"Distribution Line Inspection Using a Microcontroller Based Quad-Copter Drone with an Integrated Non-contact Voltage Detector and Infrared Thermal Temperature Sensor for Thermal Imaging","authors":"Andrew G. Bitancor, Alexander T. Montero, D. D. C. Maceda, Jan Miguel G. Rejano, Bon Jeremy R. Estrada, King Edward A. Sabacajan, Paul C. Valderama, Catherine S. Salvador","doi":"10.1109/ICCAE56788.2023.10111366","DOIUrl":"https://doi.org/10.1109/ICCAE56788.2023.10111366","url":null,"abstract":"Drones have recently been seen and employed in various fields. Their ability to be remotely controlled and fly at different distances and heights make them ideal candidates for some of the world's most difficult occupations. Electrical professionals' work is one of the vocations that could benefit from drone assistance, as they can utilize drones to investigate some hazardous electrical zones without putting themselves in danger. This drone gives much-needed safety in the field of electrical engineering. Drone technology is another step forward in enhancing linemen and other electrical workers' safety. This research aims to develop an unmanned aerial vehicle (drone) with electrical measuring instruments that will help electrical practitioners, particularly in the distribution sector, improve their efficiency and workflow. Furthermore, this research aims to increase lineworker safety in the field of electrical power distribution while performing tests and inspections on the distribution line. After a series of test flights and the actual testing of the equipment, the result showed that (1) the drone will be helpful and practical for the lineman when inspecting the distribution line because the data showed that the drone and its equipment are functioning with minimal discrepancy compared to a handheld instrument. (2) After applying a flyback converter and testing the equipment on a high voltage setting, the researchers concluded that the drone was safe enough to inspect or work near a high voltage system since there was no spark over during testing. (3) The researchers then concluded that the drone could effectively gather data while on flight and doing an inspection. There had been some problems regarding stability, but the design looks promising with some further enhancement.","PeriodicalId":406112,"journal":{"name":"2023 15th International Conference on Computer and Automation Engineering (ICCAE)","volume":"108 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":"122053516","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":"Infrared Temperature Detection Using MLX90614 Sensor for Wearable Applications","authors":"C. Paglinawan, Gaille Anne R. Bordonada, Aldous Vernon D. Roseus","doi":"10.1109/ICCAE56788.2023.10111139","DOIUrl":"https://doi.org/10.1109/ICCAE56788.2023.10111139","url":null,"abstract":"Body temperature is a significant vital sign that can provide great insight as to the state of health of a person. Nowadays, body temperatures are monitored as often as a precaution for the COVID-19 virus. This can be achieved with the use of wearables, which can be non-invasive and convenient for anybody to use. This study aims to design and construct a wearable that can accurately detect the body temperature of a person using the MLX90614 sensor as well as an I2C enabled LCD to allow the user to monitor their temperature at a moment’s notice.","PeriodicalId":406112,"journal":{"name":"2023 15th International Conference on Computer and Automation Engineering (ICCAE)","volume":"452 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":"122490018","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":"Smart Meter Modbus RS-485 Intrusion Detection by Federated Learning Approach","authors":"Md. Delwar Hossain, H. Ochiai, L. Khan, Y. Kadobayashi","doi":"10.1109/ICCAE56788.2023.10111132","DOIUrl":"https://doi.org/10.1109/ICCAE56788.2023.10111132","url":null,"abstract":"To accelerate digital transformation and assemble \"connecting the world,\" the IoT has been invented. To make and made more convenient in our daily life activities, billions of devices have been connected so far. Recently, we have noticed how they are helping cyber-physical systems (CPSs) to reach more elevated levels of evolution. Amidst diverse CPSs entities, the smart grid, Advanced Metering Infrastructure (AMI), is among the foremost essential entities since its rapid transformations. Wherein the Modbus RS-485 protocol is typically used in smart meters for physical layer communication. The key concern resides in fact that an attacker may easily compromise the smart meter systems since it lacks authentication and encryption mechanisms. As a countermeasure, an intrusion detection system (IDS), by applying a Federated Learning (FL) approach, could be an effective solution to detect the malicious activities of the RS-485 communication network, ensuring data protection from intruders. Since its built-in data protection mechanism and model could train without sharing sensitive private data. Henceforth, this research proposes a Federated Learning-based IDS for detecting critical attacks against the smart meter. We experiment with Modbus Attack DataSet for AMI (MAMI) datasets, and experiment results depict that the FL approach is reasonably effective in detecting critical smart meter attacks, moreover, protects the data privacy concern. The Multilayer Perceptron (MLP) classifier outperforms, which achieves a detection accuracy and detection rate of 99.98%, respectively.","PeriodicalId":406112,"journal":{"name":"2023 15th International Conference on Computer and Automation Engineering (ICCAE)","volume":"36 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":"114401694","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":"Variable Sampling Time Intelligent Control System For Driving the Hearth of an Industrial Furnace","authors":"Roxana-Maria Motorga, V. Muresan, M. Abrudean, I. Clitan, V. Sita, M. Ungureșan, Laurentiu Chifor","doi":"10.1109/ICCAE56788.2023.10111378","DOIUrl":"https://doi.org/10.1109/ICCAE56788.2023.10111378","url":null,"abstract":"In this paper a PID controller and an adaptive PID controller are designed and implemented in order to control the speed of the induction motors used to operate the rotary hearth furnace with constant load. The PID controller is further discretized and implemented with different values for the sampling time, leading to the online adaptation of the system which is ought to improve the obtained performances of the process. It is possible to implement the adaptive control strategy by means of artificial intelligence techniques which relay on the usage of neural networks – the neural networks are responsible with the generation of the coefficients of the PID controller, which are considered functions that depend on the sampling time. Even if the behavior of the induction motor is strongly nonlinear, the proposed control strategy can follow with high accuracy different setpoint speed values, fact proven through simulations.","PeriodicalId":406112,"journal":{"name":"2023 15th International Conference on Computer and Automation Engineering (ICCAE)","volume":"7 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":"126409518","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}