2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)最新文献_第5页

Investigation of the Impact of Sea Conditions on the Sea Surface Reflectivity in Maritime Radar Sea Clutter Modeling 海洋雷达海杂波模拟中海况对海面反射率影响的研究

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101598

Nirupam Das, Md. Selim Hossain

引用次数: 0

Blindness Risk Prediction caused by Diabetic Retinopathy from Retinal Image 从视网膜图像预测糖尿病视网膜病变致盲风险

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101653

Laboni Paul, K. H. Talukder

引用次数: 1

An Effective Framework for Identifying Pneumonia in Healthcare Using a Convolutional Neural Network 使用卷积神经网络识别医疗保健中的肺炎的有效框架

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101548

Md. Rabiul Hasan, Shah Muhammad Azmat Ullah, Md. Ebtidaul Karim

{"title":"An Effective Framework for Identifying Pneumonia in Healthcare Using a Convolutional Neural Network","authors":"Md. Rabiul Hasan, Shah Muhammad Azmat Ullah, Md. Ebtidaul Karim","doi":"10.1109/ECCE57851.2023.10101548","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101548","url":null,"abstract":"Pneumonia is now a life-threatening respiratory illness that can affect the lungs. Mainly the aged and children suffer the most. If the right diagnosis is not made, it could be fatal. So early diagnosis is very much needed to save many human lives. For diagnosis purposes Medical imaging, such as a chest x-ray can be utilized effectively and skilled radiologists are needed for this. Due to the blurriness of X-ray images, proper diagnosis can be difficult and time-consuming, even for radiographers with experience. As human judgment is involved, a pneumonia diagnosis may be erroneous. Hence, a deep learning-based automated system can be used to assist the radiographer in taking decisions more precisely and accurately. There have been several existing methods available for diagnosing pneumonia but they have accuracy issues. In this paper, we seek to automate the process of identifying and categorizing cases of pneumonia from CXR images deploying deep CNN. A deep CNN model has been built from scratch which will automate the process and provide high diagnosis performance. After passing through multiple convolutional layers and corresponding max pooling layers, the information is then fed into the dense layers. Lastly, using the sigmoidal function, the classification is performed. The model's performance improves as it simultaneously gains training and reduces loss.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131213372","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}

引用次数: 1

COMSOL-Based Modeling and Simulation of ISFET pH Sensor Using Si02 Sensing Film 基于comsol的Si02传感膜ISFET pH传感器建模与仿真

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101521

Salvir Hossain, Md Tawabur Rahman

{"title":"COMSOL-Based Modeling and Simulation of ISFET pH Sensor Using Si02 Sensing Film","authors":"Salvir Hossain, Md Tawabur Rahman","doi":"10.1109/ECCE57851.2023.10101521","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101521","url":null,"abstract":"The measurement of pH is an important routine practice in many chemical and biomedical applications. This work reports an Ion Sensitive Field Effect Transistors (ISFET) based pH sensor. The two-dimensional modeling of the sensor is performed in the COMSOL Multiphysics® v. 6.0 platform using its semiconductor module, electrostatics module, and transport of diluted species module. The binding of ions in Si02 results in induced charge carriers in the conducting channel of ISFET, which is controlled by the applied gate voltage for determining ion concentration. Here, the pH of water as the bulk electrolyte is measured by attaining the required gate voltage to achieve a certain drain current in ISFET. The sensor shows excellent sensitivities of 48.7 mV/pH and 41.3 mV/pH with linear detection ranges of pH 1–7 and 8–13, respectively. The excellent sensitivity and wide linear detection range can be attributed to the high concentration of surface sites in the Si02 sensing film and improved disassociation constants in the presence of the gate oxide in contact with the electrolyte. Finally, this sensor demonstrates its potential for real applications.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132133761","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}

引用次数: 0

IoT Based Smart Soil Fertilizer Monitoring And ML Based Crop Recommendation System 基于物联网的智能土壤肥料监测和基于机器学习的作物推荐系统

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10100744

M. Hossain, M. A. Kashem, Shabnom Mustary

{"title":"IoT Based Smart Soil Fertilizer Monitoring And ML Based Crop Recommendation System","authors":"M. Hossain, M. A. Kashem, Shabnom Mustary","doi":"10.1109/ECCE57851.2023.10100744","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10100744","url":null,"abstract":"Agricultural yield generally depends on the level of soil fertility. Nitrogen (N), Phosphorus (P), Potassium (K), pH, the temperature of the soil, and moisture as soil chemical constituents are fundamental parameters for determining soil fertility. Good yield can easily be ensured by measuring their presence and applying the right amount of fertilizer in the right season. Most farmers do not produce good crops due to insufficient knowledge and the inability to use the proper amount of fertilizers. Current methods of measuring soil nutrients involve collecting soil from the field and transporting it to a laboratory for testing, which is often subjective and very expensive. This paper suggests an efficient IoT-based soil nutrient monitoring and machine learning-based crop recommendation system that helps farmers by offering crop-related details and recommendations for crops based on different soil and weather attributes. The proposed system deploys various types of sensors to determine soil nutrients, these sensors continuously collect the required data from the farm field and transmit it via a wireless sensor network (WSN) to a cloud database. By monitoring (N, P, K, temperature, pH, humidity, rainfall) values and analyzing the permanent and temporary behavior of the soil, the machine learning approach will recommend what types of crops have the best production potential for this land. Agriculture's use of machine-learning technology makes it easier to select the best-yielding crops by reducing the cost of unnecessary fertilizer use, which reduces manual labor in crop and crop management and increases productivity. The most appropriate crops for that cropland are suggested using machine learning algorithms in IoT-based soil nutrient monitoring, which stores data from various soil nutrients in a database. As a result, agricultural production will contribute more to national growth.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129532560","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}

引用次数: 0

Cyclone Prediction Visualization Tools Using Machine Learning Models and Optical Flow 使用机器学习模型和光流的气旋预测可视化工具

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101589

Sabbir A. Rahman, N. Sharmin, Md. Mahbubur Rahman

{"title":"Cyclone Prediction Visualization Tools Using Machine Learning Models and Optical Flow","authors":"Sabbir A. Rahman, N. Sharmin, Md. Mahbubur Rahman","doi":"10.1109/ECCE57851.2023.10101589","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101589","url":null,"abstract":"A tropical cyclone is one of the most egregious natural disasters in the world that brings calamity to coastal lives by hitting the corresponding country's bordering basins since ancient time. The rapid intensification of TC has always been a threat to the coastal peoples living in different corners of the world. Geographical locations and geographical settings of being a low-lying deltaic country could trigger this calamitous event and bring individual hazards like a storm surge, inundation, oceanic flood, and many more. Tracking a tropical cyclone is not an easy task as it shows nonlinear behavior to different models to forecast. However, considering several limitations, experts from different countries use several products like satellite images, numerical data, and radar images to predict the formation, track, and the intensity of a cyclone. However, it is concerning that a full-fledged automatic cyclone prediction visualization tool for the wider populace does not exist. In this work, we are unlikely to provide an absolute automated visualization tool. Rather, we attempted to compensate for the lack of one by creating a prototype of a cyclone prediction and visualization dashboard with Streamlit, a Python framework for rapidly developing machine learning web apps. Furthermore, we considered visualizing the data sets in order to interpret them from various perspectives, and we used optical flow to determine the cyclonic behaviors as another approach.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":" 33","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113952017","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}

引用次数: 0

Sexual Harassment Detection using Machine Learning and Deep Learning Techniques for Bangla Text 使用机器学习和深度学习技术对孟加拉文本进行性骚扰检测

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101522

Mujahidul Islam, Maqsudur Rahman, M. T. Ahmed, Abu Zafor Muhammad Islam, Dipankar Das, M. M. Hoque

{"title":"Sexual Harassment Detection using Machine Learning and Deep Learning Techniques for Bangla Text","authors":"Mujahidul Islam, Maqsudur Rahman, M. T. Ahmed, Abu Zafor Muhammad Islam, Dipankar Das, M. M. Hoque","doi":"10.1109/ECCE57851.2023.10101522","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101522","url":null,"abstract":"Harassment is a kind of act that annoys or upsets someone. Harassment can be classified into different categories. Sexual harassment is one of them. Sexual harassment is a type of harassment that involves the use of implicit or explicit sexual overtones, including the inappropriate and unwelcome promises of rewards in exchange for sexual favors. At present time, the technology has become more advance and spread all over the place. That gave the toxic people a huge opportunity to spread toxicity in online platforms. Because of the increasing amount Bangla text in different social media platforms, we also need to filter such kinds of offensive Bangla texts. The objective of this research is to detect sexual harassment from Bangla text and classify them by using machine learning and deep learning algorithms as well as prevents them. In the experiment, we combined TF-IDF with different machine learning algorithms like Naive Bayes, Decision Tree, Random Forest, AdaBoost, SGD, Logistic Regression, KNN, SVM and got accuracy of 74.9%, 75.6%, 70.0%, 70.1%, 75.2%, 75.7%, 65.2%, 76.5% respectively. Deep learning algorithms like CNN, LSTM, hybrid CNN-LSTM were also used and achieved accuracy of 89% for all of them which is comparatively better than machine learning techniques.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116039701","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}

引用次数: 0

Pothole Detection and Estimation of Repair Cost in Bangladeshi Street: AI-based Multiple Case Analysis 孟加拉街道坑洼检测与修复成本估算:基于人工智能的多案例分析

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101579

Md. Safaiat Hossain, Rafiul Bari Angan, M. Hasan

引用次数: 1

An Improved Framework for Reliable Cardiovascular Disease Prediction Using Hybrid Ensemble Learning 基于混合集成学习的可靠心血管疾病预测改进框架

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101564

Tanjim Mahmud, Anik Barua, M. Begum, Eipshita Chakma, Sudhakar Das, Nahed Sharmen

{"title":"An Improved Framework for Reliable Cardiovascular Disease Prediction Using Hybrid Ensemble Learning","authors":"Tanjim Mahmud, Anik Barua, M. Begum, Eipshita Chakma, Sudhakar Das, Nahed Sharmen","doi":"10.1109/ECCE57851.2023.10101564","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101564","url":null,"abstract":"Cardiovascular diseases (CVDs), which include heart disorders, are the most prevalent and significant causes of death worldwide, including Bangladesh. Blood artery problems, rhythm issues, chest pain, heart attacks, strokes, and erratic blood pressure are a few of these. In Bangladesh, cardiovascular disease is the main factor in both male and female fatalities. More than 80% of CVD deaths are caused by heart disease and strokes, which are the predominant causes. To be able to examine the effectiveness of the various models, this research article explains the underlying methods as Support vector machines (SVM), K-Nearest Neighbors (KNN), Logistic Regression (LR), Random Forest (RF), Decision Tree (DT), and XGBoost (XGB), wherein Random Forest perform better when their hyperparameters are tuned (RandomizedSearchCV). There suggested ensemble technique such as Bagging, Voting, Stacking. Additionally, it is suggested that a hybrid strategy using Bagging and stacking ensemble approaches can boost the predictability of cardiovascular disease. For this analysis of patient performance, we used a dataset from Kaggle that comprises of 70,000 unique data values. According to the experiment's findings, the proposed model had the best disease prediction accuracy, coming in at 84.03%.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"206 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114650007","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}

引用次数: 5

Hardware/Software Co-design of an ECG- PPG Preprocessor: A Qualitative & Quantitative Analysis 一种ECG- PPG预处理器的软硬件协同设计:定性与定量分析

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101536

Aditta Chowdhury, Diba Das, R. Cheung, M. Chowdhury

{"title":"Hardware/Software Co-design of an ECG- PPG Preprocessor: A Qualitative & Quantitative Analysis","authors":"Aditta Chowdhury, Diba Das, R. Cheung, M. Chowdhury","doi":"10.1109/ECCE57851.2023.10101536","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101536","url":null,"abstract":"This paper aims to design a digital system to pre-process electrocardiogram (ECG) and photoplethysmogram (PPG) signal for the purpose of hardware implementation. Muscle signal, motion artifacts, power line interference affect the biomedical signal during data acquisition. The proposed system focuses at removing the noises by designing infinite impulse response filter to remove power line noise and finite impulse response filter to eliminate other high and low frequency noises. At first the preprocessor is designed in Matlab to validate the simulation performance. Then the hardware is designed in xilinx system generator targeting Zedboard Zynq xc7z020-1clg484. Finally, we verified the hardware software codesign by comparing both outputs. For quantity based analysis different filtering techniques have been applied to determine the most optimized system in terms of resource utilization and power consumption. Pearson correlation coefficient of 0.9993 and 0.9982 have been found for ECG and PPG, respectively using Hamming filter technique for High and low pass filter. Root squared error for both signal has been also in the range of 10−2• These data validate the accuracy of the designed system providing quality assurance. Frequency spectrum also has been analyzed to ensure denoising of undesired signals. The designed preprocessor can be utilized for further analysis of the signals and designing digital systems & wearable devices for the detection of heart rate, cardiac diseases etc.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131908907","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}

引用次数: 1