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

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

A Text Independent Speech Emotion Recognition Based on Convolutional Neural Network 基于卷积神经网络的文本独立语音情感识别

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101666

Seme Sarker, Khadija Akter, Nursadul Mamun

{"title":"A Text Independent Speech Emotion Recognition Based on Convolutional Neural Network","authors":"Seme Sarker, Khadija Akter, Nursadul Mamun","doi":"10.1109/ECCE57851.2023.10101666","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101666","url":null,"abstract":"With the advancement of deep learning approaches, the performance of speech emotion recognition (SER) has shown significant improvements. However, system performance degrades substantially when number of emotional states increased. Therefore, this study proposes a text independent SER system that can classify eight emotional states. The proposed system uses joint Mel frequency cepstral coefficient (MFCC) and Log-Mel spectrogram (LMS) to represent the speech signals and a convolutional neural network (CNN) to classify these features in to different emotional states. Results show that the proposed system can achieve an average accuracy of 93%. Two widely used datasets RAVDSESS and TESS have been used in this work to test the model performance. Experimental results present that the proposed framework can achieve significant improvement using a joint feature of MFCC and LMS. Furthermore, the proposed network outperforms state-of-art networks in terms of classification accuracy. This network could be reliably applied to recognize emotion from speech in naturalistic environment.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"32 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":"133264505","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

Study on Accuracy Improvement of Mental Arithmetic Task Classification Using Different Classifiers with DWT Feature Extraction Method 基于DWT特征提取方法的不同分类器提高心算任务分类准确率的研究

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101596

Tanvir Ibn Touhid, Mahbub Anam, Mohammad Rafiqul Alam, Mahir Foysal, Shibly Shaiham

{"title":"Study on Accuracy Improvement of Mental Arithmetic Task Classification Using Different Classifiers with DWT Feature Extraction Method","authors":"Tanvir Ibn Touhid, Mahbub Anam, Mohammad Rafiqul Alam, Mahir Foysal, Shibly Shaiham","doi":"10.1109/ECCE57851.2023.10101596","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101596","url":null,"abstract":"Near-infrared spectroscopy (NIRS) is a recently developed technique that can reveal hemodynamic and metabolic changes during cortical activation. NIRS has been used during cognitive tasks to study hemodynamic responses such as the change of oxyhemoglobin concentration. In the field of Brain Computer Interfacing (BCI), the use of fNIRS is an efficient approach. In this paper, fNIRS data from mental arithmetic tasks were proposed to classify with the help of the Discrete Wavelet Transform (DWT) based feature extraction method along with different classifiers. Raw data was preprocessed at first and stored in different frames to analyze brain activity. Using both the approximate and detail coefficients of DWT for framed data, features were extracted and used to compare brain activity during the mental arithmetic tasks and rest conditions. Finally, efficiencies of oxyhemoglobin, deoxyhemoglobin, and total hemoglobin data were measured for different channel combinations, and a satisfactory level of 95.54 % accuracy was achieved with the GentleBoost algorithm for the HAAR wavelet.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"9 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":"117184732","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

An Optimal Technique for Computation-intensive Task Allocation at Virtual Machines 虚拟机上计算密集型任务分配的优化技术

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101526

Akil Uddin Chowdhury, Md. Sazzad Hossen, M. Zahed

引用次数: 0

KNNTree: A New Method to Ameliorate K-Nearest Neighbour Classification using Decision Tree KNNTree:一种改进k近邻分类的决策树方法

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101569

Niful Islam, Most. Fatema-Tuj-Jahra, Md. Tarek Hasan, D. Farid

{"title":"KNNTree: A New Method to Ameliorate K-Nearest Neighbour Classification using Decision Tree","authors":"Niful Islam, Most. Fatema-Tuj-Jahra, Md. Tarek Hasan, D. Farid","doi":"10.1109/ECCE57851.2023.10101569","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101569","url":null,"abstract":"Classification in supervised learning is one of the major issues in machine learning and data science. K-Nearest Neighbour (KNN) and Decision Tree (DT) are one of the most widely used classification techniques that are commonly applying for single model and ensemble processes. KNN is known as lazy learner as it doesn't build any decision line from the training data. DT, on the other hand, is a top-down recursive divide-and-conquer technique that used for both classification and regression problems. DT has several advantages e.g, is requires little prior knowledge and non-linear relationship of features don't affect the tree performance. In this paper, we have proposed a new learning algorithm named KNNTree which is a hybrid model of KNN and DT algorithms. The proposed model is basically a decision tree, but leaf nodes are replaced by the KNN classifier. We have tested the proposed method with KNN and DT algorithms on 10 benchmark datasets taken from UC Irvine Machine Learning Repository and found the proposed method outperforms both KNN and DT classifiers.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"40 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":"124484806","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

The Use of Plasmonic Metal Nanoparticles to Enhance The Opto-electronic Performance of Thin-Film/Ultrathin Film CdTe Solar Cells 等离子体金属纳米颗粒增强薄膜/超薄膜CdTe太阳能电池的光电性能

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101669

Asif Al Suny, R. B. Sultan, Samina Tohfa, A. J. Haque, M. Chowdhury

{"title":"The Use of Plasmonic Metal Nanoparticles to Enhance The Opto-electronic Performance of Thin-Film/Ultrathin Film CdTe Solar Cells","authors":"Asif Al Suny, R. B. Sultan, Samina Tohfa, A. J. Haque, M. Chowdhury","doi":"10.1109/ECCE57851.2023.10101669","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101669","url":null,"abstract":"Cadmium Telluride (CdTe) thin film solar cells (TFSCs) have recently become one of the most favorable candidates to replace the traditional amorphous Si TFSCs because of its high absorption coefficient, close to ideal band gap energy and low production cost. This computational study investigates ways to enhance the opto-electronic performance levels of CdTe TFSCs by coupling plasmonic silver nanoparticles on the CdTe absorbing substrate. The finite-difference time-domain (FDTD) numerical analysis technique has been used to analyze different performance parameters including short circuit current density (Jsc), open-circuit voltage (Voc), fill-factor, output power, efficiency and others. Furthermore, this study also compares the opto-electronic performance levels of “plasmonic” CdTe TFSCs with “plasmonic” amorphous Si TFSCs. Additionally, investigations of the robustness of “plasmonic” CdTe TFSCs due to temperature variation and the performance of ultrathin CdTe absorber layer (< 250 nm thickness) is also presented. The results of this study show 13.47% increase in efficiency can be achieved for CdTe TFSCs by the use of plasmonic metal nanoparticles. Additionally, the results also strongly suggest that “plasmonic” CdTe TFSC performance levels are relatively stable across large temperature variations and can be up to 21 times more efficient than “plasmonic” Si TFSC for ultra-thin absorber layers.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"138 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":"123226581","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: 2

A Joint Bandwidth Expansion and Speech Enhancement Approach Using Deep Neural Network 一种基于深度神经网络的带宽扩展和语音增强联合方法

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101546

Taieba Taher, Nursadul Mamun, Md.Azad Hossain

{"title":"A Joint Bandwidth Expansion and Speech Enhancement Approach Using Deep Neural Network","authors":"Taieba Taher, Nursadul Mamun, Md.Azad Hossain","doi":"10.1109/ECCE57851.2023.10101546","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101546","url":null,"abstract":"Recently, joint bandwidth expansion and speech enhancement has been a topic of interest in the field of speech processing. The main challenge in this task is to increase the bandwidth of speech signals while enhancing their quality, simultaneously. Deep neural networks (DNNs) have shown great promise in addressing this challenge, as they can learn complex relationships between the input and output signals. In this study, a joint bandwidth expansion and speech enhancement approach using DNNs have been proposed, which is designed to simultaneously increase the bandwidth of speech signals and reduce noise, while preserving speech quality and intelligibility. This approach leverages the capability of DNNs to simultaneously estimate the missing speech components and the noise profile in the degraded speech signal. The estimated speech components and the noise profile are then used to synthesize a full-band speech signal from a noisy signal with limited bandwidth with improved quality. The network employs three different phases such as oracle, imaged, and noisy phase along with the magnitude spectra to recover high band components. The joint approach demonstrates that the DNN-based bandwidth extension and speech enhancement can be effectively combined to produce high-quality speech signals, outperforms traditional speech enhancement methods, and offers promising solutions for various applications, including speech communication, speech recognition, and speech synthesis.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"33 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":"115282196","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: 2

Architecture and Design of a New Non-Quadrature Vector-Sum Microwave Phase Shifter at 10 GHz With Maximum Residual Phase Error of 1.80° 一种最大剩余相位误差为1.80°的10 GHz非正交矢量和微波移相器的结构与设计

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101495

Mamady Kebe, Shakeeb Abdullah, R. Amaya, M. Yagoub

{"title":"Architecture and Design of a New Non-Quadrature Vector-Sum Microwave Phase Shifter at 10 GHz With Maximum Residual Phase Error of 1.80°","authors":"Mamady Kebe, Shakeeb Abdullah, R. Amaya, M. Yagoub","doi":"10.1109/ECCE57851.2023.10101495","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101495","url":null,"abstract":"This paper presents the architecture, design, and simulation of a new vector-sum phase shifter for prospected use in applications that require low amplitude loss. The architecture is based on non-quadrature phase generation and synthesis. The phase generation is done by splitting the input signal into two equal-phase output vectors and delaying one signal vector to the other; while the phase synthesis is implemented by subjecting the vectors through path selection and variable amplification & attenuation before subtracting the different paths. A two-bit phase path selection was employed for achieving 360° of coarse & fine tuning. EM simulations of the phase shifter architecture was carried out using RT-Duroid 5880 specifications $(varepsilon_{r}=2.2,boldsymbol{tandelta=0.004)}$ at center frequency of 10 GHz. A maximum phase error of $mathbf{1.82^{circ}}$ was obtained for the entire interval of 360 degrees of phase shift. With less than $2^{mathrm{o}}$ of phase error, the proposed phase shifter architecture is feasible for millimeter-wave phase array beamforming applications; as it offers the possibility of lower power consumption with the use of lesser compartmental blocks (i.e. compared to a T-bridge phase shifter which uses a chain of multiple blocks that can lead to excessive losses of more than 30 dB).","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"122 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":"121586143","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