2019 International Conference on Electrical, Computer and Communication Engineering (ECCE)最新文献_第8页

Frequency Domain Approach in CSP based Feature Extraction for EEG Signal Classification 基于CSP特征提取的频域脑电信号分类方法

2019 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2019-02-01 DOI: 10.1109/ECACE.2019.8679463

P. Saha, Md. Asadur Rahman, M. N. Mollah

引用次数: 8

Performance Analysis of Frequency and Graph Theoretic Based Text Summarization 基于频率和图论的文本摘要性能分析

2019 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2019-02-01 DOI: 10.1109/ECACE.2019.8679452

Pradip Chandra Karmaker, M. Hossen

引用次数: 3

Design a Secure Voting System Using Smart Card and Iris Recognition 基于智能卡和虹膜识别技术的安全投票系统设计

2019 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2019-02-01 DOI: 10.1109/ECACE.2019.8679118

M. Mahiuddin

引用次数: 7

Identification of Drop Out Students Using Educational Data Mining 利用教育数据挖掘识别辍学学生

2019 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2019-02-01 DOI: 10.1109/ECACE.2019.8679385

N. Tasnim, Mahit Kumar Paul, A. S. Sattar

引用次数: 13

A Recommender System Based on Deep Neural Network and Matrix Factorization for Collaborative Filtering 基于深度神经网络和矩阵分解的协同过滤推荐系统

2019 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2019-02-01 DOI: 10.1109/ECACE.2019.8679125

Mohammad Tusher Ahamed, Shyla Afroge

引用次数: 11

Design and Optimization of an Efficient Molybdenum Disulfide (MoS2) Solar cell with Tin Sulfide BSF 含硫化锡BSF的高效二硫化钼太阳能电池的设计与优化

2019 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2019-02-01 DOI: 10.1109/ECACE.2019.8679178

Mrinmoy Dey, Md Fahim Shahriar, A. Ali, Maitry Dey, N. K. Das

{"title":"Design and Optimization of an Efficient Molybdenum Disulfide (MoS2) Solar cell with Tin Sulfide BSF","authors":"Mrinmoy Dey, Md Fahim Shahriar, A. Ali, Maitry Dey, N. K. Das","doi":"10.1109/ECACE.2019.8679178","DOIUrl":"https://doi.org/10.1109/ECACE.2019.8679178","url":null,"abstract":"Two-dimensional molybdenum disulfide (MOS<inf>2</inf>) is a potential sunlight harvester due to low cost, layered type atomic structure, favorable electrical and optical properties. The performance of a molybdenum disulfide (MOS<inf>2</inf>) photovoltaic cell is investigated by using the wxAMPS simulator. The hidden potentiality of Mos2is unfolded by using BSF strategy. The photoconversion efficiency is found 21.39% <tex>$(pmb{J_{sc}}=pmb{29.89} mathbf{mA}/mathbf{cm}^{pmb{2}},pmb{V_{oc}=0.841}mathbf{V}$</tex> and <tex>$mathbf{FF}=pmb{0.856}$</tex>) for <tex>$mathbf{r} pmb{1} pmb{mu} mathbf{m MoS}_{pmb{2}}$</tex> absorber layer with 100 nm SnS BSF whereas in conventional structure, it is found 19.48% <tex>$(pmb{V_{oc}=0.826}mathbf{V}, pmb{J_{sc}}=pmb{27.848} mathbf{mA}/mathbf{cm}^{pmb{2}}$</tex>, and <tex>$mathbf{FF}=pmb{0.846)}$</tex> without BSF for 1 <tex>$pmb{mu} mathbf{m MoS}_{pmb{2}}$</tex> absorber layer. The measured temperature coefficient (TC) is <tex>$pmb{-0.047%/}^{circ}mathbf{C}$</tex> for conventional photovoltaic cell structure and −0.046<sup>%</sup>/°C for a modified structure with SnS BSF. It indicates the better thermal stability of the modified structure compared to the conventional structure.","PeriodicalId":226060,"journal":{"name":"2019 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127404206","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: 3

An efficient model reduction strategy for discrete-time index-2 descriptor control systems 离散时间指标-2广义控制系统的有效模型约简策略

2019 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2019-02-01 DOI: 10.1109/ECACE.2019.8679509

S. Omar, Mohammad‐Sahadet Hossain, Ekram Khan, A. Tahsin

引用次数: 2

Metabolomic Biomarker Identification for Lung Cancer By Combining Multiple Statistical Approaches 结合多种统计方法鉴定肺癌的代谢组学生物标志物

2019 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2019-02-01 DOI: 10.1109/ECACE.2019.8679222

Tahsin Masrur, Md. Al Mehedi Hasan, Md. Nazrul Islam Mondal

{"title":"Metabolomic Biomarker Identification for Lung Cancer By Combining Multiple Statistical Approaches","authors":"Tahsin Masrur, Md. Al Mehedi Hasan, Md. Nazrul Islam Mondal","doi":"10.1109/ECACE.2019.8679222","DOIUrl":"https://doi.org/10.1109/ECACE.2019.8679222","url":null,"abstract":"Metabolomic biomarkers are tools that can be used in early disease prediction and drug designing for diseases like lung cancer. Knowing the most differentially expressed metabolites creates a much higher probability of diagnosing lung cancer faster than normal, which can reduce the mortality rate. They are crucial during drug design too. Previously, various works have been done on discovering biomarkers for different diseases. However, it is still nowhere near sufficient since reducing the number of biomarkers and maintaining good classification accuracy are urgent issues in a sector where people's lives are at stake. Thus, to contribute more, in this paper, we have identified the influential metabolites in plasma and serum blood sample for lung cancer and then selected biomarkers from them. We first considered a parametric test (Student‘s t-test) and two non-parametric tests (Kruskal-Wallis and Mann-Whitney-Wilcoxon test) to identify the influential metabolites. We also differentiated the up-regulated and down-regulated metabolites using FC values and heatmap plot. We used SVM classifier to ascertain good accuracy with our set of influential metabolites and ROC Curve Analysis to rank the metabolites and choose biomarkers. Our analysis resulted in 28 influential $(mathbf{p}-mathbf{value}<$ 0.05) metabolites from plasma sample and 13 influential (p-value $<pmb{ 0.05)}$ metabolites from serum sample. Finally, 10 metabolites were chosen from each of the samples as respective biomarkers. All the files and codes used in our work are available at https://github.com/Zeronfinity/LungCancerBiomarkers.","PeriodicalId":226060,"journal":{"name":"2019 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127779653","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

An Approach to Estimate the Activation of Different Bands of EEG Signal using Classified Songs 一种利用分类歌曲估计脑电信号不同波段激活的方法

2019 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2019-02-01 DOI: 10.1109/ECACE.2019.8679424

Chowdhury Azimul Haque, Monira Islam, A. Saad, Md. Salah Uddin Yusuf

{"title":"An Approach to Estimate the Activation of Different Bands of EEG Signal using Classified Songs","authors":"Chowdhury Azimul Haque, Monira Islam, A. Saad, Md. Salah Uddin Yusuf","doi":"10.1109/ECACE.2019.8679424","DOIUrl":"https://doi.org/10.1109/ECACE.2019.8679424","url":null,"abstract":"Human cognition analysis from EEG signal is one of the most significant way to find the causes which affect human brain. Songs are familiar stimuli to analyze the effectiveness of different EEG bands because it is a common source of entertainment. According to linguistic variation, subject age and preference, volume level of songs, the impact on different EEG bands varies. In this research, a work has been performed to estimate the effect of songs on different EEG bands (delta, theta, alpha, beta). The songs have been categorized into three types: mild, pop, rock according to their PSD value which are 0.2114 W/Hz, 0.3271 W/Hz and 0.8448 W/Hz respectively. the volume levels are considered as 0 %-14 % volume level for low volume, 26%- 60% volume level for comfortable volume and 61%-100% volume level for high volume. An ANOVA test has been conducted to indicate the significance variation in EEG band and in which P-value has been set 0.05. For the mild, pop, and rock songs the P-values for alpha bands are 0.0146, 0.006 and 0.0006 respectively and the values indicate that alpha band is mostly active while listening to different songs. A topographical representation has been done based on the effects of songs on the alpha band activity for mild, pop and rock songs at three volume level. The maximum percentage of alpha band activation is 60% in comfortable volume which indicates that, when the volume is high human cognition state moves from relax to stress condition in which beta band is active.","PeriodicalId":226060,"journal":{"name":"2019 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127291868","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

Boosting Neuro Evolutionary Techniques for Speech Recognition 促进语音识别的神经进化技术

2019 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2019-02-01 DOI: 10.1109/ECACE.2019.8679206

Mohshin Uddin Anwar, Md Liakot Ali

{"title":"Boosting Neuro Evolutionary Techniques for Speech Recognition","authors":"Mohshin Uddin Anwar, Md Liakot Ali","doi":"10.1109/ECACE.2019.8679206","DOIUrl":"https://doi.org/10.1109/ECACE.2019.8679206","url":null,"abstract":"For long many years, various speech signal processing techniques have been experimented and optimized using expectation maximization, gradient descent optimization or their variations across end-to-end speech feature extraction and recognition scheme, but the result was below the satisfactory limit despite multitude of time, cost and effort have been invested. Very recently, huge improvement of computing power of devices made it possible to use complex multi-layered neural network technologies (i.e. deep learning or deep neural network) such as convolutional net, long short term memory, bidirectional recurrent neural network as well as complex statistical or evolutionary strategies and its variations to optimize further the results to reduce the error rates. This paper emphasizes on how to devise an efficient technique that would reduce the time, cost and complexity over the deep learning methods with the guidance of genetic algorithm (GA) through intelligently choosing hyper-parameters of the networks. It has been identified that series of iterations to estimate, tune and re-estimate the hyper-parameters can lead to substantial improvement even with the least computing power, compared to one-go implementation of genetic algorithms done earlier.","PeriodicalId":226060,"journal":{"name":"2019 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125098284","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: 3