2020 23rd International Conference on Computer and Information Technology (ICCIT)最新文献

Modified Maximum Curvature Method (MMCM) and Logistic Regression: A Hybrid Architecture for Finger Vein Biometric Recognition System 修正最大曲率法与逻辑回归:一种手指静脉生物识别系统的混合架构

2020 23rd International Conference on Computer and Information Technology (ICCIT) Pub Date : 2020-12-19 DOI: 10.1109/ICCIT51783.2020.9392736

Faizah Binte Naquib, Sharika Tabassom, Fariha Elahee, Farhana Mim, Tonmoy Hossain, K. Kalpoma

{"title":"Modified Maximum Curvature Method (MMCM) and Logistic Regression: A Hybrid Architecture for Finger Vein Biometric Recognition System","authors":"Faizah Binte Naquib, Sharika Tabassom, Fariha Elahee, Farhana Mim, Tonmoy Hossain, K. Kalpoma","doi":"10.1109/ICCIT51783.2020.9392736","DOIUrl":"https://doi.org/10.1109/ICCIT51783.2020.9392736","url":null,"abstract":"The finger vein authentication system is a prominent field in biometric-based research that prevents identity theft by forgery or spoofing. However, as the finger images are affected by many environmental factors such as illumination or shifting during imaging, they are often noisy and have irregularity in thickness or brightness which can cause a decline in the verification accuracy. Therefore, a meticulous finger vein pattern extraction method along with an accurate classification is necessary. Though the Maximum Curvature Method (MCM) gives promising verification accuracy, it fails to tackle the stated limitations. For this purpose, we proposed a Modified Maximum Curvature Method (MMCM) for vein extraction. In this paper, a hybrid architecture for finger vein biometric recognition system is stated with the combination of proposed MMCM and Logistic Regression (LR) machine learning classifier. Proposed MMCM incorporates Finger Region Extraction, Image Enhancement using Contrast Limited Adaptive Histogram Equalization (CLAHE), and Affine transform Normalization. The authentication is then carried out by fusing the proposed feature extraction with a set of Machine Learning Classifiers and evaluated based on their Equal Error Rate (EER) on the public database SDUMLA-HMT. The combination of MMCM vein extraction and LR classifier gives a satisfactory low EER of 0.043.","PeriodicalId":196122,"journal":{"name":"2020 23rd International Conference on Computer and Information Technology (ICCIT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116777931","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

A Bangladeshi License Plate Detection System Based on Extracted Color Features 基于提取颜色特征的孟加拉车牌检测系统

2020 23rd International Conference on Computer and Information Technology (ICCIT) Pub Date : 2020-12-19 DOI: 10.1109/ICCIT51783.2020.9392672

Sheikh Nooruddin, Falguni Ahmed Sharna, S. M. M. Ahsan

引用次数: 0

Nearest Blood & Plasma Donor Finding: A Machine Learning Approach 最近的血液和血浆捐献者的发现:一种机器学习方法

2020 23rd International Conference on Computer and Information Technology (ICCIT) Pub Date : 2020-12-19 DOI: 10.1109/ICCIT51783.2020.9392739

Nayan Das, Md. Asif Iqbal

{"title":"Nearest Blood & Plasma Donor Finding: A Machine Learning Approach","authors":"Nayan Das, Md. Asif Iqbal","doi":"10.1109/ICCIT51783.2020.9392739","DOIUrl":"https://doi.org/10.1109/ICCIT51783.2020.9392739","url":null,"abstract":"The necessity of blood has become a significant concern in the present context all over the world. Due to a shortage of blood, people couldn’t save themselves or their friends and family members. A bag of blood can save a precious life. Statistics show that a tremendous amount of blood is needed yearly because of major operations, road accidents, blood disorders, including Anemia, Hemophilia, and acute viral infections like Dengue, etc. Approximately 85 million people require single or multiple blood transfusions for treatment. Voluntary blood donors per 1,000 population of some countries are quite promising, such as Switzerland (113/1,000), Japan (70/1,000), while others have an unsatisfying result like India has 4/1,000, and Bangladesh has 5/1000. Recently a life-threatening virus, COVID-19, spreading throughout the globe, which is more vulnerable for older people and those with pre-existing medical conditions. For them, plasma is needed to recover their illness. Our Purpose is to build a platform with clustering algorithms which will jointly help to provide the quickest solution to find blood or plasma donor. Closest blood or plasma donors of the same group in a particular area can be explored within less time and more efficiently.","PeriodicalId":196122,"journal":{"name":"2020 23rd International Conference on Computer and Information Technology (ICCIT)","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122412018","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

Bengali Image Captioning with Visual Attention 具有视觉注意力的孟加拉语图像字幕

2020 23rd International Conference on Computer and Information Technology (ICCIT) Pub Date : 2020-12-19 DOI: 10.1109/ICCIT51783.2020.9392709

Amit Saha Ami, Mayeesha Humaira, Md Abidur Rahman Khan Jim, Shimul Paul, F. Shah

引用次数: 5

Host trait prediction from human microbiome data for Colorectal Cancer 从人类微生物组数据预测结直肠癌宿主性状

2020 23rd International Conference on Computer and Information Technology (ICCIT) Pub Date : 2020-12-19 DOI: 10.1109/ICCIT51783.2020.9392731

Faisal Bin Ashraf, Md. Shafiur Raihan Shafi, Md Rayhan Kabir

{"title":"Host trait prediction from human microbiome data for Colorectal Cancer","authors":"Faisal Bin Ashraf, Md. Shafiur Raihan Shafi, Md Rayhan Kabir","doi":"10.1109/ICCIT51783.2020.9392731","DOIUrl":"https://doi.org/10.1109/ICCIT51783.2020.9392731","url":null,"abstract":"Microbiomes, micro organisms living in a host environment, play significant r ole i n t he r egular a ctivities and abnormalities of the host. Researches throughout the world has found symbiotic relations between the human microbiomes and human physiology, immunity, diseases etc. Outstanding development in sequencing technology has paved the way to analyze large number of samples with reasonable cost. Applying supervised machine learning techniques on these data can help to find out the most important m icrobiomes residing in the host environment and build a predictive model to classify unknown samples. In this study, we have applied different supervised classification a lgorithms a long w ith s ome e nsemble techniques to find a b etter p redictive m odel t o p redict t he t rait o f human host for the prognosis of colorectal cancer. Our study finds that, tree based classification a lgorithms w orks b est f or classifying the human microbiome data for colorectal cancer which are large, sparse and dispersed in nature. We have also identified important microbiomes that acts as a deciding factor behind colorectal cancer.","PeriodicalId":196122,"journal":{"name":"2020 23rd International Conference on Computer and Information Technology (ICCIT)","volume":"713 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123649778","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

In search of frequency-limited low-rank Gramian factors for the balancing based model reduction of large-scale sparse descriptor system 寻找基于平衡的大规模稀疏描述子系统模型约简的限频低秩格兰因子

2020 23rd International Conference on Computer and Information Technology (ICCIT) Pub Date : 2020-12-19 DOI: 10.1109/ICCIT51783.2020.9392667

K. I. B. Iqbal, M. Uddin, M. F. Uddin

引用次数: 2

Performance Evaluation of a Gate All Around Junctionless Field Effect Transistor Based Biosensor with a Nano-Cavity Region 基于纳米空腔区栅极无结场效应晶体管的生物传感器性能评价

2020 23rd International Conference on Computer and Information Technology (ICCIT) Pub Date : 2020-12-19 DOI: 10.1109/ICCIT51783.2020.9392677

M.A. Rahman, E. Hossain, Farha Y. Siddiqui

引用次数: 0

Accurate Prediction of Formylation PTM Site using Multiple Feature Fusion with LightGBM Resolving Data Imbalance Issue 基于LightGBM的多特征融合精确预测甲酰化PTM位点解决数据不平衡问题

2020 23rd International Conference on Computer and Information Technology (ICCIT) Pub Date : 2020-12-19 DOI: 10.1109/ICCIT51783.2020.9392678

S. M. Shovan, Md. Al Mehedi Hasan, M. Islam

{"title":"Accurate Prediction of Formylation PTM Site using Multiple Feature Fusion with LightGBM Resolving Data Imbalance Issue","authors":"S. M. Shovan, Md. Al Mehedi Hasan, M. Islam","doi":"10.1109/ICCIT51783.2020.9392678","DOIUrl":"https://doi.org/10.1109/ICCIT51783.2020.9392678","url":null,"abstract":"Formylation is a lysine post-translational modification that is recently discovered in histone. It has significance in DNA binding and responsible for the epigenetics of chromatin activities. Identifying lysine formylation sites accurately is very important for understanding the implicit characteristics and functions which may cause a diversity of living beings as well as result in severe diseases. Mass spectrometry is the manual laboratory technique that requires human labor which is time demanding as well as costly. So it’s urgent to develop computation based effective predictor which can effectively predict the formylation PTM sites accurately. In our model, a multiple feature fusion technique is used which combines sequence based CKSAAP, physicochemical property based AAIndex and mutation based evolutionary information. The imbalanced dataset is handled by generating synthetic data using SMOTE. LightGBM, a decision tree based gradient boosting classifier, is chosen for our model. Our model achieved accuracy, sensitivity, specificity and MCC of 94.81 ± 1.2%, 90.21 ± 2.8%, 99.41 ± 1.08% and 0.90 for cross-validation and 91.5%, 83.87%, 99.14% and 0.84 for independent test set performance respectively which surpassed the previously developed tool CKSAAP_FormSite to large margin.","PeriodicalId":196122,"journal":{"name":"2020 23rd International Conference on Computer and Information Technology (ICCIT)","volume":"290 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131679249","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

SkNet: A Convolutional Neural Networks Based Classification Approach for Skin Cancer Classes SkNet:基于卷积神经网络的皮肤癌分类方法

2020 23rd International Conference on Computer and Information Technology (ICCIT) Pub Date : 2020-12-19 DOI: 10.1109/ICCIT51783.2020.9392716

Afsana Ahsan Jeny, Abu Noman Md Sakib, M. Junayed, Khadija Akter Lima, Ikhtiar Ahmed, Md Baharul Islam

引用次数: 7

Heart Monitoring Management System Embedded with Internet of Things (IoT) Cloud Processing 嵌入物联网云处理的心脏监测管理系统

2020 23rd International Conference on Computer and Information Technology (ICCIT) Pub Date : 2020-12-19 DOI: 10.1109/ICCIT51783.2020.9392673

M. Hasan, Md.Fahad Hasan, I. Rahaman, Rafiqul Alam, Mehedi Hassan, Mim Naz Rahman

{"title":"Heart Monitoring Management System Embedded with Internet of Things (IoT) Cloud Processing","authors":"M. Hasan, Md.Fahad Hasan, I. Rahaman, Rafiqul Alam, Mehedi Hassan, Mim Naz Rahman","doi":"10.1109/ICCIT51783.2020.9392673","DOIUrl":"https://doi.org/10.1109/ICCIT51783.2020.9392673","url":null,"abstract":"Amongst all technologies, IoT has turned out to be a standout amongst the most inclining subjects at this moment. At present, along with various technologies, IoT has gained popularity for its versatile use. The efficiency of modern technology is measured by its usefulness in every aspect of mankind. Different technologies are helping humanity immensely whereas IoT has turned out to be a standout amongst the most inclining subjects at this moment. IoT is making a revolutionary change to the world as well as improving the health care system continuously. In addition, in a quick and safe way, the E-based medical system is becoming much popular now for different aspects. Particularly, IoT is helping the modern medical system on the basis of real-time ensuring better technologies and community traits and the modern medical system. Apparently, the internet-based medical system seems expensive or costly, but this system can be designed by using cheap sensors, easy functional applications with security, and data accuracy. Moreover, people from the countryside can be easily get connected with the E-medical system and get proper caring under a reliable network. In this paper, some E-Based health care system is discussed which are being proposed with the help of IoT. The efficiency of the proposed prototype varies from 91.6%-98.8% comparing with the actual BPM measuring device. Error percentage also changes with finger size where Large finger (3”) shows 15.67%, Medium finger (2.5”) shows 4.31% Small finger (2.1”) shows 8.91% in this research work.","PeriodicalId":196122,"journal":{"name":"2020 23rd International Conference on Computer and Information Technology (ICCIT)","volume":"411 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114939173","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