2020 International Conference on System, Computation, Automation and Networking (ICSCAN)最新文献_第4页

FAB Classification based Leukemia Identification and prediction using Machine Learning 基于FAB分类的白血病识别与机器学习预测

2020 International Conference on System, Computation, Automation and Networking (ICSCAN) Pub Date : 2020-07-03 DOI: 10.1109/ICSCAN49426.2020.9262388

K. Jha, P. Das, H. Dutta

{"title":"FAB Classification based Leukemia Identification and prediction using Machine Learning","authors":"K. Jha, P. Das, H. Dutta","doi":"10.1109/ICSCAN49426.2020.9262388","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262388","url":null,"abstract":"Background and Objective: Leukemia identification, detection, & classification has erupted an intriguing field in medical research. Several methodologies are convenient in theprevious work to detect five types WBCs (lymphocytes, eosinophils, monocytes, neutrophils, and basophils). Single cell Blood's smear images used for experiment. Propounded method is used for leukemia recognition, uncovering and distribution based on FAB classification. Methodology: This propounded task has developed French-American and British (FAB) classification-based detection module on blood smearimages (BSIs). Methods like pretreatment, segmentation, feature extraction, distribution are used in detection method. The Propounded algorithm-based propounded model is used for segmentation, which is combination of the segmented results of the Linde-Buzo-Gray (LBG) algorithm, Adaptive canny used for edge identification and Hysteresis and watershed algorithm used for thresholding. The shape, texture features, color of segmented image are picked by neural network and classification is performed by Support Vector Machine (SVM) and prediction by Naïve Bayes Classifier (NBC). Result: Dataset-master and Cellavison dataset is being used for the experimentation. The BSIs are considered for the Evaluation based on ROC curve analysis metrics like TPR, TNR and accuracy. Our propounded solution obtains superior classification performance in the given dataset. The suggested classifier enhanced the classification average accuracy to 99.06% and Mean Square Error (MSE) is 0.0407. Conclusion: The enhanced accuracy had achieved by enhancing performance and classification with comparison with some other methods.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"39 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89806965","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: 4

Optimized Convolutional Neural Network based Colour Image Fusion 基于优化卷积神经网络的彩色图像融合

2020 International Conference on System, Computation, Automation and Networking (ICSCAN) Pub Date : 2020-07-03 DOI: 10.1109/ICSCAN49426.2020.9262439

B. Lakshmipriya, N. Pavithra, D. Saraswathi

引用次数: 2

Lean Six Sigma solutions for quality improvement in healthcare sector: a systematic review 精益六西格玛解决方案在医疗保健部门的质量改进:一个系统的审查

2020 International Conference on System, Computation, Automation and Networking (ICSCAN) Pub Date : 2020-07-03 DOI: 10.1109/ICSCAN49426.2020.9262289

Akshay Prasad, Akshay Kurup, J. K, G. Abhisek, A. Samanta, G. Varaprasad

{"title":"Lean Six Sigma solutions for quality improvement in healthcare sector: a systematic review","authors":"Akshay Prasad, Akshay Kurup, J. K, G. Abhisek, A. Samanta, G. Varaprasad","doi":"10.1109/ICSCAN49426.2020.9262289","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262289","url":null,"abstract":"The level of service quality offered to the patients is drastically declining over the years. The main purpose of this paper is to show a systematic analysis of the literature review based on lean six sigma in the healthcare process. This review aims at to improve service quality by identifying problems faced in the healthcare process and providing reliable solutions. A descriptive review focusing on lean six sigma in the healthcare process, followed by bibliometric analysis aligned with consistent literature review. The literature review related to healthcare process identifies the problems faced in hospitals. Reliable solutions for the problems are identified from literature and summarized. Primary problems are identified through literature review, while the results might not be accurate due to lack of diversity of papers reviewed. Hospital management can utilize the literature classification and the notable references provided in this review for in-process quality improvement. The procedure adopted in this paper is an integrated bibliometric and systematic literature review. The main contribution of this paper includes providing reliable solutions for problems faced in the healthcare sector as derived from the review.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"33 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78546936","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

Deletion of Thick Clouds from Landsat images using Super Pixel Segmentation and Neighbour Embedding Techniques 利用超像素分割和邻域嵌入技术删除陆地卫星图像中的厚云

2020 International Conference on System, Computation, Automation and Networking (ICSCAN) Pub Date : 2020-07-03 DOI: 10.1109/ICSCAN49426.2020.9262355

R. Thendral, S. Revathi

引用次数: 0

Brain Tumor Detection Model from MR Images using Convolutional Neural Network 基于卷积神经网络的MR图像脑肿瘤检测模型

2020 International Conference on System, Computation, Automation and Networking (ICSCAN) Pub Date : 2020-07-03 DOI: 10.1109/ICSCAN49426.2020.9262373

C. Someswararao, Shiva Shankar Reddy, S. V. Appaji, Vmnssvkr Gupta

引用次数: 9

Vehicle Recognition and Compilation in Database Software 数据库软件中的车辆识别与编译

2020 International Conference on System, Computation, Automation and Networking (ICSCAN) Pub Date : 2020-07-03 DOI: 10.1109/ICSCAN49426.2020.9262286

M. Madhumitha, P. Dhivya

引用次数: 0

Multi-Purpose Intelligent Drudgery Reducing Ecobot 多用途智能减少体力劳动的生态机器人

2020 International Conference on System, Computation, Automation and Networking (ICSCAN) Pub Date : 2020-07-03 DOI: 10.1109/ICSCAN49426.2020.9262372

R. Poovendran, B. A. Kumar, V. Bhuvaneshwari, R. Aswini, K. Priya

引用次数: 0

Beam Steering and Control Algorithm for 5-18GHz Transmit/Receive Module Based Active Planar Array 基于5-18GHz发射/接收模块有源平面阵列的波束转向与控制算法

2020 International Conference on System, Computation, Automation and Networking (ICSCAN) Pub Date : 2020-07-03 DOI: 10.1109/ICSCAN49426.2020.9262420

Maheeja Maddegalla, A. B. Bazil Raj, Gurugubelli Syamala Rao

{"title":"Beam Steering and Control Algorithm for 5-18GHz Transmit/Receive Module Based Active Planar Array","authors":"Maheeja Maddegalla, A. B. Bazil Raj, Gurugubelli Syamala Rao","doi":"10.1109/ICSCAN49426.2020.9262420","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262420","url":null,"abstract":"With the advent of Active Electronically Scanned Array (AESA) technology in the design and development of advanced multi-target handling Radar and Electronic Warfare (EW) systems, a new EW system with a Phased Array of a uniform spacing was developed, whose beam can be controlled using adaptive software programs. The critical EW system is recognized with miniaturized Planar Arrays using Transmit/Receive modules or T-R modules. The T-R modules use a novel core technology for the development of AESA technology. The planar arrays are miniaturized using multifunctional Monolithic Microwave Integrated Circuits (MMIC) with an inbuilt digital circuitry for beam steering, which requires high quality and different levels of programming using Field Programmable Gate Arrays (FPGA's). The AESA generally consists of thousands of T-R modules which can individually spread their signal emissions out across a band of the frequencies and sensitively receive the echoes from target objects, allowing it to broadcast transmitting signals while remaining stealthy and greatly increasing the detection and tracking abilities. Implementation of beam steering and control algorithms has to be designed in the frequency of 5–18 GHz for T-R module based planar arrays.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"46 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78201202","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: 17

Frequency Domain Modelling of Interrelation between Dielectric and Viscoelastic Properties of Soft Tissues 软组织介电特性与粘弹性特性相互关系的频域建模

2020 International Conference on System, Computation, Automation and Networking (ICSCAN) Pub Date : 2020-07-03 DOI: 10.1109/ICSCAN49426.2020.9262392

A. Bakiya, K. Kamalanand, S. Arunmozhi, V. Rajinikanth

引用次数: 0

An Interaction System Using Speech and Gesture Based on CNN 基于CNN的语音和手势交互系统

2020 International Conference on System, Computation, Automation and Networking (ICSCAN) Pub Date : 2020-07-03 DOI: 10.1109/ICSCAN49426.2020.9262343

S. Pariselvam, Dhanuja. N, D. S, S. B

{"title":"An Interaction System Using Speech and Gesture Based on CNN","authors":"S. Pariselvam, Dhanuja. N, D. S, S. B","doi":"10.1109/ICSCAN49426.2020.9262343","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262343","url":null,"abstract":"Nowadays, Hand gestures playing a important role for human interactions with the computer. Deep Learning is a part of machine learning methods which makes the recognition process easier by using Convolution Neural Networks (ConvNet/CNN). Convolution Neural Networks is a multilayer process network which includes Input layer, Convolution layer, Max pooling layer, Fully connected layer, Output layer. When compared to other algorithms, CNN can give more accurate results. CNN is mainly used to analyze visual images and for the image processing, segmentation and classification with higher accuracy. Here, this model consists of two main systems. One is voice input is converted into text and hand gestures and second approach is hand gestures conversion to text. These two systems are mainly used for abnormal people. These systems are implemented in Python and OpenCV is used to capture images. Each of these two systems has different modules. Human Computer Interaction are main source for the communication between humans and computer. So, these systems are helpful in communicating some information to humans. These systems are free from lighting conditions and background noise by using CNN algorithm.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"24 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87175696","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: 4