International journal of computers in healthcare最新文献_第4页

Image Compression Approach using Segmentation and Total Variation Regularization 基于分割和总变差正则化的图像压缩方法

International journal of computers in healthcare Pub Date : 2021-04-28 DOI: 10.46300/9108.2021.15.6

Ahmad Shahin, W. Moudani, Fadi Chakik

{"title":"Image Compression Approach using Segmentation and Total Variation Regularization","authors":"Ahmad Shahin, W. Moudani, Fadi Chakik","doi":"10.46300/9108.2021.15.6","DOIUrl":"https://doi.org/10.46300/9108.2021.15.6","url":null,"abstract":"In this paper we present a hybrid model for image compression based on segmentation and total variation regularization. The main motivation behind our approach is to offer decode image with immediate access to objects/features of interest. We are targeting high quality decoded image in order to be useful on smart devices, for analysis purpose, as well as for multimedia content-based description standards. The image is approximated as a set of uniform regions: The technique will assign well-defined members to homogenous regions in order to achieve image segmentation. The Adaptive fuzzy c-means (AFcM) is a guide to cluster image data. A second stage coding is applied using entropy coding to remove the whole image entropy redundancy. In the decompression phase, the reverse process is applied in which the decoded image suffers from missing details due to the coarse segmentation. For this reason, we suggest the application of total variation (TV) regularization, such as the Rudin-Osher-Fatemi (ROF) model, to enhance the quality of the coded image. Our experimental results had shown that ROF may increase the PSNR and hence offer better quality for a set of benchmark grayscale images.","PeriodicalId":89779,"journal":{"name":"International journal of computers in healthcare","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88068067","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

Evaluating the Mesh-connected Multiprocessor Running a Parallel Algorithm Representing the Gravitational Interaction Between N Bodies 评估网格连接多处理器运行表示N个物体之间引力相互作用的并行算法

International journal of computers in healthcare Pub Date : 2021-03-22 DOI: 10.46300/9108.2021.15.5

Jamil S. Al-Azzeh

引用次数: 0

Micro-Doppler Signature Based Helicopter Identification and Classification Through Machine Learning 基于微多普勒特征的直升机识别与分类

International journal of computers in healthcare Pub Date : 2021-03-22 DOI: 10.46300/9108.2021.15.4

S. Iswariya, J. Valarmathi

{"title":"Micro-Doppler Signature Based Helicopter Identification and Classification Through Machine Learning","authors":"S. Iswariya, J. Valarmathi","doi":"10.46300/9108.2021.15.4","DOIUrl":"https://doi.org/10.46300/9108.2021.15.4","url":null,"abstract":"This paper focuses on identification of helicopter by exploiting the concept of micro-Doppler effect which is prominent in targets containing rotating, oscillating or vibrating parts in it. Radar received signal is analyzed by Short Time Fourier Transform (STFT) to extract the micro Doppler (mD) signature. From the mD signature, the helicopter parameters are estimated. In a multiple helicopters scenario, estimated parameters will be a mixure, pertaining to the multiple helicopters. These parameters are classified further using a machine learning algorithm, namely k-means clustering to classify the helicopters. Simulated results for the synthesized received signal shows the betted estimates of the helicopter parameter through mD signature. Dataset containing basic parameters like number of blades, blade length and rotational rates of the UN-1N helicopter (rotor with 2 blades), the SH-3H helicopter (rotor with 5 blades) and the CH-54B helicopter (rotor with 6 blades) are considered for the classification. Results show a good classification. When analysed with different SNR level in dataset, at lower SNR, observed some ovelapping in the classification.","PeriodicalId":89779,"journal":{"name":"International journal of computers in healthcare","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82605408","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

Design of Model Reference Controller of Variable Speed Wind Generators for Frequency Regulation Contribution 变速风力发电机调频贡献模型参考控制器设计

International journal of computers in healthcare Pub Date : 2021-03-22 DOI: 10.46300/9108.2021.15.3

E. Becirovic, J. Osmic, M. Kusljugic, N. Peric

引用次数: 0

Classifications of Breast Cancer Diagnosis using Machine Learning 使用机器学习的乳腺癌诊断分类

International journal of computers in healthcare Pub Date : 2020-12-24 DOI: 10.46300/9108.2020.14.13

H. Iqbal, A. B. Nassif, I. Shahin

{"title":"Classifications of Breast Cancer Diagnosis using Machine Learning","authors":"H. Iqbal, A. B. Nassif, I. Shahin","doi":"10.46300/9108.2020.14.13","DOIUrl":"https://doi.org/10.46300/9108.2020.14.13","url":null,"abstract":"Breast Cancer (BC) is amongst the most common and leading causes of deaths in women throughout the world. Recently, classification and data analysis tools are being widely used in the medical field for diagnosis, prognosis and decision making to help lower down the risks of people dying or suffering from diseases. Advanced machine learning methods have proven to give hope for patients as this has helped the doctors in early detection of diseases like Breast Cancer that can be fatal, in support with providing accurate outcomes. However, the results highly depend on the techniques used for feature selection and classification which will produce a strong machine learning model. In this paper, a performance comparison is conducted using four classifiers which are Multilayer Perceptron (MLP), Support Vector Machine (SVM), K-Nearest Neighbors (KNN) and Random Forest on the Wisconsin Breast Cancer dataset to spot the most effective predictors. The main goal is to apply best machine learning classification methods to predict the Breast Cancer as benign or malignant using terms such as accuracy, f-measure, precision and recall. Experimental results show that Random forest is proven to achieve the highest accuracy of 99.26% on this dataset and features, while SVM and KNN show 97.78% and 97.04% accuracy respectively. MLP shows the least accuracy of 94.07%. All the experiments are conducted using RStudio as the data mining tool platform.","PeriodicalId":89779,"journal":{"name":"International journal of computers in healthcare","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78059434","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

PID Controller Gains Tuning Using Metaheuristic Optimization Methods: A survey 基于元启发式优化方法的PID控制器增益整定综述

International journal of computers in healthcare Pub Date : 2020-12-24 DOI: 10.46300/9108.2020.14.14

Abdallah Abushawish, Mohammed Hamadeh, A. B. Nassif

引用次数: 12

Approach for a Safe-SoC for Cyber-physical Application according to IEC 61508 符合IEC 61508的网络物理应用的安全soc方法

International journal of computers in healthcare Pub Date : 2020-12-22 DOI: 10.46300/9108.2020.14.12

J. Borcsok, M. Schwarz, Waldemar Muller, M. Abdelawwad

引用次数: 3

soc-approach for Safety-oriented Multi-channel Communication in Industrial Application of Human-robot-collaboration (HRC) 人机协作(HRC)工业应用中面向安全的多通道通信soc方法

International journal of computers in healthcare Pub Date : 2020-12-22 DOI: 10.46300/9108.2020.14.10

M. Abdelawwad, M. Schwarz, Malte Drabesch, J. Borcsok

引用次数: 0

Reliability Monitoring of Laser Scanner Based Navigation 基于导航的激光扫描器可靠性监测

International journal of computers in healthcare Pub Date : 2020-12-22 DOI: 10.46300/9108.2020.14.11

R. Thum, J. Borcsok

引用次数: 1

Cognitive Inductive Prejudice For Corporal Edifice In Hominids And Contraption 原始人身体结构与装置的认知归纳偏见

International journal of computers in healthcare Pub Date : 2020-12-18 DOI: 10.46300/9108.2020.14.8

Chandra Bhim Bhan Singh

{"title":"Cognitive Inductive Prejudice For Corporal Edifice In Hominids And Contraption","authors":"Chandra Bhim Bhan Singh","doi":"10.46300/9108.2020.14.8","DOIUrl":"https://doi.org/10.46300/9108.2020.14.8","url":null,"abstract":"A strong and insightful interpretation of scientific knowledge and practice must take into consideration how human cognitive skills and constraints enable as well restrict the scientific enterprise's activities and products. While existing deep learning systems are outstanding in functions such as object classification, language processing, and gameplay but few can create or transform a complex system like a Frame Pyramid. Assume that what these systems lack is a \"Cognitive Inductive Prejudice\": an ability to justify inter-object relationships and make decisions about an organized description of the incident. In order to assess this premise, this paper concentrated on a work involving stapling together stacks of frames to balance a castle and quantify how well hominids are doing. Then for analyzing contraption capability, our work introduce the Significant Stimulus Learning Tool that utilizes object-and interactioncentered scene and policy representations, these apply to the task. Our results shows that these structural portrayals enable the tool to perform both hominids and contraption for more naive methods, indicating that cognitive inductive effect is a significant element in solving structured reasoning issues and building more intelligent also flexible for machines.","PeriodicalId":89779,"journal":{"name":"International journal of computers in healthcare","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76519559","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