2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)最新文献_第2页

A Novel Method for Detecting Breast Cancer Location Based on Growing GA-FCM Approach 一种基于生长GA-FCM的乳腺癌定位检测新方法

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8964904

Milad Abaspoor, S. Meshgini, T. Y. Rezaii, A. Farzamnia

{"title":"A Novel Method for Detecting Breast Cancer Location Based on Growing GA-FCM Approach","authors":"Milad Abaspoor, S. Meshgini, T. Y. Rezaii, A. Farzamnia","doi":"10.1109/ICCKE48569.2019.8964904","DOIUrl":"https://doi.org/10.1109/ICCKE48569.2019.8964904","url":null,"abstract":"The main idea of this article is to provide a numerical diagnostic method for breast cancer diagnosis of the MRI images. To achieve this goal, we used the region’s growth method to identify the target area. In the area’s growth method, based on the similarity or homogeneity of the adjacent pixels, the image is subdivided into distinct areas according to the criteria used for homogeneity analysis to determine their belonging to the corresponding region. In this paper, we used manual methods and use of FCM as the function of genetic algorithm fitness. The presented algorithm is performed for 212 healthy and 110 patients. Results show that GA-FCM method have better performance than hand method to select initial points. The sensitivity of presented method is 0.67. The results of the comparison of the fuzzy fitness function in the genetic algorithm with other technique show that the proposed model is better suited to the Jaccard index with the highest Jaccard values and the lowest Jaccard distance. Among the techniques, the presented works well because of the similarity of techniques and the lowest Jaccard distance. Values close to 0.9 are close to 0.8.","PeriodicalId":6685,"journal":{"name":"2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"30 1","pages":"238-242"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81313424","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

Scheduling Mixed-criticality Systems on Reconfigurable Platforms 可重构平台上的混合临界系统调度

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8964800

Sadegh Sehhatbakhsh, Yasser Sedaghat

引用次数: 1

An LSTM Auto-Encoder for Single-Channel Speaker Attention System 用于单通道说话人注意系统的LSTM自编码器

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8965084

Mahnaz Rahmani, F. Razzazi

引用次数: 1

Efficiency Improvement of Differential Evolution Algorithm Using a Novel Mutation Method 利用一种新的变异方法提高差分进化算法的效率

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8964840

Milad Ghahramani, Abolfazl Laakdashti

{"title":"Efficiency Improvement of Differential Evolution Algorithm Using a Novel Mutation Method","authors":"Milad Ghahramani, Abolfazl Laakdashti","doi":"10.1109/ICCKE48569.2019.8964840","DOIUrl":"https://doi.org/10.1109/ICCKE48569.2019.8964840","url":null,"abstract":"The differential evolution algorithm is one of the fast, efficient, and strong population-based algorithms, which has extended applications in solving various problems. Although the velocity, power, and efficiency of this algorithm have been demonstrated in solving many optimization problems, this algorithm, like other metaheuristic algorithms, is not guaranteed to achieve the global optimal points of the optimization problems and may be ceased at optimal local points. One of the reasons for stopping the algorithm at the local optimum points is the imbalance between the exploration and exploitation abilities of the algorithm. One of the operators of the differential evolution algorithm, which plays an essential role in establishing the proper balance between the exploitation and exploitation of the algorithm, is the mutation operator. In this paper, a new mutation method is proposed to improve the efficiency of the differential evolution algorithm to make an appropriate balance between the exploitation and exploitation abilities of the algorithm. Comparing the results of the proposed mutation method with other mutation methods indicates that the proposed method has better speed and accuracy convergence rather than other methods, and it can be employed to solve large-scale optimization problems.","PeriodicalId":6685,"journal":{"name":"2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"97 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83596751","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

Boost PFC Converter Control using Fractional Order Fuzzy PI Controller Optimized via ICA 基于ICA优化的分数阶模糊PI控制器的升压PFC变换器控制

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8964893

Mohammad Ali Labbaf Khaniki, Amir Hossein Asnavandi, M. Manthouri

引用次数: 6

Persian Sentiment Lexicon Expansion Using Unsupervised Learning Methods 使用无监督学习方法扩展波斯语情感词典

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8964692

Reza Akhoundzade, Kourosh Hashemi Devin

引用次数: 7

Age Detection from Brain MRI Images Using the Deep Learning 基于深度学习的脑MRI图像年龄检测

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8964911

Masoumeh Siar, M. Teshnehlab

{"title":"Age Detection from Brain MRI Images Using the Deep Learning","authors":"Masoumeh Siar, M. Teshnehlab","doi":"10.1109/ICCKE48569.2019.8964911","DOIUrl":"https://doi.org/10.1109/ICCKE48569.2019.8964911","url":null,"abstract":"Estimating the age of the brains of individuals from brain images can be very useful in many applications. The brain’s age has greatly contributed to predicting and preventing early deaths in the medical community. It can also be very useful for diagnosing diseases, such as Alzheimer’s. According to the authors knowledge, this paper is one of the first researches that have been done in age detection by brain images using Deep Learning (DL). In this paper, the convolution neural network (CNN), used for age detection from brain magnetic resonance images (MRI). The images used in this paper are from the imaging centers and collected by the author of the paper. In this paper 1290 images have been collected, 941 images for train data and 349 images for test images. Images collected at the centers were labeled age. In this paper, the Alexnet model is used in CNN architecture. The used architecture of the architecture has 5 Convolutional layers and 3 Sub-sampling layers that the last layer has been used to categorize the image. The CNN that the last layer has been used to categorize the images into five age classes.The accuracy of the CNN is obtained by the Softmax classifier 79%, Support Vector Machine (SVM) classifier 75% and the Decision Tree (DT) classifier, 49%. In addition to the accuracy criterion, we use the benchmarks of Recall, Precision and F1-Score to evaluate network performance.","PeriodicalId":6685,"journal":{"name":"2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"34 1","pages":"369-374"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89204174","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

Brain Tumor Detection Using Deep Neural Network and Machine Learning Algorithm 基于深度神经网络和机器学习算法的脑肿瘤检测

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8964846

Masoumeh Siar, M. Teshnehlab

{"title":"Brain Tumor Detection Using Deep Neural Network and Machine Learning Algorithm","authors":"Masoumeh Siar, M. Teshnehlab","doi":"10.1109/ICCKE48569.2019.8964846","DOIUrl":"https://doi.org/10.1109/ICCKE48569.2019.8964846","url":null,"abstract":"Brain tumor can be classified into two types: benign and malignant. Timely and prompt disease detection and treatment plan leads to improved quality of life and increased life expectancy in these patients. One of the most practical and important methods is to use Deep Neural Network (DNN). In this paper, a Convolutional Neural Network (CNN) has been used to detect a tumor through brain Magnetic Resonance Imaging (MRI) images. Images were first applied to the CNN. The accuracy of Softmax Fully Connected layer used to classify images obtained 98.67%. Also, the accuracy of the CNN is obtained with the Radial Basis Function (RBF) classifier 97.34% and the Decision Tree (DT) classifier, is 94.24%. In addition to the accuracy criterion, we use the benchmarks of Sensitivity, Specificity and Precision evaluate network performance. According to the results obtained from the categorizers, the Softmax classifier has the best accuracy in the CNN according to the results obtained from network accuracy on the image testing. This is a new method based on the combination of feature extraction techniques with the CNN for tumor detection from brain images. The method proposed accuracy 99.12% on the test data. Due to the importance of the diagnosis given by the physician, the accuracy of the doctors help in diagnosing the tumor and treating the patient increased.","PeriodicalId":6685,"journal":{"name":"2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"1 1","pages":"363-368"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89761090","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: 87

Communication-Critical Task Duplication for Cloud Workflow Scheduling with Time and Budget Concerns 通信关键任务复制的云工作流程调度与时间和预算问题

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8965163

Mohammad Kamyar Arbab, Mahmoud Naghibzadeh, S. R. Kamel Tabbakh

{"title":"Communication-Critical Task Duplication for Cloud Workflow Scheduling with Time and Budget Concerns","authors":"Mohammad Kamyar Arbab, Mahmoud Naghibzadeh, S. R. Kamel Tabbakh","doi":"10.1109/ICCKE48569.2019.8965163","DOIUrl":"https://doi.org/10.1109/ICCKE48569.2019.8965163","url":null,"abstract":"scientific workflows are suitable models in many applications for recognition and execution of tasks in parallel, especially in the Cloud. Different aspects of resource provisioning and the resource pricing model in the cloud environment cause the scheduling problem of workflow very complex. One of the main aims of the scheduling algorithms is to satisfy the users’ different quality of service requirements. Communication delay between tasks is an important affecting factor in optimal scheduling of workflows. It can also highly increase the cost of workflow scheduling if proper actions are not taken. To solve this problem, we propose a tasks duplication-based list scheduling algorithm called Communication-Critical Task Duplication (CCTD). We first define the concept of communication critical task (CCT) for a workflow. Then, by presenting a ranking-based approach, we identify communication critical tasks in a workflow as well as duplicating candidates. Task duplication in idle time slots of leased virtual machines which their children tasks are mapped to. This idea, while eliminating the cost and time of data transfer between parent-child tasks, reduces the time of execution of tasks and effectively uses leased time intervals of resources. According to the proposed scheduling algorithm, a new heuristic method has been proposed for the budget distribution. This method distribute overall budget to tasks in proportional to the workload and duplication rank of each task. The proposed algorithm was evaluated and verified using four well-known scientific workflows. The simulation results show that the CCTD algorithm, while respecting the user budget constraint, reduces the workflow overall completion time.","PeriodicalId":6685,"journal":{"name":"2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"24 1","pages":"255-262"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87529148","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 Brief Review on Vessel Extraction and Tracking Methods 血管提取与跟踪方法综述

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8964824

F. Z. Boroujeni, Simindokht Jahangard, R. Rahmat

引用次数: 0