2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp)最新文献

Neuroevolution for effective information security training 有效信息安全训练的神经进化

2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp) Pub Date : 2017-12-01 DOI: 10.1109/ICSOFTCOMP.2017.8280078

Kushal Anjaria, Arun Mishra

引用次数: 1

Automated system for Brain tumour detection and classification using eXtreme Gradient Boosted decision trees 使用极端梯度增强决策树的脑肿瘤检测和分类自动化系统

2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp) Pub Date : 2017-12-01 DOI: 10.1109/ICSOFTCOMP.2017.8280091

Tushar Kant Mudgal, Aditya Gupta, Siddhant U. Jain, Kunal Gusain

{"title":"Automated system for Brain tumour detection and classification using eXtreme Gradient Boosted decision trees","authors":"Tushar Kant Mudgal, Aditya Gupta, Siddhant U. Jain, Kunal Gusain","doi":"10.1109/ICSOFTCOMP.2017.8280091","DOIUrl":"https://doi.org/10.1109/ICSOFTCOMP.2017.8280091","url":null,"abstract":"This Brain tumor detection and classification is an intrinsic part of any diagnostic system and has witnessed extensive research and procedural advancement over time. The complexity of brain as an organ features to be identified, the presence of noise, poor contrast and intensity inhomogeneity in the images, efficient feature extraction, and accurate classification necessitates the development of an efficacious automated system. We propose a novel automated approach for detection and classification, using the Modified K-Means Clustering algorithm with Mean Shift Segmentation for pre-processing magnetic resonance images (MRI). Detection is done using Marker-Controlled Watershed Transform, and Gray-Level Co-Occurrence Matrix (GLCM) is used for feature extraction. For classification, we use the new and improved version of Gradient Boosted Machines (GBM) called eXtreme GBMs. Implemented using the XGBoost library, this supervised learning model has shown more accurate results and in lesser times, it is being used widely by data scientists and gives state of the art solutions.","PeriodicalId":118765,"journal":{"name":"2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124508497","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: 9

Machine learning approaches for breast cancer diagnosis and prognosis 乳腺癌诊断和预后的机器学习方法

2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp) Pub Date : 2017-12-01 DOI: 10.1109/ICSOFTCOMP.2017.8280082

Ayush Sharma, Sudhanshu Kulshrestha, S. Daniel

引用次数: 34

An indexing technique for fuzzy object oriented database using R tree index 基于R树索引的模糊对象数据库索引技术

2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp) Pub Date : 2017-12-01 DOI: 10.1109/ICSOFTCOMP.2017.8280089

Priyanka Israni, Dippal Israni

引用次数: 6

Dynamic question answering system based on ontology 基于本体的动态问答系统

2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp) Pub Date : 2017-12-01 DOI: 10.1109/ICSOFTCOMP.2017.8280094

P. Rajendran, Rufina Sharon

引用次数: 2

Match score level fusion of iris and sclera descriptor for iris recognition 虹膜与巩膜描述符匹配分数融合的虹膜识别

2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp) Pub Date : 2017-12-01 DOI: 10.1109/ICSOFTCOMP.2017.8280079

Mrunal K. Pathak, V. Bairagi, N. Srinivasu, Bhavana V. Chavan

{"title":"Match score level fusion of iris and sclera descriptor for iris recognition","authors":"Mrunal K. Pathak, V. Bairagi, N. Srinivasu, Bhavana V. Chavan","doi":"10.1109/ICSOFTCOMP.2017.8280079","DOIUrl":"https://doi.org/10.1109/ICSOFTCOMP.2017.8280079","url":null,"abstract":"Most recently popular biometrie systems are based on recognition and classification of unique sclera and iris patterns. Unique pattern of blood veins explore the interest in sclera recognition for person identification. However sclera segmentation of relaxed eye images in condition such as different stare direction, at-a-distance image and on-the-move image widely enquired. The drawback of iris is off angle imaging where position of iris and center for off angle imagining affect the performance of sclera segmentation in terms of accuracy. Another challenge in sclera segmentation and iris recognition is high resolution and dark images which causes draining process for mobile application. So we proposed a new method which is the fusion of both iris and sclera. In proposed system sclera and iris descriptor value are fuse together for reliable and accurate iris recognition system. The proposed method will test the execution of iris recognition system for different fusion model using iris and sclera descriptor values to ensure the performance of iris recognition for a relaxed imaging.","PeriodicalId":118765,"journal":{"name":"2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp)","volume":"07 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129420996","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

Fuzzy logic based PV STATCOM operation for grid voltage regulation in night 基于模糊逻辑的夜间电网调压运行

2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp) Pub Date : 2017-12-01 DOI: 10.1109/ICSOFTCOMP.2017.8280080

N. Solanki, J. Patel

引用次数: 1

Improving generalization of k-means clustering based probabilistic neural network using noise injection 利用噪声注入改进基于k均值聚类的概率神经网络的泛化

2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp) Pub Date : 2017-12-01 DOI: 10.1109/ICSOFTCOMP.2017.8280097

Sourabrata Mukherjee

{"title":"Improving generalization of k-means clustering based probabilistic neural network using noise injection","authors":"Sourabrata Mukherjee","doi":"10.1109/ICSOFTCOMP.2017.8280097","DOIUrl":"https://doi.org/10.1109/ICSOFTCOMP.2017.8280097","url":null,"abstract":"In this article, a methodology has been presented to enhance the generalization of the probabilistic neural network (PNN). For the purpose, in this article, I have performed a noise based training over the PNN classifier. Here, while training the PNN, I have injected random Gaussian multiplicative noise in the samples of the data set. This external noise injection mechanism improves the classification accuracy of the data set. Furthermore, to reduce the storage requirement of the network, I have used k-means clustering algorithm, and through this algorithm I have selected a subset of class samples from each class. It reduces the number of stored pattern in the pattern layer. The entire process generates a advanced classifier based on fusion neural network model. To test the classification rightness of the proposed method, eight standard data sets have been used. Proposed model has been compared with conventional PNN classifier. Comparison of result exhibit the ascendancy of the presented method. Wilcoxon signed rank trial also manifests that proposed method improves the performance of the classifier.","PeriodicalId":118765,"journal":{"name":"2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128768952","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

High speed SRT divider for intelligent embedded system 智能嵌入式系统的高速SRT分频器

2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp) Pub Date : 2017-12-01 DOI: 10.1109/ICSOFTCOMP.2017.8280077

Bhavana Mehta, Jonti Talukdar, S. Gajjar

{"title":"High speed SRT divider for intelligent embedded system","authors":"Bhavana Mehta, Jonti Talukdar, S. Gajjar","doi":"10.1109/ICSOFTCOMP.2017.8280077","DOIUrl":"https://doi.org/10.1109/ICSOFTCOMP.2017.8280077","url":null,"abstract":"Increasing development in embedded system, VLSI and processor design have given rise to increased demands from the system in terms of power, speed, area, throughput etcetera. Most of the sophisticated embedded system applications consist of processors; which now need an arithmetic unit with the ability to execute complex division operations with maximum efficiency. Hence the speed of the arithmetic unit is critically dependent on division operation. Most of the dividers use the SRT division algorithm for division. In IoT and other embedded applications typically radix 2 and radix 4 division algorithms are used. The proposed algorithm lies on parallel execution of various steps so as to reduce time critical path, use fuzzy logic to solve the overlap problem in quotient selection; hence reducing maximum delay and increasing the accuracy. Every logical circuit has a maximum delay on which the timing of the circuit is dependent and the path, causing the maximum delay is known as the critical path. Our approach uses the previous SRT algorithm methods to make a highly parallel pipelined design and use Mamdani model to determine a solution to the overlapping problem to reduce the overall execution time of radix 4 SRT division on 64 bits double precision floating point numbers to 281ns. The design is made using Bluespec System Verilog, synthesized and simulated using Vivado v.2016.1 and implemented on Xilinx VirtexUltraScale FPGA board.","PeriodicalId":118765,"journal":{"name":"2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123131858","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: 6

An intuitive algorithm for rotation about an arbitrary axis 一个直观的算法旋转围绕一个任意轴

2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp) Pub Date : 2017-12-01 DOI: 10.1109/ICSOFTCOMP.2017.8280092

C. Sabharwal, R. Prasath

引用次数: 2