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000914822 020__ $$a9789811501081$$q(electronic book)
000914822 020__ $$a9811501084$$q(electronic book)
000914822 020__ $$z9789811501074
000914822 0247_ $$a10.1007/978-981-15-0108-1$$2doi
000914822 035__ $$aSP(OCoLC)on1121031028
000914822 035__ $$aSP(OCoLC)1121031028
000914822 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dUKMGB$$dEBLCP
000914822 049__ $$aISEA
000914822 050_4 $$aQA75.5
000914822 08204 $$a004$$223
000914822 1112_ $$aInternational Conference on Advanced Informatics for Computing Research$$n(3rd :$$d2019 :$$cShimla, India)
000914822 24510 $$aAdvanced informatics for computing research :$$bthird International Conference, ICAICR 2019, Shimla, India, June 15-16, 2019, Revised selected papers.$$nPart I /$$cedited by Ashish Kumar Luhach, Dharm Singh Jat, Kamarul Bin Ghazali Hawari, Xiao-Zhi Gao, Pawan Lingras.
000914822 2463_ $$aICAICR 2019
000914822 264_1 $$aSingapore :$$bSpringer,$$c2019.
000914822 300__ $$a1 online resource (xvi, 477 pages) :$$billustrations.
000914822 336__ $$atext$$btxt$$2rdacontent
000914822 337__ $$acomputer$$bc$$2rdamedia
000914822 338__ $$aonline resource$$bcr$$2rdacarrier
000914822 4901_ $$aCommunications in computer and information science,$$x1865-0929 ;$$v1075
000914822 500__ $$aIncludes author index.
000914822 5050_ $$aIntro; Preface; Organization; Contents -- Part I; Contents -- Part II; Computing Methodologies; Naïve Bayes Model Based Improved K-Nearest Neighbor Classifier for Breast Cancer Prediction; Abstract; 1 Introduction; 2 Literature Survey; 3 Proposed Approach; 4 Result and Discussion; 5 Conclusion and Future Work; References; Evaluation of Model Using J-48 and Other Classifier on Kddcup99 Through Performance Metrics; Abstract; 1 Introduction; 2 Literature Survey; 2.1 In This Section Literature Review Is Being Discussed; 3 Type of Attacks
000914822 5058_ $$a3.1 This Section Consists of Following Types of Attacks in an IDS Network4 Types of Dataset; 4.1 Datasets and Tools; 5 Performance Metrics; 5.1 Precision Metric; 5.2 Recall Metric; 5.3 F-Measure; 5.4 Accuracy; 6 Comparisons Made by Different Researchers; 6.1 Comparisons; 7 Proposed Work; 7.1 Work; 8 Conclusion; References; Malaria Detection Using Custom Convolutional Neural Network Model on Blood Smear Slide Images; Abstract; 1 Introduction; 2 Related Work; 3 Proposed Methodology; 3.1 Convolutional Neural Networks; 3.2 Configuration of CNN Model
000914822 5058_ $$a3.3 CNN Architecture for Malaria Image Classification4 Results and Discussion; 4.1 Data Preprocessing; 5 Conclusion; References; Rank Based Multi Path Job Execution Sequencing for Multi Cluster Environment to Find Shortest Path; Abstract; 1 Introduction; 1.1 Resource Allocation Within Cloud; 1.2 Resource Allocation in Grid; 2 Literature Survey; 3 Proposed System; 3.1 Working of Shortest Job First Scheduler; 3.2 Working of Round Robin Scheduler; 3.3 Working of PBS; 3.4 Working of Multi Source Shortest Path Algorithm; 4 Performance Analysis and Results; 5 Conclusion and Future Scope; References
000914822 5058_ $$aOptimization of a Real Time Web Enabled Mixed Model Stochastic Assembly Line to Reduce Production TimeAbstract; 1 Introduction; 2 Water Bottling Plant as a Case Study; 3 Model Overview; 3.1 Customer Inputs Using Web Apps; 3.2 Source and Storage Subsystem-Subsystem A; 3.3 Bottle Manufacturing Subsystem-Subsystem B; 3.4 Water Filling Subsystem-Subsystem C; 4 Problem Formulation and Optimization; 5 Results and Discussion; 6 Conclusion and Future Work; Acknowledgements:; References; Recommendation System of Dietary Patterns for Cardiovascular Disease Patients Using Decision Making Approach
000914822 5058_ $$aAbstract1 Introduction; 2 Methodology; 3 Experimental Work; 4 Validation of the Work; 5 Results and Discussions; 6 Conclusions; References; A Model for Classification of Breast Cell Density Using ANN and Shift Invariance Wavelet Transform ConvNet; Abstract; 1 Introduction; 2 Related Work; 3 Proposed System; 3.1 Database Used in the Study; 3.2 Double Tree Complex Valued Discrete Wavelet Transform; 3.3 Digital Mammogram Attribute Vectors; 3.4 Convolutional Neural Networks; 3.5 Dual-Tree Wavelet Based Convolutional Neural Networks; 3.6 Artificial Neural Networks (ANN)
000914822 506__ $$aAccess limited to authorized users.
000914822 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed September 26, 2019).
000914822 650_0 $$aComputer science$$vCongresses.
000914822 650_0 $$aComputer science$$xResearch$$vCongresses.
000914822 7001_ $$aLuhach, Ashish Kumar,$$eeditor.
000914822 7001_ $$aJat, Dharm Singh,$$eeditor.
000914822 7001_ $$aHawari, Kamarul Bin Ghazali,$$eeditor.
000914822 7001_ $$aGao, Xiao-Zhi,$$d1972-$$eeditor.
000914822 7001_ $$aLingras, Pawan,$$eeditor.
000914822 830_0 $$aCommunications in computer and information science ;$$v1075.
000914822 852__ $$bebk
000914822 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-981-15-0108-1$$zOnline Access$$91397441.1
000914822 909CO $$ooai:library.usi.edu:914822$$pGLOBAL_SET
000914822 980__ $$aEBOOK
000914822 980__ $$aBIB
000914822 982__ $$aEbook
000914822 983__ $$aOnline
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