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International Conference on
Datamining & Cloud Computing with Bigdata Analytics & Machine Learning

Theme : Current Trends and Technologies in Software Industry

November 18-19, Barcelona, Spain

Conference Brochure Abstract Submission Organizing Committee Tentative Schedule

About the Conference

We are very glad to welcome you to participate at our “INTERNATIONAL CONFERENCE ON DATAMINING & CLOUD COMPUTING WITH BIGDATA ANALYTICS & MACHINE LEARNING” on November 18-19, 2019 at Barcelona, Spain with the theme “CURRENT TRENDS AND TECHNOLOGIES IN SOFTWARE INDUSTRY”.
Our Aim is to bring Engineers/Employees, global scientists/ researchers and business professionals to the one platform. DCBM-2019 includes the series of B2B & B2C meetings, Oral Talks, Poster Presentations, and Workshops & Exhibitions by Industries, Academicians, Professors, and Young Forum Researchers & Students.

Why

Know More

Sessions

Click on the session name to expand its sub-sessions.

    •  Data mining systems in financial market analysis
    •  High performance data mining algorithms
    •  Data mining in security
    •  Engineering data mining
    •  Data Mining in Healthcare data
    •  Medical Data Mining
    •  Advanced Database and Web Application
    •  Data mining and processing in bioinformatics, genomics and biometrics
    •  Application of data mining in education
    •  Methodologies on large scale data mining

     

    • Big data in nursing inquiry
    • Methods, tools and processes used with big data with relevance to nursing
    • Big Data and Nursing Practice

     

    •  Machine learning and statistics
    •  Machine learning tools and techniques
    •  Bayesian networks
    •  Fielded applications
    •  Generalization as search

     

    •  Big Data Analytics Adoption
    •  Benefits of Big Data Analytics
    •  Barriers to Big Data Analytics
    •  Volume Growth of Analytic Big Data
    •  Managing Analytic Big Data
    •  Data Types for Big Data

     

    •  Computational problems in magnetic resonance imaging
    •  Optimization of big data in mobile networks

     

    •  Big data storage architecture
    •  GEOSS clearinghouse
    •  Distributed and parallel computing

     

    •  Data Stream Algorithms
    •  Randomized Algorithms for Matrices and Data
    •  Algorithmic Techniques for Big Data Analysis
    •  Models of Computation for Massive Data
    •  The Modern Algorithmic Toolbox

     

    •  Ecommerce and customer service
    •  Finances and Frauds services
    •  Biomedicine
    •  Regulated Industries
    •  Clinical and healthcare
    •  Financial aspects of Big Data Industry
    •  Current and future scenario of Big Data Market
    •  Travel Industry
    •  Retail / Consumer
    •  Big Data Analytics in Enterprises
    •  Public administration
    •  E-Government
    •  Telecommunication
    •  Manufacturing
    •  Security and privacy
    •  Web and digital media

     

    •  Challenges for Forecasting with Big Data
    •  Applications of Statistical and Data Mining Techniques for Big Data Forecasting
    •  Forecasting the Michigan Confidence Index
    •  Forecasting targets and characteristics

     

    •  Novel Theoretical Models for Big Data
    •  New Computational Models for Big Data
    •  Empirical study of data mining algorithms

     

    •  Cybernetics
    •  Artificial creativity
    •  Artificial Neural networks
    •  Adaptive Systems
    •  Ontologies and Knowledge sharing

     

    •  Data encryption
    •  Data Hiding
    •  Public key cryptography
    •  Quantum Cryptography
    •  Convolution
    •  Hashing

     

    •  Data Warehouse Architectures
    •  Case studies Data Warehousing Systems
    •  Data warehousing in Business Intelligence
    •  Role of Hadoop in Business Intelligence and Data Warehousing
    •  Commercial applications of Data Warehousing
    •  Computational EDA (Exploratory Data Analysis) Techniques

     

    •  Big Data Security and Privacy
    •  Ecommerce and Web services
    •  Medical informatics
    •  Visualization Analytics for Big Data
    •  Predictive Analytics in Machine Learning and Data Mining
    •  Interface to Database Systems and Software Systems

     

    •  Competitive analysis of mining algorithms
    •  Computational Modelling and Data Integration
    •  Semantic based Data Mining and Data Pre-processing
    •  Mining on data streams
    •  Graph and sub-graph mining
    •  Scalable data pre-processing and cleaning techniques
    •  Statistical Methods in Data Mining

     

    •  Numeric attributes
    •  Categorical attributes
    •  Graph data

     

    •  Cloud Computing Applications
    •  Emerging Cloud Computing Technology
    •  Cloud Automation and Optimization
    •  High Performance Computing (HPC)
    •  Mobile Cloud Computing

     

    •  Medical and Healthcare
    •  Transportation
    •  Environmental monitoring
    •  Infrastructure Management
    •  Enterprise
    •  Consumer application

     

    •  Networks and relations
    •  Development of social network analysis
    •  Analyzing relational data
    •  Dimensions and displays
    •  Positions, sets and clusters

     

    •  Mathematical Preliminaries
    •  Recursive Algorithms
    •  The Network Flow Problem
    •  Algorithms in the Theory of Numbers
    •  NPcompleteness

     

    •  Emerging phenomena
    •  Technology drives and business analytics
    •  Capitalizing on a growing marketing opportunity

     

    •  Open Data, Government and Governance
    •  Open Development and Sustainability
    •  Open Science and Research
    •  Technology, Tools and Business

     

    •  Analysis data for visualization
    •  Scalar visualization techniques
    •  Frame work for flow visualization
    •  System aspects of visualization applications
    •  Future trends in scientific visualization

     

    •  Multifaceted and task driven search
    •  Personalized search and ranking
    •  Data, entity, event, and relationship extraction
    •  Data integration and data cleaning
    •  Opinion mining and sentiment analysis

     

    •  Frequent item sets and association
    •  Item Set Mining Algorithms
    •  Graph Pattern Mining
    •  Pattern and Role Assessment

     

    •  Hierarchical clustering
    •  Density Based Clustering
    •  Spectral and Graph Clustering
    •  Clustering Validation

     

    •  Data Storage and Access
    •  OLAP Operations
    •  OLAP Architechture
    •  OLAP tools and internet
    •  Functional requirements of OLAP systems
    •  Limitation of spread sheets and SQL

     

    •  ETL Basics in Data Warehousing
    •  ETL Tools for Data Warehouses
    •  Logical Extraction Methods
    •  ETL data structures
    •  Cleaning and conforming
    •  Delivering dimension tables

     

    •  Kernel operations in feature space
    •  Kernel for complex objectives
    •  High dimensional data
    •  Density of the multivariate normal
    •  Dimensionality reduction
    •  Kernel principal component analysis

     

    • Manufacturing

    o    Predictive maintenance or condition monitoring

    o    Warranty reserve estimation

    o    Propensity to buy

    o    Demand forecasting

    o    Process optimization

    o    Telematics

    • Retail

    o    Predictive inventory planning

    o    Recommendation engines

    o    Upsell and crosschannel marketing

    o    Market segmentation and targeting

    o    Customer ROI and lifetime value

    • Healthcare and Life Sciences

    o    Alerts and diagnostics from realtime patient data

    o    Disease identification and risk stratification

    o    Patient triangle optimization

    o    Proactive health management

    o    Healthcare provider sentiment analysis

    • Travel and Hospitality

    o    Aircraft scheduling

    o    Dynamic pricing

    o    Social mediaconsumer feedback and interaction analysis

    o    Customer complaint resolution

    o    Traffic patterns and congestion management

    • Financial Services

    o    Risk analytics and regulation

    o    Customer Segmentation

    o    Cross selling and up selling

    o    Sales and marketing campaign management

    o    Credit worthiness evaluation

    • Energy, Feedstock and Utilities

    o    Power Usage analytics

    o    Seismic data processing

    o    Carbon emission and trading

    o    Customerspecific pricing

    o    Smart grid management

    o    Energy demand and supply optimization

    Advantages of Machine Learning

    • Useful where large scale data is available
    • Large scale deployments of Machine Learning beneficial in terms of improved speed and accuracy
    • Understands nonlinearity in the data and generates a function mapping input to output (Supervised Learning)
    • Recommended for solving classification and regression problems
    • Ensures better profiling of customers to understand their needs
    • Helps serve customers better and reduce attrition

     

    • Unsupervised Pretrained Networks (UPNs)
    • Convolutional Neural Networks (CNNs)
    • Recurrent Neural Networks
    • Recursive Neural Networks

    • Feed forward and neural network
    • Radial basis function (RBF) network
    • Kohonen self-organizing network
    • Learning vector quantization
    • Recurrent neural network
    • Modular neural networks
    • Physical neural networks
    • Other types of networks

    •  Tensorflow
    •  Lasagne
    •  Microsoft Cognitive Toolkit
    •  MXNet
    •  Deeplearningj
    •  PyTorch
    •  Caffe
    •  Keras
    •  Theano
    •  BIgDL

     

    •  Disease Identification/Diagnosis
    •  Personalized Treatment/Behavioural Modification
    •  Drug Discovery/Manufacturing
    •  Clinical Trial Research
    •  Smart Electronic Health Records
    •  Epidemic Outbreak Prediction
    •  Radiology and Radiotherapy

     

    • Controlling processes
    • Navigation
    • Automatic inspection
    • Organizing information
    • Modelling objects or environments
    • Detecting events
    • Recognize objects
    • Locate objects in space
    • Recognize actions
    •  objects in motion

    • Decision Tree
    • LDA/QDA
    • Bayes
    • Kmeans
    • Networks (of any kind)
    • Reinforced learning

  • Processes included in Predictive Analytics are

    • Define Project
    • Data Collection
    • Data Analysis
    • Statistics
    • Modelling
    • Deployment
    • Model Monitoring

    There are many applications of Predictive Analytics. Few of them are

    • Customer Relationship Management (CRM)
    • Collection Analytics
    • Fraud Detection
    • Cross Sell
    • Direct Marketing
    • Risk Management
    • Underwriting
    • Health Care

    Predictive Analytics plays a very strong role in Industry Applications like

    • Predictive Analytics Software
    • Predictive Analytics Software API
    • Predictive Analytics Programs
    • Predictive Lead Scoring Platforms
    • Predictive Pricing Solutions
    • Customer Churn, Renew, Upsell, Cross Sell Software Tools

    • Principal component analysis (PCA)
    • Kernel PCA
    • Graph based kernel PCA
    • Linear Discriminant Analysis (LDA)
    • Generalized discriminant analysis (GDA)

    •  Ancient Era and the Concept of Robot
    •  Asimov and Laws of Robotics
    •  The First “Programmable” Mechanism, a PaintSprayer
    •  The Turtle Robots
    •  Landing in the Moon
    •  Deep Blue beat World Chess Champion

     

    •  Artificial Neural Networks
    •  Evolutionary Computation
    •  Virtual Agents
    •  Cognitive Robotics
    •  Artificial Metamorphosis
    •  Simulated Robotic Agents
    •  Universal Darwinism

     

    •  Actuator
    •  Soft Robotics
    •  Elastic Nanotubes
    •  Robotic Sensing
    •  Computer Vision
    •  Sensor Fusion
    •  Control Theory
    •  Optical Sensors for Robotics Technology
    •  Gyroscopes and Accelerometers
    •  Power Supply and Energy Storage

     

    •  Time to Expand Our Definition of Robot
    •  Robots And D Printing
    •  Object Recognition and Motion Planning
    •  Will Robots Rule Finance?
    •  Social Robot
    •  Human-Robot Interaction
    •  Mechatronics & Robotics

     

    •  Artificial Health Professionals
    •  Remote Surgery
    •  Robotic Surgery
    •  Microbot
    •  Bio Inspired Robotics
    •  Designing Treatment Practices
    •  Elderly Care
    •  Medical Research and Robotics
    •  Putting the “Care” Back in Healthcare
    •  AI for Disabled Person

     

    • Architecture, Storage and Virtualization
    • Cloud Services and Applications
    • Security, Privacy and Trust
    • Edge Computing and Distributed Cloud

    • Intercloud architecture models
    • Virtual Machines (VMs), containers, unikernels and microservices
    • Cloud services delivery models, campus integration & “last mile” issues
    • Virtualization technology and enablers (network virtualization, softwaredefined networking)
    • Networking technologies
    • Cloud system design with FPGAs, GPUs, APUs
    • Storage & file systems
    • Scalability & performance
    • Resource provisioning, monitoring, management & maintenance
    • Operational, economic & business models
    • Green data centers
    • Computational resources, storage & network virtualization
    • Resource monitoring
    • Virtual desktops
    • Resilience, fault tolerance, disaster recovery
    • Modeling & performance evaluation
    • Disaster recovery
    • Energy efficiency

    • XaaS (everything as a service including IaaS, PaaS, and SaaS)
    • Cloud services models & frameworks
    • Service deployment and orchestration in the Cloud
    • Cloud service management
    • Cloud workflow management
    • Cloud services reference models & standardization
    • Cloudpowered services design
    • Cloud elasticity
    • Machine learning and systems interactions
    • Data management applications & services
    • Service for computingintensive applications
    • Mining and analytics
    • Dataprovisioning services
    • Cloud programming models, benchmarks, and tools
    • Cloudbased services & protocols
    • Faulttolerance & availability of cloud services and applications
    • Application development and debugging tools
    • Business models & economics of cloud services

    • Accountability & audit
    • Authentication & authorization
    • Cloud integrity
    • Blockchain Cloud services
    • Cryptography in the Cloud
    • Hypervisor security
    • Identity management & security as a service
    • Prevention of data loss or leakage
    • Secure, interoperable identity management
    • Trust & credential management
    • Trust models for cloud services
    • Usable security Risk management in cloud computing environments
    • Privacy policy framework for clouds
    • Privacypreserving data mining for clouds
    • Information sharing and data protection in the cloud
    • Cryptographic protocols against internal attacks in clouds
    • Privacy protection in cloud platforms
    • Energy/cost/efficiency of security in clouds

  • ·         Cloudlet enabled applications

    ·         Distributed Cloud Infrastructure

    ·         Foundations and principles of distributed cloud computing

    ·         Architectural models, prototype implementations and applications

    ·         Cloud brokers and coordination across multiple resource managers

    ·         Interoperability and mobility

    ·         Software infrastructure for cloudlets

    ·         Dynamic resource, service and context management on edge computing

    ·         Fog Computing

    ·         IoT cloud architectures & models

    ·         Cloudbased contextaware IoT

    ·         Economics and pricing

    Experience with and performance evaluation of existing deployments and measurements (public, private, hybrid, federated environments)

Event Venue

Event venue location info and gallery

Barcelona, Spain

Barcelona, the cosmopolitan capital of Spain’s Catalonia region, is known for its art and architecture. The fantastical Sagrada Família church and other modernist landmarks designed by Antoni Gaudí dot the city. Museu Picasso and Fundació Joan Miró feature modern art by their namesakes. City history museum MUHBA, includes several Roman archaeological sites.

Tentative Schedule

Day 1

Time Session
08:30 - 09:00 Registrations
09:00 - 09:30 Inauguration Ceremony
09:30 - 10:30 Keynote Presentations
10:30 - 10:45 Group Photography
10:45 - 11:00 Tea/Coffee & Snacks Break
11:00 - 03:05 Plenary Presentations
13:05 - 14:00 Lunch Break
14:00 - 15:00 Hands on Workshop
15:00 - 15:50 Plenary Presentations
15:50 - 16:05 Evening Break and Networking
16:05 - 18:00 Plenary Presentations

Day 2

Time Session
09:00 - 09:30 On -Spot Registrations
09:30 - 10:30 Keynote Presentations
10:30 - 10:55 Plenary Presentation
10:55 - 11:10 Tea/Coffee & Snacks Break
11:10 - 01:05 Plenary Presentations
12:50 - 13:50 Lunch Break
13:50 - 14:50 Hands on Workshop
14:50 - 16:00 Poster Presentations
16:00 - 16:15 Evening Break and Networking
16:15 - 17:30 Plenary Presentations
17:30 - 18:00 Awards & Closing Ceremony

Registration

Speaker Registration
$ 649

  • Access to all Conference Sessions
  • Opportunity to give a Keynote/ Plenary/ Poster Presentations/ Workshop
  • Opportunity to publish your Abstract in any of our esteemed Journals & in the Conference Proceedings Book
  • Certificate Accredited by our Organizing Committee Member
  • Handbook & Conference Kit
  • Tea/Coffee & Snack, Lunch during the Conference
  •  

Delegate Registration
(No Presentation)
$ 549

  • Access to all Conference Sessions
  • Can meet the Experts of your Area of expertise arriving from 22+ different Countries
  • Participation Certificate Accredited by our Organizing Committee Member
  • Delegates are not allowed to present their papers in Oral or Poster sessions
  • Handbook & Conference Kit
  • Tea/Coffee & Snack, Lunch during the Conference

Student Registration
$ 449

  • Access to all Conference Sessions
  • Opportunity to give an Oral/ Poster Presentation
  • Opportunity to publish your Abstract in any of our esteemed Journals & in the Conference Proceedings Book
  • Certificate Accredited by our Organizing Committee Member
  • Handbook & Conference Kit
  • Tea/Coffee & Snack, Lunch during the Conference
  •  
  •  

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