Call for Abstract
2nd World International Conference on Computer Science, Machine Learning and Big Data, will be organized around the theme “Exploring the Unexplored Technology”
Computer Science Meet 2019 is comprised of keynote and speakers sessions on latest cutting edge research designed to offer comprehensive global discussions that address current issues in Computer Science Meet 2019
Submit your abstract to any of the mentioned tracks.
Register now for the conference by choosing an appropriate package suitable to you.
Computer Science Technology forms the technological infrastructure of recent commerce. Engineering is associate ever-evolving, increasing field. It is the drive of each trade and permeates way of life. It is the flexibility to mix the ability of computing with the management of multimedia system information and is arguably the key to get an ascendancy in any field.
- Track 1-1Scientific computing
- Track 1-2Computer graphics
- Track 1-3Algorithmic trading
- Track 1-4Simulation
- Track 1-5Human-Computer Interaction
AI or computer science is the simulation of human intelligence processes by machines, particularly by PC systems. These processes embrace learning (the acquisition of data and rules for victimization the information), reasoning (using the foundations to achieve approximate or definite conclusions), and self-correction. Applications of AI embrace skilled systems, speech recognition, and machine vision. Today, it's AN umbrella term that encompasses everything from robotic method automation to actual AI. It's gained prominence is recently due to the in part, to big data, or to the rise in speed, size, style of information and businesses square measure which is currently grouping. AI will perform tasks like distinguishing patterns within the information additional expeditiously than human businesses to realize additional insight out of their information.
- Track 2-1Robotic process automation
- Track 2-2Machine vision
- Track 2-3Natural language processing
- Track 2-4Robotics
Machine learning is a kind of computing (Artificial Intelligence) which permit software system applications to become additionally correct in predicting outcomes while not being expressly programmed. The essential plan of machine learning is to compile algorithms which receive input file associate degree and is used in applied mathematical analysis to foresee an output worth among a satisfactory vary.
- Track 3-1Machine learning algorithms
- Track 3-2Supervised learning
- Track 3-3Unsupervised learning
Deep learning is associated with the developments in computing power and special sorts of neural networks to check the advanced patterns in a large amount of knowledge. Deep learning techniques is a square measure, present the state of the art for characteristic objects in pictures and words are in sounds. Researchers currently expect to apply these successes in pattern recognition to a lot of advanced tasks like automatic language translation, medical diagnoses and diverse which are necessary in social and business issues.
- Track 4-1How to build neural networks
- Track 4-2Convolutional networks
- Track 4-3RNNs, LSTM, Adam, Dropout, BatchNorm
- Track 4-4Xavier/He initialization
A.I. is getting used nowadays by businesses in both huge and tiny. About what proportion of effect will the A.I have on our future and in what ways will it be succeeded in our day-to-day life? Once A.I. really blossoms, what proportion of improvement can it have on the present iterations of this technology?
- Track 5-1AI in healthcare
- Track 5-2AI in business
- Track 5-3AI in education
- Track 5-4AI in finance
- Track 5-5AI in manufacturing
Big information may be a term that describes the big volume of information – each structured and unstructured – that inundates a business on a day-after-day basis. However, it’s not the number of information that’s necessary. It is what organizations do with the information that matters. Big Data information will be analyzed for insights that cause higher selections and strategic business moves. The number of information that’s being created and hold on a world level is nearly unthinkable, and it simply keeps growing. Meaning there’s even a lot of potential to harvest key insights from business information nonetheless solely a little share of information is analyzed. What will that mean for businesses? However, they will create higher use of the raw info that flows into their organizations each day.
- Track 6-1Importance of Big data
- Track 6-2Applications of Big data
- Track 6-3Streaming data
- Track 6-4Social media data
- Track 6-5Publicly available sources
- Track 6-6Data Exploration & Visualization
Artificial Intelligence (AI), mobile, social and Internet of Things (IoT) are driving information complexness, new forms and sources of knowledge. Big Data analytics is that the use of advanced analytic techniques against terribly giant, numerous information sets that embrace structured, semi-structured and unstructured information, from totally different sources, and in several sizes from terabytes to zettabytes. Analyzing huge information permits analysts, researchers, and business users to create higher and quicker selections victimization information that was antecedently inaccessible or unusable. Victimization advanced analytics techniques like text analytics, machine learning, prognostic analytics, data processing, statistics, and language process, businesses will analyze antecedently untapped information sources freelance or at the side of their existing enterprise information to realize new insights leading to higher and quicker selections.
- Track 7-1Apache
- Track 7-2Scala
- Track 7-3Spark
Data mining is thought of a superset of the many different strategies to extract insights from knowledge. It would involve ancient applied mathematics strategies and machine learning. Data processing applies strategies from many alternative areas to spot antecedently unknown patterns from knowledge. This could embody applied mathematics, algorithms, machine learning, text analytics, statistical analysis and alternative areas of analytics. Data processing conjointly includes the study and follow the knowledge of storage and data manipulation.
- Track 8-1High performance data mining algorithm
- Track 8-2Data Mining in Healthcare data
- Track 8-3Medical Data Mining
- Track 8-4Advanced Database and Web Application
- Track 8-5Data mining and processing in bioinformatics, genomics and biometrics
The cornerstone of data analytics in cloud computing is cloud computing itself. Cloud Computing is made around a series of hardware and computer code that may be remotely accessed through any web browser. Usually, files and computer code area unit shared and worked on by multiple users and everyone knowledge is remotely centralized rather than being hold on users’ onerous drives.
- Track 9-1IoT on Cloud Computing
- Track 9-2Fog Computing
- Track 9-3Cognitive Computing
- Track 9-4Mobile Cloud Computing
Businesses have used data analytics to assist their strategy to maximize profits. Ideally, information analytics helps to eliminate a lot of the estimate concerned in making an attempt to know purchasers, instead systemically following information patterns to best construct business techniques and operations to reduce uncertainty. Not solely will analytics verify what may attract new customers, usually, analytics acknowledges existing patterns in information to assist higher serve existing customers, that is usually less expensive than establishing a replacement business. In an associate degree dynamic business world subject to unnumbered variants, analytics provides firms with the sting in recognizing dynamical climates, in order that they will take initiate applicable action to remain competitive. aboard analytics, cloud computing is additionally serving to create business simpler and therefore the consolidation of each cloud and analytics may facilitate businesses store, interpret, and method their massive information is raised to meet their clients’ wants.
- Track 10-1Software as a service (SaaS)
- Track 10-2SaaS examples
- Track 10-3Best uses of Data analytics in cloud
- Track 10-4Future of Data analytics in cloud
Distributed computing may be a style of Internet-based imagining that offers shared handling resources and knowledge to PCs and in contrast to devices on concentration. it's a typical for authorizing pervasive, on-interest access to a typical pool of configurable registering assets which might be quickly provisioned and discharged with insignificant administration travail. Distributed calculative and volume preparations provide shoppers and ventures with totally different skills to store and procedure their data in outsider data trots. It depends on sharing of assets to accomplish rationality and economy of scale, sort of a utility over a system.
- Track 11-1Microsoft Azure Cloud Computing
- Track 11-2Amazon Web Services
- Track 11-3Google Cloud
- Track 11-4Cloud Automation and Optimization
- Track 11-5High Performance Computing (HPC)
- Track 11-6Emerging Cloud Computing Technology
The competitive intelligence might be a technology-driven methodology for Analyzing data and presenting an unjust information to help executives, managers, and different company end users to produce enlightened businesses selections. Business intelligence will be employed by enterprises to support a large vary of business choices - starting from operational to strategic. Basic operational choices embody product positioning or valuation. Metal encompasses a decent kind of tools, applications, and methodologies that differentiate the corporations to collect information from internal and external sources; prepare it for analysis; develop and activate queries against the data; and build reports, dashboards and knowledge visualizations to make the analytical results on the market to the corporate decision-makers, likewise as operational staff.
- Track 12-1Why BI is important?
- Track 12-2Types of BI tools
- Track 12-3BI trends
- Track 12-4BI for Big data
SAP is an ERP (Enterprise Resource Planning) software while SAS is an analytics package developed by SAS (Statistical Analysis System) institute. It was founded by James Goodnight and several Colleagues in 1976 from North Carolina State University. Currently, it is used as an integration of software products that enables anyone to perform: Data Manipulation, Statistical and mathematical analysis, Planning, forecasting and decision Support, Report Writing and Graphics, Quality Improvement, Applications Development, Web Reporting, Data Entry, Retrieval, and Management, Data Warehousing and Data Mining. SAS runs on both Windows and UNIX platforms. It is used in a wide range of industries such as healthcare, education, financial services, life sciences etc.
- Track 13-1SAS Administrators
- Track 13-2Customer Intelligence
- Track 13-3Data Management
- Track 13-4Risk Management
- Track 13-5Fraud & Security Intelligence
- Track 13-6Data Visualization
New intelligent things typically constitute 3 categories: robots, drones and autonomous vehicles. Every one of these areas can evolve to impact a bigger section of the market and support a brand-new section of digital business, however, these represent just one aspect of intelligent things. Existing things together with internet of Things (IoT) devices can become intelligent things delivering the facility of AI enabled systems all over together with the house, office, manufacturing plant floor, and medical facility. the forthcoming revolution of the Internet-of-Things (IoT) and ensuring connectedness of sensible home technology for years.
Internet of Things (IoT) is associate degree system which is connected to physical objects that square measure accessible through the web. The ‘thing’ in IoT might be someone with a cardiac monitor or associate degree automobile with built-in-sensors, i.e. objects that are allotted associate degree science address and might collect and transfer knowledge over a network while not manual help or intervention. The embedded technology within the objects helps them to move with internal states or the external surroundings, that successively affects the choices taken. IoT – and therefore the machine-to-machine (M2M) technology behind it – square measure transfers a form of “super visibility” to just about each business. Imagine utilities and telcos that may predict and stop service outages, airlines that may remotely monitor and optimize plane performance, and care organizations that are based on health care on period ordering analysis. The business prospects square measure endless.
- Track 14-1Why IOT?
- Track 14-2What is the scope of IOT?
- Track 14-3How can IOT help?
Virtual reality (VR) associated Augmented reality (AR) rework the way people move with one another and with package systems making an immersive setting. for instance, VR will be used for coaching situations and remote experiences. AR, that allows a mixing of the important and virtual worlds, means that businesses will overlay graphics onto real-world objects, like hidden wires on the image of a wall. Immersive experiences with AR and VR area unit reaching tipping points in terms of value and capability, however, it won't replace different interface models. Over time AR and VR expand on the far side visual immersion to incorporate all human senses. Enterprises ought to rummage around for targeted applications of VR and AR through 2020.
- Track 15-1Computer-mediated reality
- Track 15-2Object recognition
- Track 15-3virtual fixture