Track 1: Computer and Information Science

It is a field that highlights both computing and informatics, upholding the strong association between the fields of computer sciences and information sciences and treating computers as a tool rather than a field. These fields have similar goals but somewhat different emphases. While computer science stresses how to use technology in problem-solving, information science emphases more on how to solve problems by organizing, sharing, and interpreting information. Computer science uses knowledge from information science to create more effective software design. Information science applies programs and algorithms from computer science to improve its techniques and processes. This combined field together uses computer information systems to deliver unique insights into information technology, network applications, database management among many other subjects.  

Track 2: Computer Network and Security

Computer network security consists of measures taken by some organizations or businesses to monitor and avoid unauthorized access from outside attackers. In the initial days of the internet, its use was limited to development purposes. Later all networks combined together and formed the internet, the data was used to travel through a public transit network. Many different methods of computer network security management have different requirements that depend on the size of the computer network.

Track 3: Applications of computer science and engineering

Computer engineering is defined as the discipline that symbolizes the science and technology of design, implementation, construction and maintenance of software and hardware components of modern computing systems and computer-controlled equipment. Computer engineering has usually been viewed as a combination of both computer science (CS) and electrical engineering (EE). It has progressed over the past three decades as a separate, although intimately related, discipline. Computer engineering is firmly grounded in the theories and principles of computing, science, mathematics and engineering and it applies these theories and principles to solve the technical problems through the design of computing software, hardware, networks, and processes.

Track 4: Computer Science & Engineering

Computer Science and Engineering use principles from Computer Science and Electrical Engineering to create hardware (physical components) and firmware that are used in a wide range of areas: consumer electronics, medical appliances or devices, communication systems, aircraft, self-driving cars, etc. Computer Engineering helps us to develop prototypes and test microchips, circuits, processors, conductors, and any other component used in computer devices or systems (e.g. supercomputers, smartphones, laptops, servers, IoT gadgets). They also develop firmware, a necessary type of software that allows operating systems(OS) and applications to take full advantage of the hardware.

Track 5: Cloud Computing

Cloud computing is the delivery of computing services that includes servers, storage, databases, networking, software, analytics, and intelligence over the Internet (“the cloud”) to offer faster innovation, flexible resources, and economies of scale. Cloud computing follows PAYG(Pay-as-you-go) means You typically pay only for cloud services you use which helps lower your operating costs, run your infrastructure more efficiently and scale as your business needs change. The top benefits of cloud computing are Cost-effective, scalable, Better performance, productivity, Reliability, and Security. It involves delivering hosted services over the internet. These services are divided into three main categories or types of cloud computing: infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). There are different cloud service providers, e.g- Amazon Web Service (AWS) Microsoft Azure Google cloud platform, etc.

Track 6: Artificial Intelligence & Machine Learning

 Artificial Intelligence (AI) is the science and engineering of making intelligent machines, especially intelligent computer programs. Machine Learning (ML) is a subset of Artificial Intelligence. Machine Learning is the science of designing and applying algorithms that are able to learn things from past instances. If some behavior exists in past, then you may predict if it can happen again or not. This means if there are no past cases then there is no prediction at all. Machine Learning can be applied to solve issues like credit card fraud detection, enable self-driving cars, and face detection and recognition. It uses complex algorithms that constantly iterate over large data sets, analyzing the patterns in data and facilitating machines to respond to different situations for which they have not been explicitly programmed. The machines learn from history to produce reliable outcomes.

Track 7: Sensors, Networks, Devices

A sensor network is a group of sensors where each sensor monitors data in a different position and sends that data to a central position for storehouse, viewing, and analysis. There are several wireless norms and results for sensor knot connectivity. Thread and ZigBee can connect sensors operating at 2.4 GHz with a data rate of 250kbit/s. Numerous use a lower frequency to increase radio range (generally 1 km), for illustration Z-wave operates at 915 MHz and in the EU 868 MHz has been extensively used but these have a lower data rate (generally 50 kb/s). The IEEE 802.15.4 working group provides a standard for low power device connectivity and generally sensors and smart meters use one of these norms for connectivity.

The Four Categories of Computer Hardware

• Input devices: For raw data input.
• Processing devices: To process raw data instructions into information.
• Output devices: To disseminate data and information.
• Storage devices: For data and information retention.

 

Track 8: Software Engineering and Programming

Software Engineers have to dissect stoner requirements, company necessities, budget, and the style to develop and apply a software system resolution that supports those demands. They also guide computer programmers to write software code. Once testing the standard of the program, software system engineers are involved with maintaining the software system to confirm responsibility and energy. They decide upon what a business or customer wants and can design the software system in line with their prospects. Computer programmers can make any opinions concerning what the software system application ought to develop and how to appear too.

Generally, programmers use code to perform their jobs, working nearly with engineers, designers, and other programmers, who can give further instructions and guidance on systems. Keep in mind, that coding is a general term that refers simply to writing code. As similar, programmers tend to write code with an entire design in mind, while coders take a narrower approach, fastening on a particular part or point in a larger project. Still, some companies will still hire programmers for the sole purpose of having them write code in addition to other job responsibilities, similar as creating programs from scrape, writing out instructions, or anything in between.

Track 9: Big Data Analytics and Data Science

Data science is a technical field that combines multiple areas similar as statistics, mathematics, intelligent data capture techniques, data sanctification, mining, and programming to prepare and align big data for intelligent analysis to extract perceptivity and information. Big data refers to any large and complex collection of data. Data analytics is the process of rooting meaningful information from data. Data science is a multidisciplinary field that aims to produce broader insights.  Data Analytics is the process of analyzing data in order to extract meaningful data from a given data set. These analytics techniques and methods are carried out on big data in most cases, though they certainly can be applied to any data set. The most important thing to remember is that the accuracy of the analytics is based on the underlying data set. If there are inconsistencies or errors in the dataset, it will result in inefficiencies or outright incorrect analytics. Any good analytical method will consider external factors like data purity, bias, and friction in the analytical methods. Normalization, purifying, and transubstantiating raw data can significantly help in this aspect

Track 10:  Computational Intelligence

Computational Intelligence, is embedded in the fields of engineering, computer science, physics and life sciences, as nicely as the methodologies at the back of them. It is the fast-growing and promising lookup subjects that have drawn a fantastic deal of interest from researchers over the years. It brings collectively many unique components of the modern-day lookup on intelligence technologies such as neural networks, guide vector machines, fuzzy good judgment and evolutionary computation, and covers a broad vary of functions from sample focus and machine modeling, to smart manipulate issues and biomedical applications.

Track 11: Human-Computer Interaction

Human-computer Interaction (HCI) is a multidisciplinary subject of learning about focusing on the graph of pc technological know-how and, in particular, the interplay between human beings (the users) and computers. While originally worried with computers, HCI has for the reason that elevated to cowl nearly all types of facts technological know-how design. It is the learning about how human beings have interacted with computer systems and to what extent computer systems are or are now not developed for profitable interplay with human beings. A big quantity of essential firms and educational establishments now learn about HCI. Historically and with some exceptions, computer system developers have no longer paid a whole lot of interest to computer ease-of-use.

Track 12: Algorithms in Bioinformatics

Bioinformatics is a new and swiftly evolving self-discipline that has emerged from the fields of molecular biology and biochemistry, and from the algorithmic disciplines of computer science and mathematics. The professional definition of bioinformatics is "the research, development, or utility of computational equipment and techniques for increasing the use of biological, medical, behavioral or fitness data, along with these to acquire, store, organize, archive, analyze. It will cowl subjects such as algorithm graph paradigms (dynamic programming, divide-and-conquer, grasping algorithm, wise search), probabilistic models of DNA/Protein sequences, sequence alignments, gene finding, Hidden Markov Models and their applications, phylogenetic tree constructions (molecular evolution), microarray picture and statistics analysis, clustering and learning algorithms.

Track 13: Scientific Computing

Scientific Computing (SC), is a hastily developing multidisciplinary area that makes use of superior computing abilities to apprehend and resolve complicated problems. It is an area of science that spans many disciplines, however, at its core, it entails the improvement of models and simulations to apprehend natural systems. Scientific Computing is currently the “third pillar of science”, standing proper subsequent to theoretical evaluation and experiments for scientific discovery.                            

Computer Engineering Market size was esteemed at around USD 1,800 billion in 2016 and will raise at a CAGR of around 5% from 2017 to 2024. Addition of records science in each and every factor of life is boosting the boom nearly 1.5 instances.

Computer Engineering Market Report Coverage - Report Coverage:     

Past Data for 2013 to 2016 Forecast Period: 2017 to 2024

Forecast Period 2017 to 2024 CAGR: 5% 2024 Value Projection: 2.5 Trillion (USD)

Pages: 350 Tables, Charts & Figures: 210

Geographies covered: U.S., Canada, UK, Germany, France, Italy, Russia, China, India, Japan, South Korea, Brazil, Mexico, Saudi Arabia, UAE, South Africa

Growth Drivers:

• Growth of Internet of Things (IoT)
• Increasing usage of FPGAs (Field Programmable Gate Arrays) in data centers
• Growing smartphone demand in India and South-East Asia
• Rising penetration in industrial and commercial environments in the Asia Pacific
• Growing demand for miniaturized products
• Growing demand for smart sensors in monitoring and diagnostics applications
• Growth of electric (EVs) and hybrid vehicles (HEVs) in North America and Asia Pacific.

Computer Science & Information Technology, and the hardware and software program related with the IT industry, are a crucial phase of each primary international economy. Information technology is useful in every aspect of economies, government, and society. It can be castoff in businesses, for communication including telecasting, for mining, education, agriculture, transportation, banking, and advertising. By 2022, The Business Research Company expects the information technology market to account for 9% of the gross world product (GWP).

The information technology (IT) market consists of sales of IT services by objects (organizations, sole traders and partnerships) that apply computers, computer peripherals, and telecommunications equipment to retrieve, store, transmit and maneuver data.

Information Technology Market Coverage:

The Business Research Company covers 92 markets wide-ranging in the financial amenities market providing global market growth, market-specific drivers and limits, trends, and additional market-specific information.