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5th World Congress on Emerging Trends in Science, Engineering and Technology, will be organized around the theme “How New Technology And Innovations Are Reshaping Engineering”

Science-Technology-2022 is comprised of keynote and speakers sessions on latest cutting edge research designed to offer comprehensive global discussions that address current issues in Science-Technology-2022

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Data science is an interdisciplinary field that uses scientific methods, processesalgorithms and systems to extract knowledge and insights from noisy, structured and unstructured data and apply knowledge and actionable insights from data across a broad range of application domains. Data science is related to data miningmachine learning and big data.

Data science is a "concept to unify statisticsdata analysisinformatics, and their related methods" in order to "understand and analyze actual phenomena" with data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. However, data science is different from computer science and information science. Turing Award winner imagined data science as a "fourth paradigm" of science and asserted that "everything about science is changing because of the impact of information technology" and the data deluge

Intelligent systems are technologically advanced machines that perceive and respond to the world around them. Intelligent systems can take many forms, from automated vacuums such as the Roomba to facial recognition programs to Amazon's personalized shopping suggestions. One way that such systems can perceive their environment is through vision. The study of how computers can understand and interpret visual information from static images and video sequences emerged in the late 1950s and early 1960s. It has since grown into a powerful technology that is central to the country's industrial, commercial, and government sectors. The key factors that have contributed to this growth are the exponential growth of processor speed and memory capacity as well as algorithmic advances. The field of intelligent systems also focuses on how these systems interact with human users in changing and dynamic physical and social environments. Early robots possessed little autonomy in making decisions: they assumed a predictable world and perfumed the same action(s) repeatedly under the same conditions. Today, a robot is considered to be an autonomous system that can sense the environment and can act in a physical world in order to achieve some goals.

 

The smart network is a collection of connected devices that allows the transfer of data and gathers different kinds of information such as who’s connected. With our expertise, we can detect all available data coming from new or historic devices in your organization and bring it together in one dashboard. This data can then be captured and analyzed. The analysis will automatically discover certain trends and needs (machine learning). The output or result is data presented in the form of one or more API’s. We use these API’s to create apps & dashboards to feed business intelligence systems for process automation. Unifying and transforming this data will unleash new possibilities for your organization. This is what we call The Smart Network. The Smart Network makes your data more accessible. The internet of things, or IoT, is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers(UIDS) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. A thing in the internet of things can be a person with a heart monitor implant, a farm animal with a biochip transponder, an automobile that has built-in sensors to alert the driver when tire pressure is low or any other natural or man-made object that can be assigned an Internet Protocol (IP) address and is able to transfer data over a network. Increasingly, organizations in a variety of industries are using IoT to operate more efficiently, better understand customers to deliver enhanced customer service, improve decision-making and increase the value of the business.

Computer securitycybersecurity, or information technology security (IT security) is the protection of computer systems and networks from information disclosure, theft of or damage to their  hardware, software, or electronic data, as well as from the disruption or misdirection of the services they provide. The field is becoming increasingly significant due to the continuously expanding reliance on computer systems, the Internet and wireless network standards such as Bluetooth and Wi-Fi, and due to the growth of "smart" devices, including smartphones, televisions, and the various devices that constitute the Internet of things (IoT). Cybersecurity is also one of the significant challenges in the contemporary world, due to its complexity, both in terms of political usage and technology. Its primary goal is to ensure the system's dependability, integrity, and data privacy.

Different types of Computer Security

 

Machine learning (ML) is the study of computer algorithms that can improve automatically through experience and by the use of data. It is seen as a part of artificial intilligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicineemail filteringspeech recognition, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.

A subset of machine learning is closely related to computational statitics, which focuses on making predictions using computers; but not all machine learning is statistical learning. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. Data mining is a related field of study, focusing on exploratory data analysis through unsupervised. Some implementations of machine learning use data and neural networks  in a way that mimics the working of a biological brain. In its application across business problems, machine learning is also referred to as predictive analytics.

 

Multimedia generally refers to images, graphics, texts, and sounds. As an important information carrier, images have features such as intuitive images and rich content. They are an important way of expressing information. Image processing technology has become a major content of multimedia processing technology. Image processing is used to find out various patterns and aspects in images. Pattern Recognition is used for Handwriting analysis, Image recognition, Computer-aided medical diagnosis, and much more

 

  1. Cloud Computing - Cloud computing is a network of resources a company can access, and this method of using a digital drive increases the efficiency of organizations. According to Forbes, 83 percent of enterprise workloads will be in the cloud by 2020, which means 2019 will show an increasing trend.
  1. Mobile Apps and computing - Mobile phones, tablets, and other devices have taken both the business world and the personal realm by storm. Mobile usage and the number of applications generated have both skyrocketed in recent years. Now, 77 percent of Americans own smartphones — a 35 percent increase since 2011.

3. Big data analyticsBig data is a trend that allows businesses to analyze extensive sets of information to achieve variety in increasing volumes and growth of velocity. Examination of data to understand markets and strategies is becoming more manageable with advances in data analytics programs.
 

4. Automation - Another current trend in the IT industry is automated processes. Automated processes can collect information from vendors, customers, and other documentation. Machine learning can enhance these automated processes for a continually developing system. Automated processes for the future will extend to groceries and other automatic payment methods to streamline the consumer experience.

 

Software engineering is a systematic engineering approach to software development.

software engineer is a person who applies the principles of software engineering to design, develop, maintain, test, and evaluate computer software. The term programmer is sometimes used as a synonym, but may also lack connotations of engineering education or skills.

Engineering techniques are used to inform the software development process which involves the definition, implementation, assessment, measurement, management, change, and improvement of the software life cycle process itself. It heavily uses software configuration management which is about systematically controlling changes to the configuration, and maintaining the integrity and traceability of the configuration and code throughout the system life cycle. Modern processes use software versionising.

 

mathematical model is a description of a system using mathematical concepts and language. The process of developing a mathematical model is termed mathematical modeling. Mathematical models are used in the natural sciences (such as physicsbiologyearth sciencechemistry) and engineering disciplines (such as computer scienceelectrical engineering), as well as in non-physical systems such as the social sciences (such as economicspsychologysociologypolitical science). The use of mathematical models to solve problems in business or military operations is a large part of the field of operations research. Mathematical models are also used in music, linguistics, and philosophy (for example, intensively in analytic philosophy).

A model may help to explain a system and to study the effects of different components, and to make predictions about behavior.

Analysis is the branch of mathematics dealing with limits and related theories, such as differentiationintegration,measuresequencesseries, and analytical functions.

These theories are usually studied in the context of real and complex numbers and functions. Analysis evolved from calculus, which involves the elementary concepts and techniques of analysis. Analysis may be distinguished from geometry; however, it can be applied to any space of mathematical objects that has a definition of nearness (a topological space) or specific distances between objects (a metric space).

 

Aerospace engineering is the primary field of engineering concerned with the development of aircraft and spacecraft. It has two major and overlapping branches: aeronautical engineering and astronautical engineering. Avionics engineering is similar, but deals with the electronics side of aerospace engineering. Automotive engineering, along with aerospace engineering and naval architecture, is a branch of vehicle engineering, incorporating elements of mechanical, electricalelectronicsoftware, and safety engineering as applied to the design, manufacture and operation of motorcyclesautomobiles, and trucks and their respective engineering subsystems. It also includes modification of vehicles. Manufacturing domain deals with the creation and assembling the whole parts of automobiles is also included in it. The automotive engineering field is research -intensive and involves direct application of mathematical models and formulas. The study of automotive engineering is to design, develop, fabricate, and test vehicles or vehicle components from the concept stage to production stage. Production, development, and manufacturing are the three major functions in this field.

 

 Computational intelligence (CI) usually refers to the ability of a computer to learn a specific task from data or experimental observation. Even though it is commonly considered a synonym of soft computing, there is still no commonly accepted definition of computational intelligence.

Generally, computational intelligence is a set of nature-inspired computational methodologies and approaches to address complex real-world problems to which mathematical or traditional modeling can be useless for a few reasons: the processes might be too complex for mathematical reasoning, it might contain some uncertainties during the process, or the process might simply be stochastic in nature Indeed, many real-life problems cannot be translated into binary language (unique values of 0 and 1) for computers to process it. Computational Intelligence therefore provides solutions for such problems.

The methods used are close to the human's way of reasoning, i.e. it uses inexact and incomplete knowledge, and it is able to produce control actions in an adaptive way. CI therefore uses a combination of five main complementary techniques. The fuzzy logic which enables the computer to understand natural language, artificial neural networks which permits the system to learn experiential data by operating like the biological one, evolutionary computing, which is based on the process of natural selection, learning theory, and probabilistic methods which helps dealing with uncertainty imprecision.

 

Automation describes a wide range of technologies that reduce human intervention in processes. Human intervention is reduced by predetermining decision criteria, sub process relationships, and related actions — and embodying those predeterminations in machines.

Automation, includes the use of various equipment and control systems such as machinery, processes in factories, boilers, and heat-treating ovens, switching on telephone networkssteering, and stabilization of shipsaircraft, and other applications and vehicles with reduced human intervention Automation has been achieved by various means including mechanical, hydraulic, pneumatic, electrical, electronic devices, and computers, usually in combination. Complicated systems, such as modern factories ,airpalnes , and ships typically use all these combined techniques. The benefit of automation includes labor savings, reducing waste, savings in electricity costs, savings in material costs, and improvements to quality, accuracy, and precision.