top of page

Parenthood Support Group

Public·11 members
Eldar Markov
Eldar Markov

Advances In Computer Science, Engineering And A...


The robotics field studies and develops robots in the pursuit of make life easier. A multidisciplinary field, robotics incorporates computer science and electrical and mechanical engineering. Robotics uses artificial intelligence, machine learning, and other computer science technologies.




Advances in Computer Science, Engineering and A...



The International conference series on Computer Science, Engineering & Applications (ICCSEA) aims to bring together researchers and practitioners from academia and industry to focus on understanding computer science, engineering and applications and to establish new collaborations in these areas. The Second International Conference on Computer Science, Engineering & Applications (ICCSEA-2012), held in Delhi, India, during May 25-27, 2012 attracted many local and international delegates, presenting a balanced mixture of intellect and research both from the East and from the West. Upon a strenuous peer-review process the best submissions were selected leading to an exciting, rich and a high quality technical conference program, which featured high-impact presentations in the latest developments of various areas of computer science, engineering and applications research.


Scientific computing, including modeling, simulation and artificial intelligence, coupled with traditional theoretical and experimental approaches, enables breakthrough scientific discoveries and pushes innovation forward. As scientific modeling and simulation become more complex and ambitious, high-performance computing (HPC), commonly known as supercomputing, provides the invaluable ability to perform these complex calculations at high speeds. Supercomputers along with advances in software, algorithms, methods, tools and workflows equip researchers with powerful tools needed to study systems that would otherwise be impractical, or impossible, to investigate by traditional means due to their complexity or the danger they pose.


Corinna Cortes is a Vice President of Google Research in New York City, where she is working on a broad range of theoretical and applied large-scale machine learning problems. She has published numerous articles on topics including supervised learning by classification, and data mining. Cortes was recently named an ACM Fellow for theoretical and practical contributions to machine learning, industrial leadership, and service to the field. In her interview, she discusses her switch from physics to computer science, her work at Google Research, and more.


ACM Journal on Autonomous Transportation Systems (JATS) aims to cover the topics in design, analysis, and control of autonomous transportation systems. The area of autonomous transportation systems is at a critical point where issues related to data, models, computation, and scale are increasingly important. Similarly, multiple disciplines including computer science, electrical engineering, civil engineering, etc., are approaching these problems with a significant growth in research activity. For further information and to submit your manuscript, please visit the journal homepage.


Dramatic advances in the ability to gather, store, and process data have led to the rapid growth of data science and its mushrooming impact on nearly all aspects of the economy and society. Data science has also had a huge effect on academic disciplines with new research agendas, new degrees, and organizational entities. Recognizing the complexity and impact of the field, Alfred Spector, Peter Norvig, Chris Wiggins, and Jeannette Wing have completed a new textbook on data science, Data Science in Context: Foundations, Challenges, Opportunities, published in October 2022. With deep and diverse experience in both research and practice, across academia, government, and industry, the authors present a holistic view of what is needed to apply data science well.


Computer scientists at Harvard pursue work in a wide range of areas including theoretical computer science, artificial intelligence, economics and computer science, privacy and security, data-management systems, intelligent interfaces, operating systems, computer graphics, computational linguistics, robotics, networks, architectures, program languages, machine learning, and visualization.


The computer engineering degree requires several classes in analog and digital circuits in addition to the core computer science classes. The degree provides students with a deeper knowledge of how computers work, thus it is for students interested in either developing computing hardware or software that communicates directly with the hardware, such as VLSI, embedded systems, device drivers, real-time operating systems, robotics and others.


Every industry uses computers so naturally that you can find computer professionals in any type of industry. Problems in science, engineering, health care, and so many other areas can be solved by computers.


Journal of Advances in Mathematics and Computer Science (ISSN: 2456-9968) aims to publish original research articles, review articles and short communications, in all areas of mathematics and computer science. Subject matters cover pure and applied mathematics, mathematical foundations, statistics and game theory, use of mathematics in natural science, engineering, medicine, and the social sciences, theoretical computer science, algorithms and data structures, computer elements and system architecture, programming languages and compilers, concurrent, parallel and distributed systems, telecommunication and networking, software engineering, computer graphics, scientific computing, database management, computational science, artificial Intelligence, human-computer interactions, etc. This is a quality controlled, OPEN peer reviewed, open access INTERNATIONAL journal.


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


Historically, the field of computer engineering has been widely viewed as "designing computers." In reality, the design of computers themselves has been the province of relatively few highly skilled engineers whose goal was to push forward the limits of computer and microelectronics technology. The successful miniaturization of silicon devices and their increased reliability as system building blocks has created an environment in which computers have replaced the more conventional electronic devices. These applications manifest themselves in the proliferation of mobile telephones, personal digital assistants, location-aware devices, digital cameras, and similar products. It also reveals itself in the myriad of applications involving embedded systems, namely those computing systems that appear in applications such as automobiles, large- scale electronic devices, and major appliances.


Technological advances and innovation continue to drive computer engineering. There is now a convergence of several established technologies (such as television, computer, and networking technologies) resulting in widespread and ready access to information on an enormous scale. This has created many opportunities and challenges for computer engineers. This convergence of technologies and the associated innovation lie at the heart of economic development and the future of many organizations. The situation bodes well for a successful career in computer engineering.


Robust studies in mathematics and science are absolutely critical to student success in the pursuit of computer engineering. Mathematical and scientific concepts and skills must be understood and mastered in a manner that enables the student to draw on these disciplines throughout the computer engineering curriculum. One cannot overstate the role that mathematics and science play in underpinning an engineering student's academic pursuits.


A strong and extensive foundation in mathematics provides the necessary basis for studies in computer engineering. This foundation must include both mathematical techniques and formal mathematical reasoning. Mathematics provides a language for working with ideas relevant to computer engineering, specific tools for analysis and verification, and a theoretical framework for understanding important concepts. For these reasons, mathematics content must be initiated early in the student's academic career, reinforced frequently, and integrated into the student's entire course of study. Curriculum content, pre- and co-requisite structures, and learning activities and laboratory assignments must be designed to reflect and support this framework. Specific mathematical content must include the principles and techniques of discrete structures; furthermore, students must master the established sequence in differential and integral calculus.


Rigorous laboratory science courses provide students with content knowledge as well as experience with the "scientific method," which can be summarized as formulating problem statements and hypothesizing; designing and conducting experiments; observing and collecting data; analyzing and reasoning; and evaluating and concluding. For students pursuing the field of computer engineering the scientific method provides a baseline methodology for much of the discipline; it also provides a process of abstraction that is vital to developing a framework for logical thought. Learning activities and laboratory assignments found in specific computer engineering courses should be designed to incorporate and reinforce this framework. Specific science coursework should include the discipline of physics, which provides the foundation and concepts that underlie the electrical engineering content reflected in the body of knowledge in this report. Additional natural science courses, such as chemistry and biology, can provide important content for distinct specializations within computer engineering; such considerations will vary by institution based on program design and resources. 041b061a72


About

Welcome to the group! You can connect with other members, ge...

Members

Group Page: Groups_SingleGroup
bottom of page