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| computer science research topics for undergraduates: Thesis Projects Mikael Berndtsson, Jörgen Hansson, B. Olsson, Björn Lundell, 2007-10-25 You’re a computing or information student with a huge mountain to climb – that final-year research project. Don’t worry, because with this book guardian angels are at hand, in the form of four brilliant academics who will guide you through the process. The book provides you with all the tools necessary to successfully complete a final year research project. Based on an approach that has been tried and tested on over 500 projects, it offers a simple step-by-step guide to the key processes involved. Not only that, but the book also contains lots of useful information for supervisors and examiners including guidelines on how to review a final year project. |
| computer science research topics for undergraduates: Concise Computer Vision Reinhard Klette, 2014-01-04 This textbook provides an accessible general introduction to the essential topics in computer vision. Classroom-tested programming exercises and review questions are also supplied at the end of each chapter. Features: provides an introduction to the basic notation and mathematical concepts for describing an image and the key concepts for mapping an image into an image; explains the topologic and geometric basics for analysing image regions and distributions of image values and discusses identifying patterns in an image; introduces optic flow for representing dense motion and various topics in sparse motion analysis; describes special approaches for image binarization and segmentation of still images or video frames; examines the basic components of a computer vision system; reviews different techniques for vision-based 3D shape reconstruction; includes a discussion of stereo matchers and the phase-congruency model for image features; presents an introduction into classification and learning. |
| computer science research topics for undergraduates: Assessing and Responding to the Growth of Computer Science Undergraduate Enrollments National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Policy and Global Affairs, Board on Higher Education and Workforce, Committee on the Growth of Computer Science Undergraduate Enrollments, 2018-04-28 The field of computer science (CS) is currently experiencing a surge in undergraduate degree production and course enrollments, which is straining program resources at many institutions and causing concern among faculty and administrators about how best to respond to the rapidly growing demand. There is also significant interest about what this growth will mean for the future of CS programs, the role of computer science in academic institutions, the field as a whole, and U.S. society more broadly. Assessing and Responding to the Growth of Computer Science Undergraduate Enrollments seeks to provide a better understanding of the current trends in computing enrollments in the context of past trends. It examines drivers of the current enrollment surge, relationships between the surge and current and potential gains in diversity in the field, and the potential impacts of responses to the increased demand for computing in higher education, and it considers the likely effects of those responses on students, faculty, and institutions. This report provides recommendations for what institutions of higher education, government agencies, and the private sector can do to respond to the surge and plan for a strong and sustainable future for the field of CS in general, the health of the institutions of higher education, and the prosperity of the nation. |
| computer science research topics for undergraduates: Digital Biology Peter J. Bentley, 2010-05-11 Imagine a future world where computers can create universes -- digital environments made from binary ones and zeros. Imagine that within these universes there exist biological forms that reproduce, grow, and think. Imagine plantlike forms, ant colonies, immune systems, and brains, all adapting, evolving, and getting better at solving problems. Imagine if our computers became greenhouses for a new kind of nature. Just think what digital biology could do for us. Perhaps it could evolve new designs for us, think up ways to detect fraud using digital neurons, or solve scheduling problems with ants. Perhaps it could detect hackers with immune systems or create music from the patterns of growth of digital seashells. Perhaps it would allow our computers to become creative and inventive. Now stop imagining. digital biology is an intriguing glimpse into the future of technology by one of the most creative thinkers working in computer science today. As Peter J. Bentley explains, the next giant step in computing technology is already under way as computer scientists attempt to create digital universes that replicate the natural world. Within these digital universes, we will evolve solutions to problems, construct digital brains that can learn and think, and use immune systems to trap and destroy computer viruses. The biological world is the model for the next generation of computer software. By adapting the principles of biology, computer scientists will make it possible for computers to function as the natural world does. In practical terms, this will mean that we will soon have smart devices, such as houses that will keep the temperature as we like it and automobiles that will start only for drivers they recognize (through voice recognition or other systems) and that will navigate highways safely and with maximum fuel efficiency. Computers will soon be powerful enough and small enough that they can become part of clothing. Digital agents will be able to help us find a bank or restaurant in a city that we have never visited before, even as we walk through the airport. Miniature robots may even be incorporated into our bodies to monitor our health. Digital Biology is also an exploration of biology itself from a new perspective. We must understand how nature works in its most intimate detail before we can use these same biological processes inside our computers. Already scientists engaged in this work have gained new insights into the elegant simplicity of the natural universe. This is a visionary book, written in accessible, nontechnical language, that explains how cutting-edge computer science will shape our world in the coming decades. |
| computer science research topics for undergraduates: Planning and Implementing your Final Year Project — with Success! Mikael Berndtsson, Jörgen Hansson, B. Olsson, Björn Lundell, 2013-03-09 Written in concise language this book is for any student who is about to undertake a final year undergraduate or MSc project. It takes them step-by-step through all the important stages of the process, from initial planning to completion. It tells them everything they need to know about key issues such as: How to formulate a suitable problem, Which research method to use, Developing an appropriate structure for the written report, Project focus, and Quality assurance. The book aims to demystify the whole process, making it invaluable for any MSc student. |
| computer science research topics for undergraduates: Advances in Computer Science, Environment, Ecoinformatics, and Education, Part III Sally Lin, Xiong Huang, 2011-08-20 This 5-volume set (CCIS 214-CCIS 218) constitutes the refereed proceedings of the International Conference on Computer Science, Environment, Ecoinformatics, and Education, CSEE 2011, held in Wuhan, China, in July 2011. The 525 revised full papers presented in the five volumes were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on information security, intelligent information, neural networks, digital library, algorithms, automation, artificial intelligence, bioinformatics, computer networks, computational system, computer vision, computer modelling and simulation, control, databases, data mining, e-learning, e-commerce, e-business, image processing, information systems, knowledge management and knowledge discovering, mulitimedia and its apllication, management and information system, moblie computing, natural computing and computational intelligence, open and innovative education, pattern recognition, parallel and computing, robotics, wireless network, web application, other topics connecting with computer, environment and ecoinformatics, modeling and simulation, environment restoration, environment and energy, information and its influence on environment, computer and ecoinformatics, biotechnology and biofuel, as well as biosensors and bioreactor. |
| computer science research topics for undergraduates: Computer Science Education Research Sally Fincher, Marian Petre, 2004-01-01 This book provides an overview of how to approach computer science education research from a pragmatic perspective. It represents the diversity of traditions and approaches inherent in this interdisciplinary area, while also providing a structure within which to make sense of that diversity. It provides multiple 'entry points'- to literature, to methods, to topics Part One, 'The Field and the Endeavor', frames the nature and conduct of research in computer science education. Part Two, 'Perspectives and Approaches', provides a number of grounded chapters on particular topics or themes, written by experts in each domain. These chapters cover the following topics: * design * novice misconceptions * programming environments for novices * algorithm visualisation * a schema theory view on learning to program * critical theory as a theoretical approach to computer science education research Juxtaposed and taken together, these chapters indicate just how varied the perspectives and research approaches can be. These chapters, too, act as entry points, with illustrations drawn from published work. |
| computer science research topics for undergraduates: Writing for Computer Science Justin Zobel, 2004-06-03 A complete update to a classic, respected resource Invaluable reference, supplying a comprehensive overview on how to undertake and present research |
| computer science research topics for undergraduates: Pure Mathematics Anthony Nicolaides, 1995 |
| computer science research topics for undergraduates: Adventures Between Lower Bounds and Higher Altitudes Hans-Joachim Böckenhauer, Dennis Komm, Walter Unger, 2018-09-04 This Festschrift volume is published in honor of Juraj Hromkovič on the occasion of his 60th birthday. Juraj Hromkovič is a leading expert in the areas of automata and complexity theory, algorithms for hard problems, and computer science education. The contributions in this volume reflect the breadth and impact of his work. The volume contains 35 full papers related to Juraj Hromkovič’s research. They deal with various aspects of the complexity of finite automata, the information content of online problems, stability of approximation algorithms, reoptimization algorithms, computer science education, and many other topics within the fields of algorithmics and complexity theory. Moreover, the volume contains a prologue and an epilogue of laudatios from several collaborators, colleagues, and friends. |
| computer science research topics for undergraduates: Introduction to Artificial Intelligence Wolfgang Ertel, 2018-01-18 This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully revised and updated, this much-anticipated second edition also includes new material on deep learning. Topics and features: presents an application-focused and hands-on approach to learning, with supplementary teaching resources provided at an associated website; contains numerous study exercises and solutions, highlighted examples, definitions, theorems, and illustrative cartoons; includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning; reports on developments in deep learning, including applications of neural networks to generate creative content such as text, music and art (NEW); examines performance evaluation of clustering algorithms, and presents two practical examples explaining Bayes’ theorem and its relevance in everyday life (NEW); discusses search algorithms, analyzing the cycle check, explaining route planning for car navigation systems, and introducing Monte Carlo Tree Search (NEW); includes a section in the introduction on AI and society, discussing the implications of AI on topics such as employment and transportation (NEW). Ideal for foundation courses or modules on AI, this easy-to-read textbook offers an excellent overview of the field for students of computer science and other technical disciplines, requiring no more than a high-school level of knowledge of mathematics to understand the material. |
| computer science research topics for undergraduates: Guide to Scientific Computing in C++ Joe Pitt-Francis, Jonathan Whiteley, 2012-02-15 This easy-to-read textbook/reference presents an essential guide to object-oriented C++ programming for scientific computing. With a practical focus on learning by example, the theory is supported by numerous exercises. Features: provides a specific focus on the application of C++ to scientific computing, including parallel computing using MPI; stresses the importance of a clear programming style to minimize the introduction of errors into code; presents a practical introduction to procedural programming in C++, covering variables, flow of control, input and output, pointers, functions, and reference variables; exhibits the efficacy of classes, highlighting the main features of object-orientation; examines more advanced C++ features, such as templates and exceptions; supplies useful tips and examples throughout the text, together with chapter-ending exercises, and code available to download from Springer. |
| computer science research topics for undergraduates: Introduction to Software Process Improvement Gerard O'Regan, 2010-12-16 This textbook is a systematic guide to the steps in setting up a Capability Maturity Model Integration (CMMI) improvement initiative. Readers will learn the project management practices necessary to deliver high-quality software solutions to the customer on time and on budget. The text also highlights how software process improvement can achieve specific business goals to provide a tangible return on investment. Topics and features: supplies review questions, summaries and key topics for each chapter, as well as a glossary of acronyms; describes the CMMI model thoroughly, detailing the five maturity levels; provides a broad overview of software engineering; reviews the activities and teams required to set up a CMMI improvement initiative; examines in detail the implementation of CMMI in a typical organization at each of the maturity levels; investigates the various tools that support organizations in improving their software engineering maturity; discusses the SCAMPI appraisal methodology. |
| computer science research topics for undergraduates: Special Topics in Information Technology Barbara Pernici, 2019-10-01 This open access book presents nine outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Controls, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the nine best theses defended in 2018-19 and selected for the IT PhD Award. Each of the nine authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists. |
| computer science research topics for undergraduates: , |
| computer science research topics for undergraduates: Digital Image Warping George Wolberg, 1990-08-10 This best-selling, original text focuses on image reconstruction, real-time texture mapping, separable algorithms, two-pass transforms, mesh warping, and special effects. The text, containing all original material, begins with the history of the field and continues with a review of common terminology, mathematical preliminaries, and digital image acquisition. Later chapters discuss equations for spatial information, interpolation kernels, filtering problems, and fast-warping techniques based on scanline algorithms. |
| computer science research topics for undergraduates: Deep Learning for Coders with fastai and PyTorch Jeremy Howard, Sylvain Gugger, 2020-06-29 Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala |
| computer science research topics for undergraduates: Thesis Projects Mikael Berndtsson, Jörgen Hansson, B. Olsson, Björn Lundell, 2007-10-30 You’re a computing or information student with a huge mountain to climb – that final-year research project. Don’t worry, because with this book guardian angels are at hand, in the form of four brilliant academics who will guide you through the process. The book provides you with all the tools necessary to successfully complete a final year research project. Based on an approach that has been tried and tested on over 500 projects, it offers a simple step-by-step guide to the key processes involved. Not only that, but the book also contains lots of useful information for supervisors and examiners including guidelines on how to review a final year project. |
| computer science research topics for undergraduates: Special Secondary Schools For The Mathematically Talented: An International Panorama Bruce R Vogeli, 2015-08-28 A review of 100 special schools for the mathematically talented students in twenty nations. Appendices contain sample syllabi, tests and documents. |
| computer science research topics for undergraduates: Computational Complexity Sanjeev Arora, Boaz Barak, 2009-04-20 New and classical results in computational complexity, including interactive proofs, PCP, derandomization, and quantum computation. Ideal for graduate students. |
| computer science research topics for undergraduates: Science: Image In Action - Proceedings Of The 7th International Workshop On Data Analysis In Astronomy "Livio Scarsi And Vito Digesu" Bertrand Zavidovique, Giosue Lo Bosco, 2011-12-08 The book gathers articles that were exposed during the seventh edition of the Workshop “Data Analysis in Astronomy”. It illustrates a current trend to search for common expressions or models transcending usual disciplines, possibly associated with some lack in the Mathematics required to model complex systems. In that, data analysis would be at the epicentre and a key facilitator of some current integrative phase of Science.It is all devoted to the question of “representation in Science”, whence its name, IMAGe IN AcTION, and main thrustsSuch a classification makes concepts as “complexity” or “dynamics” appear like transverse notions: a measure among others or a dimensional feature among others.Part A broadly discusses a dialogue between experiments and information, be information extracted-from or brought-to experiments. The concept is fundamental in statistics and tailors to the emergence of collective behaviours. Communication then asks for uncertainty considerations — noise, indeterminacy or approximation — and its wider impact on the couple perception-action. Clustering being all about uncertainty handling, data set representation appears not to be the only solution: Introducing hierarchies with adapted metrics, a priori pre-improving the data resolution are other methods in need of evaluation. The technology together with increasing semantics enables to involve synthetic data as simulation results for the multiplication of sources.Part B plays with another couple important for complex systems: state vs. transition. State-first descriptions would characterize physics, while transition-first would fit biology. That could stem from life producing dynamical systems in essence. Uncertainty joining causality here, geometry can bring answers: stable patterns in the state space involve constraints from some dynamics consistency. Stable patterns of activity characterize biological systems too. In the living world, the complexity — i.e. a global measure on both states and transitions — increases with consciousness: this might be a principle of evolution. Beside geometry or measures, operators and topology have supporters for reporting on dynamical systems. Eventually targeting universality, the category theory of topological thermodynamics is proposed as a foundation of dynamical system understanding.Part C details examples of actual data-system relations in regards to explicit applications and experiments. It shows how pure computer display and animation techniques link models and representations to “reality” in some “concrete” virtual, manner. Such techniques are inspired from artificial life, with no connection to physical, biological or physiological phenomena! The Virtual Observatory is the second illustration of the evidence that simulation helps Science not only in giving access to more flexible parameter variability, but also due to the associated data and method storing-capabilities. It fosters interoperability, statistics on bulky corpuses, efficient data mining possibly through the web etc. in short a reuse of resources in general, including novel ideas and competencies. Other examples deal more classically with inverse modelling and reconstruction, involving Bayesian techniques or chaos but also fractal and symmetry. |
| computer science research topics for undergraduates: Artificial Intelligence with Python Prateek Joshi, 2017-01-27 Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application. |
| computer science research topics for undergraduates: Past, Present and Future of Computing Education Research Mikko Apiola, Sonsoles López-Pernas, Mohammed Saqr, 2023-04-17 This book presents a collection of meta-studies, reviews, and scientometric analyses that together reveal a fresh picture about the past, present, and future of computing education research (CER) as a field of science. The book begins with three chapters that discuss and summarise meta-research about the foundations of CER, its disciplinary identity, and use of research methodologies and theories. Based on this, the book proceeds with several scientometric analyses, which explore authors and their collaboration networks, dissemination practices, international collaboration, and shifts in research focus over the years. Analyses of dissemination are deepened in two chapters that focus on some of the most influential publication venues of CER. The book also contains a series of country-, or region-level analyses, including chapters that focus on the evolution of CER in the Baltic Region, Finland, Australasia, Israel, and in the UK & Ireland. Two chapters present case studies of influential CER initiatives in Sweden and Namibia. This book also includes chapters that focus on CER conducted at school level, and cover crucially important issues such as technology ethics, algorithmic bias, and their implications for CER.In all, this book contributes to building an understanding of the past, present and future of CER. This book also contributes new practical guidelines, highlights topical areas of research, shows who to connect with, where to publish, and gives ideas of innovative research niches. The book takes a unique methodological approach by presenting a combination of meta-studies, scientometric analyses of publication metadata, and large-scale studies about the evolution of CER in different geographical regions. This book is intended for educational practitioners, researchers, students, and anyone interested in CER. This book was written in collaboration with some of the leading experts of the field. |
| computer science research topics for undergraduates: The Cambridge Handbook of Computing Education Research Sally A. Fincher, Anthony V. Robins, 2019-02-13 This is an authoritative introduction to Computing Education research written by over 50 leading researchers from academia and the industry. |
| computer science research topics for undergraduates: Basic Graph Theory Md. Saidur Rahman, 2017-05-02 This undergraduate textbook provides an introduction to graph theory, which has numerous applications in modeling problems in science and technology, and has become a vital component to computer science, computer science and engineering, and mathematics curricula of universities all over the world. The author follows a methodical and easy to understand approach. Beginning with the historical background, motivation and applications of graph theory, the author first explains basic graph theoretic terminologies. From this firm foundation, the author goes on to present paths, cycles, connectivity, trees, matchings, coverings, planar graphs, graph coloring and digraphs as well as some special classes of graphs together with some research topics for advanced study. Filled with exercises and illustrations, Basic Graph Theory is a valuable resource for any undergraduate student to understand and gain confidence in graph theory and its applications to scientific research, algorithms and problem solving. |
| computer science research topics for undergraduates: Analytic Combinatorics Philippe Flajolet, Robert Sedgewick, 2009-01-15 Analytic combinatorics aims to enable precise quantitative predictions of the properties of large combinatorial structures. The theory has emerged over recent decades as essential both for the analysis of algorithms and for the study of scientific models in many disciplines, including probability theory, statistical physics, computational biology, and information theory. With a careful combination of symbolic enumeration methods and complex analysis, drawing heavily on generating functions, results of sweeping generality emerge that can be applied in particular to fundamental structures such as permutations, sequences, strings, walks, paths, trees, graphs and maps. This account is the definitive treatment of the topic. The authors give full coverage of the underlying mathematics and a thorough treatment of both classical and modern applications of the theory. The text is complemented with exercises, examples, appendices and notes to aid understanding. The book can be used for an advanced undergraduate or a graduate course, or for self-study. |
| computer science research topics for undergraduates: Law and Economics of Regulation Klaus Mathis, Avishalom Tor, 2021-04-24 This book explores current issues regarding the regulation of various economic sectors, theoretically and empirically, discussing both neoclassical and behavioural economics approaches to regulation. Regulation has become one of the main determinants of modern economies, and virtually every sector is subject to general laws and regulations as well as specific rules and standards. A traditional argument to justify regulatory interventions is the promotion of public interests. Fixing markets that lack competition, balancing information asymmetries, internalising externalities, mitigating systemic risks, and protecting consumers from irrational behaviour are frequently invoked to complement the invisible hand of the market with the visible hand of the state.However, regulations can lead to unintended consequences, and serve the interests of powerful private interest groups rather than the public interest and social welfare. In addition, new insights from behavioural economics question the traditional regulatory approaches, most prominently in attitudes towards consumers. Furthermore, digitalisation and technological innovation in general present new challenges in terms of both the type of regulation and the regulatory process.Part I of this book discusses various theoretical approaches to the economic analysis of regulations, while Part II looks at specific applications of the law and economics of regulation. |
| computer science research topics for undergraduates: Writing Computer and Information History William Aspray, 2024-05-14 This is not a book about the history of computing or the history of information. Instead, it is a meta-historical book about the research and writing of these types of history. The formal presentation of historical research in the form of a publication often hides the process by which the topic was selected, boundaries were drawn, evidence was selected, analytic approach was chosen and applied, results were presented, how this work fits into a larger body of scholarship, the implicit goals and biases of the author, and many other similar issues. This process of learning about the various ways to carry out computer history or information history can be enriched by this collection of reflective essays by experienced scholars, discussing the craft that they practice. This is a book that concerns both computer history and information history. The first scholarship in computer history by professionally trained scholars began to appear in the 1970s, so we are approaching a half century of research and publication in this area. The field has generated numerous pieces of exemplary scholarship from various perspectives such as intellectual history of individual technologies, business histories of firms, economic histories of market sectors, externalist histories of funding and professionalization, and so on. However, the field continues to evolve, especially as computing and communication technologies have drawn together in the form of the Internet and social media; and with them a new set of scholars is participating, drawn not only from the history of science and technology, but also from the communication and media studies fields. Powerful theories, approaches, and frameworks are being increasingly drawn more widely from both the humanities and the social sciences to inform the practice of computer history. The scholars in this volume look at what’s happened, what’s happening now, and where historical scholarship in these disciplines is headed. |
| computer science research topics for undergraduates: NASA Aeronautics , 1992 |
| computer science research topics for undergraduates: Computer Science National Research Council, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Committee on the Fundamentals of Computer Science: Challenges and Opportunities, 2004-10-06 Computer Science: Reflections on the Field, Reflections from the Field provides a concise characterization of key ideas that lie at the core of computer science (CS) research. The book offers a description of CS research recognizing the richness and diversity of the field. It brings together two dozen essays on diverse aspects of CS research, their motivation and results. By describing in accessible form computer science's intellectual character, and by conveying a sense of its vibrancy through a set of examples, the book aims to prepare readers for what the future might hold and help to inspire CS researchers in its creation. |
| computer science research topics for undergraduates: Coding All-in-One For Dummies Chris Minnick, 2022-08-02 The go-to guide for learning coding from the ground-up Adding some coding know-how to your skills can help launch a new career or bolster an old one. Coding All-in-One For Dummies offers an ideal starting place for learning the languages that make technology go. This edition gets you started with a helpful explanation of how coding works and how it’s applied in the real-world before setting you on a path toward writing code for web building, mobile application development, and data analysis. Add coding to your skillset for your existing career, or begin the exciting transition into life as a professional developer—Dummies makes it easy. Learn coding basics and how to apply them Analyze data and automate routine tasks on the job Get the foundation you need to launch a career as a coder Add HTML, JavaScript, and Python know-how to your resume This book serves up insight on the basics of coding, designed to be easy to follow, even if you’ve never written a line of code in your life. You can do this. |
| computer science research topics for undergraduates: Biotechnology for Waste Management and Site Restoration C. Ronneau, O. Bitchaeva, 2012-12-06 Biotechnology for Waste Management and Site Restoration covers: waste management - solid, gaseous, liquid; site restoration - radioactivity, organics, toxic metals; educational, economic, social and business aspects; and international collaboration. International collaboration is growing apace and many concrete projects have been started. The body of knowledge is growing. Over the long term, it is envisaged that this international collaboration will result in a long-term scientific and technological strategy, new technologies and alternative solutions, and practical implementations of biotechnology for the nuclear and industrial sectors of the economy. |
| computer science research topics for undergraduates: How to Mentor Undergraduate Researchers Louise Temple, Thomas Q. Sibley, Amy J. Orr, 2019-06-01 How to Mentor Undergraduate Researchers is written for faculty members and other researchers who mentor undergraduates. It provides a concise description of the mentoring process, including the opportunities and rewards for both students and mentors of the mentoring experience. |
| computer science research topics for undergraduates: Ictacs 2006 - Proceedings Of The First International Conference On Theories And Applications Of Computer Science 2006 Duong Anh Duc, Thuy Thi Bich Dong, Tu-bao Ho, Dinh Thuc Nguyen, 2006-12-29 This volume brings together many contributions from leading research scientists, engineers and practitioners in computer science. Selected by program committee members, the topics describe innovative research and new technologies in the following areas of interest: image processing, computer vision and pattern recognition; computational linguistics and natural language processing; artificial intelligence, machine learning and algorithms; software engineering; computer networks and security; and bioinformatics. |
| computer science research topics for undergraduates: Undergraduate Announcement University of Michigan--Dearborn, 1987 |
| computer science research topics for undergraduates: NASA Technical Memorandum , 1984 |
| computer science research topics for undergraduates: Advances in Intelligent Systems and Computing V Natalya Shakhovska, Mykola O. Medykovskyy, 2020-12-22 This book reports on new theories and applications in the field of intelligent systems and computing. It covers cutting-edge computational and artificial intelligence methods, advances in computer vision, big data, cloud computing, and computation linguistics, as well as cyber-physical and intelligent information management systems. The respective chapters are based on selected papers presented at the workshop on intelligent systems and computing, held during the International Conference on Computer Science and Information Technologies, CSIT 2020, which was jointly organized on September 23-26, 2020, by the Lviv Polytechnic National University, Ukraine, the Kharkiv National University of Radio Electronics, Ukraine, and the Technical University of Lodz, Poland, under patronage of Ministry of Education and Science of Ukraine. Given its breadth of coverage, the book provides academics and professionals with extensive information and a timely snapshot of the field of intelligent systems, and is sure to foster new discussions and collaborations among different groups. |
| computer science research topics for undergraduates: A Summary of Research 1995 United States. Naval Postgraduate School, Monterey, CA., 1995 |
| computer science research topics for undergraduates: High Performance Computing and Communications Federal Coordinating Council for Science, Engineering, and Technology. Committee on Physical, Mathematical, and Engineering Sciences, 1994 |
| computer science research topics for undergraduates: Sustaining University Program Research United States. National Aeronautics and Space Administration, |
Research Methods in Computer Science - University of Liverpool
Research can be classified from three different perspectives: 1 Field Position of the research within a hierarchy of topics Example: Artificial Intelligence →Automated Reasoning → First …
Research Topics in Human-Computer Interaction - Stanford …
Most important: are you prepared to complete a mini-research project of your own choosing? Reading: come prepared! This paper was fascinating because it forces us to consider …
171+ Best Research Paper Topics For Computer Science In 2025
Why Choose the Right Research Paper Topic in Computer Science? Cho o s i ng the r i ght r e s e ar c h pape r to pi c i s c r uc i al f o r s e ve r al r e as o ns .
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The topics are organized into four areas of architecture, programming, algorithms, and cross-cutting and advanced topics. Additional elective topics are expected.
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computer science concepts, techniques, and tools that is key for their future studies and careers. Second is to help them develop appreciation, interest, and necessary skills to conduct …
COMPUTER SCIENCE - catalogs.northwestern.edu
The computer science requirements include the following five parts. Undergraduates are encouraged to participate in research projects and to take advanced courses.
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UDC's Bachelor of Science in Computer Science program prepares nationally and internationally competitive graduates to meet the needs of the current and future
Research Methods in computer science - UH
Research comprises "creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of humans, culture and society, and the use of this …
Combined Research and Curriculum Development in Machine …
provides research-oriented, team-taught course offerings that span multiple topics. This approach exposes undergraduate students to a wider breadth of research experiences.
Undergraduate Topics in Computer Science - Springer
Undergraduate Topics in Computer Science (UTiCS) delivers high-quality instruc- tional content for undergraduates studying in all areas of computing and information science.
Research Methods in Computer Science - University of Liverpool
What is the right hypothesis in a particular situation? What is the right experiment to conduct? A has been observed. The phenomenon X is observed. Hence, there is a reason to assume that …
Teaching Parallel and Distributed Computing topics for the ...
Dec 18, 2006 · To achieve these goals, we propose a set of modules which includes basic and advanced high performance computing, parallel and distributed systems programming topics, …
COMPUTER SCIENCE • 31 - ce.ucsb.edu
ct-oriented comput-ing. Topics include encapsulation, data hiding, inheritance, polymorphism, compilation, linking and loading, memory management, and debugging; recent advances in …
NSF/IEEE-TCPP Curriculum Initiative on Parallel and …
This curriculum guideline includes a core set of PDC topics that a student graduating with a Bachelor’s degree in CS or CE would be well-served to have covered through required courses …
Undergraduate Topics in Computer Science - Springer
Undergraduate Topics in Computer Science foundational and theoretical material to final-year topics and applications, UTiCS books take a fresh, concise, and modern approach and are …
Special Topics in Computer Science: Usability of Programming …
Jan 29, 2020 · In this special course, we will study how to design and evaluate the usability of programming languages. How can we design programming languages that empower …
Research Methods in Computer Science - University of Liverpool
1 to understand research and research methods in Computer Science; 2 to be able to plan, and conduct your own research, taking into account ethical, legal, and professional limitations; and
Undergraduate Topics in Computer Science - Springer
This book is directed to computer science students at the beginning of their studies. It presents the elements of discrete mathematics in a form accessible to them …
Research Methods in Computer Science - University of Liverpool
Research can be classified from three different perspectives: 1 Field Position of the research within a hierarchy of topics Example: Artificial Intelligence …
Research Topics in Human-Computer Interaction - Stanfor…
Most important: are you prepared to complete a mini-research project of your own choosing? Reading: come prepared! This paper was fascinating because it forces us …
171+ Best Research Paper Topics For Computer Science In 2025
Why Choose the Right Research Paper Topic in Computer Science? Cho o s i ng the r i ght r e s e ar c h pape r to pi c i s c r uc i al f o r s e ve r al r e as o ns .
NSF/IEEE-TCPP Curriculum Initiative on Parallel and Distrib…
The topics are organized into four areas of architecture, programming, algorithms, and cross-cutting and advanced topics. Additional elective topics are expected.
