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Medical Laboratory Science
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e-book
The traditional approach to teaching Organic Chemistry, taken by most of the textbooks that are currently available, is to focus primarily on the reactions of laboratory synthesis, with much less discussion - in the central chapters, at least - of biological molecules and reactions. This is despite the fact that, in many classrooms, a majority of students are majoring in Biology or Health Sciences rather than in Chemistry, and are presumably taking the course in order to learn about the chemistry that takes place in living things. In an effort to address this disconnect, I have developed a textbook for a two-semester, sophomore-level course in Organic Chemistry in which biological chemistry takes center stage. For the most part, the text covers the core concepts of organic structure, structure determination, and reactivity in the standard order. What is different is the context: biological chemistry is fully integrated into the explanation of central principles, and as much as possible the in-chapter and end-of-chapter problems are taken from the biochemical literature. Many laboratory synthesis reactions are also covered, generally in parallel with their biochemical counterparts - but it is intentionally the biological chemistry that comes first.
- Subjects:
- Chemistry
- Keywords:
- Chemistry Organic Textbooks
- Resource Type:
- e-book
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e-book
The traditional approach to teaching Organic Chemistry, taken by most of the textbooks that are currently available, is to focus primarily on the reactions of laboratory synthesis, with much less discussion - in the central chapters, at least - of biological molecules and reactions. This is despite the fact that, in many classrooms, a majority of students are majoring in Biology or Health Sciences rather than in Chemistry, and are presumably taking the course in order to learn about the chemistry that takes place in living things.In an effort to address this disconnect, I have developed a textbook for a two-semester, sophomore-level course in Organic Chemistry in which biological chemistry takes center stage. For the most part, the text covers the core concepts of organic structure, structure determination, and reactivity in the standard order. What is different is the context: biological chemistry is fully integrated into the explanation of central principles, and as much as possible the in-chapter and end-of-chapter problems are taken from the biochemical literature. Many laboratory synthesis reactions are also covered, generally in parallel with their biochemical counterparts - but it is intentionally the biological chemistry that comes first.
- Subjects:
- Chemistry
- Keywords:
- Chemistry Organic Textbooks
- Resource Type:
- e-book
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e-book
This is a text that covers the standard topics in a sophomore-level course in discrete mathematics: logic, sets, proof techniques, basic number theory, functions, relations, and elementary combinatorics, with an emphasis on motivation. It explains and clarifies the unwritten conventions in mathematics, and guides the students through a detailed discussion on how a proof is revised from its draft to a final polished form. Hands-on exercises help students understand a concept soon after learning it. The text adopts a spiral approach: many topics are revisited multiple times, sometimes from a different perspective or at a higher level of complexity. The goal is to slowly develop students' problem-solving and writing skills.Open SUNY Textbooks is an open access textbook publishing initiative established by State University of New York libraries and supported by SUNY Innovative Instruction Technology Grants. This initiative publishes high-quality, cost-effective course resources by engaging faculty as authors and peer-reviewers, and libraries as publishing service and infrastructure. The pilot launched in 2012, providing an editorial framework and service to authors, students and faculty, and establishing a community of practice among libraries. Participating libraries in the 2012- 2013 pilot include SUNY Geneseo, College at Brockport, College of Environmental Science and Forestry, SUNY Fredonia, Upstate Medical University, and University at Buffalo, with support from other SUNY libraries and SUNY Press. More information can be found at http://textbooks.opensuny.org.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Computer science -- Mathematics Textbooks Mathematics
- Resource Type:
- e-book
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e-book
Digital circuits, often called Integrated Circuits or ICs, are the central building blocks of a Central Processing Unit (CPU). To understand how a computer works, it is essential to understand the digital circuits which make up the CPU. This text introduces the most important of these digital circuits; adders, decoders, multiplexers, D flip-flops, and simple state machines. What makes this textbook unique is that it puts the ability to understand these circuits into the hands of anyone, from hobbyists to students studying Computer Science. This text is designed to teach digital circuits using simple projects the reader can implement. But unlike most lab manuals used in classes in Digital Circuits or Computer Organization classes, this textbook is designed to remove the barrier of a laboratory infrastructure needed in a face-to-face environment at a college or university. This textbook is designed to be used by the reader to create the circuits in their own homes. The textbook is free. The cost of the kits needed to do the labs is reasonable. And the projects are well documented and can be implemented by even novices to electronic projects. This text allows professors to add laboratory projects in digital circuits to students in online classes in Computer Organization. This enhances these classes with interesting and fun exercises that reinforce the classroom topics. This text can also be used by a hobbyist who wants to learn more about digital circuits and how computers work. The material is presented at a level that someone with no experience in digital circuits and electronics can successfully complete the projects, and gain an understanding of the circuits which go into making up a computer.
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Textbooks Digital integrated circuits
- Resource Type:
- e-book
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e-book
We have designed this third edition of Java, Java, Java to be suitable for a typical Introduction to Computer Science (CS1) course or for a slightly more advanced Java as a Second Language course. This edition retains the “objects first” approach to programming and problem solving that was characteristic of the first two editions. Throughout the text we emphasize careful coverage of Java language features, introductory programming concepts, and object-oriented design principles. The third edition retains many of the features of the first two editions, including: Early Introduction of Objects Emphasis on Object Oriented Design (OOD) Unified Modeling Language (UML) Diagrams Self-study Exercises with Answers Programming, Debugging, and Design Tips. From the Java Library Sections Object-Oriented Design Sections End-of-Chapter Exercises Companion Web Site, with Power Points and other Resources The In the Laboratory sections from the first two editions have been moved onto the book's Companion Web Site. Table 1 shows the Table of Contents for the third edition.
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e-book
Elementary Differential Equations with Boundary Value Problems is written for students in science, engineering, and mathematics who have completed calculus through partial differentiation. An elementary text should be written so the student can read it with comprehension without too much pain. I have tried to put myself in the student's place, and have chosen to err on the side of too much detail rather than not enough. An elementary text can't be better than its exercises. This text includes 1695 numbered exercises, many with several parts. They range in difficulty from routine to very challenging. An elementary text should be written in an informal but mathematically accurate way, illustrated by appropriate graphics. I have tried to formulate mathematical concepts succinctly in language that students can understand. I have minimized the number of explicitly stated theorems and definitions, preferring to deal with concepts in a more conversational way, copiously illustrated by 250 completely worked out examples. Where appropriate, concepts and results are depicted in 144 figures. Although I believe that the computer is an immensely valuable tool for learning, doing, and writing mathematics, the selection and treatment of topics in this text reflects my pedagogical orientation along traditional lines. However, I have incorporated what I believe to be the best use of modern technology, so you can select the level of technology that you want to include in your course. The text includes 336 exercises – identified by the symbols C and C/G – that call for graphics or computation and graphics. There are also 73 laboratory exercises – identified by L – that require extensive use of technology. In addition, several sections include informal advice on the use of technology. If you prefer not to emphasize technology, simply ignore these exercises and the advice.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Textbooks Boundary value problems Differential equations Partial
- Resource Type:
- e-book
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MOOC
Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI. This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.
- Course related:
- COMP4434 Big Data Analytics and EIE6207 Theoretical Fundamental and Engineering Approaches for Intelligent Signal and. Information Processing
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Artificial intelligence Machine learning
- Resource Type:
- MOOC
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MOOC
Understanding a city as a whole, its people, components, functions, scales and dynamics, is crucial for the appropriate design and management of the urban system. While the development of cities in different parts of the world is moving in diverse directions, all estimations show that cities worldwide will change and grow strongly in the coming years. Especially in the tropics over the next 3 decades, it is expected that the number of new urban residents will increase by 3 times the population of Europe today. Yet already now, there is an extreme shortage of designers and urban planners able to understand the functioning of a city as a system, and to plan a sustainable and resilient city. To answer questions like: Which methods can contribute to the sustainable performance of a city, and how can we teach this to the next generations, the ETH Future Cities Laboratory in Singapore has produced over the last 3 years many necessary research results. “Future Cities” aims to bring these latest results to the places where they are needed most. The only way to better understand the city is by going beyond the physical appearance and by focusing on different representations, properties and impact factors of the urban system. For that reason, in this course we will explore the city as the most complex human-made “organism” with a metabolism that can be modeled in terms of stocks and flows. We will open a holistic view on existing and new cities, with a focus on Asia. Data-driven approaches for the development of the future city will be studied, based on crowdsourcing and sensing. At first, we will give an overview of the components and dynamics of the future cities, and we will show the importance of information and information architecture for the cities of the future. The course will cover the origins, state-of-the-art and applications of information architecture and simulation. “Future Cities” will provide the basis to understand, shape, plan, design, build, manage and continually adapt a city. You will learn to see the consequences of citizen science and the merging of Architecture and information space. You will be up-to-date on the latest research and development on how to better understand, create and manage the future cities for a more resilient urban world.
- Subjects:
- Building Services Engineering and Building and Real Estate
- Keywords:
- Smart cities Cities towns -- Effect of technological innovations on City planning
- Resource Type:
- MOOC
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Collection
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Video
Medical Laboratory Techniques are demonstrated in a video interactive format. Approximately 20 skills are available in 4-12 minute video segments.
- Subjects:
- Medical Laboratory Science
- Keywords:
- Diagnosis Laboratory Medical laboratories
- Resource Type:
- Video
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