Computing Foundations for the Scientist

There is a need for a new style of supporting a computer course. Although it is widely recognized that computer technology provides essential tools for all current scientific work, few university curricula adequately ground science majors in the fundamentals that underlie this technology. Introducing science students to computational thinking in the areas of algorithms and data structures, data representation and accuracy, abstraction, performance issues, and database concepts can enable future scientists to become intelligent, creative and effective users of this technology. The intent of this course is not to turn scientists into computer scientists, but rather to enhance their ability to exploit computing tools to greatest scientific advantage

Emotion Based Music Player - XBeats

This paper showcases the development of an Android platform based application named XBeats which acts as a Music Player working on Image Processing fundamentals to capture, analyze and present music as per the emotion or mood of the user using this application. The Android application was developed using the Android SDK software and OpenCV software was used to implement facial recognition algorithms and cascades. The unique aspect of this project is that it focuses on facial recognition on the Android platform unlike that on Computer systems which use commonly available softwares for the same. This paper also provides comparison between use of various classification algorithms used for facial detection

A review of k-NN algorithm based on classical and Quantum Machine Learning

[EN] Artificial intelligence algorithms, developed for traditional computing, based on Von Neumann’s architecture, are slow and expen- sive in terms of computational resources. Quantum mechanics has opened up a new world of possibilities within this field, since, thanks to the basic properties of a quantum computer, a great degree of parallelism can be achieved in the execution of the quantum version of machine learning algorithms. In this paper, a study has been carried out on these proper- ties and on the design of their quantum computing versions. More specif- ically, the study has been focused on the quantum version of the k-NN algorithm that allows to understand the fundamentals when transcribing classical machine learning algorithms into its quantum versions

Formal Languages and Compilation

This textbook describes the essential principles and methods used for defining the syntax of artificial languages, and for designing efficient parsing algorithms and syntax-directed translators with semantic attributes. A comprehensive selection of topics is presented within a rigorous, unified framework, illustrated by numerous practical examples. Features and topics: presents a novel conceptual approach to parsing algorithms that applies to extended BNF grammars, together with a parallel parsing algorithm; supplies supplementary teaching tools, including course slides and exercises with solutions, at an associated website; unifies the concepts and notations used in different approaches, enabling an extended coverage of methods with a reduced number of definitions; systematically discusses ambiguous forms, allowing readers to avoid pitfalls when designing grammars; describes all algorithms in pseudocode, so that detailed knowledge of a specific programming language is not necessary; makes extensive usage of theoretical models of automata, transducers and formal grammars; includes concise coverage of algorithms for processing regular expressions and finite automata; and introduces static program analysis based on flow equations. This clearly-written, classroom-tested textbook is an ideal guide to the fundamentals of this field for advanced undergraduate and graduate students in computer science and computer engineering. Some background in programming is required, and readers should also be familiar with basic set theory, algebra and logic

Introducing Java : the case for fundamentals-first

Java has increasingly become the language of choice for teaching introductory programming. In this paper, we examine the different approaches to teaching Java (Objects-first, Fundamentals-first and GUI-first) to ascertain whether there exists an agreed ordering of topics and difficulty levels between nine relatively basic Java topics. The results of our literature survey and student questionnaire suggests that the Fundamentals-first approach may have benefits from the student's point of view and an agreed ordering of the Java topics accompanying this approach has been established

Application-Oriented Flow Control: Fundamentals, Algorithms and Fairness

This paper is concerned with flow control and resource allocation problems in computer networks in which real-time applications may have hard quality of service (QoS) requirements. Recent optimal flow control approaches are unable to deal with these problems since QoS utility functions generally do not satisfy the strict concavity condition in real-time applications. For elastic traffic, we show that bandwidth allocations using the existing optimal flow control strategy can be quite unfair. If we consider different QoS requirements among network users, it may be undesirable to allocate bandwidth simply according to the traditional max-min fairness or proportional fairness. Instead, a network should have the ability to allocate bandwidth resources to various users, addressing their real utility requirements. For these reasons, this paper proposes a new distributed flow control algorithm for multiservice networks, where the application's utility is only assumed to be continuously increasing over the available bandwidth. In this, we show that the algorithm converges, and that at convergence, the utility achieved by each application is well balanced in a proportionally (or max-min) fair manner