70,234 research outputs found

    WhistleRecognition Applied in SearchingMusicDatabase

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    This project aims at constructing an innovative Music Search Engine. The system takes human whistle as input, and return full information ofthe song which user has just whistled. Due to the fact that human being remembers the melody of composition better than the name or lyric, the project purpose is to demonstrate a new searching method which is based on composition melody. There are two main phases in Music Searching Engine: 1) Whistle Recognition: converting whistle to music note and 2) Music Search: finding the similar songs with the user whistle. Music Search Engine mainly bases onthe application of Digital Signal Processing and Dynamic Programming theory. The project was successful in constructing Music Search Engine. For demonstration purpose, author has built an online music search application which is derived from Music Search Engine above. The demonstration purpose is to show the applicability and potentially commercial value ofthe project. This search engine as well as the online application was constructed using JAVA technology

    CAES: A Model of an RBR-CBR Course Advisory Expert System

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    Academic student advising is a gargantuan task that places heavy demand on the time, emotions and mental resources of the academic advisor. It is also a mission critical and very delicate task that must be handled with impeccable expertise and precision else the future of the intended student beneficiary may be jeopardized due to poor advising. One integral aspect of student academic advising is course registration, where students make decisions on the choice of courses to take in specific semesters based on their current academic standing. In this paper, we give the description of the design, implementation and trial evaluation of the Course Advisory Expert System (CAES) which is a hybrid of a rule based reasoning (RBR) and case based reasoning (CBR). The RBR component was implemented using JESS. The result of the trial experiment revealed that the system has high performance/user satisfaction rating from the sample expert population conducted

    Skill Rating by Bayesian Inference

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    Systems Engineering often involves computer modelling the behaviour of proposed systems and their components. Where a component is human, fallibility must be modelled by a stochastic agent. The identification of a model of decision-making over quantifiable options is investigated using the game-domain of Chess. Bayesian methods are used to infer the distribution of players’ skill levels from the moves they play rather than from their competitive results. The approach is used on large sets of games by players across a broad FIDE Elo range, and is in principle applicable to any scenario where high-value decisions are being made under pressure

    Constraint specification by example in a Meta-CASE tool

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    CASE tools are very helpful to software engineers in different ways and in different phases of software development. However, they are not easy to specialise to meet the needs of particular application domains or particular software modelling requirements. Meta-CASE tools offer a way of providing such specialisation by enabling a designer to specify a tool which is then generated automatically. Constraints are often used in such meta-CASE tools as a technique for governing the syntax and semantics of model elements and the values of their attributes. However, although constraint definition is a difficult process it has attracted relatively little research attention. The PhD research described here presents an approach for improving the process of CASE tool constraint specification based on the notion of programming by example (or demonstration). The feasibility of the approach will be demonstrated via experiments with a prototype using the meta-CASE tool Diagram Editor Constraints System (DECS) as context

    The artificial retina processor for track reconstruction at the LHC crossing rate

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    We present results of an R&D study for a specialized processor capable of precisely reconstructing, in pixel detectors, hundreds of charged-particle tracks from high-energy collisions at 40 MHz rate. We apply a highly parallel pattern-recognition algorithm, inspired by studies of the processing of visual images by the brain as it happens in nature, and describe in detail an efficient hardware implementation in high-speed, high-bandwidth FPGA devices. This is the first detailed demonstration of reconstruction of offline-quality tracks at 40 MHz and makes the device suitable for processing Large Hadron Collider events at the full crossing frequency.Comment: 4th draft of WIT proceedings modified according to JINST referee's comments. 10 pages, 6 figures, 2 table
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