856 resultados para Computer aided software engineering


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Determination of sequence similarity is a central issue in computational biology, a problem addressed primarily through BLAST, an alignment based heuristic which has underpinned much of the analysis and annotation of the genomic era. Despite their success, alignment-based approaches scale poorly with increasing data set size, and are not robust under structural sequence rearrangements. Successive waves of innovation in sequencing technologies – so-called Next Generation Sequencing (NGS) approaches – have led to an explosion in data availability, challenging existing methods and motivating novel approaches to sequence representation and similarity scoring, including adaptation of existing methods from other domains such as information retrieval. In this work, we investigate locality-sensitive hashing of sequences through binary document signatures, applying the method to a bacterial protein classification task. Here, the goal is to predict the gene family to which a given query protein belongs. Experiments carried out on a pair of small but biologically realistic datasets (the full protein repertoires of families of Chlamydia and Staphylococcus aureus genomes respectively) show that a measure of similarity obtained by locality sensitive hashing gives highly accurate results while offering a number of avenues which will lead to substantial performance improvements over BLAST..

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Network Real-Time Kinematic (NRTK) is a technology that can provide centimeter-level accuracy positioning services in real time, and it is enabled by a network of Continuously Operating Reference Stations (CORS). The location-oriented CORS placement problem is an important problem in the design of a NRTK as it will directly affect not only the installation and operational cost of the NRTK, but also the quality of positioning services provided by the NRTK. This paper presents a Memetic Algorithm (MA) for the location-oriented CORS placement problem, which hybridizes the powerful explorative search capacity of a genetic algorithm and the efficient and effective exploitative search capacity of a local optimization. Experimental results have shown that the MA has better performance than existing approaches. In this paper we also conduct an empirical study about the scalability of the MA, effectiveness of the hybridization technique and selection of crossover operator in the MA.

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This paper describes a design framework intended to conceptually map the influence that game design has on the creative activity people engage in during gameplay. The framework builds on behavioral and verbal analysis of people playing puzzle games. The analysis was designed to better understand the extent to which gameplay activities within different games facilitate creative problem solving. We have used an expert review process to evaluate these games in terms of their game design elements and have taken a cognitive action approach to this process to investigate how particular elements produce the potential for creative activity. This paper proposes guidelines that build upon our understanding of the relationship between the creative processes that players undertake during a game and the components of the game that allow these processes to occur. These guidelines may be used in the game design process to better facilitate creative gameplay activity.

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Distributed computation and storage have been widely used for processing of big data sets. For many big data problems, with the size of data growing rapidly, the distribution of computing tasks and related data can affect the performance of the computing system greatly. In this paper, a distributed computing framework is presented for high performance computing of All-to-All Comparison Problems. A data distribution strategy is embedded in the framework for reduced storage space and balanced computing load. Experiments are conducted to demonstrate the effectiveness of the developed approach. They have shown that about 88% of the ideal performance capacity have be achieved in multiple machines through using the approach presented in this paper.

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We used our TopSig open-source indexing and retrieval tool to produce runs for the ShARe/CLEF eHealth 2013 track. TopSig was used to produce runs using the query fields and provided discharge summaries, where appropriate. Although the improvement was not great TopSig was able to gain some benefit from utilising the discharge summaries, although the software needed to be modified to support this. This was part of a larger experiment involving determining the applicability and limits to signature-based approaches.

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Engineers must have deep and accurate conceptual understanding of their field and Concept inventories (CIs) are one method of assessing conceptual understanding and providing formative feedback. Current CI tests use Multiple Choice Questions (MCQ) to identify misconceptions and have undergone reliability and validity testing to assess conceptual understanding. However, they do not readily provide the diagnostic information about students’ reasoning and therefore do not effectively point to specific actions that can be taken to improve student learning. We piloted the textual component of our diagnostic CI on electrical engineering students using items from the signals and systems CI. We then analysed the textual responses using automated lexical analysis software to test the effectiveness of these types of software and interviewed the students regarding their experience using the textual component. Results from the automated text analysis revealed that students held both incorrect and correct ideas for certain conceptual areas and provided indications of student misconceptions. User feedback also revealed that the inclusion of the textual component is helpful to students in assessing and reflecting on their own understanding.

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Background: A major challenge for assessing students’ conceptual understanding of STEM subjects is the capacity of assessment tools to reliably and robustly evaluate student thinking and reasoning. Multiple-choice tests are typically used to assess student learning and are designed to include distractors that can indicate students’ incomplete understanding of a topic or concept based on which distractor the student selects. However, these tests fail to provide the critical information uncovering the how and why of students’ reasoning for their multiple-choice selections. Open-ended or structured response questions are one method for capturing higher level thinking, but are often costly in terms of time and attention to properly assess student responses. Purpose: The goal of this study is to evaluate methods for automatically assessing open-ended responses, e.g. students’ written explanations and reasoning for multiple-choice selections. Design/Method: We incorporated an open response component for an online signals and systems multiple-choice test to capture written explanations of students’ selections. The effectiveness of an automated approach for identifying and assessing student conceptual understanding was evaluated by comparing results of lexical analysis software packages (Leximancer and NVivo) to expert human analysis of student responses. In order to understand and delineate the process for effectively analysing text provided by students, the researchers evaluated strengths and weakness for both the human and automated approaches. Results: Human and automated analyses revealed both correct and incorrect associations for certain conceptual areas. For some questions, that were not anticipated or included in the distractor selections, showing how multiple-choice questions alone fail to capture the comprehensive picture of student understanding. The comparison of textual analysis methods revealed the capability of automated lexical analysis software to assist in the identification of concepts and their relationships for large textual data sets. We also identified several challenges to using automated analysis as well as the manual and computer-assisted analysis. Conclusions: This study highlighted the usefulness incorporating and analysing students’ reasoning or explanations in understanding how students think about certain conceptual ideas. The ultimate value of automating the evaluation of written explanations is that it can be applied more frequently and at various stages of instruction to formatively evaluate conceptual understanding and engage students in reflective

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Collections of biological specimens are fundamental to scientific understanding and characterization of natural diversity - past, present and future. This paper presents a system for liberating useful information from physical collections by bringing specimens into the digital domain so they can be more readily shared, analyzed, annotated and compared. It focuses on insects and is strongly motivated by the desire to accelerate and augment current practices in insect taxonomy which predominantly use text, 2D diagrams and images to describe and characterize species. While these traditional kinds of descriptions are informative and useful, they cannot cover insect specimens "from all angles" and precious specimens are still exchanged between researchers and collections for this reason. Furthermore, insects can be complex in structure and pose many challenges to computer vision systems. We present a new prototype for a practical, cost-effective system of off-the-shelf components to acquire natural-colour 3D models of insects from around 3 mm to 30 mm in length. ("Natural-colour" is used to contrast with "false-colour", i.e., colour generated from, or applied to, gray-scale data post-acquisition.) Colour images are captured from different angles and focal depths using a digital single lens reflex (DSLR) camera rig and two-axis turntable. These 2D images are processed into 3D reconstructions using software based on a visual hull algorithm. The resulting models are compact (around 10 megabytes), afford excellent optical resolution, and can be readily embedded into documents and web pages, as well as viewed on mobile devices. The system is portable, safe, relatively affordable, and complements the sort of volumetric data that can be acquired by computed tomography. This system provides a new way to augment the description and documentation of insect species holotypes, reducing the need to handle or ship specimens. It opens up new opportunities to collect data for research, education, art, entertainment, biodiversity assessment and biosecurity control. © 2014 Nguyen et al.

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Energy efficient embedded computing enables new application scenarios in mobile devices like software-defined radio and video processing. The hierarchical multiprocessor considered in this work may contain dozens or hundreds of resource efficient VLIW CPUs. Programming this number of CPU cores is a complex task requiring compiler support. The stream programming paradigm provides beneficial properties that help to support automatic partitioning. This work describes a compiler for streaming applications targeting the self-build hierarchical CoreVA-MPSoC multiprocessor platform. The compiler is supported by a programming model that is tailored to fit the streaming programming paradigm. We present a novel simulated-annealing (SA) based partitioning algorithm, called Smart SA. The overall speedup of Smart SA is 12.84 for an MPSoC with 16 CPU cores compared to a single CPU implementation. Comparison with a state of the art partitioning algorithm shows an average performance improvement of 34.07%.

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The heavy haul rail network in Queensland Australia generally adopts a lightning impulse withstand voltage rating of 250 kV for the switchgear and autotransformers within its 50 kV ac traction feeder stations. The aging switchgear across a number of feeder stations in this network are undergoing upgrade and the rail network operator is considering the possibility of using 200 kV rating for the upgraded switchgear. This paper investigates the lightning over-voltages that could occur at the feeder stations under review. Fast front transient models of the feeder stations and the associated traction corridors are developed in PSCAD/EMTDC software. Simulations are conducted to evaluate the likely over-voltages under various scenarios and the results are presented. Finally, the required lightning impulse withstand voltage rating for the switchgear is determined based on the simulation results.

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This project develops the required guidelines to assure stable and accurate operation of Power-Hardware-in-the-Loop implementations. The proposals of this research have been theoretically analyzed and practically examined using a Real-Time Digital Simulator. In this research, the interaction between software simulated power network and the physical power system has been studied. The conditions for different operating regimes have been derived and the corresponding analyses have been presented.

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The aim of this project was to develop a general theory of stigmergy and a software design pattern to build collaborative websites. Stigmergy is a biological term used when describing some insect swarm-behaviour where 'food gathering' and 'nest building' activities demonstrate the emergence of self-organised societies achieved without an apparent management structure. The results of the project are an abstract model of stigmergy and a software design pattern for building Web 2.0 components exploiting this self-organizing phenomenon. A proof-of-concept implementation was also created demonstrating potential commercial viability for future website projects.

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In this chapter we aim to explore how videogames can lead to improvements in wellbeing. Following Keyes (2007) and Huppert and So (2012) we view wellbeing as a multidimensional concept with both hedonic and eudaimonic aspects. In this chapter we take a broad approach in terms of exploring the impact of videogames on the psychological, social, and physical components of wellbeing. We explore how videogames have been shown to have an impact in each of these domains. Although there is a great deal of evidence for the actual and potential positive impacts of videogames, there are many unanswered questions regarding the situations in which there is likely to be an impact of videogame play on wellbeing, as well as the aspects of wellbeing that are likely to be impacted by videogame play. We conclude the chapter by outlining the key questions for future research. Our focus in this chapter is on the positive influences of videogames. We do not explore research on contexts in which negative impacts are possible or subgroups for which videogames could cause harm. However, these questions are obviously important and we see balanced engagement with age-appropriate videogames as a key prerequisite for any of the wellbeing benefits discussed below.

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In this paper we attack round-reduced Keccak hash function with a technique called rotational cryptanalysis. We focus on Keccak variants proposed as SHA-3 candidates in the NIST’s contest for a new standard of cryptographic hash function. Our main result is a preimage attack on 4-round Keccak and a 5-round distinguisher on Keccak-f[1600] permutation — the main building block of Keccak hash function.