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Spatial visualization (SV) skills contribute to success in engineering. However, ample research from American university settings indicates that various subsets of engineering students have significantly less-developed SV skills than those demonstrated by the majority male population. A multi-modal SV workshop intervention was provided within a first-year engineering projects design course in order...
In trying to understand the big picture of how users learn to program in App Inventor, we want to be able to represent projects in a way suitable for large scale learning analytics. Here I present different representations of projects that could potentially be used to identify App Inventor projects that have structural similarities to each other, e.g., projects created by users following tutorials...
Research into computational jigsaw puzzle solving, an emerging theoretical problem with numerous applications, has focused in recent years on puzzles that constitute square pieces only. In this paper we wish to extend the scientific scope of appearance-based puzzle solving and consider ’’brick wall” jigsaw puzzles – rectangular pieces who may have different sizes, and could be placed next to each...
This paper indicates the dataset and challenges evaluated under PETS2017. In this edition PETS continues the evaluation theme of on-board surveillance systems for protection of mobile critical assets as set in PETS 2016. The datasets include (1) the ARENA Dataset; an RGB camera dataset, as used for PETS2014 to PETS 2016, which addresses protection of trucks; and (2) the IPATCH Dataset; a multi sensor...
In this paper, a new method with visual saliency detection for image quality assessment (IQA) is proposed. Through the experiments in this paper, we have verified the proposed method can be effective than most others.
This paper addresses the problem of maritime vessel identification by exploiting the state-of-the-art techniques of distance metric learning and deep convolutional neural networks since vessels are the key constituents of marine surveillance. In order to increase the performance of visual vessel identification, we propose a joint learning framework which considers a classification and a distance metric...
Spatial visualization (SV) skills are both learnable and linked to student success in engineering. Our work was motivated by previous research revealing a gender gap in SV skills that favors male engineering students. A multi-modal SV workshop intervention was incorporated into a first-year engineering projects course with the goal of fostering SV skills for all students. An analysis of SV skills,...
This paper presents an image retrieval method for insect identification based on saliency map and distance metric learning. First, the proposed method extracts regions of insects from target images by using saliency map and calculates visual features from the extracted insect regions. Next, in order to realize accurate retrieval of insects based on the calculated features, distance metric learning...
This paper presents a retrieval method of similar inspection records in road structures based on metric learning using experienced inspectors' evaluation. Inspection records of road structures include images and text-based information such as category of distress, damaged parts and degree of damage. The proposed method calculates distances from query inspection records, and rank lists of retrieval...
Depression is considered as a psychosomatic state associated with the soft biometric features. People suffering from depression always behave abnormal. Depression is a clinically proven disorder that can overwhelm a person and his ability to perform even a simple task. Soft biometric provides important information about a person without being enough for their verification because they lack uniqueness...
In large project, source code becomes increasing complex and lengthy so program comprehension plays an important and significant role for developers. Sequence diagram generated using static source code or dynamic only approach provides limited execution coverage, additionally contains redundant, dead and fault driven methods, which increase the size of the diagram and complexity. In this paper, to...
The goal of Image Quality Assessment (IQA) is to design computational models that can automatically predict the perceived image quality consistent with human subjective ratings. In this paper, we propose a full reference IQA metric gradient weighted structural similarity (GW-SSIM) by incorporating the gradient information to the well-known IQA metric SSIM. Experimental results demonstrate that GW-SSIM...
In the long term research of visual attention, various computational models have been proposed. However, most of those works do not take audio into consideration. In practice, visual signals often come along with audio. Therefore, it is natural to investigate the influence of audio on visual attention. In this paper, we focus on the problem of when will audio influence visual attention during video...
This paper presents the influence of perceived texture regularity on the visual quality of textures that are synthesized through parametric and non-parametric approaches. It is shown through subjective testing that textures with different degrees of perceived regularity exhibit different degrees of vulnerability to texture synthesis artifacts. The paper also proposes a method for adaptively selecting...
In an open Trusted Desktop Grid system, users can voluntarily participate in order to share resources. Thereby, computational trust is used to isolate malicious agents. Since a fully self-organised solution can suffer in emergent situations like the trust-breakdown scenario, we investigate an additional normative entity to guide the overall system behaviour by still keeping the autonomy of all agents...
Causal inference from observational data rely on similar treatment and control groups to isolate for variation, in addition to adjustments in estimates to account for the remaining uncontrollable variation. Propensity score matching and statistical inference are established tools to achieve for these two requirements respectively. Network structures in the underlying data of the experiment challenge...
The universal multiple outlier hypothesis testing problem is studied in two settings. In the first setting, each outlier can be arbitrarily distributed, and the number of outliers is fixed and known. In the second setting, the number of outliers is unknown at the outset. Nothing is known about the typical and outlier distributions other than that they are different and have full supports. For the...
Data visualisation with high expressive power plays an important role in code comprehension. Recent visualization tools try to fulfil the expectations of the users and use various analogies. For example, in an architectural metaphor, each class is represented by a building. Buildings are grouped into districts according to the structure of the namespaces. We think that these unique ways of code representation...
We present self-organisation processes within a decentralised P2P open Desktop Grid System. Every agent aimsto maximise the speedup of his jobs by joining the system. Therefore he needs to cooperate with other agents. We use a trust metric to assess the willingness of cooperation for other agents. To further optimise their speedup agents can form explicit Trusted Communities with trusted peers. Thus...
A novel objective measure for assessing the quality of image in-painting is proposed. In contrast to standard image quality metrics, the proposed one takes into account some constraints and characteristics related to the specific goals of inpainting techniques. The idea is to combine spatial low-level features and perceptual criteria in the design of the objective Image Inpainting Quality Metric (IIQM)...
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