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Ubiquitous availability of human mobility data has opened up new possibilities to address a multitude of application domains. However, so far, the visual analysis of this data has been hindered by the limited ability to explore and query complex movement sequences and to create models that allow meaningful aggregation. To address this problem, this paper presents a novel analytical approach that allows...
[Background]: Conceptual modeling languages have been widely studied in requirements engineering as tools for capturing, representing and reasoning about domain problems. One of these languages, goal models, has been proposed for representing the structure of stakeholder intentions. Like most other conceptual modeling languages, goal models are visualized using box-and-line diagrammatic notations...
We present a framework to analyze various aspects of models for video question answering (VideoQA) using customizable synthetic datasets, which are constructed automatically from gameplay videos. Our work is motivated by the fact that existing models are often tested only on datasets that require excessively high-level reasoning or mostly contain instances accessible through single frame inferences...
In Enterprise Modeling, we use several languages for designing, analyzing, and communicating the different domains of an enterprise. Two important criteria for choosing a domainspecific language are its appropriateness to the requirements of the enterprise, as well as the accuracy of the language in describing the domain at hand. However, in some business domains, core concepts --such as Capability,...
Models are perceived as effective tools for stakeholder communication and analysis concerning a given system. Enterprise Architecture assists organizational change with the creation and maintenance of models as a means to mitigate the business-IT misalignment and supporting decision-making regarding the strategic vision of the enterprise. Literature has acknowledged the topic of enterprise architecture...
This article intends to provide an overview of the state of art in developmental models of cognitive robots. With the development of artificial intelligence, robots have been able to perform a variety of complex tasks controlled by human. However, it is still a challenge for robots that they can explore and develop their cognitive ability in the specific environment like human beings. The current...
What is the future of fashion? Tackling this question from a data-driven vision perspective, we propose to forecast visual style trends before they occur. We introduce the first approach to predict the future popularity of styles discovered from fashion images in an unsupervised manner. Using these styles as a basis, we train a forecasting model to represent their trends over time. The resulting model...
The use of cognitive maps in support of solving practical problems of analysis of ill-structured situations and large-scale systems in economics, medicine, ecology, education and military-political sphere is growing. The problem of visual perception and understanding of cognitive maps is proven to be extremely urgent and practically important. The set of visualization methods that provide better perception...
When looking at an image, humans shift their attention towards interesting regions, making sequences of eye fixations. When describing an image, they also come up with simple sentences that highlight the key elements in the scene. What is the correlation between where people look and what they describe in an image? To investigate this problem, we look into eye fixations and image captions, two types...
Android's flexible communication model allows interactions among third-party apps, but it also leads to inter-app security vulnerabilities. Specifically, malicious apps can eavesdrop on interactions between other apps or exploit the functionality of those apps, which can expose a user's sensitive information to attackers. While the state-of-the-art tools have focused on detecting inter-app vulnerabilities...
It is said that a picture is worth a thousand words. Thus, there are various ways to describe an image, especially in aesthetic quality analysis. Although aesthetic quality assessment has generated a great deal of interest in the last decade, most studies focus on providing a quality rating of good or bad for an image. In this work, we extend the task to produce captions related to photo aesthetics...
High-radix, low-diameter, hierarchical networks based on the Dragonfly topology are common picks for building next generation HPC systems. However, effective tools are lacking for analyzing the network performance and exploring the design choices for such emerging networks at scale. In this paper, we present visual analytics methods that couple data aggregation techniques with interactive visualizations...
Taking security management of Software-Defined Networking (SDN) into consideration, the identification of attacks due to the SDN-specific vulnerabilities is of great significance. Thus in this case, formalization of security attacks becomes essential in promoting the identification process of attacks. This paper then proposes an integrated approach of attack trees and extension innovation methods...
Crowd event detection techniques aim at solving real-world surveillance problems, such as detecting crowd anomaly and tracking specific person in a highly dynamic crowd scene. In this paper, we proposed an innovate texture-based analysis method to model crowd dynamics and us it to distinguish the crowd behaviours. To describe complicated crowd scenes, homogeneous random features have been deployed...
Heterostructures of carbon nanotube on graphene, CNT-graphene, with two graphene layers connected by a CNT normal to the graphene planes, are investigated using first-principle calculations, leading to computed density of states (DOS) and electron transmission spectra. Based on these results, the structure consisting of graphene and a (4,4) CNT is determined to be metallic while that of graphene and...
Recent low-rank based matrix/tensor recovery methods have been widely explored in multispectral images (MSI) denoising. These methods, however, ignore the difference of the intrinsic structure correlation along spatial sparsity, spectral correlation and non-local self-similarity mode. In this paper, we go further by giving a detailed analysis about the rank properties both in matrix and tensor cases,...
This paper revisits visual saliency prediction by evaluating the recent advancements in this field such as crowd-sourced mouse tracking-based databases and contextual annotations. We pursue a critical and quantitative approach towards some of the new challenges including the quality of mouse tracking versus eye tracking for model training and evaluation. We extend quantitative evaluation of models...
Neural image/video captioning models can generate accurate descriptions, but their internal process of mapping regions to words is a black box and therefore difficult to explain. Top-down neural saliency methods can find important regions given a high-level semantic task such as object classification, but cannot use a natural language sentence as the top-down input for the task. In this paper, we...
There has been incredible growth of events over the internet in recent years. Google has become the giant source of knowledge for any event which has happened or happening over the internet. Some networking sites such as face book, micro blogging sites such as twitter are evolved with time and became the highly used sites over the internet. Various E-commerce websites such as Amazon, Ebay, Flipkart...
Floods can have a devastating effect on critical infrastructures, especially in the case of cascading effects among multiple infrastructures such as the Healthcare Critical Infrastructure (CI), Electricity CI, Water supply CI, etc. To ensure a resilient Healthcare Critical Infrastructure, understanding the vulnerabilities and analyzing the interdependencies on other critical infrastructures is important...
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