Visualizations of static networks in the form of node-link diagrams have evolved rapidly, though researchers are still grappling with how best to show evolution of nodes over time in these diagrams. This paper introdu...
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Visualizations of static networks in the form of node-link diagrams have evolved rapidly, though researchers are still grappling with how best to show evolution of nodes over time in these diagrams. This paper introduces NetVisia, a social network visualization system designed to support users in exploring temporal evolution in networks by using heat maps to display node attribute changes over time. NetVisia's novel contributions to network visualizations are to (1) cluster nodes in the heat map by similar metric values instead of by topological similarity, and (2) align nodes in the heat map by events. We compare NetVisia to existing systems and describe a formative user evaluation of a NetVisia prototype with four participants that emphasized the need for tool tips and coordinated views. Despite the presence of some usability issues, in 30-40 minutes the user evaluation participants discovered new insights about the data set which had not been discovered using other systems. We discuss implemented improvements to NetVisia, and analyze a co-occurrence network of 228 business intelligence concepts and entities. This analysis confirms the utility of a clustered heat map to discover outlier nodes and time periods.
This research compares several of the thematic roles of Verb Net (VN) to those of the Linguistic Infrastructure for Interoperable Resources and Systems (LIRICS). The purpose of this comparison is to develop a standard...
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This research compares several of the thematic roles of Verb Net (VN) to those of the Linguistic Infrastructure for Interoperable Resources and Systems (LIRICS). The purpose of this comparison is to develop a standard set of thematic roles that would be suited to a variety of natural language processing (NLP) applications. We draw from both resources to construct a unified set of semantic roles that will replace existing VN semantic roles. Through the process of comparison, we find that a hierarchical organization of coarse-grained, intermediate and fine-grained roles facilitates mapping between semantic resources of differing granularity and allows for flexibility in how VN can be used for diverse NLP applications, thus, we propose a hierarchical taxonomy of the unified role set. The comparison and subsequent development of the hierarchy reveals a level of granularity shared by both resources, which could be further developed into a standard set of thematic roles for the International Organization for Standardization (ISO).
The feature-based modulation flatness measure (FMSFM) and feature-based modulation crest measure (FMSCM) are proposed as novel feature vectors for music genre and mood classification. These features are extracted usin...
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The feature-based modulation flatness measure (FMSFM) and feature-based modulation crest measure (FMSCM) are proposed as novel feature vectors for music genre and mood classification. These features are extracted using a feature-based modulation spectrum to represent time-varying characteristics of the music signal. Instead of the spectrogram of the signal, timbral features such as mel-frequency cepstral coefficient (MFCC), decorrelated filter bank (DFB), and octave-based spectral contrast (OSC) are used for modulation. Combining FMSFM and FMSCM with the timbral features, we obtain significantly better accuracy in genre and mood classification than the conventional features.
In this paper we examine the causes of one of the major shortcomings of current natural feature registration approaches, failure to register when the camera's view approaches parallel to the marker. The methods us...
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In this paper we examine the causes of one of the major shortcomings of current natural feature registration approaches, failure to register when the camera's view approaches parallel to the marker. The methods used by current registration algorithms in the attempt to overcome this problem are reviewed, and a novel tracking based approach called the Optical-flow Perspective Invariant Registration Augmentation (OPIRA) is presented which significantly improves the range of registration. A thorough evaluation of OPIRA is conducted using an external ground truth, showing the improvements possible when combined with leading natural feature registration algorithms such as SIFT, SURF and Ferns.
This paper presents the results of interviews with representatives of the three key groups of stakeholders in the value chain for web accessibility: website commissioners, web developers and web accessibility experts....
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This paper presents the results of interviews with representatives of the three key groups of stakeholders in the value chain for web accessibility: website commissioners, web developers and web accessibility experts. 26 web commissioners, 7 web developers and 14 web accessibility experts were interviewed. The results show that in spite of great efforts by the World Wide Web Consortium, the European Commission and other international and national organizations to promote web accessibility, knowledge of this topic is still low. More critically, the tools to support commissioners, developers and accessibility experts are still very poor and do not provide much of the functionality that the various groups in the value chain need. We believe these results highlight some of the reasons why the state of web accessibility is still as poor as it is.
This paper presents an experimental study on environment recognition and movement control for multi-agent robotic soccer using wheeled mobile robots. A color image segmentation method based on YUV color information of...
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This paper presents an experimental study on environment recognition and movement control for multi-agent robotic soccer using wheeled mobile robots. A color image segmentation method based on YUV color information of each pixel of the color image is applied to the object recognition. The color image segmentation is performed using the tables that transform each value in a pixel to membership in several color classes, where the lower and higher threshold values of Y, U, and V are determined and described for the sample color markers. The position of objects on the field is efficiently and accurately calculated using a monocular camera. A common image processing method is used to detect landmarks such as corners/edges in the environment. A movement control algorithm is implemented based on the distance and orientation to the target. Experimental results of real-time movement control are also presented.
The present aim is to introduce first results of a new wearable prototype called Face Interface. The prototype was developed to carry both a video-based wearable eye tracker for pointing and a capacitive facial moveme...
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The present aim is to introduce first results of a new wearable prototype called Face Interface. The prototype was developed to carry both a video-based wearable eye tracker for pointing and a capacitive facial movement detector for selecting objects on a computer screen. The functionality of the prototype was evaluated in a controlled laboratory conditions in pointing and selecting tasks with three target diameters and three pointing distances. Also subjective ratings about the use of the device in interaction were collected. Participants achieved a mean pointing task time of 2.5 seconds with the prototype. This was improved to 1.2 seconds on average when the wearable eye tracker of the prototype was substituted by a commercial desktop eye tracker. The results revealed that target selection using the Face Interface prototype followed the Fitts' law with correlation of r = 0.76. The participants rated the use of the prototype as enjoyable, fast and accurate.
The primary goal of requirements engineering research is to propose, develop, and validate effective solutions for important practical problems. However practice has shown that successful projects often take from 20-2...
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The primary goal of requirements engineering research is to propose, develop, and validate effective solutions for important practical problems. However practice has shown that successful projects often take from 20-25 years to reach the stage of full industry adoption, while many other projects fizzle out and never advance beyond the initial research phase. In this interactive panel, teams of researchers representing several different requirements engineering research areas, bring ideas for technology transfer to a panel of industrial and government practitioners. The teams proceed through a series of interactive presentations and receive feedback from panelists. Underlying the game-show genre of the panel is the more serious goal to foster conversation between practitioners and researchers in order to improve the effectiveness of technology transfer in the requirements engineering community.
We study text analysis algorithms that use global optimization methods to compute local characteristics that are consistent with properties of the entire corpus rather than computed locally based on exogenous paramete...
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We study text analysis algorithms that use global optimization methods to compute local characteristics that are consistent with properties of the entire corpus rather than computed locally based on exogenous parameters. In the iterative implementations that we consider, each step both reads and updates a database of parameter values. Motivated by a need for rapid analysis of large corpora, we have developed methods for efficient access to such databases on parallel computers. These methods combine Bloom filters, in-memory caches, and an HBase cluster to reduce communication costs greatly relative to simpler approaches that either fully distribute or fully replicate the database. We also describe how this method can be incorporated into the MapReduce programming model, and illustrate its use within phrase segmentation programs. Our design can achieve considerable run time, latency and storage space improvements relative to other methods. In one phrase segmentation application, we improve performance by a factor of six relative to an HBase-based implementation.
The nociceptive withdrawal reflex (NWR) has been proven to be a valuable tool in the objective assessment of spinal cord hyperexcitability that is present in chronic pain disorders. However, most of the studies on obj...
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The nociceptive withdrawal reflex (NWR) has been proven to be a valuable tool in the objective assessment of spinal cord hyperexcitability that is present in chronic pain disorders. However, most of the studies on objective assessment of central sensitisation focus on population differences between patients and healthy individuals and do not provide tools for individual assessment. In this study, a method was developed to objectively assess pain hyperexcitability in individuals using the NWR. Results showed high rate of correct assessment with up to ~80% when differentiating between healthy volunteers and chronic pain patients.
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