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Inverse optimal control is the problem of computing a cost function that would have resulted in an observed sequence of decisions. The standard formulation of this problem assumes that decisions are optimal and tries to minimize the difference between what was observed and what would have been observed given a candidate cost function. We assume instead that decisions are only approximately optimal...
We had proposed a general model for WSD which is novel in some interesting ways and we have customized the model in form of a method (algorithm group) which is further customized in form of a number of algorithms to study the model's capability. We have introduced an optimization which has resulted in an unsupervised system which is the second best when evaluated against the renowned Senseval-3 international...
In this study, we propose a methodology to estimate 3D+time maps of left ventricular fibre strain from human structural and dynamic MRI data. A finite element model integrates fibre principal direction throughout the left ventricle from an ex vivo human diffusion tensor MRI acquisition and motion from tagged MRI. This combination enables the estimation of fibre strain and its variation throughout...
We have developed techniques to automatically generate personalised biomechanical models of patients' hearts based on 3D cardiac images. We demonstrate this approach using multi-slice computed tomography images. Unsupervised segmentation was performed using non-rigid image registration with a segmented image. A finite element model was automatically fitted to the segmented data of the left ventricle...
Mobile models aim to mimic human motion. Real traces aim at the same target. However, the latters are specific. They relate to a country or a region or smaller geographical places. Also, they cover at most few months of duration. In cons, Mobility models approach is more general in space and time for taking advantage of Social Theory. Mobile models are used in mobile networks routing protocols for...
For a natural communication robot cooperating with human, an adequate control mechanism of motion and utterance is required. This paper presents a robot motion planning method which considers utterance timing by utilizing Self-Organizing Map (SOM). Adequate target position of the robot motion and the utterance timing for an autonomous robot are decided by searching the best-matching-node on the SOM...
Individual behavior pattern captures human-centric significant places, movement trace and regular routines in the daily life. This paper proposes the BP-Mine framework, which consists of three phases, that is, location extraction, trajectory modeling and behavior pattern mining. Raw WiFi RSS readings and accelerometer sensor data are fused to extract fine grained significant locations in user's daily...
The escalating number of digitally-accessible devices pervading our everyday environments gives rise to the availability of tremendous amounts of human- and device-generated data. This data possesses strong spatial and temporal semantics, it captures phenomena and states of the environment, and is extremely volatile, being created, moved, stored, and deleted on-demand at rapid rates. The requisite...
Sustainable development analysis is the important problem in contemporary domestic and international. The analysis about sustainable development evaluation index system spreads widely in the international, this paper analyzes sustainable development index system of research results in the relevant international organizations and main developed countries. We point out the characteristics of the related...
Based on “ground truth” eye-tracking data, earlier research [1] shows that adding natural scene saliency (NSS) can improve an objective metric's performance in predicting perceived image quality. To include NSS in a real-world implementation of an objective metric, a computational model instead of eye-tracking data is needed. Existing models of visual saliency are generally designed for a specific...
Recent advances in technologies for capturing video data have opened a vast amount of new application areas. Among them, the incorporation of Time-of-Flight (ToF) cameras on Ambient Intelligence (AmI) environments. Although the performance of tracking algorithms have quickly improved, symbolic models used to represent the resulting knowledge have not yet been adapted for smart environments. This paper...
We proposed a model that is capable of handling the patterns of ambiguous recurring tasks. If we can grasp the pattern, it would be useful for prediction of the tasks which might happen in the future, and also be the hint on handing them over to co-workers. To utilize our model, we have developed a concrete method for manipulation or visualization of the modeled data. This method is useful to build...
The Command and Control (C2) system that provide information to the actors in a conflict has always been a key target for technology advancement. The ongoing development of automated digital military information systems has enabled, and is demanding the development of specific functional area support systems. The focus of communication systems and methods is shifting away from human to human communication...
In this paper, we argue that empirical research on genuine linguistic topics, such as on the production of multimodal utterances in the speaker and the interpretation of the multimodal signals in the interlocutor, can greatly benefit from the use of virtual reality technologies. Established methodologies for research on multimodal interactions, like the presentation of pre-recorded 2D videos of interaction...
Context awareness plays an essential role in systems dealing with activity recognition. The context information present to the system, and the way in which it is modelled, shape the performance of the system during activity inference. In this paper we present a novel approach for modelling human behaviour based on preconditions and effects and employing it for generating training-free probabilistic...
We present the framework design and modeling for an integrated vehicular and human-centric urban sensing system. The goal is to understand the impact of vehicles and human activities on the surrounding environment. This is achieved through a seamless integration of the human aspect into vehicular and urban sensing going beyond the traditional human-in-the-loop sampling methodologies. We describe the...
We use images that have been collected using an Internet search engine to train color name models for color naming and recognition tasks. Considering color histogram bands as being words of an image and the color names as classes, we use the supervised latent Dirichlet allocation to train our model. To pre-process the training data, we use state-ofthe art salient object detection and a Kullback-Leibler...
Basic understanding and recognition of human actions can be accomplished by modeling the spatiotemporal relationship among major skeletal joints. In this work we present an approach that models human actions using temporal causal relations of joint movements. The relations form a graph with joints as nodes and edges induced by the Granger causality measure between pairs of joint point processes. Each...
Ground-penetrating radar systems are useful for a variety scientific studies, including monitoring changes to the polar ice sheets that may give clues to climate change. A key step in analyzing radar echograms is to identify boundaries between layers of material (such as air, ice, rock, etc.). In this paper, we propose an automated technique for identifying these boundaries, posing this as an inference...
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