Incremental Road Network Generation Based on Vehicle Trajectories

Nowadays, most vehicles are equipped with positioning devices such as GPS which can generate a tremendous amount of trajectory data and upload them to the server in real time. The trajectory data can reveal the shape and evolution of the road network and therefore has an important value for road planning, vehicle navigation, traffic analysis, and so on. In this paper, a road network generation method is proposed based on the incremental learning of vehicle trajectories. Firstly, the input vehicle trajectory data are cleaned by a preprocess module. Then, the original scattered positions are clustered and mapped to the representation points which stand for the feature points of the real roads. After that, the corresponding representation points are connected based on the original connection information of the trajectories. Finally, all representation points are connected by a Delaunay triangulation network and the real road segments are found by a shortest path searching approach between the connected representation point pairs. Experiments show that this method can build the road network from scratch and refine it with the input data continuously. Both the accuracy and timeliness of the extracted road network can continuously be improved with the growth of real-time trajectory data.

Enhancing Location-Based Social Media Network Services with Semantic Technologies: A Review

Today’s location-based social media services have gone beyond mere sharing users’real-time locationsvia internet, they now serve as the bridge between the real world and the online world. Location-based social media application can now recommend point of interest to users based on geographical information and user’s profile gatheredon social media networks. Semantic web technology provides tools,platforms and techniques to extract meaning, processand integrate structure datafrom the social web and other sources.The rapid increasein number of social media networks and theenormous amount of geographical and social data flow across mobile and web platforms, have not only provided rich data source for web applications but also help developers to facilitate location-based social media services. However, unprecedented amount of noise and unstructured data exist on these networks, making knowledge representation, point of interest recommendation and precision of search engine results cumbersome processes.In this paper, we presentreview of various semantic technologies that could bedeployed to enhance location-based social media services with emphasis on architectures, tools, supporting technologies and the pros and cons of each of these technologies.

Infographics as a tool for business agreement

This paper analyzes infographics as a problem solving tool to act as a medium for establishing dialog in the business context. Businness needs agreements, usually made in a written-form in a document called “brief”. The drawings, illustrations, visual narratives or infographic work can be considered a form of visual agreements for the participants. We present two case studies that consider the use of particular elements and cognitive processes involved in this visual agreement strongly connected to synthesis in dialog , memory and message clarity. By analyzing the visual languaje structure of real case infographic projects of the national housing social debt collection process (Infonavit, 2010) and the problem of child obesity (Cepol, 2012) where drawing plays a major role as a tool to communicate the operation of visual imaginery, we suggest a prominent role of drawing in the shaping process of the client´s inner topology. We introduce a preliminar analyitical framework –drawn from studies and theories like dual-coding theory (Pavios,1971), rhethoric, neurocognitive processes (Kosslyn, 1986), aesthetics and language philosophy (Goodman, 1978)– for understanding how this visual agreement denote and connote unstated viewing conventions and prioritize particular interpretations that can significantly affect the final solution. Finally we identify areas of future inquiry of new approaches on identity construction from a synthetic representation point of view.DOI: http://dx.doi.org/10.4995/IFDP.2016.3376

3D Face Recognition in the Conception of Sparse Representation

In this paper, a novel 3D face recognition method is proposed from the sparse representation point of view. Under the framework of sparse representation, the recognition problem is transformed to solve the problem of minimization L0-norm. Three types of facial geometrical features are extracted to describe 3D faces. According to the extracted features, 3D face recognition is conducted by applying to the ranking strategy of Fisher linear discriminant analysis. The experiments employed BJUT-3D datasets demonstrate the effectiveness of the proposed method.

On the inverse kinematics of an a priori unknown general 6R-Robot

SUMMARYThis paper looks at the inverse kinematics problem of an a priori unknown 6R-Robot from the representation point of view. It describes a new representation of the Euclidean motion group. With this representation, the inverse kinematics problem can be treated entirely numerical. No symbolical methods are required.

Using Rules in the Narrative Knowledge Representation Language (NKRL) Environment

NKRL is a semantic language expressly designed to deal with all sort of ‘narratives’, in particular with those (‘non-fictional narratives’) of an economic interest. From a knowledge representation point of view, its main characteristics consists in the use of two different sorts of ontologies, a standard, binary ontology of concepts, and an ontology of n-ary templates, where each template corresponds to the formal representation of a class of elementary events. Rules in NKRL correspond to high-level reasoning paradigms like the search for causal relationships or the use of analogical reasoning. Given i) the conceptual complexity of these paradigms, and ii) the sophistication of the underlying representation language, rules in NKRL cannot be implemented in a (weak) ‘inference by inheritance’ style but must follow a powerful ‘inference by resolution’ approach. After a short reminder about these two inference styles, and a quick introduction of the NKRL language, the chapter describes in some depth the main characteristics of the NKRL inference rules.

Decomposition of functions into pairs of intrinsic mode functions

The intrinsic mode functions (IMFs) arise as basic modes from the application of the empirical mode decomposition (EMD) to functions or signals. In this procedure, instantaneous frequencies are subsequently extracted from the IMFs by the simple application of the Hilbert transform, thereby providing a multiscale analysis of the signal's nonlinear phases. The beauty of this redundant representation method is in its simplicity and extraordinary effectiveness in many important and diverse settings. A fundamental issue in the field is to better understand these demonstrated qualities of the EMD procedures and the elementary modes they produce. For example, it is easily observed that when an EMD procedure is applied to the sum of two arbitrary IMFs, the original modes are rarely reproduced in the generated collection of IMFs. An interesting question from a representation point of view may be stated as follows: for any given sufficiently smooth function and fixed n ≥2, when is it possible to represent the function as a sum of (at most) n intrinsic modes? A more interesting question is whether such a decomposition is possible when the extracted modes are constructed from a common formulation of the intrinsic properties of the function being analysed. We provide an answer to these questions for a relaxed version of IMFs, called weak IMFs , which has been shown to be characterized in terms of eigenfunctions of Sturm–Liouville operators. The objective of this study is to further extend that analogy to the relationship between sums of weak IMFs and coupled Sturm–Liouville systems . The construction of this decomposition also provides a guide to an alternate characterization of the instantaneous frequency and bandwidth.