Investigating the Feasibility of Integrating Pavement Friction and Texture Depth Data in Modeling for INDOT PMS

Under INDOT’s current friction testing program, the friction is measured annually on interstates but only once every three years on non-interstate roadways. The state’s Pavement Management System, however, would require current data if friction were to be included in the PMS. During routine pavement condition monitoring for the PMS, texture data is collected annually. This study explored the feasibility of using this pavement texture data to estimate the friction during those years when friction is not measured directly. After multi0ple approaches and a wide variety of ways of examining the currently available data and texture measuring technologies, it was determined that it is not currently feasible to use the texture data as a surrogate for friction testing. This is likely because the lasers used at this time are not capable of capturing the small-scale pavement microtexture. This situation may change, however, with advances in laser or photo interpretation technologies and improved access to materials data throughout the INDOT pavement network

Bag-of-Features Image Indexing and Classification in Microsoft SQL Server Relational Database

This paper presents a novel relational database architecture aimed to visual objects classification and retrieval. The framework is based on the bag-of-features image representation model combined with the Support Vector Machine classification and is integrated in a Microsoft SQL Server database.Comment: 2015 IEEE 2nd International Conference on Cybernetics (CYBCONF), Gdynia, Poland, 24-26 June 201

Wearable performance

This is the post-print version of the article. The official published version can be accessed from the link below - Copyright @ 2009 Taylor & FrancisWearable computing devices worn on the body provide the potential for digital interaction in the world. A new stage of computing technology at the beginning of the 21st Century links the personal and the pervasive through mobile wearables. The convergence between the miniaturisation of microchips (nanotechnology), intelligent textile or interfacial materials production, advances in biotechnology and the growth of wireless, ubiquitous computing emphasises not only mobility but integration into clothing or the human body. In artistic contexts one expects such integrated wearable devices to have the two-way function of interface instruments (e.g. sensor data acquisition and exchange) worn for particular purposes, either for communication with the environment or various aesthetic and compositional expressions. 'Wearable performance' briefly surveys the context for wearables in the performance arts and distinguishes display and performative/interfacial garments. It then focuses on the authors' experiments with 'design in motion' and digital performance, examining prototyping at the DAP-Lab which involves transdisciplinary convergences between fashion and dance, interactive system architecture, electronic textiles, wearable technologies and digital animation. The concept of an 'evolving' garment design that is materialised (mobilised) in live performance between partners originates from DAP Lab's work with telepresence and distributed media addressing the 'connective tissues' and 'wearabilities' of projected bodies through a study of shared embodiment and perception/proprioception in the wearer (tactile sensory processing). Such notions of wearability are applied both to the immediate sensory processing on the performer's body and to the processing of the responsive, animate environment. Wearable computing devices worn on the body provide the potential for digital interaction in the world. A new stage of computing technology at the beginning of the 21st Century links the personal and the pervasive through mobile wearables. The convergence between the miniaturisation of microchips (nanotechnology), intelligent textile or interfacial materials production, advances in biotechnology and the growth of wireless, ubiquitous computing emphasises not only mobility but integration into clothing or the human body. In artistic contexts one expects such integrated wearable devices to have the two-way function of interface instruments (e.g. sensor data acquisition and exchange) worn for particular purposes, either for communication with the environment or various aesthetic and compositional expressions. 'Wearable performance' briefly surveys the context for wearables in the performance arts and distinguishes display and performative/interfacial garments. It then focuses on the authors' experiments with 'design in motion' and digital performance, examining prototyping at the DAP-Lab which involves transdisciplinary convergences between fashion and dance, interactive system architecture, electronic textiles, wearable technologies and digital animation. The concept of an 'evolving' garment design that is materialised (mobilised) in live performance between partners originates from DAP Lab's work with telepresence and distributed media addressing the 'connective tissues' and 'wearabilities' of projected bodies through a study of shared embodiment and perception/proprioception in the wearer (tactile sensory processing). Such notions of wearability are applied both to the immediate sensory processing on the performer's body and to the processing of the responsive, animate environment

Land re-use, complexity and actor-networks: a framework for research

This paper will present a conceptual framework for the examination of land redevelopment based on a complex systems/networks approach. As Alvin Toffler insightfully noted, modern scientific enquiry has become exceptionally good at splitting problems into pieces but has forgotten how to put the pieces back together. Twenty-five years after his remarks, governments and corporations faced with the requirements of sustainability are struggling to promote an ‘integrated’ or ‘holistic’ approach to tackling problems. Despite the talk, both practice and research provide few platforms that allow for ‘joined up’ thinking and action. With socio-economic phenomena, such as land redevelopment, promising prospects open up when we assume that their constituents can make up complex systems whose emergent properties are more than the sum of the parts and whose behaviour is inherently difficult to predict. A review of previous research shows that it has mainly focused on idealised, ‘mechanical’ views of property development processes that fail to recognise in full the relationships between actors, the structures created and their emergent qualities. When reality failed to live up to the expectations of these theoretical constructs then somebody had to be blamed for it: planners, developers, politicians. However, from a ‘synthetic’ point of view the agents and networks involved in property development can be seen as constituents of structures that perform complex processes. These structures interact, forming new more complex structures and networks. Redevelopment then can be conceptualised as a process of transformation: a complex system, a ‘dissipative’ structure involving developers, planners, landowners, state agencies etc., unlocks the potential of previously used sites, transforms space towards a higher order of complexity and ‘consumes’ but also ‘creates’ different forms of capital in the process. Analysis of network relations point toward the ‘dualism’ of structure and agency in these processes of system transformation and change. Insights from actor network theory can be conjoined with notions of complexity and chaos to build an understanding of the ways in which actors actively seek to shape these structures and systems, whilst at the same time are recursively shaped by them in their strategies and actions. This approach transcends the blame game and allows for inter-disciplinary inputs to be placed within a broader explanatory framework that does away with many past dichotomies. Better understanding of the interactions between actors and the emergent qualities of the networks they form can improve our comprehension of the complex socio-spatial phenomena that redevelopment comprises. The insights that this framework provides when applied in UK institutional investment into redevelopment are considered to be significant

PANGAEA information system for glaciological data management

Specific parameters determined on cores from continental ice sheets or glaciers can be used to reconstruct former climate. To use this scientific resource effectively an information system is needed which guarantees consistent longtime storage of data and provides easy access for the scientific community.An information system to archive any data of paleoclimatic relevance, together with the related metadata, raw data and evaluated paleoclimatic data, is presented. The system, based on a relational database, provides standardized import and export routines, easy access with uniform retrieval functions, and tools for the visualization of the data. The network is designed as a client/server system providing access through the Internet with proprietary client software including a high functionality or read-only access on published data via the World Wide Web

Deep Markov Random Field for Image Modeling

Markov Random Fields (MRFs), a formulation widely used in generative image modeling, have long been plagued by the lack of expressive power. This issue is primarily due to the fact that conventional MRFs formulations tend to use simplistic factors to capture local patterns. In this paper, we move beyond such limitations, and propose a novel MRF model that uses fully-connected neurons to express the complex interactions among pixels. Through theoretical analysis, we reveal an inherent connection between this model and recurrent neural networks, and thereon derive an approximated feed-forward network that couples multiple RNNs along opposite directions. This formulation combines the expressive power of deep neural networks and the cyclic dependency structure of MRF in a unified model, bringing the modeling capability to a new level. The feed-forward approximation also allows it to be efficiently learned from data. Experimental results on a variety of low-level vision tasks show notable improvement over state-of-the-arts.Comment: Accepted at ECCV 201

Personalized Cinemagraphs using Semantic Understanding and Collaborative Learning

Cinemagraphs are a compelling way to convey dynamic aspects of a scene. In these media, dynamic and still elements are juxtaposed to create an artistic and narrative experience. Creating a high-quality, aesthetically pleasing cinemagraph requires isolating objects in a semantically meaningful way and then selecting good start times and looping periods for those objects to minimize visual artifacts (such a tearing). To achieve this, we present a new technique that uses object recognition and semantic segmentation as part of an optimization method to automatically create cinemagraphs from videos that are both visually appealing and semantically meaningful. Given a scene with multiple objects, there are many cinemagraphs one could create. Our method evaluates these multiple candidates and presents the best one, as determined by a model trained to predict human preferences in a collaborative way. We demonstrate the effectiveness of our approach with multiple results and a user study.Comment: To appear in ICCV 2017. Total 17 pages including the supplementary materia