Interactive frames constructed in Second Life meetings: a study in educational and professional settings

Based on the analysis of “real” Second Life meetings data, in educational and professional settings, our objective is to understand the actual uses of this kind of Virtual World and more particularly, the interactive frames constructed in SL meetings and their interrelation with uses of communication media. The originality of our analytical framework stems from the combination of two perspectives: a third view perspective based on analyses of observational data and a first view perspective based on users’ reports on their experience in SL. Our results highlight: boundaries between serious and recreational registers; avatar’s expression and attribution of feelings to the person “behind”; spatial positioning as indicators and constructors of roles and engagement; management of communication fluidity and joint focus; narrowing of communication media used for task focus content; emerging mediation role for management of fractured exchanges.     

An architectural counterpoint in Universal Everything: Fluid Bodies exhibition

ABSTRACT

This exhibition review focuses on the quest for weaving boundaries between body-form-space-and material relationship using immersive technologies. Emerging as an architectural counterpoint, Universal Everything: Fluid Bodies exhibition held in Borusan Contemporary focuses on how we perceive the motion and form in relation to it, as well as fusing senses of kinaesthetic and synaesthetic through a data driven and motion-based visual representation. Through these algorithms, the exhibition displays how neuroarchitecture reminds us of the senses of perception. The architectural counterpoint, intention as an interaction and encounter of the body with ‘the machine’ as the ‘voyeur body’ and how this observational dialogue becomes a research methodology in understanding the nature of movement in space through digital tools.     

Low level light therapy by Red–Green–Blue LEDs improves healing in an excision model of Sprague–Dawley rats

There are many methods of healing wounds. Among these, light therapy is reported to be beneficial, as beams assist the human body in treating, sterilizing, and regenerating cells. Both Laser and LED irradiation with specific wavelengths induce proliferation of fibroblasts depending on the wound area or wavelength and are effective in wound healing. This study used 8-week-old 250–300 g Male Sprague–Dawley Rats (ILAR Code: NTacSam:SD). The experiment was carried out for the non-irradiation group and the Red–Green–Blue LEDs irradiation groups (n of each group = 5). The experiment animals were relieved for 24 h after wounds had been excised and then the Red–Green–Blue LEDs irradiation groups were given irradiation therapy over 9 days 1 h per day. Immunohistochemical staining was conducted for cytokeratin in order to precisely measure the defect size. Also, Masson’s trichrome staining was conducted for comparison of collagen between the Red–Green–Blue LEDs irradiation groups and the non-irradiation group. Animals treated with Blue LEDs irradiation (p < 0.05), Green LEDs irradiation (p < 0.05), and Red LEDs irradiation (N.S.) healed at a faster rate than non-irradiated group. The LEDs irradiated groups also had more collagen, according to Masson’s trichrome staining for collagen analysis. The Red–Green–Blue LEDs irradiation had a beneficial effect on wound healing and could probably replace low power laser treatment.     

QuickBird and Hyperion data analysis of an invasive plant species in the Galapagos Islands of Ecuador: Implications for control and land use management

In the Galapagos Islands of Ecuador, one of the greatest threats to the terrestrial ecosystem is the increasing number and areal extent of invasive species. Increased human presence on the islands has hastened the introduction of plant and animal species that threaten the native and endemic flora and fauna. Considerable research on invasive species in the Galapagos Islands has been conducted by the Charles Darwin Foundation. We complement that work through a spatially- and spectrally-explicit satellite assessment of an important invasive plant species (Psidium guajava — guava) on Isabela Island that integrates diverse remote sensing systems, data types, spatial and spectral resolutions, and analytical and image processing approaches. QuickBird and Hyperion satellite data are processed to characterize the areal extent and spatial structure of guava through the following approaches: (1) QuickBird data are classified through a traditional pixel-based approach (i.e., an unsupervised classification approach using the ISODATA algorithm), as well as an Object-Based Image Analysis (OBIA) approach; (2) multiple approaches for spectral “unmixing” of the Hyperion hyper-spectral data are assessed to construct spectral end-members from QuickBird data using linear and non-linear mixture modeling approaches; and (3) landscape pattern metrics are calculated and compared for the pixel-based, object-based, and spectral unmixing approaches. The spectral–spatial characteristics of guava are interpreted relative to management strategies for the control of guava and the restoration of natural ecosystems in the Galapagos National Park.     

Multicamera people tracking with a probabilistic occupancy map

Given two to four synchronized video streams taken at eye level and from different angles, we show that we can effectively combine a generative model with dynamic programming to accurately follow up to six individuals across thousands of frames in spite of significant occlusions and lighting changes. In addition, we also derive metrically accurate trajectories for each one of them.Our contribution is twofold. First, we demonstrate that our generative model can effectively handle occlusions in each time frame independently, even when the only data available comes from the output of a simple background subtraction algorithm and when the number of individuals is unknown a priori. Second, we show that multi-person tracking can be reliably achieved by processing individual trajectories separately over long sequences, provided that a reasonable heuristic is used to rank these individuals and avoid confusing them with one another.     

Eigenfeature regularization and extraction in face recognition

This work proposes a subspace approach that regularizes and extracts eigenfeatures from the face image. Eigenspace of the within-class scatter matrix is decomposed into three subspaces: a reliable subspace spanned mainly by the facial variation, an unstable subspace due to noise and finite number of training samples and a null subspace. Eigenfeatures are regularized differently in these three subspaces based on an eigenspectrum model to alleviate problems of instability, over-fitting or poor generalization. This also enables the discriminant evaluation performed in the whole space. Feature extraction or dimensionality reduction occurs only at the final stage after the discriminant assessment. These efforts facilitate a discriminative and stable low-dimensional feature representation of the face image. Experiments comparing the proposed approach with some other popular subspace methods on the FERET, ORL, AR and GT databases show that our method consistently outperforms others.     

A two-stage hardware scheduler combining greedy and optimal scheduling

Greedy scheduling heuristics provide a low complexity and scalable albeit particularly sub-optimal strategy for hardware-based crossbar schedulers. In contrast, the maximum matching algorithm for Bipartite graphs can be used to provide optimal scheduling for crossbar-based interconnection networks with a significant complexity and scalability cost. In this paper, we show how maximum matching can be reformulated in terms of Boolean operations rather than the more traditional formulations. By leveraging the inherent parallelism available in custom hardware design, we reformulate maximum matching in terms of Boolean operations rather than matrix computations and introduce three maximum matching implementations in hardware. Specifically, we examine a Pure Logic Scheduler with three dimensions of parallelism, a Matrix Scheduler with two dimensions of parallelism and a Vector Scheduler with one dimension of parallelism. These designs reduce the algorithmic complexity for an N×N$N\times N$ network from O(N³)$O\left(N^3\right)$ to O(1)$O\left(1\right)$, O(K)$O\left(K\right)$, and O(KN)$O\left(KN\right)$, respectively, where K$K$ is the number of optimization steps. While an optimal scheduling algorithm requires K=2N−1$K=2N-1$ steps, by starting with our hardware-based greedy strategy to generate an initial schedule, our simulation results show that the maximum matching scheduler can achieve 99% of the optimal schedule when K=9$K=9$. We examine hardware and time complexity of these architectures for crossbar sizes of up to N=1024$N=1024$. Using FPGA synthesis results, we show that a greedy schedule for crossbars, ranging from 8×8 to 256×256, can be optimized in less than 20 ns per optimization step. For crossbars reaching 1024×1024 the scheduling can be completed in approximately 10 μs with current technology and could reach under 90 ns with future technologies.     

Factors affecting the implementation of electronic data interchange in Korea

Although there have been a number of studies of the determinant factors of Electronic Data Interchange (EDI) implementation, most studies were carried out in the United States or Europe. The purpose of this study is to identify the determinant factors which affect implementation of EDI systems by Korean companies. Decentralization, EDI standards, technical compatibility, technical support by EDI vendors, education and training and participation of trading partners positively affect the extent of EDI usage. Formalization, technical compatibility, user involvement and participation of trading partners affect EDI integration with internal applications. Top management support and the participation of trading partners promote the extent of EDI operations. This study provides evidence of the effect of important determinant factors such as participation of trading partners and technical compatibility replicating previous EDI studies conducted in that US and Europe. For policy makers ad EDI developers, this study provides insights as to appropriate measures and incentives system designed to encourage EDI and B2B implementation.     

Incremental application of knowledge to continuously arriving time-oriented data

In our previous work, we introduced a computational architecture that effectively supports the tasks of continuous monitoring and of aggregation querying of complex domain meaningful time-oriented concepts and patterns (temporal abstractions), in environments featuring large volumes of continuously arriving and accumulating time-oriented raw data. Examples include provision of decision support in clinical medicine, making financial decisions, detecting anomalies and potential threats in communication networks, integrating intelligence information from multiple sources, etc. In this paper, we describe the general, domain-independent but task-specific problem-solving method underling our computational architecture, which we refer to as incremental knowledge-based temporal abstraction (IKBTA). The IKBTA method incrementally computes temporal abstractions by maintaining persistence and validity of continuously computed temporal abstractions from arriving time-stamped data. We focus on the computational framework underlying our reasoning method, provide well-defined semantic and knowledge requirements for incremental inference, which utilizes a logical model of time, data, and high-level abstract concepts, and provide a detailed analysis of the computational complexity of our approach.