Spot addressing for microarray images structured in hexagonal grids

In this work, an efficient method for spot addressing in images, which are generated by the scanning of hexagonal structured microarrays, is proposed. Initially, the blocks of the image are separated using the projections of the image. Next, all the blocks of the image are processed separately for the detection of each spot. The spot addressing procedure begins with the detection of the high intensity objects, which are probably the spots of the image. Next, the Growing Concentric Hexagon algorithm, which uses the properties of the hexagonal grid, is introduced for the detection of the non-hybridized spots. Finally, the Voronoi diagram is applied to the centers of the detected spots for the gridding of the image. The method is evaluated using spots generated from the scanning of the Beadchip of Illumina, which is used for the detection of Single Nucleotide Polymorphisms in the human genome, and uses hexagonal structure for the location of the spots. For the evaluation, the detected centers for each of the spot in the image are compared to the centers of the annotation, obtaining up to 98% accuracy for the spot addressing procedure.     

Multi-view human movement recognition based on fuzzy distances and linear discriminant analysis

In this paper, a novel multi-view human movement recognition method is presented. A novel representation of multi-view human movement videos is proposed that is based on learning basic multi-view human movement primitives, called multi-view dynemes. The movement video is represented in a new feature space (called dyneme space) using these multi-view dynemes, thus producing a time invariant multi-view movement representation. Fuzzy distances from the multi-view dynemes are used to represent the human body postures in the dyneme space. Three variants of Linear Discriminant Analysis (LDA) are evaluated to achieve a discriminant movement representation in a low dimensionality space. The view identification problem is solved either by using a circular block shift procedure followed by the evaluation of the minimum Euclidean distance from any dyneme, or by exploiting the circular shift invariance property of the Discrete Fourier Transform (DFT). The discriminant movement representation combined with camera viewpoint identification and a nearest centroid classification step leads to a high human movement classification accuracy.     

Evaluating content quality and helpfulness of online product reviews: The interplay of review helpfulness vs. review content

Online reviews have received much attention recently in the literature, as their visibility has been proven to play an important role during the purchase process. Furthermore, recent theoretical insight argue that the votes casted on how helpful an online review is (review helpfulness) are of particular importance, since they constitute a focal point for examining consumer decision making during the purchase process. In this paper, we explore the interplay between online review helpfulness, rating score and the qualitative characteristics of the review text as measured by readability tests. We construct a theoretical model based on three elements: conformity, understandability and expressiveness and we investigate the directional relationship between the qualitative characteristics of the review text, review helpfulness and the impact of review helpfulness on the review score. Furthermore, we examine whether this relation holds for extreme and moderate review scores. To validate this model we applied four basic readability measures to a dataset containing 37,221 reviews collected from Amazon UK, in order to determine the relationship between the percentage of helpful votes awarded to a review and the review text’s stylistic elements. We also investigated the interrelationships between extremely helpful and unhelpful reviews, as well as absolutely positive and negative reviews using intergroup comparisons. We found that review readability had a greater effect on the helpfulness ratio of a review than its length; in addition, extremely helpful reviews received a higher score than those considered less helpful. The present study contributes to the ever growing literature on on-line reviews by showing that readability tests demonstrate a directional relationship with average length reviews and their helpfulness and that this relationship holds both for moderate and extreme review scores.     

An adaptive treadmill-style locomotion interface and its application in 3-D interactive virtual market system

The key issue in this paper is estimating speed of a human. Compared with previous researches on walking speed estimation, we predict the walking intention before gait action. Our proposed hypothesis is that a composite force index is linearly correlated with the intended walking speed. We did two experiments to test the hypothesis. One gives a regression test indicating the intended walking speed has strong linear correlation with the proposed force index; the other tests the linearity by statistical analysis, guaranteeing the tolerance of individual difference. According to the regression and statistics analyses, we built a treadmill-style locomotion interface. Compared with the normal cases of treadmill control, the tested subject does not have to follow the speed of treadmill, but can actively change the speed of treadmill by his/her feet. The designed locomotion interface is applied in a virtual market system. Here the subject walks in a virtual market street with the desired speed. The stereo display based on virtual reality and the ambient sounds of the environment make the subject to have an immersed sense. The layout of shops in the virtual market system is in Japanese style, making the subjects experience much more realistic.     

A state estimator including conventional and synchronized phasor measurements

This paper presents an effective weighted least square formulation for the solution of the state estimation problem, considering conventional as well as synchronized phasor measurements. The proposed algorithm is based on a reference-free formulation, using both rectangular and polar coordinates for branch current phasor measurements, and alleviates any numerical problems encountered during initialization stage of the state estimation algorithm. Analytical equations are provided for the conventional and the phasor measurements and their corresponding partial derivatives with respect to state variables. The proposed algorithm is tested with a seven bus system and is compared with the traditional state estimator. Simulation results show that the proposed algorithm improves the precision greatly and gets better behavior as compared with the traditional state estimator.     

Visual understanding industrial workflows under uncertainty on distributed service oriented architectures

Service Oriented Architecture (SOA) is an evolution of distributed computing based on the request/reply design paradigm for synchronous and asynchronous applications. In such architectures, application developers or system integrators can build scenarios by composing one or more services without knowing the services’ underlying implementations. In this paper, we adopt a SOA framework for on-line scheduling complex industrial workflows. The proposed SOA consists of three main layers; the input layer, the benchmarking layer, the prediction layer and the scheduler. The main innovation of our SOA architecture is the prediction layer that supports computer vision tools able to visually observe how an industrial workflow is actually executed. This way, we can automatically estimate the actual execution time for a process. In particular a new self-initialized visual tracker algorithm is proposed in this paper to robustly trace workers’ trajectory in a plant via visual observations. Then, part-to-whole curve matching is presented so as to find correspondences among the traced curve and the ideal one and thus improving scheduler efficiency. The input layer interoperably describes industrial operations using the XPDL (an XML-based) format. The benchmarker evaluates much faster than real-time and in an off-line mode how long it takes for an industrial workflow to be executed on a given resource guaranteeing an almost real-time implementation of the video processing algorithms on the plant. The last component of the proposed SOA is the scheduler with the goal to assign the workflows to the available resources. In this paper, a Maximum Benefit First (MBF) scheduler is presented which maximizes the total gain received by the industry when completing execution of all the beneficial operations with minimum violations of their delivery deadlines (that is with the minimum compensations). Experiments have been conducted on a real-world industrial plant of Nissan Iberica automobile construction indicating the efficiency of the proposed system.     

The MORPHEUS Heterogeneous Dynamically Reconfigurable Platform

Reconfigurable computing offers a wide range of low cost and efficient solutions for embedded systems. The proper choice of the reconfigurable device, the granularity of its processing elements and its memory architecture highly depend on the type of application and their data flow. Existing solutions either offer fine grain FPGAs, which rely on a hardware synthesis flow and offer the maximum degree of flexibility, or coarser grain solutions, which are usually more suitable for a particular type of data flow and applications. In this paper, we present the MORPHEUS architecture, a versatile reconfigurable heterogeneous System-on-Chip targeting streaming applications. The presented architecture exploits different reconfigurable technologies at several computation granularities that efficiently address the different applications needs. In order to efficiently exploit the presented architecture, we implemented a complete software solution to map C applications to the reconfigurable architecture. In this paper, we describe the complete toolset and provide concrete use cases of the architecture.