A new framework for sign language alphabet hand posture recognition using geometrical features through artificial neural network (part 1)

Neural Computing and Applications - Hand pose tracking is essential in sign languages. An automatic recognition of performed hand signs facilitates a number of applications, especially for people...     

Mental imagery classification using one-dimensional convolutional neural network for target selection in single-channel BCI-controlled mobile robot

Neural Computing and Applications - This paper introduces the use of the one-dimensional convolutional neural network (1D-CNN) for end-to-end EEG decoding with application towards a BCI system with...     

In Vitro Characterization of Human CD24hiCD38hi Regulatory B Cells Shows CD9 Is Not a Stable Breg Cell Marker

Regulatory B (Breg) cells are endowed with immune suppressive functions. Various human and murine Breg subtypes have been reported. While interleukin (IL)-10 intracellular staining remains the most reliable way to identify Breg cells, this technique hinders further essential functional studies. Recent findings suggest that CD9 is an effective surface marker of murine IL-10 competent Breg cells. However, the stability of CD9 and its relevance as a unique marker for human Breg cells, which have been widely characterized as CD24^hiCD38^hi, have not been investigated. Here, we demonstrate that CD9 expression is sensitive to in vitro B cell stimulations. CD9 expression could either be re-expressed or downregulated in purified CD9-negative B cells and CD9-positive B cells, respectively. We found no significant differences in the Breg differentiation capacity of the CD9-negative and CD9-positive B cells. Furthermore, CD9-positive B cells co-express CD40 and CD86, suggesting their nature as B cell activation or co-stimulatory molecules, rather than regulatory ones. Therefore, we report the relatively unstable CD9 as a distinct surface molecule, indicating the need for further research for a more reliable marker to purify human Breg cells.     

Single mask fabrication process for movable MEMS devices

The current work reports on the realization of movable micromachining devices using self-aligned single-mask fabrication process. Only dry etching process utilizing inductively coupled plasma reactive ion etching was used to release 3D micro structures from single crystal silicon substrate. No wet etching process is required to release the structures as is the case with silicon on insulator (SOI) wafers. Also the developed process does not require an SOI substrate and accordingly dispensing with the application of a wet etching step, thus yielding uniform structures without stiction. The optimized process was applied to realize thermally actuated microgrippers. The article presents the development of the fabrication process and demonstrates the operation of the fabricated device. The optimized process provides an avenue for low cost fabrication of movable micromachining devices without the use of complicated wet etching steps typically associated with SOI substrates.     

Silhouette-based human action recognition using SAX-Shapes

Human action recognition is an important problem in Computer Vision. Although most of the existing solutions provide good accuracy results, the methods are often overly complex and computationally expensive, hindering practical applications. In this regard, we introduce the combination of time-series representation for the silhouette and Symbolic Aggregate approXimation (SAX), which we refer to as SAX-Shapes, to address the problem of human action recognition. Given an action sequence, the extracted silhouettes of an actor from every frame are transformed into time series. Each of these time series is then efficiently converted into the symbolic vector: SAX. The set of all these SAX vectors (SAX-Shape) represents the action. We propose a rotation invariant distance function to be used by a random forest algorithm to perform the human action recognition. Requiring only silhouettes of actors, the proposed method is validated on two public datasets. It has an accuracy comparable to the related works and it performs well even in varying rotation.     

Monitoring web services’ quality of service: a literature review

Monitoring Quality of Service (QoS) compliance is an important procedure in web service environment. It determines whether users’ expectations are met, and becomes the vital factor for them to decide whether to continue paying for the service or not. The monitoring is performed by checking the actual services performance against the QoS stated in Service Level Agreement (SLA). In relation to that, the need for monitoring vague QoS specifications in SLA has become more apparent nowadays. This paper reviews the published literature on web services QoS monitoring. A total of 60 selected articles were systematically analyzed. There were 23 of the articles selected through restrictive search criteria while the other 37 were selected based on unrestrictive search criteria. The review shows that little evidence exists on monitoring vague QoS specifications of web services. Providing ability for monitoring QoS that is specified vaguely in SLA could give new insights and implications to web services field. This paper concludes with some recommended future works to construct the theory and perform the empirical research.     

A quadratic spline approximation using detail multi-layer for soft shadow generation in augmented reality

Implementation of shadows is crucial to enhancement of images in AR environments. Without shadows, virtual objects would look floating over the scene resulting in unrealistic rendering of AR environments. Casting hard shadows would provide only spatial information while soft shadows help improve realism of AR environments. Several algorithms have been proposed to render realistic shadows which often incurred high computational costs. Little attention has been directed towards the balanced trade-off between shadow quality and computational costs. In this study, two approaches are proposed: Quadratic Spline Interpolation (QSI) to soften the outline of the shadow and Detail Multi-Layer (DML) technique to optimize the volume of computations for the generation of soft shadows based on real light sources. QSI estimates boarder hard shadow samples while DML involves three main phases: real light sources estimation, soft shadow production and reduction of the complexity of 3-Dimensional objects’ shadows. To be more precise, a reflective hemisphere is used to capture real light and to create an environment map. The Median Cut algorithm is implemented to locate the direction of real light sources on the environment map. Subsequently, the original hard shadows are retrieved and a sample of multilayer hard shadows is produced where each layer has its unique size and colour. These layers overlap to produce soft shadows based on the real light sources’ directions. Finally, the Level of Details (LOD) algorithm is implemented to increase the efficiency of soft shadows by decreasing the complexity of vertex transformations. The proposed technique is tested using three samples of multilayer hard shadows with varying numbers of light sources generated from the Median Cut algorithm. The experimental results show that the proposed technique successfully produces realistic soft shadows at low computational costs.     

Robust face recognition against expressions and partial occlusions

Facial features under variant-expressions and partial occlusions could have degrading effect on overall face recognition performance. As a solution, we suggest that the contribution of these features on final classification should be determined. In order to represent facial features contribution according to their variations, we propose a feature selection process that describes facial features as local independent component analysis(ICA) features. These local features are acquired using locally lateral subspace(LLS) strategy.Then, through linear discriminant analysis(LDA) we investigate the intraclass and interclass representation of each local ICA feature and express each feature s contribution via a weighting process. Using these weights, we define the contribution of each feature at local classifier level. In order to recognize faces under single sample constraint, we implement LLS strategy on locally linear embedding(LLE) along with the proposed feature selection. Additionally, we highlight the efficiency of the implementation of LLS strategy. The overall accuracy achieved by our approach on datasets with different facial expressions and partial occlusions such as AR, JAFFE,FERET and CK+ is 90.70%. We present together in this paper survey results on face recognition performance and physiological feature selection performed by human subjects.     

A cross-layer approach for partition detection at overlay layer for structured P2P in MANETs

Due to limited radio range and mobility of nodes in mobile ad hoc networks (MANETs), the network partitioning and merging could occur frequently. When structured peer-to-peer (P2P) overlays are running over MANETs, then network partition in the physical network can also cause network partition at the overlay layer. Existing approaches for structured P2P overlay over MANETs do not detect network partition at the overlay layer. This paper proposes a cross-layer approach to detect network partition at the overlay layer for structured P2P overlay over MANETs. Simulation results show that the proposed approach is highly effective and efficient in terms of routing overhead, success ratio and false-negative ratio.