Flight-vehicle structures education in the united states—Assessment and recommendations

An assessment is made of the technical contents of flight-vehicle structures curricula at 41 U.S. universities with accredited aerospace engineering programs. The assessment is based on the technical needs for the new and projected aeronautical and space systems as well as on the likely characteristics of the aerospace engineering work environment. A number of deficiencies and areas of concern are identified and recommendations are presented for enhancing the effectiveness of flight-vehicle structures education. A number of government supported programs that can help aerospace engineering education are listed in the appendix.     

Direct conversion receiver for radio communication systems

Direct conversion receiver (DCR) architecture, which has introduced the zero intermediate frequency (IF) approach, supports efficient wireless handset designs with a high level of integration. Transmission over wireless channels is subject to time dispersion due to multipath propagation and frequency dispersion due to Doppler effect, the design of wireless receivers are tremendously important in supporting reliable communication links. With wireless technology growing, the choice of optimal wireless receiver architecture that supports monolithic integration without performance degradation becomes an important dimension in modern handset design. The increasing demand for mobile terminals with smaller physical dimensions has led to the investigation of DCR, which supports single chip and multinode designs. Since DCR is a promising architecture for fourth generation mobile terminals, it is important to note that implementation of a certain dc offset technique does not compromise the benefits of low complexity receiver design.     

Applications,databases and open computer vision research from drone videos and images: a survey

Analyzing videos and images captured by unmanned aerial vehicles or aerial drones is an emerging application attracting significant attention from researchers in various areas of computer vision. Currently, the major challenge is the development of autonomous operations to complete missions and replace human operators. In this paper, based on the type of analyzing videos and images captured by drones in computer vision, we have reviewed these applications by categorizing them into three groups. The first group is related to remote sensing with challenges such as camera calibration, image matching, and aerial triangulation. The second group is related to drone-autonomous navigation, in which computer vision methods are designed to explore challenges such as flight control, visual localization and mapping, and target tracking and obstacle detection. The third group is dedicated to using images and videos captured by drones in various applications, such as surveillance, agriculture and forestry, animal detection, disaster detection, and face recognition. Since most of the computer vision methods related to the three categories have been designed for real-world conditions, providing real conditions based on drones is impossible. We aim to explore papers that provide a database for these purposes. In the first two groups, some survey papers presented are current. However, the surveys have not been aimed at exploring any databases. This paper presents a complete review of databases in the first two groups and works that used the databases to apply their methods. Vision-based intelligent applications and their databases are explored in the third group, and we discuss open problems and avenues for future research.

     

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.     

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.