Forming an intention to act on recommendations given via online social networks

Online social networks (OSN) are technology-enabled relationship tools in which a user creates a profile, connects to other individuals, and shares user-generated content with them. One of the many features OSN offer is the ability to post messages in the form of product and service recommendations. Although word-of-mouth research has examined this type of personal communication to intentionally influence consumer decisions, limited understanding exists regarding when a user acts upon a recommendation received from one of their contacts. In this study, we draw on relationship theories and research on trust to analyze the impact relationship characteristics and behaviors of the OSN contacts have on trust in the recommendation that subsequently leads a user to act on this OSN contact’s recommendation. The results of a survey of 116 OSN users showed that closeness, excessive posting behavior, and past recommendation experience have a positive impact on trust and intention to act on the recommendation. One characteristic of the relationships, that is, similarity, however, does not affect recommendation trust in the context of OSN. The findings enhance our understanding of relationships and their defining characteristics in OSN. The results also provide insights into how companies might leverage OSN in their marketing efforts.     

Sensitivity analysis of complex embedded real-time systems

The robustness of an architecture to changes is a major concern in the design of efficient and reliable state-of-the-art embedded real-time systems. Robustness is important during design process to identify if and in how far a system can accommodate later changes or updates, or whether it can be reused in a next generation product. In the product life-cycle, robustness helps the designer to perform changes as a result of product updates, integration of new components and subsystems, or modifications of the environment. In this paper we determine robustness as a performance reserve, the slack in performance before a system fails to meet timing requirements. This is measured as design sensitivity. Due to complex component interactions, resource sharing and functional dependencies, one-dimensional sensitivity analysis might not cover all effects that modifications of one system property may have on system performance. One reason is that the variation of one property can also affect the values of other system properties requiring new approaches to keep track of simultaneous parameter changes. In this paper we present a framework for one-dimensional and multi-dimensional sensitivity analysis of real-time systems. The framework is based on compositional analysis that is scalable to large systems. The one-dimensional sensitivity analysis combines a binary search technique with a set of formal equations derived from the real-time scheduling theory. The multi-dimensional sensitivity analysis engine consists of an exact algorithm that extends the one-dimensional approach, and a stochastic algorithm based on evolutionary search techniques.     

Shaping stable periodic motions of inertia wheel pendulum: theory and experiment

We consider an underactuated two‐link robot called the inertia wheel pendulum. The system consists of a free planar rotational pendulum and a symmetric disk attached to its end, which is directly controlled by a DC‐motor. The goal is to create stable oscillations of the pendulum, which is not directly actuated. We exploit a recently proposed feedback‐control design strategy based on motion planning via virtual holonomic constraints. This strategy is shown to be useful for design of regulators for achieving orbitally exponentially stable oscillatory motions. The main contribution is a step‐by‐step procedure on how to achieve oscillations with pre‐specified amplitude from a given range and an arbitrary independently chosen period. The theoretical results are verified via experiments with a real hardware setup. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Sound synthesis and evaluation of interactive footsteps and environmental sounds rendering for virtual reality applications

We propose a system that affords real-time sound synthesis of footsteps on different materials. The system is based on microphones, which detect real footstep sounds from subjects, from which the ground reaction force (GRF) is estimated. Such GRF is used to control a sound synthesis engine based on physical models. Two experiments were conducted. In the first experiment, the ability of subjects to recognize the surface they were exposed to was assessed. In the second experiment, the sound synthesis engine was enhanced with environmental sounds. Results show that, in some conditions, adding a soundscape significantly improves the recognition of the simulated environment.     

Optimal Sparse Matrix Dense Vector Multiplication in the I/O-Model

We study the problem of sparse-matrix dense-vector multiplication (SpMV) in external memory. The task of SpMV is to compute y:=Ax, where A is a sparse N×N matrix and x is a vector. We express sparsity by a parameter k, and for each choice of k consider the class of matrices where the number of nonzero entries is kN, i.e., where the average number of nonzero entries per column is k.     

Fixed-Parameter Algorithms for Cluster Vertex Deletion

We initiate the first systematic study of the NP-hard Cluster Vertex Deletion (CVD) problem (unweighted and weighted) in terms of fixed-parameter algorithmics. In the unweighted case, one searches for a minimum number of vertex deletions to transform a graph into a collection of disjoint cliques. The parameter is the number of vertex deletions. We present efficient fixed-parameter algorithms for CVD applying the fairly new iterative compression technique. Moreover, we study the variant of CVD where the maximum number of cliques to be generated is prespecified. Here, we exploit connections to fixed-parameter algorithms for (weighted) Vertex Cover.     

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.     

Nonlinear ceramics for tunable microwave devices

The research on materials and systems for tunable microwave devices has gained attraction within the last years. The radio frequency characterization and the component design of tunable microwave components based on dielectric ceramics especially barium-strontium-titanate (BST) are presented in this second part, whereas the basic material properties are discussed in detail in the first part. After a short introduction to the processing technology used for the fabrication of tunable components based on a BST thick film, the relations between microwave properties and material properties as well as the microstructure are presented in detail. The design process for tunable microwave components based on BST thick films is described. Especially the considerations related to micro- and macrostructure and their connection are highlighted. The paper closes with two different application examples: a reconfigurable array antenna for satellite communication and varactors for high power applications.     

Nanoparticles in polymer-matrix composites

Regarding the development of nanoparticles for polymer matrix composites the particle/agglomerate size and particle/agglomerate distribution in the composites, respectively, is often crucial. This is exemplarily shown for, e.g. optical applications with measurements of refractive index and transmittance. Classical blending techniques, where nanoparticles are dispersed in polymers or resins, are compared to a combination of a special gas-phase synthesis method with subsequent in-situ deposition of nanoparticles in high-boiling liquids. The particles/agglomerates were characterized regarding particle size and particle size distribution using transmission electron microscopy and dynamic light scattering. Additionally, important material properties like mechanical properties, relevant for application, or like viscosity, relevant for processing, are determined. It is shown, that with in-situ dispersed nanoparticles synthesized in a microwave plasma process composites with finely dispersed particles/agglomerates are attainable.