Dynamic Parameter Identification Based on Lagrangian Formulation and Servomotor-type Actuators for Industrial Robots

International Journal of Control, Automation and Systems - This article presents the design of a parameter identification model for industrial manipulator robots. This model includes the dynamics...     

A multimodal feature learning approach for sentiment analysis of social network multimedia

In this paper we investigate the use of a multimodal feature learning approach, using neural network based models such as Skip-gram and Denoising Autoencoders, to address sentiment analysis of micro-blogging content, such as Twitter short messages, that are composed by a short text and, possibly, an image. The approach used in this work is motivated by the recent advances in: i) training language models based on neural networks that have proved to be extremely efficient when dealing with web-scale text corpora, and have shown very good performances when dealing with syntactic and semantic word similarities; ii) unsupervised learning, with neural networks, of robust visual features, that are recoverable from partial observations that may be due to occlusions or noisy and heavily modified images. We propose a novel architecture that incorporates these neural networks, testing it on several standard Twitter datasets, and showing that the approach is efficient and obtains good classification results.     

Understanding student participation in undergraduate course communities: A case study

Participation is the cornerstone of any community. Promoting, understanding and properly managing it allows not only keeping the community sustainable, but also providing personalized services to its members and managers. This article presents a case study in which student participation in a course community was motivated using two different extrinsic mechanisms, and mediated by a software platform. The results were compared with a baseline community of the same course, in which participation was not motivated by external means. The analysis of these results indicates that managing a partially virtual course community requires the introduction of monitoring services, community managers and extrinsic mechanisms to motivate participation. These findings allow community managers to improve their capability for promoting participation and keeping the community sustainable. The findings also raise several implications that should be considered in the design of software supporting this kind of community, when managing the participation of its members.     

Fabrication of layered polydimethylsiloxane/perfluoropolyether microfluidic devices with solvent compatibility and valve functionality

The development of multilayer soft lithography methodology has seen polydimethysiloxane (PDMS) as the preferred material for the fabrication of microfluidic devices. However, the functionality of these PDMS microfluidic chips is often limited by the poor chemical resistance of PDMS to certain solvents. Here, we propose the use of a photocurable perfluoropolyether (PFPE), specifically FOMBLIN^® MD40 PFPE, as a candidate material to provide a solvent-resistant buffer layer to make the device substantially impervious to chemically induced swelling. We first carried out a systematic study of the solvent resistance properties of FOMBLIN^® MD40 PFPE as compared with PDMS. The comparison presented here demonstrates the superiority of FOMBLIN^® MD40 PFPE over PDMS in this regard; moreover, the results permitted to categorize solvents in four different groups depending on their swelling ratio. We then present a step-by-step recipe for a novel fabrication process that uses multilayer lithography to construct a comprehensive solvent-resistant device with fluid and control channels integrated with a valve structure and also permitting easy establishment of outside connections.     

High power GaN‐HEMT SPDT switches for microwave applications

In this article, the design, fabrication, and on‐wafer test of X‐Band and 2–18 GHz wideband high‐power SPDT MMIC switches in AlGaN/GaN technology are presented. The switches have demonstrated state‐of‐the‐art performance and RF fabrication yield better than 65%. Linear and power measurements for different control voltages have been reported and an explanation of the dependence of the power performances on the control voltage is given. In particular, the X‐band switch exhibits a 0.4 dB compression level at 10 GHz when driven by a 38 dBm input signal. The wideband switch shows a compression level of 1 dB at an input drive higher than 38 dBm across the entire bandwidth. © 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.     

Landscape-aware location-privacy protection in location-based services

Mobile network providers have developed a variety of location-based services (LBSs), such as friend-finder, point of interest services, emergency rescue and many other safety and security services. The protection of location-privacy has consequently become a key aspect to the success of LBSs, since users consider their own physical location and movements highly privacy-sensitive, and demand for solutions able to protect such an information in a variety of environments. The idea behind location-privacy protection is that the individual should be able to set the level at which the location information is released to avoid undesired exploitation by a potential attacker: one of the approaches to this problem is given by the application of spatial obfuscation techniques, actuated by a trusted agent, and consisting in artificial perturbations of the location information collected by sensing technologies, before its disclosure to third parties. In many situations, however, landscape/map information can help a third party to perform Bayesian inference over spatially obfuscated data and to refine the user’s location estimate up to a violation of the original user’s location-privacy requirements. The goal of this paper is to provide a map-dependent obfuscation procedure that enables the release of the maximum possible user’s location information, that does not lead to a violation of the original user’s location-privacy requirements, even when refined through map-based inference.     

Tracing pathway activities with kinase inhibitors and reverse phase protein arrays

Controlling aberrant protein kinase activity is a promising strategy for a variety of diseases, particularly cancer. Hence, the development of kinase inhibitors is currently a focal point for pharmaceutical research. In this study we utilize a chip-based reverse phase protein array (RPA) platform for profiling of kinase inhibitors in cell-based assays. In combination with the planar wave-guide technology the assay system has an absolute LOD down to the low zeptomole range. A431 cell lysates were analyzed for the activation state of key effectors in the epidermal growth factor (EGF) and insulin signaling pathways to validate this model for compound screening. A microtiter-plate format for growing, treating, and lysing cells was shown to be suitable for this approach, establishing the value of the technology as a screening tool for characterization of large numbers of kinase inhibitors against a wide variety of cellular signaling pathways. Moreover, the reverse array format allows rapid development of site-specific phosphorylation assays, since in contrast to ELISA type systems only a single antigen-specific antibody is required.     

A Multi-Criteria Decision Analysis Technique for Stochastic Task Criticality in Project Management

Inherent in project management is the risk that a project fails to meet planned completion deadlines due to delays experienced in individual tasks. As such, certain critical tasks may be candidates for risk management (e.g., the allocation of additional resources such as labor, materials, and equipment) to prevent delays. A common means to identify such critical tasks is with the critical path method (CPM), which identifies a path of tasks in a project network that, when delayed, result in project delays. This work offers a complementary, stochastic approach to CPM that ranks tasks according to their effect on the project completion time distribution, when the distributions of task completion time are delayed. The new hybrid approach is based on the use of a Monte Carlo simulation and a multi-criteria decision analysis technique. Monte Carlo simulation allows for approximating the cumulative distribution function of the total duration of the project, while the multi-criteria decision analysis technique is used to compare and rank the tasks across percentiles of the resulting project completion time distributions. Doing so allows for different percentile weighting schemes to represent decision maker risk preferences. The suggested approach is applied to two project network examples. The examples illustrate that the proposed approach highlights some tasks as risky, which may not always lie on the critical path as identified by CPM. This is valuable for practicing managers as it allows them to properly consider their risk preferences when determining task criticality based on the distribution of project completion time (e.g., emphasizing median vs. upper tail completion time).     

A Novel Particle/Photon Detector Based on a Superconducting Proximity Array of Nanodots

The current frontiers in the investigation of high-energy particles demand for new detection methods. Higher sensitivity to low-energy deposition, high-energy resolution to identify events and improve the background rejection, and large detector masses have to be developed to detect even an individual particle that weakly interacts with ordinary matter. Here, we will describe the concept and the layout of a novel superconducting proximity array which show dynamic vortex Mott insulator to metal transitions, as an ultra-sensitive compact radiation-particle detector.     

Recommendation of RILEM Technical Committee 250-CSM: Test method for Textile Reinforced Mortar to substrate bond characterization

Textile Reinforced Mortar (TRM), also known as Fabric Reinforced Mortar or Fabric Reinforced Cementitious Matrix, composites are an emerging technology for the external repair and strengthening of existing structures. For most applications, the effectiveness of the TRM reinforcement relies on its bond performance. This recommendation identifies the best practice to characterize the bond behaviour of TRM. A shear bond test method is proposed to determine the peak axial stress (associated with the maximum load that can be transferred from the structural member to the externally bonded TRM reinforcement), the stress–slip relationship and the failure mode that controls the TRM-to-substrate load transfer capacity. Guidelines on specimen manufacturing, experimental setup, test execution, and determination of test results are provided.