Design and Analysis of a Novel 3D Decoupled Manipulator Based on Compliant Pantograph for Micromanipulation

A novel 3D compliant manipulator for micromanipulation is introduced based on pantograph linkage. The proposed manipulator provides decoupled 3DOF translational motions. The key design feature is the use of parallelograms, which maintain the orientation of the end-effector fixed. The proposed manipulator provides advantages over its counterparts in the literature. It has significantly higher workspace to size ratio if its pantograph acts as a magnification device. On the other hand, it has higher resolution if its pantograph acts as a miniaturizing device. This provides great flexibility in the design process to account for the limited variety of the micro-actuators and the large variety of the micro-scale tasks in terms of workspace and resolution. Thus, the proposed system possesses the characteristics of gearing (speed up or speed down). A suitable choice of flexure hinges and material is done. The position and velocity kinematic analysis are carried out. Analytical expressions are derived for singularity-free-workspace boundaries in terms of physical constraints of the flexure joints. Dexterity analysis is performed to evaluate the design performance. A synthesis methodology of the proposed manipulator is developed. A finite element analysis is carried out and a prototype is manufactured to validate the conceptual design. Simulation and experimental results have successfully demonstrated the linearity and consistency between input and output displacements with acceptable parasitic motions. Moreover, the manipulability of the proposed manipulator is found to be configuration independent. Also, the manipulator could have isotropic performance over its workspace for certain actuator setup.     

Segmented OTA Platform Over ICN Vehicular Networks

Mobile Networks and Applications - The Internet Protocol (IP) architecture could not fully satisfy the Vehicular Ad-hoc Networks (VANETs) needed efficiency, due to their dynamic topology and high...     

Coupled Visual and Kinematic Manifold Models for Tracking

In this paper, we consider modeling data lying on multiple continuous manifolds. In particular, we model the shape manifold of a person performing a motion observed from different viewpoints along a view circle at a fixed camera height. We introduce a model that ties together the body configuration (kinematics) manifold and visual (observations) manifold in a way that facilitates tracking the 3D configuration with continuous relative view variability. The model exploits the low-dimensionality nature of both the body configuration manifold and the view manifold, where each of them are represented separately. The resulting representation is used for tracking complex motions within a Bayesian framework, in which the model provides a low-dimensional state representation as well as a constrained dynamic model for both body configuration and view variations. Experimental results estimating the 3D body posture from a single camera are presented for the HUMANEVA dataset and other complex motion video sequences.     

Text to multi-level MindMaps

MindMapping (Tony Buzan and Harrison, 2010) is a well-known technique for note-taking, which encourages learning and studying. MindMapping has been manually adopted to help present knowledge and concepts in a visual form. Unfortunately, there is no reliable automated approach to generate MindMaps from Natural Language text. This work firstly introduces the MindMap Multi-level Visualization concept that jointly visualize and summarize textual information. The visualization is achieved pictorially across multiple levels using semantic information (i.e. ontology), while the summarization is achieved by the information in the highest levels as they represent abstract information in the text. This work also presents the first automated approach that takes a text input and generates a MindMap visualization out of it. The approach could visualize text documents in multi-level MindMaps, in which a high-level MindMap node could be expanded into child MindMaps. The proposed method involves understanding of the input text and converting it into intermediate Detailed Meaning Representation (DMR). The DMR is then visualized with two modes; Single level or Multiple levels, which is convenient for larger text. The generated MindMaps from both approaches were evaluated based on human subject experiments performed on Amazon Mechanical Turk with various parameter settings.     

Al0.3Ga0.7As/GaAs concentrator solar cells

An Al_0.3Ga_0.7As/GaAs tandem solar cell was fabricated in a commercial reactor which has been specially modified for dual operation of both atomic layer epitaxy (ALE) and metalorganic chemical vapor deposition (MOCVD) growth modes. The p-type and n-type dopants were carbon and silicon, respectively, and the required doping concentrations were achieved by optimizing growth conditions such as V/III ratio (mole ratio of group V atoms to group III atoms), exposure times to reactant gases, and growth temperatures. The current-voltage (I–V) characteristics indicate that, up to 53 Suns, the tunnel junction does not seem to result in any appreciable deterioration in the multijunction solar cell's performance. The measured efficiency increases with increasing solar concentration up to a point where a region of negative resistance starts to appear in the I–V characteristics.     

Formalizing and appling compliance patterns for business process compliance

Today’s enterprises demand a high degree of compliance of business processes to meet diverse regulations and legislations. Several industrial studies have shown that compliance management is a daunting task, and organizations are still struggling and spending billions of dollars annually to ensure and prove their compliance. In this paper, we introduce a comprehensive compliance management framework with a main focus on design-time compliance management as a first step towards a preventive lifetime compliance support. The framework enables the automation of compliance-related activities that are amenable to automation, and therefore can significantly reduce the expenditures spent on compliance. It can help experts to carry out their work more efficiently, cut the time spent on tedious manual activities, and reduce potential human errors. An evident candidate compliance activity for automation is the compliance checking, which can be achieved by utilizing formal reasoning and verification techniques. However, formal languages are well known of their complexity as only versed users in mathematical theories and formal logics are able to use and understand them. However, this is generally not the case with business and compliance practitioners. Therefore, in the heart of the compliance management framework, we introduce the Compliance Request Language (CRL), which is formally grounded on temporal logic and enables the abstract pattern-based specification of compliance requirements. CRL constitutes a series of compliance patterns that spans three structural facets of business processes; control flow, employed resources and temporal perspectives. Furthermore, CRL supports the specification of compensations and non-monotonic requirements, which permit the relaxation of some compliance requirements to handle exceptional situations. An integrated tool suite has been developed as an instantiation artefact, and the validation of the approach is undertaken in several directions, which includes internal validity, controlled experiments, and functional testing.     

Homeomorphic Manifold Analysis (HMA): Generalized separation of style and content on manifolds

The problem of separation of style and content is an essential element of visual perception, and is a fundamental mystery of perception. This problem appears extensively in different computer vision applications. The problem we address in this paper is the separation of style and content when the content lies on a low-dimensional nonlinear manifold representing a dynamic object. We show that such a setting appears in many human motion analysis problems. We introduce a framework for learning parameterization of style and content in such settings. Given a set of topologically equivalent manifolds, the Homeomorphic Manifold Analysis (HMA) framework models the variation in their geometries in the space of functions that maps between a topologically-equivalent common representation and each of them. The framework is based on decomposing the style parameters in the space of nonlinear functions that map between a unified embedded representation of the content manifold and style-dependent visual observations. We show the application of the framework in synthesis, recognition, and tracking of certain human motions that follow this setting, such as gait and facial expressions.