Integrated Computer-Aided Engineering

In this paper, we present the design and performance analysis of an innovative system for tracking Automated Guided Vehicles (AGVs) in indoor industrial scenarios. An on-board odometer provides information about the dynamic state of the AGV, allowing to predict its pose (i.e., its position and orientation). At the same time, an external Ultra-Wide Band (UWB) wireless network provides the information necessary to compensate for the error drift accumulated by the odometer. Two novel alternative solutions for AGV tracking are proposed: (i) a classical Time Differences Of Arrivals (TDOA) approach with a single receiver; (ii) a "Twin-receiver" TDOA (TTDOA) approach, that requires the presence of two independent receivers on the AGV. The TTDOA configuration allows to indirectly estimate the orientation of the vehicle, thus increasing the estimation accuracy. Moreover, this allows direct estimation of the vehicle's movement even when the odometer is not working properly (e.g., temporary failure) or when the AGV is not moving (e.g., at the start-up). The system performance with the two proposed tracking algorithms is evaluated in realistic conditions, by considering a consolidated UWB channel model and a simple on-board energy detector receiver. The impact of the wireless network architecture and of the presence of moving obstacles is analyzed. The obtained results show clearly that the implementation of a tracking system with a sub-centimeter accuracy can be realized by means of low-complexity UWB receiver and commercial odometers. The automatic movement of goods within a warehouse is one of the most appealing application of the proposed tracking system.

Grammar-based compression is to find a small grammar that generates a given data and has been well-studied in text compression. In this paper, we apply this methodology to compression of rectangular image data. We first define a context-free rectangular image grammar (CFRIG) by extending the context-free grammar. Then we propose a quadsection type algorithm by extending a bisection type algorithm for grammar-based compression of text data. We show that our proposed algorithm approximates in polynomial time the smallest CFRIG within a factor of O(n)^4/3, where an input image data is of size O(n) × O(n). Furthermore, we practically improve the proposed algorithm by adding several rules concerning sub-images. We also present results on computational experiments on the proposed algorithms.

Cloud computing offers an economical and feasible solution for scientific workflow applications requiring large amounts of computational resources and expensive hardware. Supporting Cloud workflow execution involves: (i) allocating and composing a collection of Cloud resources, and (ii) coordinating distributed and self-interested participants. The contributions of this research are: (i) proposing an agent-based approach for supporting workflow execution in one or multiple Clouds, (ii) defining Petri-net based methodologies to design workflows and Cloud resources that sustain concurrent and parallel management of workflows, (iii) implementing an agent-based testbed to simulate distributed workflow execution, and (iv) providing empirical evidence to demonstrate the effectiveness and efficiency of agent-based Cloud workflow execution. The agents are endowed with distributed algorithms, e.g., contract net protocol, to allocate and compose Cloud resources based on workflow requirements. Simulation results demonstrated that: (i) Agents effectively executed (with a 100% success rate) workflows autonomously, even when dealing with concurrent workflow executions, (ii) task parallelization was efficiently achieved in randomly created workflows with different levels of parallelism and ordering constraints, (iii) workflow execution was efficiently achieved since the makespan and number of messages exchanged increased linearly with the number of tasks.

Recently, the attention on electric vehicle (EV)/plug-in hybrid electric vehicle (PHEV) has been growing. The EV/PHEV will be one of important electric loads from the viewpoint of smart grid in near future. It is anticipated that the EV/PHEV will affect the load pattern of power grids. For this reason, the effective management of the EV/PHEV based on the information and communications technologies will be a major function of smart grid. For EV/PHEV applications, a user interface device equipped on EVs/PHEVs allows the driver to receive instructions or seek advice to manage EV's/PHEV's battery charging/discharging process. In this paper, we present a design of vehicle-grid communications system. To improve the performance of the system, we customize our communication protocol for distributing EV/PHEV's charging information reliably. Also, we model a one-step ahead nonlinear predictor of the charge or discharge price using a neural network ensemble technique. In the experiments, we verify the performance of our protocol with respect to the data delivery ratio and the number of message forwarding. We also compare the price prediction accuracy using the real energy price data, compared with the conventional methods.

Although we have many electric devices at home, there are just few systems to evaluate, monitor and control them. Sometimes users go out and leave their electric devices turned on what can cause energy wasting and dangerous situations. Therefore most of the users may want to know the using states of their electrical appliances through their mobile devices in a pervasive way. In this paper, we propose an Intelligent Supervisory Control System to evaluate, monitor and control the use of electric devices in home, from outside. Because of the transferring data to evaluate, monitor and control user's location and state of home (ex. nobody at home) may be opened to attacks leading to dangerous situations. In our model we include a location privacy module and encryption module to provide security to user location and data. Intelligent Supervising Control System gives to the user the ability to manage electricity loads by means of a multi-agent system involving evaluation, monitoring, control and energy resource agents

Digital watermarking techniques have been proposed for copyright protection and multimedia data authentication. The achieved tradeoffs from these techniques between imperceptibility and robustness are always controversial. This paper proposes the application of Discrete Wavelet Transform (DWT) into image watermarking by using Particle Swarm Optimization (PSO) which is an evolutionary technique with the stochastic, population-based algorithm for solving this problem. To protect copyright information of digital images, the original image is decomposed according to two-dimensional discrete wavelet transform. Subsequently the preprocessed watermark with an affined scrambling transform is optimal embedded into the vertical subband (HL_m) coefficients in wavelet domain without compromising the quality of the image. In the optimal process, the scaling factors are trained with the assistance of PSO. Furthermore, a novel algorithmic framework is proposed via a forecasted feasibility of the approach to parameters evaluation of hypothesized watermarked images in DWT domain. Simulation results show that the proposed watermarking procedure has better performances in imperceptibility and robustness under various distortions in the comparison of the previous scheme.

In this paper, we investigate how the Semantic Web can enhance web navigation and accessibility by following a hybrid approach of document-oriented and data-oriented considerations. Precisely, we propose a methodology for specifying, extracting, and presenting semantic data embedded in (X)HTML documents with RDFa in order to enable and improve ubiquitous web navigation and accessibility for end-users. In our context, embedded data does not only contain data type property annotations, but also object properties for interlinking, and embedded domain knowledge for enhanced content navigation through ontology reasoning. We provide a prototype implementation, called Semantic Web Component (SWC) and evaluate our methodology along a concrete scenario for mobile devices and with respect to precision, performance, network traffic, and usability. Evaluation results suggest that our approach decreases network traffic as well as the amount of information presented to a user without requiring significantly more processing time, and that it allows creating a satisfactory navigation experience.