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We consider the multivariate linear regression model with shuffled data and additive noise, which arises in various correspondence estimation and matching problems. We focus on the denoising problem and characterize the minimax error rate up to logarithmic factors. We also analyze the performance of two versions of a computationally efficient estimator that are consistent for a large range of input...
In the era of E-Learning, most research on learner model is focused on the analysis of learning-related data, but ignored the analysis of the multidimensional data and relationship among them. This will make it difficult to constructing dynamic, real-time and accurate learner model. However, in the era of U-Learning, the learning device has powerful ability of sensing the context awareness. With these...
Virtual testing can improve safety and quality of driver assistance systems. However, for the accuracy of the whole simulation, the realism of the virtual sensors is crucial. This paper describes a method for simulating an automotive FMCW radar from the wave transmission up to the intermediate frequency signal. The wave propagation is simulated using geometrical optics and ray launching. To obtain...
Participatory sensing is a rising paradigm which utilizes mobile phones to collect data and build application on the cloud. But there are many problems to be resolved, poor quality of received information caused by task executors has been one of them. So incentive mechanism is essential for attracting users to participate in and submit high-quality data. Inspired by contract theory, we model participatory...
This paper introduces a novel paradigm for resource management in distributed systems, called decision-driven execution. The paradigm is appropriate for mission-driven systems, where the goal is to enable faster, leaner, and more effective decision making. All resource consumption, in this paradigm, is tied to the needs of making decisions on alternative courses of action. A point of departure from...
Future Advanced Driver Assistance Systems (ADAS) need to create an accurate model of the environment. Accordingly, an enormous amount of data has to be fused and processed. From this data, information such as the positions of the vehicles, has to be extracted out of the model, e.g., to create a convoy track. Common architectures used today, like single-core processors in automotive Electronic Control...
This paper presents a fixed-wing autopilot code base called ROSplane. ROSplane utilizes the ROSflight board, firmware, and driver, which was developed to make autopilot development faster, easier and cheaper. By leveraging a textbook and university course content, the autopilot facilitates education and accelerates research and development. The textbook provides high-level documentation for the code...
The rapid growth of sensor-embedded smartphones has led to a new data sensing and collecting paradigm, known as crowdsensing. Many auction-based incentive mechanisms have been proposed to stimulate smartphone users to participate in crowdsensing. However, none of them have taken into consideration the Sybil attack where a user illegitimately pretends multiple identities to gain benefits. This attack...
Mobile sensor networks (MSNs) enable extensive applications of data collection, such as accident report in transportation and health prediction in public health. Incentive mechanism (IM) is applied for sensing user (SU) recruitment. However, the IM used in traditional MSN is not efficient due to limited information of SU used for recruitment. With the development of cloud computing technology, cloud-based...
In the Era of the Internet of Things (IoT) the validity of sensing coverage is of utmost importance as it affects the reliability of sensing services. The presence of anchor misplacement poses a challenge on the validity of sensing coverage. This kind of challenge has generally been overlooked in sensing coverage research. In this paper, we investigate the sensing validity under several scenarios...
Fog computing provides a decentralized approach to data processing and resource provisioning in the Internet of Things (IoT). Particular challenges of adopting fog-based computational resources are the adherence to geographical distribution of IoT data sources, the delay sensitivity of IoT services, and the potentially very large amounts of data emitted and consumed by IoT devices. Despite existing...
In this paper the design of a Soft Sensor to estimate the sulphur concentration in a desulphuring unit of a refinery operating in Sicily is described. In particular the problem of the input variables selection is addressed by comparing two different methods. The first method is based on the generalization of the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm to nonlinear models...
Automotive Machine Type Communication (MTC) features three groups of applications: safety, road traffic efficiency and infotainment. The concrete set of automotive applications is yet uncertain. This application uncertainty and, thus communication traffic uncertainty, directly translates into the need for a highly flexible traffic model. Traffic model is required in order to chose appropriate communication...
Cyber-Physical Systems (CPSs) represent a new generation of engineered systems facing significant scientific challenges in terms of modeling, architecture, distributed computations and network control, verification/validation mechanisms, and many others. CPSs modeling, a significant aspect of their design and development, can be performed using the Model-Driven Engineering (MDE) paradigm. This approach...
With the ubiquitous deployment of the mobile devices with increasingly better communication and computation capabilities, an emerging model called spatial crowdsourcing is proposed to solve the problem of unstructured big data by publishing location-based tasks to participating workers. However, massive spatial data generated by spatial crowdsourcing entails a critical challenge that the system has...
In this paper we present a novel joint approach for optimising surface curvature and pose alignment. We present two implementations of this joint optimisation strategy, including a fast implementation that uses two frames and an offline multi-frame approach. We demonstrate an order of magnitude improvement in simulation over state of the art dense relative point-to-plane Iterative Closest Point (ICP)...
Leak or fault detection in the energy and fluids utilities distribution networks represents a topic with important implications, where the safety of life and pollution are the covered priorities. Scientific literature and industry practices include dedicated solutions, suggested by theory and verified by actual use over long periods. Beginning with some of them, this article suggests and improves...
Urea based selective catalytic reduction (SCR) control strategies regulate urea dosing in diesel powertrains with the goal of achieving NOx emissions targets while being robust to transient disturbances such as exhaust temperature. A model based approach is typically pursued, where an estimated quantity of NH3 stored on the SCR catalyst is controlled to a temperature dependent setpoint. The choice...
We propose an equation free control method to control dissipative distributed parameter systems, in which the dynamics of the system are unknown while the effect of the control action is. A static observer is used to estimate the state using proper orthogonal decomposition (POD) so that a complete profile of the system can be estimated when a limited number of point sensors are available. Sensor locations...
Industry 4.0 aims to dramatically enhance the productivity of manufacturing technologies through the collection and analysis of real-time data. This combines the ubiquity of the IoT with the processing capabilities of cloud computing to generate insights that help to optimize the decision making process. The increasing demand of data and the explosion in the number of sensing devices, which might...
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