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This paper focuses on target motion analysis by fusion of information from two moving acoustic sensors. These two sensors may obtain small measurements in order to make quick analysis of moving targets. In this situation, conventional approaches often fail to find accurate motion of targets. In this paper, a fusion algorithm for target motion analysis designed to handle this situation is proposed...
The Air Force is shifting its cybersecurity paradigm from an information technology (IT)-centric toward a mission oriented approach. Instead of focusing on how to defend its IT infrastructure, it seeks to provide mission assurance by defending mission relevant cyber terrain enabling mission execution in a contested environment. In order to actively defend a mission in cyberspace, efforts must be taken...
Compared to conventional processors, stochastic computing architectures have strong potential to speed up computation time and to reduce power consumption. We present such an architecture, called Bayesian Machine (BM), dedicated to solving Bayesian inference problems. Given a set of noisy signals provided by low-level sensors, a BM estimates the posterior probability distribution of an unknown target...
Wireless Sensor Networks present several advantages when compared to wired ones, among them, the low consumption and simplicity of installation. In some cases, energy consumption may be so low as to allow the use of energy harvesting techniques, as in the case of EnOcean protocol. In other networks, it is necessary to meet specific requirements, such as in industrial ones, where communication must...
Current solutions for sensor-cloud integration do not offer tools or platforms providing both efficient data management and standardized interfaces for the development of WSN-based applications on a shared infrastructure. This paper proposes a new architecture based on the paradigm of Service-Oriented Computing and virtualization of sensors for efficient management of heterogeneous WSNs data. The...
Hardware-in-the-Loop Simulation is being increasingly used in verification and validation of embedded computer systems; as well as for rapid prototyping and validation of models. The numerous benefits of this technique and the possibility of widespread use is hindered by the high cost of the necessary infrastructure. The proposed solution is based on a PC executing the plant simulation and connected,...
In this paper, we review the main middleware re-quirements applied to Internet of Things and High-Performance Computing combined, here called IoT/HPC. The goal was to describe a unique set of requirements that middleware systems should attempt to guarantee the development of integrated applications. Among many core complex services, the IoT/HPC challenges are related to the support of sensing, actuating,...
Model based tracking techniques allow computing the pose of 3d objects without needing to use markers. In order to perform a precise tracking, these techniques have been using RGB-D sensors together with particle filters for evaluating several pose hypotheses of the object in a given frame from features such as points 3D coordinates, color and normal vector. This work presents a proposal to use of...
Recognition of human actions is an intelligent way for human-machine communication and Radial basis function (RBF) models are among the most powerful machines on this task. One prerequisite of using this traditional model is that the movement data must be translated into a vector space via the feature extraction process. Recent development of the convolutional neural networks (CNNs) has been shown...
Today's data centers, their handheld computers and network sensors, are discussed in terms of how they are penetrated by viruses and rootkits. This paper then presents a new computer architecture, implemented to be semantically compatible with an existing microprocessor, along with modification of several system components commonly found in data centers. The new computer architecture physically separates...
A multi-beam LiDAR scheme based on an integrated star coupler is proposed. The architecture allows for acquisition of multiple scanning directions within a single pulse repetition interval, enabling multi-target detection and tracking, thus combining the advantages of flash and scanning LiDAR.
Compressive sensing originates in the field of signal processing and has recently become a topic of energy-efficient data gathering in wireless sensor networks. In this paper, we introduce a distributed compressive sensing approach, which utilizes spatial correlation among sensor nodes to group them into coalitions. The coalition formation method is represented by a block diagonal measurement matrix...
Data or measurement-to-track association is an integral and expensive part of any solution performing multi-target multi-sensor Cooperative Localization (CL) for better state estimation. Various performance evaluations have been performed between various state-of-the-art solutions, but they have been often limited within same family of algorithms. However, there exist solutions which avoid the task...
Mapping is a very critical issue for enabling autonomous driving. This paper proposes a robust approach to generate high definition maps based on LIDAR point clouds and post-processed localization measurements. Many problems are addressed including quality, saving size, global labeling and processing time. High quality is guaranteed by accumulating and killing the sparsity of the point clouds in a...
Due to much imperfect detection performance of onboard sensors in dense driving scenarios, the accurate and explicit perception of surrounding objects for Advanced Driver Assistance Systems and Autonomous Driving is challenging. This paper proposes a novel detection-level fusion approach for multi-object perception in dense traffic environment based on evidence theory. In order to remove uninterested...
We are living in an ageing population with an escalation in chronic illnesses including dementia and other age related diseases. People living with dementia often continue to live at home and are supported by caregivers and next of kin. It is often important to monitor the wellbeing of people living with dementia in order to measure their level of independence and to provide proper support at the...
In this paper, we propose and evaluate the application of unsupervised machine learning to anomaly detection for a Cyber-Physical System (CPS). We compare two methods: Deep Neural Networks (DNN) adapted to time series data generated by a CPS, and one-class Support Vector Machines (SVM). These methods are evaluated against data from the Secure Water Treatment (SWaT) testbed, a scaled-down but fully...
In the age of Internet of Things (IoT), sensors form a foundational component of IoT services, yet they are rigid with little capability for programmable configuration or reusability as they are application-specific, manufacturer-specific. Emerging IoT applications often deploy a vast number of sensors which may serve multiple applications. Programmability is thus essential but not found in legacy...
In order to navigate a robotic base in an unfamiliar environment, some mechanisms to detect positioning and location must be provided. When the base is in the process of navigation and makes use of these mechanisms, errors originating from the environment and base are inserted into the system, resulting in an erroneous position estimation. One relevant approach to reduce the error amplitude is to...
Interaction with non-rigid objects poses a challenge for manufacturing systems. The dimensions, locations and physical properties of soft-tissue objects like fruit or meat are subject to considerable variation and uncertainty. Possible ways to accommodate this are to use a number of different types of sensors and actors. However, a control system physically located next to a manufacturing system is...
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