http://hdl.handle.net/10316/27708 Sat, 07 Mar 2020 13:55:03 GMT 2020-03-07T13:55:03Z http://hdl.handle.net/10316/87656 Title: A survey of real locomotion techniques for immersive virtual reality applications on head-mounted displays Authors: Cardoso, Jorge C.S.; Perrotta, André Abstract: Locomotion is a fundamental activity in Virtual Reality (VR) and has been the focus of a large body of research since the implementation of the first systems. In real locomotion techniques, users physically move in the real world to affect movement in the Virtual Environment (VE). Real locomotion has been found to perform better than other forms of locomotion for many tasks. To overcome the challenges imposed by restricted physical space, researchers have devised ingenious interaction techniques for real locomotion. In this paper, we present a survey of interaction techniques for real locomotion in VR. Our analysis is focused on the interaction techniques – the combination of devices, user’s actions, and system’s responses. We categorize interaction techniques for real locomotion in VR into: unmediated, warnings, reorientation/resetting, scaling, redirection, and dynamic VE. These categories represent fundamentally different approaches to real locomotion and user action feedback. We further characterize techniques in each of these categories according to category-specific parameters. Finally, it is important to state that this paper was developed with the aim of helping newcomers to the field to understand and implement the techniques here presented. Tue, 01 Jan 2019 00:00:00 GMT http://hdl.handle.net/10316/87656 2019-01-01T00:00:00Z http://hdl.handle.net/10316/87225 Title: Financial credit risk assessment via learning-based hashing Authors: Ribeiro, Bernardete Martins; Chen, Ning Abstract: With the increasing amount of financial data produced today, the problem of finding the k-nearest neighbors to the query point in high-dimensional space is itself of importance to access the financial credit risk. Binary embeddings are efficient tools of indexing big datasets for financial credit risk analysis. The idea is to find a good hash function such that similar data points in Euclidean space preserve their similarities in the Hamming space for fast data retrieval. By exploring out-of-sample extension to test data it is possible to set forth a go-forward strategy to establish a fast retrieval model of companies' status thereby rendering the stakeholders' evaluation task very efficiently. First, we use semi-supervised learning-based hashing to take into account the pairwise information for constructing the weight adjacency graph matrix needed or building the binarised Laplacian EigenMap. Second, we train a generalised regression neural network (GRNN) to learn the k-bits hash function. Third, the k-bit binary code for the test data is efficiently found in the recall phase. Experimental results on financial data demonstrated the proposed approach showed the applicability and advantages of learning-based hashing to credit risk assessment. Sun, 01 Jan 2017 00:00:00 GMT http://hdl.handle.net/10316/87225 2017-01-01T00:00:00Z http://hdl.handle.net/10316/84963 Title: A stealth monitoring mechanism for cyber-physical systems Authors: Graveto, Vitor; Rosa, Luis; Cruz, Tiago José dos Santos Martins da; Simões, Paulo Abstract: Supervisory Control and Data Acquisition (SCADA) systems, which are often used in several types of Essential Systems and Critical Infrastructures, depend on control devices such as Programmable Logic Controllers, Remote Terminal Units and Intelligent Electronic Devices. Such devices, which are deployed at the edge of the SCADA infrastructure, directly interface with the physical processes under control. They are often based on embedded systems with limited capabilities and exposed to significant security and safety-related risks, as demonstrated by past incidents such as Stuxnet. However, despite the recognized relevance of those edge devices, they usually lack monitoring mechanisms able to detect device anomalies and/or cyber-physical threats. In this paper we propose a novel approach for stealth monitoring of those control devices, for purposes of security and safety management. This approach builds on cost-effective probes, which we designate as Shadow Security Units (SSU), directly attached to the monitored control devices. This privileged positioning enables the direct and fine-grained observation of both physical inputs/outputs (i.e. the physical processes under control) and network communication flows -- allowing the exploitation of various novel monitoring approaches able to address sophisticated security threats not noticeable otherwise. Moreover, the SSU approach is not limited to SCADA scenarios, being also applicable to similar domains such as the Internet of Things (IoT), Avionics and Self-Driving systems. Mon, 22 Oct 2018 00:00:00 GMT http://hdl.handle.net/10316/84963 2018-10-22T00:00:00Z http://hdl.handle.net/10316/84959 Title: Virtualizing Programmable Logic Controllers: Toward a Convergent Approach Authors: Cruz, Tiago; Simoes, Paulo; Monteiro, Edmundo Abstract: Modern Programmable Logic Controllers (PLCs) are pervasive components in Industrial Control Systems (ICS) such as Supervisory Control and Data Acquisition (SCADA), designed to control industrial processes autonomously or as part of a distributed system topology. Its success may be explained by its robustness and reliability, being one of the most enduring legacies on modern ICS, despite having evolved very little over the last years. This paper proposes an x86-based virtual PLC (vPLC) architecture that decouples the logic and control capabilities from the I/O components, while virtualizing the PLC logic within a real-time hypervisor. To demonstrate the feasibility of this concept, the topic of real-time virtualization for x86 platforms is analyzed, together with an evaluation study of the properties of real-time workloads in partitioned hypervisor environments. Mon, 12 Sep 2016 00:00:00 GMT http://hdl.handle.net/10316/84959 2016-09-12T00:00:00Z