94 resultados para SLAM RGB-D SlamDunk Android 3D mobile


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With over 50 billion downloads and more than 1.3 million apps in Google’s official market, Android has continued to gain popularity amongst smartphone users worldwide. At the same time there has been a rise in malware targeting the platform, with more recent strains employing highly sophisticated detection avoidance techniques. As traditional signature based methods become less potent in detecting unknown malware, alternatives are needed for timely zero-day discovery. Thus this paper proposes an approach that utilizes ensemble learning for Android malware detection. It combines advantages of static analysis with the efficiency and performance of ensemble machine learning to improve Android malware detection accuracy. The machine learning models are built using a large repository of malware samples and benign apps from a leading antivirus vendor. Experimental results and analysis presented shows that the proposed method which uses a large feature space to leverage the power of ensemble learning is capable of 97.3 % to 99% detection accuracy with very low false positive rates.

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The battle to mitigate Android malware has become more critical with the emergence of new strains incorporating increasingly sophisticated evasion techniques, in turn necessitating more advanced detection capabilities. Hence, in this paper we propose and evaluate a machine learning based approach based on eigenspace analysis for Android malware detection using features derived from static analysis characterization of Android applications. Empirical evaluation with a dataset of real malware and benign samples show that detection rate of over 96% with a very low false positive rate is achievable using the proposed method.

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The majority of children in our society are loved andcherished. The occasional cases of intentional injury to a childresulting in death or significant harm evoke powerful anduncomfortable feelings (Devaney et al, 2013), and the publicoutcry may result in health and social workers facing criticism.Identifying whether an infant is at risk of abuse is a challengefor practitioners, and can be a source of stress and anxiety(Brandon et al, 2011). Bruising is a strong indicator of childabuse involving intentional injury (Kemp et al, 2014). Theincidence of bruising correlates to developmental stage, withnon-mobile infants least likely to incur bruising. Therefore, itspresence in pre-mobile infants requires immediate assessment.A search of the literature around bruising in pre-mobile infantsrevealed themes of missed opportunities for early intervention,the role of the father in the family and the significance of childdevelopment. Sharing of knowledge and expertise within themultidisciplinary team is key to safeguarding infants.

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Fishing is well known to curtail the size distribution of fish populations. This paper reports the discovery of small-scale spatial patterns in length appearing in several exploited species of Celtic Sea demersal 'groundfish'. These patterns match well with spatial distributions of fishing activity, estimated from vessel monitoring records taken over a period of 6 years, suggesting that this 'mobile' fish community retains a persistent impression of local-scale fishing pressure. An individual random-walk model of fish movement best matched these exploitation 'footprints' with individual movement rates set to <35 km per year. We propose that Celtic Sea groundfish may have surprisingly low movement rates for much of the year, such that fishing impact is spatially heterogeneous and related to local fishing intensity.

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As an emerging hole-machining methodology, helical milling process has become increasingly popular in aeromaterials manufacturing research, especially in areas of aircraft structural parts, dies, and molds manufacturing. Helical milling process is highly demanding due to its complex tool geometry and the progressive material failure on the workpiece. This paper outlines the development of a 3D finite element model for helical milling hole of titanium alloy Ti-6Al-4V using commercial FE code ABAQUS/Explicit. The proposed model simulates the helical milling hole process by taking into account the damage initiation and evolution in the workpiece material. A contact model at the interface between end-mill bit and workpiece has been established and the process parameters specified. Furthermore, a simulation procedure is proposed to simulate different cutting processes with the same failure parameters. With this finite element model, a series of FEAs for machined titanium alloy have been carried out and results compared with laboratory experimental data. The effects of machining parameters on helical milling have been elucidated, and the capability and advantage of FE simulation on helical milling process have been well presented.

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Free-roaming dogs (FRD) represent a potential threat to the quality of life in cities from an ecological, social and public health point of view. One of the most urgent concerns is the role of uncontrolled dogs as reservoirs of infectious diseases transmittable to humans and, above all, rabies. An estimate of the FRD population size and characteristics in a given area is the first step for any relevant intervention programme. Direct count methods are still prominent because of their non-invasive approach, information technologies can support such methods facilitating data collection and allowing for a more efficient data handling. This paper presents a new framework for data collection using a topological algorithm implemented as ArcScript in ESRI® ArcGIS software, which allows for a random selection of the sampling areas. It also supplies a mobile phone application for Android® operating system devices which integrates Global Positioning System (GPS) and Google Maps™. The potential of such a framework was tested in 2 Italian regions. Coupling technological and innovative solutions associated with common counting methods facilitate data collection and transcription. It also paves the way to future applications, which could support dog population management systems.

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Bone tissue engineering may provide an alternative to autograft, however scaffold optimisation is required to maximize bone ingrowth. In designing scaffolds, pore architecture is important and there is evidence that cells prefer a degree of non-uniformity. The aim of this study was to compare scaffolds derived from a natural porous marine sponge (Spongia agaricina) with unique architecture to those derived from a synthetic polyurethane foam. Hydroxyapatite scaffolds of 1 cm3 were prepared via ceramic infiltration of a marine sponge and a polyurethane (PU) foam. Human foetal osteoblasts (hFOB) were seeded at 1x105 cells/scaffold for up to 14 days. Cytotoxicity, cell number, morphology and differentiation were investigated. PU-derived scaffolds had 84-91% porosity and 99.99% pore interconnectivity. In comparison marine sponge-derived scaffolds had 56-61% porosity and 99.9% pore interconnectivity. hFOB studies showed that a greater number of cells were found on marine sponge-derived scaffolds at than on the PU scaffold but there was no significant difference in cell differentiation. X-ray diffraction (XRD) and inductively coupled plasma mass spectrometry (ICP-MS) showed that Si ions were released from the marine-derived scaffold. In summary, three dimensional porous constructs have been manufactured that support cell attachment, proliferation and differentiation but significantly more cells were seen on marine-derived scaffolds. This could be due both to the chemistry and pore architecture of the scaffolds with an additional biological stimulus from presence of Si ions. Further in vivo tests in orthotopic models are required but this marine-derived scaffold shows promise for applications in bone tissue engineering.

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In order to protect user privacy on mobile devices, an event-driven implicit authentication scheme is proposed in this paper. Several methods of utilizing the scheme for recognizing legitimate user behavior are investigated. The investigated methods compute an aggregate score and a threshold in real-time to determine the trust level of the current user using real data derived from user interaction with the device. The proposed scheme is designed to: operate completely in the background, require minimal training period, enable high user recognition rate for implicit authentication, and prompt detection of abnormal activity that can be used to trigger explicitly authenticated access control. In this paper, we investigate threshold computation through standard deviation and EWMA (exponentially weighted moving average) based algorithms. The result of extensive experiments on user data collected over a period of several weeks from an Android phone indicates that our proposed approach is feasible and effective for lightweight real-time implicit authentication on mobile smartphones.

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Recent measurements using an X-ray Free Electron Laser (XFEL) and an Electron Beam Ion Trap at the Linac Coherent Light Source facility highlighted large discrepancies between the observed and theoretical values for the Fe XVII 3C/3D line intensity ratio. This result raised the question of whether the theoretical oscillator strengths may be significantly in error, due to insufficiencies in the atomic structure calculations. We present time-dependent spectral modeling of this experiment and show that non-equilibrium effects can dramatically reduce the predicted 3C/3D line intensity ratio, compared with that obtained by simply taking the ratio of oscillator strengths. Once these non-equilibrium effects are accounted for, the measured line intensity ratio can be used to determine a revised value for the 3C/3D oscillator strength ratio, giving a range from 3.0 to 3.5. We also provide a framework to narrow this range further, if more precise information about the pulse parameters can be determined. We discuss the implications of the new results for the use of Fe XVII spectral features as astrophysical diagnostics and investigate the importance of time-dependent effects in interpreting XFEL-excited plasmas.

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In this paper, we describe how the pathfinder algorithm converts relatedness ratings of concept pairs to concept maps; we also present how this algorithm has been used to develop the Concept Maps for Learning website (www.conceptmapsforlearning.com) based on the principles of effective formative assessment. The pathfinder networks, one of the network representation tools, claim to help more students memorize and recall the relations between concepts than spatial representation tools (such as Multi- Dimensional Scaling). Therefore, the pathfinder networks have been used in various studies on knowledge structures, including identifying students’ misconceptions. To accomplish this, each student’s knowledge map and the expert knowledge map are compared via the pathfinder software, and the differences between these maps are highlighted. After misconceptions are identified, the pathfinder software fails to provide any feedback on these misconceptions. To overcome this weakness, we have been developing a mobile-based concept mapping tool providing visual, textual and remedial feedback (ex. videos, website links and applets) on the concept relations. This information is then placed on the expert concept map, but not on the student’s concept map. Additionally, students are asked to note what they understand from given feedback, and given the opportunity to revise their knowledge maps after receiving various types of feedback.

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Android OS supports multiple communication methods between apps. This opens the possibility to carry out threats in a collaborative fashion, c.f. the Soundcomber example from 2011. In this paper we provide a concise definition of collusion and report on a number of automated detection approaches, developed in co-operation with Intel Security.