26 resultados para digital forensic tool testing


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Silicon carbide (SiC) is a material of great technological interest for engineering applications concerning hostile environments where silicon-based components cannot work (beyond 623 K). Single point diamond turning (SPDT) has remained a superior and viable method to harness process efficiency and freeform shapes on this harder material. However, it is extremely difficult to machine this ceramic consistently in the ductile regime due to sudden and rapid tool wear. It thus becomes non trivial to develop an accurate understanding of tool wear mechanism during SPDT of SiC in order to identify measures to suppress wear to minimize operational cost.

In this paper, molecular dynamics (MD) simulation has been deployed with a realistic analytical bond order potential (ABOP) formalism based potential energy function to understand tool wear mechanism during single point diamond turning of SiC. The most significant result was obtained using the radial distribution function which suggests graphitization of diamond tool during the machining process. This phenomenon occurs due to the abrasive processes between these two ultra hard materials. The abrasive action results in locally high temperature which compounds with the massive cutting forces leading to sp3–sp2 order–disorder transition of diamond tool. This represents the root cause of tool wear during SPDT operation of cubic SiC. Further testing led to the development of a novel method for quantitative assessment of the progression of diamond tool wear from MD simulations.

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We demonstrate genuine three-mode nonlocality based on phase-space formalism. A Svetlichny-type Bell inequality is formulated in terms of the s-parametrized quasiprobability function. We test such a tool using exemplary forms of three-mode entangled states, identifying the ideal measurement settings required for each state. We thus verify the presence of genuine three-mode nonlocality that cannot be reproduced by local or nonlocal hidden variable models between any two out of three modes. In our results, GHZ- and W-type nonlocality can be fully discriminated. We also study the behavior of genuine tripartite nonlocality under the effects of detection inefficiency and dissipation induced by local thermal environments. Our formalism can be useful to test the sharing of genuine multipartite quantum correlations among the elements of some interesting physical settings, including arrays of trapped ions and intracavity ultracold atoms. DOI: 10.1103/PhysRevA.87.022123

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This paper presents a novel real-time power-device temperature estimation method that monitors the power MOSFET's junction temperature shift arising from thermal aging effects and incorporates the updated electrothermal models of power modules into digital controllers. Currently, the real-time estimator is emerging as an important tool for active control of device junction temperature as well as online health monitoring for power electronic systems, but its thermal model fails to address the device's ongoing degradation. Because of a mismatch of coefficients of thermal expansion between layers of power devices, repetitive thermal cycling will cause cracks, voids, and even delamination within the device components, particularly in the solder and thermal grease layers. Consequently, the thermal resistance of power devices will increase, making it possible to use thermal resistance (and junction temperature) as key indicators for condition monitoring and control purposes. In this paper, the predicted device temperature via threshold voltage measurements is compared with the real-time estimated ones, and the difference is attributed to the aging of the device. The thermal models in digital controllers are frequently updated to correct the shift caused by thermal aging effects. Experimental results on three power MOSFETs confirm that the proposed methodologies are effective to incorporate the thermal aging effects in the power-device temperature estimator with good accuracy. The developed adaptive technologies can be applied to other power devices such as IGBTs and SiC MOSFETs, and have significant economic implications. 

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The design of a high-performance IIR (infinite impulse response) digital filter is described. The chip architecture operates on 11-b parallel, two's complement input data with a 12-b parallel two's complement coefficient to produce a 14-b two's complement output. The chip is implemented in 1.5-µm, double-layer-metal CMOS technology, consumes 0.5 W, and can operate up to 15 Msample/s. The main component of the system is a fine-grained systolic array that internally is based on a signed binary number representation (SBNR). Issues addressed include testing, clock distribution, and circuitry for conversion between two's complement and SBNR.

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A novel digital image correlation (DIC) technique has been developed to track changes in textile yarn orientations during shear characterisation experiments, requiring only low-cost digital imaging equipment. Fabric shear angles and effective yarn strains are calculated and visualised using this new DIC technique for bias extension testing of an aerospace grade, carbon-fibre reinforcement material with a plain weave architecture. The DIC results are validated by direct measurement, and the use of a wide bias extension sample is evaluated against a more commonly used narrow sample. Wide samples exhibit a shear angle range 25% greater than narrow samples and peak loads which are 10 times higher. This is primarily due to excessive yarn slippage in the narrow samples; hence, the wide sample configuration is recommended for characterisation of shear properties which are required for accurate modelling of textile draping.

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Like any new technology, tidal power converters are being assessed for potential environmental impacts. Similar to wind power, where noise emissions have led to some regulations and limitations on consented installation sites, noise emissions of these new tidal devices attract considerable attention, especially due to the possible interaction with the marine fauna. However, the effect of turbine noise cannot be assessed as a stand-alone issue, but must be investigated in the context of the natural background noise in high flow environments. Noise measurements are also believed to be a useful tool for monitoring the operating conditions and health of equipment. While underwater noise measurements are not trivial to perform, this non-intrusive mon- itoring method could prove to be very cost effective. This paper presents sound measurements performed on the SCHOTTEL Instream Turbine as part of the MaRINET testing campaign at the QUB tidal test site in Portaferry during the summer of 2014. This paper demonstrates a comparison of the turbine noise emissions with the normal background noise at the test site and presents possible applications as a monitoring system.

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Cloud data centres are critical business infrastructures and the fastest growing service providers. Detecting anomalies in Cloud data centre operation is vital. Given the vast complexity of the data centre system software stack, applications and workloads, anomaly detection is a challenging endeavour. Current tools for detecting anomalies often use machine learning techniques, application instance behaviours or system metrics distribu- tion, which are complex to implement in Cloud computing environments as they require training, access to application-level data and complex processing. This paper presents LADT, a lightweight anomaly detection tool for Cloud data centres that uses rigorous correlation of system metrics, implemented by an efficient corre- lation algorithm without need for training or complex infrastructure set up. LADT is based on the hypothesis that, in an anomaly-free system, metrics from data centre host nodes and virtual machines (VMs) are strongly correlated. An anomaly is detected whenever correlation drops below a threshold value. We demonstrate and evaluate LADT using a Cloud environment, where it shows that the hosting node I/O operations per second (IOPS) are strongly correlated with the aggregated virtual machine IOPS, but this correlation vanishes when an application stresses the disk, indicating a node-level anomaly.

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Producing concrete with secondary raw materials is an excellent way to contribute to a moresustainable world, provided that this concrete has at least the same performance during itsservice life as concrete made with the primary raw materials it replaces. Secondary rawmaterials for Light Weight (LW) aggregates (rigid polyurethane foams, shredded tire rubberand mixed plastic scraps) have been combined with secondary raw materials for the binder(fly ash, slag and perlite tailings) making sustainable concretes that were investigated fortheir suitability as LW, highly insulating concrete for four different types of applications.Compliance to desired engineering properties (workability, setting time) was not alwaysfeasible: it was mostly the low workability of the mixtures that limited their application.Contrary to well established cements, steering the workability by adding water was not anoption for these binders that rely on alkali-activation. Eight successful mixtures have beentested further. The results have shown that it is possible to produce a non-structuralsustainable concrete with good mechanical and thermal insulation properties.Design of concrete made with novel materials is currently not feasible without extensiveexperimentation as no design rules exist other than empirically derived rules based ontraditional materials. As a radical different approach, a flexible concrete mix design has beendeveloped with which the concrete can be modelled in the fresh and hardened state. Thenumerical concrete mix design method proves a promising tool in designing concrete forperformance demands such as elasticity parameters and thermal conductivity

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Background: Identifying new and more robust assessments of proficiency/expertise (finding new "biomarkers of expertise") in histopathology is desirable for many reasons. Advances in digital pathology permit new and innovative tests such as flash viewing tests and eye tracking and slide navigation analyses that would not be possible with a traditional microscope. The main purpose of this study was to examine the usefulness of time-restricted testing of expertise in histopathology using digital images.
Methods: 19 novices (undergraduate medical students), 18 intermediates (trainees), and 19 experts (consultants) were invited to give their opinion on 20 general histopathology cases after 1 s and 10 s viewing times. Differences in performance between groups were measured and the internal reliability of the test was calculated.
Results: There were highly significant differences in performance between the groups using the Fisher's least significant difference method for multiple comparisons. Differences between groups were consistently greater in the 10-s than the 1-s test. The Kuder-Richardson 20 internal reliability coefficients were very high for both tests: 0.905 for the 1-s test and 0.926 for the 10-s test. Consultants had levels of diagnostic accuracy of 72% at 1 s and 83% at 10 s.
Conclusions: Time-restricted tests using digital images have the potential to be extremely reliable tests of diagnostic proficiency in histopathology. A 10-s viewing test may be more reliable than a 1-s test. Over-reliance on "at a glance" diagnoses in histopathology is a potential source of medical error due to over-confidence bias and premature closure.

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The paper addresses the quality of the interface and edge bonded joints in layers of cross-laminated timber (CLT) panels. The shear performance was studied to assess the suitability of two different adhesives, Polyurethane (PUR) and Phenol-Resorcinol-Formaldehyde (PRF), and to determine the optimum clamping pressure. Since there is no established testing procedure to determine the shear strength of the surface bonds between layers in a CLT panel, block shear tests of specimens in two different configurations were carried out, and further shear tests of edge bonded specimen in two configurations were performed. Delamination tests were performed on samples which were subjected to accelerated aging to assess the durability of bonds in severe environmental conditions. Both tested adhesives produced boards with shear strength values within the edge bonding requirements of prEN 16351 for all manufacturing pressures. While the PUR specimens had higher shear strength values, the PRF specimens demonstrated superior durability characteristics in the delamination tests. It seems that the test protocol introduced in this study for crosslam bonded specimens, cut from a CLT panel, and placed in the shearing tool horizontally, accurately reflects the shearing strength of glue lines in CLT.

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Schistosomiasis is a chronically debilitating helminth infection with a significant socio-economic and public health impact. Accurate diagnostics play a pivotal role in achieving current schistosomiasis control and elimination goals. However, many of the current diagnostic procedures, which rely on detection of schistosome eggs, have major limitations including lack of accuracy and the inability to detect pre-patent infections. DNA-based detection methods provide a viable alternative to the current tests commonly used for schistosomiasis diagnosis. Here we describe the optimisation of a novel droplet digital PCR (ddPCR) duplex assay for the diagnosis of Schistosoma japonicum infection which provides improved detection sensitivity and specificity. The assay involves the amplification of two specific and abundant target gene sequences in S. japonicum; a retrotransposon (SjR2) and a portion of a mitochondrial gene (nad1). The assay detected target sequences in different sources of schistosome DNA isolated from adult worms, schistosomules and eggs, and exhibits a high level of specificity, thereby representing an ideal tool for the detection of low levels of parasite DNA in different clinical samples including parasite cell free DNA in the host circulation and other bodily fluids. Moreover, being quantitative, the assay can be used to determine parasite infection intensity and, could provide an important tool for the detection of low intensity infections in low prevalence schistosomiasis-endemic areas.