Need For Extensive Measurements Research Articles

Ontology-guided attribute learning to accelerate certification for developing new printing processes

Identifying printing defects is vital for process certification, especially with evolving printing technologies. However, this task proves challenging, especially for micro-level defects necessitating microscopy, which presents a scalability barrier for manufacturing. To address this challenge, we propose an attribute learning methodology inspired by human learning, which identifies shared attributes among seen and unseen objects. First, it extracts defect class embeddings from an engineering-guided defect ontology. Then, attribute learning identifies the combination of attributes for defect estimation. This approach enables it to recognize previously unseen defects by identifying shared attributes, even those not included in the training dataset. The research formulates a joint optimization problem for learning and fine-tuning class embedding and ontology and solves it by integrating natural language processing, metaheuristics for exploration and exploitation, and stochastic gradient descent. In a case study involving a direct-ink-writing process for creating nanocomposites, this methodology was used to learn new defects not found in the training data using the optimized ontology. Compared to traditional zero-shot learning, this ontology-based approach significantly improves class embedding, outperforming transfer learning in one-shot and two-shot learning scenarios. This research represents an early effort to learn new defect concepts, potentially reducing the need for extensive measurements in defect identification.

Findings from measurements of noise levels in indoor and outdoor environments in an expanding urban area: a case of Tirana

AbstractThe increasing human population and the increasing number of vehicles in Tirana, Albania, emerges the need for extensive measurements of noise levels. The 831 measurements of noise levels were taken in Tirana in November 2015 for education purposes. Measurements were collected in eight locations in indoor like a classroom in a school building environment, a library and a healthcare facility and in outdoor environments like five crossroads. Noise levels were then compared with domestic and World Health Organization (WHO) standards. The logarithmic average of noise levels and the maximum value of noise level measured for the period of measurement (LAFmax) were interpolated using Interpolated Noise Levels for Observer Points in ArcGIS producing noise level maps for crossroads. The logarithmic average of noise levels and LAFmax measurements were respectively above domestic and WHO standards in 96% and 100% of outdoor environment and indoor environment locations. Interpolated values of logarithmic average of noise levels and LAFmax for five crossroads were above domestic and WHO standards indicating noise levels in road traffic could remain high. A yearly acoustic measurement for vehicles should be implemented. Participatory measurements of noise levels in quite indoor environments can be used to increase the awareness of inhabitants in Tirana.

SU-G-BRC-10: Feasibility of a Web-Based Monte Carlo Simulation Tool for Dynamic Electron Arc Radiotherapy (DEAR)

Purpose: DEAR is a radiation therapy technique utilizing synchronized motion of gantry and couch during delivery to optimize dose distribution homogeneity and penumbra for treatment of superficial disease. Dose calculation for DEAR is not yet supported by commercial TPSs. The purpose of this study is to demonstrate the feasibility of using a web-based Monte Carlo (MC) simulation tool (VirtuaLinac) to calculate dose distributions for a DEAR delivery. Methods: MC simulations were run through VirtuaLinac, which is based on the GEANT4 platform. VirtuaLinac utilizes detailed linac head geometry and material models, validated phase space files, and a voxelized phantom. The input was expanded to include an XML file for simulation of varying mechanical axes as a function of MU. A DEAR XML plan was generated and used in the MC simulation and delivered on a TrueBeam in Developer Mode. Radiographic film wrapped on a cylindrical phantom (12.5 cm radius) measured dose at a depth of 1.5 cm and compared to the simulation results. Results: A DEAR plan was simulated using an energy of 6 MeV and a 3×10 cm2 cut-out in a 15×15 cm2 applicator for a delivery of a 90° arc. The resulting data were found to provide qualitative and quantitative evidence that the simulation platform could be used as the basis for DEAR dose calculations. The resulting unwrapped 2D dose distributions agreed well in the cross-plane direction along the arc, with field sizes of 18.4 and 18.2 cm and penumbrae of 1.9 and 2.0 cm for measurements and simulations, respectively. Conclusion: Preliminary feasibility of a DEAR delivery using a web-based MC simulation platform has been demonstrated. This tool will benefit treatment planning for DEAR as a benchmark for developing other model based algorithms, allowing efficient optimization of trajectories, and quality assurance of plans without the need for extensive measurements.

HINODE/EXTREME-ULTRAVIOLET IMAGING SPECTROMETER OBSERVATIONS OF THE TEMPERATURE STRUCTURE OF THE QUIET CORONA

We present a Differential Emission Measure (DEM) analysis of the quiet solar corona on disk using data obtained by the Extreme-ultraviolet Imaging Spectrometer (EIS) on {\it Hinode}. We show that the expected quiet Sun DEM distribution can be recovered from judiciously selected lines, and that their average intensities can be reproduced to within 30%. We present a subset of these selected lines spanning the temperature range $\log$ T = 5.6 to 6.4 K that can be used to derive the DEM distribution reliably. The subset can be used without the need for extensive measurements and the observed intensities can be reproduced to within the estimated uncertainty in the pre-launch calibration of EIS. Furthermore, using this subset, we also demonstrate that the quiet coronal DEM distribution can be recovered on size scales down to the spatial resolution of the instrument (1$$ pixels). The subset will therefore be useful for studies of small-scale spatial inhomogeneities in the coronal temperature structure, for example, in addition to studies requiring multiple DEM derivations in space or time. We apply the subset to 45 quiet Sun datasets taken in the period 2007 January to April, and show that although the absolute magnitude of the coronal DEM may scale with the amount of released energy, the shape of the distribution is very similar up to at least $\log$ T $\sim$ 6.2 K in all cases. This result is consistent with the view that the {\it shape} of the quiet Sun DEM is mainly a function of the radiating and conducting properties of the plasma and is fairly insensitive to the location and rate of energy deposition. This {\it universal} DEM may be sensitive to other factors such as loop geometry, flows, and the heating mechanism, but if so they cannot vary significantly from quiet Sun region to region.

Performance response of wireless channels for quantitatively different loss and arrival statistics

In this paper we propose a cross-layer performance evaluation framework for wireless channels and subsequently explore the performance response at the FEC and ARQ enabled data-link layer in terms of frame losses and delays for different first- and second-order error and arrival statistics. For a wireless channel model to be appropriate for various FEC capabilities without the need for extensive measurements of the frame error process for each particular FEC code, the error process of the wireless channel is modeled at the physical layer. We assume weak stationary property for bit error observations and model them using a hidden Markov model. The associated parameters matching algorithm allows us to explicitly capture bit error rate and lag-1 autocorrelation of the bit error process. To explore the performance response of the wireless channel at the data-link layer, a cross-layer extension of the bit error model to the data-link layer is then developed. The performance of applications is evaluated using the queuing-theoretic approach that allows both arrival and error processes to be autocorrelated and still retains analytical tractability. The proposed methodology allows us to obtain estimators of frame loss and delay probabilities in the presence of FEC and ARQ procedures at the data-link layer eliminating the need for time-consuming simulations and extensive measurements of wireless channel characteristics for different error correction capabilities of the data-link layer. It is analytical in nature, efficient for small and moderate frame sizes and suitable for performance control purposes where fixed size frames are used at the data-link layer. Particularly, it provides a way to choose the required correction capability of the FEC code resulting in best possible performance at the data-link layer. Numerical results indicate that first- and second-order bit error and frame arrival statistics significantly affect performance parameters provided by a wireless channel and should be taken into account when choosing an appropriate correction capability of the FEC code for given wireless channel conditions.

A New Dose Model for Assessment of Health Risk Due to Contaminants in Air

ABSTRACT The problem of making quantitative assessments of the risks associated with human exposure to toxic contaminants in the environment is a pressing one. This study demonstrates the capability of a new computational technique involving the use of fuzzy logic and neural networks to produce realistic risk assessments. The systematic analysis of human exposure involves the use of measurements and models, the results of which are sometimes used in regulatory decisions or in the drafting of legislation. Because of limited scientific understanding, however, interpretation of models often involves substantial uncertainty. Extensive measurement programs can be very expensive. The high complexity and inherent heterogeneity of exposure analysis is still a major challenge. The approach to this challenge tested here is to use a new model incorporating sophisticated artificial intelligence algorithms. Exposure assessment often requires that a number of factors be evaluated, including exposure concentrations, intake rates, exposure times, and frequencies. These factors are incorporated into a system that can “learn” the relevant relationships based on a known data set. The results can then be applied to new data sets and thus be applied widely without the need for extensive measurements. In this analysis, an example is developed for human health risk through inhalation exposure to benzene from vehicular emissions in the cities of Auckland and Christchurch, New Zealand. Risk factors considered were inhaled contaminant concentration, age, body weight, and activity patterns of humans. Three major variables affecting the inhaled contaminant concentration were emissions (mainly from motor vehicles), meteorology (wind speed, temperature, and atmospheric stability), and site factors (hilly, flat, etc.). The results are preliminary and used principally to demonstrate the technique, but they are very encouraging.

Hydrodynamischer In-vitro-Vergleich einer neuen künstlichen Herzklappe mit der Björk-Shiley-Klappe (Standard) - Hydrodynamic In-vitro Comparison of a New Artificial Heart Valve with the Björk-Shiley Valve (Standard)

Measurements performed to compare a newly developed tilting disc valve with the Björk-Shiley valve included velocity profiles downstream of the heart valves, valve-induced flow turbulence and pressure drop across the opened valves. The velocity profiles measured with pulsed Doppler ultrasound are similar, although they do not permit a quantitative comparison of the valves. The interpretation of the 90 degrees-component of Doppler signals as a measure of the turbulence permits a quantitative comparison without the need for extensive measurements. However, only large vortices are recorded, so that our turbulent shear stresses are lower than these reported in the literature. The pressure drop across the opened valve is a measure of the energy loss, and important parameters for the valve can be derived from it. The pressure drop is dependent on the test conditions, and is therefore not a characteristic constant of the valve. The transformation of the power law Q = C delta P beta into a relation between Re- and Eu-number gives a nondimensional similarity number that is characteristic for tilting disc valves. Its verification requires more investigations, involving variation of valve size and the viscosity of the test fluid.