Search results for: refractive errors

Authors: R. A. Shahmiri, O. Standard, J. Hart, C. C. Sorrell

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Yttrium stabilized tetragonal zirconium polycrystalline (Y-TZP) has been used as a dental biomaterial. The strength and toughness of zirconia can be accounted for by its toughening mechanisms, such as crack deflection, zone shielding, contact shielding, and crack bridging. Prevention of crack propagation is of critical importance in high-fatigue situations, such as those encountered in mastication and para-function. However, the poor translucency of Y-TZP means that it may not meet the aesthetic requirements due to its white/grey appearance in polycrystalline form. To improve optical property of the Zirconia, precise evaluation of its refractive index is of significance. Zirconia`s optical properties need to be studied more in depth. Number of studies assumed, scattered light is isotropically distributed over all angles from biological media when defining optical parameters. Nevertheless, optical behaviour of real biological material depends on angular scattering of light by anisotropy material. Therefore, the average cosine of the scattering angle (which represent recovery phase function in the scattering angular distribution) usually characterized by anisotropy material. It has been identified that yttrium anti-sites present in the space charge layer have no significant role in the absorption of light in the visible range. Addition of cation dopant to polycrystalline zirconia results in segregate to grain boundaries and grain growth. Intrinsic and extrinsic properties of ZrO2 and their effect on optical properties need to be investigated. Intrinsic properties such as chemical composition, defect structure (oxygen vacancy), phase configuration (porosity, second phase) and distribution of phase need to be studied to comprehend their effect on refraction index, absorption/reflection and scattering. Extrinsic properties such as surface structure, thickness, underlying tooth structure, cement layer (type, thickness), and light source (natural, curing, artificial) of ZrO2 need to be studied to understand their effect on colour and translucency of material. This research reviewed effect of stabilization of tetragonal zirconia on optical property of zirconia for dental application.

Keywords: optical properties, zirconia dental biomaterial, chemical composition, phase composition

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Authors: Peregrine James Dalziel, Philip Vu Tran

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Objective / Introduction: Demand for radiology services from Emergency Departments (ED) continues to increase with greater demands placed on radiology staff providing reports for the management of complex cases. Queuing theory indicates that wide variability of process time with the random nature of request arrival increases the probability of significant queues. This can lead to delays in the time-to-availability of radiology reports (TTA-RR) and potentially impaired ED patient flow. In addition, greater “cognitive workload” of greater volume may lead to reduced productivity and increased errors. We sought to quantify the potential ED flow improvements obtainable from increased radiology providers serving 3 public hospitals in Melbourne Australia. We sought to assess the potential productivity gains, quality improvement and the cost-effectiveness of increased labor inputs. Methods & Materials: The Western Health Medical Imaging Department moved from single resident coverage on weekend days 8:30 am-10:30 pm to a limited period of 2 resident coverage 1 pm-6 pm on both weekend days. The TTA-RR for weekend CT scans was calculated from the PACs database for the 8 month period symmetrically around the date of staffing change. A multivariate linear regression model was developed to isolate the improvement in TTA-RR, between the two 4-months periods. Daily and hourly scan volume at the time of each CT scan was calculated to assess the impact of varying department workload. To assess any improvement in report quality/errors a random sample of 200 studies was assessed to compare the average number of clinically significant over-read addendums to reports between the 2 periods. Cost-effectiveness was assessed by comparing the marginal cost of additional staffing against a conservative estimate of the economic benefit of improved ED patient throughput using the Australian national insurance rebate for private ED attendance as a revenue proxy. Results: The primary resident on call and the type of scan accounted for most of the explained variability in time to report availability (R2=0.29). Increasing daily volume and hourly volume was associated with increased TTA-RR (1.5m (p<0.01) and 4.8m (p<0.01) respectively per additional scan ordered within each time frame. Reports were available 25.9 minutes sooner on average in the 4 months post-implementation of double coverage (p<0.01) with additional 23.6 minutes improvement when 2 residents were on-site concomitantly (p<0.01). The aggregate average improvement in TTA-RR was 24.8 hours per weekend day This represents the increased decision-making time available to ED physicians and potential improvement in ED bed utilisation. 5% of reports from the intervention period contained clinically significant addendums vs 7% in the single resident period but this was not statistically significant (p=0.7). The marginal cost was less than the anticipated economic benefit based assuming a 50% capture of improved TTA-RR inpatient disposition and using the lowest available national insurance rebate as a proxy for economic benefit. Conclusion: TTA-RR improved significantly during the period of increased staff availability, both during the specific period of increased staffing and throughout the day. Increased labor utilisation is cost-effective compared with the potential improved productivity for ED cases requiring CT imaging.

Keywords: workflow, quality, administration, CT, staffing

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Authors: Jaqueline Maria Ribeiro Vieira

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Different strategies and tools are available at the oil and gas industry for detecting and analyzing tension and possible fractures in borehole walls. Most of these techniques are based on manual observation of the captured borehole images. While this strategy may be possible and convenient with small images and few data, it may become difficult and suitable to errors when big databases of images must be treated. While the patterns may differ among the image area, depending on many characteristics (drilling strategy, rock components, rock strength, etc.). Previously we developed and proposed a novel strategy capable of detecting patterns at borehole images that may point to regions that have tension and breakout characteristics, based on segmented images. In this work we propose the inclusion of data-mining classification strategies in order to create a knowledge database of the segmented curves. These classifiers allow that, after some time using and manually pointing parts of borehole images that correspond to tension regions and breakout areas, the system will indicate and suggest automatically new candidate regions, with higher accuracy. We suggest the use of different classifiers methods, in order to achieve different knowledge data set configurations.

Keywords: image segmentation, oil well visualization, classifiers, data-mining, visual computer

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Authors: Hossein Gitinavard, Mohammad Hossein Fazel Zarandi

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In the last decades, concerns about the environmental issues lead to professional and academic efforts on green supplier selection problems. In this sake, one of the main issues in evaluating the green supplier selection problems, which could increase the uncertainty, is the preferences of the experts' judgments about the candidate green suppliers. Therefore, preparing an expert system to evaluate the problem based on the historical data and the experts' knowledge can be sensible. This study provides an expert evaluation system to assess the candidate green suppliers under selected criteria in a multi-period approach. In addition, a ranking approach under interval-valued hesitant fuzzy set (IVHFS) environment is proposed to select the most appropriate green supplier in planning horizon. In the proposed ranking approach, the IVHFS and the last aggregation approach are considered to margin the errors and to prevent data loss, respectively. Hence, a comparative analysis is provided based on an illustrative example to show the feasibility of the proposed approach.

Keywords: green supplier selection, expert system, ranking approach, interval-valued hesitant fuzzy setting

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Authors: Tisciane Perpetuo e Oliveira, Dante Inga Narvaez, Marcelo Gradella Villalva

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Installations of solar photovoltaic systems have increased considerably in the last decade. Therefore, it has been noticed that monitoring of meteorological data (solar irradiance, air temperature, wind velocity, etc.) is important to predict the potential of a given geographical area in solar energy production. In this sense, the present work compares two computational tools that are capable of estimating the energy generation of a photovoltaic system through correlation analyzes of solar radiation data: PVsyst software and an algorithm based on the PVlib package implemented in MATLAB. In order to achieve the objective, it was necessary to obtain solar radiation data (measured and from a solarimetric database), analyze the decomposition of global solar irradiance in direct normal and horizontal diffuse components, as well as analyze the modeling of the devices of a photovoltaic system (solar modules and inverters) for energy production calculations. Simulated results were compared with experimental data in order to evaluate the performance of the studied methods. Errors in estimation of energy production were less than 30% for the MATLAB algorithm and less than 20% for the PVsyst software.

Keywords: energy production, meteorological data, irradiance decomposition, solar photovoltaic system

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Authors: Liang-Hsuan Chen, Sheng-Shing Nien

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This study aims to develop approaches to formulate intuitionistic fuzzy regression (IFR) models for many decision-making applications in the fuzzy environments using intuitionistic fuzzy observations. Intuitionistic fuzzy numbers (IFNs) are used to characterize the fuzzy input and output variables in the IFR formulation processes. A mathematical programming problem (MPP) is built up to optimally determine the IFR parameters. Each parameter in the MPP is defined as a couple of alternative numerical variables with opposite signs, and an intuitionistic fuzzy error term is added to the MPP to characterize the uncertainty of the model. The IFR model is formulated based on the distance measure to minimize the total distance errors between estimated and observed intuitionistic fuzzy responses in the MPP resolution processes. The proposed approaches are simple/efficient in the formulation/resolution processes, in which the sign of parameters can be determined so that the problem to predetermine the sign of parameters is avoided. Furthermore, the proposed approach has the advantage that the spread of the predicted IFN response will not be over-increased, since the parameters in the established IFR model are crisp. The performance of the obtained models is evaluated and compared with the existing approaches.

Keywords: fuzzy sets, intuitionistic fuzzy number, intuitionistic fuzzy regression, mathematical programming method

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Authors: Mahadev Bhise, Nabanita Majumder

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Recent studies have found association between air pollutants and mortality, particularly how concentration of air pollutant explains under-five mortality across the countries. Thus, the present study evaluates the relationship between Carbon dioxide (CO2) emission and under-five mortality, while controlling other well-being determinant of Under-five mortality in 100 countries using panel unbalanced cross sectional data. We have used PCSE and GMM model for the period 1990-2011 to meet our objectives. Our findings suggest that, the positive relationship between lagged periods of carbon dioxide and under-five mortality; the percentage of rural population with access of improved water is negatively associated with under-five mortality, while in case of urban population with access of improved water, is positively related to under-five mortality. Access of sanitation facility, food production index, GDP per capita, and concentration of urban population have significant negative impact on under-five mortality. Further, total fertility rate is significantly associated (positive) with under-five mortality which indicates relative change in fertility is related to relative change in under-five mortality.

Keywords: arbon dioxide (CO2), under-five mortality (0q5), gross domestic product (GDP), urban population, food production, panel corrected standard errors (PCSE), generalized method of moments (GMM)

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Authors: M. V. Chidananda Murthy, M. Z. Kurian, H. S. Guruprasad

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Super-resolution is the technique of intelligently upscaling images, avoiding artifacts or blurring, and deals with the recovery of a high-resolution image from one or more low-resolution images. Single-image super-resolution is a process of obtaining a high-resolution image from a set of low-resolution observations by signal processing. While super-resolution has been demonstrated to improve image quality in scaled down images in the image domain, its effects on the Fourier-based technique remains unknown. Super-resolution substantially improved the spatial resolution of the patient LGE images by sharpening the edges of the heart and the scar. This paper aims at investigating the effects of single image super-resolution on Fourier-based and image based methods of scale-up. In this paper, first, generate a training phase of the low-resolution image and high-resolution image to obtain dictionary. In the test phase, first, generate a patch and then difference of high-resolution image and interpolation image from the low-resolution image. Next simulation of the image is obtained by applying convolution method to the dictionary creation image and patch extracted the image. Finally, super-resolution image is obtained by combining the fused image and difference of high-resolution and interpolated image. Super-resolution reduces image errors and improves the image quality.

Keywords: image dictionary creation, image super-resolution, LGE images, patch extraction

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Authors: Ruilian Zhao, Shukai Zhang, Yan Wang, Weiwei Wang

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Repairing broken test cases is an expensive and challenging task in evolving software systems. Although an automated repair technique with intent preservation has been proposed, but it does not take into account the association between test repairs and assertions, leading to a large number of irrelevant candidates and decreasing the repair capability. This paper proposes an assertion-driven test repair approach. Furthermore, an intent-oriented priority criterion is raised to guide the repair candidate generation, making the repairs closer to the intent of the test. In more detail, repair targets are determined through post-dominance relations between assertions and the methods that directly cause compilation errors. Then, test repairs are generated from the target in a bottom-up way, guided by the intent-oriented priority criteria. Finally, the generated repair candidates are prioritized to match the original test intent. The approach is implemented and evaluated on the benchmark of 4 open-source programs and 91 broken test cases. The result shows that the approach can fix 89% (81/91) of broken test cases, which is more effective than the existing intentpreserved test repair approach, and our intent-oriented priority criteria work well.

Keywords: test repair, test intent, software test, test case evolution

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Authors: Edlira Donefski, Lorenc Ekonomi, Tina Donefski

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Edgeworth approximation is one of the most important statistical methods that has a considered contribution in the reduction of the sum of standard deviation of the independent variables’ coefficients in a Quantile Regression Model. This model estimates the conditional median or other quantiles. In this paper, we have applied approximating statistical methods in an economical problem. We have created and generated a quantile regression model to see how the profit gained is connected with the realized sales of the cosmetic products in a real data, taken from a local business. The Linear Regression of the generated profit and the realized sales was not free of autocorrelation and heteroscedasticity, so this is the reason that we have used this model instead of Linear Regression. Our aim is to analyze in more details the relation between the variables taken into study: the profit and the finalized sales and how to minimize the standard errors of the independent variable involved in this study, the level of realized sales. The statistical methods that we have applied in our work are Edgeworth Approximation for Independent and Identical distributed (IID) cases, Bootstrap version of the Model and the Edgeworth approximation for Bootstrap Quantile Regression Model. The graphics and the results that we have presented here identify the best approximating model of our study.

Keywords: bootstrap, edgeworth approximation, IID, quantile

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Authors: Maya Agarwala

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Objectives: Audit the quality of clinical photographs taken for Orthodontic patients at Queen’s hospital, Romford. Design and setting: All Orthodontic photographs are taken in the Medical Photography Department at Queen’s Hospital. Retrospective audit with data collected between January - March 2023. Gold standard: Institute of Medical Illustrators (IMI) standard 12 photographs: 6 extraoral and 6 intraoral. 100% of patients to have the standard 12 photographs meeting a satisfactory diagnostic quality. Materials and methods: 30 patients randomly selected. All photographs analysed against the IMI gold standard. Results: A total of 360 photographs were analysed. 100% of the photographs had the 12 photographic views. Of which, 93.1% met the gold standard. Of the extraoral photos: 99.4% met the gold standard, 0.6% had incorrect head positioning. Of the intraoral photographs: 87.2% met the gold standard. The most common intraoral errors were: the presence of saliva pooling (7.2%), insufficient soft tissue retraction (3.3%), incomplete occlusal surface visibility (2.2%) and mirror fogging (1.1%). Conclusion: The gold standard was not met, however the overall standard of Orthodontic photographs is high. Further training of the Medical Photography team is needed to improve the quality of photographs. Following the training, the audit will be repeated. High-quality clinical photographs are an important part of clinical record keeping.

Keywords: orthodontics, paediatric, photography, audit

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Authors: Mohammad Anwar, Shah Waliullah

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This study investigated panel data regression models. This paper used Bayesian and classical methods to study the impact of institutions on economic growth from data (1990-2014), especially in developing countries. Under the classical and Bayesian methodology, the two-panel data models were estimated, which are common effects and fixed effects. For the Bayesian approach, the prior information is used in this paper, and normal gamma prior is used for the panel data models. The analysis was done through WinBUGS14 software. The estimated results of the study showed that panel data models are valid models in Bayesian methodology. In the Bayesian approach, the effects of all independent variables were positively and significantly affected by the dependent variables. Based on the standard errors of all models, we must say that the fixed effect model is the best model in the Bayesian estimation of panel data models. Also, it was proved that the fixed effect model has the lowest value of standard error, as compared to other models.

Keywords: Bayesian approach, common effect, fixed effect, random effect, Dynamic Random Effect Model

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Authors: Ruxandra Barbulescu, Daniel Ioan, Gabriela Ciuprina

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The saltatory conduction is the way the action potential is transmitted along a myelinated axon. The potential diffuses along the myelinated compartments and it is regenerated in the Ranvier nodes due to the ion channels allowing the flow across the membrane. For an efficient simulation of populations of neurons, it is important to use reduced order models both for myelinated compartments and for Ranvier nodes and to have control over their accuracy and inner parameters. The paper presents a reduced order model of this neural system which allows an efficient simulation method for the saltatory conduction in myelinated axons. This model is obtained by concatenating reduced order linear models of 1D myelinated compartments and nonlinear 0D models of Ranvier nodes. The models for the myelinated compartments are selected from a series of spatially distributed models developed and hierarchized according to their modeling errors. The extracted model described by a nonlinear PDE of hyperbolic type is able to reproduce the saltatory conduction with acceptable accuracy and takes into account the finite propagation speed of potential. Finally, this model is again reduced in order to make it suitable for the inclusion in large-scale neural circuits.

Keywords: action potential, myelinated segments, nonlinear models, Ranvier nodes, reduced order models, saltatory conduction

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Authors: Christoph Lohr, Hanna Wund, Peter Elsner, Kay André Weidenmann

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Injection molding is one of the most commonly used techniques in the industrial polymer processing. In the conventional process of injection molding, the liquid polymer is injected into the cavity of the mold, where the polymer directly starts hardening at the cooled walls. To compensate the shrinkage, which is caused predominantly by the immediate cooling, holding pressure is applied. Through that whole process, residual stresses are produced by the temperature difference of the polymer melt and the injection mold and the relocation of the polymer chains, which were oriented by the high process pressures and injection speeds. These residual stresses often weaken or change the structural behavior of the parts or lead to deformation of components. One solution to reduce the residual stresses is the use of variothermal processing. Hereby the mold is heated – i.e. near/over the glass transition temperature of the polymer – the polymer is injected and before opening the mold and ejecting the part the mold is cooled. For the next cycle, the mold gets heated again and the procedure repeats. The rapid heating and cooling of the mold are realized indirectly by convection of heated and cooled liquid (here: water) which is pumped through fluid channels underneath the mold surface. In this paper, the influences of variothermal processing on the residual stresses are analyzed with samples in a larger scale (500 mm x 250 mm x 4 mm). In addition, the influence on functional elements, such as abrupt changes in wall thickness, bosses, and ribs, on the residual stress is examined. Therefore the polycarbonate samples are produced by variothermal and isothermal processing. The melt is injected into a heated mold, which has in our case a temperature varying between 70 °C and 160 °C. After the filling of the cavity, the closed mold is cooled down varying from 70 °C to 100 °C. The pressure and temperature inside the mold are monitored and evaluated with cavity sensors. The residual stresses of the produced samples are illustrated by birefringence where the effect on the refractive index on the polymer under stress is used. The colorful spectrum can be uncovered by placing the sample between a polarized light source and a second polarization filter. To show the achievement and processing effects on the reduction of residual stress the birefringence images of the isothermal and variothermal produced samples are compared and evaluated. In this comparison to the variothermal produced samples have a lower amount of maxima of each color spectrum than the isothermal produced samples, which concludes that the residual stress of the variothermal produced samples is lower.

Keywords: birefringence, injection molding, polycarbonate, residual stress, variothermal processing

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Authors: Syed Nauman Bin Asghar Bukhari, Mohtashim Mansoor, Mohammad Nouman

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Engine test-Bed system is a fundamental tool to measure dynamic parameters, economic performance, and reliability of an aircraft Engine, and its automation and accuracy directly influences the precision of acquired and analysed data. In this paper, we present the design of digital Data Acquisition (DAQ) system for a vintage aircraft engine test bed that lacks the capability of displaying all the analyzed parameters at one convenient location (one panel-one screen). Recording such measurements in the vintage test bed is not only time consuming but also prone to human errors. Digitizing such measurement system requires a Data Acquisition (DAQ) system capable of recording these parameters and displaying them on one screen-one panel monitor. The challenge in designing upgrade to the vintage systems arises with a need to build and integrate digital measurement system from scratch with a minimal budget and modifications to the existing vintage system. The proposed design not only displays all the key performance / maintenance parameters of the gas turbine engines for operator as well as quality inspector on separate screens but also records the data for further processing / archiving.

Keywords: Gas turbine engine, engine test cell, data acquisition, instrumentation

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Authors: Samuel Quashie

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The importance of theory for PhD construction management research cannot be underestimated, as it requires a sound theoretical basis. Theory efficiency reduces errors in the research problem, solving it by building upon current theory. Provides a structure for examination, enables the efficient development of the construction management field and to it practical real world problems. The aim is to develop the theoretical framework for the application of descriptive theory within the PhD research design To apply the proposed theoretical framework using the case of the topic of ‘integrated management system,’ classifying the phenomena into categories, explore the association between the category–defining attributes and the outcome observed. Forming categorization based upon attributes of phenomena (framework and typologies), and statement of association (models). Predicting (deductive process) and confirming (inductive process). The descriptive theory is important and provides a structure for examination, enables the efficient development of construction management field and to it practical real world problems. In conclusion, the work done in management presents fertile ground for research and theory development.

Keywords: descriptive theory, PhD research design, theoretical framework, construction management

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Authors: Liang Wang, Beste F. Yuksel, David Guy Brizan

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A computational model of affect that can distinguish between spontaneous and posed smiles with no errors on a large, popular data set using deep learning techniques is presented in this paper. A Long Short-Term Memory (LSTM) classifier, a type of Recurrent Neural Network, is utilized and compared to human classification. Results showed that while human classification (mean of 0.7133) was above chance, the LSTM model was more accurate than human classification and other comparable state-of-the-art systems. Additionally, a high accuracy rate was maintained with small amounts of training videos (70 instances). The derivation of important features to further understand the success of our computational model were analyzed, and it was inferred that thousands of pairs of points within the eyes and mouth are important throughout all time segments in a smile. This suggests that distinguishing between a posed and spontaneous smile is a complex task, one which may account for the difficulty and lower accuracy of human classification compared to machine learning models.

Keywords: affective computing, affect detection, computer vision, deep learning, human-computer interaction, machine learning, posed smile detection, spontaneous smile detection

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Authors: Je Young Lee, Hee Sung Kim, Kwang Ho Choi, Joonhoo Lim, Sebum Chun, Hyung Keun Lee

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A purpose of this study is to develop efficient detection method for Global Navigation Satellite Systems (GNSS) applications based on adaptive estimation. Due to dependence of radio frequency signals, GNSS measurements are dominated by systematic errors in receiver’s operating environment. Thus, to utilize GNSS for aerospace or ground vehicles requiring high level of safety, unhealthy measurements should be considered seriously. For the reason, this paper proposes adaptive fault detection method to deal with unhealthy measurements in various harsh environments. By the proposed method, the test statistics for fault detection is generated by estimated measurement noise. Pseudorange and carrier-phase measurement noise are obtained at time propagations and measurement updates in process of Carrier-Smoothed Code (CSC) filtering, respectively. Performance of the proposed method was evaluated by field-collected GNSS measurements. To evaluate the fault detection capability, intentional faults were added to measurements. The experimental result shows that the proposed detection method is efficient in detecting unhealthy measurements and improves the accuracy of GNSS positioning under fault occurrence.

Keywords: adaptive estimation, fault detection, GNSS, residual

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Authors: Mohamed Elhakeem, A. N. Thanos Papanicolaou, Christopher Wilson, Yi-Jia Chang

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In this study, a physically-based, modelling framework was developed to predict saturated hydraulic conductivity (KSAT) dynamics in the Clear Creek Watershed (CCW), Iowa. The modelling framework integrated selected pedotransfer functions and watershed models with geospatial tools. A number of pedotransfer functions and agricultural watershed models were examined to select the appropriate models that represent the study site conditions. Models selection was based on statistical measures of the models’ errors compared to the KSAT field measurements conducted in the CCW under different soil, climate and land use conditions. The study has shown that the predictions of the combined pedotransfer function of Rosetta and the Water Erosion Prediction Project (WEPP) provided the best agreement to the measured KSAT values in the CCW compared to the other tested models. Therefore, Rosetta and WEPP were integrated with the Geographic Information System (GIS) tools for visualization of the data in forms of geospatial maps and prediction of KSAT variability in CCW due to the seasonal changes in climate and land use activities.

Keywords: saturated hydraulic conductivity, pedotransfer functions, watershed models, geospatial tools

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Authors: Robert Jacobsen

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Flood inundation maps (FIMs) are an essential tool in communicating flood threat scenarios to the public as well as in floodplain governance. With an increasing demand for online raster FIMs, the FIM State-of-the-Practice (SOP) is rapidly advancing to meet the dual requirements for high-resolution and high-accuracy—or High-Definition. Importantly, today’s technology also enables the resolution of problems of local—neighborhood-scale—bias errors that often occur in FIMs, even with the use of SOP two-dimensional flood modeling. To facilitate the development of HD-FIMs, a new GIS method--Raster Adjustment with Scenario Profiles, RASPTM—is described for adjusting kernel raster FIMs to match refined scenario profiles. With RASPTM, flood professionals can prepare HD-FIMs for a wide range of scenarios with available kernel rasters, including kernel rasters prepared from vector FIMs. The paper provides detailed procedures for RASPTM, along with an example of applying RASPTM to prepare an HD-FIM for the August 2016 Flood in Louisiana using both an SOP kernel raster and a kernel raster derived from an older vector-based flood insurance rate map. The accuracy of the HD-FIMs achieved with the application of RASPTM to the two kernel rasters is evaluated.

Keywords: hydrology, mapping, high-definition, inundation

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Authors: Ashwag O. Maghraby, Nida N. Khan, Hosnia A. Ahmed, Ghufran N. Brohi, Hind F. Assouli, Jawaher S. Melibari

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The Arabic language is one of the most important languages. Learning it is so important for many people around the world because of its religious and economic importance and the real challenge lies in practicing it without grammatical or syntactical mistakes. This research focused on detecting and correcting the syntactic mistakes of Arabic syntax according to their position in the sentence and focused on two of the main syntactical rules in Arabic: Dual and Plural. It analyzes each sentence in the text, using Stanford CoreNLP morphological analyzer and machine-learning approach in order to detect the syntactical mistakes and then correct it. A prototype of the proposed system was implemented and evaluated. It uses support vector machine (SVM) algorithm to detect Arabic grammatical errors and correct them using the rule-based approach. The prototype system has a far accuracy 81%. In general, it shows a set of useful grammatical suggestions that the user may forget about while writing due to lack of familiarity with grammar or as a result of the speed of writing such as alerting the user when using a plural term to indicate one person.

Keywords: Arabic language acquisition and learning, natural language processing, morphological analyzer, part-of-speech

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Authors: Rafid Mueen, Konstantin Konstantinov, Micheal Lerch, Zhenxiang Cheng

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In the past two decades, the concern for skin protection from ultraviolet (UV) radiation has attracted considerable attention due to the increased intensity of UV rays that can reach the Earth’s surface as a result of the breakdown of ozone layer. Recently, UVA has also attracted attention, since, in comparison to UVB, it can penetrate deeply into the skin, which can result in significant health concerns. Sunscreen agents are one of the significant tools to protect the skin from UV irradiation, and it is either organic or in organic. Developing of inorganic UV blockers is essential, which provide efficient UV protection over a wide spectrum rather than organic filters. Furthermore inorganic UV blockers are good comfort, and high safety when applied on human skin. Inorganic materials can absorb, reflect, or scatter the ultraviolet radiation, depending on their particle size, unlike the organic blockers, which absorb the UV irradiation. Nowadays, most inorganic UV-blocking filters are based on (TiO2) and ZnO). ZnO can provide protection in the UVA range. Indeed, ZnO is attractive for in sunscreen formulization, and this relates to many advantages, such as its modest refractive index (2.0), absorption of a small fraction of solar radiation in the UV range which is equal to or less than 385 nm, its high probable recombination of photogenerated carriers (electrons and holes), large direct band gap, high exciton binding energy, non-risky nature, and high tendency towards chemical and physical stability which make it transparent in the visible region with UV protective activity. A significant issue for ZnO use in sunscreens is that it can generate ROS in the presence of UV light because of its photocatalytic activity. Therefore it is essential to make a non-photocatalytic material through modification by other metals. Several efforts have been made to deactivate the photocatalytic activity of ZnO by using inorganic surface modifiers. The doping of ZnO by different metals is another way to modify its photocatalytic activity. Recently, successful doping of ZnO with different metals such as Ce, La, Co, Mn, Al, Li, Na, K, and Cr by various procedures, such as a simple and facile one pot water bath, co-precipitation, hydrothermal, solvothermal, combustion, and sol gel methods has been reported. These materials exhibit greater performance than undoped ZnO towards increasing the photocatalytic activity of ZnO in visible light. Therefore, metal doping can be an effective technique to modify the ZnO photocatalytic activity. However, in the current work, we successfully reduce the photocatalytic activity of ZnO through Na doped ZnO fabricated via sol-gel and hydrothermal methods.

Keywords: photocatalytic, ROS, UVA, ZnO

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Authors: M. P. Sebastian

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Health for all is considered as a sign of well-being and inclusive growth. New healthcare technologies are contributing to the quality of human lives by promoting health education and awareness, leading to the prevention, early diagnosis and treatment of the symptoms of diseases. Healthcare technologies have now migrated from the medical and institutionalized settings to the home and everyday life. This paper explores these new technologies and investigates how they contribute to health education and awareness, promoting the objective of high-value health system for all. The methodology used for the research is literature review. The paper also discusses the opportunities and challenges with futuristic healthcare technologies. The combined advances in genomics medicine, wearables and the IoT with enhanced data collection in electronic health record (EHR) systems, environmental sensors, and mobile device applications can contribute in a big way to high-value health system for all. The promise by these technologies includes reduced total cost of healthcare, reduced incidence of medical diagnosis errors, and reduced treatment variability. The major barriers to adoption include concerns with security, privacy, and integrity of healthcare data, regulation and compliance issues, service reliability, interoperability and portability of data, and user friendliness and convenience of these technologies.

Keywords: big data, education, healthcare, information communication technologies (ICT), patients, technologies

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Authors: Cristiane C. B. Alves, Livia Eisler, Gustavo Mota, Kurt Faltin Jr., Cristina L. F. Ortolani

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The correct positioning of the brackets is essential for the success of orthodontic treatment. Indirect bracket placing technique has the main objective of eliminating the positioning errors, which commonly occur in the technique of direct system of brackets. The objective of this study is to demonstrate that the exact positioning of the brackets is of extreme relevance for the success of the treatment. The present work shows a case report of an adult female patient who attended the clinic with the complaint of being in orthodontic treatment for more than 5 years without noticing any progress. As a result of the intra-oral clinical examination and documentation analysis, a class III malocclusion, an anterior open bite, and absence of all third molars and first upper and lower bilateral premolars were observed. For the treatment, the indirect bonding technique with self-ligating ceramic braces was applied. The preparation of the trays was done after the intraoral digital scanning and printing of models with a 3D printer. Brackets were positioned virtually, using a specialized software. After twelve months of treatment, correction of the malocclusion was observed, as well as the closing of the anterior open bite. It is concluded that the adequate and precise positioning of brackets is necessary for a successful treatment.

Keywords: anterior open-bite, CAD/CAM, orthodontics, malocclusion, angle class III

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Authors: Michael Ngongeh Mombe

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This Paper seeks to investigate an assertion made by some colleagues that there is no need paying a human translator to translate their literary texts, that there are softwares such as Reverso that can be used to do the translation. The main objective of this study is to examine the veracity of this assertion using Reverso to translate a literary text without any post-editing by a human translator. The work is based on two theories: Skopos and Communicative theories of translation. The work is a documentary research where data were collected from published documents in libraries, on the internet and from the translation produced by Reverso. We made a comparative text analyses of both source and target texts in a bid to highlight the weaknesses and strengths of the software. Findings of this work revealed that those who advocate the use of only Machine translation do so in ignorance of the translation mistakes usually made by the software. From the review of all the 268 segments of translation, we found out that the translation produced by Reverso is fraught with errors. We therefore recommend the use of human translators to either do the translation of their literary texts or revise the translation produced by machine to conform to the skopos of the work. This paper is based on Reverso translation. Similar works in the near future will be based on the other translation softwares to determine their weaknesses and strengths.

Keywords: machine translation, human translator, Reverso, literary text

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Authors: Joung Hyoun Lee

Abstract:

Intransitive verbs consist of two subclasses called unergatives and unaccusatives. However, traditionally Italian intransitive verbs have been taught regardless their semantic distinctions and any mention of grammatical terms such as unaccusatives and unergatives even though there is a huge gap between them. This paper aims to explore the teaching of Italian intransitive verbs categorizing them into unaccusatives and unergatives, which is compared with researches on the teaching of English unaccusative and unergative verbs. For this purpose, first, the study analyses various aspects of English vs. Italian unergatives and unaccusatives, and their properties of the constructions. Next, this study highlights the research trend on Korean students' learning errors, which is leaning toward causal analyses of the over passivization of English unaccusative verbs. In order to investigate these issues, 53 students of the Busan University of Foreign Studies, who are studying Italian language as a second language, were surveyed through a grammaticality judgment test divided into 9 sections. As expected, the findings confirmed that the test results of Italian unaccusatives and unergatives showed similar and different aspects comparing to those of English. Moreover, there was a highly affirmative demand for a more careful way of teaching which should be considered both syntactically and semantically according to the grammatical items. The research provides a framework of a more effective and systematic teaching method of Italian intransitive verbs for further research.

Keywords: unaccusative verbs, unergative verbs, agent, patient, theme, overpassivization

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Authors: Richa Mishra, Sonia Munjal

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In this increasingly hectic and competitive climate, employees are expected to manage the resources available to them to perform their work. However, many are wasting the most precious and scarce resource at their disposal, time, by procrastinating on tasks and thereby costing themselves and their organizations. As timely performance is a requirement of most jobs, procrastination is particularly problematic in the workplace. Evidence suggests that procrastination and poor performance go hand-in-hand, as procrastinators miss more deadlines than non-procrastinators and make more errors and work at a slower speed than non-procrastinators when performing timed tasks. This research is hence an effort to add a little in the sparse knowledge base. It is an effort to throw light on the relationship of Levenson’s multi dimensions of locus of control and also an effort to identify if it is one of the causes and of employees procrastination which have not been explored earlier. The study also explores the effect and relationship of multidimensional locus of control and various levels of stress on procrastination. The results of the research have ascertained that there is significant impact of LOC dimensions on the procrastinating behavior of the employees. One of the major findings to emerge from the current research that managers with powerful others as their LOC dimensions were least procrastinating, contradicts the previous research results that external procrastinate more than internals.

Keywords: Multidimensional Locus of Control, workplace procrastination, employee behaviour, manufacturing industry

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Authors: Feng Wang, Shencheng Ni, Shuying Han, Shanhong You

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With the development of optical communication, optical performance monitoring (OPM) has received more and more attentions. Since optical signal-to-noise ratio (OSNR) is directly related to bit error rate (BER), it is one of the important parameters in optical networks. Recently, artificial neural network (ANN) has been greatly developed. ANN has strong learning and generalization ability. In this paper, a method of OSNR monitoring based on delay-tap sampling (DTS) and ANN has been proposed. DTS technique is used to extract the eigenvalues of the signal. Then, the eigenvalues are input into the ANN to realize the OSNR monitoring. The experiments of 10 Gb/s non-return-to-zero (NRZ) on–off keying (OOK), 20 Gb/s pulse amplitude modulation (PAM4) and 20 Gb/s return-to-zero (RZ) differential phase-shift keying (DPSK) systems are demonstrated for the OSNR monitoring based on the proposed method. The experimental results show that the range of OSNR monitoring is from 15 to 30 dB and the root-mean-square errors (RMSEs) for 10 Gb/s NRZ-OOK, 20 Gb/s PAM4 and 20 Gb/s RZ-DPSK systems are 0.36 dB, 0.45 dB and 0.48 dB respectively. The impact of chromatic dispersion (CD) on the accuracy of OSNR monitoring is also investigated in the three experimental systems mentioned above.

Keywords: artificial neural network (ANN), chromatic dispersion (CD), delay-tap sampling (DTS), optical signal-to-noise ratio (OSNR)

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Authors: M. S. Gadala, Khaled Ahmed, Elasadig Mahdi

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In this paper, we introduced a gradient-based inverse solver to obtain the missing boundary conditions based on the readings of internal thermocouples. The results show that the method is very sensitive to measurement errors, and becomes unstable when small time steps are used. The artificial neural networks are shown to be capable of capturing the whole thermal history on the run-out table, but are not very effective in restoring the detailed behavior of the boundary conditions. Also, they behave poorly in nonlinear cases and where the boundary condition profile is different. GA and PSO are more effective in finding a detailed representation of the time-varying boundary conditions, as well as in nonlinear cases. However, their convergence takes longer. A variation of the basic PSO, called CRPSO, showed the best performance among the three versions. Also, PSO proved to be effective in handling noisy data, especially when its performance parameters were tuned. An increase in the self-confidence parameter was also found to be effective, as it increased the global search capabilities of the algorithm. RPSO was the most effective variation in dealing with noise, closely followed by CRPSO. The latter variation is recommended for inverse heat conduction problems, as it combines the efficiency and effectiveness required by these problems.

Keywords: inverse analysis, function specification, neural net works, particle swarm, run-out table

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Authors: Jacob Nortey

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Introduction: In recent years, there has been an enormous success in discoveries of scientific knowledge in medicine coupled with the advancement of technology. Despite all these successes, diagnoses and treatment of diseases have become complex. According to the Ibero – American Study of Adverse Effects (IBEAS), about 10% of hospital patients suffer from secondary damage during the care process, and approximately 2% die from this process. Many clinical decision support systems have been developed to help mitigate some healthcare medical errors. Method: Relevant databases were searched, including ones that were peculiar to the clinical decision support system (that is, using google scholar, Pub Med and general google searches). The articles were then screened for a comprehensive overview of the functionality, consultative style and statistical usage of Dxplain Clinical decision support systems. Results: Inferences drawn from the articles showed high usage of Dxplain clinical decision support system for problem-based learning among students in developed countries as against little or no usage among students in Low – and Middle – income Countries. The results also indicated high usage among general practitioners. Conclusion: Despite the challenges Dxplain presents, the benefits of its usage to clinicians and students are enormous.

Keywords: dxplain, clinical decision support sytem, diagnosis, support systems

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