Search results for: real time data analysis

Authors: Seham El Kareh, Miramar Etman

Abstract:

Recently, detecting liars and extracting features which distinguish them from truth-tellers have been the focus of a wide range of disciplines. To the author’s best knowledge, most of the work has been done on facial expressions and body gestures but only few works have been done on the language used by both liars and truth-tellers. This paper sheds light on four axes. The first axis copes with building an audio corpus for deceptive and truthful speech for Egyptian Arabic speakers. The second axis focuses on examining the human perception of lies and proving our need for computational linguistic-based methods to extract features which characterize truthful and deceptive speech. The third axis is concerned with building a linguistic analysis program that could extract from the corpus the inter- and intra-linguistic cues for deceptive and truthful speech. The program built here is based on selected categories from the Linguistic Inquiry and Word Count program. Our results demonstrated that Egyptian Arabic speakers on one hand preferred to use first-person pronouns and present tense compared to the past tense when lying and their lies lacked of second-person pronouns, and on the other hand, when telling the truth, they preferred to use the verbs related to motion and the nouns related to time. The results also showed that there is a need for bigger data to prove the significance of words related to emotions and numbers.

Keywords: Egyptian Arabic corpus, computational analysis, deceptive features, forensic linguistics, human perception, truthful features.

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Authors: K.L. Verma

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Analysis for the generalized thermoelastic Lamb waves, which propagates in anisotropic thin plates in generalized thermoelasticity, is presented employing normal mode expansion method. The displacement and temperature fields are expressed by a summation of the symmetric and antisymmetric thermoelastic modes in the surface thermal stresses and thermal gradient free orthotropic plate, therefore the theory is particularly appropriate for waveform analyses of Lamb waves in thin anisotropic plates. The transient waveforms excited by the thermoelastic expansion are analyzed for an orthotropic thin plate. The obtained results show that the theory provides a quantitative analysis to characterize anisotropic thermoelastic stiffness properties of plates by wave detection. Finally numerical calculations have been presented for a NaF crystal, and the dispersion curves for the lowest modes of the symmetric and antisymmetric vibrations are represented graphically at different values of thermal relaxation time. However, the methods can be used for other materials as well

Keywords: Anisotropic, dispersion, frequency, normal, thermoelasticity, wave modes.

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Authors: Patrick Maier, Marcus Tönnis, Gudrun Klinker

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Spatial understanding and the understanding of dynamic change in the spatial structure of molecules during a reaction is essential for designing new molecules. Knowing the physical processes in the reactions helps to speed up the designing process. To support the designer with the correct representation of the designed molecule as well as showing the dynamic behavior of the whole reacting system is the goal of our application. Our system shows the spatial deformation of the molecules at every time interval by minimizing the energy level of the molecules. The position and orientation of the molecules can be intuitively controlled by manipulating objects of the real world using Augmented Reality techniques. Our approach has the potential to speed up the design of new molecules and help students to understand the chemical processes better.

Keywords: Augmented Augmented Chemical Reactions, Augmented Reality, chemistry, education.

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Authors: Ghulam Murtaza, Kalsoom Farzana

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The aim of this article is to narrate the utility of novel simulation approach i.e. convolution method to predict blood concentration of drug utilizing dissolution data of salbutamol sulphate microparticulate formulations with different release patterns (1:1, 1:2 and 1:3, drug:polymer). Dissolution apparatus II USP 2007 and 900 ml double distilled water stirrd at 50 rpm was employed for dissolution analysis. From dissolution data, blood drug concentration was determined, and in return predicted blood drug concentration data was used to calculate the pharmacokinetic parameters i.e. Cmax, Tmax, and AUC. Convolution is a good biwaiver technique; however its better utility needs it application in the conditions where biorelevant dissolution media are used.

Keywords: Convolution, Dissolution, Pharmacokinetics, Salbutamol sulphate

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Authors: Daniel Badulescu

Abstract:

Under the difficult access to finance of SMEs, they expect that its relationship with the banks shall constitute a real help to access appropriate financing, at reasonable costs and requirements, given the possibility of mutually beneficial and long lasting relation. The literature, but also the research we have carried on, is centered on such determinants as concentration and the length of the relationship, but at the same time, there is little certainty that banks are responding positively to them. Furthermore, although the trust is considered as being a fundamental element of bank relationship – see the case house bank – SMEs find that the banks finance them looking rather on collaterals and covenants than to trust. Moreover, a positive behavior, such as prompt or advance repayments of loans, doesn-t generate any positive feedback from the banks side. All these show a deep un-satisfaction of the SMEs concerning their relationship banking.

Keywords: Banks' behavior, relationship banking, SMEs.

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Authors: Rana Khalid Naeem, Asif Mansoor

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The hydrologic time series data display periodic structure and periodic autoregressive process receives considerable attention in modeling of such series. In this communication long term record of monthly waste flow of Lyari river is utilized to quantify by using PAR modeling technique. The parameters of model are estimated by using Frances & Paap methodology. This study shows that periodic autoregressive model of order 2 is the most parsimonious model for assessing periodicity in waste flow of the river. A careful statistical analysis of residuals of PAR (2) model is used for establishing goodness of fit. The forecast by using proposed model confirms significance and effectiveness of the model.

Keywords: Diagnostic checks, Lyari river, Model selection, Monthly waste flow, Periodicity, Periodic autoregressive model.

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Authors: H. Alves, J. T. Assis, M. Geraldes, I. Lima, R. T. Lopes

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Microtomographic images and thin section (TS) images were analyzed and compared against some parameters of geological interest such as porosity and its distribution along the samples. The results show that microtomography (CT) analysis, although limited by its resolution, have some interesting information about the distribution of porosity (homogeneous or not) and can also quantify the connected and non-connected pores, i.e., total porosity. TS have no limitations concerning resolution, but are limited by the experimental data available in regards to a few glass sheets for analysis and also can give only information about the connected pores, i.e., effective porosity. Those two methods have their own virtues and flaws but when paired together they are able to complement one another, making for a more reliable and complete analysis.

Keywords: Microtomography, petrographical microscopy, sediments, thin sections.

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Authors: Aqsa Jamil, Hiroshi Tamura, Hiroshi Katsuchi, Jiaqi Wang

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Yield point represents the upper limit of forces which can be applied on a specimen without causing any permanent deformation. After yielding, the behavior of specimen suddenly changes including the possibility of cracking or buckling. So, the accumulation of damage or type of fracture changes depending on this condition. As it is difficult to accurately detect yield points of the several stress concentration points in structural steel specimens, an effort has been made in this research work to develop a convenient technique using thermography (temperature-based detection) during tensile tests for the precise detection of yield point initiation. To verify the applicability of thermography camera, tests were conducted under different loading conditions and measuring the deformation by installing various strain gauges and monitoring the surface temperature with the help of thermography camera. The yield point of specimens was estimated by the help of temperature dip which occurs due to the thermoelastic effect during the plastic deformation. The scattering of the data has been checked by performing repeatability analysis. The effect of temperature imperfection and light source has been checked by carrying out the tests at daytime as well as midnight and by calculating the signal to noise ratio (SNR) of the noised data from the infrared thermography camera, it can be concluded that the camera is independent of testing time and the presence of a visible light source. Furthermore, a fully coupled thermal-stress analysis has been performed by using Abaqus/Standard exact implementation technique to validate the temperature profiles obtained from the thermography camera and to check the feasibility of numerical simulation for the prediction of results extracted with the help of thermographic technique.

Keywords: Signal to noise ratio, thermoelastic effect, thermography, yield point.

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Authors: Jalal M. Abdallah

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There is a great problem in testing and investigations the reliability of different type of transformers insulation materials. It summarized in how to create and simulate the real conditions of working transformer and testing its insulation materials for Partial Discharge PD, typically as in the working mode. A lot of tests may give untrue results as the physical behavior of the insulation material differs under tests from its working condition. In this work, the real working conditions were simulated, and a large number of specimens have been tested. The investigations first stage, begin with choosing samples of different types of insulation materials (papers, pressboards, etc.). The second stage, the samples were dried in ovens at 105 C⁰and 0.01bar for 48 hours, and then impregnated with dried and gasless oil (the water content less than 6 ppm.) at 105 C⁰and 0.01bar for 48 hours, after so specimen cooling at room pressure and temperature for 24 hours. The third stage is investigating PD for the samples using ICM PD measuring device. After that, a continuous test on oil-impregnated insulation materials (paper, pressboards) was developed, and the phase resolved partial discharge pattern of PD signals was measured. The important of this work in providing the industrial sector with trusted high accurate measuring results based on real simulated working conditions. All the PD patterns (results) associated with a discharge produced in well-controlled laboratory condition. They compared with other previous and other laboratory results. In addition, the influence of different temperatures condition on the partial discharge activities was studied.

Keywords: Transformers, insulation materials, voids, partial discharge (PD).

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Authors: A. Bencsik, - A. Sólyom

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The role of knowledge is a determinative factor in the life of economy and society. To determine knowledge is not an easy task yet the real task is to determine the right knowledge. From this view knowledge is a sum of experience, ideas and cognitions which can help companies to remain in markets and to realize a maximum profit. At the same time changes of circumstances project in advance that contents and demands of the right knowledge are changing. In this paper we will analyse a special segment on the basis of an empirical survey. We investigated the behaviour and strategies of small and medium sized enterprises (SMEs) in the area of knowledge-handling. This survey was realized by questionnaires and wide range statistical methods were used during processing. As a result we will show how these companies are prepared to operate in a knowledge-based economy and in which areas they have prominent deficiencies.

Keywords: education, knowledge, knowledgemanagement, strategy, SME

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Authors: Seiichi Gohshi, Hiroyuki Sekiguchi, Yoshiyasu Shimizu, Takeshi Ikenaga

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Super resolution (SR) technologies are now being applied to video to improve resolution. Some TV sets are now equipped with SR functions. However, it is not known if super resolution image reconstruction (SRR) for TV really works or not. Super resolution with non-linear signal processing (SRNL) has recently been proposed. SRR and SRNL are the only methods for processing video signals in real time. The results from subjective assessments of SSR and SRNL are described in this paper. SRR video was produced in simulations with quarter precision motion vectors and 100 iterations. These are ideal conditions for SRR. We found that the image quality of SRNL is better than that of SRR even though SRR was processed under ideal conditions.

Keywords: Super Resolution Image Reconstruction, Super Resolution with Non-Linear Signal Processing, Subjective Assessment, Image Quality

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Authors: Amal M. Alrayes

Abstract:

Data and system quality play a central role in organizational success, and the quality of any existing information system has a major influence on the effectiveness of overall system performance. Given the importance of system and data quality to an organization, it is relevant to highlight their importance on organizational performance in the Kingdom of Bahrain. This research aims to discover whether system quality and data quality are related, and to study the impact of system and data quality on organizational success. A theoretical model based on previous research is used to show the relationship between data and system quality, and organizational impact. We hypothesize, first, that system quality is positively associated with organizational impact, secondly that system quality is positively associated with data quality, and finally that data quality is positively associated with organizational impact. A questionnaire was conducted among public and private organizations in the Kingdom of Bahrain. The results show that there is a strong association between data and system quality, that affects organizational success.

Keywords: Data quality, performance, system quality.

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Authors: Evisa Mitrou, Nicholas Tsitsianis, Supriya Shinde

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In the age of digitisation and globalisation, businesses have shifted online and are investing in big data analytics (BDA) to respond to changing market conditions and sustain their performance. Our study shifts the focus from the adoption of BDA to the impact of BDA on financial performance. We explore the financial performance of both BDA-vendors (business-to-business) and BDA-clients (business-to-customer). We distinguish between the five BDA-technologies (big-data-as-a-service (BDaaS), descriptive, diagnostic, predictive, and prescriptive analytics) and discuss them individually. Further, we use four perspectives (internal business process, learning and growth, customer, and finance) and discuss the significance of how each of the five BDA-technologies affect the performance measures of these four perspectives. We also present the analysis of employee engagement, average turnover, average net income, and average net assets for BDA-clients and BDA-vendors. Our study also explores the effect of the COVID-19 pandemic on business continuity for both BDA-vendors and BDA-clients.

Keywords: BDA-clients, BDA-vendors, big data analytics, financial performance.

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Authors: Migbar Assefa

Abstract:

The performance of a machine tool is eventually assessed by its ability to produce a component of the required geometry in minimum time and at small operating cost. It is customary to base the structural design of any machine tool primarily upon the requirements of static rigidity and minimum natural frequency of vibration. The operating properties of machines like cutting speed, feed and depth of cut as well as the size of the work piece also have to be kept in mind by a machine tool structural designer. This paper presents a novel approach to the design of machine tool column for static and dynamic rigidity requirement. Model evaluation is done effectively through use of General Finite Element Analysis software ANSYS. Studies on machine tool column are used to illustrate finite element based concept evaluation technique. This paper also presents results obtained from the computations of thin walled box type columns that are subjected to torsional and bending loads in case of static analysis and also results from modal analysis. The columns analyzed are square and rectangle based tapered open column, column with cover plate, horizontal partitions and with apertures. For the analysis purpose a total of 70 columns were analyzed for bending, torsional and modal analysis. In this study it is observed that the orientation and aspect ratio of apertures have no significant effect on the static and dynamic rigidity of the machine tool structure.

Keywords: Finite Element Modeling, Modal Analysis, Machine tool structure, Static Analysis.

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Authors: X. Gu, K. L. Blackmore

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The impact factor was introduced to measure the quality of journals. Various impact measures exist from multiple bibliographic databases. In this research, we aim to provide a broader understanding of the relationship between scholarly impact and other characteristics of academic journals. Data used for this research were collected from Ulrich’s Periodicals Directory (Ulrichs), Cabell’s (Cabells), and SCImago Journal & Country Rank (SJR) from 1999 to 2015. A master journal dataset was consolidated via Journal Title and ISSN. We adopted a two-step analysis process to study the quantitative relationships between scholarly impact and other journal characteristics. Firstly, we conducted a correlation analysis over the data attributes, with results indicating that there are no correlations between any of the identified journal characteristics. Secondly, we examined the quantitative relationship between scholarly impact and other characteristics using quartile analysis. The results show interesting patterns, including some expected and others less anticipated. Results show that higher quartile journals publish more in both frequency and quantity, and charge more for subscription cost. Top quartile journals also have the lowest acceptance rates. Non-English journals are more likely to be categorized in lower quartiles, which are more likely to stop publishing than higher quartiles. Future work is suggested, which includes analysis of the relationship between scholars and their publications, based on the quartile ranking of journals in which they publish.

Keywords: Academic journal, acceptance rate, impact factor, journal characteristics.

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Authors: Namal A. Senanayake, A. Beg, Withana C. Prasad

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This paper analyzes the patterns of the Monte Carlo data for a large number of variables and minterms, in order to characterize the circuit path length behavior. We propose models that are determined by training process of shortest path length derived from a wide range of binary decision diagram (BDD) simulations. The creation of the model was done use of feed forward neural network (NN) modeling methodology. Experimental results for ISCAS benchmark circuits show an RMS error of 0.102 for the shortest path length complexity estimation predicted by the NN model (NNM). Use of such a model can help reduce the time complexity of very large scale integrated (VLSI) circuitries and related computer-aided design (CAD) tools that use BDDs.

Keywords: Monte Carlo data, Binary decision diagrams, Neural network modeling, Shortest path length estimation.

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Authors: Y. Saylan, F. Yılmaz, A. Denizli

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In this study, we have focused our attention on combining of molecular imprinting into nanofilms and QCM nanosensor approaches and producing QCM nanosensor for anti- CCP, chosen as model protein, using anti-CCP imprinted nanofilms. The nonimprinted nanosensor was also prepared to evaluate the selectivity of the imprinted nanosensor. Anti-CCP imprinted QCM nanosensor was tested for real time detection of anti-CCP from aqueous solution. The kinetic and affinity studies were determined by using anti-CCP solutions with different concentrations. The responses related with mass shifts (%m) and frequency shifts (%f) were used to evaluate adsorption properties. To show the selectivity of the anti-CCP imprinted QCM nanosensor, competitive adsorption of anti-CCP and IgM was investigated. The results indicate that anti- CCP imprinted QCM nanosensor has higher adsorption capabilities for anti-CCP than for IgM, due to selective cavities in the polymer structure.

Keywords: Anti-CCP, molecular imprinting, QCM nanosensor, rheumatoid arthritis.

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Authors: K. Atashgar

Abstract:

When an assignable cause(s) manifests itself to a multivariate process and the process shifts to an out-of-control condition, a root-cause analysis should be initiated by quality engineers to identify and eliminate the assignable cause(s) affected the process. A root-cause analysis in a multivariate process is more complex compared to a univariate process. In the case of a process involved several correlated variables an effective root-cause analysis can be only experienced when it is possible to identify the required knowledge including the out-of-control condition, the change point, and the variable(s) responsible to the out-of-control condition, all simultaneously. Although literature addresses different schemes to monitor multivariate processes, one can find few scientific reports focused on all the required knowledge. To the best of the author’s knowledge this is the first time that a multi task model based on artificial neural network (ANN) is reported to monitor all the required knowledge at the same time for a multivariate process with more than two correlated quality characteristics. The performance of the proposed scheme is evaluated numerically when different step shifts affect the mean vector. Average run length is used to investigate the performance of the proposed multi task model. The simulated results indicate the multi task scheme performs all the required knowledge effectively.

Keywords: Artificial neural network, Multivariate process, Statistical process control, Change point.

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Authors: Sudipta Majumdar, Akansha Singh

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Frequency estimation of a sinusoid in white noise using maximum entropy power spectral estimation has been shown to be very sensitive to initial sinusoidal phase. This paper presents use of wavelet transform to find an analytic signal for frequency estimation using maximum entropy method (MEM) and compared the results with frequency estimation using analytic signal by Hilbert transform method and frequency estimation using real data together with MEM. The presented method shows the improved estimation precision and antinoise performance.

Keywords: Frequency estimation, analytic signal, maximum entropy method, wavelet transform.

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Authors: C. B. Vishwakarma

Abstract:

The author presented a method for model order reduction of large-scale time-invariant systems in time domain. In this approach, two modified Hankel matrices are suggested for getting reduced order models. The proposed method is simple, efficient and retains stability feature of the original high order system. The viability of the method is illustrated through the examples taken from literature.

Keywords: Model Order Reduction, Stability, Hankel Matrix, Time-Domain, Integral Square Error.

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Authors: Ziad Abdeldayem, Jakub Markiewicz, Kunal Kansara, Laura Edwards

Abstract:

Airborne Laser Scanning (ALS) is one of the main technologies for generating high-resolution digital terrain models (DTMs). DTMs are crucial to several applications, such as topographic mapping, flood zone delineation, geographic information systems (GIS), hydrological modelling, spatial analysis, etc. Laser scanning system generates irregularly spaced three-dimensional cloud of points. Raw ALS data are mainly ground points (that represent the bare earth) and non-ground points (that represent buildings, trees, cars, etc.). Removing all the non-ground points from the raw data is referred to as filtering. Filtering heavily forested areas is considered a difficult and challenging task as the canopy stops laser pulses from reaching the terrain surface. This research presents an approach for removing non-ground points from raw ALS data in densely forested areas. Smoothing splines are exploited to interpolate and fit the noisy ALS data. The presented filter utilizes a weight function to allocate weights for each point of the data. Furthermore, unlike most of the methods, the presented filtering algorithm is designed to be automatic. Three different forested areas in the United Kingdom are used to assess the performance of the algorithm. The results show that the generated DTMs from the filtered data are accurate (when compared against reference terrain data) and the performance of the method is stable for all the heavily forested data samples. The average root mean square error (RMSE) value is 0.35 m.

Keywords: Airborne laser scanning, digital terrain models, filtering, forested areas.

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Authors: S. Sadi-Nezhad, K. Khalili Damghani, N. Pilevari

Abstract:

In this article, a mathematical programming model for choosing an optimum portfolio of investments is developed. The investments are considered as investment projects. The uncertainties of the real world are associated through fuzzy concepts for coefficients of the proposed model (i. e. initial investment costs, profits, resource requirement, and total available budget). Model has been coded by using LINGO 11.0 solver. The results of a full analysis of optimistic and pessimistic derivative models are promising for selecting an optimum portfolio of projects in presence of uncertainty.

Keywords: Fuzzy Programming, Fuzzy Knapsack, FuzzyCapital Budgeting, Fuzzy Project Selection

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Authors: Acumsiri Tantiakrnpanit

Abstract:

This paper aims to examine the relationship between urbanization and income inequality in Thailand during the period 2002–2020, using a panel of data for 76 provinces collected from Thailand’s National Statistical Office (Labor Force Survey: LFS), as well as geospatial data from the U.S. Air Force Defense Meteorological Satellite Program (DMSP) and the Visible Infrared Imaging Radiometer Suite Day/Night band (VIIRS-DNB) satellite for 19 selected years. This paper employs two different definitions to identify urban areas: 1) Urban areas defined by Thailand's National Statistical Office (LFS), and 2) Urban areas estimated using nighttime light data from the DMSP and VIIRS-DNB satellite. The second method includes two sub-categories: 2.1) Determining urban areas by calculating nighttime light density with a population density of 300 people per square kilometer, and 2.2) Calculating urban areas based on nighttime light density corresponding to a population density of 1,500 people per square kilometer. The empirical analysis based on Ordinary Least Squares (OLS), fixed effects, and random effects models reveals a consistent U-shaped relationship between income inequality and urbanization. The findings from the econometric analysis demonstrate that urbanization or population density has a significant and negative impact on income inequality. Moreover, the square of urbanization shows a statistically significant positive impact on income inequality. Additionally, there is a negative association between logarithmically transformed income and income inequality. This paper also proposes the inclusion of satellite imagery, geospatial data, and spatial econometric techniques in future studies to conduct quantitative analysis of spatial relationships.

Keywords: Income inequality, nighttime light, population density, Thailand, urbanization.

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Authors: K. Jitkue, W. Srisang, C. Yaiprasert, K. Jaroensutasinee, M. Jaroensutasinee

Abstract:

This study aims at using multi-source data to monitor coral biodiversity and coral bleaching. We used coral reef at Racha Islands, Phuket as a study area. There were three sources of data: coral diversity, sensor based data and satellite data.

Keywords: Coral reefs, Remote sensing, Sea surfacetemperatue, Satellite imagery.

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Authors: Andrew John Zeller, Francis Pouatcha

Abstract:

Working according to the DevOps principle has gained in popularity over the past decade. While its extension DevSecOps started to include elements of cybersecurity, most real-life projects do not focus risk and security until the later phases of a project as teams are often more familiar with engineering and infrastructure services. To help bridge the gap between security and engineering, this paper will take six building blocks of cybersecurity and apply them to the DevOps approach. After giving a brief overview of the stages in the DevOps lifecycle, the main part discusses to what extent six cybersecurity blocks can be utilized in various stages of the lifecycle. The paper concludes with an outlook on how to stay up to date in the dynamic world of cybersecurity.

Keywords: Information security, data security, cybersecurity, DevOps, IT management.

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Authors: Tahany W. Sadak

Abstract:

Presented work discusses research results concerning the effect of the heat treatment process. Thermal fatigue which expresses repeated heating and cooling processes affect the ductility or the brittleness of the material. In this research, 70 specimens of copper (1.5 mm thickness, 85 mm length, 32 mm width) are subjected to thermal fatigue at different conditions. Heating temperatures T_h are 100, 300 and 500 °C. Number of repeated cycles N is from 1 to 100. Heating time t_h =600 Sec, and Cooling time; t_C= 900 Sec.  Results are evaluated and then compared to each other and to that of specimens without subjected to thermal fatigue.

Keywords: Copper, hardness, heat treatment, thermal fatigue, thermal analysis.

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Authors: Wei Lei, Hui Chen, Lin Lu

Abstract:

Microscopic emission and fuel consumption models have been widely recognized as an effective method to quantify real traffic emission and energy consumption when they are applied with microscopic traffic simulation models. This paper presents a framework for developing the Microscopic Emission (HC, CO, NOx, and CO2) and Fuel consumption (MEF) models for light-duty vehicles. The variable of composite acceleration is introduced into the MEF model with the purpose of capturing the effects of historical accelerations interacting with current speed on emission and fuel consumption. The MEF model is calibrated by multivariate least-squares method for two types of light-duty vehicle using on-board data collected in Beijing, China by a Portable Emission Measurement System (PEMS). The instantaneous validation results shows the MEF model performs better with lower Mean Absolute Percentage Error (MAPE) compared to other two models. Moreover, the aggregate validation results tells the MEF model produces reasonable estimations compared to actual measurements with prediction errors within 12%, 10%, 19%, and 9% for HC, CO, NOx emissions and fuel consumption, respectively.

Keywords: Emission, Fuel consumption, Light-duty vehicle, Microscopic, Modeling.

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Authors: Wen-Tsann Lin, Yung-Tsan Jou, Yih-Chuan Wu, Yuan-Du Hsiao

Abstract:

The Emergency Department of a medical center in Taiwan cooperated to conduct the research. A predictive model of triage system is contracted from the contract procedure, selection of parameters to sample screening. 2,000 pieces of data needed for the patients is chosen randomly by the computer. After three categorizations of data mining (Multi-group Discriminant Analysis, Multinomial Logistic Regression, Back-propagation Neural Networks), it is found that Back-propagation Neural Networks can best distinguish the patients- extent of emergency, and the accuracy rate can reach to as high as 95.1%. The Back-propagation Neural Networks that has the highest accuracy rate is simulated into the triage acuity expert system in this research. Data mining applied to the predictive model of the triage acuity expert system can be updated regularly for both the improvement of the system and for education training, and will not be affected by subjective factors.

Keywords: Back-propagation Neural Networks, Data Mining, Emergency Department, Triage System.

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Authors: A. Ghodbane, M. Saad, J.-F. Boland, C. Thibeault

Abstract:

Historically, actuators’ redundancy was used to deal with faults occurring suddenly in flight systems. This technique was generally expensive, time consuming and involves increased weight and space in the system. Therefore, nowadays, the on-line fault diagnosis of actuators and accommodation plays a major role in the design of avionic systems. These approaches, known as Fault Tolerant Flight Control systems (FTFCs) are able to adapt to such sudden faults while keeping avionics systems lighter and less expensive. In this paper, a (FTFC) system based on the Geometric Approach and a Reconfigurable Flight Control (RFC) are presented. The Geometric approach is used for cosmic ray fault reconstruction, while Sliding Mode Control (SMC) based on Lyapunov stability theory is designed for the reconfiguration of the controller in order to compensate the fault effect. Matlab®/Simulink® simulations are performed to illustrate the effectiveness and robustness of the proposed flight control system against actuators’ faulty signal caused by cosmic rays. The results demonstrate the successful real-time implementation of the proposed FTFC system on a non-linear 6 DOF aircraft model.

Keywords: Actuators’ faults, Fault detection and diagnosis, Fault tolerant flight control, Sliding mode control, Geometric approach for fault reconstruction, Lyapunov stability.

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Authors: J. H. Park, S. K. Lee, Y. W. Kim, D. C. Ko

Abstract:

A large variety of pipe flange is required in marine and construction industry. Pipe flanges are usually welded or screwed to the pipe end and are connected with bolts. This approach is very simple and widely used for a long time; however, it results in high development cost and low productivity, and the productions made by this approach usually have safety problem at the welding area. In this research, a new approach of forming pipe flange based on cold forging and floating die concept is presented. This innovative approach increases the effectiveness of the material usage and save the time cost compared with conventional welding method. To ensure the dimensional accuracy of the final product, the finite element analysis (FEA) was carried out to simulate the process of cold forging, and the orthogonal experiment methods were used to investigate the influence of four manufacturing factors (pin die angle, pipe flange angle, rpm, pin die distance from clamp jig) and predicted the best combination of them. The manufacturing factors were obtained by numerical and experimental studies and it shows that the approach is very useful and effective for the forming of pipe flange, and can be widely used later.

Keywords: Cold forging, FEA, finite element analysis, Forge- 3D, rotating forming, tubes.

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