Search results for: five factor model of personality

Authors: Linghua Kong, Xinxia Chen, Mika Gissler, Catharina Lavebratt

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Background: Prenatal exposure to preeclampsia has been associated with an increased risk of offspring attention-deficit/hyperactivity disorders (ADHD), autism spectrum disorder (ASD), and intellectual disability. However, little is known about the association between prenatal exposure to severe preeclampsia and neurodevelopmental and psychiatric disorders in offspring. Objective: This study aimed to assess the risk of maternal preeclampsia combined with perinatal problems, specifically low birth weight and prematurity, on offspring neuropsychiatric disorders. Methods: All singleton live births in Finland between 1996 and 2014 (n=1 012 723) were followed up in nation-wide registries until 2018. Main exposures included pre-eclampsia, small for gestational age, and delivery before 34 gestational weeks. Offspring neurodevelopmental and psychiatric disorders (ICD-10 codes) were examined as outcomes variables. Offspring birth year, sex, maternal age at delivery, parity, marital status at birth, mother's country of birth, maternal smoking, maternal gestational diabetes, maternal use of psychotropic medication during pregnancy, and maternal systemic inflammatory diseases were used as covariates. Risks for neurodevelopmental and psychiatric disorders were estimated using Cox proportional hazards modeling. Results: Of the 1 012 723 offspring, 25 901 (2.6%) were exposed to preeclampsia, and 93 281 (9.2%) were diagnosed with a neuropsychiatric disorder. Compared to births unexposed to preeclampsia, small for gestational age or delivery before 34 gestational weeks, those exposed to preeclampsia only had a 21% increase in the likelihood of any neuropsychiatric disorders after adjusting for potential confounding (adjusted HR=1.21, 95% CI: 1.15-1.26), while exposure to preeclampsia combined with small for gestational age or delivery before 34 gestational weeks had a more than twofold increased risk of having a child with neuropsychiatric disorders (adjusted HR=2.16, 95% CI: 2.02-2.32). The adjusted HR for neuropsychiatric disorders in offspring with small for gestational age or delivery before 34 gestational weeks only was 1.79 (95% CI: 1.73-1.83). In addition, the risk estimate in offspring exposed to both preeclampsia and perinatal problems was greater than those only exposed to preeclampsia for having personality disorders (adjusted HR=1.66; 95% CI: 1.07-2.57), intellectual disabilities (adjusted HR=3.47; 95% CI: 2.86-4.22), specific developmental disorders (adjusted HR=2.91; 95% CI: 2.69-3.15), ASD (adjusted HR=1.75; 95% CI: 1.42-2.17), ADHD and conduct disorders (adjusted HR=2.00; 95%CI: 1.76-2.27), and other behavioral and emotional disorders (adjusted HR=2.09; 95% CI: 1.84-2.37). Conclusion: In utero exposure to severe preeclampsia increased the risk of several neurodevelopmental and psychiatric disorders in offspring. Our findings are relevant to women with hypertensive disorders with regard to pregnancy consultation and management and may yield effective clues for the prevention of neurodevelopmental and psychiatric disorders in childhood.

Keywords: low birth weight, neurodevelopmental disorders, preeclampsia, prematurity, psychiatric disorders

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Authors: Dara Singh, Keikhosrow Firouzbakhsh, Mohammad Taghi Ahmadian

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In this paper, conventional laser Keratoplasty surgeries in the human eye are studied. For this purpose, a validated 3D finite volume model of the human eye is introduced. In this model the fluid flow has also been considered. The discretized domain of the human eye incorporates a bio-heat transfer equation coupled with a Boussinesq equation. Both continuous and pulsed lasers have been modeled and the results are compared. Moreover, two different conventional surgical positions that are upright and recumbent are compared for these laser therapies. The simulation results show that in these conventional surgeries, the temperature rises above the critical values at the laser insertion areas. However, due to the short duration and the localized nature, the potential damages are restricted to very small regions and can be ignored. The conclusion is that the present day lasers are acceptably safe to the human eye.

Keywords: eye, heat-transfer, keratoplasty laser, surgery

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Authors: Nicolas Haber

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The study addresses the design process of integrated product-service offerings as a measure of answering environmental sustainability concerns by replacing stand-alone physical artefacts with comprehensive solutions relying on functional results rather than conventional product sales. However, views regarding this transformation are dissimilar and differentiated: The study discusses the importance and requirements of product-service systems before analysing the theoretical studies accomplished in the extent of their design and development processes. Based on this, a framework, built on a design science approach, is proposed, where the distinct approaches from the literature are merged towards a unified structure serving as a generic methodology to designing product-service systems. Each stage of this model is then developed to present a holistic design proposal called the Functional Engineered Product-Service System (FEPSS) model. Product-service systems are portrayed as customisable solutions tailored to specific settings and defined circumstances. Moreover, the approaches adopted to guide the design process are diversified. A thorough analysis of the design strategies and development processes however, allowed the extraction of a design backbone, valid to varied situations and contexts whether they are product-oriented, use-oriented or result-oriented. The goal is to guide manufacturers towards an eased adoption of these integrated offerings, given their inherited environmental benefits, by proposing a robust all-purpose design process.

Keywords: functional product, integrated product-service offerings, product-service systems, sustainable design

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Authors: I. Rodionov, A. Semenov, E. Gosteva, O. Sokolova

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Currently, the venture capital becomes more and more advanced and effective source of the innovation project financing, connected with a high-risk level. In the developed countries, it plays a key role in transforming innovation projects into successful businesses and creating prosperity of the modern economy. Actually, in Russia there are many necessary preconditions for creation of the effective venture investment system: the network of the public institutes for innovation financing operates; there is a significant number of the small and medium-sized enterprises, capable to sell production with good market potential. However, the current system does not confirm the necessary level of efficiency in practice that can be substantially explained by the absence of the accurate plan of action to form the national venture model and by the lack of experience of successful venture deals with profitable exits in Russian economy. This paper studies the influence of various factors on the venture industry development by the example of the IT-sector in Russia. The choice of the sector is based on the fact, that this segment is the main driver of the venture capital market growth in Russia, and the necessary set of data exists. The size of investment of the second round is used as the dependent variable. To analyse the influence of the previous round such determinant as the volume of the previous (first) round investments is used. There is also used a dummy variable in regression to examine that the participation of an investor with high reputation and experience in the previous round can influence the size of the next investment round. The regression analysis of short-term interrelations between studied variables reveals prevailing influence of the volume of the first round investments on the venture investments volume of the second round. Because of the research, the participation of investors with first-class reputation has a small impact on an indicator of the value of investment of the second round. The expected positive dependence of the second round investments on the forecasted market growth rate now of the deal is also rejected. So, the most important determinant of the value of the second-round investment is the value of first–round investment, so it means that the most competitive on the Russian market are the start-up teams which can attract more money on the start, and the target market growth is not the factor of crucial importance.

Keywords: venture industry, venture investment, determinants of the venture sector development, IT-sector

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Authors: Ofosuhene O. Apenteng, Noor Azina Ismail

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The human immunodeficiency virus (HIV) that causes acquired immune deficiency syndrome (AIDS) remains a global cause of morbidity and mortality. It has caused panic since its emergence. Relationships between migration and HIV/AIDS have become complex. In the absence of prospectively designed studies, dynamic mathematical models that take into account the migration movement which will give very useful information. We have explored the utility of mathematical models in understanding transmission dynamics of HIV and AIDS and in assessing the magnitude of how migration has impact on the disease. The model was calibrated to HIV and AIDS incidence data from Malaysia Ministry of Health from the period of 1986 to 2011 using Bayesian analysis with combination of Markov chain Monte Carlo method (MCMC) approach to estimate the model parameters. From the estimated parameters, the estimated basic reproduction number was 22.5812. The rate at which the susceptible individual moved to HIV compartment has the highest sensitivity value which is more significant as compared to the remaining parameters. Thus, the disease becomes unstable. This is a big concern and not good indicator from the public health point of view since the aim is to stabilize the epidemic at the disease-free equilibrium. However, these results suggest that the government as a policy maker should make further efforts to curb illegal activities performed by migrants. It is shown that our models reflect considerably the dynamic behavior of the HIV/AIDS epidemic in Malaysia and eventually could be used strategically for other countries.

Keywords: epidemic model, reproduction number, HIV, MCMC, parameter estimation

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Authors: Sarra Zaied, Arthur Bonpain, Pierre Yves Fravallo

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The permanent supply of marine litter implies their accumulation in the oceans, which causes the presence of more compact wastes layers. Their Spatio-temporal distribution is never homogeneous and depends mainly on the hydrodynamic characteristics of the environment and the size and location of the wastes. As part of optimizing collect of marine plastic wastes, it is important to measure and monitor their evolution over time. For this, many research studies have been dedicated to describing the wastes behavior in order to identify their accumulation in oceans areas. Several models are therefore developed to understand the mechanisms that allow the accumulation and the displacements of marine litter. These models are able to accurately simulate the drift of wastes to study their behavior and stranding. However, these works aim to study the wastes behavior over a long period of time and not at the time of waste collection. This work investigates the transport of floating marine litter (FML) to provide basic information that can help in optimizing wastes collection by proposing a model for predicting their behavior during collection. The proposed study is based on a Lagrangian modeling approach that uses the main factors influencing the dynamics of the waste. The performance of the proposed method was assessed on real data collected from the Copernicus Marine Environment Monitoring Service (CMEMS). Evaluation results in the Java Sea (Indonesia) prove that the proposed model can effectively predict the position and the velocity of marine wastes during collection.

Keywords: floating marine litter, lagrangian transport, particle-tracking model, wastes drift

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Authors: Paolo Russu

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The purpose of the present paper is to highlight some features of an economic growth model with environmental negative externalities, giving rise to a three-dimensional dynamic system. In particular, we show that the economy, which is based on a Perfect-Substitution Technologies function of production, has no neither indeterminacy nor poverty trap. This implies that equilibrium select by economy depends on the history (initial values of state variable) of the economy rather than on expectations of economies agents. Moreover, by contrast, we prove that the basin of attraction of locally equilibrium points may be very large, as they can extend up to the boundary of the system phase space. The infinite-horizon optimal control problem has the purpose of maximizing the representative agent’s instantaneous utility function depending on leisure and consumption.

Keywords: Hopf bifurcation, open-access natural resources, optimal control, perfect-substitution technologies, Poincarè compactification

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Authors: Awol Mekonnen, Temesgen Sidamo, Epherm Engdawork, Kaleab Asresb

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Ethnopharmacological Relevance: The leaves of Kalanchoe petitiana A. Rich (Crassulaceae) are used in Ethiopian folk medicine for treatment of evil eye, fractured surface for bone setting and several skin disorders including for the treatment of sores, boils, and malignant wounds. Aim of the Study: In order to scientifically prove the claimed utilization of the plant, the effects of the extracts and the fractions were investigated using in vivo excision, incision and dead space wound models. Materials and Method: Mice were used for wound healing study, while rats and rabbit were used for skin irritation test. For studying healing activity, 80% methanolic extract and the fractions were formulated in strength of 5% and 10%, either as ointment (hydroalcoholic extract, aqueous and methanol fractions) or gel (chloroform fraction). Oral administration of the crude extract was used for dead space model. Negative controls were treated either with simple ointment or sodium carboxyl methyl cellulose xerogel, while positive controls were treated with nitrofurazone (0.2 w/v) skin ointment. Negative controls for dead space model were treated with 1% carboxy methyl cellulose. Parameters, including rate of wound contraction, period of complete epithelializtion, hydroxyproline contents and skin breaking strength were evaluated. Results: Significant wound healing activity was observed with ointment formulated from the crude extract at both 5% and 10% concentration (p<0.01) compared to controls in both excision and incision models. In dead space model, 600 mg/kg (p<0.01), but not 300 mg/kg, significantly increased hydroxyproline content. Fractions showed variable effect, with the chloroform fraction lacking any significant effect. Both 5% and 10% formulations of the aqueous and methanolic fractions significantly increased wound contraction, decreased epithelializtion time and increased hydroxyproline content in excision wound model (p<0.05) as compared to controls. These fractions were also endowed with higher skin breaking strength in incision wound model (p<0.01). Conclusions: The present study provided evidence that the leaves of Kalanchoe petitiana A. Rich possess remarkable wound healing activities supporting the folkloric assertion of the plant. Fractionation revealed that polar or semi-polar compound may play vital role, as both aqueous and methanolic fractions were endowed with wound healing activity.

Keywords: wound healing, Kalanchoae petitiana, excision wound, incision wound, dead space model

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Authors: Conrad Weber

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The modelling of railway noise over large projects areas can be very time consuming in terms of preparing the noise models and calculation time. An open-source GIS program has been utilised to assist with the modelling of operational noise levels for 675km of railway corridor. A range of GIS algorithms were utilised to break up the noise model area into manageable calculation sizes. GIS was utilised to prepare and filter a range of noise modelling inputs, including building files, land uses and ground terrain. A spreadsheet was utilised to manage the accuracy of key input parameters, including train speeds, train types, curve corrections, bridge corrections and engine notch settings. GIS was utilised to present the final noise modelling results. This paper explains the noise modelling process and how the spreadsheet and GIS were utilised to accurately model this massive project efficiently.

Keywords: noise, modeling, GIS, rail

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Authors: G. S. Androulakis, G. Deli, M. Kaisari, N. Mihos

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Teaching practices at the university level have changed and developed during the last decade. Implementation of inverted classroom method in secondary education consists of a well-formed basis for academic teachers. On the other hand, distance learning is a well-known field in education research and widespread as a method of teaching. Nonetheless, the new pandemic found many Universities all over the world unprepared, which made adaptations to new methods of teaching a necessity. In this paper, we analyze a model of an inverted university classroom in a distance learning context. Thus, the main purpose of our research is to investigate students’ difficulties as they transit to a new style of teaching and explore their learning development during a semester totally different from others. Our teaching experiment took place at the Business Administration department of the University of Patras, in the context of two courses: Calculus, a course aimed at first-year students, and Statistics, a course aimed at second-year students. Second-year students had the opportunity to attend courses in the university classroom. First-year students started their semester with distance learning. Using a comparative study of these two groups, we explored significant differences in students’ learning procedures. Focused group interviews, written tests, analyses of students’ dialogues were used in a mixed quantity and quality research. Our analysis reveals students’ skills, capabilities but also a difficulty in following, non-traditional style of teaching. The inverted classroom model, according to our findings, offers benefits in the educational procedure, even in a distance learning environment.

Keywords: distance learning, higher education, inverted classroom, mathematics teaching

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Authors: Michael Nicolosi, Karola Dillenburger

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The University of California at Los Angeles-Young Autism Project (UCLA-YAP) provides one of the best-known and most researched comprehensive applied behavior analysis-based intervention models for young children on the autism spectrum. This paper reports a systematic literature review of replication studies over more than 30 years. The data show that the relatively high-intensity UCLA-YAP model can be greatly beneficial for children on the autism spectrum, particularly with regard to their cognitive functioning and adaptive behavior. This review concludes that, while more research is always welcome, the impact of the UCLA-YAP model on autism interventions is justified by more than 30 years of outcome evidence.

Keywords: ABA, applied behavior analysis, autism, California at Los Angeles Young Autism project, intervention, Lovaas, UCLA-YAP

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Authors: Navid Zarif Karimi, Hossein Heidary, Giangiacomo Minak, Mehdi Ahmadi

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In this paper analytical model based on the mechanics of oblique cutting, linear elastic fracture mechanics (LEFM) and bending plate theory has been presented to determine the critical feed rate causing delamination in drilling of composite materials. Most of the models in this area used LEFM and bending plate theory; hence, they can only determine the critical thrust force which is an incorporable parameter. In this model by adding cutting oblique mechanics to previous models, critical feed rate has been determined. Also instead of simplification in loading condition, actual thrust force induced by chisel edge and cutting lips on composite plate is modeled.

Keywords: composite material, delamination, drilling, thrust force

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Authors: Margarita Zavala, Gabriel Chavira, José González, Jorge Orozco, Julio Rolón, Roberto Pichardo

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Adolescence is a neuralgic stage in the formation of every human being, generally this stage is when the middle school level is studied. In 2006, Mexico incorporated 'mentoring' space to assist students in their integration and participation in life. In public middle schools, it is sometimes difficult to be aware of situations that affect students because of the number of them and traditional records management. With this, they lose the opportunity to provide timely support as a preventive way. In order to provide this support, it is required to know the students by detecting the relevant information that has greater impact on their learning process. This research is looking to check if it is possible to identify student’s relevant information to detect when it is at risk, and then to propose a model to manage in a proper way such information.

Keywords: adolescence, mentoring, middle school students, mentoring system support

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Authors: Etienne K. Ngoy

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This analysis suggests that the comprehensive degradation caused by any environmental factor on fiber reinforced plastics under mechanical stress can be measured as a change in viscoelastic properties of the material. The change in viscoelastic characteristics is experimentally determined as a time-dependent function expressing the amplification of the stress relaxation. The variation of this experimental function provides a measure of the environmental degradation rate. Where real service environment conditions can be reliably simulated in the laboratory, it is possible to generate master curves that include environmental degradation effect and hence predict the durability of the fiber reinforced plastics under environmental degradation.

Keywords: environmental effects, fiber reinforced plastics durability, prediction, stress effect

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Authors: Narava Manose

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Distillation is a very old separation technology for separating liquid mixtures that can be traced back to the chemists in Alexandria in the first century A. D. Today distillation is the most important industrial separation technology. By the eleventh century, distillation was being used in Italy to produce alcoholic beverages. At that time, distillation was probably a batch process based on the use of just a single stage, the boiler. The word distillation is derived from the Latin word destillare, which means dripping or trickling down. By at least the sixteenth century, it was known that the extent of separation could be improved by providing multiple vapor-liquid contacts (stages) in a so called Rectifactorium. The term rectification is derived from the Latin words rectefacere, meaning to improve. Modern distillation derives its ability to produce almost pure products from the use of multi-stage contacting. Throughout the twentieth century, multistage distillation was by far the most widely used industrial method for separating liquid mixtures of chemical components.The basic principle behind this technique relies on the different boiling temperatures for the various components of the mixture, allowing the separation between the vapor from the most volatile component and the liquid of other(s) component(s). •Developed a simple non-linear model of a binary distillation column using Skogestad equations in Simulink. •We have computed the steady-state operating point around which to base our analysis and controller design. However, the model contains two integrators because the condenser and reboiler levels are not controlled. One particular way of stabilizing the column is the LV-configuration where we use D to control M_D, and B to control M_B; such a model is given in cola_lv.m where we have used two P-controllers with gains equal to 10.

Keywords: modelling, distillation column, control, binary distillation

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Authors: A. Samer Ezeldin, Sarah A. Fotouh

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Optimization of resources is very important in all fields, as in construction management. Project managers have to face problems regarding management of cost, time and available resources of single projects and more problems arise when managing multiple projects. Most of the studies focused on optimization of resources for a single project, but, this paper will discuss the design and modeling of multiple resources optimization for multiple projects using Genetic Algorithm. Most of the companies in construction industry optimize the resources for single projects only, but with the presence of several mega projects in several developing countries running at the same time, there is a need for a model to enhance the efficiency of available resources and decreases the fluctuation as much as possible. The proposed model calculates the cost of each resource, tries to minimize the cost of extra resources as much as possible and generates the schedule of each project within a selected program.

Keywords: construction management, genetic algorithm, multiple projects, multiple resources, optimization

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Authors: C. B. Le, V. N. Pham

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In modern data analysis, multi-source data appears more and more in real applications. Multi-source data clustering has emerged as a important issue in the data mining and machine learning community. Different data sources provide information about different data. Therefore, multi-source data linking is essential to improve clustering performance. However, in practice multi-source data is often heterogeneous, uncertain, and large. This issue is considered a major challenge from multi-source data. Ensemble is a versatile machine learning model in which learning techniques can work in parallel, with big data. Clustering ensemble has been shown to outperform any standard clustering algorithm in terms of accuracy and robustness. However, most of the traditional clustering ensemble approaches are based on single-objective function and single-source data. This paper proposes a new clustering ensemble method for multi-source data analysis. The fuzzy optimized multi-objective clustering ensemble method is called FOMOCE. Firstly, a clustering ensemble mathematical model based on the structure of multi-objective clustering function, multi-source data, and dark knowledge is introduced. Then, rules for extracting dark knowledge from the input data, clustering algorithms, and base clusterings are designed and applied. Finally, a clustering ensemble algorithm is proposed for multi-source data analysis. The experiments were performed on the standard sample data set. The experimental results demonstrate the superior performance of the FOMOCE method compared to the existing clustering ensemble methods and multi-source clustering methods.

Keywords: clustering ensemble, multi-source, multi-objective, fuzzy clustering

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Authors: Junior Nomani

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This paper presents a novel approach to modelling the metal cutting of duplex stainless steels, a two-phase alloy regarded as a difficult-to-machine material. Calculation and control of shear strain and stresses during cutting are essential to achievement of ideal cutting conditions. Too low or too high leads to higher required cutting force or excessive heat generation causing premature tool wear failure. A 2D finite element cutting model was created based on electron backscatter diffraction (EBSD) data imagery of duplex microstructure. A mesh was generated using ‘object-oriented’ software OOF2 version V2.1.11, converting microstructural images to quadrilateral elements. A virtual workpiece was created on ABAQUS modelling software where a rigid body toolpiece advanced towards workpiece simulating chip formation, generating serrated edge chip formation cutting. Model results found calculated stress strain contour plots correlated well with similar finite element models tied with austenite stainless steel alloys. Virtual chip form profile is also similar compared experimental frozen machining chip samples. The output model data provides new insight description of strain behavior of two phase material on how it transitions from workpiece into the chip.

Keywords: Duplex stainless steel, ABAQUS, OOF2, Chip formation

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Authors: Minjuan Sun

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Ever since the late 1990s, China has experienced explosive growth in consumer lending, especially in short-term consumer loans, among which, the growth rate of non-bank lending has surpassed bank lending due to the development in financial technology. On the other hand, China does not have a universal credit scoring and registration system that can guide lenders during the processes of credit evaluation and risk control, for example, an individual’s bank credit records are not available for online lenders to see and vice versa. Given this context, the purpose of this paper is three-fold. First, we explore if and how alternative digital footprint data can be utilized to assess borrower’s creditworthiness. Then, we perform a comparative analysis of machine learning methods for the canonical problem of credit default prediction. Finally, we analyze, from an institutional point of view, the necessity of establishing a viable and nationally universal credit registration and scoring system utilizing online digital footprints, so that more people in China can have better access to the consumption loan market. Two different types of digital footprint data are utilized to match with bank’s loan default records. Each separately captures distinct dimensions of a person’s characteristics, such as his shopping patterns and certain aspects of his personality or inferred demographics revealed by social media features like profile image and nickname. We find both datasets can generate either acceptable or excellent prediction results, and different types of data tend to complement each other to get better performances. Typically, the traditional types of data banks normally use like income, occupation, and credit history, update over longer cycles, hence they can’t reflect more immediate changes, like the financial status changes caused by the business crisis; whereas digital footprints can update daily, weekly, or monthly, thus capable of providing a more comprehensive profile of the borrower’s credit capabilities and risks. From the empirical and quantitative examination, we believe digital footprints can become an alternative information source for creditworthiness assessment, because of their near-universal data coverage, and because they can by and large resolve the "thin-file" issue, due to the fact that digital footprints come in much larger volume and higher frequency.

Keywords: credit score, digital footprint, Fintech, machine learning

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Authors: Chansheng He, Zhongfu Wang, Xiao Bai, Jie Tian, Xin Jin

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Heterogeneity of soil hydraulic properties directly affects hydrological processes at different scales. Understanding heterogeneity of soil hydraulic properties such as soil moisture is therefore essential for modeling watershed ecohydrological processes, particularly in hard to access, topographically complex mountainous watersheds. This study maps spatial variations of soil moisture by in situ observation network that consists of sampling points, zones, and tributaries, and monitors corresponding hydrological variables of air and soil temperatures, evapotranspiration, infiltration, and runoff in the Upper Reach of the Heihe River Watershed, a second largest inland river (terminal lake) with a drainage area of over 128,000 km² in Northwest China. Subsequently, the study uses a hydrological model, SWAT (Soil and Water Assessment Tool) to simulate the effects of heterogeneity of soil moisture on watershed hydrological processes. The spatial clustering method, Full-Order-CLK was employed to derive five soil heterogeneous zones (Configuration 97, 80, 65, 40, and 20) for soil input to SWAT. Results show the simulations by the SWAT model with the spatially clustered soil hydraulic information from the field sampling data had much better representation of the soil heterogeneity and more accurate performance than the model using the average soil property values for each soil type derived from the coarse soil datasets. Thus, incorporating detailed field sampling soil heterogeneity data greatly improves performance in hydrologic modeling.

Keywords: heterogeneity, soil moisture, SWAT, up-scaling

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Authors: Monika Zalewska

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Hans Kelsen was a versatile legal thinker whose achievements in the fields of legal theory, international law, and the theory of democracy are remarkable. All of the fields tackled by Kelsen are regarded as part of his “pure theory of law.” While the link between international law and Kelsen’s pure theory of law is apparent, the same cannot be said about the link between the theory of democracy and his pure theory of law. On the contrary, the general thinking concerning Kelsen’s thought is that it can be used to legitimize authoritarian regimes. The aim of this presentation is to address this concern by identifying the common ground between Kelsen’s pure theory of law and his theory of democracy and to show that they are compatible in a way that his pure theory of law and authoritarianism cannot be. The conceptual analysis of the purity of Kelsen’s theory and his goal of creating ideology-free legal science hints at how Kelsen’s pure theory of law and the theory of democracy are brought together. The presentation will first demonstrate that these two conceptions have common underlying values and meta-ethical convictions. Both are founded on relativism and a rational worldview, and the aim of both is peaceful co-existence. Second, it will be demonstrated that the separation of law and morality provides the maximum space for deliberation within democratic processes. The conclusion of this analysis is that striking similarities exist between Kelsen’s legal theory and his theory of democracy. These similarities are grounded in the Enlightenment tradition and its values, including rationality, a scientific worldview, tolerance, and equality. This observation supports the claim that, for Kelsen, legal positivism and the theory of democracy are not two separate theories but rather stem from the same set of values and from Kelsen’s relativistic worldview. Furthermore, three main issues determine Kelsen’s orientation toward a positivistic and democratic outlook. The first, which is associated with personality type, is the distinction between absolutism and relativism. The second, which is associated with the values that Kelsen favors in the social order, is peace. The third is legality, which creates the necessary condition for democracy to thrive and reveals that democracy is capable of fulfilling Kelsen’s ideal of law at its fullest. The first two categories exist in the background of Kelsen’s pure theory of law, while the latter is an inherent part of Kelsen’s concept of law. The analysis of the text concerning natural law doctrine and democracy indicates that behind the technical language of Kelsen’s pure theory of law is a strong concern with the trends that appeared after World War I. Despite his rigorous scientific mind, Kelsen was deeply humanistic. He tried to create a powerful intellectual weapon to provide strong arguments for peaceful coexistence and a rational outlook in Europe. The analysis provided by this presentation facilitates a broad theoretical, philosophical, and political understanding of Kelsen’s perspectives and, consequently, urges a strong endorsement of Kelsen’s approach to constitutional democracy.

Keywords: hans kelsen, democracy, legal positivism, pure theory of law

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Authors: Gonzalez Carlos, Martinez Fransisco

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The creation of a seismic prediction model that considers all the regional variations and perfectly adjusts its results to the response spectra is very complicated. To achieve statistically acceptable results, it is necessary to process a sufficiently robust data set, and even if high efficiencies are achieved, this model will only work properly in this region. However, when using it in other regions, differences are found due to different parameters that have not been calibrated to other regions, such as the site effect. The fact that impedance contrasts, as well as other factors belonging to the site, have a great influence on the local response is well known, which is why this work, using the residual method, is intended to establish a regional calibration of the corresponding parameters site effect for the Spain region in the global GMPM BSSA 14.

Keywords: GMPM, seismic prediction equations, residual method, response spectra, impedance contrast

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Authors: A. Shoiynbek, K. Kozhakhmet, P. Menezes, D. Kuanyshbay, D. Bayazitov

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Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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Authors: Mohamed Othmani, Yassine Khlifi

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This paper presents a technique for compact three dimensional (3D) object model reconstruction using wavelet networks. It consists to transform an input surface vertices into signals,and uses wavelet network parameters for signal approximations. To prove this, we use a wavelet network architecture founded on several mother wavelet families. POLYnomials WindOwed with Gaussians (POLYWOG) wavelet families are used to maximize the probability to select the best wavelets which ensure the good generalization of the network. To achieve a better reconstruction, the network is trained several iterations to optimize the wavelet network parameters until the error criterion is small enough. Experimental results will shown that our proposed technique can effectively reconstruct an irregular 3D object models when using the optimized wavelet network parameters. We will prove that an accurateness reconstruction depends on the best choice of the mother wavelets.

Keywords: 3d object, optimization, parametrization, polywog wavelets, reconstruction, wavelet networks

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Authors: Feng-Tsung Cheng, Shu-Li Wang, Mei-Fang Wu, , Hui-Yu Chuang

Abstract:

Due to the rapid development of modern technology, the widespread usage of the Internet makes business environment changing quickly. In order to be a leader in the global competitive market and to pursuit survive, “changing” becomes an unspoken rules need to follow for the company survival. The purpose of this paper is to build change model by using SWOT, strategy map, and balance scorecard, KPI and change management theory. The research findings indicate that organizational change plan formulated by the case company should require the employee to resist change factors and performance management system issues into consideration and must be set organizational change related programs, such as performance appraisal reward system, consulting and counseling mechanisms programs to improve motivation and reduce staff negative emotions. Then according to the model revised strategy maps and performance indicators proposed in this paper, such as strategy maps add and modify corporate culture, improve internal processes management, increase the growth rate of net income and other strategies. The performance indicators are based on strategy maps new and modified by adding net income growth rate, to achieve target production rate, manpower training achievement rates and other indicators, through amendments to achieve the company’s goal, be a leading brand of precision machinery industry.

Keywords: organizational change, SWOT analysis, strategy maps, performance indicators

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Authors: Pongsatorn Tantrabundit, Lersak Phothong, Ong-art Chanprasitchai

Abstract:

Due to the emergence of the Internet, it has extended the traditional Word-of-Mouth (WOM) to a new form called “Electronic Word-of-Mouth (eWOM).” Unlike traditional WOM, eWOM is able to present information in various ways by applying different components. Each eWOM component generates different effects on online consumer behavior. This research investigates the effects of Webcare (responding message) from product/ service providers on negative eWOM by applying two types of products (search and experience). The proposed conceptual model was developed based on the combination of the stages in consumer decision-making process, theory of reasoned action (TRA), theory of planned behavior (TPB), the technology acceptance model (TAM), the information integration theory and the elaboration likelihood model. The methodology techniques used in this study included multivariate analysis of variance (MANOVA) and multiple regression analysis. The results suggest that Webcare does slightly increase Thai online consumer’s perceptions on perceived eWOM trustworthiness, information diagnosticity and quality. For negative eWOM, we also found that perceived eWOM Trustworthiness, perceived eWOM diagnosticity and quality have a positive relationship with eWOM influence whereas perceived valence has a negative relationship with eWOM influence in Thai online consumers.

Keywords: consumer behavior, electronic word-of-mouth, online review, online word-of-mouth, Thai online consumer, webcare

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Authors: Taehan Lee

Abstract:

We consider a network design problem which has shortest routing restriction based on the values determined by the installed facilities on each arc. In conventional multicommodity network design problem, a commodity can be routed through any possible path when the capacity is available. But, we consider a problem in which the commodity between two nodes must be routed on a path which has shortest metric value and the link metric value is determined by the installed facilities on the link. By this routing restriction, the problem has a distinct characteristic. We present an integer programming formulation containing the primal-dual optimality conditions to the shortest path routing. We give some computational results for the model.

Keywords: integer programming, multicommodity network design, routing, shortest path

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Authors: Georgia C. Kosta, Christos S. Nicolaidis

Abstract:

The present paper discusses the role of teams’ climate in the intrapreneurial process. Intrapreneurship, which corresponds for entrepreneurship in existing organizations, puts special emphasis on climate as an influential factor of the intrapreneurial behavior. Although climate exists at every level and in every subgroup of the organizational structure, research focuses mainly on the study of climate that characterizes organization as a whole. However, the climate of a work team may differ radically from the organizational climate, and in fact it can be far more influential. The paper provides a conceptual analysis of organizational climate from the intrapreneurial point of view, and sheds light upon teams’ climate role in the intrapreneurial posture.

Keywords: entrepreneurship, innovation, intrapreneurship, organizational climate, teams’ climate

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Authors: Michael Tilahun Mulugeta

Abstract:

Pedestrians are the most vulnerable road users as they are more exposed to the risk of collusion. Pedestrian safety at road intersections still remains the most vital and yet unsolved issue in Addis Ababa, Ethiopia. One of the critical points in pedestrian safety is the occurrence of conflict between turning vehicle and pedestrians at un-signalized intersection. However, a better understanding of the factors that affect the likelihood of the conflicts would help provide direction for countermeasures aimed at reducing the number of crashes. This paper has sorted to explore a model to describe the relation between traffic conflicts and influencing factors using Multiple Linear regression methodology. In this research the main focus is to study the interaction of turning (left & right) vehicle with pedestrian at unsignalized intersections. The specific objectives also to determine factors that affect the number of potential conflicts and develop a model of potential conflict.

Keywords: potential, regression analysis, pedestrian, conflicts

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Authors: Chen Xi, Lao Xuerui, Li Junjie, Jiang Yike, Wang Hanwei, Zeng Zihao

Abstract:

To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behaviour recognition models, to provide empirical data such as 'pedestrian flow data and human behavioural characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, convolutional neural network

Procedia PDF Downloads 110