Search results for: rupture risk prediction

Authors: Mohammad Aziz Shah Mohamed Arip, Aslina Ahmad, Fauziah Mohd Sa'ad, Samsiah Mohd Jais, Syed Sofian Syed Salim

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This experimental study evaluates the effect of using Cognitive-Behavioral Therapy (CBT) and Multidimensional Self- Concept Model (MSCM) in a drug prevention programme to increase resiliency and reduce aggression among at-risk youth in Malaysia. A number of 60 (N=60) university students who were at-risk of taking drugs were involved in this study. Participants were identified with self-rating scales, Adolescent Resilience Attitude Scale (ARAS) and Aggression Questionnaire. Based on the mean score of these instruments, the participants were divided into the treatment group, and the control group. Data were analyzed using t-test. The finding showed that the mean score of resiliency was increased in the treatment group compared to the control group. It also shows that the mean score of aggression was reduced in the treatment group compared to the control group. Drug Prevention Programme was found to help in enhancing resiliency and reducing aggression among participants in the treatment group compared to the controlled group. Implications were given regarding the preventive actions on drug abuse among youth in Malaysia.

Keywords: Drug Prevention Programme, Cognitive-Behavioral Therapy (CBT), Multidimensional Self Concept Model (MSCM), resiliency, aggression, at-risk youth.

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Authors: Seyed Hossein Iranmanesh, Zahra Mokhtari

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Estimation time and cost of work completion in a project and follow up them during execution are contributors to success or fail of a project, and is very important for project management team. Delivering on time and within budgeted cost needs to well managing and controlling the projects. To dealing with complex task of controlling and modifying the baseline project schedule during execution, earned value management systems have been set up and widely used to measure and communicate the real physical progress of a project. But it often fails to predict the total duration of the project. In this paper data mining techniques is used predicting the total project duration in term of Time Estimate At Completion-EAC (t). For this purpose, we have used a project with 90 activities, it has updated day by day. Then, it is used regular indexes in literature and applied Earned Duration Method to calculate time estimate at completion and set these as input data for prediction and specifying the major parameters among them using Clem software. By using data mining, the effective parameters on EAC and the relationship between them could be extracted and it is very useful to manage a project with minimum delay risks. As we state, this could be a simple, safe and applicable method in prediction the completion time of a project during execution.

Keywords: Data Mining Techniques, Earned Duration Method, Earned Value, Estimate At Completion.

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Authors: E. Harrer, M. Mauerhofer, T. Werginz

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As a result of intensive competition, the building sector is suffering from a high degree of rivalry. Furthermore, there can be observed an unbalanced distribution of project risks. Clients are aimed to shift their own risks into the sphere of the constructors or planners. The consequence of this is that the number of conflicts between the involved parties is inordinately high or even increasing; an alternative approach to counter on that developments are cooperative project forms in the construction sector. This research compares conventional contract models and models with partnering agreements to examine the influence on project risks by an early integration of the involved parties. The goal is to show up deviations in different project stages from the design phase to the project transfer phase. These deviations are evaluated by a survey of experts from the three spheres: clients, contractors and planners. By rating the influence of the participants on specific risk factors it is possible to identify factors which are relevant for a smooth project execution.

Keywords: Collaborative work, construction industry, contract-models, influence, partnering, project management, risk.

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Authors: R. Bourziza, W. El Khoumsi, I. Mghabbar, I. Rahou

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The flood-risk zones called Merjas are lowlands that are flooded during the rainy season. Indeed, these depressed areas were reclaimed to dry them out in order to exploit their agricultural potential. Thus, farmers were able to start exploiting these drained lands. As the development of modern agriculture in Morocco progressed, farmers began to practice irrigated agriculture. In a context of vulnerability to floods and the need for optimal exploitation of the agricultural potential of the flood-risk zones, the question of how farmers are adapting to this context and the degree of exploitation of this potential arises. It is in these circumstances that this work was initiated, aiming at the characterization of irrigation practices in the flood-risk zones of the Ghareb lowland (Morocco). This characterization is based on two main axes: the characterization of irrigation techniques used, as well as the management of irrigation in these areas. In order to achieve our objective, two complementary approaches have been adopted; the first one is based on interviews with administrative agents and on farmer surveys, and the second one is based on field measurements of a few parameters, such as flow rate, pressure, uniformity coefficient of drippers and salinity. The results of this work led to conclude that the choice of the practiced crop (crop resistant to excess water in winter and vegetable crops during other seasons) and the availability and nature of water resources are the main criteria that determine the choice of the irrigation system. Even if irrigation management is imprecise, farmers are able to achieve agricultural yields that are comparable to those recorded in the entire irrigated perimeter. However, agricultural yields in these areas are still threatened by climate change, since these areas play the role of water retaining basins during floods by protecting the downstream areas, which can also damage the crops there instilled during the autumn. This work has also noted that the predominance of private pumping in flood-risk zones in the coastal zone creates a risk of marine intrusion, which risks endangering the groundwater table. Thus, this work enabled us to understand the functioning and the adaptation measures of these vulnerable zones for the sustainability of the Merjas and a better valorization of these marginalized lowlands.

Keywords: Flood-risk zones, irrigation practices, climate change, adaptation measures.

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Authors: Nahid Ardalani, Ahmadreza Khoogar, H. Roohi

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In this paper we compare the response of linear and nonlinear neural network-based prediction schemes in prediction of received Signal-to-Interference Power Ratio (SIR) in Direct Sequence Code Division Multiple Access (DS/CDMA) systems. The nonlinear predictor is Multilayer Perceptron MLP and the linear predictor is an Adaptive Linear (Adaline) predictor. We solve the problem of complexity by using the Minimum Mean Squared Error (MMSE) principle to select the optimal predictors. The optimized Adaline predictor is compared to optimized MLP by employing noisy Rayleigh fading signals with 1.8 GHZ carrier frequency in an urban environment. The results show that the Adaline predictor can estimates SIR with the same error as MLP when the user has the velocity of 5 km/h and 60 km/h but by increasing the velocity up-to 120 km/h the mean squared error of MLP is two times more than Adaline predictor. This makes the Adaline predictor (with lower complexity) more suitable than MLP for closed-loop power control where efficient and accurate identification of the time-varying inverse dynamics of the multi path fading channel is required.

Keywords: Power control, neural networks, DS/CDMA mobilecommunication systems.

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Authors: Tessy Badriyah, Jim S. Briggs, Dave R. Prytherch

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It is well known that Logistic Regression is the gold standard method for predicting clinical outcome, especially predicting risk of mortality. In this paper, the Decision Tree method has been proposed to solve specific problems that commonly use Logistic Regression as a solution. The Biochemistry and Haematology Outcome Model (BHOM) dataset obtained from Portsmouth NHS Hospital from 1 January to 31 December 2001 was divided into four subsets. One subset of training data was used to generate a model, and the model obtained was then applied to three testing datasets. The performance of each model from both methods was then compared using calibration (the χ2 test or chi-test) and discrimination (area under ROC curve or c-index). The experiment presented that both methods have reasonable results in the case of the c-index. However, in some cases the calibration value (χ2) obtained quite a high result. After conducting experiments and investigating the advantages and disadvantages of each method, we can conclude that Decision Trees can be seen as a worthy alternative to Logistic Regression in the area of Data Mining.

Keywords: Decision Trees, Logistic Regression, clinical outcome, risk of mortality.

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Authors: Worachat Wannawong, Usa W. Humphries, Prungchan Wongwises, Suphat Vongvisessomjai, Wiriya Lueangaram

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A numerical analysis of wave and hydrodynamic models is used to investigate the influence of WAve and Storm Surge (WASS) in the regional and coastal zones. The numerical analyzed system consists of the WAve Model Cycle 4 (WAMC4) and the Princeton Ocean Model (POM) which used to solve the energy balance and primitive equations respectively. The results of both models presented the incorporated surface wave in the regional zone affected the coastal storm surge zone. Specifically, the results indicated that the WASS generally under the approximation is not only the peak surge but also the coastal water level drop which can also cause substantial impact on the coastal environment. The wave–induced surface stress affected the storm surge can significantly improve storm surge prediction. Finally, the calibration of wave module according to the minimum error of the significant wave height (Hs) is not necessarily result in the optimum wave module in the WASS analyzed system for the WASS prediction.

Keywords: energy balance equation, numerical analysis, primitiveequation, storm surge, wave.

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Authors: M.O. Makhmalbaf, F. Mohajeri Nav, M. Zabihi Samani

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The recent drive for use of performance-based methodologies in design and assessment of structures in seismic areas has significantly increased the demand for the development of reliable nonlinear inelastic static pushover analysis tools. As a result, the adaptive pushover methods have been developed during the last decade, which unlike their conventional pushover counterparts, feature the ability to account for the effect that higher modes of vibration and progressive stiffness degradation might have on the distribution of seismic storey forces. Even in advanced pushover methods, little attention has been paid to the Unsymmetric structures. This study evaluates the seismic demands for three dimensional Unsymmetric-Plan buildings determined by the Displacement-based Adaptive Pushover (DAP) analysis, which has been introduced by Antoniou and Pinho [2004]. The capability of DAP procedure in capturing the torsional effects due to the irregularities of the structures, is investigated by comparing its estimates to the exact results, obtained from Incremental Dynamic Analysis (IDA). Also the capability of the procedure in prediction the seismic behaviour of the structure is discussed.

Keywords: Nonlinear static procedures, Unsymmetric-PlanBuildings, Torsional effects, IDA.

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Authors: Hamed Rahmani, Wim Groot

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The term "youth not in employment, education or training (NEET)" refers to a combination of youth unemployment and school dropout. This study investigates the variables that increase the risk of becoming NEET in Iran. A selection bias-adjusted Probit model was employed using machine learning to identify these risk factors. We used cross-sectional data obtained from the Statistical Center of Iran and the Ministry of Cooperatives Labor and Social Welfare that are taken from the labor force survey conducted in the spring of 2021. We look at years of education, work experience, housework, the number of children under the age of 6 years in the home, family education, birthplace, and the amount of land owned by households. Results show that hours spent performing domestic chores enhance the likelihood of youth becoming NEET, and years of education, years of potential work experience decrease the chance of being NEET. The findings also show that female youth born in cities were less likely than those born in rural regions to become NEET.

Keywords: NEET youth, probit, CART, machine learning, unemployment.

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Authors: Mohammad Rajabalinejad

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Safety is often seen as a requirement or a performance indicator through the design process, and this does not always result in optimally safe products or systems. This paper suggests integrating the best safety practices with the design process to enrich the exploration experience for designers and add extra values for customers. For this purpose, the commonly practiced safety standards and design methods have been reviewed and their common blocks have been merged forming Safety Cube. Safety Cube combines common blocks for design, hazard identification, risk assessment and risk reduction through an integral approach. An example application presents the use of Safety Cube for design of machinery.

Keywords: Safety, safety cube, design, product, system, machinery.

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Authors: Jawad Makki, Anne-Marie Alquier, Violaine Prince

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In this paper we propose an NLP-based method for Ontology Population from texts and apply it to semi automatic instantiate a Generic Knowledge Base (Generic Domain Ontology) in the risk management domain. The approach is semi-automatic and uses a domain expert intervention for validation. The proposed approach relies on a set of Instances Recognition Rules based on syntactic structures, and on the predicative power of verbs in the instantiation process. It is not domain dependent since it heavily relies on linguistic knowledge. A description of an experiment performed on a part of the ontology of the PRIMA1 project (supported by the European community) is given. A first validation of the method is done by populating this ontology with Chemical Fact Sheets from Environmental Protection Agency2. The results of this experiment complete the paper and support the hypothesis that relying on the predicative power of verbs in the instantiation process improves the performance.

Keywords: Information Extraction, Instance Recognition Rules, Ontology Population, Risk Management, Semantic analysis.

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Authors: Li Li, Kai-Hsuan Chu

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It is well known that the real estate price depends on a lot of factors. Each house current value is dependent on the location, room number, transportation, living convenience, year and surrounding environments. Although, there are different experienced models for housing agent to estimate the price, it is a case by case study without overall dynamic variation investigation. However, many economic parameters may more or less influence the real estate price variation. Here, the influences of most macroeconomic parameters on real estate price are investigated individually based on least-square scheme and grey correlation strategy. Then those parameters are classified into leading indices, simultaneous indices and laggard indices. In addition, the leading time period is evaluated based on least square method. The important leading and simultaneous indices can be used to establish an artificial intelligent neural network model for real estate price variation prediction. The real estate price variation of Taipei, Taiwan during 2005 ~ 2017 are chosen for this research data analysis and validation. The results show that the proposed method has reasonable prediction function for real estate business reference.

Keywords: Real estate price, least-square, grey correlation, macroeconomics.

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Authors: Y. Cifuentes, L. Beltrán, L. Ramírez

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The availability to deploy mobile applications for health care is increasing daily thru different mobile app stores. But within these capabilities the number of hacking attacks has also increased, in particular into medical mobile applications. The security vulnerabilities in medical mobile apps can be triggered by errors in code, incorrect logic, poor design, among other parameters. This is usually used by malicious attackers to steal or modify the users’ information. The aim of this research is to analyze the vulnerabilities detected in mobile medical apps according to risk factor standards defined by OWASP in 2014.

Keywords: mHealth apps, OWASP, protocols, security vulnerabilities, risk factors.

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Authors: Y. Mohammadi, H. M. Ghasemzadeh, T. B. Talari, M. A. Ghorbani

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Concrete pavement has superior durability and longer structural life than asphalt pavement. Concrete pavement requires less maintenance compared to asphalt pavement which requires maintenance and major rehabilitation. Use of the concrete pavement has been grown over the past decade in developing countries. Fibre reinforced concrete (FRC) has been successfully used in design of concrete pavement in past decade. In this research, the effect of fibre volume fraction in modulus of rupture, load-deflection, equivalent flexural strength (fe,3) and the equivalent flexural strength ratio (Re,3) has been used in different fibre volume fraction. Crimped-type flat steel fibre of size 50 x 2.0 x 0.6 mm was used with 1.0%, 1.5% and 2.0% volume fraction. Beam specimens of size 500 x 100 x 100 mm were used for flexural as well as with JCI method for analysis flexural toughness, equivalent flexural strength. It was obtained as the 2% fibre volume fractions; reduce 45% of the concrete pavement thickness.

Keywords: Concrete pavement, Equivalent flexural strength, Fibre, Load-deflection curves.

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Authors: Sharan Badiger, Prema T. Akkasaligar, Patil LS, Manish Patel, Biradar MS

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Human immunodeficiency virus infection and acquired immunodeficiency syndrome is a global pandemic with cases reporting from virtually every country and continues to be a common infection in developing country like India. Microalbuminuria is a manifestation of human immunodeficiency virus associated nephropathy. Therefore, microalbuminuria may be an early marker of human immunodeficiency virus associated nephropathy, and screening for its presence may be beneficial. A strikingly high prevalence of microalbuminuria among human immunodeficiency virus infected patients has been described in various studies. Risk factors for clinically significant proteinuria include African - American race, higher human immunodeficiency virus ribonucleic acid level and lower CD4 lymphocyte count. The cardiovascular risk factors of increased systolic blood pressure and increase fasting blood sugar level are strongly associated with microalbuminuria in human immunodeficiency virus patient. These results suggest that microalbuminuria may be a sign of current endothelial dysfunction and micro-vascular disease and there is substantial risk of future cardiovascular disease events. Positive contributing factors include early kidney disease such as human immunodeficiency virus associated nephropathy, a marker of end organ damage related to co morbidities of diabetes or hypertension, or more diffuse endothelial cells dysfunction. Nevertheless after adjustment for non human immunodeficiency virus factors, human immunodeficiency virus itself is a major risk factor. The presence of human immunodeficiency virus infection is independent risk to develop microalbuminuria in human immunodeficiency virus patient. Cardiovascular risk factors appeared to be stronger predictors of microalbuminuria than markers of human immunodeficiency virus severity person with human immunodeficiency virus infection and microalbuminuria therefore appear to potentially bear the burden of two separate damage related to known vascular end organ damage related to know vascular risk factors, and human immunodeficiency virus specific processes such as the direct viral infection of kidney cells.The higher prevalence of microalbuminuria among the human immunodeficiency virus infected could be harbinger of future increased risks of both kidney and cardiovascular disease. Further study defining the prognostic significance of microalbuminuria among human immunodeficiency virus infected persons will be essential. Microalbuminuria seems to be a predictor of cardiovascular disease in diabetic and non diabetic subjects, hence it can also be used for early detection of micro vascular disease in human immunodeficiency virus positive patients, thus can help to diagnose the disease at the earliest.

Keywords: Acquired immunodeficiency syndrome, Human immunodeficiency virus, Microalbuminuria.

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Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi

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In this paper, we want to determine whether the accurate prediction of nicotine concentration can be obtained by using a network of smart objects and an e-cigarette. The approach consists of, first, the recognition of factors influencing smoking cessation such as physical activity recognition and participant’s behaviors (using both smartphone and smartwatch), then the prediction of the configuration of the e-cigarette (in terms of nicotine concentration, power, and resistance of e-cigarette). The study uses a network of commonly connected objects; a smartwatch, a smartphone, and an e-cigarette transported by the participants during an uncontrolled experiment. The data obtained from sensors carried in the three devices were trained by a Long short-term memory algorithm (LSTM). Results show that our LSTM-based model allows predicting the configuration of the e-cigarette in terms of nicotine concentration, power, and resistance with a root mean square error percentage of 12.9%, 9.15%, and 11.84%, respectively. This study can help to better control consumption of nicotine and offer an intelligent configuration of the e-cigarette to users.

Keywords: Iot, activity recognition, automatic classification, unconstrained environment, deep neural networks.

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Authors: S. N. A. Azraai, K. S. Lim, N. Yahaya, N. M. Noor

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This experimental study consists of a characterization of epoxy grout where an amount of 2% of graphene nanoplatelets particles were added to commercial epoxy resin to evaluate their behavior regarding neat epoxy resin. Compressive tests, tensile tests and flexural tests were conducted to study the effect of graphene nanoplatelets on neat epoxy resin. By comparing graphene-based and neat epoxy grout, there is no significant increase of strength due to weak interface in the graphene nanoplatelets/epoxy composites. From this experiment, the tension and flexural strength of graphenebased epoxy grouts is slightly lower than ones of neat epoxy grout. Nevertheless, the addition of graphene has produced more consistent results according to a smaller standard deviation of strength. Furthermore, the graphene has also improved the ductility of the grout, hence reducing its brittle behaviour. This shows that the performance of graphene-based grout is reliably predictable and able to minimise sudden rupture. This is important since repair design of damaged pipeline is of deterministic nature.

Keywords: Composite, epoxy resin, graphene nanoplatelets.

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Authors: Mikhail V. Khachaturyan

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The article analyzes problems of improving the management systems of the ownership risks in the conditions of the transformation of the Russian economy. Among the main sources of threats business owners should highlight is the inefficiency of the implementation of business models and interaction with hired managers. In this context, it is particularly important to analyze the relationship of business models and ownership risks. The analysis of this problem appears to be relevant for a number of reasons: Firstly, the increased risk appetite of the owner directly affects the business model and the composition of his holdings; secondly, owners with significant stakes in the company are factors in the formation of particular types of risks for owners, for which relations have a significant influence on a firm's competitiveness and ultimately determines its survival; and thirdly, inefficient system of management ownership of risk is one of the main causes of mass bankruptcies, which significantly affects the stable operation of the economy as a whole. The separation of the processes of possession, disposal and use in modern organizations is the cause of not only problems in the process of interaction between the owner and managers in managing the organization as a whole, but also the asymmetric information about the kinds and forms of the main risks. Managers tend to avoid risky projects, inhibit the diversification of the organization's assets, while owners can insist on the development of such projects, with the aim not only of creating new values for themselves and consumers, but also increasing the value of the company as a result of increasing capital. In terms of separating ownership and management, evaluation of projects by the ratio of risk-yield requires preservation of the influence of the owner on the process of development and making management decisions. It is obvious that without a clearly structured system of participation of the owner in managing the risks of their business, further development is hopeless. In modern conditions of forming a risk management system, owners are compelled to compromise between the desire to increase the organization's ability to produce new value, and, consequently, increase its cost due to the implementation of risky projects and the need to tolerate the cost of lost opportunities of risk diversification. Improving the effectiveness of the management of ownership risks may also contribute to the revitalization of creditors on implementation claims to inefficient owners, which ultimately will contribute to the efficiency models of ownership control to exclude variants of insolvency. It is obvious that in modern conditions, the success of the model of the ownership of risk management and audit is largely determined by the ability and willingness of the owner to find a compromise between potential opportunities for expanding the firm's ability to create new value through risk and maintaining the current level of new value creation and an acceptable level of risk through the use of models of diversification.

Keywords: Risk management, ownership risks, economic transformation, Russian economy, management systems.

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Authors: J. Y. Jang, Y. W. Lee, C. N. Lin, C. H. Wang

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The reheating furnace is used to reheat the steel slabs before the hot-rolling process. The supported system includes the stationary/moving beams, and the skid buttons which block some thermal radiation transmitted to the bottom of the slabs. Therefore, it is important to analyze the steel slab temperature distribution during the heating period. A three-dimensional mathematical transient heat transfer model for the prediction of temperature distribution within the slab has been developed. The effects of different skid button height (H=60mm, 90mm, and 120mm) and different gap distance between two slabs (S=50mm, 75mm, and 100mm) on the slab skid mark formation and temperature profiles are investigated. Comparison with the in-situ experimental data from Steel Company in Taiwan shows that the present heat transfer model works well for the prediction of thermal behavior of the slab in the reheating furnace. It is found that the skid mark severity decreases with an increase in the skid button height. The effect of gap distance is important only for the slab edge planes, while it is insignificant for the slab central planes.

Keywords: 3-D, slab, transient heat conduction, reheating furnace, thermal radiation.

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Authors: B. Prashantha, S. Anish

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The aim of the present study is to computationally evaluate the hemodynamic factors which affect the formation of atherosclerosis and plaque rupture in the human artery. An increase of atherosclerosis disease in the artery causes geometry changes, which results in hemodynamic changes such as flow separation, reattachment, and adhesion of new cells (chemotactic) in the artery. Hence, geometry plays an important role in the determining the nature of hemodynamic patterns. Influence of stenosis in the non-bifurcating artery, under pulsatile flow condition, has been studied on an idealized geometry. Analysis of flow through symmetric and asymmetric stenosis in the artery revealed the significance of oscillating shear index (OSI), flow separation, low WSS zones and secondary flow patterns on plaque formation. The observed characteristic of flow in the post-stenotic region highlight the importance of plaque eccentricity on the formation of secondary stenosis on the arterial wall.

Keywords: Atherosclerotic plaque, Oscillatory Shear Index, Stenosis nature, Wall Shear Stress.

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Authors: Chau-Kuang Chen, John Hughes, Jr., A. Dexter Samuels

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The prediction models for the United States Medical Licensure Examination (USMLE) Steps 1 and 2 performances were constructed by the Monte Carlo simulation modeling approach via linear regression. The purpose of this study was to build robust simulation models to accurately identify the most important predictors and yield the valid range estimations of the Steps 1 and 2 scores. The application of simulation modeling approach was deemed an effective way in predicting student performances on licensure examinations. Also, sensitivity analysis (a/k/a what-if analysis) in the simulation models was used to predict the magnitudes of Steps 1 and 2 affected by changes in the National Board of Medical Examiners (NBME) Basic Science Subject Board scores. In addition, the study results indicated that the Medical College Admission Test (MCAT) Verbal Reasoning score and Step 1 score were significant predictors of the Step 2 performance. Hence, institutions could screen qualified student applicants for interviews and document the effectiveness of basic science education program based on the simulation results.

Keywords: Prediction Model, Sensitivity Analysis, Simulation Method, USMLE.

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Authors: Hong Son Hoang, Remy Baraille

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This paper addresses the problem of how one can improve the performance of a non-optimal filter. First the theoretical question on dynamical representation for a given time correlated random process is studied. It will be demonstrated that for a wide class of random processes, having a canonical form, there exists a dynamical system equivalent in the sense that its output has the same covariance function. It is shown that the dynamical approach is more effective for simulating and estimating a Markov and non- Markovian random processes, computationally is less demanding, especially with increasing of the dimension of simulated processes. Numerical examples and estimation problems in low dimensional systems are given to illustrate the advantages of the approach. A very useful application of the proposed approach is shown for the problem of state estimation in very high dimensional systems. Here a modified filter for data assimilation in an oceanic numerical model is presented which is proved to be very efficient due to introducing a simple Markovian structure for the output prediction error process and adaptive tuning some parameters of the Markov equation.

Keywords: Statistical simulation, canonical form, dynamical system, Markov and non-Markovian processes, data assimilation.

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Authors: M. Allagoa, A. Al-Tabbaa

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The study explores the use of binders and additives, such as Portland cement, pulverized fuel ash, ground granulated blast furnace slag, and MgO, to reduce the concentration and leachability of pollutants in contaminated site soils. The research investigates their effectiveness and associated risks of binders, with a focus on Total Heavy Metals (THM) and Total Petroleum Hydrocarbon (TPH). The goal of this research is to evaluate the performance and effectiveness of binders and additives in remediating soil pollutants. The study aims to assess the suitability of the mixtures for ground improvement purposes, determine the optimal dosage, and investigate the associated risks. The research utilizes physical (unconfined compressive strength) and chemical tests (batch leachability test) to assess the efficacy of the binders and additives. A completely randomized design one-way ANOVA is used to determine the significance within mix binders of THM. The study also employs incremental lifetime cancer risk (ILCR) assessments and other indices to evaluate the associated risks. The study finds that Ground Granulated Blast Furnace Slag (GGBS): MgO is the most effective binder for remediation, particularly when using low dosages of MgO combined with higher dosages of GGBS binders on TPH. The results indicate that binders and additives can encapsulate and immobilize pollutants, thereby reducing their leachability and toxicity. The mean unconfined compressive strength of the soil ranges from 285.0-320.5 kPa, while THM levels with a combination of Ground granulated blast furnace slag and Magnesium oxide, Portland cement and Pulverised fuel ash were less than 10 µg/l. Portland cement was below 1 µg/l. The ILCR ranged from 6.77E-02 - 2.65E-01 and 5.444E-01 - 3.20 E+00, with the highest values observed under extreme conditions. The hazard index (HI), risk allowable daily dose intake (ADI), and risk chronic daily intake (CDI) were all less than 1 for the THM. The study identifies MgO as the best additive for use in soil remediation.

Keywords: Risk daily dose intake, risk chronic daily intake, incremental lifetime cancer risk, ILCR, novel binders, additives binders, hazard index.

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Authors: Kevin Fong-Rey Liu, Ken Yeh, Cheng-Wu Chen, Han-Hsi Liang

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Environmental aspects plays a central role in environmental management system (EMS) because it is the basis for the identification of an organization-s environmental targets. The existing methods for the assessment of environmental aspects are grouped into three categories: risk assessment-based (RA-based), LCA-based and criterion-based methods. To combine the benefits of these three categories of research, this study proposes an integrated framework, combining RA-, LCA- and criterion-based methods. The integrated framework incorporates LCA techniques for the identification of the causal linkage for aspect, pathway, receptor and impact, uses fuzzy logic to assess aspects, considers fuzzy conditions, in likelihood assessment, and employs a new multi-criteria decision analysis method - multi-criteria and multi-connection comprehensive assessment (MMCA) - to estimate significant aspects in EMS. The proposed model is verified, using a real case study and the results show that this method successfully prioritizes the environmental aspects.

Keywords: Environmental management system, environmental aspect, risk assessment, life cycle assessment.

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Authors: Siham G. Farag

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The main objective of this paper is to provide a new methodology for road safety assessment in Oman through the development of suitable accident prediction models. GLM technique with Poisson or NBR using SAS package was carried out to develop these models. The paper utilized the accidents data of 31 un-signalized T-intersections during three years. Five goodness-of-fit measures were used to assess the overall quality of the developed models. Two types of models were developed separately; the flow-based models including only traffic exposure functions, and the full models containing both exposure functions and other significant geometry and traffic variables. The results show that, traffic exposure functions produced much better fit to the accident data. The most effective geometric variables were major-road mean speed, minor-road 85th percentile speed, major-road lane width, distance to the nearest junction, and right-turn curb radius. The developed models can be used for intersection treatment or upgrading and specify the appropriate design parameters of T-intersections. Finally, the models presented in this thesis reflect the intersection conditions in Oman and could represent the typical conditions in several countries in the middle east area, especially gulf countries.

Keywords: Accidents Prediction Models (APMs), Generalized Linear Model (GLM), T-intersections, Oman.

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Authors: Jaimin Patel

Abstract:

Cloud computing is one of the most sharp and important movement in various computing technologies. It provides flexibility to users, cost effectiveness, location independence, easy maintenance, enables multitenancy, drastic performance improvements, and increased productivity. On the other hand, there are also major issues like security. Being a common server, security for a cloud is a major issue; it is important to provide security to protect user’s private data, and it is especially important in e-commerce and social networks. In this paper, encryption algorithms such as Advanced Encryption Standard algorithms, their vulnerabilities, risk of attacks, optimal time and complexity management and comparison with other algorithms based on software implementation is proposed. Encryption techniques to improve the performance of AES algorithms and to reduce risk management are given. Secure Hash Algorithms, their vulnerabilities, software implementations, risk of attacks and comparison with other hashing algorithms as well as the advantages and disadvantages between hashing techniques and encryption are given.

Keywords: Cloud computing, encryption algorithm, secure hashing algorithm, brute force attack, birthday attack, plaintext attack, man-in-the-middle attack.

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Authors: Andreia Guimarães Farnese, Mateus Fernandes Réu Urban, Leandro Procópio, Renato Zângaro, Regiane Albertini

Abstract:

Senescence changes include postural balance, inferring the risk of falls, and can lead to fractures, bedridden, and the risk of death. Physical activity, e.g., cardiovascular exercises, is notable for improving balance due to brain cell stimulations, but fine coordination exercises also elevate cell brain metabolism. This study aimed to verify whether the elderly person who performs fine motor activity has a balance similar to that of those who practice physical activity. The subjects were divided into three groups according to the activity practice: control group (CG) with seven participants for the sedentary individuals, motor coordination group (MCG) with six participants, and physical activity group (PAG) with eight participants. Data comparisons were from the Berg balance scale, Time up and Go test, and stabilometric analysis. Descriptive statistical and ANOVA analyses were performed for data analysis. The results reveal that including fine motor activities can improve the balance of the elderly and indirectly decrease the risk of falls.

Keywords: Balance, barapodometer, coordination, elderly.

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Authors: Prof. Chokri SLIM

Abstract:

A Novel fuzzy neural network combining with support vector learning mechanism called support-vector-based fuzzy neural networks (SVBFNN) is proposed. The SVBFNN combine the capability of minimizing the empirical risk (training error) and expected risk (testing error) of support vector learning in high dimensional data spaces and the efficient human-like reasoning of FNN.

Keywords: Neural network, fuzzy inference, machine learning, fuzzy modeling and rule extraction, support vector regression.

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Authors: V. Agrawal, A. Sharma

Abstract:

High Strength Concrete (HSC) is defined as concrete that meets special combination of performance and uniformity requirements that cannot be achieved routinely using conventional constituents and normal mixing, placing, and curing procedures. It is a highly complex material, which makes modeling its behavior a very difficult task. This paper aimed to show possible applicability of Neural Networks (NN) to predict the slump in High Strength Concrete (HSC). Neural Network models is constructed, trained and tested using the available test data of 349 different concrete mix designs of High Strength Concrete (HSC) gathered from a particular Ready Mix Concrete (RMC) batching plant. The most versatile Neural Network model is selected to predict the slump in concrete. The data used in the Neural Network models are arranged in a format of eight input parameters that cover the Cement, Fly Ash, Sand, Coarse Aggregate (10 mm), Coarse Aggregate (20 mm), Water, Super-Plasticizer and Water/Binder ratio. Furthermore, to test the accuracy for predicting slump in concrete, the final selected model is further used to test the data of 40 different concrete mix designs of High Strength Concrete (HSC) taken from the other batching plant. The results are compared on the basis of error function (or performance function).

Keywords: Artificial Neural Networks, Concrete, prediction ofslump, slump in concrete

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Authors: M. Izzat Md. Nor, N. Jaffar, N. Zaitulakma Md. Zain, N. Izyanti Mohd Suppian, S. Balakrishnan, G. Kandavello

Abstract:

During the Coronavirus (COVID-19) pandemic, Malaysia has been focusing on building herd immunity by introducing vaccination programs into the community. Hospital Standard Operating Procedures (SOP) were developed to prevent inpatient transmission. In this study, we focus on the positivity rate of inpatient Person Under Surveillance (PUS) becoming COVID-19 positive and compare this to the national rate in order to see the outcomes of the patient who becomes COVID-19 positive in relation to their vaccination status. This is a retrospective observational study carried out from 1 January until 30 March 2022 in Institut Jantung Negara (IJN). There were 5,255 patients admitted during the time of this study. Pre-admission Polymerase Chain Reaction (PCR) swab was done for all patients. Patients with positive PCR on pre-admission screening were excluded. The patients who had exposure to COVID-19-positive staff or patients during hospitalization were defined as PUS and were quarantined and monitored for potential COVID-19 infection. Their frequency and risk of exposure (WHO definition) were recorded. On the final day of quarantine, a second PCR swab was performed on PUS patients who exhibit clinical deterioration, whether or not they exhibit COVID-19 symptoms. The severity of COVID-19 infection was defined as category 1-5A. All patients' vaccination status was recorded, and they were divided into three groups: fully immunised, partially immunised, and unvaccinated. We analysed the positivity rate of PUS patients becoming COVID-positive, outcomes, and correlation with the vaccination status. The ratio of positive inpatient PUS to the total inpatient PUS is 492; only 13 became positive, giving a positivity rate of 2.6%. Eight (62%) had multiple exposures. The majority, 8/13(72.7%), had a high-risk exposure, and the remaining 5 had medium-risk exposure. Four (30.8%) were boosted, 7(53.8%) were fully vaccinated, and 2(15.4%) were partial/unvaccinated. Eight patients were in categories 1-2, whilst 38% were in categories 3-5. Vaccination status did not correlate with COVID-19 Category (P = 0.641). One (7.7%) patient died due to COVID-19 complications and sepsis. Within the first quarter of 2022, our institution's positivity rate (2.6%) is significantly lower than the country's (14.4%). High-risk exposure and multiple exposures to positive COVID-19 cases increased the risk of PUS becoming COVID-19 positive despite their underlying vaccination status.

Keywords: COVID-19, boosted, high risk, Malaysia, quarantine, vaccination status.

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