Search results for: discrete-time queueing inventory model

Authors: Shank Kulkarni, Alireza Tabarraei

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The fantastic properties of polyurea such as flexibility, durability, and chemical resistance have brought it a wide range of application in various industries. Effective prediction of the response of polyurea under different loading and environmental conditions necessitates the development of an accurate constitutive model. Similar to most polymers, the behavior of polyurea depends on both strain and strain rate. Therefore, the constitutive model should be able to capture both these effects on the response of polyurea. To achieve this objective, in this paper, a nonlinear hyper-viscoelastic constitutive model is developed by the superposition of a hyperelastic and a viscoelastic model. The proposed constitutive model can capture the behavior of polyurea under compressive loading conditions at various strain rates. Four parameter Ogden model and Mooney Rivlin model are used to modeling the hyperelastic behavior of polyurea. The viscoelastic behavior is modeled using both a three-parameter standard linear solid (SLS) model and a K-BKZ model. Comparison of the modeling results with experiments shows that Odgen and SLS model can more accurately predict the behavior of polyurea. The material parameters of the model are found by curve fitting of the proposed model to the uniaxial compression test data. The proposed model can closely reproduce the stress-strain behavior of polyurea for strain rates up to 6500 /s.

Keywords: constitutive modelling, ogden model, polyurea, SLS model, uniaxial compression test

Procedia PDF Downloads 245

Authors: Maffo Maffo Nicole Liliane, Mounmeni Kpoumie Hubert, Mbaire Matindje Karl Marx, Zapfack Louis

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Sacred forests play a valuable role in conserving local biodiversity and provide numerous ecosystem services in Cameroon. The study was carried out in the sacred forests of Bandrefam and Batoufam (western Cameroon). The aim was to estimate the diversity of woody species, carbon stocks and degradation factors in these sacred forests. The floristic inventory was carried out in plots measuring 25m × 25m for trees with diameters greater than 10 cm and 5m × 5m for trees with diameters less than 10 cm. Carbon stocks were estimated using the non-destructive method and the allometric equations. Data on degradation factors were collected using semi-structured surveys in the Bandrefam and Batoufam neighborhoods. The floristic inventory identified 65 species divided into 57 genera and 30 families in the Bandrefam Sacred Forest and 45 species divided into 42 genera and 27 families in the Batoufam Sacres Forest. The families common to both sacred forests are as follows: Phyllanthaceae, Fabaceae, Moraceae, Lamiaceae, Malvaceae, Rubiaceae, Meliaceae, Anacardiaceae, and Sapindaceae. Three genera are present in both sites. These are: Albizia, Macaranga, Trichillia. In addition, there are 27 species in common between the two sites. The total carbon stock is 469.26 tC/ha at Batoufam and 291.41 tC/ha at Bandrefam. The economic value varies between 15 823 877.05 fcfa at Batoufam and 9 825 530.528 fcfa at Bandrefam. The study shows that despite the sacred nature of these forests, they are subject to degradation factors such as bushfires (35.42 %), the creation of plantations (23.96 %), illegal timber exploitation (21.88 %), young people's lack of interest in the notion of conservation (9.38 %), climate change (7.29 %) and growing urbanization (2.08 %). These factors threaten biodiversity and reduce carbon storage in these forests.

Keywords: sacred forests, degradation factors, carbon stocks, semi-structured surveys

Procedia PDF Downloads 49

Authors: Hussein Altartouri

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In this paper the kinematic and kinetic models of an omnidirectional holonomic mobile robot is presented. The kinematic and kinetic models form the OmniDrive model. Therefore, a mathematical model for the robot equipped with three- omnidirectional wheels is derived. This model which takes into consideration the kinematics and kinetics of the robot, is developed to state space representation. Relative analysis of the velocities and displacements is used for the kinematics of the robot. Lagrange’s approach is considered in this study for deriving the equation of motion. The drive train and the mechanical assembly only of the Festo Robotino® is considered in this model. Mainly the model is developed for motion control. Furthermore, the model can be used for simulation purposes in different virtual environments not only Robotino® View. Further use of the model is in the mechatronics research fields with the aim of teaching and learning the advanced control theories.

Keywords: mobile robot, omni-direction wheel, mathematical model, holonomic mobile robot

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Authors: Arkadiusz Zurek

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The potential of using drones is visible in many areas of logistics, especially in terms of their use for monitoring and control of many processes. The technologies implemented in the last decade concern new possibilities for companies that until now have not even considered them, such as warehouse inventories. Unmanned aerial vehicles are no longer seen as a revolutionary tool for Industry 4.0, but rather as tools in the daily work of factories and logistics operators. The research problem is to develop a method for measuring the weight of goods in a selected link of the clothing supply chain by drones. However, the purpose of this article is to analyze the causes of errors in traditional measurements, and then to identify adverse events related to the use of drones for the inventory of a heap of textiles intended for production purposes. On this basis, it will be possible to develop guidelines to eliminate the causes of these events in the measurement process using drones. In a real environment, work was carried out to determine the volume and weight of textiles, including, among others, weighing a textile sample to determine the average density of the assortment, establishing a local geodetic network, terrestrial laser scanning and photogrammetric raid using an unmanned aerial vehicle. As a result of the analysis of measurement data obtained in the facility, the volume and weight of the assortment and the accuracy of their determination were determined. In this article, this work presents how such heaps are currently being tested, what adverse events occur, indicate and describes the current use of photogrammetric techniques of this type of measurements so far performed by external drones for the inventory of wind farms or construction of the station and compare them with the measurement system of the aforementioned textile heap inside a large-format facility.

Keywords: drones, unmanned aerial system, UAS, indoor system, security, process automation, cost optimization, photogrammetry, risk elimination, industry 4.0

Procedia PDF Downloads 87

Authors: T. N. Mac, B. Shahbodaghkhan, N. Khalili

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A new elastic-viscoplastic (EVP) constitutive model is proposed for the analysis of time-dependent behavior of clay. The proposed model is based on the bounding surface plasticity and the concept of viscoplastic consistency framework to establish continuous transition from plasticity to rate dependent viscoplasticity. Unlike the overstress based models, this model will meet the consistency condition in formulating the constitutive equation for EVP model. The procedure of deriving the constitutive relationship is also presented. Simulation results and comparisons with experimental data are then presented to demonstrate the performance of the model.

Keywords: bounding surface, consistency theory, constitutive model, viscosity

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Authors: T. Arshad

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A correlation study was done to explore the relationship of intrusiveness, appraisal and thought control strategies in patients with Obsessive Compulsive Disorder. Theoretical frame work for the present study was Salkovskis (1985) cognitive model of obsessive compulsive disorder. Sample of 100 patients (men=48, women=52) of age 14-62 years (M=32.13, SD=10.37) was recruited from hospitals of Lahore, Pakistan. Revised Obsessional Intrusion Inventory, Stress Appraisal Measure, Thought Control Questionnaire and Symptoms Checklist-R were self-administered. Findings revealed that intrusiveness is correlated with appraisals (controllable by self, controllable by others, uncontrollable, stressfulness) and thought control strategy (punishment). Furthermore, appraisals (uncontrollable, stressfulness, controllable by others) were emerged as strong predictors for different through control strategies (distraction, punishment and social control). Moreover, men have higher frequency of intrusion, whereas women were frequently using social control as thought control strategy. Results implied that intrusiveness, appraisals (controllable by others, uncontrollable, stressfulness) and thought control strategy (punishment) are related which maintains the disorder.

Keywords: appraisal, intrusiveness, obsessive compulsive disorder, thought control strategies

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Authors: Fatmah Almathkour

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Managing and controlling the construction supply chain (CSC) are very important components of effective construction project execution. The goals of managing the CSC are to reduce uncertainty and optimize the performance of a construction project by improving efficiency and reducing project costs. The heart of much SC activity is addressing risk, and the CSC is no different. The delivery and consumption of construction materials is highly variable due to the complexity of construction operations, rapidly changing demand for certain components, lead time variability from suppliers, transportation time variability, and disruptions at the job site. Current notions of managing and controlling CSC, involve focusing on one project at a time with a push-based material ordering system based on the initial construction schedule and, then, holding a tremendous amount of inventory. A two-stage methodology was proposed to coordinate the feed-forward control of advanced order placement with a supplier to a feedback local control in the form of adding the ability to transship materials between projects to improve efficiency and reduce costs. It focused on the single supplier integrated production and transshipment problem with multiple products. The methodology is used as a design tool for the CSC because it includes an external storage site not associated with one of the projects. The idea is to add this feature to a highly constrained environment to explore its effectiveness in buffering the impact of variability and maintaining project schedule at low cost. The methodology uses deterministic optimization models with objectives that minimizing the total cost of the CSC. To illustrate how this methodology can be used in practice and the types of information that can be gleaned, it is tested on a number of cases based on the real example of multiple construction projects in Kuwait.

Keywords: construction supply chain, inventory control supply chain, transshipment

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Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

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Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies

Keywords: crop yield, roughness coefficient, PAR, WRM model

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Authors: Anna Avramenko, Heikki Haario

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This paper reports the development and application of a 2D depth-averaged model. The main goal of this contribution is to apply the depth averaged equations to a wind park model in which the treatment of the geometry, introduced on the mathematical model by the mass and momentum source terms. The depth-averaged model will be used in future to find the optimal position of wind turbines in the wind park. K-E and 2D LES turbulence models were consider in this article. 2D CFD simulations for one hill was done to check the depth-averaged model in practise.

Keywords: depth-averaged equations, numerical modeling, CFD, wind park model

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Authors: Jui-Ching Chou

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Numerical simulation is a popular method used to evaluate the effects of soil liquefaction on a structure or the effectiveness of a mitigation plan. Many constitutive models (UBCSAND model, PM4 model, SANISAND model, etc.) were presented to model the liquefaction phenomenon. In general, inputs of a constitutive model need to be calibrated against the soil cyclic resistance before being applied to the numerical simulation model. Then, simulation results can be compared with results from simplified liquefaction potential assessing methods. In this article, inputs of the UBCSAND model, a simple elastic-plastic stress-strain model, are calibrated against several popular generic liquefaction triggering curves of simplified liquefaction potential assessing methods via FLAC program. Calibrated inputs can provide engineers to perform a preliminary evaluation of an existing structure or a new design project.

Keywords: calibration, liquefaction, numerical simulation, UBCSAND Model

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Authors: Katharina Eberhardt, Florian Klaus Kaiser, Frank Schultmann

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Last-mile distribution is one of the most critical parts of a disaster relief operation. Various uncertainties, such as infrastructure conditions, resource availability, and fluctuating beneficiary demand, render last-mile distribution challenging in disaster relief operations. The need to balance critical performance criteria like response time, meeting demand and cost-effectiveness further complicates the task. The occurrence of disasters cannot be controlled, and the magnitude is often challenging to assess. In summary, these uncertainties create a need for additional flexibility, agility, and preparedness in logistics operations. As a result, strategic planning and efficient network design are critical for an effective and efficient response. Furthermore, the increasing frequency of disasters and the rising cost of logistical operations amplify the need to provide robust and resilient solutions in this area. Therefore, we formulate a scenario-based bi-objective optimization model that integrates pre-positioning, allocation, and distribution of relief supplies extending the general form of a covering location problem. The proposed model aims to minimize underlying logistics costs while maximizing demand coverage. Using a set of disruption scenarios, the model allows decision-makers to identify optimal network solutions to address the risk of disruptions. We provide an empirical case study of the public authorities’ emergency food storage strategy in Germany to illustrate the potential applicability of the model and provide implications for decision-makers in a real-world setting. Also, we conduct a sensitivity analysis focusing on the impact of varying stockpile capacities, single-site outages, and limited transportation capacities on the objective value. The results show that the stockpiling strategy needs to be consistent with the optimal number of depots and inventory based on minimizing costs and maximizing demand satisfaction. The strategy has the potential for optimization, as network coverage is insufficient and relies on very high transportation and personnel capacity levels. As such, the model provides decision support for public authorities to determine an efficient stockpiling strategy and distribution network and provides recommendations for increased resilience. However, certain factors have yet to be considered in this study and should be addressed in future works, such as additional network constraints and heuristic algorithms.

Keywords: humanitarian logistics, bi-objective optimization, pre-positioning, last mile distribution, decision support, disaster relief networks

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Authors: Charles Chikwendu Okpala, Christopher Chukwutoo Ihueze

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As a technique that reduces variation in a product by lessening the sensitivity of the design to sources of variation, rather than by controlling their sources, Taguchi Robust Design entails the designing of ideal goods, by developing a product that has minimal variance in its characteristics and also meets the desired exact performance. This paper examined the concept of the manufacturing approach and its application to brake pad product of an automotive parts manufacturing company. Although the firm claimed that only defects, excess inventory, and over-production were the few wastes that grossly affect their productivity and profitability, a careful study and analysis of their manufacturing processes with the application of Single Minute Exchange of Dies (SMED) tool showed that the waste of waiting is the fourth waste that bedevils the firm. The selection of the Taguchi L9 orthogonal array which is based on the four parameters and the three levels of variation for each parameter revealed that with a range of 2.17, that waiting is the major waste that the company must reduce in order to continue to be viable. Also, to enhance the company’s throughput and profitability, the wastes of over-production, excess inventory, and defects with ranges of 2.01, 1.46, and 0.82, ranking second, third, and fourth respectively must also be reduced to the barest minimum. After proposing -33.84 as the highest optimum Signal-to-Noise ratio to be maintained for the waste of waiting, the paper advocated for the adoption of all the tools and techniques of Lean Production System (LPS), and Continuous Improvement (CI), and concluded by recommending SMED in order to drastically reduce set up time which leads to unnecessary waiting.

Keywords: lean production system, single minute exchange of dies, signal to noise ratio, Taguchi robust design, waste

Procedia PDF Downloads 127

Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

Abstract:

Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies.

Keywords: runoff, roughness coefficient, PAR, WRM model

Procedia PDF Downloads 378

Authors: Leilani Forby, Farid Pazhoohi, Alan Kingstone

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There is abundant research on the nature and content of mind wandering (MW) in neurotypical (NT) adults, however, there is little to no research in these areas on autistic individuals. The objective of the current study was to uncover any differences between low and high autistic trait individuals in their MW. In particular, we examined their attitudes toward, and the themes and temporal dimensions (past, present, future) of, their MW episodes. For our online study, we recruited 518 students (394 women and 124 men), between the ages of 18 and 51 years (M = 20.93, SD = 3.40) from the undergraduate Human Subject Pool at the University of British Columbia. Participants completed the Short Imaginal Processes Inventory (SIPI), which includes the three subscales Positive-Constructive Daydreaming (SIPI-PC), Guilt and Fear of Failure Daydreaming (SIPI-GFF), and Poor Attentional Control (SIPI-PAC). Participants also completed the Past (IPI-past) and Present (IPI-present) subscales of the Imaginal Processes Inventory (IPI), the Deliberate (MW-D) and Spontaneous (MW-S) Mind Wandering scales, the Short Form Perceived Stress Scale (PSS-4), and the 10-item Autism Quotient (AQ-10). Results showed that overall, participant AQ-10 scores were significantly correlated with MW-S, SIPI-GFF, and PSS-4 scores, such that as the number of autistic traits endorsed by participants increased, so did their reports of spontaneous mind wandering, guilt and fear of failure themed day dreaming, and stress levels. This same pattern held for female participants, however, AQ-10 scores were positively correlated with only PSS-4 scores for males. These results suggest that compared to males with autistic traits, MW in females with autistic traits is more similar to individuals with low autistic traits in terms of content and intentionality. Results are discussed in terms of clinical implications, their limitations, and suggested directions for future research.

Keywords: autism, deliberate, mind wandering, spontaneous, perceived stress

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Authors: Masahiro Ohmura, Koh Kakusho, Takeshi Okadome

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This paper presents a regression model with autocorrelated errors in which the inputs are social moods obtained by analyzing the adjectives in Twitter posts using a document topic model. The regression model predicts Dow Jones Industrial Average (DJIA) more precisely than autoregressive moving-average models.

Keywords: stock market prediction, social moods, regression model, DJIA

Procedia PDF Downloads 549

Authors: Adji Achmad Rinaldo Fernandes

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SEM analysis is a complex multivariate analysis because it involves a number of exogenous and endogenous variables that are interconnected to form a model. The measurement model is divided into two, namely, the reflective model (reflecting) and the formative model (forming). Before carrying out further tests on SEM, there are assumptions that must be met, namely the linearity assumption, to determine the form of the relationship. There are three modeling approaches to path analysis, including parametric, nonparametric and semiparametric approaches. The aim of this research is to develop semiparametric SEM and obtain the best model. The data used in the research is secondary data as the basis for the process of obtaining simulation data. Simulation data was generated with various sample sizes of 100, 300, and 500. In the semiparametric SEM analysis, the form of the relationship studied was determined, namely linear and quadratic and determined one and two knot points with various levels of error variance (EV=0.5; 1; 5). There are three levels of closeness of relationship for the analysis process in the measurement model consisting of low (0.1-0.3), medium (0.4-0.6) and high (0.7-0.9) levels of closeness. The best model lies in the form of the relationship X1Y1 linear, and. In the measurement model, a characteristic of the reflective model is obtained, namely that the higher the closeness of the relationship, the better the model obtained. The originality of this research is the development of semiparametric SEM, which has not been widely studied by researchers.

Keywords: semiparametric SEM, measurement model, structural model, reflective model, formative model

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Authors: Chengfang Wang, Zichao Wu, Jianying Zhou

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At present, much attention is paid to the development of new industrial parks in the era of inventory planning. Generally speaking, there are two types of development models: incremental development models and stock development models. The former relies on key projects to build a value innovation park, and the latter relies on the iterative update of the park to build a value innovation park. Take the Baiyun Western Digital Park as an example, considering the growth model of value units, determine the evaluation target. Based on a GIS platform, comprehensive land-use status, regulatory detailed planning, land use planning, blue-green ecological base, rail transit system, road network system, industrial park distribution, public service facilities, and other factors are used to carry out the land use within the planning multi-factor superimposed comprehensive evaluation, constructing a value unit evaluation system, and delineating value units based on implementation orientation and combining two different development models. The research hopes to provide a reference for the planning and construction of new domestic industrial parks.

Keywords: value units, GIS, multi-factor evaluation, implementation orientation

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Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

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In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: deep learning, indoor quality, metabolism, predictive model

Procedia PDF Downloads 258

Authors: Alan Wan

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In recent years, the body of literature on frequentist model averaging in statistics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the variance consideration. In this paper, we consider a regression model with multiplicative heteroscedasticity and develop a model averaging method that combines maximum likelihood estimators of unknown parameters in both the mean and variance functions of the model. Our weight choice criterion is based on a minimisation of a plug-in estimator of the model average estimator's squared prediction risk. We prove that the new estimator possesses an asymptotic optimality property. Our investigation of finite-sample performance by simulations demonstrates that the new estimator frequently exhibits very favourable properties compared to some existing heteroscedasticity-robust model average estimators. The model averaging method hedges against the selection of very bad models and serves as a remedy to variance function misspecification, which often discourages practitioners from modeling heteroscedasticity altogether. The proposed model average estimator is applied to the analysis of two real data sets.

Keywords: heteroscedasticity-robust, model averaging, multiplicative heteroscedasticity, plug-in, squared prediction risk

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Authors: Myung Hwan Na, Ho- Chun Song, EunHee Hong

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We widely use normal linear mixed-effects model to analysis data in repeated measurement. In case of detecting heteroscedasticity and the non-normality of the population distribution at the same time, normal linear mixed-effects model can give improper result of analysis. To achieve more robust estimation, we use heavy tailed linear mixed-effects model which gives more exact and reliable analysis conclusion than standard normal linear mixed-effects model.

Keywords: reliability, tires, field data, linear mixed-effects model

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Authors: Axelle Bertrand, Tom Bauer, Carole Charbuillet, Martin Bonte, Marie Voyer, Nicolas Perry

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The complexity of Life Cycle Assessment (LCA) can be identified as the ultimate obstacle to massification. Due to these obstacles, the diffusion of eco-design and LCA methods in the manufacturing sectors could be impossible. This article addresses the research question: How to adapt the LCA method to generalize it massively and improve its performance? This paper aims to develop an approach for automating LCA in order to carry out assessments on a massive scale. To answer this, we proceeded in three steps: First, an analysis of the literature to identify existing automation methods. Given the constraints of large-scale manual processing, it was necessary to define a new approach, drawing inspiration from certain methods and combining them with new ideas and improvements. In a second part, our development of automated construction is presented (reconciliation and implementation of data). Finally, the LCA case study of a conduit is presented to demonstrate the feature-based approach offered by the developed tool. A computerized environment supports effective and efficient decision-making related to materials and processes, facilitating the process of data mapping and hence product modeling. This method is also able to complete the LCA process on its own within minutes. Thus, the calculations and the LCA report are automatically generated. The tool developed has shown that automation by code is a viable solution to meet LCA's massification objectives. It has major advantages over the traditional LCA method and overcomes the complexity of LCA. Indeed, the case study demonstrated the time savings associated with this methodology and, therefore, the opportunity to increase the number of LCA reports generated and, therefore, to meet regulatory requirements. Moreover, this approach also presents the potential of the proposed method for a wide range of applications.

Keywords: automation, EEE, life cycle assessment, life cycle inventory, massively

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Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

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The e-government emerging concept transforms the way in which the citizens are dealing with their governments. Thus, the citizens can execute the intended services online anytime and anywhere. This results in great benefits for both the governments (reduces the number of officers) and the citizens (more flexibility and time saving). Therefore, building a maturity model to assess the e-government portals becomes desired to help in the improvement process of such portals. This paper aims at proposing an e-government maturity model based on the measurement of the best practices’ presence. The main benefit of such maturity model is to provide a way to rank an e-government portal based on the used best practices, and also giving a set of recommendations to go to the higher stage in the maturity model.

Keywords: best practices, e-government portal, maturity model, quality model

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Authors: Ibrahim Abdullahi Mohammad

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A library catalogue exists not only as an inventory of the collections of the particular library, but also as a retrieval device. It is provided to assist the library user in finding whatever information or information resources they may be looking for. The paper proposes that this location objective of the library catalogue can only be fulfilled, if the library catalogue is constructed, bearing in mind the information needs and searching behavior of the library user. Comparing AACR2 and RDA viz-a-viz the changes RDA has introduced into bibliographic standards, the paper tries to establish the level of viability of RDA in relation to AACR2.

Keywords: library catalogue, information retrieval, AACR2, RDA

Procedia PDF Downloads 55

Authors: Nidesh Sapkota, Garima Pudasaini, Dikshya Agrawal, Binav Baral, Umesh Bhagat, Dharanidhar Baral

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Background: Medical and Dental students are vulnerable to higher levels of Psychological distress than other age matched peers. Many studies reveals that there is high prevalence of psychoactive substance use and Psychiatric co-morbidities among them. Objectives: -To study the prevalence of substance use among medical and dental students of a Medical University. -To study the prevalence of depression and anxiety in medical and dental students of a Medical University. Materials and Method: A cross-sectional descriptive study in which simple random sampling was done. Semi-structured questionnaire, AUDIT for alcohol use, Fagerstrom test for Nicotine dependence, Cannabis screening test (CAST), Beck’s Depression Inventory (BDI), Beck’s Anxiety Inventory (BAI) were used for the assessment. Results: Total sample size was 588 in which the mean age of participants was 22±2years. Among them the prevalence of alcohol users was 47.75%(281) in which 32%(90) were harmful users. Among 19.55%(115) nicotine users 56.5%(65), 37.4%(43), 6.1%(7) had low, low to moderate and moderate dependence respectively. The prevalence of cannabis users was 9%(53) with 45.3%(24), 18.9%(10) having low and high addiction respectively. Depressive symptoms were recorded in 25.3%(149) out of which 12.6%(74), 6.5%(38), 5.3%(31), 0.5%(3), 0.5%(3) had mild, borderline, moderate, severe and extreme depressive symptoms respectively. Similarly anxiety was recorded among 7.8%(46) students with 42 having moderate and 4 having severe anxiety symptoms. Among them 6.3%(37) had suicidal thoughts and 4(0.7%) of them had suicide attempt in last one year. Statistically significant association was noted with harmful alcohol users, Depression and suicidal attempts. Similar association was noted between Depression and suicide with moderate use of nicotine. Conclusion: There is high prevalence of Psychoactive substance use and psychiatric co-morbidities noted in the studies sample. Statistically significant association was noted with Psychiatric co-morbidities and substance use.

Keywords: alcohol, cannabis, dependence, depression, medical students

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Authors: Sara Dalma Galgoczi, Judith Gabriella Kengyel

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Sex scandals are quite an engaging topic to work with, especially with their judgment in society. Most people are interested in other people's lives, specifically in public figures' such as celebrities or politicians, because ordinary people feel like they have the right to know more things about the famous and notorious ones than they would probably willing to share. Intimacy and sexual acts aren't exceptions; moreover, sexuality is one of the central interests of humans ever since. Besides, knowing and having an opinion about any kind of scandal can change even whole social groups or classes estimation of anyone. This study aims to research the social judgment of some Hungarian politicians' sex scandals and asks important questions like diverse public opinions in the light of gender or delegates’ abuse of power. Considering that this study is about collecting and evaluating opinions from the public, and no one before researched and published this exact topic and cases, an online survey was created. In the survey were different sections. We collected data about party-preference, conservativism-liberalism scale; then we used the following questionnaires: from Zero-sum perspective with regard to gender equality (Ruthig, Kehn, Gamblin, Vanderzanden & Jones, 2017), Ambivalent Sexism Inventory (ASI; Glick & Fiske, 1996), Ambivalence Toward Men Inventory (AMI; Glick & Fiske, 1999). Finally, 5 short summaries were presented about five Hungarian politicians' sex scandal cases (3 males, 2 females) from the recent past. These stories were followed by questions about their opinion of the party and attitudes towards the parties' reactions to the cases. We came to the conclusion that people are more permissive with the scandals of men, and benevolent sexism and ambivalence towards men mediate this relation. Men tend to see these cases as part of politicians' private lives more than women. Party preference had a significant effect - people tend to pass a sentence the delegates of the opposing parties, and they rather release the delegates of their preferred party.

Keywords: sex scandal, sexism, social judgement, politician

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Authors: Azimollah Aleshzadeh, Enver Vural Yavuz

Abstract:

The main goal of this study is to produce landslide susceptibility maps using different data-driven bivariate statistical approaches; namely, entropy weight method (EWM), evidence belief function (EBF), and information content model (ICM), at Uzundere county, Erzurum province, in the north-eastern part of Turkey. Past landslide occurrences were identified and mapped from an interpretation of high-resolution satellite images, and earlier reports as well as by carrying out field surveys. In total, 42 landslide incidence polygons were mapped using ArcGIS 10.4.1 software and randomly split into a construction dataset 70 % (30 landslide incidences) for building the EWM, EBF, and ICM models and the remaining 30 % (12 landslides incidences) were used for verification purposes. Twelve layers of landslide-predisposing parameters were prepared, including total surface radiation, maximum relief, soil groups, standard curvature, distance to stream/river sites, distance to the road network, surface roughness, land use pattern, engineering geological rock group, topographical elevation, the orientation of slope, and terrain slope gradient. The relationships between the landslide-predisposing parameters and the landslide inventory map were determined using different statistical models (EWM, EBF, and ICM). The model results were validated with landslide incidences, which were not used during the model construction. In addition, receiver operating characteristic curves were applied, and the area under the curve (AUC) was determined for the different susceptibility maps using the success (construction data) and prediction (verification data) rate curves. The results revealed that the AUC for success rates are 0.7055, 0.7221, and 0.7368, while the prediction rates are 0.6811, 0.6997, and 0.7105 for EWM, EBF, and ICM models, respectively. Consequently, landslide susceptibility maps were classified into five susceptibility classes, including very low, low, moderate, high, and very high. Additionally, the portion of construction and verification landslides incidences in high and very high landslide susceptibility classes in each map was determined. The results showed that the EWM, EBF, and ICM models produced satisfactory accuracy. The obtained landslide susceptibility maps may be useful for future natural hazard mitigation studies and planning purposes for environmental protection.

Keywords: entropy weight method, evidence belief function, information content model, landslide susceptibility mapping

Procedia PDF Downloads 133

Authors: I. C. Tolias, A. G. Venetsanos, N. Markatos

Abstract:

In the present work, CFD simulations of a large scale open deflagration experiment are performed. Stoichiometric hydrogen-air mixture occupies a 20 m hemisphere. Two combustion models are compared and are evaluated against the experiment. The Eddy Dissipation Model and a Multi-physics combustion model which is based on Yakhot’s equation for the turbulent flame speed. The values of models’ critical parameters are investigated. The effect of the turbulence model is also examined. k-ε model and LES approach were tested.

Keywords: CFD, deflagration, hydrogen, combustion model

Procedia PDF Downloads 504

Authors: J. Rhodes, V. Cheng, P. Lok

Abstract:

The aim of this study is to develop a parsimonious model that explains the effect of different stimulus on a tourist’s intention to visit a new destination. The model consists of destination trust and interest as the mediating variables. The model was tested using two different types of stimulus; both studies empirically supported the proposed model. Furthermore, the first study revealed that advertising has a stronger effect than positive online reviews. The second study found that the peripheral route of the elaboration likelihood model has a stronger influence power than the central route in this context.

Keywords: advertising, electronic word-of-mouth, elaboration likelihood model, intention to visit, trust

Procedia PDF Downloads 459

Authors: A. Ballard

Abstract:

The ability to track goods and products en route in the delivery system, in the warehouse, and on the top floor is a huge advantage to shippers and retailers. Recently the emergence of radio frequency identification (RFID) technology has enabled this better than ever before. However, a significant problem exists in that RFID technology depends on the quality of the information stored for each tagged product. Because of the profusion of names for colours, it is very difficult to ascertain that stored values are recognised by all users who view the product visually. This paper reports the findings of a study in which 50 consumers and 50 logistics workers were shown colour swatches and asked to choose the name of the colour from a multiple choice list. They were then asked to match consumer products, including toasters, jumpers, and toothbrushes, with the identifying inventory information available for each one. The findings show that the ability to match colours was significantly stronger with the color swatches than with the consumer products and that while logistics professionals made more frequent correct identification than the consumers, their results were still unsatisfactorily low. Based on these findings, a proposed universal model of colour identification numbers has been developed.

Keywords: consumer preferences, supply chain logistics, radio frequency identification, RFID, colour preference

Procedia PDF Downloads 121

Authors: Ahmad Sarfaraz, Raiyad Herwies

Abstract:

In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.

Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making

Procedia PDF Downloads 386