Search results for: sport services model

Authors: A. C. Dey, H. M. Ahsan

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Heterogeneous traffic composed of both motorized and non-motorized vehicles that are a common feature of urban Bangladeshi roads. Popular non-motorized vehicles include rickshaws, rickshaw-van, and bicycle. These modes performed an important role in moving people and goods in the absence of a dependable mass transport system. However, rickshaws play a major role in meeting the demand for door-to-door public transport services to the city dwellers. But there is no separate lane for non-motorized vehicles in this city. Non-motorized vehicles generally occupy the outermost or curb-side lanes, however, at intersections non-motorized vehicles get mixed with the motorized vehicles. That’s why the conventional models fail to analyze the situation completely. Microscopic traffic simulation software VISSIM 5.3, itself a lane base software but default behavioral parameters [such as driving behavior, lateral distances, overtaking tendency, CCO=0.4m, CC1=1.5s] are modified for calibrating a model to analyze the effects of non-motorized traffic at an intersection (Mirpur-10) in a non-lane based mixed traffic condition. It is seen from field data that NMV occupies an average 20% of the total number of vehicles almost all the link roads. Due to the large share of non-motorized vehicles, capacity significantly drop. After analyzing simulation raw data, significant variation is noticed. Such as the average vehicular speed is reduced by 25% and the number of vehicles decreased by 30% only for the presence of NMV. Also the variation of lateral occupancy and queue delay time increase by 2.37% and 33.75% respectively. Thus results clearly show the negative effects of non-motorized vehicles on capacity at an intersection. So special management technics or restriction of NMV at major intersections may be an effective solution to improve this existing critical condition.

Keywords: lateral occupancy, non lane based intersection, nmv, queue delay time, VISSIM 5.3

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Authors: Golnush Masghati-Amoli, Paul Chin

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Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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Authors: Michaela Vašková

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With the increasing dependence of countries on the critical infrastructure, it increases their vulnerability. Big threat is primarily in the human factor (personnel of the critical infrastructure) and in terrorist attacks. It emphasizes the development of methodology for searching of weak points and their subsequent elimination. This article discusses methods for the analysis of safety in the objects of critical infrastructure. It also contains proposal for methodology for training employees of security services in the objects of the critical infrastructure and developing scenarios of attacks on selected objects of the critical infrastructure.

Keywords: critical infrastructure, object of critical infrastructure, protection, safety, security, security audit

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Authors: Sergio Curilef, Boris Atenas

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Systems with long-range interactions are very common in nature. They are observed from the atomic scale to the astronomical scale and exhibit anomalies, such as inequivalence of ensembles, negative heat capacity, ergodicity breaking, nonequilibrium phase transitions, quasistationary states, and anomalous diffusion. These anomalies are exacerbated when special initial conditions are imposed; in particular, we use the so-called water bag initial conditions that stand for a uniform distribution. Several theoretical and practical implications are discussed here. A potential energy inspired by dipole-dipole interactions is proposed to build the dipole-type Hamiltonian mean-field model. As expected, the dynamics is novel and general to the behavior of systems with long-range interactions, which is obtained through molecular dynamics technique. Two plateaus sequentially emerge before arriving at equilibrium, which are corresponding to two different quasistationary states. The first plateau is a type of quasistationary state the lifetime of which depends on a power law of N and the second plateau seems to be a true quasistationary state as reported in the literature. The general behavior of the model according to its dynamics and thermodynamics is described. Using numerical simulation we characterize the mean kinetic energy, caloric curve, and the diffusion law through the mean square of displacement. The present challenge is to characterize the distributions in phase space. Certainly, the equilibrium state is well characterized by the Gaussian distribution, but quasistationary states in general depart from any Gaussian function.

Keywords: dipole-type interactions, dynamics and thermodynamics, mean field model, quasistationary states

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Authors: Saniye Çeşmecioğlu

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The importance of project sustainability and success has become increasingly significant due to the proliferation of external environmental factors that have decreased project resistance in contemporary times. The primary approach to forestall the failure of projects is to ensure their long-term viability through the strategic selection of projects as creating judicious project selection framework within the organization. Decision-makers require precise decision contexts (models) that conform to the company's business objectives and sustainability expectations during the project selection process. The establishment of a rational model for project selection enables organizations to create a distinctive and objective framework for the selection process. Additionally, for the optimal implementation of this decision-making model, it is crucial to establish a Project Management Office (PMO) team and Project Steering Committee within the organizational structure to oversee the framework. These teams enable updating project selection criteria and weights in response to changing conditions, ensuring alignment with the company's business goals, and facilitating the selection of potentially viable projects. This paper presents a multi-criteria decision model for selecting project sustainability and project success criteria that ensures timely project completion and retention. The model was developed using MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) and was based on broadcaster companies’ expectations. The ultimate results of this study provide a model that endorses the process of selecting the appropriate project objectively by utilizing project selection and sustainability criteria along with their respective weights for organizations. Additionally, the study offers suggestions that may ascertain helpful in future endeavors.

Keywords: project portfolio management, project selection, multi-criteria decision making, project sustainability and success criteria, MACBETH

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Authors: M. G. N. A. S. Fernando

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This study uses a researchable framework to improve the quality of ICT education and the Teaching Learning Assessment/ Evaluation (TLA/TLE) process. It utilizes existing resources while improving the methodologies along with pedagogical techniques and e-Learning approaches used in the secondary schools of Sri Lanka. The study was carried out in two phases. Phase I focused on investigating the factors which affect the quality of ICT education. Based on the key factors of phase I, the Phase II focused on the design of an Experimental Application Model with 6 activity levels. Each Level in the Activity Model covers one or more levels in the Revised Bloom’s Taxonomy. Towards further enhancement of activity levels, other pedagogical techniques (activity based learning, e-learning techniques, problem solving activities and peer discussions etc.) were incorporated to each level in the activity model as appropriate. The application model was validated by a panel of teachers including a domain expert and was tested in the school environment too. The validity of performance was proved using 6 hypotheses testing and other methodologies. The analysis shows that student performance with problem solving activities increased by 19.5% due to the different treatment levels used. Compared to existing process it was also proved that the embedded techniques (mixture of traditional and modern pedagogical methods and their applications) are more effective with skills development of teachers and students.

Keywords: activity models, Bloom’s taxonomy, ICT education, pedagogies

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Authors: Tapas Acharya, Monalisa Mitra

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Overlay modeling is the most widely used conventional analysis for spatial decision support system. Overlay modeling requires a set of themes with different weightage computed in varied manners, which gives a resultant input for further integrated analysis. In spite of the popularity and most widely used technique; it gives inconsistent and erroneous results for similar inputs while processed in various GIS overlay techniques. This study is an attempt to compare and analyse the differences in the outputs of different overlay methods using GIS platform with same set of themes of the Precambrian metamorphic to obtain groundwater prospecting in Precambrian metamorphic rocks. The objective of the study is to emphasize the most suitable overlay method for groundwater prospecting in older Precambrian metamorphics. Seven input thematic layers like slope, Digital Elevation Model (DEM), soil thickness, lineament intersection density, average groundwater table fluctuation, stream density and lithology have been used in the spatial overlay models of fuzzy overlay, weighted overlay and weighted sum overlay methods to yield the suitable groundwater prospective zones. Spatial concurrence analysis with high yielding wells of the study area and the statistical comparative studies among the outputs of various overlay models using RStudio reveal that the Weighted Overlay model is the most efficient GIS overlay model to delineate the groundwater prospecting zones in the Precambrian metamorphic rocks.

Keywords: fuzzy overlay, GIS overlay model, groundwater prospecting, Precambrian metamorphics, weighted overlay, weighted sum overlay

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Authors: Elena Pozdnyakova

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“Government Relations” is a field of knowledge presently taught at the majority of universities around the globe. English as the default language can become the language of teaching since the issues discussed are both global and national in character. However for this field of knowledge key concepts and their word representations in English don’t often coincide with those in other languages. International master’s degree students abroad as well as students, taught the course in English at their national universities, are exposed to difficulties, connected with correct conceptualizing of terminology of GR in British and American academic traditions. The study was carried out during the GR English language course elaboration (pilot research: 2013 -2015) at Moscow State Institute of Foreign Relations (University), Russian Federation. Within this period, English language instructors designed and elaborated the three-semester course of GR. Methodologically the course design was based on elaboration model with the special focus on conceptual elaboration sequence and theoretical elaboration sequence. The course designers faced difficulties in concept selection and theoretical elaboration sequence. To improve the results and eliminate the problems with concept selection, a new, corpus-based approach was worked out. The computer-based tool WordSmith 6.0 was used with the aim to build a model of key concept selection. The corpus of GR English texts consisted of 1 million words (the study corpus). The approach was based on measuring effect size, i.e. the percent difference of the frequency of a word in the study corpus when compared to that in the reference corpus. The results obtained proved significant improvement in the process of concept selection. The corpus-based model also facilitated theoretical elaboration of teaching materials.

Keywords: corpus-based study, English as the default language, key concepts, measuring effect size, model of key concept selection

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Authors: Rabiul Islam

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The study was in order to assess soil erosion at plot scale Universal Soil Loss Equation (USLE) erosion model and Geographic Information System (GIS) technique have been used for the study 8 plots in Guthrie Corridor Expressway, Selangor, Malaysia. The USLE model estimates an average soil loss soil integrating several factors such as rainfall erosivity factor(R ), Soil erodibility factor (K), slope length and steepness factor (LS), vegetation cover factor as well as conservation practice factor (C &P) and Results shows that the four plots have very low rates of soil loss, i.e. NLDNM, NDNM, PLDM, and NDM having an average soil loss of 0.059, 0.106, 0.386 and 0.372 ton/ha/ year, respectively. The NBNM, PLDNM and NLDM plots had a relatively higher rate of soil loss, with an average of 0.678, 0.757 and 0.493ton/ha/year. Whereas, the NBM is one of the highest rate of soil loss from 0.842 ton/ha/year to maximum 16.466 ton/ha/year. The NBM plot was located at bare the land; hence the magnitude of C factor(C=0.15) was the highest one.

Keywords: USLE model, GIS, Guthrie Corridor Expressway (GCE), Malaysia

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Authors: Masoud Swalehe, Semra Günay

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Developed countries are losing many lives to non-communicable diseases as compared to their developing counterparts. The effects of these diseases are mostly sudden and manifest at a very short time prior to death or a dangerous attack and this has consolidated the significance of emergency medical system (EMS) as one of the vital areas of healthcare service delivery. The primary objective of this research is to reduce ambulance response times (RT) of Eskişehir province EMS since a number of studies have established a relationship between ambulance response times and survival chances of patients especially out of hospital cardiac arrest (OHCA) victims. It has been found out that patients who receive out of hospital medical attention in few (4) minutes after cardiac arrest because of low ambulance response times stand higher chances of survival than their counterparts who take longer times (more than 12 minutes) to receive out of hospital medical care because of higher ambulance response times. The study will make use of geographic information systems (GIS) technology to dynamically reallocate ambulance resources according to demand and time so as to reduce ambulance response times. Geospatial-time distribution of ambulance calls (demand) will be used as a basis for optimal ambulance deployment using system status management (SSM) strategy to achieve much demand coverage with the same number of ambulance resources to cause response time reduction. Drive-time polygons will be used to come up with time specific facility coverage areas and suggesting additional facility candidate sites where ambulance resources can be moved to serve higher demands making use of network analysis techniques. Emergency Ambulance calls’ data from 1st January 2014 to 31st December 2014 obtained from Eskişehir province health directorate will be used in this study. This study will focus on the reduction of ambulance response times which is a key Emergency Medical Services performance indicator.

Keywords: emergency medical services, system status management, ambulance response times, geographic information system, geospatial-time distribution, out of hospital cardiac arrest

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Authors: Sumaira Ashraf, Elisabete G.S. Félix, Zélia Serrasqueiro

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Traditional financial distress prediction models performed well to predict bankrupt and insolvent firms of the developed markets. Previous studies particularly focused on the predictability of financial distress, financial failure, and bankruptcy of firms. This paper contributes to the literature by extending the definition of financial distress with the inclusion of early warning signs related to quotation of face value, dividend/bonus declaration, annual general meeting, and listing fee. The study used five well-known distress prediction models to see if they have the ability to predict early warning signs of financial distress. Results showed that the predictive ability of the models varies over time and decreases specifically for the sample with early warning signs of financial distress. Furthermore, the study checked the differences in the predictive ability of the models with respect to the financial crisis. The results conclude that the predictive ability of the traditional financial distress prediction models decreases for the firms with early warning signs of financial distress and during the time of financial crisis. The study developed a new model comprising significant variables from the five models and one new variable earning response. This new model outperforms the old distress prediction models before, during and after the financial crisis. Thus, it can be used by researchers, organizations and all other concerned parties to indicate early warning signs for the emerging markets.

Keywords: financial distress, emerging market, prediction models, Z-Score, logit analysis, probit model

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Authors: Natalia Feruleva

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The goal of this paper is to develop the fraud risk assessment model basing on both relational and financial data and test the impact of the relationships between Russian non-public companies on the likelihood of financial fraud commitment. Relationships mean various linkages between companies such as parent-subsidiary relationship and person-related relationships. These linkages may provide additional opportunities for committing fraud. Person-related relationships appear when firms share a director, or the director owns another firm. The number of companies belongs to CEO and managed by CEO, the number of subsidiaries was calculated to measure the relationships. Moreover, the dummy variable describing the existence of parent company was also included in model. Control variables such as financial leverage and return on assets were also implemented because they describe the motivating factors of fraud. To check the hypotheses about the influence of the chosen parameters on the likelihood of financial fraud, information about person-related relationships between companies, existence of parent company and subsidiaries, profitability and the level of debt was collected. The resulting sample consists of 160 Russian non-public firms. The sample includes 80 fraudsters and 80 non-fraudsters operating in 2006-2017. The dependent variable is dichotomous, and it takes the value 1 if the firm is engaged in financial crime, otherwise 0. Employing probit model, it was revealed that the number of companies which belong to CEO of the firm or managed by CEO has significant impact on the likelihood of financial fraud. The results obtained indicate that the more companies are affiliated with the CEO, the higher the likelihood that the company will be involved in financial crime. The forecast accuracy of the model is about is 80%. Thus, the model basing on both relational and financial data gives high level of forecast accuracy.

Keywords: financial fraud, fraud prediction, non-public companies, regression analysis, relational data

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Authors: Nabila Jaman, K. E. Hoque, S. Sawall, M. Ferdows

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Coronary artery disease (CAD) is one of the most lethal diseases of the cardiovascular diseases. Coronary arteries stenosis and bifurcation angles closely interact for myocardial infarction. We want to use computer-aided design model coupled with computational hemodynamics (CHD) simulation for detecting several types of coronary artery stenosis with different locations in an idealized model for identifying virtual fractional flow reserve (vFFR). The vFFR provides us the information about the severity of stenosis in the computational models. Another goal is that we want to imitate patient-specific computed tomography coronary artery angiography model for constructing our idealized models with different left anterior descending (LAD) and left circumflex (LCx) bifurcation angles. Further, we want to analyze whether the bifurcation angles has an impact on the creation of narrowness in coronary arteries or not. The numerical simulation provides the CHD parameters such as wall shear stress (WSS), velocity magnitude and pressure gradient (PGD) that allow us the information of stenosis condition in the computational domain.

Keywords: CAD, CHD, vFFR, bifurcation angles, coronary stenosis

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Authors: Yi-Hsien Wang, Fu-Ju Yang, Hwa-Rong Shen, Rui-Lin Tseng

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The business is notably related to the market risk according to the increase of liberalization of financial markets. Hence, the company usually utilized high financial leverage of derivatives to hedge the risk. When the company choose different hedging instruments to face a variety of exchange rate risk, we employ the Multinomial Logistic-AHP to analyze the impact of various derivatives. Hence, the research summarized the literature on relevant factors affecting managers selected exchange rate hedging instruments, using Multinomial Logistic Model and and further integrate AHP. Using Experts’ Questionnaires can test multi-level selection and hedging effect of different hedging instruments in order to calculate the hedging instruments and the multi-level factors of weights to understand the gap between the empirical results and practical operation. Finally, the Multinomial Logistic-AHP Model will sort the weights to analyze. The research findings can be a basis reference for investors in decision-making.

Keywords: exchange rate risk, derivatives, hedge, multinomial logistic-AHP

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Authors: Andres Nieto-Leal, Victor N. Kaliakin, Tania P. Molina

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The nature of most engineering materials is quite complex. It is, therefore, difficult to devise a general mathematical model that will cover all possible ranges and types of excitation and behavior of a given material. As a result, the development of mathematical models is based upon simplifying assumptions regarding material behavior. Such simplifications result in some material idealization; for example, one of the simplest material idealization is to assume that the material behavior obeys the elasticity. However, soils are nonhomogeneous, anisotropic, path-dependent materials that exhibit nonlinear stress-strain relationships, changes in volume under shear, dilatancy, as well as time-, rate- and temperature-dependent behavior. Over the years, many constitutive models, possessing different levels of sophistication, have been developed to simulate the behavior geomaterials, particularly cohesive soils. Early in the development of constitutive models, it became evident that elastic or standard elastoplastic formulations, employing purely isotropic hardening and predicated in the existence of a yield surface surrounding a purely elastic domain, were incapable of realistically simulating the behavior of geomaterials. Accordingly, more sophisticated constitutive models have been developed; for example, the bounding surface elastoplasticity. The essence of the bounding surface concept is the hypothesis that plastic deformations can occur for stress states either within or on the bounding surface. Thus, unlike classical yield surface elastoplasticity, the plastic states are not restricted only to those lying on a surface. Elastoplastic bounding surface models have been improved; however, there is still need to improve their capabilities in simulating the response of anisotropically consolidated cohesive soils, especially the response in extension tests. Thus, in this work an improved constitutive model that can more accurately predict diverse stress-strain phenomena exhibited by cohesive soils was developed. Particularly, an improved rotational hardening rule that better simulate the response of cohesive soils in extension. The generalized definition of the bounding surface model provides a convenient and elegant framework for unifying various previous versions of the model for anisotropically consolidated cohesive soils. The Generalized Bounding Surface Model for cohesive soils is a fully three-dimensional, time-dependent model that accounts for both inherent and stress induced anisotropy employing a non-associative flow rule. The model numerical implementation in a computer code followed an adaptive multistep integration scheme in conjunction with local iteration and radial return. The one-step trapezoidal rule was used to get the stiffness matrix that defines the relationship between the stress increment and the strain increment. After testing the model in simulating the response of cohesive soils through extensive comparisons of model simulations to experimental data, it has been shown to give quite good simulations. The new model successfully simulates the response of different cohesive soils; for example, Cardiff Kaolin, Spestone Kaolin, and Lower Cromer Till. The simulated undrained stress paths, stress-strain response, and excess pore pressures are in very good agreement with the experimental values, especially in extension.

Keywords: bounding surface elastoplasticity, cohesive soils, constitutive model, modeling of geomaterials

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Authors: Michal Biały, Konrad Pietrykowski, Rafal Sochaczewski

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The kinematics and dynamics analysis of crank-piston system of aircraft engine. The object of the study was the high power aircraft engine ASz 62-IR. This engine is produced by a Polish company WSK "PZL-KALISZ" S.A.". All analyzes were performed numerically using CAD and CAE environment. Three-dimensional model of the crank-piston system was developed based on real engine located in the Laboratory of Centre of Innovation and Advanced Technologies of Lublin University of Technology. During the development of the model, the technique of reverse engineering - 3D scanning was used. ASz 62-IR engine is characterized by a radial type of crank-piston system. In this system the cylinders are arranged radially around the circle. This crank-piston system consists of a main connecting rod and eight additional connecting rods. In addition, three-dimensional model consists of a piston pins, pistons and piston rings. As a result of the specific engine design, characteristics of the piston individual movement are slightly different from each other. But the model assumes that they are the same during the analysis. Three-dimensional model of the engine was implemented into the MSC Adams software. The environment of MSC Adams allows for multibody simulation of the dynamic phenomena. This determines the state parameters of the moving elements, among which the load or force distribution on each kinematic node can be distinguished. Materials and characteristic materials parameters were adopted on the basis of commonly used materials for engine parts. The mass values of individual elements were adopted on the basis of real engine parts. The piston gas forces were replaced by calculation of pressure variations recorded during engine tests on the engine test bench. The research the changes of forces acting in the individual kinematic pairs of crank-piston system. The model allows to determine the load on the crankshaft main bearings. This gives the possibility for the main supports forces analysis The model allows for testing and simulation of kinematics and dynamics of a radial aircraft engine. This is the first stage of the work, which aims to numerical simulation of vibration of multi-cylinder aircraft engine. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under Grant Agreement No. INNOLOT/I/1/NCBR/2013.

Keywords: aircraft engine, CAD, CAE, dynamics, kinematics, MSC Adams, numerical simulation

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Authors: Dongju Kim, Youngjoo Suh, Hyojin Kim, Gyeongyeong Kim

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Acoustic Emission Testing (AET) is widely used to test the structural integrity of an operational hydrogen storage container, and clustering algorithms are frequently used in pattern recognition methods to interpret AET results. However, the interpretation of AET results can vary from user to user as the tuning of the relevant parameters relies on the user's experience and knowledge of AET. Therefore, it is necessary to use a deep learning model to identify patterns in acoustic emission (AE) signal data that can be used to classify defects instead. In this paper, a deep learning-based model for classifying the types of defects in hydrogen storage tanks, using AE sensor waveforms, is proposed. As hydrogen storage tanks are commonly constructed using carbon fiber reinforced polymer composite (CFRP), a defect classification dataset is collected through a tensile test on a specimen of CFRP with an AE sensor attached. The performance of the classification model, using one-dimensional convolutional neural network (1-D CNN) and synthetic minority oversampling technique (SMOTE) data augmentation, achieved 91.09% accuracy for each defect. It is expected that the deep learning classification model in this paper, used with AET, will help in evaluating the operational safety of hydrogen storage containers.

Keywords: acoustic emission testing, carbon fiber reinforced polymer composite, one-dimensional convolutional neural network, smote data augmentation

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Authors: T. Yuri, M. Zagloel, Inaki M. Hakim, Tegu Bintang Nugraha

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In an era of customer centricity, automotive parts manufacturer in Indonesia must be able to keep up with the uncertainty and fluctuation of consumer demand. Flexible Manufacturing System (FMS) is a strategy to react to predicted and unpredicted changes of demand in automotive industry. This research is about flexible mixed model assembly line design through Value Stream Mapping (VSM) and Line Balancing in mixed model assembly line prior to simulation. It uses value stream mapping to identify and reduce waste while finding the best position to add or reduce manpower. Line balancing is conducted to minimize or maximize production rate while increasing assembly line productivity and efficiency. Results of this research is a recommendation of standard work combination for specifics demand scenario which can enhance assembly line efficiency and productivity.

Keywords: automotive industry, demand uncertainty, flexible assembly system, line balancing, value stream mapping

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Authors: Vishal H. Shukla, Sanjay B. Deshmukh

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Traffic engineering, at its center, is the ability of moving traffic approximately so that traffic from a congested link is moved onto the unused capacity on another link. Traffic Engineering ensures the best possible use of the resources. Now to support traffic engineering in the today’s network, Multiprotocol Label Switching (MPLS) is being used which is very helpful for reliable packets delivery in an ongoing internet services. Here a topology is been implemented on GNS3 to focus on the analysis of the communication take place from one site to other through the ISP. The comparison is made between the IP network & MPLS network based on Bandwidth & Jitter which are one of the performance parameters using JPERF simulator.

Keywords: GNS3, JPERF, MPLS, traffic engineering, VMware

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Authors: Jutamas Wisansing, Thanakarn Vongvisitsin, Udom Hongchatikul

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Designated Areas for Sustainable Tourism Administration (DASTA) is a public organization, dedicating to sustainable tourism development in 6 designated areas in Thailand. This paper provides rich reflections from a decade of DASTA, formulating an advanced model to deepen our understanding of 2 key intertwining issues; 1) what are the new landscapes of actors for community based tourism and 2) who are the benefactors and beneficiaries of tourism development within the community? An action research approach was used, enabling the process and evidence-based cases to be better captured. The aim is to build theoretical foundation through 13 communities/cases, which have engaged in community based tourism pilot projects. Drawing from emic and qualitative research, specific and contextual phenomenon provides succinct patterns of ‘Community Benefitting through Tourism (CbtT)’ model. The re-definition of the 2 key issues helps shape the interlinking of actors; practicalities of inclusive tourism and inter-sectoral framework and its value chain will also be set forth. In tourism sector, community members could be active primarily on the supply side as employees, entrepreneurs and local heritage experts. CbtT when well defined stimulates the entire value chain of local economy while promoting social innovation through positive dialogue with wider actors. Collaboration with a new set of actors who are from the tourism-related businesses and non-tourism related businesses create better impacts on mutual benefits.

Keywords: community based tourism, community benefitting through tourism -CbtT DASTA model, sustainable tourism in thailand, value chain and inclusive business

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Authors: David Percy

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Landslides are a geologic phenomenon that affects a large number of inhabited places and are constantly being monitored and studied for the prediction of future occurrences. Reconstructability analysis (RA) is a methodology for extracting informative models from large volumes of data that work exclusively with discrete data. While RA has been used in medical applications and social science extensively, we are introducing it to the spatial sciences through applications like landslide prediction. Since RA works exclusively with discrete data, such as soil classification or bedrock type, working with continuous data, such as porosity, requires that these data are binned for inclusion in the model. RA constructs models of the data which pick out the most informative elements, independent variables (IVs), from each layer that predict the dependent variable (DV), landslide occurrence. Each layer included in the model retains its classification data as a primary encoding of the data. Unlike other machine learning algorithms that force the data into one-hot encoding type of schemes, RA works directly with the data as it is encoded, with the exception of continuous data, which must be binned. The usual physical and derived layers are included in the model, and testing our results against other published methodologies, such as neural networks, yields accuracy that is similar but with the advantage of a completely transparent model. The results of an RA session with a data set are a report on every combination of variables and their probability of landslide events occurring. In this way, every combination of informative state combinations can be examined.

Keywords: reconstructability analysis, machine learning, landslides, raster analysis

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Authors: Salman Obaidoon, Mohamed Hassan, Omer Bakather

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As environmental regulations increase, the need for a clean and inexpensive energy is becoming necessary these days using an available raw material with high efficiency and low emissions of toxic gases. This paper presents a study on modifying a gas turbine power plant fired by diesel, which is located in Saudi Arabia in order to increase the efficiency and capacity of the station as well as decrease the rate of emissions. The studied power plant consists of 30 units with different capacities and total net power is 1470 MW. The study was conducted on unit number 25 (GT-25) which produces 72.3 MW with 29.5% efficiency. In the beginning, the unit was modeled and simulated by using WinSim Design II software. In this step, actual unit data were used in order to test the validity of the model. The net power and efficiency obtained from software were 76.4 MW and 32.2% respectively. A difference of about 6% was found in the simulated power plant compared to the actual station which means that the model is valid. After the validation of the model, the simple gas turbine power plant was converted to a combined cycle power plant (CCPP). In this case, the exhausted gas released from the gas turbine was introduced to a heat recovery steam generator (HRSG), which consists of three heat exchangers: an economizer, an evaporator and a superheater. In this proposed model, many scenarios were conducted in order to get the optimal operating conditions. The net power of CCPP was increased to 116.4 MW while the overall efficiency of the unit was reached to 49.02%, consuming the same amount of fuel for the gas turbine power plant. For the purpose of comparing the rate of emissions of carbon dioxide on each model. It was found that the rate of CO₂ emissions was decreased from 15.94 kg/s to 9.22 kg/s by using the combined cycle power model as a result of reducing of the amount of diesel from 5.08 kg/s to 2.94 kg/s needed to produce 76.5 MW. The results indicate that the rate of emissions of carbon dioxide was decreased by 42.133% in CCPP compared to the simple gas turbine power plant.

Keywords: combined cycle power plant, efficiency, heat recovery steam generator, simulation, validation, WinSim design II software

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Authors: Emanuela Zilli, Antonio Madia, Milvia Marchiori, Paola Anello, Chiara Cabbia, Emanuela Velo, Delia Campagnolo, Michele Scomazzon, Emanuela Salvatico, S. Tikvina, Antonio Miotti

Abstract:

Hepatitis C is an inflammation of the liver caused by the hepatitis C virus (HCV). Antiviral medicines can cure more than 95% of cases of hepatitis C infection, but access to diagnosis and treatment remains low. The ULSS 6 Euganea – Health Trust has implemented a campaign to eradicate hepatitis C in the province of Padua (North-East of Italy), which can be subdivided into three areas: North (300.000 inhabitants), Centre (400.000) and South (300.000). In September 2021, the project was launched in the Northern area; a set of brochures was distributed in outpatient services, general practitioners’ clinics and offices, community pharmacy services, social health districts, and through social networks. The Hepatology Service contacted 460 patients selected by the Clinical Laboratory (positivity for HCV antibodies): 83 patients (18.0%) had been already cured of HCV infection, missing or deceased; 377 patients (82.0%) met the criteria to be eligible for HCV eradication therapy and were therefore included in a Day Service specific agenda and followed by a multidisciplinary team of healthcare professionals, with a dedicated telephone line. Haemato-chemical tests, general medical check-ups and ultrasound tests with fibroscan were performed. Patients were tested for Sars-CoV-2 positivity; those not yet vaccinated against Covid-19 were encouraged to complete the vaccination scheme. All 377 patients (100%) received HCV eradication therapy at the community pharmacy service; a detailed explanation of how to take their medication was provided. At the end of the first phase, Covid-19 vaccination rate was 100% (377/377), including patients already vaccinated and new-vaccinated. Check-up appointments were arranged after 2 or 3 months, according to the treatment plan. The awareness campaign and the organization of HCV eradication therapy service by ULSS 6 Euganea are proving to be effective; the project is now going to be applied to Central and Southern areas of the province (1.132 patients).

Keywords: public health, HCV-eradication, Covid-19 emergency, health communication strategies

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Authors: Schehrazad Selmane

Abstract:

We present a deterministic model which describes the dynamics of tuberculosis in Algerian population where the vaccination program with BCG is in place since 1969 and where the WHO recommendations regarding the DOTS (directly observed treatment, short course) strategy are in application. The impact of an intervention program, targeting recently infected people among all close contacts of active cases and their treatment to prevent endogenous reactivation, on the incidence of tuberculosis, is investigated. We showed that a widespread treatment of latently infected individuals for some years is recommended to shift from higher to lower equilibrium state and thereafter relaxation is recommended.

Keywords: deterministic model, reproduction number, stability, tuberculosis

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Authors: Zunaira Asif, Zhi Chen

Abstract:

The sustainable measures on air quality management are recognized as one of the most serious environmental concerns in the mining region. The mining operations emit various types of pollutants which have significant impacts on the environment. This study presents a stochastic control strategy by developing the air pollution control model to achieve a cost-effective solution. The optimization method is formulated to predict the cost of treatment using linear programming with an objective function and multi-constraints. The constraints mainly focus on two factors which are: production of metal should not exceed the available resources, and air quality should meet the standard criteria of the pollutant. The applicability of this model is explored through a case study of an open pit metal mine, Utah, USA. This method simultaneously uses meteorological data as a dispersion transfer function to support the practical local conditions. The probabilistic analysis and the uncertainties in the meteorological conditions are accomplished by Monte Carlo simulation. Reasonable results have been obtained to select the optimized treatment technology for PM_2.5, PM₁₀, NO_x, and SO₂. Additional comparison analysis shows that baghouse is the least cost option as compared to electrostatic precipitator and wet scrubbers for particulate matter, whereas non-selective catalytical reduction and dry-flue gas desulfurization are suitable for NO_x and SO₂ reduction respectively. Thus, this model can aid planners to reduce these pollutants at a marginal cost by suggesting control pollution devices, while accounting for dynamic meteorological conditions and mining activities.

Keywords: air pollution, linear programming, mining, optimization, treatment technologies

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Authors: Thiago Victor Cordeiro Marcos, Joao Felipe de Araujo Martos, Ronaldo de Lima Cardoso, David Romanelli Pinto, Paulo Gilberto de Paula Toro, Israel da Silveira Rego, Antonio Carlos de Oliveira

Abstract:

Currently, the use of 3D rapid prototyping, also known as 3D printing, has been investigated by some universities around the world as an innovative technique, fast, flexible and cheap for a direct plastic models manufacturing that are lighter and with complex geometries to be tested for hypersonic shock tunnel. Initially, the purpose is integrated prototyped parts with metal models that actually are manufactured through of the conventional machining and hereafter replace them with completely prototyped models. The mechanical design models to be tested in hypersonic shock tunnel are based on conventional manufacturing processes, therefore are limited forms and standard geometries. The use of 3D rapid prototyping offers a range of options that enables geometries innovation and ways to be used for the design new models. The conception and project of a prototyped model for hypersonic shock tunnel should be rethought and adapted when comparing the conventional manufacturing processes, in order to fully exploit the creativity and flexibility that are allowed by the 3D prototyping process. The objective of this paper is to compare the conception and project of a 3D rapid prototyping model and a conventional machining model, while showing the advantages and disadvantages of each process and the benefits that 3D prototyping can bring to the manufacture of models to be tested in hypersonic shock tunnel.

Keywords: 3D printing, 3D prototyping, experimental research, hypersonic shock tunnel

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Authors: Jiayun Shen, Lorenz Wyss, Thierry Golliard, Matthias Finger

Abstract:

Innovation is widely recognized as the key for private enterprises to win the market competition. The state-owned-enterprises need to be innovative to compete in the market after the privatization as well. However, it is a lack of research to study how state-owned-enterprises manage innovation to create new products and services. Swiss Post, a Swiss state-owned-enterprises, has established a department to transform the corporate culture and foster innovation to achieve digital transformation. This paper describes the innovation management process at the Swiss Post and analyzes the impacts of the instruments, the organizational structure, and explores the barriers of innovation. This study used qualitative methods based on a review of the literature on innovation management and semi-structured interviews. Being established for over five years, the Swiss Post’s innovation management department has established a software-assisted modularized platform with systematic instruments to help the internal employees with the different innovation processes. It guides the innovators from idea creation to piloting in markets and supports with a separate financing source, with knowledge inputs and coaching, as well as with connections to external partners through the open innovation and venturing team. The platform also adapts to different business units within the corporate with a customized tailor for the various operational business units. The separate financing instruments enabled the creation and further development of new ideas; the coaching services contribute greatly to the transformation of teams’ innovation culture by providing new knowledge, thinking methods, and use cases for inspiration. It also facilitates organizational learning to help the whole corporate with the digital transformation. However, it is also confronted with a big challenge in twofold. Internally, the disruptive projects often hardly overcome the obstacles of long-established operational processes in the traditional business units; externally, the expectations of the public and restrictions from the federal government have become high hurdles for the company to stay and compete in the innovation track.

Keywords: empirical case study, innovation management, state-owned-enterprise, Swiss Post

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Authors: Mehdi Mirzaei Alavijeh, Farzad Jalilian

Abstract:

Background: Marijuana is the most widely used illicit drug worldwide, especially among adolescents and young adults, which can cause numerous complications. The aim of this study was to determine the pattern, motivation use, and factors related to marijuana use among Iranian youths based on the integrative model of behavioral prediction Methods: A cross-sectional study was conducted among 174 youths marijuana user in Kermanshah County and Isfahan County, during summer 2014 which was selected with the convenience sampling for participation in this study. A self-reporting questionnaire was applied for collecting data. Data were analyzed by SPSS version 21 using bivariate correlations and linear regression statistical tests. Results: The mean marijuana use of respondents was 4.60 times at during week [95% CI: 4.06, 5.15]. Linear regression statistical showed, the structures of integrative model of behavioral prediction accounted for 36% of the variation in the outcome measure of the marijuana use at during week (R2 = 36% & P < 0.001); and among them attitude, marijuana refuse, and subjective norms were a stronger predictors. Conclusion: Comprehensive health education and prevention programs need to emphasize on cognitive factors that predict youth’s health-related behaviors. Based on our findings it seems, designing educational and behavioral intervention for reducing positive belief about marijuana, marijuana self-efficacy refuse promotion and reduce subjective norms encourage marijuana use has an effective potential to protect youths marijuana use.

Keywords: marijuana, youth, integrative model of behavioral prediction, Iran

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Authors: Giorgi Katamadze

Abstract:

Open public service and accountability towards citizens is an important feature of democratic state based on rule of law. Effective use of electronic resources simplifies bureaucratic procedures, makes direct communications, helps exchange information, ensures government’s openness and in general helps develop electronic/digital democracy. Development of electronic democracy should be a strategic dimension of Georgian governance. Formation of electronic democracy, its functional improvement should become an important dimension of the state’s information policy. Electronic democracy is based on electronic governance and implies modern information and communication systems, their adaptation to universal standards. E-democracy needs involvement of governments, voters, political parties and social groups in an electronic form. In the last years the process of interaction between the citizen and the state becomes simpler. This process is achieved by the use of modern technological systems which gives to a citizen a possibility to use different public services online. For example, the website my.gov.ge makes interaction between the citizen, business and the state more simple, comfortable and secure. A higher standard of accountability and interaction is being established. Electronic democracy brings new forms of interactions between the state and the citizen: e-engagement – participation of society in state politics via electronic systems; e-consultation – electronic interaction among public officials, citizens and interested groups; e-controllership – electronic rule and control of public expenses and service. Public transparency is one of the milestones of electronic democracy as well as representative democracy as only on mutual trust and accountability can democracy be established. In Georgia, institutional changes concerning establishment and development of electronic democracy are not enough. Effective planning and implementation of a comprehensive and multi component e-democracy program (central, regional, local levels) requires telecommunication systems, institutional (public service, competencies, logical system) and informational (relevant conditions for public involvement) support. Therefore, a systematic project of formation of electronic governance should be developed which will include central, regional, municipal levels and certain aspects of development of instrumental basis for electronic governance.

Keywords: e-democracy, e-governance, e-services, information technology, public administration

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Authors: Reza Lotfalian, Sudarshan Martins, Peter Radziszewski

Abstract:

The effect of reliability on life-cycle cost, including initial and maintenance cost of a system is studied. The failure probability of a component is used to calculate the average maintenance cost during the operation cycle of the component. The standard deviation of the life-cycle cost is also calculated as an error measure for the average life-cycle cost. As a numerical example, the model is used to study the average life cycle cost of an electric motor.

Keywords: initial cost, life-cycle cost, maintenance cost, reliability

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