Search results for: convection-diffusion controlled model

Authors: Anwar Jarndal

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In this paper, a genetic-neural-network (GNN) based large-signal model for GaN HEMTs is presented along with its parameters extraction procedure. The model is easy to construct and implement in CAD software and requires only DC and S-parameter measurements. An improved decomposition technique is used to model self-heating effect. Two GNN models are constructed to simulate isothermal drain current and power dissipation, respectively. The two model are then composed to simulate the drain current. The modeling procedure was applied to a packaged GaN-on-Si HEMT and the developed model is validated by comparing its large-signal simulation with measured data. A very good agreement between the simulation and measurement is obtained.

Keywords: GaN HEMT, computer-aided design and modeling, neural networks, genetic optimization

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Authors: Abdulrazzak Akroot, Lutfu Namli

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Solid oxide fuel cells (SOFCs) are one of the most promising technologies since they can produce electricity directly from fuel and generate a lot of waste heat that is generally used in the gas turbines to promote the general performance of the thermal power plant. In this study, the energy, and exergy analysis of a solid oxide fuel cell/gas turbine hybrid system was proceed in MATLAB to examine the performance characteristics of the hybrid system in two different configurations: anode-supported model and electrolyte-supported model. The obtained results indicate that if the fuel utilization factor reduces from 0.85 to 0.65, the overall efficiency decreases from 64.61 to 59.27% for the anode-supported model whereas it reduces from 58.3 to 56.4% for the electrolyte-supported model. Besides, the overall exergy reduces from 53.86 to 44.06% for the anode-supported model whereas it reduces from 39.96 to 33.94% for the electrolyte-supported model. Furthermore, increasing the air utilization factor has a negative impact on the electrical power output and the efficiencies of the overall system due to the reduction in the O₂ concentration at the cathode-electrolyte interface.

Keywords: solid oxide fuel cell, anode-supported model, electrolyte-supported model, energy analysis, exergy analysis

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Authors: Lugean K. Alomari, Rahaf K. Sharif, Basil K. Alomari, Hind M. Aljabri, Faisal F. Aljahdali, Amal A. Alomari, Saeed A. Alghamdi

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Background: The thermal pulsation system is a therapy that uses heat and massage to treat dry eye disease; thus, some trials have been published to compare it with the conventional treatment. The aim of this study is to conduct a systematic review and meta-analysis comparing the efficacy of thermal pulsation systems with conventional treatment in patients undergoing cataract surgery. Methods: Medline, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL) databases were searched for eligible trials. We included three randomized controlled trials (RCTs) that compared the thermal pulsation system with the conventional treatment in patients undergoing cataract surgery. A table of characteristics was plotted, and the Quality of the studies was assessed using the Cochrane risk-of-bias tool for randomized trials (RoB 2). Forest plots were plotted using the Random-effect Inverse Variance method. χ2 test and the Higgins-I-squared (I2) model were used to assess heterogeneity. A total of 201 cataract surgery patients were included, with 105 undergoing preoperative pulsation therapy and 96 receiving conventional treatment. Demographic analysis revealed comparable distributions across groups. Results: All the studies in our analysis are of good quality with a low risk of bias. A total of 201 patients were included in the analysis, out of which 105 underwent pulsation therapy, and 95 were in the control group. Tear Break-up Time (TBUT) analysis revealed no significant baseline differences, except pulsation therapy being better at 1 month. (SMD 0.42 [95%CI 0.14 - 0.70] p=0.004). This positive trend continued at three months (SMD 0.52 [95% CI (0.20 – 0.84)] p=0.002). Corneal fluorescein staining scores and Meibomian gland-yielding secretion scores showed no significant differences at baseline. However, at one month, pulsation therapy significantly improved Meibomian gland function (SMD -0.86 [95% CI (-1.20 - -0.53)] p<0.00001), indicating a reduced risk of dry eye syndrome. Conclusion: Preoperative pulsation therapy appears to enhance post-cataract surgery outcomes, particularly in terms of tear film stability and Meibomian gland secretory function. The sustained positive effects observed at one and three months post-surgery suggest the potential for long-term benefits.

Keywords: lipiflow, cataract, thermal pulsation, dry eye

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Authors: Mustapha Kamel Mihoubi, Hocine Dahmani

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The purpose of work is to study the phenomenon of agitation of storm waves at basin caused by different directions of waves relative to the current provision thrown numerical model based on the equation in shallow water using Boussinesq model MIKE 21 BW. According to the diminishing effect of penetration of a wave optimal solution will be available to be reproduced in reduced model. Another alternative arrangement throws will be proposed to reduce the agitation and the effects of the swell reflection caused by the penetration of waves in the harbor.

Keywords: agitation, Boussinesq equations, combination, harbor

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Authors: Vedanki Khandenwal, Pawan Srivastava, Kartick Tarafder, Subhasis Ghosh

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We present here the experimental realization of controlled doping of graphene monolayers through charge transfer by trapping selected organic molecules between the graphene layer and underlying substrates. This charge transfer between graphene and trapped molecule leads to controlled n-type or p-type doping in monolayer graphene (MLG), depending on whether the trapped molecule acts as an electron donor or an electron acceptor. Doping controllability has been validated by a shift in corresponding Raman peak positions and a shift in Dirac points. In the transfer characteristics of field effect transistors, a significant shift of Dirac point towards positive or negative gate voltage region provides the signature of p-type or n-type doping of graphene, respectively, as a result of the charge transfer between graphene and the organic molecules trapped within it. In order to facilitate the charge transfer interaction, it is crucial for the trapped molecules to be situated in close proximity to the graphene surface, as demonstrated by findings in Raman and infrared spectroscopies. However, the mechanism responsible for this charge transfer interaction has remained unclear at the microscopic level. Generally, it is accepted that the dipole moment of adsorbed molecules plays a crucial role in determining the charge-transfer interaction between molecules and graphene. However, our findings clearly illustrate that the doping effect primarily depends on the reactivity of the constituent atoms in the adsorbed molecules rather than just their dipole moment. This has been illustrated by trapping various molecules at the graphene−substrate interface. Dopant molecules such as acetone (containing highly reactive oxygen atoms) promote adsorption across the entire graphene surface. In contrast, molecules with less reactive atoms, such as acetonitrile, tend to adsorb at the edges due to the presence of reactive dangling bonds. In the case of low-dipole moment molecules like toluene, there is a lack of substantial adsorption anywhere on the graphene surface. Observation of (i) the emergence of the Raman D peak exclusively at the edges for trapped molecules without reactive atoms and throughout the entire basal plane for those with reactive atoms, and (ii) variations in the density of attached molecules (with and without reactive atoms) to graphene with their respective dipole moments provides compelling evidence to support our claim. Additionally, these observations were supported by first principle density functional calculations.

Keywords: graphene, doping, charge transfer, liquid phase exfoliation

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Authors: Jang kyun Cho, Jeong-dong Lee

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The advent of the Internet, mobile communications, and social network services has stimulated social interactions among consumers, allowing people to affect one another’s innovation adoptions by exchanging information more frequently and more quickly. Previous diffusion models, such as the Bass model, however, face limitations in reflecting such recent phenomena in society. These models are weak in their ability to model interactions between agents; they model aggregated-level behaviors only. The agent based model, which is an alternative to the aggregate model, is good for individual modeling, but it is still not based on an economic perspective of social interactions so far. This study assumes the presence of social utility from other consumers in the adoption of innovation and investigates the effect of individual interactions on innovation diffusion by developing a new model called the interaction-based diffusion model. By comparing this model with previous diffusion models, the study also examines how the proposed model explains innovation diffusion from the perspective of economics. In addition, the study recommends the use of a small-world network topology instead of cellular automata to describe innovation diffusion. This study develops a model based on individual preference and heterogeneous social interactions using utility specification, which is expandable and, thus, able to encompass various issues in diffusion research, such as reservation price. Furthermore, the study proposes a new framework to forecast aggregated-level market demand from individual level modeling. The model also exhibits a good fit to real market data. It is expected that the study will contribute to our understanding of the innovation diffusion process through its microeconomic theoretical approach.

Keywords: innovation diffusion, agent based model, small-world network, demand forecasting

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Authors: Hamideh Marefat, Eskandar Samadi

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This study examined the effect of semantics on processing ambiguous sentences containing Relative Clauses (RCs) preceded by a complex Determiner Phrase (DP) by Persian-speaking learners of L2 English with different proficiency and Working Memory Capacities (WMCs). The semantic relationship studied was one between the subject of the main clause and one of the DPs in the complex DP to see if, as predicted by Spreading Activation Model, priming one of the DPs through this semantic manipulation affects the L2ers’ preference. The results of a task using Rapid Serial Visual Processing (time-controlled paradigm) showed that manipulation of the relationship between the subject of the main clause and one of the DPs in the complex DP preceding RC has no effect on the choice of the antecedent; rather, the L2ers' processing is guided by the phrase structure information. Moreover, while proficiency did not have any effect on the participants’ preferences, WMC brought about a difference in their preferences, with a DP1 preference by those with a low WMC. This finding supports the chunking hypothesis and the predicate proximity principle, which is the strategy also used by monolingual Persian speakers.

Keywords: semantics, relative clause processing, ambiguity resolution, proficiency, working memory capacity

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Authors: Retius Chifurira

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Logistic regression model is the most used regression model to predict meteorological drought probabilities. When the dependent variable is extreme, the logistic model fails to adequately capture drought probabilities. In order to adequately predict drought probabilities, we use the generalized linear model (GLM) with the quantile function of the generalized extreme value distribution (GEVD) as the link function. The method maximum likelihood estimation is used to estimate the parameters of the generalized extreme value (GEV) regression model. We compare the performance of the logistic and the GEV regression models in predicting drought probabilities for Zimbabwe. The performance of the regression models are assessed using the goodness-of-fit tests, namely; relative root mean square error (RRMSE) and relative mean absolute error (RMAE). Results show that the GEV regression model performs better than the logistic model, thereby providing a good alternative candidate for predicting drought probabilities. This paper provides the first application of GLM derived from extreme value theory to predict drought probabilities for a drought-prone country such as Zimbabwe.

Keywords: generalized extreme value distribution, general linear model, mean annual rainfall, meteorological drought probabilities

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Authors: Dorota Miroslaw-Swiatek, Mateusz Grygoruk, Sylwia Szporak

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We applied a two-dimensional surface water flow model with irregular wet boundaries. In this model, flow equations are in the form of a 2-D, non-linear diffusion equations which allows to account spatial variations in flow resistance and topography. Calculation domain to simulate the flow pattern in the floodplain is congruent with a Digital Elevation Model (DEM) grid. The rate and direction of sheet flow in wetlands is affected by vegetation type and density, therefore the developed model take into account spatial distribution vegetation resistance to the water flow. The model was tested in a part of the Biebrza Valley, of an outstanding heterogeneity in the elevation and flow resistance distributions due to various ecohydrological conditions and management measures. In our approach we used the highest-possible quality of the DEM in order to obtain hydraulic slopes and vegetation distribution parameters for the modelling. The DEM was created from the cloud of points measured in the LiDAR technology. The LiDAR reflects both the land surface as well as all objects on top of it such as vegetation. Depending on the density of vegetation cover the ability of laser penetration is variable. Therefore to obtain accurate land surface model the “vegetation effect” was corrected using data collected in the field (mostly the vegetation height) and satellite imagery such as Ikonos (to distinguish different vegetation types of the floodplain and represent them spatially). Model simulation was performed for the spring thaw flood in 2009.

Keywords: floodplain flow, Biebrza valley, model simulation, 2D surface flow model

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Authors: Young-Hyun Seo, Hyunwoo Park, Dong-Kyu Kim, Seung-Young Kho

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The purpose of this study is providing an improved mode choice model considering parameters including age grouping of prime-aged and old age. In this study, 2010 Household Travel Survey data were used and improper samples were removed through the analysis. Chosen alternative, date of birth, mode, origin code, destination code, departure time, and arrival time are considered from Household Travel Survey. By preprocessing data, travel time, travel cost, mode, and ratio of people aged 45 to 55 years, 55 to 65 years and over 65 years were calculated. After the manipulation, the mode choice model was constructed using LIMDEP by maximum likelihood estimation. A significance test was conducted for nine parameters, three age groups for three modes. Then the test was conducted again for the mode choice model with significant parameters, travel cost variable and travel time variable. As a result of the model estimation, as the age increases, the preference for the car decreases and the preference for the bus increases. This study is meaningful in that the individual and households characteristics are applied to the aggregate model.

Keywords: age grouping, aging, mode choice model, multinomial logit model

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Authors: Li Xiaoge, Wang Chaodong

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We introduce the first Chinese Coreference Resolution Model based on BERT (CCRM-BERT) and show that it significantly outperforms all previous work. The key idea is to consider the features of the mention, such as part of speech, width of spans, distance between spans, etc. And the influence of each features on the model is analyzed. The model computes mention embeddings that combine BERT with features. Compared to the existing state-of-the-art span-ranking approach, our model significantly improves accuracy on the Chinese OntoNotes benchmark.

Keywords: BERT, coreference resolution, deep learning, nature language processing

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Authors: Awol Seid Ebrie

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HIV results as an incurable disease, AIDS. After a person is infected with virus, the virus gradually destroys all the infection fighting cells called CD4 cells and makes the individual susceptible to opportunistic infections which cause severe or fatal health problems. Several studies show that the CD4 cells count is the most determinant indicator of the effectiveness of the treatment or progression of the disease. The objective of this paper is to investigate the progression of the disease over time among patient under HAART treatment. Two main approaches of the generalized multilevel ordinal models; namely the proportional odds model and the nonproportional odds model have been applied to the HAART data. Also, the multilevel part of both models includes random intercepts and random coefficients. In general, four models are explored in the analysis and then the models are compared using the deviance information criteria. Of these models, the random coefficients nonproportional odds model is selected as the best model for the HAART data used as it has the smallest DIC value. The selected model shows that the progression of the disease increases as the time under the treatment increases. In addition, it reveals that gender, baseline clinical stage and functional status of the patient have a significant association with the progression of the disease.

Keywords: nonproportional odds model, proportional odds model, random coefficients model, random intercepts model

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Authors: Babak Bashari Rad

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A metamorphic computer virus uses different code transformation techniques to mutate its body in duplicated instances. Characteristics and function of new instances are mostly similar to their parents, but they cannot be easily detected by the majority of antivirus in market, as they depend on string signature-based detection techniques. The purpose of this research is to propose a Hidden Markov Model for classification of metamorphic viruses in executable files. In the proposed solution, portable executable files are inspected to extract the instructions opcodes needed for the examination of code. A Hidden Markov Model trained on portable executable files is employed to classify the metamorphic viruses of the same family. The proposed model is able to generate and recognize common statistical features of mutated code. The model has been evaluated by examining the model on a test data set. The performance of the model has been practically tested and evaluated based on False Positive Rate, Detection Rate and Overall Accuracy. The result showed an acceptable performance with high average of 99.7% Detection Rate.

Keywords: malware classification, computer virus classification, metamorphic virus, metamorphic malware, Hidden Markov Model

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Authors: Umar Adli Amran, Tan Choon Chek, Mohd Shahkhirat Norizan, Then Kek Hoe

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Controlled release fertilizer (CRF) enables a regulated nutrients release for more efficient plant uptake compared to the normal granular fertilizer. It reduces nutrients loss via surface run-off and leaching, hence promotes sustainable agriculture. Although the performance of CRF in providing consistent and timely nutrients supply is well known, its expensive price limits it usage in a large scale plantation. This study is conducted to evaluate the properties and performance of bio-based polyurethane (PU)-coated CRF via laboratory and oil palm main nursery trial. The CRF is produced by coating of a normal commercial compound granular fertilizer from FGV Fertiliser Sdn. Bhd., namely Felda 10 (10.5-8-20-3+0.5B), and designated as CRF FGV10. Based on laboratory evaluation, the CRF FGV10 can sustain nutrients release for more than 6 months. Vegetative growth parameters such as girth size, palm height, third frond length, and the total number of fronds produced were recorded. Besides that, dry biomass of the oil palm seedlings was also determined. From the evaluation, it is proved that at 50% reduction of nutrients application rate and for only two times application (T3), CRF FGV10 enabled the oil palm seedlings to achieve similar vegetative growth with the control samples (T1). It is also proven that only PU-coated CRF FGV10 had allowed the reduction of fertilizer rate and application rounds.

Keywords: nutrition, oil palm seedlings, polyurethane, sustainable manuring, vegetative growth

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Authors: Heung Sun Yoon, Jong Tae Kim

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In this paper, we present an activity diagram model for double-loop control self-adaptive braking system. Since activity diagram helps to improve visibility of self-adaption, we can easily find where improvement is needed on double-loop control. Double-loop control is adopted since the design conditions and actual conditions can be different. The system is reconfigured in runtime by using double-loop control. We simulated to verify and validate our model by using MATLAB. We compared single-loop control model with double-loop control model. Simulation results show that double-loop control provides more consistent brake power control than single-loop control.

Keywords: activity diagram, automotive, braking system, double-loop, self-adaptive, UML, vehicle

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Authors: Ahmad Zaini, F. Muhammad Reza Hadafi, Surya Sumpeno, Muhtadin, Mochamad Hariadi

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The lack of information about museum’s collection reduces the number of visits of museum. Museum’s revitalization is an urgent activity to increase the number of visits. The research's roadmap is building a web-based application that visualizes museum in the virtual form including museum's statue reconstruction in the form of 3D. This paper describes implementation of three-dimensional model reconstruction method based on light-strip pattern on the museum statue using 3D scanner. Noise removal, alignment, meshing and refinement model's processes is implemented to get a better 3D object reconstruction. Model’s texture derives from surface texture mapping between object's images with reconstructed 3D model. Accuracy test of dimension of the model is measured by calculating relative error of virtual model dimension compared against the original object. The result is realistic three-dimensional model textured with relative error around 4.3% to 5.8%.

Keywords: 3D reconstruction, light pattern structure, texture mapping, museum

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Authors: Sara Ataei, Molouk Hadjibabaie, Amirhossein Moslehi, Maryam Taghizadeh-Ghehi, Asieh Ashouri, Elham Amini, Kheirollah Gholami, Alireza Hayatshahi, Mohammad Vaezi, Ardeshir Ghavamzadeh

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Acute kidney injury (AKI) is one of the complications of hematopoietic stem cell transplantation and is associated with increased mortality. N-acetylcysteine (NAC) is a thiol compound with antioxidant and vasodilatory properties that has been investigated for the prevention of AKI in several clinical settings. In the present study, we evaluated the effects of intravenous NAC on the prevention of AKI in allogeneic hematopoietic stem cell transplantation patients. A double-blind randomized placebo-controlled trial was conducted, and 80 patients were recruited to receive 100 mg/kg/day NAC or placebo as intermittent intravenous infusion from day -6 to day +15. AKI was determined on the basis of the Risk-Injury-Failure-Loss-Endstage renal disease and AKI Network criteria as the primary outcome. We assessed urine neutrophil gelatinase-associated lipocalin (uNGAL) on days -6, -3, +3, +9, and +15 as the secondary outcome. Moreover, transplant-related outcomes and NAC adverse reactions were evaluated during the study period. Statistical analysis was performed using appropriate parametric and non-parametric methods including Kaplan–Meier for AKI and generalized estimating equation for uNGAL. At the end of the trial, data from 72 patients were analyzed (NAC: 33 patients and placebo: 39 patients). Participants of each group were not different considering baseline characteristics. AKI was observed in 18% of NAC recipients and 15% of placebo group patients, and the occurrence pattern was not significantly different (p = 0.73). Moreover, no significant difference was observed between groups for uNGAL measures (p = 0.10). Transplant-related outcomes were similar for both groups, and all patients had successful engraftment. Three patients did not tolerate NAC because of abdominal pain, shortness of breath and rash with pruritus and were dropped from the intervention group before transplantation. However, the frequency of adverse reactions was not significantly different between groups. In conclusion, our findings could not show any clinical benefits from high-dose NAC particularly for AKI prevention in allogeneic hematopoietic stem cell transplantation patients.

Keywords: acute kidney injury, N-acetylcysteine, hematopoietic stem cell transplantation, urine neutrophil gelatinase-associated lipocalin, randomized controlled trial

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Authors: Mengke Zhan, Cheng-Gang Xie, Jian-Jun Shu

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A venturi flowmeter is a common device used in multiphase flow rate measurement in the upstream oil and gas industry. Having a robust computational model for multiphase flow in a venturi is desirable for understanding the gas-liquid and fluid-pipe interactions and predicting pressure and phase distributions under various flow conditions. A steady Eulerian-Eulerian framework is used to simulate upward gas-liquid flow in a vertical venturi. The simulation results are compared with experimental measurements of venturi differential pressure and chord-averaged gas holdup in the venturi throat section. The choice of turbulence model is nontrivial in the multiphase flow modelling in a venturi. The performance cross-comparison of the k-ϵ model, Reynolds stress model (RSM) and shear-stress transport (SST) k-ω turbulence model is made in the study. In terms of accuracy and computational cost, the SST k-ω turbulence model is observed to be the most efficient.

Keywords: computational fluid dynamics (CFD), gas-liquid flow, turbulence modelling, venturi

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Authors: Kyeong Hoon Park, Taiji Mazuda

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High damping rubber (HDR) bearings are dissipating devices mainly used in seismic isolation systems and have a great damping performance. Although many studies have been conducted on the dynamic model of HDR bearings, few models can reflect phenomena such as dependency of experienced shear strain on initial history. In order to develop a model that can represent the dependency of experienced shear strain of HDR by Mullins effect, dynamic loading test was conducted using HDR specimen. The reaction of HDR was measured by applying a horizontal vibration using a hybrid actuator under a constant vertical load. Dynamic program analysis was also performed after dynamic loading test. The dynamic model applied in program analysis is a bilinear type double-target model. This model is modified from typical bilinear model. This model can express the nonlinear characteristics related to the initial history of HDR bearings. Based on the dynamic loading test and program analysis results, equivalent stiffness and equivalent damping ratio were calculated to evaluate the mechanical properties of HDR and the feasibility of the bilinear type double-target model was examined.

Keywords: base-isolation, bilinear model, high damping rubber, loading test

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Authors: Anurag Savarnya

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The reliability of the various parts of electric mining shovel has been assessed through the application of Weibull Model. The study was initiated to find reliability of components of electric mining shovel. The paper aims to optimize the reliability of components and increase the life cycle of component. A multilevel decomposition of the electric mining shovel was done and maintenance records were used to evaluate the failure data and appropriate system characterization was done to model the system in terms of reasonable number of components. The approach used develops a mathematical model to assess the reliability of the electric mining shovel components. The model can be used to predict reliability of components of the hydraulic mining shovel and system performance. Reliability is an inherent attribute to a system. When the life-cycle costs of a system are being analyzed, reliability plays an important role as a major driver of these costs and has considerable influence on system performance. It is an iterative process that begins with specification of reliability goals consistent with cost and performance objectives. The data were collected from an Indian open cast coal mine and the reliability of various components of the electric mining shovel has been assessed by following a Weibull Model.

Keywords: reliability, Weibull model, electric mining shovel

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Authors: Ahmed Mateen, Zhu Qingsheng, Faisal Shahzad

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Requirement Engineering (RE) is a part being created for programming structure during the software development lifecycle. Software product line development is a new topic area within the domain of software engineering. It also plays important role in decision making and it is ultimately helpful in rising business environment for productive programming headway. Decisions are central to engineering processes and they hold them together. It is argued that better decisions will lead to better engineering. To achieve better decisions requires that they are understood in detail. In order to address the issues, companies are moving towards Software Product Line Engineering (SPLE) which helps in providing large varieties of products with minimum development effort and cost. This paper proposed a new framework for software product line and compared with other models. The results can help to understand the needs in SPL testing, by identifying points that still require additional investigation. In our future scenario, we will combine this model in a controlled environment with industrial SPL projects which will be the new horizon for SPL process management testing strategies.

Keywords: requirements engineering, software product lines, scoping, process structure, domain specific language

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Authors: Budi Nurani Ruchjana, Atje Setiawan Abdullah, I. Gede Nyoman Mindra Jaya, Eddy Hermawan

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In this paper, we propose the application package to estimate parameters of spatiotemporal model based on the multivariate time series analysis using the R open-source software. We build packages mainly to estimate the parameters of the Generalized Space Time Autoregressive (GSTAR) model. GSTAR is a combination of time series and spatial models that have parameters vary per location. We use the method of Ordinary Least Squares (OLS) and use the Mean Average Percentage Error (MAPE) to fit the model to spatiotemporal real phenomenon. For case study, we use oil production data from volcanic layer at Jatibarang Indonesia or climate data such as rainfall in Indonesia. Software R is very user-friendly and it is making calculation easier, processing the data is accurate and faster. Limitations R script for the estimation of model parameters spatiotemporal GSTAR built is still limited to a stationary time series model. Therefore, the R program under windows can be developed either for theoretical studies and application.

Keywords: GSTAR Model, MAPE, OLS method, oil production, R software

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Authors: Watcharin Sangma, Onsiri Chanmuang, Pitsanu Tongkhow

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A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.

Keywords: forecasting model, steel demand uncertainty, hierarchical Bayesian framework, exponential smoothing method

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Authors: Soroor K. H. Al-Khafaji, Manal Mohammad Abed

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The research aim of this paper is to evaluate the reliability of a complex engineering system and to design a fuzzy model for the reliability estimation. The designed model has been applied on Vegetable Oil Purification System (neutralization system) to help the specialist user based on the concept of FMEA (Failure Mode and Effect Analysis) to estimate the reliability of the repairable system at the vegetable oil industry. The fuzzy model has been used to predict the system reliability for a future time period, depending on a historical database for the two past years. The model can help to specify the system malfunctions and to predict its reliability during a future period in more accurate and reasonable results compared with the results obtained by the traditional method of reliability estimation.

Keywords: fuzzy logic, reliability, repairable systems, FMEA

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Authors: Kuan-Chou Chen

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This paper will demonstrate a simulation model of an information security system by using the systems dynamic approach. The relationships in the system model are designed to be simple and functional and do not necessarily represent any particular information security environments. The purpose of the paper aims to develop a generic system dynamic information security system model with implications on information security research. The interrelated and interdependent relationships of five primary sectors in the system dynamic model will be presented in this paper. The integrated information security systems model will include (1) information security characteristics, (2) users, (3) technology, (4) business functions, and (5) policy and management. Environments, attacks, government and social culture will be defined as the external sector. The interactions within each of these sectors will be depicted by system loop map as well. The proposed system dynamic model will not only provide a conceptual framework for information security analysts and designers but also allow information security managers to remove the incongruity between the management of risk incidents and the management of knowledge and further support information security managers and decision makers the foundation for managerial actions and policy decisions.

Keywords: system thinking, information security systems, security management, simulation

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Authors: Semih Sözer

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One of the most common issues in economic systems is understanding characteristics of economic activities in cities and regions. Although there are critics to economic base models in conceptual and empirical aspects, these models are useful tools to examining the economic structure of a nation, regions or cities. This paper uses one of the methodologies of economic base models namely the location quotients model. Data for this model includes employment numbers of provinces and NUTS II regions in Turkey. Time series of data covers the years of 1990, 2000, 2003, and 2009. Aim of this study is finding which sectors are export-base and which sectors are import-base in provinces and regions. Model results show that big provinces or powerful regions (population, size etc.) mostly have basic sectors in their economic system. However, interesting facts came from different sectors in different provinces and regions in the model results.

Keywords: economic base, location quotients model, regional economics, regional development

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Authors: Albert Gyamfi

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Cocoa plays critical role in the socio-economic development of Ghana. Meanwhile, smallholder farmers most of whom are illiterate dominate the industry. According to the cocoa-based agricultural knowledge and information system (AKIS) model knowledge is created and transferred to the industry between three key actors: cocoa researchers, extension experts, and cocoa farmers. Dwelling on the SECI model, the media richness theory (MRT), and the AKIS model, a conceptual model of web 2.0-based AKIS model (AKIS 2.0) is developed and used to assess the possible effects of social media usage for knowledge creation in the Ghanaian cocoa industry. A mixed method approach with a survey questionnaire was employed, and a second-order multi-group structural equation model (SEM) was used to analyze the data. The study concludes that the use of web 2.0 applications for knowledge creation would lead to sustainable interactions among the key knowledge actors for effective knowledge creation in the cocoa industry in Ghana.

Keywords: agriculture, cocoa, knowledge, media, web 2.0

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Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh

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Developing speed model is a challenging task particularly under mixed traffic condition where the traffic composition plays a significant role in determining vehicular speed. The present research has been conducted to model individual vehicular speed in the context of mixed traffic on an urban arterial. Traffic speed and volume data have been collected from three midblock arterial road sections in New Delhi. Using the field data, a volume based speed prediction model has been developed adopting the methodology of Artificial Neural Network (ANN). The model developed in this work is capable of estimating speed for individual vehicle category. Validation results show a great deal of agreement between the observed speeds and the predicted values by the model developed. Also, it has been observed that the ANN based model performs better compared to other existing models in terms of accuracy. Finally, the sensitivity analysis has been performed utilizing the model in order to examine the effects of traffic volume and its composition on individual speeds.

Keywords: speed model, artificial neural network, arterial, mixed traffic

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Authors: Irbulat Utepbergenov, Lyazzat Issabekova, Shara Toybayeva

Abstract:

This article discusses quality management using the bread baking process as an example. The baking process must be strictly controlled and repeatable. Automation and monitoring of quality management systems can help. After baking bread, quality control of the finished product should be carried out. This may include an evaluation of appearance, weight, texture, and flavor. It is important to continuously work to improve processes and products based on data and feedback from the quality management system. A method and model of automated quality management and an intelligent automated management system based on intelligent technologies are proposed, which allow to automate the processes of QMS implementation and support and improve the validity, efficiency, and effectiveness of management decisions by automating a number of functions of decision makers and staff. This project is supported by the grant of the Ministry of Education and Science of the Republic of Kazakhstan (Zhas Galym project No. AR 13268939 Research and development of digital technologies to ensure consistency of the carriers of normative documents of the quality management system).

Keywords: automated control system, quality management, efficiency evaluation, bakery oven, intelligent system

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Authors: Anderson Ngowa Chembe, John Olukuru

Abstract:

Greenhouse emissions by human activities are known to irreversibly increase global temperatures through the greenhouse effect. This study seeks to propose a mortality model with sensitivity to heat-change effects as one of the underlying parameters in the model. As such, the study sought to establish the relationship between greenhouse emissions and mortality indices in five OECD countries (USA, UK, Japan, Canada & Germany). Upon the establishment of the relationship using correlation analysis, an additional parameter that accounts for the sensitivity of heat-changes to mortality rates was incorporated in the Lee-Carter model. Based on the proposed model, new parameter estimates were calculated using iterative algorithms for optimization. Finally, the goodness of fit for the original Lee-Carter model and the proposed model were compared using deviance comparison. The proposed model provides a better fit to mortality rates especially in USA, UK and Germany where the mortality indices have a strong positive correlation with the level of greenhouse emissions. The results of this study are of particular importance to actuaries, demographers and climate-risk experts who seek to use better mortality-modeling techniques in the wake of heat effects caused by increased greenhouse emissions.

Keywords: climate risk, greenhouse emissions, Lee-Carter model, OECD

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