Search results for: generalised linear modelling

Authors: G. Obregon-Pulido , G. C. Solis-Perales, J. A. Meda-Campaña

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In this paper, we present a sliding mode controller in discrete time. The design of the controller is based on the theory of regulation for nonlinear systems. In the problem of disturbance rejection and/or output tracking, it is known that in discrete time, a controller that uses the zero-order holder only guarantees tracking at the sampling instances but not between instances. It is shown that using the so-called exponential holder, it is possible to guarantee asymptotic zero output tracking error, also between the sampling instant. For stabilizing the problem of close loop system we introduce the sliding mode approach relaxing the requirements of the existence of a linear stabilizing control law.

Keywords: regulation theory, sliding modes, discrete controller, ripple-free tracking

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Authors: Yunus Onur Yildiz, Mesut Kirca

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In this study, mechanical properties of a nanoporous metal coated with a different metallic material are studied through a new atomistic modelling technique and molecular dynamics (MD) simulations. This new atomistic modelling technique is based on the Voronoi tessellation method for the purpose of geometric representation of the ligaments. With the proposed technique, atomistic models of nanoporous metals which have randomly oriented ligaments with non-uniform mass distribution along the ligament axis can be generated by enabling researchers to control both ligament length and diameter. Furthermore, by the utilization of this technique, atomistic models of coated nanoporous materials can be numerically obtained for further mechanical or thermal characterization. In general, this study consists of two stages. At the first stage, we use algorithms developed for generating atomic coordinates of the coated nanoporous material. In this regard, coordinates of randomly distributed points are determined in a controlled way to be employed in the establishment of the Voronoi tessellation, which results in randomly oriented and intersected line segments. Then, line segment representation of the Voronoi tessellation is transformed to atomic structure by a special process. This special process includes generation of non-uniform volumetric core region in which atoms can be generated based on a specific crystal structure. As an extension, this technique can be used for coating of nanoporous structures by creating another volumetric region encapsulating the core region in which atoms for the coating material are generated. The ultimate goal of the study at this stage is to generate atomic coordinates that can be employed in the MD simulations of randomly organized coated nanoporous structures. At the second stage of the study, mechanical behavior of the coated nanoporous models is investigated by examining deformation mechanisms through MD simulations. In this way, the effect of coating on the mechanical behavior of the selected material couple is investigated.

Keywords: atomistic modelling, molecular dynamic, nanoporous metals, voronoi tessellation

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Authors: Sergey Kuznetsov, Yuri Urman

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We present an approach to investigate non-linear dynamical effects occurring in the noncontact superconducting and diamagnetic suspensions, when levitated body has finite size. This approach is based on the calculation of interaction energy between spherical finite size superconducting or diamagnetic body with external magnetic field. Effects of small deviations from spherical shape may be also taken into account by introducing small corrections to the energy. This model allows investigating dynamical effects important for practical applications, such as nonlinear resonances, change of vibration plane, coupling of rotational and translational motions etc. We also show how the geometry of suspension affects various dynamical effects and how an inverse problem may be formulated to enforce or diminish various dynamical effects.

Keywords: levitation, non-linear dynamics, superconducting, diamagnetic stability

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Authors: Ankit Kargeti, Ravikant Shrivastav, Tabish Rasheed

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The electronic structure calculation for the nanoclusters of AsSiTeB/SiAsBTe quaternary semiconductor alloy belonging to the III-V Group elements was performed. Motivation for this research work was to look for accurate electronic and geometric data of small nanoclusters of AsSiTeB/SiAsBTe in the gaseous form. The two clusters, one in the linear form and the other in the bent form, were studied under the framework of Density Functional Theory (DFT) using the B3LYP functional and LANL2DZ basis set with the software packaged Gaussian 16. We have discussed the Optimized Energy, Frontier Orbital Energy Gap in terms of HOMO-LUMO, Dipole Moment, Ionization Potential, Electron Affinity, Binding Energy, Embedding Energy, Density of States (DoS) spectrum for both structures. The important findings of the predicted nanostructures are that these structures have wide band gap energy, where linear structure has band gap energy (Eg) value is 2.375 eV and bent structure (Eg) value is 2.778 eV. Therefore, these structures can be utilized as wide band gap semiconductors. These structures have high electron affinity value of 4.259 eV for the linear structure and electron affinity value of 3.387 eV for the bent structure form. It shows that electron acceptor capability is high for both forms. The widely known application of these compounds is in the light emitting diodes due to their wide band gap nature.

Keywords: density functional theory, DFT, density functional theory, nanostructures, HOMO-LUMO, density of states

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Authors: Pavel Shcherban, Vlad Golovanov

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Nowadays, the depletion of hydrocarbon deposits on the land of the Kaliningrad region leads to active geological exploration and development of oil and natural gas reserves in the southeastern part of the Baltic Sea. LLC 'Lukoil-Kaliningradmorneft' implements a comprehensive program for the development of the region's shelf in 2014-2023. Due to heterogeneity of reservoir rocks in various open fields, as well as with ambiguous conclusions on the contours of deposits, additional geological prospecting and refinement of the recoverable oil reserves are carried out. The key element is use of an effective technique of computer stock modeling at the first stage of processing of the received data. The following step uses information for the cluster analysis, which makes it possible to optimize the field development approaches. The article analyzes the effectiveness of various methods for reserves' calculation and computer modelling methods of the offshore hydrocarbon fields. Cluster analysis allows to measure influence of the obtained data on the development of a technical and economic model for mining deposits. The relationship between the accuracy of the calculation of recoverable reserves and the need of modernization of existing mining infrastructure, as well as the optimization of the scheme of opening and development of oil deposits, is observed.

Keywords: cluster analysis, computer modelling of deposits, correction of the feasibility study, offshore hydrocarbon fields

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Authors: Saeed Javaherzadeh, Babak Dindar Safa

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Structure, given its ductility, can depreciate significant amount of seismic energy in the form of hysteresis behavior; the amount of energy depreciation depends on the structure ductility rate. So in seismic guidelines such as ASCE7-10 code, to reduce the number of design forces and using the seismic energy dissipation capacity of structure, when entering non-linear behavior range of the materials, the response modification factor is used. Various parameters such as ductility modification factor, overstrength factor and reliability factor, are effective in determining the value of this factor. Also, gradually, energy dissipation systems, especially added dampers, have become an inseparable part of the seismic design. In this paper, in addition to reviewing of previous studies, using the response modification factor caused by using more added viscoelastic dampers, a new design method has introduced for steel moment-frame with added dampers installed. To do this, in addition to using bilinear behavior models and quick ways such as using the equivalent lateral force method and capacity spectrum method for the proposed design methodology, the results has been controlled with non-linear time history analysis for a number of structural. The analysis is done by Opensees Software.

Keywords: added viscoelastic damper, design base shear, response modification factor, non-linear time history

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Authors: Congping Lin

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Intracellular transport in fungi has a number of important roles in, e.g., filamentous fungal growth and cellular metabolism. Two basic mechanisms for intracellular transport are motor-driven trafficking along microtubules (MTs) and diffusion. Mathematical modelling has been actively developed to understand such intracellular transport and provide unique insight into cellular complexity. Based on live-cell imaging data in Ustilago hyphal cells, probabilistic models have been developed to study mechanism underlying spatial organization of molecular motors and organelles. In particular, anther mechanism - stochastic motility of dynein motors along MTs has been found to contribute to half of its accumulation at hyphal tip in order to support early endosome (EE) recycling. The EE trafficking not only facilitates the directed motion of peroxisomes but also enhances their diffusive motion. Considering the importance of spatial organization of early endosomes in supporting peroxisome movement, computational and experimental approaches have been combined to a whole-cell level. Results from this interdisciplinary study promise insights into requirements for other membrane trafficking systems (e.g., in neurons), but also may inform future 'synthetic biology' studies.

Keywords: intracellular transport, stochastic process, molecular motors, spatial organization

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Authors: Olivia A. Wilson, Hannah E. Power, Murray Kendall

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Sydney Harbour is an iconic location with a dense population and low-lying development. On the east coast of Australia, facing the Pacific Ocean, it is exposed to several tsunamigenic trenches. This paper presents a component of the most detailed assessment of the potential for earthquake-generated tsunami impact on Sydney Harbour to date. Models in this study use dynamic tides to account for tide-tsunami interaction. Sydney Harbour’s tidal range is 1.5 m, and the spring tides from January 2015 that are used in the modelling for this study are close to the full tidal range. The tsunami wave trains modelled include hypothetical tsunami generated from earthquakes of magnitude 7.5, 8.0, 8.5, and 9.0 M_W from the Puysegur and New Hebrides trenches as well as representations of the historical 1960 Chilean and 2011 Tohoku events. All wave trains are modelled for the peak wave to coincide with both a low tide and a high tide. A single wave train, representing a 9.0 M_W earthquake at the Puysegur trench, is modelled for peak waves to coincide with every hour across a 12-hour tidal phase. Using the hydrodynamic model ANUGA, results are compared according to the impact parameters of inundation area, depth variation and current speeds. Results show that both maximum inundation area and depth variation are tide dependent. Maximum inundation area increases when coincident with a higher tide, however, hazardous inundation is only observed for the larger waves modelled: NH90high and P90high. The maximum and minimum depths are deeper on higher tides and shallower on lower tides. The difference between maximum and minimum depths varies across different tidal phases although the differences are slight. Maximum current speeds are shown to be a significant hazard for Sydney Harbour; however, they do not show consistent patterns according to tide-tsunami phasing. The maximum current speed hazard is shown to be greater in specific locations such as Spit Bridge, a narrow channel with extensive marine infrastructure. The results presented for Sydney Harbour are novel, and the conclusions are consistent with previous modelling efforts in the greater area. It is shown that tide must be a consideration for both tsunami modelling and emergency management planning. Modelling with peak tsunami waves coinciding with a high tide would be a conservative approach; however, it must be considered that maximum current speeds may be higher on other tides.

Keywords: emergency management, sydney, tide-tsunami interaction, tsunami impact

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Authors: Azam Mohammadbagheri, Bahram Fathi

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DEA has become a very popular method of performance measure, but it still suffers from some shortcomings. One of these shortcomings is the issue of having multiple optimal solutions to weights for efficient DMUs. The cross efficiency evaluation as an extension of DEA is proposed to avoid this problem. Lam (2010) is also proposed a mixed-integer linear programming formulation based on linear discriminate analysis and super efficiency method (MILP model) to avoid having multiple optimal solutions to weights. In this study, we modified MILP model to determine more suitable weight sets and also evaluate the energy efficiency of MENA countries as an application of the proposed model.

Keywords: data envelopment analysis, discriminate analysis, cross efficiency, MILP model

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Authors: Eric Dede, Marcus Tindall, John W. Cherrie, Steve Hankin, Christopher Collins

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Current exposure models used in contaminated land risk assessment are highly conservative. Use of these models may lead to over-estimation of actual exposures, possibly resulting in negative financial implications due to un-necessary remediation. Thus, we are carrying out a study seeking to improve our understanding of human exposure to selected toxic elements in soil: arsenic (As), cadmium (Cd), chromium (Cr), nickel (Ni), and lead (Pb) resulting from allotment land-use. The study employs biomonitoring and physiologically-based pharmacokinetic (PBPK) modelling to quantify human exposure to these elements. We recruited 37 allotment users (adults > 18 years old) in Scotland, UK, to participate in the study. Concentrations of the elements (and their bioaccessibility) were measured in allotment samples (soil and allotment produce). Amount of produce consumed by the participants and participants’ biological samples (urine and blood) were collected for up to 12 consecutive months. Ethical approval was granted by the University of Reading Research Ethics Committee. PBPK models (coded in MATLAB) were used to estimate the distribution and accumulation of the elements in key body compartments, thus indicating the internal body burden. Simulating low element intake (based on estimated ‘doses’ from produce consumption records), predictive models suggested that detection of these elements in urine and blood was possible within a given period of time following exposure. This information was used in planning biomonitoring, and is currently being used in the interpretation of test results from biological samples. Evaluation of the models is being carried out using biomonitoring data, by comparing model predicted concentrations and measured biomarker concentrations. The PBPK models will be used to generate bioavailability values, which could be incorporated in contaminated land exposure models. Thus, the findings from this study will promote a more sustainable approach to contaminated land management.

Keywords: biomonitoring, exposure, PBPK modelling, toxic elements

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Authors: Mohammed Seyam, Faridah Othman, Ahmed El-Shafie

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The early warning of high stream flow events (HSF) and floods is an important aspect in the management of surface water and rivers systems. This process can be performed using either process-based models or data driven-based models such as artificial intelligence (AI) techniques. The main goal of this study is to develop efficient AI-based model for predicting the real-time hourly stream flow (Q) and apply it as early warning tool of HSF and floods in the downstream area of the Selangor River basin, taken here as a paradigm of humid tropical rivers in Southeast Asia. The performance of AI-based models has been improved through the integration of the lag time (Lt) estimation in the modelling process. A total of 8753 patterns of Q, water level, and rainfall hourly records representing one-year period (2011) were utilized in the modelling process. Six hydrological scenarios have been arranged through hypothetical cases of input variables to investigate how the changes in RF intensity in upstream stations can lead formation of floods. The initial SF was changed for each scenario in order to include wide range of hydrological situations in this study. The performance evaluation of the developed AI-based model shows that high correlation coefficient (R) between the observed and predicted Q is achieved. The AI-based model has been successfully employed in early warning throughout the advance detection of the hydrological conditions that could lead to formations of floods and HSF, where represented by three levels of severity (i.e., alert, warning, and danger). Based on the results of the scenarios, reaching the danger level in the downstream area required high RF intensity in at least two upstream areas. According to results of applications, it can be concluded that AI-based models are beneficial tools to the local authorities for flood control and awareness.

Keywords: floods, stream flow, hydrological modelling, hydrology, artificial intelligence

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Authors: Majid Khalili, Hamed Tayebi

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This paper considers a stochastic flexible job-shop scheduling (SFJSS) problem in the presence of production disruptions, and reactive scheduling is implemented in order to find the optimal solution under uncertainty. In this problem, there are two main disruptions including machine failure which influences operation time, and modification or cancellation of the order delivery date during production. In order to decrease the negative effects of these difficulties, two derived strategies from reactive scheduling are used; the first one is relevant to being able to allocate multiple machine to each job, and the other one is related to being able to select the best alternative process from other job while some disruptions would be created in the processes of a job. For this purpose, a Mixed Integer Linear Programming model is proposed.

Keywords: flexible job-shop scheduling, reactive scheduling, stochastic environment, mixed integer linear programming

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Authors: Jianqin Qu

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This paper proposes a rigid point set matching algorithm in arbitrary dimensions based on the idea of symmetric covariant function. A group of functions of the points in the set are formulated using rigid invariants. Each of these functions computes a pair of correspondence from the given point set. Then the computed correspondences are used to recover the unknown rigid transform parameters. Each computed point can be geometrically interpreted as the weighted mean center of the point set. The algorithm is compact, fast, and dimension free without any optimization process. It either computes the desired transform for noiseless data in linear time, or fails quickly in exceptional cases. Experimental results for synthetic data and 2D/3D real data are provided, which demonstrate potential applications of the algorithm to a wide range of problems.

Keywords: covariant point, point matching, dimension free, rigid registration

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Authors: Tofigh Hamidavi, Sepehr Abrishami, Pasquale Ponterosso, David Begg

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Structural design and analysis is an important and time-consuming process, particularly at the conceptual design stage. Decisions made at this stage can have an enormous effect on the entire project, as it becomes ever costlier and more difficult to alter the choices made early on in the construction process. Hence, optimisation of the early stages of structural design can provide important efficiencies in terms of cost and time. This paper suggests a structural design optimisation (SDO) framework in which Genetic Algorithms (GAs) may be used to semi-automate the production and optimisation of early structural design alternatives. This framework has the potential to leverage conceptual structural design innovation in Architecture, Engineering and Construction (AEC) projects. Moreover, this framework improves the collaboration between the architectural stage and the structural stage. It will be shown that this SDO framework can make this achievable by generating the structural model based on the extracted data from the architectural model. At the moment, the proposed SDO framework is in the process of validation, involving the distribution of an online questionnaire among structural engineers in the UK.

Keywords: building information, modelling, BIM, genetic algorithm, GA, architecture-engineering-construction, AEC, optimisation, structure, design, population, generation, selection, mutation, crossover, offspring

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Authors: Meriem Mossaddek, El Mehdi Laadissi, El Mehdi Loualid, Chouaib Ennawaoui, Sohaib Bouzaid, Abdelowahed Hajjaji

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An electrochemical system is a subset of mechatronic systems that includes a wide variety of batteries and nickel-cadmium, lead-acid batteries, and lithium-ion. Those structures have several non-linear behaviors and uncertainties in their running range. This paper studies an effective technique for modeling Lithium-Ion (Li-Ion) batteries using a Nonlinear Auto-Regressive model with exogenous input (NARX). The Artificial Neural Network (ANN) is trained to employ the data collected from the battery testing process. The proposed model is implemented on a Li-Ion battery cell. Simulation of this model in MATLAB shows good accuracy of the proposed model.

Keywords: lithium-ion battery, neural network, energy storage, battery model, nonlinear models

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Authors: Bojana Horvat, Barbara Karleusa, Goran Volf, Nevenka Ozanic, Ivica Kisic

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Forest fire is a major threat in many regions in Croatia, especially in coastal areas. Although they are often caused by natural processes, the most common cause is the human factor, intentional or unintentional. Forest fires drastically transform landscapes and influence natural processes. The main goal of the presented research is to analyse and quantify the impact of the forest fire on hydrological processes and propose the model that best describes changes in hydrological patterns in the analysed catchments. Keeping in mind the spatial component of the processes, geospatial analysis is performed to gain better insight into the spatial variability of the hydrological response to disastrous events. In that respect, two catchments that experienced severe forest fire were delineated, and various hydrological and meteorological data were collected both attribute and spatial. The major drawback is certainly the lack of hydrological data, common in small torrential karstic streams; hence modelling results should be validated with the data collected in the catchment that has similar characteristics and established hydrological monitoring. The event chosen for the modelling is the forest fire that occurred in July 2019 and burned nearly 10% of the analysed area. Surface (land use/land cover) conditions before and after the event were derived from the two Sentinel-2 images. The mapping of the burnt area is based on a comparison of the Normalized Burn Index (NBR) computed from both images. To estimate and compare hydrological behaviour before and after the event, curve number (CN) values are assigned to the land use/land cover classes derived from the satellite images. Hydrological modelling resulted in surface runoff generation and hence prediction of hydrological responses in the catchments to a forest fire event. The research was supported by the Croatian Science Foundation through the project 'Influence of Open Fires on Water and Soil Quality' (IP-2018-01-1645).

Keywords: Croatia, forest fire, geospatial analysis, hydrological response

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Authors: Omar Qaftan

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Earthquakes can cause tremendous loss of human life and can result in severe damage to a several of civil engineering structures especially the tall buildings. The response of a multistory structure subjected to earthquake loading is a complex task, and it requires to be studied by physical and numerical modelling. For many circumstances, the scale models on shaking table may be a more economical option than the similar full-scale tests. A shaking table apparatus is a powerful tool that offers a possibility of understanding the actual behaviour of structural systems under earthquake loading. It is required to use a set of scaling relations to predict the behaviour of the full-scale structure. Selecting the scale factors is the most important steps in the simulation of the prototype into the scaled model. In this paper, the principles of scaling modelling procedure are explained in details, and the simulation of scaled multi-storey concrete structure for dynamic studies is investigated. A procedure for a complete dynamic simulation analysis is investigated experimentally and numerically with a scale factor of 1/50. The frequency domain accounting and lateral displacement for both numerical and experimental scaled models are determined. The procedure allows accounting for the actual dynamic behave of actual size porotype structure and scaled model. The procedure is adapted to determine the effects of the tall multi-storey structure on a raft foundation. Four generated accelerograms were used as inputs for the time history motions which are in complying with EC8. The output results of experimental works expressed regarding displacements and accelerations are compared with those obtained from a conventional fixed-base numerical model. Four-time history was applied in both experimental and numerical models, and they concluded that the experimental has an acceptable output accuracy in compare with the numerical model output. Therefore this modelling methodology is valid and qualified for different shaking table experiments tests.

Keywords: structure, raft, soil, interaction

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Authors: Fajana Sola Isaac

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In the last two decades, we have witnessed an increased interest in exchange rate pass-through (ERPT) in developing economies and emerging markets. This is perhaps due to the acknowledged significance of the pattern of exchange rate pass-through as a key instrument in monetary policy design, principally in retort to a shock in exchange rate in literature. This paper analyzed Exchange Rate Pass-Through by A Model of Oil Prices and Asymmetric Exchange Rate Fluctuations in Selected African Countries. The study adopted A Non-Linear Autoregressive Distributed Lag approach using yearly data on Algeria, Burundi, Nigeria and South Africa from 1986 to 2022. The paper found asymmetry in exchange rate pass-through in net oil-importing and net oil-exporting countries in the short run during the period under review. An ERPT exhibited a complete pass-through in the short run in the case of net oil-importing countries but an incomplete pass-through in the case of the net oil-exporting countries that were examined. An extended result revealed a significant impact of oil price shock on exchange rate pass-through to domestic price in the long run only for net oil importing countries. The Wald restriction test also confirms the evidence of asymmetric with the role of oil price acting as an accelerator to exchange rate pass-through to domestic price in the countries examined. The study found the outcome to be very useful for gaining expansive knowledge on the external shock impact on ERPT and could be of critical value for national monetary policy decisions on inflation targeting, especially for countries examined and other developing net oil importers and exporters.

Keywords: pass through, exchange rate, ARDL, monetary policy

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Authors: Victoria Goodall, Paul Fatti, Norman Owen-Smith

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Hidden Markov Models have become popular for the analysis of animal tracking data. These models are being used to model the movements of a variety of species in many areas around the world. A common assumption of the model is that the observations need to have regular time steps. In many ecological studies, this will not be the case. The objective of the research is to modify the movement model to allow for irregularly spaced locations and investigate the effect on the inferences which can be made about the latent states. A modification of the likelihood function to allow for these irregular spaced locations is investigated, without using interpolation or averaging the movement rate. The suitability of the modification is investigated using GPS tracking data for lion (Panthera leo) in South Africa, with many observations obtained during the night, and few observations during the day. Many nocturnal predator tracking studies are set up in this way, to obtain many locations at night when the animal is most active and is difficult to observe. Few observations are obtained during the day, when the animal is expected to rest and is potentially easier to observe. Modifying the likelihood function allows the popular Hidden Markov Model framework to be used to model these irregular spaced locations, making use of all the observed data.

Keywords: hidden Markov Models, irregular observations, animal movement modelling, nocturnal predator

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Authors: Jiun-Horng Tsai, Shi-Jie, Nieh

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Fine particulate matter (PM₂.₅) has become an important issue all over the world over the last decade. Annual mean PM₂.₅ concentration has been over the ambient air quality standard of PM₂.₅ (annual average concentration as 15μg/m³) which adapted by Taiwan Environmental Protection Administration (TEPA). TEPA, therefore, has developed a number of air pollution control measures to improve the ambient concentration by reducing the emissions of primary fine particulate matter and the precursors of secondary PM₂.₅. This study investigated the potential improvement of ambient PM₂.₅ concentration by the TEPA program and the other scenario for further emission reduction on various sources. Four scenarios had been evaluated in this study, including a basic case and three reduction scenarios (A to C). The ambient PM₂.₅ concentration was evaluated by Community Multi-scale Air Quality modelling system (CMAQ) ver. 4.7.1 along with the Weather Research and Forecasting Model (WRF) ver. 3.4.1. The grid resolutions in the modelling work are 81 km × 81 km for domain 1 (covers East Asia), 27 km × 27 km for domain 2 (covers Southeast China and Taiwan), and 9 km × 9 km for domain 3 (covers Taiwan). The result of PM₂.₅ concentration simulation in different regions of Taiwan shows that the annual average concentration of basic case is 24.9 μg/m³, and are 22.6, 18.8, and 11.3 μg/m³, respectively, for scenarios A to C. The annual average concentration of PM₂.₅ would be reduced by 9-55 % for those control scenarios. The result of scenario C (the emissions of precursors reduce to allowance levels) could improve effectively the airborne PM₂.₅ concentration to attain the air quality standard. According to the results of unit precursor reduction contribution, the allowance emissions of PM₂.₅, SOₓ, and NOₓ are 16.8, 39, and 62 thousand tons per year, respectively. In the Kao-Ping air basin, the priority for reducing precursor emissions is PM₂.₅ > NOₓ > SOₓ, whereas the priority for reducing precursor emissions is PM₂.₅ > SOₓ > NOₓ in others area. The result indicates that the target pollutants that need to be reduced in different air basin are different, and the control measures need to be adapted to local conditions.

Keywords: airborne PM₂.₅, community multi-scale air quality modelling system, control measures, weather research and forecasting model

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Authors: Wassana Naiyapo, Atichat Sangtong

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The processes in software development by Object Oriented methodology have many stages those take time and high cost. The inconceivable error in system analysis process will affect to the design and the implementation process. The unexpected output causes the reason why we need to revise the previous process. The more rollback of each process takes more expense and delayed time. Therefore, the good test process from the early phase, the implemented software is efficient, reliable and also meet the user’s requirement. Unified Modelling Language (UML) is the tool which uses symbols to describe the work process in Object Oriented Analysis (OOA). This paper presents the approach for automatically generated UML use case diagram and test cases. UML use case diagram is generated from the event table and test cases are generated from use case specifications and Graphic User Interfaces (GUI). Test cases are derived from the Classification Tree Method (CTM) that classify data to a node present in the hierarchy structure. Moreover, this paper refers to the program that generates use case diagram and test cases. As the result, it can reduce work time and increase efficiency work.

Keywords: classification tree method, test case, UML use case diagram, use case specification

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Authors: Mohammed Salahat, Steve Wade

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This paper presents and compares the SSDDD “Systematic Soft Domain Driven Design Framework” to DDD “Domain Driven Design Framework” as a soft system approach of information systems development. The framework use SSM as a guiding methodology within which we have embedded a sequence of design tasks based on the UML leading to the implementation of a software system using the Naked Objects framework. This framework has been used in action research projects that have involved the investigation and modelling of business processes using object-oriented domain models and the implementation of software systems based on those domain models. Within this framework, Soft Systems Methodology (SSM) is used as a guiding methodology to explore the problem situation and to develop the domain model using UML for the given business domain. The framework is proposed and evaluated in our previous works, a comparison between SSDDD and DDD is presented in this paper, to show how SSDDD improved DDD as an approach to modelling and implementing business domain perspectives for Information Systems Development. The comparison process, the results, and the improvements are presented in the following sections of this paper.

Keywords: domain-driven design, soft domain-driven design, naked objects, soft language

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Authors: Adel Mohsen

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A direct method based on the good Broyden's updates for evaluating the inverse of a nonsingular square matrix of full rank and solving related system of linear algebraic equations is studied. For a matrix A of order n whose LU-decomposition is A = LU, the multiplication count is O (n3). This includes the evaluation of the LU-decompositions of the inverse, the lower triangular decomposition of A as well as a “reduced matrix inverse”. If an explicit value of the inverse is not needed the order reduces to O (n3/2) to compute to compute inv(U) and the reduced inverse. For a symmetric matrix only O (n3/3) operations are required to compute inv(L) and the reduced inverse. An example is presented to demonstrate the capability of using the reduced matrix inverse in treating ill-conditioned systems. Besides the simplicity of Broyden's update, the method provides a mean to exploit the possible sparsity in the matrix and to derive a suitable preconditioner.

Keywords: Broyden's updates, matrix inverse, inverse factorization, solution of linear algebraic equations, ill-conditioned matrices, preconditioning

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Authors: Grienggrai Rajchakit

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This paper is concerned with the exponential stability of switched linear systems with interval time-varying delays. The time delay is any continuous function belonging to a given interval, in which the lower bound of delay is not restricted to zero. By constructing a suitable augmented Lyapunov-Krasovskii functional combined with Leibniz-Newton's formula, a switching rule for the exponential stability of switched linear systems with interval time-varying delays and new delay-dependent sufficient conditions for the exponential stability of the systems are first established in terms of LMIs. Finally, some examples are exploited to illustrate the effectiveness of the proposed schemes.

Keywords: exponential stability, hybrid systems, time-varying delays, lyapunov-krasovskii functional, leibniz-newton's formula

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Authors: Raziyeh Shamsi

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In this paper, we present a multiple objective linear programming (MOLP) problem in full fuzzy case and find Data Envelopment Analysis(DEA) targets. In the presented model, we are seeking the least inputs and the most outputs in the production possibility set (PPS) with the variable return to scale (VRS) assumption, so that the efficiency projection is obtained for all decision making units (DMUs). Then, we provide an algorithm for finding DEA targets interactively in the full fuzzy case, which solves the full fuzzy problem without defuzzification. Owing to the use of interactive methods, the targets obtained by our algorithm are more applicable, more realistic, and they are according to the wish of the decision maker. Finally, an application of the algorithm in 21 educational institutions is provided.

Keywords: DEA, MOLP, full fuzzy, target

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Authors: Nor Mazlin Zahari, Lian Gan, Xuerui Mao

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The power production in wind farms and the mechanical loads on the turbines are strongly impacted by the wake of the wind turbine. Thus, there is a need for understanding and modelling the turbine wake dynamic in the wind farm and the layout optimization. Having a good wake model is important in predicting plant performance and understanding fatigue loads. In this paper, the Dynamic Mode Decomposition (DMD) was applied to the simulation data generated by a Direct Numerical Simulation (DNS) of flow around a turbine, perturbed by upstream inflow noise. This technique is useful in analyzing the wake flow, to predict its future states and to reflect flow dynamics associated with the coherent structures behind wind turbine wake flow. DMD was employed to describe the dynamic of the flow around turbine from the DNS data. Since the DNS data comes with the unstructured meshes and non-uniform grid, the interpolation of each occurring within each element in the data to obtain an evenly spaced mesh was performed before the DMD was applied. DMD analyses were able to tell us characteristics of the travelling waves behind the turbine, e.g. the dominant helical flow structures and the corresponding frequencies. As the result, the dominant frequency will be detected, and the associated spatial structure will be identified. The dynamic mode which represented the coherent structure will be presented.

Keywords: coherent structure, Direct Numerical Simulation (DNS), dominant frequency, Dynamic Mode Decomposition (DMD)

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Authors: Wael Elsaady, S. Olutunde Oyadiji, Adel Nasser

Abstract:

The non-linear flow characteristics of magnetorheological (MR) fluids in MR dampers are studied via a coupled numerical approach that incorporates a two-phase flow model. The approach couples the Finite Element (FE) modelling of the damper magnetic circuit, with the Computational Fluid Dynamics (CFD) analysis of the flow field in the damper. The two-phase flow CFD model accounts for the effect of fluid compressibility due to the presence of liquid and gas in the closed domain of the damper. The dynamic mesh model included in ANSYS/Fluent CFD solver is used to simulate the movement of the MR damper piston in order to perform the fluid excitation. The two-phase flow analysis is studied by both Volume-Of-Fluid (VOF) model and mixture model that are included in ANSYS/Fluent. The CFD models show that the hysteretic behaviour of MR dampers is due to the effect of fluid compressibility. The flow field shows the distributions of pressure, velocity, and viscosity contours. In particular, it shows the high non-Newtonian viscosity in the affected fluid regions by the magnetic field and the low Newtonian viscosity elsewhere. Moreover, the dependence of gas volume fraction on the liquid pressure inside the damper is predicted by the mixture model. The presented approach targets a better understanding of the complicated flow characteristics of viscoplastic fluids that could be applied in different applications.

Keywords: viscoplastic fluid, magnetic FE analysis, computational fluid dynamics, two-phase flow, dynamic mesh, user-defined functions

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Authors: Krishang Surapaneni

Abstract:

The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

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Authors: Nikola Tomasevic, Marko Batic, Sanja Vranes

Abstract:

Emerging Semantic Web technologies can be seen as the next step in evolution of the intelligent facility management systems. Particularly, this considers increased usage of open source and/or standardized concepts for data classification and semantic interpretation. To deliver such facility management systems, providing the comprehensive integration and interoperability platform in from of the facility data model is a prerequisite. In this paper, one of the possible modelling approaches to provide such integrative facility data model which was based on the ontology modelling concept was presented. Complete ontology development process, starting from the input data acquisition, ontology concepts definition and finally ontology concepts population, was described. At the beginning, the core facility ontology was developed representing the generic facility infrastructure comprised of the common facility concepts relevant from the facility management perspective. To develop the data model of a specific facility infrastructure, first extension and then population of the core facility ontology was performed. For the development of the full-blown facility data models, Malpensa and Fiumicino airports in Italy, two major European air-traffic hubs, were chosen as a test-bed platform. Furthermore, the way how these ontology models supported the integration and interoperability of the overall airport energy management system was analyzed as well.

Keywords: airport ontology, energy management, facility data model, ontology modeling

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Authors: Odd Ivar Haugen

Abstract:

Society increasingly relies on complex systems whose behaviour is determined, not by the properties of each part, but by the interaction between them. The behaviour of such systems is emergent. Modelling emergent system behaviour requires a systems approach that incorporates the necessary concepts that are capable of determining such behaviour. The CESM metamodel is a model of system models. A set of system models needs to address the elements of CESM at different levels of abstraction to be able to model the behaviour of a complex system. Modern ships contain numerous sophisticated equipment, often accompanied by a local safety system to protect its integrity. These control systems are then connected into a larger integrated system in order to achieve the ship’s objective or mission. The integrated system becomes what is commonly known as a system of systems, which can be termed a complex system. Examples of such complex systems are the dynamic positioning system and the power management system. Three ship accidents are provided as examples of how system complexity may contribute to accidents. Then, the three accidents are discussed in terms of how the Multi-Level/Multi-Model Safety Analysis might catch scenarios such as those leading to the accidents described.

Keywords: emergent properties, CESM metamodel, multi-level/multi-model safety analysis, safety, system complexity, system models, systems thinking

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