Search results for: Dynamic Model

Authors: Václav Sadílek, Miroslav Vořechovský

Abstract:

The paper deals with the classical fiber bundle model of equal load sharing, sometimes referred to as the Daniels’ bundle or the democratic bundle. Daniels formulated a multidimensional integral and also a recursive formula for evaluation of the strength cumulative distribution function. This paper describes three algorithms for evaluation of the recursive formula and also their implementations with source codes in the Python high-level programming language. A comparison of the algorithms are provided with respect to execution time. Analysis of orders of magnitudes of addends in the recursion is also provided.

Keywords: Daniels bundle model, equal load sharing, Python, mpmath.

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Authors: Borna Jafarpour, Azadeh Nematzadeh, Vahid Kazempour, Babak Sadeghian

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Cellular automata have been used for design of cryptosystems. Recently some secret sharing schemes based on linear memory cellular automata have been introduced which are used for both text and image. In this paper, we illustrate that these secret sharing schemes are vulnerable to dishonest participants- collusion. We propose a cheating model for the secret sharing schemes based on linear memory cellular automata. For this purpose we present a novel uniform model for representation of all secret sharing schemes based on cellular automata. Participants can cheat by means of sending bogus shares or bogus transition rules. Cheaters can cooperate to corrupt a shared secret and compute a cheating value added to it. Honest participants are not aware of cheating and suppose the incorrect secret as the valid one. We prove that cheaters can recover valid secret by removing the cheating value form the corrupted secret. We provide methods of calculating the cheating value.

Keywords: Cellular automata, cheating model, secret sharing, threshold scheme.

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Authors: U. Chattaraj, K. Dhusiya, M. Raviteja

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Perception reaction time of drivers is an outcome of human thought process, which is vague and approximate in nature and also varies from driver to driver. So, in this study a fuzzy logic based model for prediction of the same has been presented, which seems suitable. The control factors, like, age, experience, intensity of driving of the driver, speed of the vehicle and distance of stimulus have been considered as premise variables in the model, in which the perception reaction time is the consequence variable. Results show that the model is able to explain the impacts of the control factors on perception reaction time properly.

Keywords: Driver, fuzzy logic, perception reaction time, premise variable.

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Authors: V. Vidučić, T. Brešan Ančić, M. Tomelić Ćurlin

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Prior to quantifying the variables of the information model for using school terminology in Croatia's region of Dalmatia from 1884 to 2014, the most relevant model variables had to be determined: historical circumstances, standard of living, education system, linguistic situation, and media. The research findings show that there was no significant transfer of the 1884 school terms into 1949 usage; likewise, the 1949 school terms were not widely used in 2014. On the other hand, the research revealed that the meaning of school terms changed over the decades. The quantification of the variables will serve as the groundwork for creating an information model for using school terminology in Dalmatia from 1884 to 2014 and for defining direct growth rates in further research.

Keywords: Education system, historical circumstances, linguistic situation, media, school terminology, standard of living.

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Authors: Jun-ya Nagase, Toshiyuki Satoh, Norihiko Saga, Koichi Suzumori

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In recent years, Japanese society has been aging, engendering a labor shortage of young workers. Robots are therefore expected to perform tasks such as rehabilitation, nursing elderly people, and day-to-day work support for elderly people. The pneumatic balloon actuator is a rubber artificial muscle developed for use in a robot hand in such environments. This actuator has a long stroke and a high power-to-weight ratio compared with the present pneumatic artificial muscle. Moreover, the dynamic characteristics of this actuator resemble those of human muscle. This study evaluated characteristics of force control of balloon actuator using a predictive functional control (PFC) system with disturbance observer. The predictive functional control is a model-based predictive control (MPC) scheme that predicts the future outputs of the actual plants over the prediction horizon and computes the control effort over the control horizon at every sampling instance. For this study, a 1-link finger system using a pneumatic balloon actuator is developed. Then experiments of PFC control with disturbance observer are performed. These experiments demonstrate the feasibility of its control of a pneumatic balloon actuator for a robot hand.

Keywords: Disturbance observer, Pneumatic balloon, Predictive functional control, Rubber artificial muscle.

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Authors: C. Nutphuang, S. Chirarattananon, V.D. Hien

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In research on natural ventilation, and passive cooling with forced convection, is essential to know how heat flows in a solid object and the pattern of temperature distribution on their surfaces, and eventually how air flows through and convects heat from the surfaces of steel under roof. This paper presents some results from running the computational fluid dynamic program (CFD) by comparison between natural ventilation and forced convection within roof attic that is received directly from solar radiation. The CFD program for modeling air flow inside roof attic has been modified to allow as two cases. First case, the analysis under natural ventilation, is closed area in roof attic and second case, the analysis under forced convection, is opened area in roof attic. These extend of all cases to available predictions of variations such as temperature, pressure, and mass flow rate distributions in each case within roof attic. The comparison shows that this CFD program is an effective model for predicting air flow of temperature and heat transfer coefficient distribution within roof attic. The result shows that forced convection can help to reduce heat transfer through roof attic and an around area of steel core has temperature inner zone lower than natural ventilation type. The different temperature on the steel core of roof attic of two cases was 10-15 oK.

Keywords: CFD program, natural ventilation, forcedconvection, heat transfer, air flow.

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Authors: Manouchehr Amiri

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This article presents a general notion of physical bit information that is compatible with the basics of quantum mechanics and incorporates the Shannon entropy as a special case. This notion of physical information leads to the Binary Data Matrix model (BDM), which predicts the basic results of quantum mechanics, general relativity, and black hole thermodynamics. The compatibility of the model with holographic, information conservation, and Landauer’s principle is investigated. After deriving the “Bit Information principle” as a consequence of BDM, the fundamental equations of Planck, De Broglie, Bekenstein, and mass-energy equivalence are derived.

Keywords: Physical theory of information, binary data matrix model, Shannon information theory, bit information principle.

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Authors: A. Ahmadi Nadooshan, S. Daneshmand, C. Aghanajafi

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Traditionally, wind tunnel models are made of metal and are very expensive. In these years, everyone is looking for ways to do more with less. Under the right test conditions, a rapid prototype part could be tested in a wind tunnel. Using rapid prototype manufacturing techniques and materials in this way significantly reduces time and cost of production of wind tunnel models. This study was done of fused deposition modeling (FDM) and their ability to make components for wind tunnel models in a timely and cost effective manner. This paper discusses the application of wind tunnel model configuration constructed using FDM for transonic wind tunnel testing. A study was undertaken comparing a rapid prototyping model constructed of FDM Technologies using polycarbonate to that of a standard machined steel model. Testing covered the Mach range of Mach 0.3 to Mach 0.75 at an angle-ofattack range of - 2° to +12°. Results from this study show relatively good agreement between the two models and rapid prototyping Method reduces time and cost of production of wind tunnel models. It can be concluded from this study that wind tunnel models constructed using rapid prototyping method and materials can be used in wind tunnel testing for initial baseline aerodynamic database development.

Keywords: Polycarbonate, Fabrication, FDM, Model, RapidPrototyping, Wind Tunnel.

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Authors: Nahlah Abbas, Saleh A. Wasimi, Nadhir Al-Ansari

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The Greater Zab and Lesser Zab are the major tributaries of Tigris River contributing the largest flow volumes into the river. The impacts of climate change on water resources in these basins have not been well addressed. To gain a better understanding of the effects of climate change on water resources of the study area in near future (2049-2069) as well as in distant future (2080-2099), Soil and Water Assessment Tool (SWAT) was applied. The model was first calibrated for the period from 1979 to 2004 to test its suitability in describing the hydrological processes in the basins. The SWAT model showed a good performance in simulating streamflow. The calibrated model was then used to evaluate the impacts of climate change on water resources. Six general circulation models (GCMs) from phase five of the Coupled Model Intercomparison Project (CMIP5) under three Representative Concentration Pathways (RCPs) RCP 2.6, RCP 4.5, and RCP 8.5 for periods of 2049-2069 and 2080-2099 were used to project the climate change impacts on these basins. The results demonstrated a significant decline in water resources availability in the future.

Keywords: Tigris River, climate change, water resources, SWAT.

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Authors: Tithdanin Chav, Phichhang Ou

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The study is about the e-banking consumer behavior of five major banks in Cambodia. This work aims to examine the relationships among job relevance, trust, mobility, perceived ease of use, perceived usefulness, attitude toward using, and intention to use of internet banking and apps. Also, the research develops and tests a conceptual model of intention to use internet banking by integrating the Technology Acceptance Model (TAM) and job relevance, trust, and mobility which were supported by Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB). The proposed model was tested using Structural Equation Modeling (SEM), which was processed by using SPSS and AMOS with a sample size of 250 e-banking users. The results showed that there is a significant positive relationship among variables and attitudes toward using internet banking, and apps are the most factor influencing consumers’ intention to use internet banking and apps with the importance level in SEM 0.82 accounted by 82%. Significantly, all six hypotheses were accepted.

Keywords: Bank Apps, consumer intention, internet banking, technology acceptance model.

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Authors: W. Kaowumpai, D. Koolpiruck, K. Viravaidya

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Female breast cancer is the second in frequency after cervical cancer. Surgery is the most common treatment for breast cancer, followed by chemotherapy as a treatment of choice. Although effective, it causes serious side effects. Controlled-release drug delivery is an alternative method to improve the efficacy and safety of the treatment. It can release the dosage of drug between the minimum effect concentration (MEC) and minimum toxic concentration (MTC) within tumor tissue and reduce the damage of normal tissue and the side effect. Because an in vivo experiment of this system can be time-consuming and labor-intensive, a mathematical model is desired to study the effects of important parameters before the experiments are performed. Here, we describe a 3D mathematical model to predict the release of doxorubicin from pluronic gel to treat human breast cancer. This model can, ultimately, be used to effectively design the in vivo experiments.

Keywords: Breast Cancer, Doxorubicin, Controlled ReleaseSystem, Diffusion and Convection Equation.

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Authors: Y. Mohseniahouei, K. Abdella, M. Pollanen

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In this paper, we explore the applicability of the Sinc- Collocation method to a three-dimensional (3D) oceanography model. The model describes a wind-driven current with depth-dependent eddy viscosity in the complex-velocity system. In general, the Sinc-based methods excel over other traditional numerical methods due to their exponentially decaying errors, rapid convergence and handling problems in the presence of singularities in end-points. Together with these advantages, the Sinc-Collocation approach that we utilize exploits first derivative interpolation, whose integration is much less sensitive to numerical errors. We bring up several model problems to prove the accuracy, stability, and computational efficiency of the method. The approximate solutions determined by the Sinc-Collocation technique are compared to exact solutions and those obtained by the Sinc-Galerkin approach in earlier studies. Our findings indicate that the Sinc-Collocation method outperforms other Sinc-based methods in past studies.

Keywords: Boundary Value Problems, Differential Equations, Sinc Numerical Methods, Wind-Driven Currents

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Authors: Fatema-Tuz-Zahura, Raquib Ahsan

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Punching shear failure is usually the governing failure mode of flat plate structures. Punching failure is brittle in nature which induces more vulnerability to this type of structure. In the present study, a 3D finite element model of a flat plate with low reinforcement ratio and without any transverse reinforcement has been developed. Punching shear stress and the deflection data were obtained on the surface of the flat plate as well as through the thickness of the model from numerical simulations. The obtained data were compared with the experimental results. Variation of punching stress with respect to deflection as obtained from numerical results is found to be in good agreement with the experimental results; the range of variation of punching stress is within 5%. The numerical simulation shows an early and gradual onset of nonlinearity, whereas the same is late and abrupt as observed in the experimental results. The range of variation of punching stress for different slab thicknesses between experimental and numerical results is less than 15%. The developed numerical model is useful to complement available punching test series performed in the past. The results obtained from the numerical model will be helpful for designing retrofitting schemes of flat plates.

Keywords: Flat plate, finite element model, punching shear, reinforcement ratio.

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Authors: I. Falconett, K. Nagasaka

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This study investigates the performance of radial basis function networks (RBFN) in forecasting the monthly CO2 emissions of an electric power utility. We also propose a method for input variable selection. This method is based on identifying the general relationships between groups of input candidates and the output. The effect that each input has on the forecasting error is examined by removing all inputs except the variable to be investigated from its group, calculating the networks parameter and performing the forecast. Finally, the new forecasting error is compared with the reference model. Eight input variables were identified as the most relevant, which is significantly less than our reference model with 30 input variables. The simulation results demonstrate that the model with the 8 inputs selected using the method introduced in this study performs as accurate as the reference model, while also being the most parsimonious.

Keywords: Correlation analysis, CO2 emissions forecasting, electric power utility, radial basis function networks.

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Authors: Jahar Sarkar

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In the present study, a steady-state simulation model has been developed to evaluate the system performance of a transcritical carbon dioxide heat pump system for simultaneous water cooling and heating. Both the evaporator (including both two-phase and superheated zone) and gas cooler models consider the highly variable heat transfer characteristics of CO2 and pressure drop. The numerical simulation model of transcritical CO2 heat pump has been validated by test data obtained from experiments on the heat pump prototype. Comparison between the test results and the model prediction for system COP variation with compressor discharge pressure shows a modest agreement with a maximum deviation of 15% and the trends are fairly similar. Comparison for other operating parameters also shows fairly similar deviation between the test results and the model prediction. Finally, the simulation results are presented to study the effects of operating parameters such as, temperature of heat exchanger fluid at the inlet, discharge pressure, compressor speed on system performance of CO2 heat pump, suitable in a dairy plant where simultaneous cooling at 4oC and heating at 73oC are required. Results show that good heat transfer properties of CO2 for both two-phase and supercritical region and efficient compression process contribute a lot for high system COPs.

Keywords: CO2 heat pump, dairy system, experiment, simulation model, validation.

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Authors: Elina Bakhtieva

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The variety of available digital tools, strategies and activities might confuse and disorient even an experienced marketer. This applies in particular to B2B companies, which are usually less flexible in uptaking of digital technology than B2C companies. B2B companies are lacking a framework that corresponds to the specifics of the B2B business, and which helps to evaluate a company’s capabilities and to choose an appropriate path. A B2B digital marketing maturity model helps to fill this gap. However, modern marketing offers no widely approved digital marketing maturity model, and thus, some marketing institutions provide their own tools. The purpose of this paper is building an optimized B2B digital marketing maturity model based on a SWOT (strengths, weaknesses, opportunities, and threats) analysis of existing models. The current study provides an analytical review of the existing digital marketing maturity models with open access. The results of the research are twofold. First, the provided SWOT analysis outlines the main advantages and disadvantages of existing models. Secondly, the strengths of existing digital marketing maturity models, helps to identify the main characteristics and the structure of an optimized B2B digital marketing maturity model. The research findings indicate that only one out of three analyzed models could be used as a separate tool. This study is among the first examining the use of maturity models in digital marketing. It helps businesses to choose between the existing digital marketing models, the most effective one. Moreover, it creates a base for future research on digital marketing maturity models. This study contributes to the emerging B2B digital marketing literature by providing a SWOT analysis of the existing digital marketing maturity models and suggesting a structure and main characteristics of an optimized B2B digital marketing maturity model.

Keywords: B2B digital marketing strategy, digital marketing, digital marketing maturity model, SWOT analysis.

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Authors: Yves Lacroix, Van Van Than, Didier Leandri, Pierre Liardet

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The western Tombolo of the Giens peninsula in southern France, known as Almanarre beach, is subject to coastal erosion. We are trying to use computer simulation in order to propose solutions to stop this erosion. Our aim was first to determine the main factors for this erosion and successfully apply a coupled hydrosedimentological numerical model based on observations and measurements that have been performed on the site for decades. We have gathered all available information and data about waves, winds, currents, tides, bathymetry, coastal line, and sediments concerning the site. These have been divided into two sets: one devoted to calibrating a numerical model using Mike 21 software, the other to serve as a reference in order to numerically compare the present situation to what it could be if we implemented different types of underwater constructions. This paper presents the first part of the study: selecting and melting different sources into a coherent data basis, identifying the main erosion factors, and calibrating the coupled software model against the selected reference period. Our results bring calibration of the numerical model with good fitting coefficients. They also show that the winter South-Western storm events conjugated to depressive weather conditions constitute a major factor of erosion, mainly due to wave impact in the northern part of the Almanarre beach. Together, current and wind impact is shown negligible.

Keywords: Almanarre beach, coastal erosion, hydro-sedimentological, numerical model.

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Authors: A. Chaouachi, R. M. Kamel, K. Nagasaka

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This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW Photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three Radial Basis Function Neural Networks (RBFNN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated RBFNN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and non-linear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network.

Keywords: MPPT, neuro-fuzzy, RBFN, grid-connected, photovoltaic.

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Authors: T. T. Manikandan, Rajeev Sukumaran

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For maintaining the biodiversity of many ecosystems the existence of coral reefs play a vital role. But due to many factors such as pollution and coral mining, coral reefs are dying day by day. One way to protect the coral reefs is to farm them in a carefully monitored underwater environment and restore it in place of dead corals. For successful farming of corals in coral farms, different parameters of the water in the farming area need to be monitored and maintained at optimal level. Sensing underwater parameters using wireless sensor nodes is an effective way for precise and continuous monitoring in a highly dynamic environment like oceans. Here the sensed information is of varying importance and it needs to be provided with desired Quality of Service(QoS) guarantees in delivering the information to offshore monitoring centers. The main interest of this research is Stochastic Network Calculus (SNC) based modeling of network layer design for underwater wireless sensor communication. The model proposed in this research enforces differentiation of service in underwater wireless sensor communication with the help of buffer sizing and link scheduling. The delay and backlog bounds for such differentiated services are analytically derived using stochastic network calculus.

Keywords: Underwater Coral Farms, SNC, differentiated service, delay bound, backlog bound.

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Authors: Navjot Kaur, Mini Ghosh, S.S. Bhatia

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This paper proposes and analyzes an SIRS epidemic model incorporating the effects of the awareness programs driven by the media. Media and media driven awareness programs play a promising role in disseminating the information about outbreak of any disease across the globe. This motivates people to take precautionary measures and guides the infected individuals to get hospitalized. Timely hospitalization helps to reduce diagnostic delays and hence results in fast recovery of infected individuals. The aim of this study is to investigate the impact of the media on the spread and control of infectious diseases. This model is analyzed using stability theory of differential equations. The sensitivity of parameters has been discussed and it has been found that the awareness programs driven by the media have positive impact in reducing the infection prevalence of the infective population in the region under consideration.

Keywords: Infectious diseases, SIRS model, Media, Stability theory, Simulation.

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Authors: S. Jarernprasert, E. Bazan-Zurita, P. C. Rizzo

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Currently, seismic probabilistic risk assessments (SPRA) for nuclear facilities use In-Structure Response Spectra (ISRS) in the calculation of fragilities for systems and components. ISRS are calculated via dynamic analyses of the host building subjected to two orthogonal components of horizontal ground motion. Each component is defined as the median motion in any horizontal direction. Structural engineers applied the components along selected X and Y Cartesian axes. The ISRS at different locations in the building are also calculated in the X and Y directions. The choice of the directions of X and Y are not specified by the ground motion model with respect to geographic coordinates, and are rather arbitrarily selected by the structural engineer. Normally, X and Y coincide with the “principal” axes of the building, in the understanding that this practice is generally conservative. For SPRA purposes, however, it is desirable to remove any conservatism in the estimates of median ISRS. This paper examines the effects of the direction of horizontal seismic motion on the ISRS on typical nuclear structure. We also evaluate the variability of ISRS calculated along different horizontal directions. Our results indicate that some central measures of the ISRS provide robust estimates that are practically independent of the selection of the directions of the horizontal Cartesian axes.

Keywords: Seismic, Directionality, In-Structure Response Spectra, Probabilistic Risk Assessment.

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Authors: Kenneth M. Oba

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Adequate management, control, and optimization of cost is an essential element for a successful construction project. A multiple linear regression optimization model was formulated to address the problem of costs associated with pile construction operations. A total of 32 PVC-reinforced concrete piles with diameter of 300 mm, 5.4 m long, were studied during the construction. The soil upon which the piles were installed was mostly silty sand, and completely submerged in water at Bonny, Nigeria. The piles are friction piles installed by boring method, using a piling auger. The volumes of soil removed, the weight of reinforcement cage installed, and volumes of fresh concrete poured into the PVC void were determined. The cost of constructing each pile based on the calculated quantities was determined. A model was derived and subjected to statistical tests using Statistical Package for the Social Sciences (SPSS) software. The model turned out to be adequate, fit, and have a high predictive accuracy with an R2 value of 0.833.

Keywords: Cost optimization modelling, multiple linear models, pile construction, regression models.

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Authors: Jiaji Zhou, Le Liang, Long Chen

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Geographic Profiling has successfully assisted investigations for serial crimes. Considering the multi-cluster feature of serial criminal spots, we propose a Multi-point Centrography model as a natural extension of Single-point Centrography for geographic profiling. K-means clustering is first performed on the data samples and then Single-point Centrography is adopted to derive a probability distribution on each cluster. Finally, a weighted combinations of each distribution is formed to make next-crime spot prediction. Experimental study on real cases demonstrates the effectiveness of our proposed model.

Keywords: Geographic profiling, Centrography model, K-means algorithm

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Authors: Yunyong Guo, Man Wang, Bryan Guo, Nathan Guo

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This paper presents an advanced security and privacy model tailored for Telehealth systems, emphasizing end-to-end protection across IoT, Fog, and Cloud components. The proposed model integrates encryption, key management, intrusion detection, and privacy-preserving measures to safeguard patient data. A comprehensive simulation study evaluates the model's effectiveness in scenarios such as unauthorized access, physical breaches, and insider threats. Results indicate notable success in detecting and mitigating threats yet underscore areas for refinement. The study contributes insights into the intricate balance between security and usability in Telehealth environments, setting the stage for continued advancements.

Keywords: Cloud, enhancing security, Fog, IoT, telehealth.

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Authors: Kamal K.Bharadwaj, Rekha Kandwal

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An important structuring mechanism for knowledge bases is building clusters based on the content of their knowledge objects. The objects are clustered based on the principle of maximizing the intraclass similarity and minimizing the interclass similarity. Clustering can also facilitate taxonomy formation, that is, the organization of observations into a hierarchy of classes that group similar events together. Hierarchical representation allows us to easily manage the complexity of knowledge, to view the knowledge at different levels of details, and to focus our attention on the interesting aspects only. One of such efficient and easy to understand systems is Hierarchical Production rule (HPRs) system. A HPR, a standard production rule augmented with generality and specificity information, is of the following form Decision If < condition> Generality Specificity . HPRs systems are capable of handling taxonomical structures inherent in the knowledge about the real world. In this paper, a set of related HPRs is called a cluster and is represented by a HPR-tree. This paper discusses an algorithm based on cumulative learning scenario for dynamic structuring of clusters. The proposed scheme incrementally incorporates new knowledge into the set of clusters from the previous episodes and also maintains summary of clusters as Synopsis to be used in the future episodes. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested incremental structuring of clusters would be useful in mining data streams.

Keywords: Cumulative learning, clustering, data mining, hierarchical production rules.

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Authors: S. Pirrello

Abstract:

Sydney’s booming real estate market has pushed property developers to invest in historically “no-go” areas, which were previously too expensive to develop. These areas are usually near rivers where the sites are underlain by deep alluvial and estuarine sediments. In these ground conditions, conventional bored pile techniques are often not competitive. Contiguous Flight Auger (CFA) and Drilled Displacement (DD) Piles techniques are on the other hand suitable for these ground conditions. This paper deals with the design and construction challenges encountered with these piling techniques for a series of high-rise towers in Sydney’s West. The advantages of DD over CFA piles such as reduced overall spoil with substantial cost savings and achievable rock sockets in medium strength bedrock are discussed. Design performances were assessed with PIGLET. Pile performances are validated in two stages, during constructions with the interpretation of real-time data from the piling rigs’ on-board computer data, and after construction with analyses of results from high strain pile dynamic testing (PDA). Results are then presented and discussed. High Strain testing data are presented as Case Pile Wave Analysis Program (CAPWAP) analyses.

Keywords: Contiguous flight auger, case pile wave analysis, high strain pile, drilled displacement, pile performance.

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Authors: V. Viduĉić, J. Žanić Mikuliĉić, M. Raĉić, K. Sladojević

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The research presented in this paper has been focused on analysing the impact of traffic on the sustainable development of tourism in Croatia's Dubrovacko-Neretvanska County by the year 2020, based on the figures and trends reported in 2014 and using the relevant variables that characterise the synergy of traffic and tourism in, speaking from the geographic viewpoint, the most problematic county in the Republic of Croatia. The basic hypothesis has been confirmed through scientifically obtained research results, through the quantification of the model's variables and the direct growth rates of the designed model. On the basis of scientific insights into the sustainable development of traffic and tourism in Dubrovacko- Neretvanska County, it is possible to propose a new information model for traffic at the service of the sustainable development of tourism in the County for the period 2014-2020.

Keywords: Environment protection, hotel industry, private sector, quantification.

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Authors: Alia Abdul Ghaffar, Tom Richardson

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A model reference adaptive control and a fixed gain LQR control were implemented in the height controller of a quadrotor that has parametric uncertainties due to the act of picking up an object of unknown dimension and mass. It is shown that an adaptive controller, unlike the fixed gain controller, is capable of ensuring a stable tracking performance under such condition, although adaptive control suffers from several limitations. The combination of both adaptive and fixed gain control in the controller architecture can result in an enhanced tracking performance in the presence parametric uncertainties.

Keywords: UAV, quadrotor, model reference adaptive control, LQR control.

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Authors: Mahmood Reza Shakarami, Reza Sedaghati

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Electricity market activities and a growing demand for electricity have led to heavily stressed power systems. This requires operation of the networks closer to their stability limits. Power system operation is affected by stability related problems, leading to unpredictable system behavior. Voltage stability refers to the ability of a power system to sustain appropriate voltage levels through large and small disturbances. Steady-state voltage stability is concerned with limits on the existence of steady-state operating points for the network. FACTS devices can be utilized to increase the transmission capacity, the stability margin and dynamic behavior or serve to ensure improved power quality. Their main capabilities are reactive power compensation, voltage control and power flow control. Among the FACTS controllers, Static Var Compensator (SVC) provides fast acting dynamic reactive compensation for voltage support during contingency events. In this paper, voltage stability assessment with appropriate representations of tap-changer transformers and SVC is investigated. Integrating both of these devices is the main topic of this paper. Effect of the presence of tap-changing transformers on static VAR compensator controller parameters and ratings necessary to stabilize load voltages at certain values are highlighted. The interrelation between transformer off nominal tap ratios and the SVC controller gains and droop slopes and the SVC rating are found. P-V curves are constructed to calculate loadability margins.

Keywords: SVC, voltage stability, P-V curve, reactive power, tap changing transformer.

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Authors: Naeem Muhammad, Yves Vandewoude, Yolande Berbers, Robert Feldt

Abstract:

The Requirements Abstraction Model (RAM) helps in managing abstraction in requirements by organizing them at four levels (product, feature, function and component). The RAM is adaptable and can be tailored to meet the needs of the various organizations. Because software requirements are an important source of information for developing high-level tests, organizations willing to adopt the RAM model need to know the suitability of the RAM requirements for developing high-level tests. To investigate this suitability, test cases from twenty randomly selected requirements were developed, analyzed and graded. Requirements were selected from the requirements document of a Course Management System, a web based software system that supports teachers and students in performing course related tasks. This paper describes the results of the requirements document analysis. The results show that requirements at lower levels in the RAM are suitable for developing executable tests whereas it is hard to develop from requirements at higher levels.

Keywords: Market-driven requirements engineering, requirements abstraction model, requirements abstraction, system testing.

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