Search results for: business model innovation

Authors: Sang-Lae Lee, Ji-Hwan Kim

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In this study, it is investigated the stability boundary of Functionally Graded (FG) panel under the heats and supersonic airflows. Material properties are assumed to be temperature dependent, and a simple power law distribution is taken. First-order shear deformation theory (FSDT) of plate is applied to model the panel, and the von-Karman strain- displacement relations are adopted to consider the geometric nonlinearity due to large deformation. Further, the first-order piston theory is used to model the supersonic aerodynamic load acting on a panel and Rayleigh damping coefficient is used to present the structural damping. In order to find a critical value of the speed, linear flutter analysis of FG panels is performed. Numerical results are compared with the previous works, and present results for the temperature dependent material are discussed in detail for stability boundary of the panel with various volume fractions, and aerodynamic pressures.

Keywords: Functionally graded panels, Linear flutter analysis, Supersonic airflows, Temperature dependent material property.

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Authors: Paula Ferreira, Madalena Araújo, M.E.J. O’Kelly

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Combining energy efficiency with renewable energy sources constitutes a key strategy for a sustainable future. The wind power sector stands out as a fundamental element for the achievement of the European renewable objectives and Portugal is no exception to the increase of the wind energy for the electricity generation. This work proposes an optimization model for the long range electricity power planning in a system similar to the Portuguese one, where the expected impacts of the increasing installed wind power on the operating performance of thermal power plants are taken into account. The main results indicate that the increasing penetration of wind power in the electricity system will have significant effects on the combined cycle gas power plants operation and on the theoretically expected cost reduction and environmental gains. This research demonstrated the need to address the impact that energy sources with variable output may have, not only on the short-term operational planning, but especially on the medium to long range planning activities, in order to meet the strategic objectives for the energy sector.

Keywords: Wind power, electricity planning model, cost, emissions.

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Authors: Folorunso Olufemi Ayinde, Mohd Shahrizal Sunar, Sarudin Kari, Dzulkifli Mohamad

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In this paper we discuss the development of an Augmented Reality (AR) - based scientific visualization system prototype that supports identification, localisation, and 3D visualisation of oil leakages sensors datasets. Sensors generates significant amount of multivariate datasets during normal and leak situations. Therefore we have developed a data model to effectively manage such data and enhance the computational support needed for the effective data explorations. A challenge of this approach is to reduce the data inefficiency powered by the disparate, repeated, inconsistent and missing attributes of most available sensors datasets. To handle this challenge, this paper aim to develop an AR-based scientific visualization interface which automatically identifies, localise and visualizes all necessary data relevant to a particularly selected region of interest (ROI) along the virtual pipeline network. Necessary system architectural supports needed as well as the interface requirements for such visualizations are also discussed in this paper.

Keywords: Sensor Leakages Datasets, Augmented Reality, Sensor Data-Model, Scientific Visualization.

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Authors: Sarah O. Alhumoud, Mawaheb I. Altuwaijri, Tarfa M. Albuhairi, Wejdan M. Alohaideb

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Large-scale data stream analysis has become one of the important business and research priorities lately. Social networks like Twitter and other micro-blogging platforms hold an enormous amount of data that is large in volume, velocity and variety. Extracting valuable information and trends out of these data would aid in a better understanding and decision-making. Multiple analysis techniques are deployed for English content. Moreover, one of the languages that produce a large amount of data over social networks and is least analyzed is the Arabic language. The proposed paper is a survey on the research efforts to analyze the Arabic content in Twitter focusing on the tools and methods used to extract the sentiments for the Arabic content on Twitter.

Keywords: Big Data, Social Networks, Sentiment Analysis.

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Authors: Babak Abedin, Babak Sohrabi

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Website plays a significant role in success of an e-business. It is the main start point of any organization and corporation for its customers, so it's important to customize and design it according to the visitors' preferences. Also, websites are a place to introduce services of an organization and highlight new service to the visitors and audiences. In this paper, we will use web usage mining techniques, as a new field of research in data mining and knowledge discovery, in an Iranian government website. Using the results, a framework for web content layour is proposed. An agent is designed to dynamically update and improve web links locations and layout. Then, we will explain how it is used to directly enable top managers of the organization to influence on the arrangement of web contents and also to enhance customization of web site navigation due to online users' behaviors.

Keywords: Web usage mining, website design, agent, website customization.

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Authors: Yan Su, L. C. Chan

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A novel typical day prediction model have been built and validated by the measured data of a grid-connected solar photovoltaic (PV) system in Macau. Unlike conventional statistical method used by previous study on PV systems which get results by averaging nearby continuous points, the present typical day statistical method obtain the value at every minute in a typical day by averaging discontinuous points at the same minute in different days. This typical day statistical method based on discontinuous point averaging makes it possible for us to obtain the Gaussian shape dynamical distributions for solar irradiance and output power in a yearly or monthly typical day. Based on the yearly typical day statistical analysis results, the maximum possible accumulated output energy in a year with on site climate conditions and the corresponding optimal PV system running time are obtained. Periodic Gaussian shape prediction models for solar irradiance, output energy and system energy efficiency have been built and their coefficients have been determined based on the yearly, maximum and minimum monthly typical day Gaussian distribution parameters, which are obtained from iterations for minimum Root Mean Squared Deviation (RMSD). With the present model, the dynamical effects due to time difference in a day are kept and the day to day uncertainty due to weather changing are smoothed but still included. The periodic Gaussian shape correlations for solar irradiance, output power and system energy efficiency have been compared favorably with data of the PV system in Macau and proved to be an improvement than previous models.

Keywords: Grid Connected, RMSD, Solar PV System, Typical Day.

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Authors: Ren Jian-min, Wu Si-wei, Jin Wei

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CTMA-bentonite and BTEA-Bentonite prepared by Na-bentonite cation exchanged with cetyltrimethylammonium(CTMA) and benzyltriethylammonium (BTEA). Products were characterized by XRD and IR techniques.The d001 spacing value of CTMA-bentonite and BTEA-bentonite are 7.54Å and 3.50Å larger than that of Na-bentonite at 100% cation exchange capacity, respectively. The IR spectrum showed that the intensities of OH stretching and bending vibrations of the two organoclays decreased greatly comparing to untreated Na-bentonite. Batch experiments were carried out at 303 K, 318 K and 333 K to obtain the sorption isotherms of Crystal violet onto the two organoclays. The results show that the sorption isothermal data could be well described by Freundlich model. The dynamical data for the two organoclays fit well with pseudo-second-order kinetic model. The adsorption capacity of CTMA-bentonite was found higher than that of BTEA-Bentonite. Thermodynamic parameters such as changes in the free energy (ΔG°), the enthalpy (ΔH°) and the entropy (ΔS°) were also evaluated. The overall adsorption process of Crystal violet onto the two organoclays were spontaneous, endothermic physisorption. The CTMA-bentonite and BTEA-Bentonite could be employed as low-cost alternatives to activated carbon in wastewater treatment for the removal of color which comes from textile dyes.

Keywords: Characterization, Adsorption, Crystal violet, Bentonite, BTEA, CTMA

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Authors: Jinyong Yao, Hongzhi Li, Chao Du, Jiao Li

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Reliability of long-term storage products is related to the availability of the whole system, and the evaluation of storage life is of great necessity. These products are usually highly reliable and little failure information can be collected. In this paper, an analytical method based on data from accelerated storage life test is proposed to evaluate the reliability index of the long-term storage products. Firstly, singularities are eliminated by data normalization and residual analysis. Secondly, with the preprocessed data, the degradation path model is built to obtain the pseudo life values. Then by life distribution hypothesis, we can get the estimator of parameters in high stress levels and verify failure mechanism consistency. Finally, the life distribution under the normal stress level is extrapolated via the acceleration model and evaluation of the actual average life is available. An application example with the camera stabilization device is provided to illustrate the methodology we proposed.

Keywords: Accelerated storage life test, failure mechanism consistency, life distribution, reliability.

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Authors: Waldemiro Francisco Sorte Junior

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The Japanese integrative approach to social systems can be observed in supply chain management as well as in the relationship between public and private sectors. Both the Lean Production System and the Developmental State Model are characterized by efforts towards the achievement of mutual goals, resulting in initiatives for capacity building which emphasize the system level. In Brazil, although organizations undertake efforts to build capabilities at the individual and organizational levels, the system level is being neglected. Fieldwork data confirmed the findings of other studies in terms of the lack of integration in supply chain management in the Brazilian automobile industry. Moreover, due to the absence of an active role of the Brazilian state in its relationship with the private sector, automakers are not fully exploiting the opportunities in the domestic and regional markets. For promoting a higher level of economic growth as well as to increase the degree of spill-over of technologies and techniques, a more integrative approach is needed.

Keywords: Integration, Lean Production System, DevelopmentalState Model, Brazilian automobile industry.

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Authors: Berkay Ergene, Çağın Bolat

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In this study, we mainly focused on a simulation study regarding composite footbed in order to contribute to shoe industry. As a footbed, e-glass fiber reinforced polyurethane was determined since polyurethane based materials are already used for footbed in shoe manufacturing frequently. Flat, elliptical and rectangular grooved shoe soles were modeled and analyzed separately as TPU, 10% glass fiber reinforced, 30% glass fiber reinforced and 50% glass fiber reinforced materials according to their properties under three point bending and compression situations to determine the relationship between model, material type and mechanical behaviours of composite model. ANSYS 14.0 APDL mechanical structural module is utilized in all simulations and analyzed stress and strain distributions for different footbed models and materials. Furthermore, materials constants like young modulus, shear modulus, Poisson ratio and density of the composites were calculated theoretically by using composite mixture rule and interpreted for mechanical aspects.

Keywords: Composite, elastic behaviour, footbed, simulation.

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Authors: L. J. de Bessa Neto, V. S. Filho, J. V. Ferreira Nunes, G. C. Bergamo

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There are many situations in which human activities have significant effects on the environment. Damage to the ozone layer is one of them. The objective of this work is to use the Least Squares Method, considering the linear, exponential, logarithmic, power and polynomial models of the second degree, to analyze through the coefficient of determination (R²), which model best fits the behavior of the chlorodifluoromethane (HCFC-142b) in parts per trillion between 1992 and 2018, as well as estimates of future concentrations between 5 and 10 periods, i.e. the concentration of this pollutant in the years 2023 and 2028 in each of the adjustments. A total of 809 observations of the concentration of HCFC-142b in one of the monitoring stations of gases precursors of the deterioration of the ozone layer during the period of time studied were selected and, using these data, the statistical software Excel was used for make the scatter plots of each of the adjustment models. With the development of the present study, it was observed that the logarithmic fit was the model that best fit the data set, since besides having a significant R² its adjusted curve was compatible with the natural trend curve of the phenomenon.

Keywords: Chlorodifluoromethane (HCFC-142b), ozone (O3), least squares method, regression models.

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Authors: S. R. Nikhashemi, L. Haj Paim, Ali Khatibi

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Structural Equation Modeling (SEM) was used to test a hypothesized model explaining Malaysian hypermarket customers’ perceptions of brand trust (BT), customer perceived value (CPV) and perceived service quality (PSQ) on building their brand loyalty (CBL) and generating positive word-of-mouth communication (WOM). Self-administered questionnaires were used to collect data from 374 Malaysian hypermarket customers from Mydin, Tesco, Aeon Big and Giant in Kuala Lumpur, a metropolitan city of Malaysia. The data strongly supported the model exhibiting that BT, CPV and PSQ are prerequisite factors in building customer brand loyalty, while PSQ has the strongest effect on prediction of customer brand loyalty compared to other factors. Besides, the present study suggests the effect of the aforementioned factors via customer brand loyalty strongly contributes to generate positive word of mouth communication.

Keywords: Brand trust, perceived value, perceived service quality, brand loyalty, positive word of mouth communication.

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Authors: Muhammad F. Yaqub, Iqbal Gondal, Joarder Kamruzzaman

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Occurrence of a multiple-points fault in machine operations could result in exhibiting complex fault signatures, which could result in lowering fault diagnosis accuracy. In this study, a multiple-points defect model (MPDM) is proposed which can simulate fault signature-s dynamics for n-points bearing faults. Furthermore, this study identifies that in case of multiple-points fault in the rotary machine, the location of the dominant component of defect frequency shifts depending upon the relative location of the fault points which could mislead the fault diagnostic model to inaccurate detections. Analytical and experimental results are presented to characterize and validate the variation in the dominant component of defect frequency. Based on envelop detection analysis, a modification is recommended in the existing fault diagnostic models to consider the multiples of defect frequency rather than only considering the frequency spectrum at the defect frequency in order to incorporate the impact of multiple points fault.

Keywords: Envelop detection, machine defect frequency, multiple faults, machine health monitoring.

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Authors: Norma Rodrigues Gomes

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This paper presents initiatives of Knowledge Management (KM) applied to Forensic Sciences field, especially developed at the Forensic Science Institute of the Brazilian Federal Police. Successful projects, related to knowledge sharing, drugs analysis and environmental crimes, are reported in the KM perspective. The described results are related to: a) the importance of having an information repository, like a digital library, in such a multidisciplinary organization; b) the fight against drug dealing and environmental crimes, enabling the possibility to map the evolution of crimes, drug trafficking flows, and the advance of deforestation in Amazon rain forest. Perspectives of new KM projects under development and studies are also presented, tracing an evolution line of the KM view at the Forensic Science Institute.

Keywords: Business Intelligence, Digital Library, Forensic Science, Knowledge Management

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Authors: Mircea Pastrav, Horia Constantinescu

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The construction industry is currently trying to develop sustainable reinforced concrete structures. In trying to aid in the effort, the research presented in this paper aims to prove the efficiency of modified special hybrid moment frames composed of discretely jointed precast and post-tensioned concrete members. This aim is due to the fact that current design standards do not cover the spatial design of moment frame structures assembled by post-tensioning with special hybrid joints. This lack of standardization is coupled with the fact that previous experimental programs, available in scientific literature, deal mainly with plane structures and offer little information regarding spatial behavior. A spatial model of a modified hybrid moment frame is experimentally analyzed. The experimental results of a natural scale model test of a corner column-beams sub-structure, cut from an actual multilevel building tested to seismic type loading are presented in order to highlight the behavior of this type of structure. The test is performed under alternative cycles of imposed lateral displacements, up to a storey drift ratio of 0.035. Seismic response of the spatial model is discussed considering the acceptance criteria for reinforced concrete frame structures designed based on experimental tests, as well as some of its major sustainability features. The results obtained show an overall excellent behavior of the system. The joint detailing allows for quick and cheap repairs after an accidental event and a self-balancing behavior of the system that ensures it can be used almost immediately after an accidental event it.

Keywords: Modified hybrid joint, seismic type loading response, self-balancing structure, acceptance criteria.

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Authors: Ashwani K. Rana, Narottam Chand, Vinod Kapoor

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In this paper, gate leakage current has been mitigated by the use of novel nanoscale MOSFET with Source/Drain-to-Gate Non-overlapped and high-k spacer structure for the first time. A compact analytical model has been developed to study the gate leakage behaviour of proposed MOSFET structure. The result obtained has found good agreement with the Sentaurus Simulation. Fringing gate electric field through the dielectric spacer induces inversion layer in the non-overlap region to act as extended S/D region. It is found that optimal Source/Drain-to-Gate Non-overlapped and high-k spacer structure has reduced the gate leakage current to great extent as compared to those of an overlapped structure. Further, the proposed structure had improved off current, subthreshold slope and DIBL characteristic. It is concluded that this structure solves the problem of high leakage current without introducing the extra series resistance.

Keywords: Gate tunneling current, analytical model, spacer dielectrics, DIBL, subthreshold slope.

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Authors: Hidetoshi Konno, Akio Suzuki

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The paper presented a transient population dynamics of phase singularities in 2D Beeler-Reuter model. Two stochastic modelings are examined: (i) the Master equation approach with the transition rate (i.e., λ(n, t) = λ(t)n and μ(n, t) = μ(t)n) and (ii) the nonlinear Langevin equation approach with a multiplicative noise. The exact general solution of the Master equation with arbitrary time-dependent transition rate is given. Then, the exact solution of the mean field equation for the nonlinear Langevin equation is also given. It is demonstrated that transient population dynamics is successfully identified by the generalized Logistic equation with fractional higher order nonlinear term. It is also demonstrated the necessity of introducing time-dependent transition rate in the master equation approach to incorporate the effect of nonlinearity.

Keywords: Transient population dynamics, Phase singularity, Birth-death process, Non-stationary Master equation, nonlinear Langevin equation, generalized Logistic equation.

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Authors: Adeolu O. Dairo

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Getting the consumer marketing strategy right is a crucial and complex task for firms with a large customer base such as mobile operators in a competitive mobile market. While empirical studies have made efforts to identify key constructs, no geospatial model has been developed to comprehensively assess the viability and interdependency of ground realities regarding the customer, competition, channel and the network quality of mobile operators. With this research, a geo-analytic framework is proposed for strategy formulation and allocation for mobile operators. Firstly, a fuzzy analytic network using a self-organizing feature map clustering technique based on inputs from managers and literature, which depicts the interrelationships amongst ground realities is developed. The model is tested with a mobile operator in the Nigeria mobile market. As a result, a customer-centric geospatial and visualization solution is developed. This provides a consolidated and integrated insight that serves as a transparent, logical and practical guide for strategic, tactical and operational decision making.

Keywords: Geospatial, geo-analytics, self-organizing map, customer-centric.

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Authors: Shin Je Lee, Go Bong Choi, Jeong Cheol Seo, Jong Min Lee, Gibaek Lee

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Water pipe network is installed underground and once equipped, it is difficult to recognize the state of pipes when the leak or burst happens. Accordingly, post management is often delayed after the fault occurs. Therefore, the systematic fault management system of water pipe network is required to prevent the accident and minimize the loss. In this work, we develop online fault detection system of water pipe network using data of pipes such as flow rate or pressure. The transient model describing water flow in pipelines is presented and simulated using MATLAB. The fault situations such as the leak or burst can be also simulated and flow rate or pressure data when the fault happens are collected. Faults are detected using statistical methods of fast Fourier transform and discrete wavelet transform, and they are compared to find which method shows the better fault detection performance.

Keywords: fault detection, water pipeline model, fast Fourier transform, discrete wavelet transform.

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Authors: Bekim Fetaji, Majlinda Fetaji, Mirlinda Ebibi

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The objective of the research was focused on the design, development and evaluation of a sustainable web based network system to be used as an interoperable environment for University process workflow and document management. In this manner the most of the process workflows in Universities can be entirely realized electronically and promote integrated University. Definition of the most used University process workflows enabled creating electronic workflows and their execution on standard workflow execution engines. Definition or reengineering of workflows provided increased work efficiency and helped in having standardized process through different faculties. The concept and the process definition as well as the solution applied as Case study are evaluated and findings are reported.

Keywords: design process workflows, workflow and documentmanagement, Business Process, software engineering

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Authors: Achmad Nizar Hidayanto, Elisabeth Martha Koeanan

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Image clustering is a process of grouping images based on their similarity. The image clustering usually uses the color component, texture, edge, shape, or mixture of two components, etc. This research aims to explore image clustering using color composition. In order to complete this image clustering, three main components should be considered, which are color space, image representation (feature extraction), and clustering method itself. We aim to explore which composition of these factors will produce the best clustering results by combining various techniques from the three components. The color spaces use RGB, HSV, and L*a*b* method. The image representations use Histogram and Gaussian Mixture Model (GMM), whereas the clustering methods use KMeans and Agglomerative Hierarchical Clustering algorithm. The results of the experiment show that GMM representation is better combined with RGB and L*a*b* color space, whereas Histogram is better combined with HSV. The experiments also show that K-Means is better than Agglomerative Hierarchical for images clustering.

Keywords: Image clustering, feature extraction, RGB, HSV, L*a*b*, Gaussian Mixture Model (GMM), histogram, Agglomerative Hierarchical Clustering (AHC), K-Means, Expectation-Maximization (EM).

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Authors: Sorana M. Manoiu, Razvan V. Mustata, Jiří Strouhal, Carmen G. Bonaci, Dumitru Matis, Jiřina Bokšová

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In the current context of globalization, accountability has become a key subject of real interest for both, national and international business areas, due to the need for comparability and transparency of the economic situation, so we can speak about the harmonization and convergence of international accounting. The paper presents a qualitative research through content analysis of several reports concerning the roadmap for convergence. First, we develop a conceptual framework for the evolution of standards’ convergence and further we discuss the degree of standards harmonization and convergence between US GAAP and IAS/IFRS as to October 2012. We find that most topics did not follow the expected progress. Furthermore there are still some differences in the long-term project that are in process to be completed and other that were reassessed as a lower priority project.

Keywords: Convergence, harmonization, FASB, IASB, IFRS, US GAAP.

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Authors: Ivan Živanović, Žužana Vaštag, Senka Popović, Ljiljana Popović, Draginja Peričin

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The present work represents an investigation of the hydrolysis of hull-less pumpkin (Cucurbita Pepo L.) oil cake protein isolate (PuOC PI) by pepsin. To examine the effectiveness and suitability of pepsin towards PuOC PI the kinetic parameters for pepsin on PuOC PI were determined and then, the hydrolysis process was studied using Response Surface Methodology (RSM). The hydrolysis was carried out at temperature of 30°C and pH 3.00. Time and initial enzyme/substrate ratio (E/S) at three levels were selected as the independent parameters. The degree of hydrolysis, DH, was mesuared after 20, 30 and 40 minutes, at initial E/S of 0.7, 1 and 1.3 mA/mg proteins. Since the proposed second-order polynomial model showed good fit with the experimental data (R2 = 0.9822), the obtained mathematical model could be used for monitoring the hydrolysis of PuOC PI by pepsin, under studied experimental conditions, varying the time and initial E/S. To achieve the highest value of DH (39.13 %), the obtained optimum conditions for time and initial E/S were 30 min and 1.024 mA/mg proteins.

Keywords: Enzymatic hydrolysis, Pepsin, Pumpkin (CucurbitaPepo L.) oil cake protein isolate, Response surface methodology.

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Authors: Wenzhe Li, Xiaoyu Ying, Grace Ding

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Architecture plane form is an important consideration in the design of green buildings due to its significant impact on energy performance. The most effective method to consider energy performance in the early design stages is parametric modelling. This paper presents a methodology to program plane forms using MATLAB language, generating 16 kinds of plane forms by changing four designed parameters. DesignBuilder (an energy consumption simulation software) was proposed to simulate the energy consumption of the generated planes. A regression mathematical model was established to study the relationship between the plane forms and their energy consumption. The main finding of the study suggested that there was a cubic function relationship between the depth-ratio of U-shaped buildings and energy consumption, and there is also a cubic function relationship between the width-ratio and energy consumption. In the design, the depth-ratio of U-shaped buildings should not be less than 2.5, and the width-ratio should not be less than 2.

Keywords: Graphic parameterization, green building design, mathematical model, U-shaped buildings.

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Authors: Mona Lisa M. Oliveira, Nara A. Policarpo, Ana Luiza B. P. Barros, Carla A. Silva

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Selective catalytic reduction systems for nitrogen oxides reduction by ammonia has been the chosen technology by most of diesel vehicle (i.e. bus and truck) manufacturers in Brazil, as also in Europe. Furthermore, at some conditions, over-stoichiometric ammonia availability is also needed that increases the NH₃ slips even more. Ammonia (NH₃) by this vehicle exhaust aftertreatment system provides a maximum efficiency of NOx removal if a significant amount of NH₃ is stored on its catalyst surface. In the other words, the practice shows that slightly less than 100% of the NOx conversion is usually targeted, so that the aqueous urea solution hydrolyzes to NH₃ via other species formation, under relatively low temperatures. This paper presents a model based on neural networks integrated with a road vehicle simulator that allows to estimate NH₃-slip emission factors for different driving conditions and patterns. The proposed model generates high NH₃slips which are not also limited in Brazil, but more efforts needed to be made to elucidate the contribution of vehicle-emitted NH₃ to the urban atmosphere.

Keywords: Ammonia slip, neural-network, vehicles emissions, SCR-NOx.

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Authors: Lim Chen Kim, Tan Kian Lam, Chan Yi Chee

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This research presents a multi-modal simulation in the reconstruction of the past and the construction of present in digital cultural heritage on mobile platform. In bringing the present life, the virtual environment is generated through a presented scheme for rapid and efficient construction of 360° panoramic view. Then, acoustical heritage model and crowd model are presented and improvised into the 360° panoramic view. For the reconstruction of past life, the crowd is simulated and rendered in an old trading port. However, the keystone of this research is in a virtual walkthrough that shows the virtual present life in 2D and virtual past life in 3D, both in an environment of virtual heritage sites in George Town through mobile device. Firstly, the 2D crowd is modelled and simulated using OpenGL ES 1.1 on mobile platform. The 2D crowd is used to portray the present life in 360° panoramic view of a virtual heritage environment based on the extension of Newtonian Laws. Secondly, the 2D crowd is animated and rendered into 3D with improved variety and incorporated into the virtual past life using Unity3D Game Engine. The behaviours of the 3D models are then simulated based on the enhancement of the classical model of Boid algorithm. Finally, a demonstration system is developed and integrated with the models, techniques and algorithms of this research. The virtual walkthrough is demonstrated to a group of respondents and is evaluated through the user-centred evaluation by navigating around the demonstration system. The results of the evaluation based on the questionnaires have shown that the presented virtual walkthrough has been successfully deployed through a multi-modal simulation and such a virtual walkthrough would be particularly useful in a virtual tour and virtual museum applications.

Keywords: Boid algorithm, crowd simulation, mobile platform, Newtonian laws, virtual heritage.

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Authors: Jia Xin Low, Keng Wah Choo

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This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.

Keywords: Convolutional neural network, discrete wavelet transform, deep learning, heart sound classification.

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Authors: Jaideep Motwani, Asli Yagmur Akbulut

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Using a methodology grounded in business process change theory, we investigate the critical success factors that affect ERP implementation success in United States and India. Specifically, we examine the ERP implementation at two case study companies, one in each country. Our findings suggest that certain factors that affect the success of ERP implementations are not culturally bound, whereas some critical success factors depend on the national culture of the country in which the system is being implemented. We believe that the understanding of these critical success factors will deepen the understanding of ERP implementations and will help avoid implementation mistakes, thereby increasing the rate of success in culturally different contexts. Implications of the findings and future research directions for both academicians and practitioners are also discussed.

Keywords: Critical Success Factors, Culture, Enterprise Resource Planning Systems, India, United States

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Authors: Behnam Mehrkian, Arash Bahar, Ali Chaibakhsh

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Magneto-rheological (MR) fluid damper is a semiactive control device that has recently received more attention by the vibration control community. But inherent hysteretic and highly nonlinear dynamics of MR fluid damper is one of the challenging aspects to employ its unique characteristics. The combination of artificial neural network (ANN) and fuzzy logic system (FLS) have been used to imitate more precisely the behavior of this device. However, the derivative-based nature of adaptive networks causes some deficiencies. Therefore, in this paper, a novel approach that employ genetic algorithm, as a free-derivative algorithm, to enhance the capability of fuzzy systems, is proposed. The proposed method used to model MR damper. The results will be compared with adaptive neuro-fuzzy inference system (ANFIS) model, which is one of the well-known approaches in soft computing framework, and two best parametric models of MR damper. Data are generated based on benchmark program by applying a number of famous earthquake records.

Keywords: Benchmark program, earthquake record filtering, fuzzy logic, genetic algorithm, MR damper.

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Authors: Alia Alghosoun, Nabil El Moçayd, Mohammed Seaid

Abstract:

Modeling dam-break flows over non-flat beds requires an accurate representation of the topography which is the main source of uncertainty in the model. Therefore, developing robust and accurate techniques for reconstructing topography in this class of problems would reduce the uncertainty in the flow system. In many hydraulic applications, experimental techniques have been widely used to measure the bed topography. In practice, experimental work in hydraulics may be very demanding in both time and cost. Meanwhile, computational hydraulics have served as an alternative for laboratory and field experiments. Unlike the forward problem, the inverse problem is used to identify the bed parameters from the given experimental data. In this case, the shallow water equations used for modeling the hydraulics need to be rearranged in a way that the model parameters can be evaluated from measured data. However, this approach is not always possible and it suffers from stability restrictions. In the present work, we propose an adaptive optimal control technique to numerically identify the underlying bed topography from a given set of free-surface observation data. In this approach, a minimization function is defined to iteratively determine the model parameters. The proposed technique can be interpreted as a fractional-stage scheme. In the first stage, the forward problem is solved to determine the measurable parameters from known data. In the second stage, the adaptive control Ensemble Kalman Filter is implemented to combine the optimality of observation data in order to obtain the accurate estimation of the topography. The main features of this method are on one hand, the ability to solve for different complex geometries with no need for any rearrangements in the original model to rewrite it in an explicit form. On the other hand, its achievement of strong stability for simulations of flows in different regimes containing shocks or discontinuities over any geometry. Numerical results are presented for a dam-break flow problem over non-flat bed using different solvers for the shallow water equations. The robustness of the proposed method is investigated using different numbers of loops, sensitivity parameters, initial samples and location of observations. The obtained results demonstrate high reliability and accuracy of the proposed techniques.

Keywords: Optimal control, ensemble Kalman Filter, topography reconstruction, data assimilation, shallow water equations.

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