Search results for: restructuringbuilding information modeling

Authors: Sameut Bouhaik Mostafa

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Information Act is the Canadian law gives the right of access to information for the institution of government. It declares the availability of government information to the public, but that exceptions should be limited and the necessary right of access to be specific, and also states the need to constantly re-examine the decisions on the disclosure of any government information independently from the government. By 1982, it enacted a dozen countries, including France, Denmark, Finland, Sweden, the Netherlands and the United States (1966) newly legally to access the information. It entered access to Canadian information into force of the Act of 1983, under the government of Pierre Trudeau, allowing Canadians to recover information from government files, and the development of what can be accessed from the information, and the imposition of timetables to respond. It has been applied by the Information Commissioner in Canada.

Keywords: law, information, management, legal

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Authors: Seyed Abbas Tabatabaei, Fereydoon Moghadas Nejad, Mohammad Saed

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The bleeding prediction of the asphalt is one of the most complex subjects in the pavement engineering. In this paper, an Adaptive Neuro Fuzzy Inference System (ANFIS) is used for modeling the effect of important parameters on bleeding is trained and tested with the experimental results. bleeding index based on the asphalt film thickness differential as target parameter,asphalt content, temperature depth of two centemeter, heavy traffic, dust to effective binder, Marshall strength, passing 3/4 sieves, passing 3/8 sieves,passing 3/16 sieves, passing NO8, passing NO50, passing NO100, passing NO200 as input parameters. Then, we randomly divided empirical data into train and test sections in order to accomplish modeling. We instructed ANFIS network by 72 percent of empirical data. 28 percent of primary data which had been considered for testing the approprativity of the modeling were entered into ANFIS model. Results were compared by two statistical criterions (R2, RMSE) with empirical ones. Considering the results, it is obvious that our proposed modeling by ANFIS is efficient and valid and it can also be promoted to more general states.

Keywords: bleeding, asphalt film thickness differential, Anfis Modeling

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Authors: Yanling Li, Linying Ji, Zita Oravecz, Timothy R. Brick, Michael D. Hunter, Sy-Miin Chow

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Assessing several individuals intensively over time yields intensive longitudinal data (ILD). Even though ILD provide rich information, they also bring other data analytic challenges. One of these is the increased occurrence of missingness with increased study length, possibly under non-ignorable missingness scenarios. Multiple imputation (MI) handles missing data by creating several imputed data sets, and pooling the estimation results across imputed data sets to yield final estimates for inferential purposes. In this article, we introduce dynr.mi(), a function in the R package, Dynamic Modeling in R (dynr). The package dynr provides a suite of fast and accessible functions for estimating and visualizing the results from fitting linear and nonlinear dynamic systems models in discrete as well as continuous time. By integrating the estimation functions in dynr and the MI procedures available from the R package, Multivariate Imputation by Chained Equations (MICE), the dynr.mi() routine is designed to handle possibly non-ignorable missingness in the dependent variables and/or covariates in a user-specified dynamic systems model via MI, with convergence diagnostic check. We utilized dynr.mi() to examine, in the context of a vector autoregressive model, the relationships among individuals’ ambulatory physiological measures, and self-report affect valence and arousal. The results from MI were compared to those from listwise deletion of entries with missingness in the covariates. When we determined the number of iterations based on the convergence diagnostics available from dynr.mi(), differences in the statistical significance of the covariate parameters were observed between the listwise deletion and MI approaches. These results underscore the importance of considering diagnostic information in the implementation of MI procedures.

Keywords: dynamic modeling, missing data, mobility, multiple imputation

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Authors: Temami Oussama, Bessais Lakhdar, Hamadi Djamal, Abderrahmani Sifeddine

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The analysis of complex structures encourages the engineer to make simplifying assumptions, sometimes attempting the analysis of the whole structure as complex as it is, and it can be done using the finite element method (FEM). In the modeling of complex structures by finite elements, various elements can be used: beam element, membrane element, solid element, plates and shells elements. These elements formulated according to the classical formulation and do not generally share the same nodal degrees of freedom, which complicates the development of a compatible model. The compatibility of the elements with each other is often a difficult problem for modeling complicated structure. This compatibility is necessary to ensure the convergence. To overcome this problem, we have proposed finite elements with a rotational degree of freedom. The study used is based on the strain approach formulation with 2D and 3D formulation with different degrees of freedom at each node. For the comparison and confrontation of results; the finite elements available in ABAQUS/Standard are used.

Keywords: compatibility requirement, complex structures, finite elements, modeling, strain approach

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Authors: Saritdikhun Somasa

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3D printing fabrication has empowered many artists in many fields. Artists who work in stop motion, 3D modeling, toy design, product design, sculpture, and fine arts become one-stop shop operations–where they can design, prototype, and distribute their designs for commercial or fine art purposes. The author has developed a digital sculpting course that fosters digital software, peripheral hardware, and 3D printing with traditional sculpting concept techniques to address the complexities of this multifaceted process, allowing the students to produce complex 3d-printed work. The author will detail the preparation and planning for pre- to post-process 3D printing elements, including software, materials, space, equipment, tools, and schedule consideration for small to medium figurine design statues in a semester-long class. In addition, the author provides insight into teaching challenges in the non-studio space that requires students to work intensively on post-printed models to assemble parts, finish, and refine the 3D printed surface. Even though this paper focuses on the 3D printing processes and techniques for small to medium design statue projects for the Digital Media program, the author hopes the paper will benefit other fields of study such as craft practices, product design, and fine-arts programs. Other schools that might implement 3D printing and fabrication in their programs will find helpful information in this paper, such as a teaching plan, choices of equipment and materials, adaptation for non-studio spaces, and putting together a complete and well-resolved project for students.

Keywords: 3D digital modeling, 3D digital sculpting, 3D modeling, 3D printing, 3D digital fabrication

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Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

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This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: river stage-discharge process, LSSVM, discrete wavelet transform, Ensemble Empirical Decomposition Mode, multi-station modeling

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Authors: Akram Mahdaviparsa, Tamera McCuen, Vahideh Karimimansoob

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Fire service is responsible for protecting life, assets, and natural resources from fire and other hazardous incidents. Search and rescue in unfamiliar buildings is a vital part of firefighters’ responsibilities. Providing firefighters with precise building information in an easy-to-understand format is a potential solution for mitigating the negative consequences of fire hazards. The negative effect of insufficient knowledge about a building’s indoor environment impedes firefighters’ capabilities and leads to lost property. A data rich building information modeling (BIM) is a potentially useful source in three-dimensional (3D) visualization and data/information storage for fire emergency response. Therefore, this research’s purpose is prioritizing the required information for firefighters from the most important information to the least important. A survey was carried out with firefighters working in the Norman Fire Department to obtain the importance of each building information item. The results show that “the location of exit doors, windows, corridors, elevators, and stairs”, “material of building elements”, and “building data” are the three most important information specified by firefighters. The results also implied that the 2D model of architectural, structural and way finding is more understandable in comparison with the 3D model, while the 3D model of MEP system could convey more information than the 2D model. Furthermore, color in visualization can help firefighters to understand the building information easier and quicker. Sufficient internal consistency of all responses was proven through developing the Pearson Correlation Matrix and obtaining Cronbach’s alpha of 0.916. Therefore, the results of this study are reliable and could be applied to the population.

Keywords: BIM, building fire response, ranking, visualization

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Authors: Hayoung Cho, Gabi Cho

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In response to the continuing increase of demands for living environment safety, the Korean government has established and implemented various environmental health policies and set a high priority to the related R&D. However, the level of related technologies such as environmental risk assessment are still relatively low, and there is a need for detailed investment strategies in the field of environmental health research. As scientific research papers can give valuable implications on the development of a certain field, this study analyzed the global research trends in the field of environmental health over the past 10 years (2005~2015). Research topics were extracted from abstracts of the collected SCI papers using topic modeling to study the changes in research trends and discover emerging technologies. The method of topic modeling can improve the traditional bibliometric approach and provide a more comprehensive review of the global research development. The results of this study are expected to help provide insights for effective policy making and R&D investment direction.

Keywords: environmental health, paper analysis, research trends, topic modeling

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Authors: Changqiao Wu, Guoqing Ding, Xin Chen

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In this paper, ways of modeling dynamic measurement systems are discussed. Specially, for linear system with single-input single-output, it could be modeled with shallow neural network. Then, gradient based optimization algorithms are used for searching the proper coefficients. Besides, method with normal equation and second order gradient descent are proposed to accelerate the modeling process, and ways of better gradient estimation are discussed. It shows that the mathematical essence of the learning objective is maximum likelihood with noises under Gaussian distribution. For conventional gradient descent, the mini-batch learning and gradient with momentum contribute to faster convergence and enhance model ability. Lastly, experimental results proved the effectiveness of second order gradient descent algorithm, and indicated that optimization with normal equation was the most suitable for linear dynamic models.

Keywords: dynamic system modeling, neural network, normal equation, second order gradient descent

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Authors: Amin Eslami, Jafar Bolouri Bazaz

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Under active stress conditions, a rigid cantilever retaining wall tends to rotate about a pivot point located within the embedded depth of the wall. For purely granular and cohesive soils, a methodology was previously reported called minimization of moment ratio to determine the location of the pivot point of rotation. The usage of this new methodology is to estimate the rotational stability safety factor. Moreover, the degree of improvement required in a backfill to get a desired safety factor can be estimated by the concept of the shear strength demand. In this article, the accuracy of this method for another type of cantilever walls called Contiguous Bored Pile (CBP) retaining wall is evaluated by using physical modeling technique. Based on observations, the results of moment ratio minimization method are in good agreement with the results of the carried out physical modeling.

Keywords: cantilever retaining wall, physical modeling, minimization of moment ratio method, pivot point

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Authors: Z. Hormozi Moghaddam, M. Mokhtari-Dizaji, M. Movahedin, M. E. Ravari

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Mechanical index (MI) is used for quantifying acoustic cavitation and the relationship between acoustic pressure and the frequency. In this study, modeling of the MI was applied to provide treatment protocol and to understand the effective physical processes on reproducibility of stem cells. The acoustic pressure and MI equations are modeled and solved to estimate optimal MI for 28, 40, 150 kHz and 1 MHz frequencies. Radial and axial acoustic pressure distribution was extracted. To validate the results of the modeling, the acoustic pressure in the water and near field depth was measured by a piston hydrophone. Results of modeling and experiments show that the model is consistent well to experimental results with 0.91 and 0.90 correlation of coefficient (p<0.05) for 1 MHz and 40 kHz. Low intensity ultrasound with 0.40 MI is more effective on the proliferation rate of the spermatogonial stem cells during the seven days of culture, in contrast, high MI has a harmful effect on the spermatogonial stem cells. This model provides proper treatment planning in vitro and in vivo by estimating the cavitation phenomenon.

Keywords: ultrasound, mechanical index, modeling, stem cell

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Authors: Taweechai Nuntawisuttiwong, Natasha Dejdumrong

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Geometric modeling plays an important role in the constructions and manufacturing of curve, surface and solid modeling. Their algorithms are critically important not only in the automobile, ship and aircraft manufacturing business, but are also absolutely necessary in a wide variety of modern applications, e.g., robotics, optimization, computer vision, data analytics and visualization. The calculation and display of geometric objects can be accomplished by these six techniques: Polynomial basis, Recursive, Iterative, Coefficient matrix, Polar form approach and Pyramidal algorithms. In this research, the coefficient matrix (simply called monomial form approach) will be used to model polynomial rectangular patches, i.e., Said-Ball, Wang-Ball, DP, Dejdumrong and NB1 surfaces. Some examples of the monomial forms for these surface modeling are illustrated in many aspects, e.g., construction, derivatives, model transformation, degree elevation and degress reduction.

Keywords: monomial forms, rectangular surfaces, CAGD curves, monomial matrix applications

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Authors: Melih Cattik

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The present study investigate effectiveness of video modeling procedures on request an item behavior of children with ASD. Two male and a female children with ASD participated in the study. A multiple baseline across participant single-subject design was used to evaluate the effects of the video modeling procedures on request an item behavior. During baseline, no prompts were presented to participants. In the intervention phase, the teacher gave video model to the participant and than created opportunity for request an item to him/her. When the first participant reached to criterion, the second participant began intervention. This procedure continued till all participants completed intervention. Finally, all three participants learned to request an item behavior. Based upon findings of this study, it will make suggestions to future researches.

Keywords: autism spectrum disorders, video modeling procedures, request an item behavior, single subject design

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Authors: Rafayel Azizyan, Valeri Arakelyan, Aram Gevorgyan, Varduhi Balayan, Emil Gevorgyan

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Currently, mathematical and computer modeling are widely used in different biological studies to predict or assess behavior of such complex systems as biological ones. This study deals with mathematical and computer modeling of bi-substrate enzymatic reactions, which play an important role in different biochemical pathways. The main objective of this study is to represent the results from in silico investigation of bi-substrate enzymatic reactions in the presence of uncompetitive inhibitors, as well as to describe in details the inhibition effects. Four models of uncompetitive inhibition were designed using different software packages. Particularly, uncompetitive inhibitor to the first [ES1] and the second ([ES1S2]; [FS2]) enzyme-substrate complexes have been studied. The simulation, using the same kinetic parameters for all models allowed investigating the behavior of reactions as well as determined some interesting aspects concerning influence of different cases of uncompetitive inhibition. Besides that shown, that uncompetitive inhibitors exhibit specific selectivity depending on mechanism of bi-substrate enzymatic reaction.

Keywords: mathematical modeling, bi-substrate enzymatic reactions, reversible inhibition

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Authors: Rushiraj Heshi, Smriti Bhandari

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Master Data Management requires creation of Central repository, applying constraints on Repository and designing processes to manage data. Designing of Repository, constraints on repository and business processes is very tedious and time consuming task for large Enterprise. Hence Visual Repository, constraints and Process (Workflow) modeling is the most critical step in Master Data Management.In this paper, we realize a Visual Modeling tool for implementing Repositories, Constraints and Processes based on Eclipse Plugin using GMF/EMF which follows principles of Model Driven Engineering (MDE).

Keywords: EMF, GMF, GEF, repository, constraint, process

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Authors: J. Fernandez de Canete, P. Del Saz Orozco, I. Garcia-Moral, A. Akhrymenka

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Object-oriented modeling is spreading in current simulation of wastewater treatments plants through the use of the individual components of the process and its relations to define the underlying dynamic equations. In this paper, we describe the use of the free-software OpenModelica simulation environment for the object-oriented modeling of an activated sludge process under feedback control. The performance of the controlled system was analyzed both under normal conditions and in the presence of disturbances. The object-oriented described approach represents a valuable tool in teaching provides a practical insight in wastewater process control field.

Keywords: object-oriented programming, activated sludge process, OpenModelica, feedback control

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Authors: Erzen Muharemi, Emmanuel De Jaeger, Jos Knockaert

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The work presented here investigates the modeling of power electronics converters in terms of their harmonic production. Specifically, it addresses high-frequency emissions in the range of 2-150 kHz, referred to as supraharmonics. This paper models a conventional converter, namely the boost converter used as an active power factor corrector (APFC). Furthermore, the modeling is extended to the case of the interleaved boost converter, which offers advantages such as halving the emissions. Finally, a comparison between the theoretical, numerical, and experimental results will be provided.

Keywords: APFC, boost converter, converter modeling, double fourier series, supraharmonics

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Authors: Bothinah Altaf, Gary Montague, Elaine B. Martin

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This study involves the modeling and monitoring of an ammonia synthesis fixed-bed reactor using partial least squares (PLS) and its variants. The process exhibits complex dynamic behavior due to the presence of heat recycling and feed quench. One limitation of static PLS model in this situation is that it does not take account of the process dynamics and hence dynamic PLS was used. Although it showed, superior performance to static PLS in terms of prediction, the monitoring scheme was inappropriate hence adaptive PLS was considered. A limitation of adaptive PLS is that non-conforming observations also contribute to the model, therefore, a new adaptive approach was developed, robust adaptive dynamic PLS. This approach updates a dynamic PLS model and is robust to non-representative data. The developed methodology showed a clear improvement over existing approaches in terms of the modeling of the reactor and the detection of faults.

Keywords: ammonia synthesis fixed-bed reactor, dynamic partial least squares modeling, recursive partial least squares, robust modeling

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Authors: Noora Al-Shanfari, M. Mazharul Islam

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The cumulative incidence function (CIF) is a fundamental approach for analyzing survival data in the presence of competing risks, which estimates the marginal probability for each competing event. Parametric modeling of CIF has the advantage of fitting various shapes of CIF and estimates the impact of covariates with maximum efficiency. To calculate the total CIF's covariate influence using a parametric model., it is essential to parametrize the baseline of the CIF. As the CIF is an improper function by nature, it is necessary to utilize an improper distribution when applying parametric models. The Gompertz distribution, which is an improper distribution, is limited in its applicability as it only accounts for monotone hazard shapes. The generalized Gompertz distribution, however, can adapt to a wider range of hazard shapes, including unimodal, bathtub, and monotonic increasing or decreasing hazard shapes. In this paper, the generalized Gompertz distribution is used to parametrize the baseline of the CIF, and the parameters of the proposed model are estimated using the maximum likelihood approach. The proposed model is compared with the existing Gompertz model using the Akaike information criterion. Appropriate statistical test procedures and model-fitting criteria will be used to test the adequacy of the model. Both models are applied to the ‘colon’ dataset, which is available in the “biostat3” package in R.

Keywords: competing risks, cumulative incidence function, improper distribution, parametric modeling, survival analysis

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Authors: Parveen Kumar

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This article discusses institute information resources. Information, in its most restricted technical sense, is a sequence of symbols that can be interpreted as message information can be recorded as signs, or transmitted as signals. Information is any kind of event that affects the state of a dynamic system. Conceptually, information is the message being conveyed. This concept has numerous other meanings in different contexts. Moreover, the concept of information is closely related to notions of constraint, communication, control, data, form, instruction, knowledge, meaning, mental stimulus, pattern, perception, representation, and especially entropy.

Keywords: institutions, information institutions, information services for mission-oriented institute, pattern

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Authors: Yousef Abu Nahleh, Arun Kumar, Fugen Daver, Reham Al-Hindawi

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Despite the availability of natural disaster related time series data for last 110 years, there is no forecasting tool available to humanitarian relief organizations to determine forecasts for emergency logistics planning. This study develops a forecasting tool based on identifying probability of disaster for each country in the world by using decision tree modeling. Further, the determination of aggregate forecasts leads to efficient pre-disaster planning. Based on the research findings, the relief agencies can optimize the various resources allocation in emergency logistics planning.

Keywords: decision tree modeling, forecasting, humanitarian relief, emergency supply chain

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Authors: Vladimir A. Vinnikov

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The paper proposes a model of an inhomogeneous rock mass with initially random distribution of microcracks on mineral grain boundaries. It describes the behavior of cracks in a medium under the effect of thermal field, the medium heated instantaneously to a predetermined temperature. Crack growth occurs according to the concept of fracture mechanics provided that the stress intensity factor K exceeds the critical value of Kc. The modeling of thermally induced acoustic emission memory effects is based on the assumption that every event of crack nucleation or crack growth caused by heating is accompanied by a single acoustic emission event. Parameters of the thermally induced acoustic emission memory effect produced by cyclic heating and cooling (with the temperature amplitude increasing from cycle to cycle) were calculated for several rock texture types (massive, banded, and disseminated). The study substantiates the adaptation of the proposed model to humidity interference with the thermally induced acoustic emission memory effect. The influence of humidity on the thermally induced acoustic emission memory effect in quasi-homogeneous and banded rocks is estimated. It is shown that such modeling allows the structure and texture of rocks to be taken into account and the influence of interference factors on the distinctness of the thermally induced acoustic emission memory effect to be estimated. The numerical modeling can be used to obtain information about the thermal impacts on rocks in the past and determine the degree of rock disturbance by means of non-destructive testing.

Keywords: degree of rock disturbance, non-destructive testing, thermally induced acoustic emission memory effects, structure and texture of rocks

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Authors: Jamil Khalil Izraqi

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This paper investigates the transition of a 1970 Volkswagen Beetle from an internal combustion engine (ICE) to an EV using Matlab/Simulink modeling and simulation. The performance of the EV drivetrain system was simulated under various operating conditions, including standard and custom driving cycles in Turkey and Jordan (Amman), respectively. The results of this paper indicate that the transition is viable and that modeling and simulation can help in understanding the performance and efficiency of the electric drivetrain system, including battery pack, power electronics, and brushless direct current (BLDC) Motor.

Keywords: BLDC, buck-boost, inverter, SOC, drive-cycle

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Authors: Hesham A. Khalek, Shafik S. Khoury, Remon F. Aziz, Mohamed A. Hakam

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Slipforming operation’s linearity is a source of planning complications, and operation is usually subjected to bottlenecks at any point, so careful planning is required in order to achieve success. On the other hand, Discrete-event simulation concepts can be applied to simulate and analyze construction operations and to efficiently support construction scheduling. Nevertheless, preparation of input data for construction simulation is very challenging, time-consuming and human prone-error source. Therefore, to enhance the benefits of using DES in construction scheduling, this study proposes an integrated module to establish a framework for automating the generation of time schedules and decision support for Slipform construction projects, particularly through the project feasibility study phase by using data exchange between project data stored in an Intermediate database, DES and Scheduling software. Using the stored information, proposed system creates construction tasks attribute [e.g. activities durations, material quantities and resources amount], then DES uses all the given information to create a proposal for the construction schedule automatically. This research is considered a demonstration of a flexible Slipform project modeling, rapid scenario-based planning and schedule generation approach that may be of interest to both practitioners and researchers.

Keywords: discrete-event simulation, modeling, construction planning, data exchange, scheduling generation, EZstrobe

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Authors: Rene Hellmuth, Jorg Frohnmayer

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The requirements of the factory planning and the building concerned have changed in the last years. Factory planning has the task of designing products, plants, processes, organization, areas, and the building of a factory. Regular restructuring gains more importance in order to maintain the competitiveness of a factory. Even today, the methods and process models used in factory planning are predominantly based on the classical planning principles of Schmigalla, Aggteleky and Kettner, which, however, are not specifically designed for reorganization. In addition, they are designed for a largely static environmental situation and a manageable planning complexity as well as for medium to long-term planning cycles with a low variability of the factory. Existing approaches already regard factory planning as a continuous process that makes it possible to react quickly to adaptation requirements. However, digital factory models are not yet used as a source of information for building data. Approaches which consider building information modeling (BIM) or digital factory models in general either do not refer to factory conversions or do not yet go beyond a concept. This deficit can be further substantiated. A method for factory conversion planning using a current digital building model is lacking. A corresponding approach must take into account both the existing approaches to factory planning and the use of digital factory models in practice. A literature review will be conducted first. In it, approaches to classic factory planning and approaches to conversion planning are examined. In addition, it will be investigated which approaches already contain digital factory models. In the second step, an approach is presented how digital factory models based on building information modeling can be used as a basis for augmented reality tablet applications. This application is suitable for construction sites and provides information on the costs and time required for conversion variants. Thus a fast decision making is supported. In summary, the paper provides an overview of existing factory planning approaches and critically examines the use of digital tools. Based on this preliminary work, an approach is presented, which suggests the sensible use of digital factory models for decision support in the case of conversion variants of the factory building. The augmented reality application is designed to summarize the most important information for decision-makers during a reconstruction process.

Keywords: augmented reality, digital factory model, factory planning, restructuring

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Authors: K. D. Sharma, M. Parida, S. S. Jain, Anju Saini, V. K. Katiyar

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Air quality models form one of the most important components of an urban air quality management plan. Various statistical modeling techniques (regression, multiple regression and time series analysis) have been used to predict air pollution concentrations in the urban environment. These models calculate pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. Artificial neural network (ANN) is increasingly used as an alternative tool for modeling the pollutants from vehicular traffic particularly in urban areas. In the present paper, an attempt has been made to model traffic air pollution, specifically CO concentration using neural networks. In case of CO concentration, two scenarios were considered. First, with only classified traffic volume input and the second with both classified traffic volume and meteorological variables. The results showed that CO concentration can be predicted with good accuracy using artificial neural network (ANN).

Keywords: air quality management, artificial neural network, meteorological variables, statistical modeling

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Authors: José Luis Carrillo-Medina, Roberto Latorre

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Experimental evidence has revealed that different living neural systems can sign their output signals with some specific neural signature. Although experimental and modeling results suggest that neural signatures can have an important role in the activity of neural networks in order to identify the source of the information or to contextualize a message, the functional meaning of these neural fingerprints is still unclear. The existence of cellular mechanisms to identify the origin of individual neural signals can be a powerful information processing strategy for the nervous system. We have recently built different models to study the ability of a neural network to process information based on the emission and recognition of specific neural fingerprints. In this paper we further analyze the features that can influence on the information processing ability of this kind of networks. In particular, we focus on the role that the duration of a refractory period in each neuron after emitting a signed message can play in the network collective dynamics.

Keywords: neural signature, neural fingerprint, processing based on signal identification, self-organizing neural network

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Authors: Oumaima Lahmar

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This paper aims to define a structured topography for finance researchers seeking to navigate the body of knowledge in their extrapolation of finance phenomena. To make sense of the body of knowledge in finance, a probabilistic topic modeling approach is applied on 6000 abstracts of academic articles published in three top journals in finance between 1976 and 2020. This approach combines both machine learning techniques and natural language processing to statistically identify the conjunctions between research articles and their shared topics described each by relevant keywords. The topic modeling analysis reveals 35 coherent topics that can well depict finance literature and provide a comprehensive structure for the ongoing research themes. Comparing the extracted topics to the Journal of Economic Literature (JEL) classification system, a significant similarity was highlighted between the characterizing keywords. On the other hand, we identify other topics that do not match the JEL classification despite being relevant in the finance literature.

Keywords: finance literature, textual analysis, topic modeling, perplexity

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Authors: Abdelghani Leghouchi

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This study aims to predict the consequences associated with the propagation of the flood wave that may occur after the failure of the Taksebt dam and suggest an efficient emergency action plan (EAP) for mitigation purposes. To achieve the objectives of this study, the hydrodynamic model HEC-RAS 2D was used for the flood routing of the dam break wave, which gave an estimate of the hydraulic characteristics downstream the Taksebt dam. Geospatial analysis of the simulation results conducted in a Geographic information system (GIS) environment showed that many residential areas are considered to be in danger in case of the Taksebt dam break event. Based on the obtained results, an emergency actions plan was suggested to moderate the causalities in the downstream area at risk. Overall, the present study showed that the integration of 2D hydraulic modeling and GIS provides great capabilities in providing realistic view of the dam break wave propagation that enhances assessing the associated risks and proposing appropriate mitigation measures.

Keywords: taksebt dam, dam break, wave propagation time, HEC-RAS 2D

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Authors: Kenneth O. Otasowie, Matthew Ikuabe, Clinton Aigbavboa, Ayodeji Oke

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The quantity surveying (QS) profession is one of the professions in the construction industry, and it is saddled with the responsibility of measuring the number of materials as well as the workmanship required to get work done in the industry. This responsibility is vital to the success of a construction project as it determines if a project will be completed on time, within budget, and up to the required standard. However, the practice has been criticised severally for failure to accurately execute her responsibility. The need to reduce errors, inaccuracies and omissions has made the adoption of modern technologies such as building information modeling (BIM) inevitable in its practice. Nevertheless, there are barriers to the adoption of BIM in QS practice in South Africa (SA). Thus, this study aims to investigate these barriers. A survey design was adopted. A total number of one hundred and fifteen (115) questionnaires were administered to quantity surveyors in Guateng Province, SA, and ninety (90) were returned and found suitable for analysis. Collected data were analysed using percentage, mean item score, standard deviation, one-sample t-test, and Kruskal-Wallis. The findings show that lack of BIM expertise, lack of government enforcement, resistance to change, and no client demand for BIM are the most significant barriers to the adoption of BIM in QS practice. As a result, this study recommends that trainings on BIM technology be prioritised, and government must take the lead in BIM adoption in the country, particularly in public projects.

Keywords: barriers, BIM, quantity surveying practice, South Africa

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