Search results for: integrated modeling approach

Authors: Lan Luo

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In China’s construction industry, it is a normal practice to separately subcontract the decoration engineering part from construction engineering, and Building Information Modeling (BIM) is also done separately. Application of BIM in decoration engineering should be integrated with other disciplines, but Chinese current practice makes this very difficult and complicated. Currently, there are three barriers in the auditing of BIM application in decoration engineering in China: heavy workload; scarcity of qualified professionals; and lack of literature concerning audit contents, standards, and methods. Therefore, it is significant to perform research on what (contents) should be evaluated, in which phase, and by whom (professional qualifications) in BIM application in decoration construction so that the application of BIM can be promoted in a better manner. Based on this consideration, four principles of BIM auditing are proposed: Comprehensiveness of information, accuracy of data, aesthetic attractiveness of appearance, and scheme optimization. In the model audit, three methods should be used: Collision, observation, and contrast. In addition, BIM auditing at six stages is discussed and a checklist for work items and results to be submitted is proposed. This checklist can be used for reference by decoration project participants.

Keywords: audit, evaluation, dimensions, methods, standards, BIM application in decoration engineering projects

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Authors: Zhanat Umarova

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Until the present time, modeling of the pores form influence on the hydraulic resistance of membranes and their permeability has not been analyzed. The aim of the given work is the theoretical consideration of the issue on the productivity of polymer membranes with the profile pores and determination of the optimum form of pores.

Keywords: modeling, polymer membranes, permeability, pore’s density

Procedia PDF Downloads 366

Authors: Atakan Aral Ormancı, Tuğçe Arslantaş, Murat Özcü

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This study presents the design and implementation of an experimental chassis-level system for various control applications. Specifically, the height level of the chassis is controlled using proportional integrated derivative, fuzzy logic, and deep learning control methods. Real-time data obtained from height and pressure sensors installed in a 6x2 truck chassis, in combination with pulse-width modulation signal values, are utilized during the tests. A prototype pneumatic system of a 6x2 truck is added to the setup, which enables the Smart Pneumatic Actuators to function as if they were in a real-world setting. To obtain real-time signal data from height sensors, an Arduino Nano is utilized, while a Raspberry Pi processes the data using Matlab/Simulink and provides the correct output signals to control the Smart Pneumatic Actuator in the truck chassis. The objective of this research is to optimize the time it takes for the chassis to level down and up under various loads. To achieve this, proportional integrated derivative control, fuzzy logic control, and deep learning techniques are applied to the system. The results show that the deep learning method is superior in optimizing time for a non-linear system. Fuzzy logic control with a triangular membership function as the rule base achieves better outcomes than proportional integrated derivative control. Traditional proportional integrated derivative control improves the time it takes to level the chassis down and up compared to an uncontrolled system. The findings highlight the superiority of deep learning techniques in optimizing the time for a non-linear system, and the potential of fuzzy logic control. The proposed approach and the experimental results provide a valuable contribution to the field of control, automation, and systems engineering.

Keywords: automotive, chassis level control, control systems, pneumatic system control

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Authors: Edgard Gnansounoua, Pavel Vaskan, Elia Ruiz Pachón

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This work addresses the economic and environmental performance of integrated biorefineries based on sugarcane juice and residues in the context of Brazil. We have considered four multiproduct scenarios; two from existing Brazilian sugar mills and the others from ethanol autonomous distilleries. They are integrated biorefineries producing first (1G) and second (2G) generation ethanol, sugar, molasses (for animal feed) and electricity. We show the results for the analysis and comparison of the different scenarios using a techno-economic value-based approach and LCA methodology. We have found that all the analysed scenarios show positive values of Climate change and Fossil depletion reduction as compared to the reference systems. However the scenario producing only ethanol shows less efficiency in Human toxicity, Freshwater ecotoxicity and Freshwater eutrophication impacts. The best economic configuration is provided by the scenario with the largest ethanol production. On the other hand, the best environmental performance is presented by the scenario with full integration sugar – 1G2G ethanol production. The integration of 2G based residues in a 1G ethanol production plant leads to positive environmental impacts compared to the conventional 1G industrial plant but proves to be more expensive.

Keywords: sugarcane, biorefinery, 1G/2G bioethanol integration, LCA, Brazil

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Authors: Ridha Salhi, Mondher Labidi, Fethi Choubani

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Metamaterials have attracted much attention in recent years because of their electromagnetic exquisite proprieties. We will present, in this paper, the modeling of three metamaterial structures by equivalent circuit model. We begin by modeling the SRR (Split Ring Resonator), then we model the HIS (High Impedance Surfaces), and finally, we present the model of the CPW (Coplanar Wave Guide). In order to validate models, we compare the results obtained by an equivalent circuit models with numerical simulation.

Keywords: metamaterials, SRR, HIS, CPW, IDC

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Authors: Ashwani Kumar

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Abstract- This study presents an analytical modeling approach for analyzing the drain current behavior in Tunnel Field-Effect Transistor (TFET) biosensors used for the detection of DNA biomolecules. The proposed model focuses on elucidating the relationship between the drain current and the presence of DNA biomolecules, taking into account the impact of various device parameters and biomolecule characteristics. Through comprehensive analysis, the model offers insights into the underlying mechanisms governing the sensing performance of TFET biosensors, aiding in the optimization of device design and operation. A non-local tunneling model is incorporated with other essential models to accurately trace the simulation and modeled data. An experimental validation of the model is provided, demonstrating its efficacy in accurately predicting the drain current response to DNA biomolecule detection. The sensitivity attained from the analytical model is compared and contrasted with the ongoing research work in this area.

Keywords: biosensor, double-gate TFET, DNA detection, drain current modeling, sensitivity

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Authors: M. M. Wagh, V. V. Kulkarni

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The rising economic activities, growing population and improving living standards of world have led to a steady growth in its appetite for quality and quantity of energy services. As the economy expands the electricity demand is going to grow further, increasing the challenges of the more generation and stresses on the utility grids. Appropriate energy model will help in proper utilization of the locally available renewable energy sources such as solar, wind, biomass, small hydro etc. to integrate in the available grid, reducing the investments in energy infrastructure. Further to these new technologies like smart grids, decentralized energy planning, energy management practices, energy efficiency are emerging. In this paper, the attempt has been made to study and review the recent energy planning models, energy forecasting models, and renewable energy integration models. In addition, various modeling techniques and tools are reviewed and discussed.

Keywords: energy modeling, integration of renewable energy, energy modeling tools, energy modeling techniques

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Authors: Lindy Van Vliet, Saloni Phadke, Anthea Nelson, Ann Gallant

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Holistic and patient-centred palliative care and support require an integrated system of care that includes health and social service providers working together to ensure that patients and families have access to the care they need. The objective of this study is to further explore and understand the benefits and challenges of mobilizing multidisciplinary care teams for health care professionals and social service providers. Drawing on an interpretivist, exploratory, qualitative design, our multidisciplinary research team (medicine, nursing and social work) conducted interviews with 15 health care and social service providers in the Ottawa region. Interview data was audio-recorded, transcribed, and analyzed using a reflexive thematic analysis approach. The data deepens our understandings of the facilitators and barriers posed by multidisciplinary care teams. Three main findings emerged: First, the data highlighted the benefits of multidisciplinary care teams for both patient outcomes and quality of life and provider mental health; second, the data showed that the lack of a system-wide integrated communication system reduces the quality of patient care and increases provider stress while working in multidisciplinary care teams; finally, the data demonstrated the existence of implicit hierarchies between disciplines, this coupled with different disciplinary perspectives of palliative care provision can lead to friction and challenges within care teams. These findings will have important implications for the future of palliative care as they will help to facilitate and build stronger person-centred/relationship-centred palliative care practices by naming the challenges faced by multidisciplinary palliative care teams and providing examples of best practices.

Keywords: public health palliative care, palliative care nursing, care networks, integrated health care, palliative care approach, public health, multidisciplinary work, care teams

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Authors: Vahid Ebrahimipour

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Word representation and context meaning of text-based documents play an essential role in knowledge modeling. Business procedures written in natural language are meant to store technical and engineering information, management decision and operation experience during the production system life cycle. Context meaning representation is highly dependent upon word sense, lexical relativity, and sematic features of the argument. This paper proposes a method for lexical semantic analysis and context meaning representation of maintenance activity in a mass production system. Our approach constructs a straightforward lexical semantic approach to analyze facilitates semantic and syntactic features of context structure of maintenance report to facilitate translation, interpretation, and conversion of human-readable interpretation into computer-readable representation and understandable with less heterogeneity and ambiguity. The methodology will enable users to obtain a representation format that maximizes shareability and accessibility for multi-purpose usage. It provides a contextualized structure to obtain a generic context model that can be utilized during the system life cycle. At first, it employs a co-occurrence-based clustering framework to recognize a group of highly frequent contextual features that correspond to a maintenance report text. Then the keywords are identified for syntactic and semantic extraction analysis. The analysis exercises causality-driven logic of keywords’ senses to divulge the structural and meaning dependency relationships between the words in a context. The output is a word contextualized representation of maintenance activity accommodating computer-based representation and inference using OWL/RDF.

Keywords: lexical semantic analysis, metadata modeling, contextual meaning extraction, ontology modeling, knowledge representation

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Authors: Arun Prabhakar

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Threat modeling is an important activity carried out in the initial stages of the development lifecycle that helps in building proactive security measures in the product. Though there are many techniques and tools available today, one of the common challenges with the traditional methods is the lack of a systematic approach in identifying security threats. The proposed solution describes an organized model by defining ontologies that help in building patterns to enumerate threats. The concepts of graph theory are applied to build the pattern for discovering threats for any given scenario. This graph-based solution also brings in other benefits, making it a customizable and scalable model.

Keywords: directed acyclic graph, ontology, patterns, threat identification, threat modeling

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Authors: Azzam Alosaimi

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Different countries attempt to reduce energy demands and Greenhouse Gas (GHG) emissions to mitigate global warming potential. They set different building codes to regulate excessive building’s energy losses. Energy losses occur due to pressure difference between the indoor and outdoor environments, and thus, heat transfers from one region to another. One major sources of energy loss is known as building airtightness. Building airtightness is the fundamental feature of the building envelope that directly impacts infiltration. Most of international building codes require minimum performance for new construction to ensure acceptable airtightness. The execution of airtightness required standards has become more challenging in recent years due to a lack of expertise and equipment, making it costly and time-consuming. Hence, researchers have developed predictive models to predict buildings infiltration rates to meet building codes and to reduce energy and cost. This research applies a theoretical modeling approach using Matlab software to predict mean infiltration rate distributions and total heat loss of Saudi Arabia’s housing stock.

Keywords: infiltration rate, energy demands, heating loss, cooling loss, carbon emissions

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Authors: Jhe-Hao Huang, Kun-Da Wu, Wei-Cheng Shih, Jui-Pin Hung

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This study presented the investigation on the dynamic characteristics of a spindle tool system by experimental and finite element modeling approaches. As well known facts, the machining stability is greatly determined by the dynamic characteristics of the spindle tool system. Therefore, understanding the factors affecting dynamic behavior of a spindle tooling system is a prerequisite in dominating the final machining performance of machine tool system. To this purpose, a physical spindle unit was employed to assess the dynamic characteristics by vibration tests. Then, a three-dimensional finite element model of a high-speed spindle system integrated with tool holder was created to simulate the dynamic behaviors. For modeling the angular contact bearings, a series of spring elements were introduced between the inner and outer rings. The spring constant can be represented by the contact stiffness of the rolling bearing based on Hertz theory. The interface characteristic between spindle nose and tool holder taper can be quantified from the comparison of the measurements and predictions. According to the results obtained from experiments and finite element predictions, the vibration behavior of the spindle is dominated by the bending deformation of the spindle shaft in different modes, which is further determined by the stiffness of the bearings in spindle housing. Also, the spindle unit with tool holder shows a different dynamic behavior from that of spindle without tool holder. This indicates the interface property between tool holder and spindle nose plays an dominance on the dynamic characteristics the spindle tool system. Overall, the dynamic behaviors the spindle with and without tool holder can be successfully investigated through the finite element model proposed in this study. The prediction accuracy is determined by the modeling of the rolling interface of ball bearings in spindles and the interface characteristics between tool holder and spindle nose. Besides, identifications of the interface characteristics of a ball bearing and spindle tool holder are important for the refinement of the spindle tooling system to achieve the optimum machining performance.

Keywords: contact stiffness, dynamic characteristics, spindle, tool holder interface

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Authors: Mohammad Reza Mohammadian, Dariush Sattarzadeh, Mir Mohammad Javad Poor Hadi Hosseini

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Population growth, urban development and urban buildup have disturbed the balance between the nature and the city, and so leading to the loss of quality of sustainability of proximity to rivers. While in the past, the sides of urban rivers were considered as urban green space. Urban rivers and their sides that have environmental, social and economic values are important to achieve sustainable development. So far, efforts have been made at various scales in various cities around the world to revitalize these areas. On the other hand, biophilic design is an innovative design approach in which attention to natural details and relation to nature is a fundamental concept. The purpose of this study is to provide an integrated framework of urban design using the potential of urban rivers (in order to increase sustainability) with a biophilic design approach to be used in cities in developing countries. The methodology of the research is based on the collection of data and information from research and projects including a study on biophilic design, investigations and projects related to the urban rivers, and a review of the literature on sustainable urban development. Then studying the boundary of urban rivers is completed by examining case samples. Eventually, integrated framework of urban design, to design the boundaries of urban rivers in the cities of developing countries is presented regarding the factors affecting the design of these areas. The result shows that according to this framework, the potential of the river banks is utilized to increase not only the environmental sustainability but also social, economic and physical stability with regard to water, light, and the usage of indigenous materials, etc.

Keywords: urban rivers, biophilic design, urban sustainability, nature

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Authors: M. Eskandarighadi, C. R. McGann

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It is observed from past experiences of earthquakes that local site conditions can significantly affect the strong ground motion characteristics experience at the site. One-dimensional seismic site response analysis is the most common approach for investigating site response. This approach assumes that soil is homogeneous and infinitely extended in the horizontal direction. Therefore, tying side boundaries together is one way to model this behavior, as the wave passage is assumed to be only vertical. However, 1D analysis cannot capture the 2D nature of wave propagation, soil heterogeneity, and 2D soil profile with features such as inclined layer boundaries. In contrast, 2D seismic site response modeling can consider all of the mentioned factors to better understand local site effects on strong ground motions. 2D wave propagation and considering that the soil profile on the two sides of the model may not be identical clarifies the importance of a boundary condition on each side that can minimize the unwanted reflections from the edges of the model and input appropriate loading conditions. Ideally, the model size should be sufficiently large to minimize the wave reflection, however, due to computational limitations, increasing the model size is impractical in some cases. Another approach is to employ free-field boundary conditions that take into account the free-field motion that would exist far from the model domain and apply this to the sides of the model. This research focuses on implementing free-field boundary conditions in OpenSees for 2D site response analysisComparisons are made between 1D models and 2D models with various boundary conditions, and details and limitations of the developed free-field boundary modeling approach are discussed.

Keywords: boundary condition, free-field, opensees, site response analysis, wave propagation

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Authors: A. M. Naraghi, V. Gonzalez, M. O'Sullivan, C. G. Walker, M. Poshdar, F. Ying, M. Abdelmegid

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Discrete Event Simulation (DES) and Agent Based Simulation (ABS) are two simulation approaches that have been proposed to support decision-making in the construction industry. Despite the wide use of these simulation approaches in the construction field, their applications for production and material planning is still limited. This is largely due to the dynamic and complex nature of construction material supply chain systems. Moreover, managing the flow of construction material is not well integrated with site logistics in traditional construction planning methods. This paper presents a hybrid of DES and ABS to simulate on-site and off-site material supply processes. DES is applied to determine the best production scenarios with information of on-site production systems, while ABS is used to optimize the supply chain network. A case study of a construction piling project in New Zealand is presented illustrating the potential benefits of using the proposed hybrid simulation model in construction material flow planning. The hybrid model presented can be used to evaluate the impact of different decisions on construction supply chain management.

Keywords: construction supply-chain management, simulation modeling, decision-support tools, hybrid simulation

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Authors: Quoc Ngoc Phan, Hieu Van Nguyen, Minh Hong Nguyen

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This study presents an integrated approach using Mercury Injection Capillary Pressure (MICP) and petrographic analysis to assess the seal quality of the inter-bedded shale formations which are considered the intra-formation top seals of hydrocarbon bearing zones in Green Dragon structure. Based on the hydrocarbon column height (HCH) at leak point derived from capillary pressure data, four seal types were identified. Furthermore, the results of scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis were interpreted to clarify the influence of clay minerals on seal capacity. The result of the study indicated that the inter-bedded shale formations are the good sealing quality with a majority of analyzed samples ranked type A and B seals in the sample set. Both seal types occurred mainly in mudstones with pore radius estimated less than 0.251 µm. Overall, type A and B seals contained a large amount of authigenic clay minerals such as illite, chlorite which showed the complexity of morphological arrangement in pore space. Conversely, the least common seal type C and D were presented in moderately compacted sandstones with more open pore radius. It is noticeable that there was a reduction of illite and chlorite in clay mineral fraction of these seal type. It is expected that the integrated analysis approach using Mercury Injection Capillary Pressure and petrographic data employed in this study can be applied to assess the sealing quality of future well sites in Green Dragon or other structures.

Keywords: seal capacity, hydrocarbon height column, seal type, SEM, XRD

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Authors: N. Nivedita, S. Durbha

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Critical Infrastructure (CI) consists of services and technological networks such as healthcare, transport, water supply, electricity supply, information technology etc. These systems are necessary for the well-being and to maintain effective functioning of society. Critical Infrastructures can be represented as nodes in a network where they are connected through a set of links depicting the logical relationship among them; these nodes are interdependent on each other and interact with each at other at various levels, such that the state of each infrastructure influences or is correlated to the state of another. Disruption in the service of one infrastructure nodes of the network during a disaster would lead to cascading and escalating disruptions across other infrastructures nodes in the network. The operation of Healthcare Infrastructure is one such Critical Infrastructure that depends upon a complex interdependent network of other Critical Infrastructure, and during disasters it is very vital for the Healthcare Infrastructure to be protected, accessible and prepared for a mass casualty. To reduce the consequences of a disaster on the Critical Infrastructure and to ensure a resilient Critical Health Infrastructure network, knowledge, understanding, modeling, and analyzing the inter-dependencies between the infrastructures is required. The paper would present inter-dependencies related to Healthcare Critical Infrastructure based on Hierarchical Coloured Petri Nets modeling approach, given a flood scenario as the disaster which would disrupt the infrastructure nodes. The model properties are being analyzed for the various state changes which occur when there is a disruption or damage to any of the Critical Infrastructure. The failure probabilities for the failure risk of interconnected systems are calculated by deriving a reachability graph, which is later mapped to a Markov chain. By analytically solving and analyzing the Markov chain, the overall vulnerability of the Healthcare CI HCPN model is demonstrated. The entire model would be integrated with Geographic information-based decision support system to visualize the dynamic behavior of the interdependency of the Healthcare and related CI network in a geographically based environment.

Keywords: critical infrastructure interdependency, hierarchical coloured petrinet, healthcare critical infrastructure, Petri Nets, Markov chain

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Authors: Rawaa Maher, Ahmed Allam, Haruichi Kanaya, Adel B. Abdelrahman

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In this paper, a compact, high-efficiency integrated rectenna is presented to operate in the 2.45 GHz band. A comparison between two rectifier topologies is performed to verify the benefits of removing the matching network from the rectifier. A rectifier high conversion efficiency of 74.1% is achieved. To complete the rectenna system, a novel omnidirectional antenna with high gain (3.72 dB) and compact size (25 mm * 29 mm) is designed and fabricated. The same antenna is used with a reflector for raising the gain to nearly 8.3 dB. The simulation and measurement results of the antenna are in good agreement.

Keywords: internet of things, integrated rectenna, rectenna, RF energy harvesting, wireless sensor networks(WSN)

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Authors: Diogo Ferreira Lima Filho, José Roberto Amazonas

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Nanotechnology opens the door to new paradigms that introduces a variety of novel tools enabling a plethora of potential applications in the biomedical, industrial, environmental, and military fields. This work proposes an integrated node model by applying the same concepts of TCNet to networks of nanodevices where the nodes are cooperatively interconnected with a low-complexity Mealy Machine (MM) topology integrating in the same electronic system the modules necessary for independent operation in wireless sensor networks (WSNs), consisting of Rectennas (RF to DC power converters), Code Generators based on Finite State Machine (FSM) & Trellis Decoder and On-chip Transmit/Receive with autonomy in terms of energy sources applying the Energy Harvesting technique. This approach considers the use of a Graphene Composite Substrate (GCS) for the integrated electronic circuits meeting the following characteristics: mechanical flexibility, miniaturization, and optical transparency, besides being ecological. In addition, graphene consists of a layer of carbon atoms with the configuration of a honeycomb crystal lattice, which has attracted the attention of the scientific community due to its unique Electrical Characteristics.

Keywords: composite substrate, energy harvesting, finite state machine, graphene, nanotechnology, rectennas, wireless sensor networks

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Authors: Houda Abadlia, Nadia Smairi, Khaled Ghedira

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Multiobjective Particle Swarm Optimization (MOPSO) has shown an effective performance for solving test functions and real-world optimization problems. However, this method has a premature convergence problem, which may lead to lack of diversity. In order to improve its performance, this paper presents a hybrid approach which embedded the MOPSO into the island model and integrated a local search technique, Variable Neighborhood Search, to enhance the diversity into the swarm. Experiments on two series of test functions have shown the effectiveness of the proposed approach. A comparison with other evolutionary algorithms shows that the proposed approach presented a good performance in solving multiobjective optimization problems.

Keywords: particle swarm optimization, migration, variable neighborhood search, multiobjective optimization

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Authors: Mohammad Lemar Zalmai, Mustafa Nabi Kocakaya, Cemil Akcay, Ekrem Manisali

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In recent years, the Building Information Modeling (BIM) approach has been developed expeditiously. As people see the benefits of this approach, it has begun to be used widely in construction projects and some countries made it mandatory to get more benefits from it. To promote the implementation of BIM in construction projects, it will be helpful to get some relevant information from surveys and interviews. The purpose of this study is to research the current adoption and implementation of BIM in public projects in Turkey. This study specified the challenges of BIM implementation in Turkey and proposed some solutions to overcome them. In this context, the challenges for BIM implementation and the factors that affect the BIM usage are determined based on previous academic researches and expert opinions by conducting interviews and questionnaire surveys. Several methods are used to process information in order to obtain weights of different factors to make BIM widespread in Turkey. This study concluded interviews' and questionnaire surveys' outcomes and proposed some suggestions to promote the implementation of BIM in Turkey. We believe research findings will be a good reference for boosting BIM implementation in Turkey.

Keywords: building information modelling, BIM implementations, Turkish construction industry, Turkish government sector projects

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Authors: K. Passbakhsh

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Determination of reinforcement forces is one of the most important and main discussions in designing retaining walls. By determining these forces we refrain from conservative planning. By numerically modeling the reinforced soil retaining walls under dynamic loading reinforcement forces can be calculated. In this study we try to approach the gained forces by pseudo-static method according to FHWA code and gained forces from numerical modeling by finite element method, by selecting seismic horizontal coefficient for different wall height. PLAXIS software was used for numerical analysis. Then the effect of reinforcement stiffness and soil type on reinforcement forces is examined.

Keywords: reinforced soil, PLAXIS, reinforcement forces, retaining walls

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Authors: Selin Guney, Andres Riquelme

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Among the main purposes of optimal and efficient forecasts of agricultural commodity prices is to guide the firms to advance the economic decision making process such as planning business operations and marketing decisions. Governments are also the beneficiaries and suppliers of agricultural price forecasts. They use this information to establish a proper agricultural policy, and hence, the forecasts affect social welfare and systematic errors in forecasts could lead to a misallocation of scarce resources. Various empirical approaches have been applied to forecast commodity prices that have used different methodologies. Most commonly-used approaches to forecast commodity sectors depend on classical time series models that assume values of the response variables are precise which is quite often not true in reality. Recently, this literature has mostly evolved to a consideration of fuzzy time series models that provide more flexibility in terms of the classical time series models assumptions such as stationarity, and large sample size requirement. Besides, fuzzy modeling approach allows decision making with estimated values under incomplete information or uncertainty. A number of fuzzy time series models have been developed and implemented over the last decades; however, most of them are not appropriate for forecasting repeated and nonconsecutive transitions in the data. The modeling scheme used in this paper eliminates this problem by introducing Markov modeling approach that takes into account both the repeated and nonconsecutive transitions. Also, the determination of length of interval is crucial in terms of the accuracy of forecasts. The problem of determining the length of interval arbitrarily is overcome and a methodology to determine the proper length of interval based on the distribution or mean of the first differences of series to improve forecast accuracy is proposed. The specific purpose of this paper is to propose and investigate the potential of a new forecasting model that integrates methodologies for determining the proper length of interval based on the distribution or mean of the first differences of series and Fuzzy Time Series- Markov Chain model. Moreover, the accuracy of the forecasting performance of proposed integrated model is compared to different univariate time series models and the superiority of proposed method over competing methods in respect of modelling and forecasting on the basis of forecast evaluation criteria is demonstrated. The application is to daily corn and soybean prices observed at three commercially important North Carolina markets; Candor, Cofield and Roaring River for corn and Fayetteville, Cofield and Greenville City for soybeans respectively. One main conclusion from this paper is that using fuzzy logic improves the forecast performance and accuracy; the effectiveness and potential benefits of the proposed model is confirmed with small selection criteria value such MAPE. The paper concludes with a discussion of the implications of integrating fuzzy logic and nonarbitrary determination of length of interval for the reliability and accuracy of price forecasts. The empirical results represent a significant contribution to our understanding of the applicability of fuzzy modeling in commodity price forecasts.

Keywords: commodity, forecast, fuzzy, Markov

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Authors: Jisong Ryu, Woosik Lee, Yonggu Jang

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The paper discusses the process of establishing a reliable test bed for verifying the usability of Ground Penetrating Radar (GPR) exploration equipment based on an integrated underground spatial map in Korea. The aim of this study is to construct a test bed consisting of metal and non-metal pipelines to verify the performance of GPR equipment and improve the accuracy of the underground spatial integrated map. The study involved the design and construction of a test bed for metal and non-metal pipe detecting tests. The test bed was built in the SOC Demonstration Research Center (Yeoncheon) of the Korea Institute of Civil Engineering and Building Technology, burying metal and non-metal pipelines up to a depth of 5m. The test bed was designed in both vehicle-type and cart-type GPR-mounted equipment. The study collected data through the construction of the test bed and conducting metal and non-metal pipe detecting tests. The study analyzed the reliability of GPR detecting results by comparing them with the basic drawings, such as the underground space integrated map. The study contributes to the improvement of GPR equipment performance evaluation and the accuracy of the underground spatial integrated map, which is essential for urban planning and construction. The study addressed the question of how to verify the usability of GPR exploration equipment based on an integrated underground spatial map and improve its performance. The study found that the test bed is reliable for verifying the performance of GPR exploration equipment and accurately detecting metal and non-metal pipelines using an integrated underground spatial map. The study concludes that the establishment of a test bed for verifying the usability of GPR exploration equipment based on an integrated underground spatial map is essential. The proposed Korean-style test bed can be used for the evaluation of GPR equipment performance and support the construction of a national non-metal pipeline exploration equipment performance evaluation center in Korea.

Keywords: Korea-style GPR testbed, GPR, metal pipe detecting, non-metal pipe detecting

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Authors: Soulayma Smirani, Mourad Aidi, Taoufik Aguili

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Energy harvesting has arisen as a prominent research area for low power delivery to RF devices. Rectennas have become a key element in this technology. In this paper, electromagnetic modeling of a rectenna system is presented. In our approach, a hybrid technique was demonstrated to associate both the method of auxiliary sources (MAS) and MoM-GEC (the method of moments combined with the generalized equivalent circuit technique). Auxiliary sources were used in order to substitute specific electronic devices. Therefore, a simple and controllable model is obtained. Also, it can easily be interconnected to form different topologies of rectenna arrays for more energy harvesting. At last, simulation results show the feasibility and simplicity of the proposed rectenna model with high precision and computation efficiency.

Keywords: computational electromagnetics, MoM-GEC method, rectennas, RF energy harvesting

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Authors: Craig Mertens

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Teaching art history or any other academic subject to EFL students can be done successfully. A course called Western Images was created to teach Japanese students art history while only using English in the classroom. An approach known as Content and Language Integrated Learning (CLIL) was used as a basis for this course. This paper’s purpose is to state the reasons why learning about art history is important, go through the process of creating content for the course, and suggest multiple tasks to help students practice the critical thinking skills used in analyzing and drawing conclusions of works of art from western culture. As a guide for this paper, Brown’s (1995) six elements of a language curriculum will be used. These stages include needs analysis, goals and objectives, assessment, materials, teaching method and tasks, and evaluation of the course. The goal here is to inspire debate and discussion regarding CLIL and its pros and cons, and to question current curriculum in university language courses.

Keywords: art history, EFL, content and language integration learning, critical thinking

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Authors: Sumit Kumar, Sunil Kumar, Chandan Deep Singh

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This paper presents modeling and simulation of flexible robot in an underwater environment. The underwater environment completely contrasts with ground or space environment. The robot in an underwater situation is subjected to various dynamic forces like buoyancy forces, hydrostatic and hydrodynamic forces. The underwater robot is modeled as Rayleigh beam. The developed model further allows estimating the deflection of tip in two directions. The complete dynamics of the underwater robot is analyzed, which is the main focus of this investigation. The control of robot trajectory is not discussed in this paper. Simulation is performed using Symbol Shakti software.

Keywords: bond graph modeling, dynamics. modeling, rayleigh beam, underwater robot

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Authors: Meng Su

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High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

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Authors: Axelle Bertrand, Tom Bauer, Carole Charbuillet, Martin Bonte, Marie Voyer, Nicolas Perry

Abstract:

The complexity of Life Cycle Assessment (LCA) can be identified as the ultimate obstacle to massification. Due to these obstacles, the diffusion of eco-design and LCA methods in the manufacturing sectors could be impossible. This article addresses the research question: How to adapt the LCA method to generalize it massively and improve its performance? This paper aims to develop an approach for automating LCA in order to carry out assessments on a massive scale. To answer this, we proceeded in three steps: First, an analysis of the literature to identify existing automation methods. Given the constraints of large-scale manual processing, it was necessary to define a new approach, drawing inspiration from certain methods and combining them with new ideas and improvements. In a second part, our development of automated construction is presented (reconciliation and implementation of data). Finally, the LCA case study of a conduit is presented to demonstrate the feature-based approach offered by the developed tool. A computerized environment supports effective and efficient decision-making related to materials and processes, facilitating the process of data mapping and hence product modeling. This method is also able to complete the LCA process on its own within minutes. Thus, the calculations and the LCA report are automatically generated. The tool developed has shown that automation by code is a viable solution to meet LCA's massification objectives. It has major advantages over the traditional LCA method and overcomes the complexity of LCA. Indeed, the case study demonstrated the time savings associated with this methodology and, therefore, the opportunity to increase the number of LCA reports generated and, therefore, to meet regulatory requirements. Moreover, this approach also presents the potential of the proposed method for a wide range of applications.

Keywords: automation, EEE, life cycle assessment, life cycle inventory, massively

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Authors: Mueller Jann, Hoffmann Christian Hugo

Abstract:

Conventional quantitative risk management in banking is a risk factor of its own, because it rests on assumptions such as independence and availability of data which do not hold when rare events of extreme consequences are involved. There is a growing recognition of the need for alternative risk measures that do not make these assumptions. We propose a novel method for modeling the risk associated with investment products, in particular derivatives, by using a formal language for specifying financial contracts. Expressions in this language are interpreted in the category of values annotated with (a formal representation of) uncertainty. The choice of uncertainty formalism thus becomes a parameter of the model, so it can be adapted to the particular application and it is not constrained to classical probabilities. We demonstrate our approach using a simple logic-based uncertainty model and a case study in which we assess the risk of counter party default in a portfolio of collateralized loans.

Keywords: risk model, uncertainty monad, derivatives, contract algebra

Procedia PDF Downloads 545