Search results for: behavioral modeling

Authors: Ganiyat Soliu, Glen Bright, Chiemela Onunka

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Performance optimization plays a key role in controlling the waiting time during manufacturing in an advanced manufacturing environment to improve productivity. Queuing mathematical modeling theory was used to examine the performance of the multi-stage production line. Robotics as a disruptive technology was implemented into a virtual manufacturing scenario during the packaging process to study the effect of waiting time on productivity. The queuing mathematical model was used to determine the optimum service rate required by robots during the packaging stage of manufacturing to yield an optimum production cost. Different rates of production were assumed in a virtual manufacturing environment, cost of packaging was estimated with optimum production cost. An equation was generated using queuing mathematical modeling theory and the theorem adopted for analysis of the scenario is the Newton Raphson theorem. Queuing theory presented here provides an adequate analysis of the number of robots required to regulate waiting time in order to increase the number of output. Arrival rate of the product was fast which shows that queuing mathematical model was effective in minimizing service cost and the waiting time during manufacturing. At a reduced waiting time, there was an improvement in the number of products obtained per hour. The overall productivity was improved based on the assumptions used in the queuing modeling theory implemented in the virtual manufacturing scenario.

Keywords: performance optimization, productivity, queuing theory, robotics

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Authors: Gabriele Barrocas, Habon Issa

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The amygdala is one of various brain regions that tend to be pathological in individuals with autism spectrum disorder (ASD). ASD is a prevalent and heterogeneous developmental disorder affecting all ethnic and socioeconomic groups and consists of a broad range of severity, etiology, and behavioral symptoms. Common features of ASD include but are not limited to repetitive behaviors, obsessive interests, and anxiety. Neuroscientists view the amygdala as the core of the neural system that regulates behavioral responses to anxiogenic and threatening stimuli. Despite this consensus, many previous studies and literature reviews on the amygdala’s alterations in individuals with ASD have reported inconsistent findings. In this review, we will address these conflicts by highlighting recent studies which reveal that anatomical and related socio-emotional differences detected between individuals with and without ASD are highly age-dependent. We will specifically discuss studies using functional magnetic resonance imaging (fMRI), structural MRI, and diffusion tensor imaging (DTI) to provide insights into the neuroanatomical substrates of ASD across development, with a focus on amygdala volumes, cell densities, and connectivity.

Keywords: autism, amygdala, development, abnormalities

Procedia PDF Downloads 113

Authors: Makhlouf Mourad, Medkour Mihoub, Bouchher Omar, Messabih Sidi Mohamed, Benrachedi Khaled

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This work is the modeling and simulation of fluid flow (liquid) through porous media. This type of flow occurs in many situations of interest in applied sciences and engineering, fluid (oil) consists of several individual substances in pure, single-phase flow is incompressible and isothermal. The porous medium is isotropic, homogeneous optionally, with the rectangular format and the flow is two-dimensional. Modeling of hydrodynamic phenomena incorporates Darcy's law and the equation of mass conservation. Correlations are used to model the density and viscosity of the fluid. A finite volume code is used in the discretization of differential equations. The nonlinearity is treated by Newton's method with relaxation coefficient. The results of the simulation of the pressure and the mobility of liquid flowing through porous media are presented, analyzed, and illustrated.

Keywords: Darcy equation, middle porous, continuity equation, Peng Robinson equation, mobility

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Authors: Shu-Lien Chou, Chung-Feng Liu

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Self-health management of chronic illnesses plays an important part in chronic illness treatments. However, various kinds of health information (health education materials) which government or healthcare institutions provide for patients may not achieve the expected outcome. One of the critical reasons affecting patients’ use intention could be patients’ perceived Information overload regarding the health information. This study proposed an extended model of Theory of Planned Behavior, which integrating perceived information overload as another construct to explore patients’ use intention of the health information for self-health management. The independent variables are attitude, subject norm, perceived behavior control and perceived information overload while the dependent variable is behavior intention to use the health information. The cross-sectional study used a structured questionnaire for data collection, focusing on the chronic patients with coronary artery disease (CAD), who are the potential users of the health information, in a medical center in Taiwan. Data were analyzed using descriptive statistics of the basic information distribution of the questionnaire respondents, and the Partial Least Squares (PLS) structural equation model to study the reliability and construct validity for testing our hypotheses. A total of 110 patients were enrolled in this study and 106 valid questionnaires were collected. The PLS analysis result indicates that the patients’ perceived information overload of health information contributes the most critical factor influencing the behavioral intention. Subjective norm and perceived behavioral control of TPB constructs had significant effects on patients’ intentions to use health information also, whereas the attitude construct did not. This study demonstrated a comprehensive framework, which extending perceived information overload into TPB model to predict patients’ behavioral intention of using heath information. We expect that the results of this study will provide useful insights for studying health information from the perspectives of academia, governments, and healthcare providers.

Keywords: chronic patients, health information, information overload, theory of planned behavior

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Authors: Furry A. Wilis, Dewi Larasati, Suhendri

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Around 96% of architecture firms in Indonesia are classified as small-medium enterprises (SME). This number shows that the SME firms have an important role in architecture, engineering, and construction (AEC) industry in Indonesia. Some of them are still using conventional system (2D based) in arranging construction project documents. This system is fragmented and not fully well-coordinated, so causes many changes in the whole project cycle. Building information modeling (BIM), as a new developed system in Indonesian construction industry, has been assumed can decrease changes in the project. But BIM has not fully implemented in Indonesian AEC industry, especially in SME architecture firms. This article identifies the challenges of implementing BIM in SME architecture firms in Indonesia. Quantitative-explorative research with questionnaire was chosen to achieve the goal of this article. The scarcity of skilled BIM user, low demand from client, high investment cost, and the unwillingness of the firm to switch into BIM were found as the result of this paper.

Keywords: architecture consultants, BIM, SME, Indonesia

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Authors: Sungho Kim, Dae Shik Kim, Jong Min Lee

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Fluid catalytic cracking (FCC) process is one of the most important process in modern refinery industry. This paper focuses on the fluid catalytic cracking (FCC) process. As the FCC process is difficult to model well, due to its non linearities and various interactions between its process variables, rigorous process modeling of whole FCC plant is demanded for control and plant-wide optimization of the plant. In this study, a process design for the FCC plant includes riser reactor, main fractionator, and gas processing unit was developed. A reactor model was described based on four-lumped kinetic scheme. Main fractionator, gas processing unit and other process units are designed to simulate real plant data, using a process flow sheet simulator, Aspen PLUS. The custom reactor model was integrated with the process flow sheet simulator to develop an integrated process model.

Keywords: fluid catalytic cracking, simulation, plant data, process design

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Authors: Slim Chokri

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Load forecasting is one of the central functions in power systems operations. Electricity cannot be stored, which means that for electric utility, the estimate of the future demand is necessary in managing the production and purchasing in an economically reasonable way. A majority of the recently reported approaches are based on neural network. The attraction of the methods lies in the assumption that neural networks are able to learn properties of the load. However, the development of the methods is not finished, and the lack of comparative results on different model variations is a problem. This paper presents a new approach in order to predict the Tunisia daily peak load. The proposed method employs a computational intelligence scheme based on the Fuzzy neural network (FNN) and support vector regression (SVR). Experimental results obtained indicate that our proposed FNN-SVR technique gives significantly good prediction accuracy compared to some classical techniques.

Keywords: neural network, load forecasting, fuzzy inference, machine learning, fuzzy modeling and rule extraction, support vector regression

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Authors: Cyrillus Prabandana

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Supply chain optimisation requires multiple factors as consideration or constraints. These factors are including but not limited to demand forecasting, raw material fulfilment, production capacity, inventory level, facilities locations, transportation means, and manpower availability. By knowing all manageable factors involved and assuming the uncertainty with pre-defined percentage factors, an integrated supply chain model could be developed to manage various business scenarios. This paper analyse the utilisation of geographical point of view to develop an integrated supply chain network model to optimise the distribution of finished product appropriately according to forecasted demand and available supply. The supply chain optimisation model shows that small change in one supply chain constraint is possible to largely impact other constraints, and the new information from the model should be able to support the decision making process. The model was focused on three areas, i.e. raw material fulfilment, production capacity and finished products transportation. To validate the model suitability, it was implemented in a project aimed to optimise the concrete supply chain in a mining location. The high level of operations complexity and involvement of multiple stakeholders in the concrete supply chain is believed to be sufficient to give the illustration of the larger scope. The implementation of this geographical supply chain network modeling resulted an optimised concrete supply chain from raw material fulfilment until finished products distribution to each customer, which indicated by lower percentage of missed concrete order fulfilment to customer.

Keywords: decision making, geographical supply chain modeling, supply chain optimisation, supply chain

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Authors: Fouad. Inel, Lakhdar. Khochemane

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This article presents a comparative response specification performance between two controllers of three and four cable based robots for various applications. The main objective of this work is: The first is to use the direct and inverse geometric model to study and simulate the end effector position of the robot with three and four cables. A graphical user interface has been implemented in order to visualizing the position of the robot. Secondly, we present the determination of static and dynamic tensions and lengths of cables required to flow different trajectories. At the end, we study the response of our systems in closed loop with a Proportional-Integrated Derivative (PID) and Proportional-Integrated (PD) controllers then this last are compared the results of the same examples using MATLAB/Simulink; we found that the PID method gives the better performance, such as rapidly speed response, settling time, compared to PD controller.

Keywords: parallel cable-based robots, geometric modeling, dynamic modeling, graphical user interface, open loop, PID/PD controllers

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Authors: Fety Nurlia Muzayanah, Arif Imam Suroso, Mukhamad Najib

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The market share of organic food in Indonesia just reaches 0.5-2 percents from the entire of agricultural products. The aim of this research is to analyze the relation of gender, work, age and final education toward the buying interest of organic food, to identify the factors influencing the resistance of the purchase of organic food, and to identify the market education process. The analysis result of Structural Equation Modeling (SEM) shows the factors causing the resistance of the purchase of organic food are the negative attitude toward organic food, the lack of affordable in range for organic food product and the lack of awareness toward organic food, while the subjective norms have no significant effect toward the buying interest. The market education process which can be done is the education about the use of the health of organic food, the organic certification and the economic value.

Keywords: market education, organic food, consumer behavior, structural equation modeling

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Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

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Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks

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Authors: Asaad Y. Shamseldin

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Analytical probabilistic approach is an innovative approach for urban stormwater modeling. It can provide information about the long-term performance of a stormwater management facility without being computationally very demanding. This paper explores the application of the analytical probabilistic approach in New Zealand. The paper presents the results of a case study aimed at development of an objective way of identifying what constitutes a rainfall storm event and the estimation of the corresponding statistical properties of storms using two selected automatic rainfall stations located in the Auckland region in New Zealand. The storm identification and the estimation of the storm statistical properties are regarded as the first step in the development of the analytical probabilistic models. The paper provides a recommendation about the definition of the storm inter-event time to be used in conjunction with the analytical probabilistic approach.

Keywords: hydrology, rainfall storm, storm inter-event time, New Zealand, stormwater management

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Authors: Rudan Xue, Annika Moscati, Rehel Zeleke Kebede, Peter Johansson

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Successful buildings’ simulation and analysis inevitably require information exchange between multiple building information modeling (BIM) software. The BIM infor-mation exchange based on IFC is widely used. However, Industry Foundation Classifi-cation (IFC) files are not always reliable and information can get lost when using dif-ferent software for modeling and simulations. In this research, interviews with lighting simulation experts and a case study provided by a company producing lighting devices have been the research methods used to identify the necessary steps and data for suc-cessful information exchange between lighting simulation tools and authoring design tools. Model creation, information exchange, and model simulation have been identi-fied as key aspects for the success of information exchange. The paper concludes with recommendations for improved information exchange and more reliable simulations that take all the needed parameters into consideration.

Keywords: BIM, data exchange, interoperability issues, lighting simulations

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Authors: Ezra Yehuwalashet, Alireza Malehmir

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Blötberget mining area in central Sweden, part of the Bergslagen mineral district, is well known for its various type of mineralization particularly iron-oxide deposits since the 1600. To shed lights on the knowledge of the host rock structures, depth extent and tonnage of the mineral deposits and support deep mineral exploration potential in the study area, new ground gravity and existing aeromagnetic data (from the Geological Survey of Sweden) were used for interpretations and modelling. A major boundary separating a gravity low from a gravity high in the southern part of the study area is noticeable and likely representing a fault boundary separating two different lithological units. Gravity data and modeling offers a possible new target area in the southeast of the known mineralization while suggesting an excess high-density region down to 800 m depth.

Keywords: gravity, magnetics, ore deposit, geophysics

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Authors: Donatello Cardone

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Bilinear hysteresis models are usually used to describe the cyclic behavior of high damping rubber bearings. However, they neglect a number of phenomena (such as the interaction between axial load and shear force, buckling and post-buckling behavior, cavitation, scragging effects, etc.) that can significantly influence the dynamic behavior of such isolation devices. In this work, an advanced hysteresis model is examined and properly calibrated using consolidated procedures. Results of preliminary numerical analyses, performed in OpenSees, are shown and compared with the results of experimental tests on high damping rubber bearings and simulation analyses using alternative nonlinear models. The findings of this study can provide an useful tool for the accurate evaluation of the seismic response of structures with rubber-based isolation systems.

Keywords: seismic isolation, high damping rubber bearings, numerical modeling, axial-shear force interaction

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Authors: S. A. Naeini, A. Khalili

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Nowadays, tunnels with different applications are developed, and most of them are related to subway tunnels. The excavation of shallow tunnels that pass under municipal utilities is very important, and the surface settlement control is an important factor in the design. The study sought to analyze the settlement and also to find an appropriate model in order to predict the behavior of the tunnel in Tehran subway line-3. The displacement in these sections is also determined by using numerical analyses and numerical modeling. In addition, the Adaptive Neuro-Fuzzy Inference System (ANFIS) method is utilized by Hybrid training algorithm. The database pertinent to the optimum network was obtained from 46 subway tunnels in Iran and Turkey which have been constructed by the new Austrian tunneling method (NATM) with similar parameters based on type of their soil. The surface settlement was measured, and the acquired results were compared to the predicted values. The results disclosed that computing intelligence is a good substitute for numerical modeling.

Keywords: settlement, Subway Line, FLAC3D, ANFIS Method

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Authors: Lucian Capitanu, Virgil Florescu

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Often for the laboratory studies, modeling of specific tribological processes raises special problems. One such problem is the modeling of some temperatures and extremely high contact pressures, allowing modeling of temperatures and pressures at which the injection or extrusion processing of thermoplastic materials takes place. Tribological problems occur mainly in thermoplastics materials reinforced with glass fibers. They produce an advanced wear to the barrels and screws of processing machines, in short time. Obtaining temperatures around 210 °C and higher, as well as pressures around 100 MPa is very difficult in the laboratory. This paper reports a simple and convenient solution to get these conditions, using friction sliding couples with linear contact, cylindrical liner plastic filled with glass fibers on plate steel samples, polished and super-finished. C120 steel, which is a steel for moulds and Rp3 steel, high speed steel for tools, were used. Obtaining the pressure was achieved by continuous request of the liner in rotational movement up to its elasticity limits, when the dry friction coefficient reaches or exceeds the hardness value of 0.5 HB. By dissipation of the power lost by friction on flat steel sample, are reached contact temperatures at the metal surface that reach and exceed 230 °C, being placed in the range temperature values of the injection. Contact pressures (in load and materials conditions used) ranging from 16.3-36.4 MPa were obtained depending on the plastic material used and the glass fibers content.

Keywords: plastics with glass fibers, dry friction, linear contact, contact temperature, contact pressure, experimental simulation

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Authors: Daniel Pinheiro Da Silva Junior, Aline Paes, Daniel De Oliveira, Christiano Lacerda Ghuerren, Marcio Duran

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The Courts of Accounts are institutions responsible for overseeing and point out irregularities of Public Administration expenses. They have a high demand for processes to be analyzed, whose decisions must be grounded on severity laws. Despite the existing large amount of processes, there are several cases reporting similar subjects. Thus, previous decisions on already analyzed processes can be a precedent for current processes that refer to similar topics. Identifying similar topics is an open, yet essential task for identifying similarities between several processes. Since the actual amount of topics is considerably large, it is tedious and error-prone to identify topics using a pure manual approach. This paper presents a tool based on Machine Learning and Natural Language Processing to assists in building a labeled dataset. The tool relies on Topic Modelling with Latent Dirichlet Allocation to find the topics underlying a document followed by Jensen Shannon distance metric to generate a probability of similarity between documents pairs. Furthermore, in a case study with a corpus of decisions of the Rio de Janeiro State Court of Accounts, it was noted that data pre-processing plays an essential role in modeling relevant topics. Also, the combination of topic modeling and a calculated distance metric over document represented among generated topics has been proved useful in helping to construct a labeled base of similar and non-similar document pairs.

Keywords: courts of accounts, data labelling, document similarity, topic modeling

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Authors: Deborah Weidner, Melissa Morgera

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The model of care delivery in the Behavioral Health Network (BHN) is integrated across all five regions of Hartford Healthcare and thus spans the entirety of the state of Connecticut, with care provided in seven inpatient settings and over 30 ambulatory outpatient locations. While safety has been a core priority of the BHN in alignment with High Reliability practices, safety initiatives have historically been facilitated locally in each region or within each entity, with interventions implemented locally as opposed to throughout the network. To address this, the BHN introduced a network wide Safety Huddle during 2022. Launched in January, the BHN Safety Huddle brought together internal stakeholders, including medical and administrative leaders, along with executive institute leadership, quality, and risk management. By bringing leaders together and introducing a network-wide safety huddle into the way we work, the benefit has been an increase in awareness of safety events occurring in behavioral health areas as well as increased systemization of countermeasures to prevent future events. One significant discussion topic presented in huddles has pertained to environmental design and patient access to potentially dangerous items, addressing some of the most relevant factors resulting in harm to patients in inpatient and emergency settings for behavioral health patients. The safety huddle has improved visibility of potential environmental safety risks through the generation of over 15 safety alerts cascaded throughout the BHN and also spurred a rapid improvement project focused on standardization of patient belonging searches to reduce patient access to potentially dangerous items on inpatient units. Safety events pertaining to potentially dangerous items decreased by 31% as a result of standardized interventions implemented across the network and as a result of increased awareness. A second positive outcome originating from the BHN Safety Huddle was implementation of a recommendation to increase the emergency Narcan®(naloxone) supply on hand in ambulatory settings of the BHN after incidents involving accidental overdose resulted in higher doses of naloxone administration. By increasing the emergency supply of naloxone on hand in all ambulatory and residential settings, colleagues are better prepared to respond in an emergency situation should a patient experience an overdose while on site. Lastly, discussions in safety huddle spurred a new initiative within the BHN to improve responsiveness to assaultive incidents through a consultation service. This consult service, aligned with one of the network’s improvement priorities to reduce harm events related to assaultive incidents, was borne out of discussion in huddle in which it was identified that additional interventions may be needed in providing clinical care to patients who are experiencing multiple and/ or frequent safety events.

Keywords: quality, safety, behavioral health, risk management

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Authors: Seyed Mehrdad Gholami

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Nowadays, using rail transport system (Metro) is increased in most cities of The world, so the need for safe and economical way of building tunnels and subway stations is felt more and more. One of the most commonly used methods for constructing underground structures in urban areas is NATM (New Austrian tunneling method). In this method, there are some key parameters such as excavation steps and cross-sectional area that have a significant effect on the surface settlement. Settlement is a very important control factor related to safe excavation. In this paper, Finite Element Method is used by Abaqus. R6 station of Tehran Metro Line 6 is built by NATM and the construction of that is studied and analyzed. Considering the outcomes obtained from numerical modeling and comparison with the results of the instrumentation and monitoring of field, finally, the excavation step of 1 meter and longitudinal distance of 14 meters between side drifts is suggested to achieve safe tunneling with allowable settlement.

Keywords: excavation step, NATM, numerical modeling, settlement.

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Authors: Christopher Mkirema Maghanga, Maurice Mghendi Mwamburi

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Parametric modeling provides a means to deeper understand the properties of materials. Drude, Brendel, Lorentz and OJL incorporated in SCOUT® software are some of the models used to study dielectric films. In our work, we utilized Brendel and Drude models to extract the optical constants from spectroscopic data of fabricated undoped and niobium doped titanium oxide thin films. The individual contributions by the two models were studied to establish how they influence the dielectric function. The effect of dopants on their influences was also analyzed. For the undoped films, results indicate minimal contribution from the Drude term due to the dielectric nature of the films. However as doping levels increase, the rise in the concentration of free electrons favors the use of Drude model. Brendel model was confirmed to work well with dielectric films - the undoped titanium Oxide films in our case.

Keywords: modeling, Brendel model, optical constants, titanium oxide, Drude Model

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Authors: Aymen Laadhari, Gábor Székely

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This paper is concerned with the development of a fully implicit and purely Eulerian fluid-structure interaction method tailored for the modeling of the large deformations of elastic membranes in a surrounding Newtonian fluid. We consider a simplified model for the mechanical properties of the membrane, in which the surface strain energy depends on the membrane stretching. The fully Eulerian description is based on the advection of a modified surface tension tensor, and the deformations of the membrane are tracked using a level set strategy. The resulting nonlinear problem is solved by a Newton-Raphson method, featuring a quadratic convergence behavior. A monolithic solver is implemented, and we report several numerical experiments aimed at model validation and illustrating the accuracy of the presented method. We show that stability is maintained for significantly larger time steps.

Keywords: finite element method, implicit, level set, membrane, Newton method

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Authors: Jean-michel Sahut, Lubica Hikkerova, Wissal Ben Arfi

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The Internet of Things (IoT) emerged over the last few decades in many fields. Healthcare can significantly benefit from IoT. This study aims to examine factors influencing the adoption of IoT in eHealth. To do so, an innovative framework has been developed which applies both the Technology Acceptance Model (TAM) and the United Theory of Acceptance and Use of Technology (UTAUT) model and builds on them by analyzing trust and perceived-risk dimensions to predict intention to use IoT in eHealth. In terms of methodology, a Partial Least Approach Structural Equation Modelling was carried out on a sample of 267 French users. The findings of this research support the significant positive effect of constructs set out in the TAM (perceived ease of use) on predicting behavioral intention by adding the effects identified for UTAUT variables. This research also demonstrates how perceived risk and trust are significant factors for models examining behavioral intentions to use IoT. Perceived risk enhanced by the trust has a significant effect on patients’ behavioral intentions. Moreover, the results highlight the key role of prescription as a moderator of IoT adoption in eHealth. Depending on whether an individual has a prescription to use connected devices or not, ease of use has a stronger impact on adoption, while trust has a negative impact on adoption for users without a prescription. In accordance with the empirical results, several practical implications can be proposed. All connected devices applied in a medical context should be divided into groups according to their functionality: whether they are essential for the patient’s health and whether they require a prescription or not. Devices used with a prescription are easily accepted because the intention to use them is moderated by the medical trust (discussed above). For users without a prescription, ease of use is a more significant factor than for users who have a prescription. This suggests that currently, connected e-Health devices and online healthcare systems have to take this factor into account to better meet the needs and expectations of end-users.

Keywords: internet of things, Healthcare, trust, consumer acceptance

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Authors: Nitish Kumar Vaja, Oumar Barry, Brian DeJong

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Aeolian vibrations are the major cause for the failure of conductor cables. Using a Stockbridge damper reduces these vibrations and increases the life span of the conductor cable. Designing an efficient Stockbridge damper that suits the conductor cable requires a robust mathematical model with minimum assumptions. However it is not easy to analytically model the complex geometry of the messenger. Therefore an equivalent stiffness must be determined so that it can be used in the analytical model. This paper examines the bending stiffness of the cable and discusses the effect of this stiffness on the natural frequencies. The obtained equivalent stiffness compensates for the assumption of modeling the messenger as a rod. The results from the free vibration analysis of the analytical model with the equivalent stiffness is validated using the full scale finite element model of the Stockbridge damper.

Keywords: equivalent stiffness, finite element model, free vibration response, Stockbridge damper

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Authors: Eui-Jin Kim, Hasik Lee, Su-Jin Park, Dong-Kyu Kim

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Smart-card data are expected to provide information on activity pattern as an alternative to conventional person trip surveys. The focus of this study is to propose a method for training the person trip surveys to supplement the smart-card data that does not contain the purpose of each trip. We selected only available features from smart card data such as spatiotemporal information on the trip and geographic information system (GIS) data near the stations to train the survey data. XGboost, which is state-of-the-art tree-based ensemble classifier, was used to train data from multiple sources. This classifier uses a more regularized model formalization to control the over-fitting and show very fast execution time with well-performance. The validation results showed that proposed method efficiently estimated the trip purpose. GIS data of station and duration of stay at the destination were significant features in modeling trip purpose.

Keywords: activity pattern, data fusion, smart-card, XGboost

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Authors: Fadzai Munyuki

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Parental divorce is one of youth's most stressful life events and is associated with long-lasting emotional and behavioral problems. Over the last few decades, research has consistently found strong associations between divorce and adverse health effects in adolescents. Parental divorce has been hypothesized to lead to psychosocial development problems, mental health challenges, internalizing and externalizing behavior problems, and low academic performance among adolescents. This is supported by the Positive youth development theory, which states that a family setup has a major role to play in adolescent development and well-being. So, the focus of this research will be to test this hypothesized process model among adolescents in five provinces in Zimbabwe. A cross-sectional study will be conducted to test this hypothesis, and 1840 (n = 1840) adolescents aged between 14 to 17 will be employed for this study. A Stress and Questionnaire scale, a Child behavior checklist scale, and an academic concept scale will be used for this study. Data analysis will be done using Structural Equations Modeling. This study has many limitations, including the lack of a 'real-time' study, a few cross-sectional studies, a lack of a thorough and validated population measure, and many studies that have been done that have focused on one variable in relation to parental divorce. Therefore, this study seeks to bridge this gap between past research and current literature by using a validated population measure, a real-time study, and combining three latent variables in this study.

Keywords: mental health, internalizing and externalizing behavior, divorce, academic achievements

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Authors: Youssef Mazloum, Haytham Sayah, Maroun Nemer

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The penetration of renewable energy sources into the electric grid is significantly increasing. However, the intermittence of these sources breaks the balance between supply and demand for electricity. Hence, the importance of the energy storage technologies, they permit restoring the balance and reducing the drawbacks of intermittence of the renewable energies. This paper discusses the modeling and the cost-effectiveness of an isobaric adiabatic compressed air energy storage (IA-CAES) system. The proposed system is a combination among a compressed air energy storage (CAES) system with pumped hydro storage system and thermal energy storage system. The aim of this combination is to overcome the disadvantages of the conventional CAES system such as the losses due to the storage pressure variation, the loss of the compression heat and the use of fossil fuel sources. A steady state model is developed to perform an energy and exergy analyses of the IA-CAES system and calculate the distribution of the exergy losses in the latter system. A sensitivity analysis is also carried out to estimate the effects of some key parameters on the system’s efficiency, such as the pinch of the heat exchangers, the isentropic efficiency of the rotating machinery and the pressure losses. The conducted sensitivity analysis is a local analysis since the sensibility of each parameter changes with the variation of the other parameters. Therefore, an exergoeconomic study is achieved as well as a cost optimization in order to reduce the electricity cost produced during the production phase. The optimizer used is OmOptim which is a genetic algorithms based optimizer.

Keywords: cost-effectiveness, Exergoeconomic analysis, isobaric adiabatic compressed air energy storage (IA-CAES) system, thermodynamic modeling

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Authors: Duygu Dere, Mert Ergeneci, Kaan Gokcesu

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Google Trends data has gained increasing popularity in the applications of behavioral finance, decision science and risk management. Because of Google’s wide range of use, the Trends statistics provide significant information about the investor sentiment and intention, which can be used as decisive factors for corporate and risk management fields. However, an anomaly, a significant increase or decrease, in a certain query cannot be detected by the state of the art applications of computation due to the random baseline noise of the Trends data, which is modelled as an Additive white Gaussian noise (AWGN). Since through time, the baseline noise power shows a gradual change an adaptive thresholding method is required to track and learn the baseline noise for a correct classification. To this end, we introduce an online method to classify meaningful deviations in Google Trends data. Through extensive experiments, we demonstrate that our method can successfully classify various anomalies for plenty of different data.

Keywords: adaptive data processing, behavioral finance , convex optimization, online learning, soft minimum thresholding

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Authors: Kavish Kejriwal, Richa Grover

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Consumer awareness and pending legislation have pushed environmental issues into the spotlight, making it imperative for organizations to have a plan of action for “going green.” This is the reason why Green Supply Chain Management has become the integral part of many organization with a goal to reduce cost, increase efficiency and be environmental friendly. Implementation of GSCM involves many factors which act as barriers, making it a tedious task. These barriers have different relationship among themselves creating different impact on implementation Green Supply Chain Management. This work focuses on determining those barriers which have essentially to be removed in the initial stages of GSCM adoption. In this work, the author has taken the case of a petroleum industry in order to come up with a solution. A DEMATEL approach is used to reach the solution.

Keywords: barriers, environment, green supply chain management, impact, interpretive structural modeling

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Authors: K. A. Chinmaya, M. Udaya Bhaskar

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Multiphase motor drives are now a day considered for numerous applications due to the advantages that they offer when compared to their three-phase counterparts. Proper modeling of inverters and motors are important in devising an appropriate control algorithm. This paper develops a complete modeling of a five-phase inverter and five-phase space vector modulation schemes which can be used for five-phase motor drives. A novel modified algorithm is introduced which enables the sinusoidal output voltages up to certain voltage value. The waveforms of phase to neutral voltage are compared with the different modulation techniques and also different modulation indexes in terms of Low-order Harmonic (LH) voltage of 3rd and 7th present. A detailed performance evolution of existing and newly modified schemes is done in terms of Total Harmonic Distortion (THD).

Keywords: multi-phase drives, space vector modulation, voltage source inverter, low order harmonic voltages, total harmonic distortion

Procedia PDF Downloads 387