Search results for: customer behavior model graph

Authors: Yuhong Zhang, Dan Lu, Chenyang Bu, Peipei Li, Kui Yu, Xindong Wu

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The Cross-Lingual Entity Alignment (CLEA) task aims to find the aligned entities that refer to the same identity from two knowledge graphs (KGs) in different languages. It is an effective way to enhance the performance of data mining for KGs with scarce resources. In real-world applications, the neighborhood structures of the same entities in different KGs tend to be non-isomorphic, which makes the representation of entities contain diverse semantic information and then poses a great challenge for CLEA. In this paper, we try to address this challenge from two perspectives. On the one hand, the cross-KG relation completion rules are designed with the alignment constraint of entities and relations to improve the topology isomorphism of two KGs. On the other hand, a representation method combining isomorphic weights is designed to include more isomorphic semantics for counterpart entities, which will benefit the CLEA. Experiments show that our model can improve the isomorphism of two KGs and the alignment performance, especially for two non-isomorphic KGs.

Keywords: knowledge graphs, cross-lingual entity alignment, non-isomorphic, relation completion

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Authors: Olumuyiwa Ojo, Masengo Ilunga

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Artificial neural network (ANN) has broken the bounds of the convention programming, which is actually a function of garbage in garbage out by its ability to mimic the human brain. Its ability to adopt, adapt, adjust, evaluate, learn and recognize the relationship, behavior, and pattern of a series of data set administered to it, is tailored after the human reasoning and learning mechanism. Thus, the study aimed at modeling wastewater treatment process in order to accurately diagnose water control problems for effective treatment. For this study, a stage ANN model development and evaluation methodology were employed. The source data analysis stage involved a statistical analysis of the data used in modeling in the model development stage, candidate ANN architecture development and then evaluated using a historical data set. The model was developed using historical data obtained from Daspoort Wastewater Treatment plant South Africa. The resultant designed dimensions and model for wastewater treatment plant provided good results. Parameters considered were temperature, pH value, colour, turbidity, amount of solids and acidity. Others are total hardness, Ca hardness, Mg hardness, and chloride. This enables the ANN to handle and represent more complex problems that conventional programming is incapable of performing.

Keywords: ANN, artificial neural network, wastewater treatment, model, development

Procedia PDF Downloads 148

Authors: Manoj Reghu, Prabhu Rajagopal, C. V. Krishnamurthy, Krishnan Balasubramaniam

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A thorough understanding of guided ultrasonic wave behavior in structures is essential for the application of existing Non Destructive Evaluation (NDE) technologies, as well as for the development of new methods. However, the analysis of guided wave phenomena is challenging because of their complex dispersive and multimodal nature. Although numerical solution procedures have proven to be very useful in this regard, the increasing complexity of features and defects to be considered, as well as the desire to improve the accuracy of inspection often imposes a large computational cost. Hybrid models that combine numerical solutions for wave scattering with faster alternative methods for wave propagation have long been considered as a solution to this problem. However usually such models require modification of the base code of the solution procedure. Here we aim to develop Generic Hybrid models that can be directly applied to any two different solution procedures. With this goal in mind, a Numerical Hybrid model and an Analytical-Numerical Hybrid model has been developed. The concept and implementation of these Hybrid models are discussed in this paper.

Keywords: guided ultrasonic waves, Finite Element Method (FEM), Hybrid model

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Authors: Kuo-Chun Chien, Chia-Hui Chang, Ren-Der Sun

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Legal Judgment Prediction (LJP) is a subtask for legal AI. Its main purpose is to use the facts of a case to predict the judgment result. In Taiwan's criminal procedure, when prosecutors complete the investigation of the case, they will decide whether to prosecute the suspect and which article of criminal law should be used based on the facts and evidence of the case. In this study, we collected 305,240 indictments from the public inquiry system of the procuratorate of the Ministry of Justice, which included 169 charges and 317 articles from 21 laws. We take the crime facts in the indictments as the main input to jointly learn the prediction model for law source, article, and charge simultaneously based on the pre-trained Bert model. For single article cases where the frequency of the charge and article are greater than 50, the prediction performance of law sources, articles, and charges reach 97.66, 92.22, and 60.52 macro-f1, respectively. To understand the big performance gap between articles and charges, we used a bipartite graph to visualize the relationship between the articles and charges, and found that the reason for the poor prediction performance was actually due to the wording precision. Some charges use the simplest words, while others may include the perpetrator or the result to make the charges more specific. For example, Article 284 of the Criminal Law may be indicted as “negligent injury”, "negligent death”, "business injury", "driving business injury", or "non-driving business injury". As another example, Article 10 of the Drug Hazard Control Regulations can be charged as “Drug Control Regulations” or “Drug Hazard Control Regulations”. In order to solve the above problems and more accurately predict the article and charge, we plan to include the article content or charge names in the input, and use the sentence-pair classification method for question-answer problems in the BERT model to improve the performance. We will also consider a sequence-to-sequence approach to charge prediction.

Keywords: legal judgment prediction, deep learning, natural language processing, BERT, data visualization

Procedia PDF Downloads 119

Authors: Loredana Elena Nita, Maria Bercea, Aurica P. Chiriac, Iordana Neamtu

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The paper is devoted to the behavior of gels based on poly(itaconic anhydride-co-3, 9-divinyl-2, 4, 8, 10-tetraoxaspiro (5.5) undecane) copolymers, with different ratio between the comonomers, and hyaluronic acid (HA). The gel formation was investigated by small-amplitude oscillatory shear measurements following the viscoelastic behavior as a function of gel composition, temperature and shear conditions. Hyaluronic acid was investigated in the same conditions and its rheological behavior is typical to viscous fluids. In the case of the copolymers, the ratio between the two comonomers influences the viscoelastic behavior, a higher content of itaconic anhydride favoring the gel formation. Also, the sol-gel transition was evaluated according to Winter-Chambon criterion that identifies the gelation point when the viscoelastic moduli (G’ and G”) behave similarly as a function of oscillation frequency. From rheological measurements, an optimum composition was evidenced for which the system presents a typical gel-like behavior at 37 °C: the elastic modulus is higher than the viscous modulus and they are not dependent on the oscillation frequency. The formation of the 3D macroporous network was also evidenced by FTIR spectra, SEM microscopy and chemical imaging. These hydrogels present a high potential as drug delivery systems.

Keywords: copolymer, viscoelasticity, gelation, 3D network

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Authors: Glenda Marie D. Balitaan

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The branch of business management that deals with inventory planning and control is known as inventory management. It comprises keeping track of supply levels and forecasting demand, as well as scheduling when and how to plan. Keeping excess inventory results in a loss of money, takes up physical space, and raises the risk of damage, spoilage, and loss. On the other hand, too little inventory frequently causes operations to be disrupted and raises the possibility of low customer satisfaction, both of which can be detrimental to a company's reputation. The United Victorious Feed mill Corporation's present inventory management practices were assessed in terms of inventory level, warehouse allocation, ordering frequency, shelf life, and production requirement. To help the company achieve their optimal level of inventory, a mathematical model was created using Integer Linear Programming. Due to the season, the goal function was to reduce the cost of purchasing US Soya and Yellow Corn. Warehouse space, annual production requirements, and shelf life were all considered. To ensure that the user only uses one application to record all relevant information, like production output and delivery, the researcher built a Visual Basic system. Additionally, the technology allows management to change the model's parameters.

Keywords: inventory management, integer linear programming, inventory management system, feed mill

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Authors: Netta Horesh Reinman

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The inability to communicate feelings and thoughts to people close to oneself may be an important risk factor for suicidal behavior. This inability has been operationalized in the concept of “self-disclosure.” The purpose of this paper was to evaluate the correlation of self-disclosure with suicidal behavior in adolescents. Eighty consecutive admissions to an adolescent psychiatric inpatient unit were evaluated. Thirty-four were suicide attempters, 18 were suicidal ideators, and 18 were non-suicidal. Assessment measures included the Child Suicide Potential Scale, the Suicide Intent Scale, the Suicide Ideation Scale, and the Self-Disclosure Scale. The results show that low self-disclosure levels are associated with suicidal thinking, suicide attempts and suicidal attitudes. Thus, low self-disclosure may well be a risk factor worthy of further evaluation in the attempt to understand adolescent suicidal behavior.

Keywords: self disclosure, suicide, adolescents, treatment

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Authors: Sabina Huč, Staffan Svensson, Tomaž Hozjan

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Timber structures may be exposed to various environmental conditions during their service life. Often, the structures have to resist extreme changes in the relative humidity of surrounding air, with simultaneously carrying the loads. Wood material response for this load case is seen as increasing deformation of the timber structure. Relative humidity variations cause moisture changes in timber and consequently shrinkage and swelling of the material. Moisture changes and loads acting together result in mechano-sorptive creep, while sustained load gives viscoelastic creep. In some cases, magnitude of the mechano-sorptive strain can be about five times the elastic strain already at low stress levels. Therefore, analyzing mechano-sorptive creep and its influence on timber structures’ long-term behavior is of high importance. Relatively many one-dimensional rheological models for rheological behavior of wood can be found in literature, while a number of models coupling creep response in each material direction is limited. In this study, mathematical formulation of a coupled two-dimensional mechano-sorptive model and its application to the experimental results are presented. The mechano-sorptive model constitutes of a moisture transport model and a mechanical model. Variation of the moisture content in wood is modelled by multi-Fickian moisture transport model. The model accounts for processes of the bound-water and water-vapor diffusion in wood, that are coupled through sorption hysteresis. Sorption defines a nonlinear relation between moisture content and relative humidity. Multi-Fickian moisture transport model is able to accurately predict unique, non-uniform moisture content field within the timber member over time. Calculated moisture content in timber members is used as an input to the mechanical analysis. In the mechanical analysis, the total strain is assumed to be a sum of the elastic strain, viscoelastic strain, mechano-sorptive strain, and strain due to shrinkage and swelling. Mechano-sorptive response is modelled by so-called spring-dashpot type of a model, that proved to be suitable for describing creep of wood. Mechano-sorptive strain is dependent on change of moisture content. The model includes mechano-sorptive material parameters that have to be calibrated to the experimental results. The calibration is made to the experiments carried out on wooden blocks subjected to uniaxial compressive loaded in tangential direction and varying humidity conditions. The moisture and the mechanical model are implemented in a finite element software. The calibration procedure gives the required, distinctive set of mechano-sorptive material parameters. The analysis shows that mechano-sorptive strain in transverse direction is present, though its magnitude and variation are substantially lower than the mechano-sorptive strain in the direction of loading. The presented mechano-sorptive model enables observing real temporal and spatial distribution of the moisture-induced strains and stresses in timber members. Since the model’s suitability for predicting mechano-sorptive strains is shown and the required material parameters are obtained, a comprehensive advanced analysis of the stress-strain state in timber structures, including connections subjected to constant load and varying humidity is possible.

Keywords: mechanical analysis, mechano-sorptive creep, moisture transport model, timber

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Authors: E. Verduci, I. Aguglia, A. Filocamo, I. Macrì, R. Scala, A. Vinci

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One of the first indicator of autism spectrum disorder (ASD) is a decreasing tendency or failure to respond to name (RTN) call. Despite RTN is important for social and language developmentand it’s a common target for early interventions for children with ASD, research on specific treatments is insufficient and does not consider the importance of the discrimination between the own name and other names. The purpose of the current study was to replicate an assessment and treatment model proposed by Conine et al. (2020) to teach children with ASD to respond to their own name and to not respond to other names (RTO). The model includes three different phases (baseline/screening, treatment, and generalization), and itgradually introduces the different treatment components, starting with the most naturalistic ones (such as social interaction) and adding more intrusive components (such as tangible reinforcements, prompt and fading procedures) if necessary. The participants of this study were three children with ASD diagnosis: D. (5 years old) with a low frequency of RTN, M. (7 years old) with a RTN unstable and no ability of discrimination between his name and other names, S. (3 years old) with a strong RTN but a constant response to other names. Moreover, the treatment for D. and M. consisted of social and tangible reinforcements (treatment T1), for S. the purpose of the treatment was to teach the discrimination between his name and the others. For all participants, results suggest the efficacy of the model to acquire the ability to selectively respond to the own name and the generalization of the behavior with other people and settings.

Keywords: response to name, autism spectrum disorder, progressive training, ABA

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Authors: Sagar Hedaoo, Fazle Baki, Ahmed Azab

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In supply chain management, network design for scalable manufacturing facilities is an emerging field of research. Facility location allocation assigns facilities to customers to optimize the overall cost of the supply chain. To further optimize the costs, capacities of these facilities can be changed in accordance with customer demands. A mathematical model is formulated to fully express the problem at hand and to solve small-to-mid range instances. A dedicated constraint has been developed to restrict emissions in line with the Kyoto protocol. This problem is NP-Hard; hence, a simulated annealing metaheuristic has been developed to solve larger instances. A case study on the USA-Canada cross border crossing is used.

Keywords: emission, mixed integer linear programming, metaheuristic, simulated annealing

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Authors: Shari S. C. Shang, Lynn S. L. Chiu

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In the digital payment market, some consumers use only one payment wallet while many others play multi-homing with a variety of payment services. With the diffusion of new payment systems, we examined the determinants of the adoption of multi-homing behavior. This study aims to understand how a digital payment provider dynamically expands business touch points with cross-business strategies to enrich the digital ecosystem and avoid the trap of multi-homing in customers. By synthesizing platform ecosystem literature, we constructed a two-dimensional research framework with one determinant of user digital behavior from offline to online intentions and the other determinant of digital payment touch points from convenient accessibility to cross-business platforms. To explore on a broader scale, we selected 12 digital payments from 5 countries of UK, US, Japan, Korea, and Taiwan. With the interplays of user digital behaviors and payment touch points, we group the study cases into four types: (1) Channel Initiated: users originated from retailers with high access to in-store shopping with face-to-face guidance for payment adoption. Providers offer rewards for customer loyalty and secure the retailer’s efficient cash flow management. (2) Social Media Dependent: users usually are digital natives with high access to social media or the internet who shop and pay digitally. Providers might not own physical or online shops but are licensed to aggregate money flows through virtual ecosystems. (3) Early Life Engagement: digital banks race to capture the next generation from popularity to profitability. This type of payment aimed to give children a taste of financial freedom while letting parents track their spending. Providers are to capitalize on the digital payment and e-commerce boom and hold on to new customers into adulthood. (4) Traditional Banking: plastic credit cards are purposely designed as a control group to track the evolvement of business strategies in digital payments. Traditional credit card users may follow the bank’s digital strategy to land on different types of digital wallets or mostly keep using plastic credit cards. This research analyzed business growth models and inter-firms’ coopetition strategies of the selected cases. Results of the multiple case analysis reveal that channel initiated payments bundled rewards with retailer’s business discount for recurring purchases. They also extended other financial services, such as insurance, to fulfill customers’ new demands. Contrastively, social media dependent payments developed new usages and new value creation, such as P2P money transfer through network effects among the virtual social ties, while early life engagements offer virtual banking products to children who are digital natives but overlooked by incumbents. It has disrupted the banking business domains in preparation for the metaverse economy. Lastly, the control group of traditional plastic credit cards has gradually converted to a BaaS (banking as a service) model depending on customers’ preferences. The multi-homing behavior is not avoidable in digital payment competitions. Payment providers may encounter multiple waves of a multi-homing threat after a short period of success. A dynamic cross-business collaboration strategy should be explored to continuously evolve the digital ecosystems and allow users for a broader shopping experience and continual usage.

Keywords: digital payment, digital ecosystems, multihoming users, cross business strategy, user digital behavior intentions

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Authors: Narumon Piaseu

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This survey research was aimed to describe and compare consumption behavior of health risk food among students in Suan Sunandha Rajabhat University. Sample included 400 undergraduate students enrolled in the first semester of 2008 academic year. Data were collected by using self reported questionnaire developed by the researcher. Data were then analyzed by descriptive statistics including frequency, percentage, mean, standard deviation, and inferential statistics including independent t-test, and Oneway ANOVA. Results revealed that most of the sample were women (67%), enrolled in social related programs (74%). Approximately half of them (45.5%) stayed in dormitory. The mean of monthly income was 5,164 Baht and daily food expenditure was 114.55 Baht. Majority of them (83%) had ready-to-eat food. A major factor influencing their food selection was their parents (61%). A main reason for their food selection was food that looks good (70.75%). Almost half of them (46.25%) had heavy exercise less than 3 times per week. Regarding knowledge on health risk food, 43.5% of the sample had good knowledge. The followings were moderate (41%) and poor (41%). Most of the sample (60.75%) had consumption behavior at low risk. The following was at moderate risk (37.25%). Only 2% were at high risk. Among the sample, consumption behavior of health risk food were significantly different in years of study (F = 3.168, p = .024), daily food expenditure (F = 8.950, p <.001), and knowledge on health risk food (F = 37.856, p <.001), while no significant difference in consumption behavior of health risk food was found in those with a difference in gender, program of study, living place, and monthly income. Results indicate the importance of providing knowledge regarding health risk food for students and their parents in order to promote appropriate food consumption behavior among the students.

Keywords: food consumption, risky behavior, Suan Sunandha Rajabhat University, health risk

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Authors: Johannes Atug, Andreas Radke, Mitchell Tseng, Gunther Reinhart

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In modern supply chains, large numbers of SKU (Stock-Keeping-Unit) need to be timely managed, and any delays in noticing disruptions of items often limit the ability to defer the impact on customer order fulfillment. However, in supply chains of IoT-connected enterprises, the ERP (Enterprise-Resource-Planning), the MES (Manufacturing-Execution-System) and the SCADA (Supervisory-Control-and-Data-Acquisition) systems generate large amounts of data, which generally glean much earlier notice of deviations in the business process steps. That is, analyzing these streams of data with process mining techniques allows the monitoring of the supply chain business processes and thus identification of items that deviate from the standard order fulfillment process. In this paper, a framework to enable event-based SCM (Supply-Chain-Management) processes including an overview of core enabling technologies are presented, which is based on the RAMI (Reference-Architecture-Model for Industrie 4.0) architecture. The application of this framework in the industry is presented, and implications for SCM in industry 4.0 and further research are outlined.

Keywords: cyber-physical production systems, event-based monitoring, supply chain management, RAMI (Reference-Architecture-Model for Industrie 4.0)

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Authors: Charita Jashi

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The aim of the paper is to explore the role of social marketing in changing the behavior of consumers on road safety, identify critical aspects and priority needs which impede the implementation of road safety program in Georgia. Given the goals of the study, a quantitative method was used to carry out interviews for primary data collection. This research identified the awareness level of road safety, legislation base, and marketing interventions to change behavior of drivers and pedestrians. During several years the non-governmental sector together with the local authorities and media have been very intensively working on the road safety issue in Georgia, but only seat-belts campaign should be considered rather successful. Despite achievements in this field, efficiency of road safety programs far from fulfillment and needs strong empowering.

Keywords: road safety, social marketing interventions, behavior change, well-being

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Authors: Ela Ari, Aysi̇ma Findikoglu

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Consumers’ switching GSM operators’ has been an important research issue since the rise of their competitive offers. Recent research has looked at consumer switching behavior through the theory of planned behavior, but not yet extended the theory with identity, psycho-social and cultural influences within the service context. This research explores an extended version of the theory of planned behavior including social and financial risks and brand loyalty. Moreover, the role of individualism and collectivism at the individual level is investigated in a collectivistic culture that moves toward to individualism due to changing family relationships, use of technology and education. Our preliminary analysis showed that financial risk and vertical individualism prove to be a significant determinant of intention to switch. The study also investigates social risk and intention, subjective norm, perceived behavioral control relationship. The effect of individualism and collectivism and attitudes relationship has been also examined within a service industry. Implications for marketing managers and scholars are also discussed.

Keywords: attitude, individualism, intention, subjective norm

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Authors: Gargi S. Kumar, Mrinmoyi Kulkarni

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Food choice behavior is complex and determined by biological, psychological, socio-cultural, and economic factors. The past two decades, have seen dramatic changes in food consumption patterns among urban Indian consumers. The objective of the current study was to evaluate perceptions about changes with respect to food choice behavior. Ten participants [urban men and women] ranging in age from 40 to 65 were selected and in-depth interviews were conducted with a set of open ended questions. The recorded interviews were transcribed and thematically analyzed using inductive, open and axial coding. The results identified themes that act as drivers and consequences of change in food choice behavior. Drivers such as globalization [sub themes of urbanization, education, income, and work environment], media and advertising, changing gender roles, women in the workforce, and change in family structure have influenced food choice, both at an individual and national level. The consequences of changes in food choice were health implications, processed food consumption, food decisions driven by children and eating out among others. The study reveals that, over time, food choices change and evolve. However it is interesting to note how market forces and culture interact to influence individual behavior and the overall food environment which subsequently affects food choice and the health of the people.

Keywords: change, consequences, drivers, food choice, globalization

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Authors: A. A. Dare, E. U. Iniegbedion

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Industrial furnaces generally involve enclosures of fire typically initiated by the combustion of gases. The fire leads to temperature distribution inside the enclosure. A proper understanding of the temperature and velocity distribution within the enclosure is often required for optimal design and use of the furnace. This study was therefore directed at numerical modeling of temperature distribution inside an enclosure as typical in a furnace. A mathematical model was developed from the conservation of mass, momentum and energy. The stream function-vorticity formulation of the governing equations was solved by an alternating direction implicit (ADI) finite difference technique. The finite difference formulation obtained were then developed into a computer code. This was used to determine the temperature, velocities, stream function and vorticity. The effect of the wall heat conduction was also considered, by assuming a one-dimensional heat flow through the wall. The computer code (MATLAB program) developed was used for the determination of the aforementioned variables. The results obtained showed that the transient temperature distribution assumed a uniform profile which becomes more chaotic with increasing time. The vertical velocity showed increasing turbulent behavior with time, while the horizontal velocity assumed decreasing laminar behavior with time. All of these behaviours were equally reported in the literature. The developed model has provided understanding of heat transfer process in an industrial furnace.

Keywords: heat source, modelling, enclosure, furnace

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Authors: Abdelhakam A. Noreldien, Sakhr B. Abudarag, Muslim S. Eltoum, Salih O. Osman

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This paper presents an analytical study of Small Unmanned Aerial Vehicle (SUAV) dynamic stability derivatives. Simulating SUAV dynamics and analyzing its behavior at the earliest design stages is too important and more efficient design aspect. The approach suggested in this paper is using the wind tunnel experiment to collect the aerodynamic data and get the dynamic stability derivatives. AutoCAD Software was used to draw the case study (wildlife surveillance SUAV). The SUAV is scaled down to be 0.25% of the real SUAV dimensions and converted to a wind tunnel model. The model was tested in three different speeds for three different attitudes which are; pitch, roll and yaw. The wind tunnel results were then used to determine the case study stability derivative values, and hence it used to calculate the roots of the characteristic equation for both longitudinal and lateral motions. Finally, the characteristic equation roots were found and discussed in all possible cases.

Keywords: model, simulating, SUAV, wind tunnel

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Authors: Iman Farasat, Howard M. Salis

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Engineered genetic circuits reprogram cellular behavior to act as living computers with applications in detecting cancer, creating self-controlling artificial tissues, and dynamically regulating metabolic pathways. Phenemenological models are often used to simulate and design genetic circuit behavior towards a desired behavior. While such models assume that each circuit component’s function is modular and independent, even small changes in a circuit (e.g. a new promoter, a change in transcription factor expression level, or even a new media) can have significant effects on the circuit’s function. Here, we use statistical thermodynamics to account for the several factors that control transcriptional regulation in bacteria, and experimentally demonstrate the model’s accuracy across 825 measurements in several genetic contexts and hosts. We then employ our first principles model to design, experimentally construct, and characterize a family of signal amplifying genetic circuits (genetic OpAmps) that expand the dynamic range of cell sensors. To develop these models, we needed a new approach to measuring the in vivo binding free energies of transcription factors (TFs), a key ingredient of statistical thermodynamic models of gene regulation. We developed a new high-throughput assay to measure RNA polymerase and TF binding free energies, requiring the construction and characterization of only a few constructs and data analysis (Figure 1A). We experimentally verified the assay on 6 TetR-homolog repressors and a CRISPR/dCas9 guide RNA. We found that our binding free energy measurements quantitatively explains why changing TF expression levels alters circuit function. Altogether, by combining these measurements with our biophysical model of translation (the RBS Calculator) as well as other measurements (Figure 1B), our model can account for changes in TF binding sites, TF expression levels, circuit copy number, host genome size, and host growth rate (Figure 1C). Model predictions correctly accounted for how these 8 factors control a promoter’s transcription rate (Figure 1D). Using the model, we developed a design framework for engineering multi-promoter genetic circuits that greatly reduces the number of degrees of freedom (8 factors per promoter) to a single dimensionless unit. We propose the Ptashne (Pt) number to encapsulate the 8 co-dependent factors that control transcriptional regulation into a single number. Therefore, a single number controls a promoter’s output rather than these 8 co-dependent factors, and designing a genetic circuit with N promoters requires specification of only N Pt numbers. We demonstrate how to design genetic circuits in Pt number space by constructing and characterizing 15 2-repressor OpAmp circuits that act as signal amplifiers when within an optimal Pt region. We experimentally show that OpAmp circuits using different TFs and TF expression levels will only amplify the dynamic range of input signals when their corresponding Pt numbers are within the optimal region. Thus, the use of the Pt number greatly simplifies the genetic circuit design, particularly important as circuits employ more TFs to perform increasingly complex functions.

Keywords: transcription factor, synthetic biology, genetic circuit, biophysical model, binding energy measurement

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Authors: Hounyèmè Romuald, Mama Daouda, Argillier Christine

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The present study focused on the use of benthic macrofauna to define the reference state of an anthropized lagoon (Nokoué-Benin) from the responses of relevant metrics to proxies. The approach used is a combination of a joint species distribution model and Bayesian networks. The joint species distribution model was used to select the relevant metrics and generate posterior probabilities that were then converted into posterior response probabilities for each of the quality classes (pressure levels), which will constitute the conditional probability tables allowing the establishment of the probabilistic graph representing the different causal relationships between metrics and pressure proxies. For the definition of the reference thresholds, the predicted responses for low-pressure levels were read via probability density diagrams. Observations collected during high and low water periods spanning 03 consecutive years (2004-2006), sampling 33 macroinvertebrate taxa present at all seasons and sampling points, and measurements of 14 environmental parameters were used as application data. The study demonstrated reliable inferences, selection of 07 relevant metrics and definition of quality thresholds for each environmental parameter. The relevance of the metrics as well as the reference thresholds for ecological assessment despite the small sample size, suggests the potential for wider applicability of the approach for aquatic ecosystem monitoring and assessment programs in developing countries generally characterized by a lack of monitoring data.

Keywords: pressure proxies, bayesian inference, bioindicators, acadjas, functional traits

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Authors: Hung-Yu Lin

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Background: Parts of researchers assert that external hyperactivity behaviors of ADHD children interfere with their abilities to perform internal cognitive tasks; however, there are still other researchers hold the opposite viewpoint, the external high level of activity may serve as the role of improving internal executive function.Objectives: Thisstudy explored the effects of external motor behavior of ADHD on internal visual attentional performance. Methods: A randomized, two-period crossover design was used in this study, a total of 80 children (aged 6-12) were recruited in this study. 40participants have received ADHD diagnosis, and others are children with typically developing. These children were measured through the visual edition of TOVA (The Test of Variables of Attention) when they wore actigraphy, their testing behavior and movement data werecollected through closely observation and the actigraphies under different research conditions. Result: According to the research result, the author found (1) Higherfrequencyof movement under attentional testing condition was found in children with ADHD, comparing to children with typically developing, and (2) Higher frequency of foot movement showed better attentional performance of the visual attentional test in children with ADHD. However, these results were not showed in children with typically developing. Conclusions: The findings support the functional working memory model, which advocated that a positive relation between gross motor activity and attentional performance within the context of attentive behavior in children with ADHD.

Keywords: ADHD, movement, visual attention, children

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Authors: Selvan Bellan, Koji Matsubara, Nobuyuki Gokon, Tatsuya Kodama, Hyun Seok-Cho

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In concentrated solar thermal industry, fluidized-bed technology has been used to produce hydrogen by thermochemical two step water splitting cycles, and synthetic gas by gasification of coal coke. Recently, couple of fluidized bed reactors have been developed and tested at Niigata University, Japan, for two-step thermochemical water splitting cycles and coal coke gasification using Xe light, solar simulator. The hydrodynamic behavior of the gas-solid flow plays a vital role in the aforementioned fluidized bed reactors. Thus, in order to study the dynamics of dense gas-solid flow, a CFD-DEM model has been developed; in which the contact forces between the particles have been calculated by the spring-dashpot model, based on the soft-sphere method. Heat transfer and hydrodynamics of a solar thermochemical fluidized bed reactor filled with ceria particles have been studied numerically and experimentally for beam-down solar concentrating system. An experimental visualization of particles circulation pattern and mixing of two-tower fluidized bed system has been presented. Simulation results have been compared with experimental data to validate the CFD-DEM model. Results indicate that the model can predict the particle-fluid flow of the two-tower fluidized bed reactor. Using this model, the key operating parameters can be optimized.

Keywords: solar reactor, CFD-DEM modeling, fluidized bed, beam-down solar concentrating system

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Authors: Zhaoan Wang

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Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation

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Authors: Lilia Righi

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Recently, the fashion industry has demonstrated a keen interest in sustainability and the environment. Sustainable fashion has huge potential and appeals to environmentally conscious Generation Z shoppers. Meanwhile, Generation Z customers have attracted researchers' interest due to their overconsumption of clothing. However, most studies in this area focus on designing or producing sustainable clothing, with little exploration of consumers. To fill this gap, the present study aims to determine the important factors influencing Generation Z consumers' decisions to purchase sustainable fashion by mobilizing the theory of planned behavior (TPB). It uses deductive qualitative research based on 18 semi-structured interviews with Generation Z consumers in France. Qualitative data will be analyzed using reflective thematic analysis. On a theoretical level, this research contributes to enriching the literature by mobilizing, for the first time, the theory of planned behavior in the context of sustainable fashion. On a practical level, the results can help practitioners determine effective marketing strategies to persuade Generation Z to consume sustainable clothing.

Keywords: generation Z, qualitative methodology, sustainable fashion, theory of planned behavior (TPB).

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Authors: Mohamed M. El Gendy, Ibrahim A. El Arabi, Rafeek W. Abdel-Missih, Omar A. Kandil

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Nonlinear analysis is one of the most important design and safety tools in structural engineering. Based on the finite-element method, a geometrical and material nonlinear analysis of large span reinforced concrete arches is carried out considering soil-structure interaction. The concrete section details and reinforcement distribution are taken into account. The behavior of soil is considered via Winkler's and continuum models. A computer program (NARC II) is specially developed in order to follow the structural behavior of large span reinforced concrete arches up to failure. The results obtained by the proposed model are compared with available literature for verification. This work confirmed that the geometrical and material nonlinearities, as well as soil structure interaction, have considerable influence on the structural response of reinforced concrete arches.

Keywords: nonlinear analysis, reinforced concrete arched structure, soil-structure interaction, geotechnical engineering

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Authors: Pankhuri Dagaonkar, Charumani Singh, Poornima Krothapalli, Krishna Karthik

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The backbone of any retail e-commerce success story is a unique design of supply chain network, providing the business an unparalleled speed and scalability. Primary goal of the supply chain strategy is to meet customer expectation by offering fastest deliveries while keeping the cost minimal. Meeting this objective at the large market that India provides is the problem statement that we have targeted here. There are many models and optimization techniques focused on network design to identify the ideal facility location and size, optimizing cost and speed. In this paper we are presenting a tactical approach to optimize cost of an existing network for a predefined speed. We have considered both forward and reverse logistics of a retail e-commerce supply chain consisting of multiple fulfillment (warehouse) and delivery centers, which are connected via sortation nodes. The mathematical model presented here determines if the shipment from a node should get sorted directly for the last mile delivery center or it should travel as consolidated package to another node for further sortation (resort). The objective function minimizes the total cost by varying the resort percentages between nodes and provides the optimal resource allocation and number of sorts at each node.

Keywords: distribution strategy, mathematical model, network design, supply chain management

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Authors: Mariel L. Alonzo, Patricia Mae T. Chi, Juliana Patrice P. Mayormita, Sanjana A. Sorio

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Compassion fade proposes an inverse relationship between the magnitude of stimuli to elicited compassion. This phenomenon is viewed within a framework that integrates a 3-Act Compassion structure with Latané and Darley’s Unresponsive Bystander Model and Prospect Theory of Decision-making under risk. Students (N=211) from Ateneo de Davao were sampled to examine the effects of mass perception (increasing number of needy persons) and intertemporal choice (soon versus later) on volunteering behavior. Collegiate classes in their natural setting were randomly assigned to five different treatment groups and were presented with audiovisual presentations featuring an increasing number of needy persons. The students were deceived to believe that two hypothetical feeding programs for Marawi refugees, taking place in 1 month and 6 months, were in need of volunteers for its preparatory phase. Results show a statistically significant (p=0.000; p=0.013) non-linear trend consistently for both feeding programs. There was a decrease in volunteered time means as identifiable victims increased from 0-47 and an increase as it progressed towards 267 non-identifiable victims. Highest interest was expressed for the 0 needy people shown and least for 47. The 0 hours volunteered was consistently the mode and median in all treatments. There was no statistically significant temporal discounting effect.

Keywords: compassion, group perception, identifiable victim, intertemporal choice, prosocial behavior, unresponsive bystander

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Authors: Buddhi Arachchige, Hessam Ghasemnejad

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In this study, the post impact behavior of curved composite plates subjected to low velocity impact was studied analytically and numerically. Approaches to damage modelling are proposed through the degradation of stiffness in the damaged region by reduction of thickness in the damage region. Spring-mass models were used to model the impact response of the plate and impactor. The study involved designing two damage models to compare and contrast the model best fitted with the numerical results. The theoretical force-time responses were compared with the numerical results obtained through a detailed study carried out in LS-DYNA. The modified damage model established a good prediction with the analytical force-time response for different layups and geometry. This study provides a gateway in selecting the most effective layups for variable stiffness curved composite panels able to withstand a higher impact damage.

Keywords: analytical modelling, composite damage, impact, variable stiffness

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Authors: Meng-Jou Chien, Jheng-Cheng Chen, Chang-Hsiung Tsai

Abstract:

Let maxζG(m) denote the maximum number of edges in a subgraph of graph G induced by m nodes. The n-dimensional augmented cube, denoted as AQn, a variation of the hypercube, possesses some properties superior to those of the hypercube. We study the cases when G is the augmented cube AQn.

Keywords: interconnection network, augmented cube, induced subgraph, bisection width

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Authors: Rhoda N. Kayongo

Abstract:

As behavior analysts in education continue to debate on how higher institutions can continue to benefit from their social and academic related programs, higher education is facing challenges in the area of character development. This is manifested in the percentages of college completion rates, teen pregnancies, drug abuse, sexual abuse, suicide, plagiarism, lack of academic integrity, and violence among their students. Attending college is a perceived opportunity to positively influence the actions and behaviors of the next generation of society; thus colleges and universities have to provide opportunities to develop students’ values and behaviors. Prior studies were mainly conducted in private institutions and more so in developed countries. However, with the complexity of the nature of student body currently due to the changing world, a multidimensional approach combining multiple factors that enhance character development outcomes is needed to suit the changing trends. The main purpose of this study was to identify opportunities in colleges and develop a model for predicting character development outcomes. A survey questionnaire composed of 7 scales including in-classroom interaction, out-of-classroom interaction, school climate, personal lifestyle, home environment, and peer influence as independent variables and character development outcomes as the dependent variable was administered to a total of five hundred and one students of 3rd and 4th year level in selected public colleges and universities in the Philippines and Rwanda. Using structural equation modelling, a predictive model explained 57% of the variance in character development outcomes. Findings from the results of the analysis showed that in-classroom interactions have a substantial direct influence on character development outcomes of the students (r = .75, p < .05). In addition, out-of-classroom interaction, school climate, and home environment contributed to students’ character development outcomes but in an indirect way. The study concluded that in the classroom are many opportunities for teachers to teach, model and integrate character development among their students. Thus, suggestions are made to public colleges and universities to deliberately boost and implement experiences that cultivate character within the classroom. These may contribute tremendously to the students' character development outcomes and hence render effective models of behaviour analysis in higher education.

Keywords: character development, tertiary institutions, predictive model, behavior analysis

Procedia PDF Downloads 133