Analysis Of Behavior Research Articles

Analysis of surimi extrusion behavior during 3D printing by modified Computational Fluid Dynamics (CFD) and quick prediction of printability using machine learning based on texture data

The purpose of this study was to develop a modifying Computational Fluid Dynamics (CFD) model for precise analysis of surimi extrusion behavior and establish a machine learning method for quickly prediction of surimi printability. The 2D rotational axisymmetric model used in this study to replace the 3D/4D physical model, which could improve the simulation efficiency. To improve the accuracy of the CFD simulations, the wall “no-slip” boundary condition assumed in the textbook was replaced with a boundary condition of wall slip. This reduced the error between the simulated results and the measured ones to <1%, and thus calculated required extrusion pressure below 17,034 Pa for printability. The CFD calculation efficiency was improved 33 times than the previously reports by the modifying CFD model, and the simulated results for the required extrusion pressure of inks could be obtained within 10 s. Additionally, a machine-learning method (partial least squares regression model) based on texture data was proposed to quickly predict the required extrusion pressure of surimi to assessed printability. The machine learning model showed a good performance with an R2 > 0.95.

Network-based representations and dynamic discrete choice models for multiple discrete choice analysis

In many choice modeling applications, consumer demand is frequently characterized as multiple discrete, which means that consumer choose multiple items simultaneously. The analysis and prediction of consumer behavior in multiple discrete choice situations pose several challenges. In this paper, to address this, we propose a random utility maximization (RUM) based model that considers each subset of choice alternatives as a composite alternative, where individuals choose a subset according to the RUM framework. While this approach offers a natural and intuitive modeling approach for multiple-choice analysis, the large number of subsets of choices in the formulation makes its estimation and application intractable. To overcome this challenge, we introduce directed acyclic graph (DAG) based representations of choices where each node of the DAG is associated with an elemental alternative and additional information such as the number of selected elemental alternatives. Our innovation is to show that the multi-choice model is equivalent to a recursive route choice model on the DAG, leading to the development of new efficient estimation algorithms based on dynamic programming. In addition, the DAG representations enable us to bring some advanced route choice models to capture the correlation between subset choice alternatives. Numerical experiments based on synthetic and real datasets show many advantages of our modeling approach and the proposed estimation algorithms.

Analysis of the Dynamical Behavior of a Modified Cubic-Map with a Discrete Memristor

Analysis of the Dynamical Behavior of a Modified Cubic-Map with a Discrete Memristor

Rebar-concrete bond behaviour in grouted sleeve connectors

Grouted sleeve connectors (GSCs) are commonly used in precast/prefabricated concrete structures. To ensure force transfer, connectors tend to be overdesigned, and this has a detrimental effect on the plastic deformation capacity of the connection region and the displacement ductility of the precast structure. To enable improvements in the design of precast RC connections involving GSCs, an accurate analysis of the bond behaviour of GSCs is required. This paper presents an analytical model for the local bond behaviour under the particular sleeve confinement. A representative cross-section of a GSC is treated as interconnected hollow circular tubes. Three stages are identified according to the state of the grout, namely elastic, partially cracked, and fully cracked. The confining pressure is formulated within the cross-section, and the bond stress is subsequently evaluated by a modified bond stress-slip law accounting explicitly for the confinement. Compared with traditional bond-slip laws, the model is capable of representing the evolution of confining stress in the loading process. Comparison with relevant experimental results show good agreement. A subsequent parametric study demonstrates the trends of influence of various parameters, and notably, within allowable limits, a reduction of the grout thickness tends to increase the bond strength in the connectors.

The extended finite element method in endodontics: A scoping review and future directions for cyclic fatigue testing of nickel-titanium instruments.

The present study reviews the current literature regarding the utilization of the extended finite element method (XFEM) in clinical and experimental endodontic studies and the suitability of XFEM in the assessment of cyclic fatigue in rotary endodontic nickel-titanium (NiTi) instruments. An electronic literature search was conducted using the appropriate search terms, and the titles and abstracts were screened for relevance. The search yielded 13 hits after duplicates were removed, and four studies met the inclusion criteria for review. No studies to date have utilized XFEM to study cyclic fatigue or crack propagation in rotary endodontic NiTi instruments. Challenges such as modelling material inputs and fatigue criteria could explain the lack of utilization of XFEM in the analysis of mechanical behavior in NiTi instruments. The review showed that XFEM was seldom employed in endodontic literature. Recent work suggests potential promise in using XFEM for modelling NiTi structures.

Theoretical Analysis of Behavior of FRP-Strengthened Reinforced Concrete Members Subjected to Combined Torsion and Biaxial Bending

Theoretical Analysis of Behavior of FRP-Strengthened Reinforced Concrete Members Subjected to Combined Torsion and Biaxial Bending

Microarray-based analysis of differential gene expression profile in rotenone-induced Parkinson's disease zebrafish model.

Despite much clinical and laboratory research that has been performed to explore the mechanisms of Parkinson's disease (PD), its pathogenesis remains elusive to date. Therefore, this study aimed to identify possible regulators of neurodegeneration by performing microarray analysis of the zebrafish PD model's brain following rotenone exposure. A total of 36 adult zebrafish were divided into two groups: control (n = 17) and rotenone-treated (n = 19). Fish were treated with rotenone water (5 µg/L water) for 28 days and subjected to locomotor behavior analysis. Total RNA was extracted from the brain tissue after rotenone treatment. The cDNA synthesized was subjected to microarray analysis and subsequently validated by qPCR. Administration of rotenone has significantly reduced locomotor activity in zebrafish (p < 0.05), dysregulated dopamine-related gene expression (dat, th1, and th2, p < 0.001), and reduced dopamine level in the brain (p < 0.001). In the rotenone-treated group, genes involved in cytotoxic T lymphocytes (gzm3, cd8a, p < 0.001) and T cell receptor signaling (themis, lck, p < 0.001) were upregulated significantly. Additionally, gene expression involved in microgliosis regulation (tyrobp, p < 0.001), cellular response to IL-1 (ccl34b4, il2rb, p < 0.05), and regulation of apoptotic process (dedd1, p < 0.001) were also upregulated significantly. The mechanisms of T cell receptor signaling, microgliosis regulation, cellular response to IL-1, and apoptotic signaling pathways have potentially contributed to PD development in rotenone-treated zebrafish.

Consumer Behaviour Analysis for AI Services in the Tourism Industry

Amidst the integration of Artificial Intelligence (AI) and robotics, this study investigates consumer behaviour with a specific emphasis on the determinants that impact the adoption and purchase of AI tourism applications by tourists, thereby augmenting their perceived value. The study aims to identify the factors that impact tourists’ inclination to adopt and buy AI tourism applications, with a focus on enhancing perceived value. Using data collected from a survey of 301 visitors of different nationalities visiting Greece, this study conducts structural equation modelling to assess the relationship between technology adoption and certain factors influencing customers’ perceived value in the tourism sector, considering the Value Adoption Model (VAM). Findings indicate that suggested modifications in the VAM demonstrate that factors including Happiness, Perceived Immersion, Trust and Effort are relevant to the successful acceptance concept of paying for using AI tourism apps. The most likely outcome is the mediating role of Perceived Value in willingness to accept and pay for AI tourism apps. The study recontextualizes the VAM theory by analyzing the acceptance of AI apps in tourism and hospitality sector research. The findings are valuable to hotel directors, ICT developers, and researchers studying the difficulties of technology adoption and implementation of service management in the hospitality industry.

Mass evacuation planning for disasters management: A household evacuation route choice behavior analysis

This paper presents a multi-methodological approach to analyzing household evacuation route choice behaviors and the related decision-making for mass evacuation planning in disaster management. Specifically, the proposed multi-methodological approach integrates a syncretic risk perception conceptual model with a household-based group utility evolution model. The dynamics of household evacuation route choice are explored in two stages, namely the individual utility initiation and accommodation. The unique feature of the proposed approach is that it links individual risk perception, survival psychology, and group behavioral dynamics together to characterize household decision-making about choosing the evacuation routes. An empirical study coupled with experiments is conducted to help validate the proposed household evacuation route choice behavior model. Through various designed disaster scenarios, the applicability and strengths of the proposed model for mass evacuation planning and management are demonstrated. Particularly, the mean relative prediction errors of the proposed model with respect to household-based evacuation route switching probability and path flow splits are 3.79% and 6.88%, respectively, all within an acceptable range of ±10 %. This demonstrates that the proposed model and analytical results align closely with household choice behavior.

Machining behaviour analysis of PBF-LB warped components with internal lattice microstructures

Metal additive Powder Bed Fusion, Laser Based (PBF-LB) manufacturing offers significant improvements in the design of complex parts of inner components areas for several sectors, from dies and moulds, to blades and aerofoils. Generating internal structures helps to move fluids, work as heat exchanges, or achieve dramatic weight relief, only possible by additive manufacturing, concretely PBF-LB. Along with these designs, sculptured surfaces and warped surfaces are also common in blades and other aerodynamic pieces. However, it is mandatory that these designs accomplish the final required mechanical properties without surface damage and non-admissible dimensional deviations. In this study, the five-axis milling of a part containing internal structures has been investigated. Two types of PBF-LB Inconel® 718 blades were manufactured, one solid and one with internal microstructures. They were finished using two types of ball-ended mills, ball and barrel-lens tooltip. The analysis of the blade with internal structures shows better machining behaviour, dynamic behaviour, and surface quality.

Analysis of nonlinear bending behavior of nano-switches considering surface effects

Nano-switch structures are important control elements in nanoelectromechanical systems and have potential applications in future nanodevices. This paper analyzes the effects of surface effects, geometric nonlinearity, electrostatic forces, and intermolecular forces on the nonlinear bending behavior and adhesion stability of nano-switches. Based on the Von Karman geometric nonlinearity theory, four types of boundary conditions for the nano-switch structure were specifically calculated. The results show that surface effects have a significant impact on the nonlinear bending and adhesion stability of nano-switches. Surface effects increase the adhesion voltage of the nano-switch and decrease its adhesion displacement, and as the size of the nano-switch structure increases, the impact of surface effects decreases. A comparative analysis of the linear theory and the nonlinear theory results shows that the adhesion voltage predicted by the linear theory is smaller than that predicted by the nonlinear theory. The effect of geometric nonlinearity increases as the size of the nano-switch structure increases, as the distance between the electrodes increases, and as the aspect ratio of the nano-switch structure increases. These findings provide theoretical support and reference for the design and use of future nanodevices and nanoelectromechanical systems.

Experiment and simulation study on the functional fatigue of shape memory alloy beam actuators

The functional fatigue behavior of shape memory alloy (SMA) beam actuators is gaining importance as their utilization in engineering applications becomes more widespread. However, research on the functional fatigue behavior of SMA beam actuators under bending conditions is not as extensive as that on SMA wires. In this paper, an experimental study and theoretical analysis of the functional fatigue behavior of SMA beam actuators were conducted. A measuring method for bending deflection and an automatic thermal cyclic test bench was designed. A series of functional fatigue tests were conducted on SMA beam actuators under different bias load conditions and the functional fatigue patterns were obtained. The material damage factor is defined and calculated through specimen tests. By incorporating the damage factor to modify the existing constitutive model, a model considering functional fatigue and tension-compression asymmetry is obtained. Finite element analysis (FEA) is performed based on this modified model to simulate the actuating performance of SMA beam actuators and to compute the deflection at different numbers of cycles. Additionally, a small parameter study on the actuator shape is conducted using FEA. By comparing the FEA results with functional fatigue experimental data, the effectiveness of the modified model is validated, demonstrating its capability to describe functional fatigue and predict actuator lifespan.

A Bibliometric Analysis of Employee Withdrawal Behaviour: Current Status, Development, and Future Research Directions

A Bibliometric Analysis of Employee Withdrawal Behaviour: Current Status, Development, and Future Research Directions

Miller capacitance reduction in negative capacitance TFETs

ABSTRACT A dielectric stacked hetero-gate topology is proposed to reduce the Miller capacitance in a negative capacitance double gate TFET. An analytical charge-based model is introduced for the analysis of the terminal capacitance behaviour of the device. Charge and capacitance models are developed using the surface potential modelling approach by solving the Poisson Equation. The proposed closed-form charge model is SPICE-compatible and can be used for circuit simulations. The model accuracy is validated by combining one-dimensional Landau–Khalatnikov equation with the two-dimensional simulations of the double gate stacked-hetero-gate tunnel field effect transistor. The model shows excellent agreement with device simulations. The proposed topology exhibits Miller capacitance reduction of 30% which results in the gain band width product improvement of 43% more than the stacked homo-gate counterpart.

Observation system for the technical-tactical analysis of judo by the Rio 2016 Olympic champions.

An observational methodology system has been designed which allows the observation and analysis of the technical-tactical behaviour and interaction of judokas during competition. The observation instrument (JUTACTIC) is composed of 8 fixed criteria that provide information related to the competition and the competitors and 13 variable criteria that, throughout the intrasessional monitoring of each combat, allow the behaviour displayed by both judokas and their interaction to be recorded. From an observational sample consisting of matches from the Rio 2016 Olympic champions and the corresponding samples made using the LINCE PLUS software, evidence of validity, reliability, generalizability and applicability of the observation system is provided. The content validity of the observation instrument has been endorsed by a panel of experts (n = 11). Intra and inter-observer reliability has been guaranteed from the results obtained in the Fleiss Kappa and the Krippendorff Alpha. The generalizability analysis with the design structure [Category] [Participants] / [Matches] has confirmed that around seven matches are needed to accurately analyse the behaviour of the competitor under study. The practical application possibilities of the observation instrument has been shown with an example of the results obtained and the regular behaviour structures detected (T-patterns) using the THEME software.

Financial Literacy and Investment Choices: Unravelling the Knowledge-behaviour Gap among Women

Uncovering the knowledge-behaviour gap is the main goal of this research article, which explores the relationship between women's financial literacy and investment decision-making. This study attempts to clarify the variables causing differences in women investors' financial knowledge and their actual investing behaviours, acknowledging the importance of making educated financial decisions. With a thorough study approach that includes surveys, interviews, and behavioural analysis, we aim to determine the main factors impacting women's investing decisions as well as the degree to which financial literacy leads to wise choices. With an eye towards overcoming the observed gap, our studies attempt to illuminate the complex link between knowledge acquisition and real-world application in the financial domain.

Modeling travel mode choice behavior for planned special events using CPT-based HI-MADM approach

ABSTRACT Planned special events (PSEs) can significantly increase traffic demand, posing greater challenges than daily operations. In response, host cities often invest heavily in transportation upgrades. This study proposes a model integrating cumulative prospect theory (CPT) and multiple-attribute decision-making to understand mode choice behavior of PSE attendees. This integration enables direct extraction of traveler preference information, offering a more suitable description of the decision-making process. The decision matrix considers mode and attribute heterogeneity. The reference point for CPT is derived from previous PSE trips or commutes. Furthermore, this paper assesses asymmetric nonlinear sensitivity and distorted perceptions of different attributes. Analysis of mode-choice behavior for PSE participation, using survey data from Tianjin, China, validates the approach. It better characterizes PSE choice behaviors and demonstrates varying sensitivity to gains and losses, dependent on different attributes and distances. Thus, event planners should prioritize improving travel time and convenience to increase public transport mode share.

Coupling intention and actions of vehicle–pedestrian interaction: A virtual reality experiment study

The interactions between vehicles and pedestrians are complex due to their interdependence and coupling. Understanding these interactions is crucial for the development of autonomous vehicles, as it enables accurate prediction of pedestrian crossing intentions, more reasonable decision-making, and human-like motion planning at unsignalized intersections. Previous studies have devoted considerable effort to analyzing vehicle and pedestrian behavior and developing models to forecast pedestrian crossing intentions. However, these studies have two limitations. First, they mainly focus on investigating variables that explain pedestrian crossing behavior rather than predicting pedestrian crossing intentions. Moreover, some factors such as age, sensation seeking and social value orientation, used to establish decision-making models in these studies are not easily accessible in real-world scenarios. In this paper, we explored the critical factors influencing the decision-making processes of human drivers and pedestrians respectively by using virtual reality technology. To do this, we considered available kinematic variables and analyzed the internal relationship between motion parameters and pedestrian behavior. The analysis results indicate that longitudinal distance and vehicle acceleration are the most influential factors in pedestrian decision-making, while pedestrian speed and longitudinal distance also play a crucial role in determining whether the vehicle yields or not. Furthermore, a mathematical relationship between a pedestrian’s intention and kinematic variables is established for the first time, which can help dynamically assess when pedestrians desire to cross. Finally, the results obtained in driver-yielding behavior analysis provide valuable insights for autonomous vehicle decision-making and motion planning.

Synthetic Data for Video Surveillance Applications of Computer Vision: A Review

AbstractIn recent years, there has been a growing interest in synthetic data for several computer vision applications, such as automotive, detection and tracking, surveillance, medical image analysis and robotics. Early use of synthetic data was aimed at performing controlled experiments under the analysis by synthesis approach. Currently, synthetic data are mainly used for training computer vision models, especially deep learning ones, to address well-known issues of real data, such as manual annotation effort, data imbalance and bias, and privacy-related restrictions. In this work, we survey the use of synthetic training data focusing on applications related to video surveillance, whose relevance has rapidly increased in the past few years due to their connection to security: crowd counting, object and pedestrian detection and tracking, behaviour analysis, person re-identification and face recognition. Synthetic training data are even more interesting in this kind of application, to address further, specific issues arising, e.g., from typically unconstrained image or video acquisition conditions and cross-scene application scenarios. We categorise and discuss the existing methods for creating synthetic data, analyse the synthetic data sets proposed in the literature for each of the considered applications, and provide an overview of their effectiveness as training data. We finally discuss whether and to what extent the existing synthetic data sets mitigate the issues of real data, highlight existing open issues, and suggest future research directions in this field.

Analysis of Sound Propagation Behaviors for Supersonic Jet on Far Field Region by Computational Aero-Acoustics (CAA) Simulation

Noise emission is an essential issue for the aviation industry, as it harms health and induces various physiological responses. The noise generated by supersonic jets is very intense. It will cause fatigue and even damage the human hearing system in the surrounding area of jet operation. Besides, the experimental and prototyping cost for the jet model is prohibitive, and it is a vast project and process that takes a lot of time to run. The purpose of this study is to determine the sound propagation behaviours of a supersonic jet in the far-field region and to analyse the consequences of the velocity of a supersonic jet on sound propagation of supersonic jet by using computational fluid dynamics (CFD) and computational aeroacoustics (CAA) simulations. This study focused on the perspective of observing the distance of the receiver when receiving the sound propagation of a supersonic jet, the observed angle of the receiver when receiving the sound propagation of a supersonic jet, and the velocity of the supersonic jet. The CFD and CAA analyses were performed in transient state simulation and the 2-inch Acoustics Reference Nozzle (ARN2). The result shows that the overall SPL throughout the frequency is proportional to the jet velocity of the supersonic jet. However, the distance and angle of the receiver gave different results in sound propagation behaviour. The results also conclude that as the distance between the receiver and jet nozzle exit increases, the overall SPL trend will decrease throughout the frequency increase. As the vertical distance between the receiver and the axisymmetric line of the jet nozzle increases, the frequency of the receiver starts to observe will decrease.