Search results for: factor models

Authors: Quy Dang Nguyen, Reza Nakhaie Jazar

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The paper investigates vibration dynamics of tire-road separation for a quarter-car model; this separation model is developed to be close to the real situation considering the tire is able to separate from the ground plane. A set of piecewise linear mathematical models is developed and matches the in-contact and no-contact states to be considered as mother models for further investigations. The bound dynamics are numerically simulated in the time response and phase portraits. The separation analysis may determine which values of suspension parameters can delay and avoid the no-contact phenomenon, which results in improving ride comfort and eliminating the potentially dangerous oscillation. Finally, model verification is carried out in the MSC-ADAMS environment.

Keywords: quarter-car vibrations, tire-road separation, separation analysis, separation dynamics, ride comfort, ADAMS validation

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Authors: P. Sankar, P. James Daniel Paul, Siddhant Sahu

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A brief review of the empirical studies on the methodology of the stock market decision support would indicate that they are at a threshold of validating the accuracy of the traditional and the fuzzy, artificial neural network and the decision trees. Many researchers have been attempting to compare these models using various data sets worldwide. However, the research community is on the way to the conclusive confidence in the emerged models. This paper attempts to use the automotive sector stock prices from National Stock Exchange (NSE), India and analyze them for the intra-sectorial support for stock market decisions. The study identifies the significant variables and their lags which affect the price of the stocks using OLS analysis and decision tree classifiers.

Keywords: Indian automotive sector, stock market decisions, equity portfolio analysis, decision tree classifiers, statistical data analysis

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Authors: Sun Jin Park, Kyung-Ja Cho

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This study focused on characteristics related to hasty behaviour. To investigate the relation between personal characteristics and hasty behaviour, 601 data were collected, 335 males and 256 females answered their own 'social avoidance and distress’, ‘anxiety’, ‘sensation seeking', 'hope', and ' hasty behaviour. And then 591 data were used for the analysis. The factor analysis resulted hasty behaviour consisted of 5 factors, time pressure, isolation, uncomfortable situation, boring condition, and expectation of reward. The result showed anxiety, sensation seeking, and hope related to hasty behaviour. Specifically, anxiety was involved in every hasty behaviour. This result means that psychological tension and worry are related to hasty behaviour in common. 'Social avoidance and distress', 'sensation seeking' and 'hope' influenced on hasty behaviour under time pressure, in isolation, in expectation of rewards respectively. This means that each factor of hasty behaviour has anxiety as its basis, expressed through a varied nature.

Keywords: hasty behaviour, social avoidance and distress, anxiety, sensation seeking, hope

Procedia PDF Downloads 328

Authors: Milagros Jaén-Vargas, Javier García Martínez, Karla Miriam Reyes Leiva, María Fernanda Trujillo-Guerrero, Francisco Fernandes, Sérgio Barroso Gonçalves, Miguel Tavares Silva, Daniel Simões Lopes, José Javier Serrano Olmedo

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Human Activity Recognition (HAR) is having a growing impact in creating new applications and is responsible for emerging new technologies. Also, the use of wearable sensors is an important key to exploring the human body's behavior when performing activities. Hence, the use of these dispositive is less invasive and the person is more comfortable. In this study, a database that includes three activities is used. The activities were acquired from inertial measurement unit sensors (IMU) and motion capture systems (MOCAP). The main objective is differentiating the performance from four Deep Learning (DL) models: Deep Neural Network (DNN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and hybrid model Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), when considering acceleration, velocity and position and evaluate if integrating the IMU acceleration to obtain velocity and position represent an increment in performance when it works as input to the DL models. Moreover, compared with the same type of data provided by the MOCAP system. Despite the acceleration data is cleaned when integrating, results show a minimal increase in accuracy for the integrated signals.

Keywords: HAR, IMU, MOCAP, acceleration, velocity, position, feature maps

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Authors: Inaki Maulida Hakim, T. Yuri M. Zagloel, Astari Wulandari

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Six sigma is a framework that is used to identify inefficiency so that the cause of inefficiency will be known and right improvement to overcome cause of inefficiency can be conducted. This paper presents result of implementing six sigma to improve piston assembly line in Manufacturing Laboratory, Universitas Indonesia. Six sigma framework will be used to analyze the significant factor of inefficiency that needs to be improved which causes bottleneck in assembly line. After analysis based on six sigma framework conducted, line balancing method was chosen for improvement to overcome causative factor of inefficiency which is differences time between workstation that causes bottleneck in assembly line. Then after line balancing conducted in piston assembly line, the result is increase in efficiency. Efficiency is shown in the decreasing of Defects per Million Opportunities (DPMO) from 900,000 to 700,000, the increasing of level of labor productivity from 0.0041 to 0.00742, the decreasing of idle time from 121.3 seconds to 12.1 seconds, and the increasing of output, which is from 1 piston in 5 minutes become 3 pistons in 5 minutes.

Keywords: assembly line, line balancing, productivity, six sigma

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Authors: B. Van Kessel, P. T. Kockelkorn, T. R. Speelman, T. C. Wierikx, C. Mai Van, T. A. Bogaard

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Saltwater intrusion is a common problem in estuaries around the world, as it could hinder the freshwater supply of coastal zones. This problem is likely to grow due to climate change and sea-level rise. The influence of these factors on the saltwater intrusion was investigated for the Cai River in the Khanh Hoa province in Vietnam. In addition, the Cai River has high seasonal fluctuations in discharge, leading to increased saltwater intrusion during the dry season. Sea level rise, river discharge changes, river mouth widening and a proposed saltwater intrusion prevention dam can have influences on the saltwater intrusion but have not been quantified for the Cai River estuary. This research used both an analytical and numerical model to investigate the effect of the aforementioned factors. The analytical model was based on a model proposed by Savenije and was calibrated using limited in situ data. The numerical model was a 3D hydrodynamic model made using the Delft3D4 software. The analytical model and numerical model agreed with in situ data, mostly for tidally average data. Both models indicated a roughly similar dependence on discharge, also agreeing that this parameter had the most severe influence on the modeled saltwater intrusion. Especially for discharges below 10 m/s3, the saltwater was predicted to reach further than 10 km. In the models, both sea-level rise and river widening mainly resulted in salinity increments up to 3 kg/m3 in the middle part of the river. The predicted sea-level rise in 2070 was simulated to lead to an increase of 0.5 km in saltwater intrusion length. Furthermore, the effect of the saltwater intrusion dam seemed significant in the model used, but only for the highest position of the gate.

Keywords: Cai River, hydraulic models, river discharge, saltwater intrusion, tidal barriers

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Authors: Shaleeza Sohail

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Self, and peer evaluations are some of the main components in almost all group assignments and projects in higher education institutes. These evaluations provide students an opportunity to better understand the learning outcomes of the assignment and/or project. A number of online systems have been developed for this purpose that provides automated assessment and feedback of students’ contribution in a group environment based on self and peer evaluations. All these systems lack a progressive aspect of these assessments and feedbacks which is the most crucial factor for ongoing improvement and life-long learning. In addition, a number of assignments and projects are designed in a manner that smaller or initial assessment components lead to a final assignment or project. In such cases, the evaluation and feedback may provide students an insight into their performance as a group member for a particular component after the submission. Ideally, it should also create an opportunity to improve for next assessment component as well. Self and Peer Progressive Assessment and Feedback System encourages students to perform better in the next assessment by providing a comparative analysis of the individual’s contribution score on an ongoing basis. Hence, the student sees the change in their own contribution scores during the complete project based on smaller assessment components. Self-Assessment Factor is calculated as an indicator of how close the self-perception of the student’s own contribution is to the perceived contribution of that student by other members of the group. Peer-Assessment Factor is calculated to compare the perception of one student’s contribution as compared to the average value of the group. Our system also provides a Group Coherence Factor which shows collectively how group members contribute to the final submission. This feedback is provided for students and teachers to visualize the consistency of members’ contribution perceived by its group members. Teachers can use these factors to judge the individual contributions of the group members in the combined tasks and allocate marks/grades accordingly. This factor is shown to students for all groups undertaking same assessment, so the group members can comparatively analyze the efficiency of their group as compared to other groups. Our System provides flexibility to the instructors for generating their own customized criteria for self and peer evaluations based on the requirements of the assignment. Students evaluate their own and other group members’ contributions on the scale from significantly higher to significantly lower. The preliminary testing of the prototype system is done with a set of predefined cases to explicitly show the relation of system feedback factors to the case studies. The results show that such progressive feedback to students can be used to motivate self-improvement and enhanced team skills. The comparative group coherence can promote a better understanding of the group dynamics in order to improve team unity and fair division of team tasks.

Keywords: effective group work, improvement of team skills, progressive feedback, self and peer assessment system

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Authors: Amira M. Attia, Karim H. Youssef, Nabil H. Abbasi

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Demand Side Management (DSM) is an essential characteristic of current and future smart grid systems. As one of DSM functions, load management aims to control customers’ total electric consumption and utility’s load factor by using various load shaping techniques. However, applying load shaping techniques such as load shifting, peak clipping, or strategic conservation individually does not provide the desired level of improvement for load factor increment and/or customer’s bill reduction. In this paper, two load shaping techniques will be simulated as constrained optimization problems. The purpose is to reflect the application of combined load shifting and strategic conservation model together at the same time, and the application of combined load shifting and peak clipping model as well. The problem will be formulated and solved by using disciplined convex programming (CVX) based MATLAB® R2013b. Simulation results will be evaluated and compared for studying the most impactful multi-techniques model in improving load curve.

Keywords: convex programing, demand side management, load shaping, multiple, building energy optimization

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Authors: Aspasia Koutsokosta, Stefanos Katsavounis

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This paper reviews the model-based qualitative and quantitative Operations Management research in the context of Construction Supply Chain Management (CSCM). Construction industry has been traditionally blamed for low productivity, cost and time overruns, waste, high fragmentation and adversarial relationships. The construction industry has been slower than other industries to employ the Supply Chain Management (SCM) concept and develop models that support the decision-making and planning. However the last decade there is a distinct shift from a project-based to a supply-based approach of construction management. CSCM comes up as a new promising management tool of construction operations and improves the performance of construction projects in terms of cost, time and quality. Modeling the Construction Supply Chain (CSC) offers the means to reap the benefits of SCM, make informed decisions and gain competitive advantage. Different modeling approaches and methodologies have been applied in the multi-disciplinary and heterogeneous research field of CSCM. The literature review reveals that a considerable percentage of CSC modeling accommodates conceptual or process models which discuss general management frameworks and do not relate to acknowledged soft OR methods. We particularly focus on the model-based quantitative research and categorize the CSCM models depending on their scope, mathematical formulation, structure, objectives, solution approach, software used and decision level. Although over the last few years there has been clearly an increase of research papers on quantitative CSC models, we identify that the relevant literature is very fragmented with limited applications of simulation, mathematical programming and simulation-based optimization. Most applications are project-specific or study only parts of the supply system. Thus, some complex interdependencies within construction are neglected and the implementation of the integrated supply chain management is hindered. We conclude this paper by giving future research directions and emphasizing the need to develop robust mathematical optimization models for the CSC. We stress that CSC modeling needs a multi-dimensional, system-wide and long-term perspective. Finally, prior applications of SCM to other industries have to be taken into account in order to model CSCs, but not without the consequential reform of generic concepts to match the unique characteristics of the construction industry.

Keywords: construction supply chain management, modeling, operations research, optimization, simulation

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Authors: Sahar Heidary, Ramin Ghasemi Shayan

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The overall goal Monte Carlo N-atom radioactivity transference PC program (MCNP4C) was done for the regeneration of x-ray groups in diagnostic radiology and mammography. The electrons were transported till they slow down and stopover in the target. Both bremsstrahlung and characteristic x-ray creation were measured in this study. In this issue, the x-ray spectra forecast by several computational models recycled in the diagnostic radiology and mammography energy kind have been calculated by appraisal with dignified spectra and their outcome on the scheming of absorbed dose and effective dose (ED) told to the adult ORNL hermaphroditic phantom quantified. This comprises practical models (TASMIP and MASMIP), semi-practical models (X-rayb&m, X-raytbc, XCOMP, IPEM, Tucker et al., and Blough et al.), and Monte Carlo modeling (EGS4, ITS3.0, and MCNP4C). Images got consuming synchrotron radiation (SR) and both screen-film and the CR system were related with images of the similar trials attained with digital mammography equipment. In sight of the worthy feature of the effects gained, the CR system was used in two mammographic inspections with SR. For separately mammography unit, the capability acquiesced bilateral mediolateral oblique (MLO) and craniocaudal(CC) mammograms attained in a woman with fatty breasts and a woman with dense breasts. Referees planned the common groups and definite absences that managed to a choice to miscarry the part that formed the scientific imaginings.

Keywords: mammography, monte carlo, effective dose, radiology

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Authors: Shyam, G. N. Tiwari

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Energy matrices of flate plate water collectors partially covered by PV module have been estimated in the present study. Photovoltaic thermal (PVT) water collector assembly is consisting of 5 water collectors having 2 m^2 area which are partially covered by photovoltaic module at its lower portion (inlet) and connected in series. The annual overall thermal energy and exergy are computed by using climatic data of New Delhi provided by Indian Meteorological Department (IMD) Pune, India. The Energy payback time on overall thermal and exergy basis are found to be 1.6 years and 17.8 years respectively. For 25 years of life time of system the energy production factor and life cycle conversion efficiency are estimated to be 15.8 and 0.04 respectively on overall thermal energy basis whereas for the same life time the energy production factor and life cycle conversion efficiency on exergy basis are obtained as 1.4 and 0.001.

Keywords: overall thermal energy, exergy, energy payback time, PVT water collectors

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Authors: Sevde Altuntas, Fatih Buyukserin

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Alzheimer’s disease is responsible for irreversible neural damage of brain parts. One of the disease markers is Amyloid-β 1-42 protein that accumulates in the brain in the form plaques. The basic problem for detection of the protein is the low amount of protein that cannot be detected properly in body liquids such as blood, saliva or urine. To solve this problem, tests like ELISA or PCR are proposed which are expensive, require specialized personnel and can contain complex protocols. Therefore, Surface-enhanced Raman Spectroscopy (SERS) a good candidate for detection of Amyloid-β 1-42 protein. Because the spectroscopic technique can potentially allow even single molecule detection from liquid and solid surfaces. Besides SERS signal can be improved by using nanopattern surface and also is specific to molecules. In this context, our study proposes to fabricate diagnostic test models that utilize Au-coated nanopatterned polycarbonate (PC) surfaces modified with Thioflavin - T to detect low concentrations of Amyloid-β 1-42 protein in water and artificial saliva medium by the enhancement of protein SERS signal. The nanopatterned PC surface that was used to enhance SERS signal was fabricated by using Anodic Alumina Membranes (AAM) as a template. It is possible to produce AAMs with different column structures and varying thicknesses depending on voltage and anodization time. After fabrication process, the pore diameter of AAMs can be arranged with dilute acid solution treatment. In this study, two different columns structures were prepared. After a surface modification to decrease their surface energy, AAMs were treated with PC solution. Following the solvent evaporation, nanopatterned PC films with tunable pillared structures were peeled off from the membrane surface. The PC film was then modified with Au and Thioflavin-T for the detection of Amyloid-β 1-42 protein. The protein detection studies were conducted first in water via this biosensor platform. Same measurements were conducted in artificial saliva to detect the presence of Amyloid Amyloid-β 1-42 protein. SEM, SERS and contact angle measurements were carried out for the characterization of different surfaces and further demonstration of the protein attachment. SERS enhancement factor calculations were also completed via experimental results. As a result, our research group fabricated diagnostic test models that utilize Au-coated nanopatterned polycarbonate (PC) surfaces modified with Thioflavin-T to detect low concentrations of Alzheimer’s Amiloid – β protein in water and artificial saliva medium. This work was supported by The Scientific and Technological Research Council of Turkey (TUBITAK) Grant No: 214Z167.

Keywords: alzheimer, anodic aluminum oxide, nanotopography, surface enhanced Raman spectroscopy

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Authors: Ramin Amirmardfar

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Throughout Necessary oxygen should be supplied for all cells of a mammal at any moment through blood to make it possible remain alive all cells the mammal’s body. In case a mammal’s bulk is large, there is a farther distance between cells in different tissues and mammals’ heart. Therefore red blood cells in bulky mammal’s body should be capable of conveying oxygen to farther distances. To make it practical, oxygen should be glued red blood cells tenaciously. In other words, cohesion strength of oxygen to red blood cell of bulky mammal’s blood should be much more than the same of small mammal’s blood. In mammal’s bodies, the controlling factor of amount of cohesion of oxygen to red blood cell, are organic phosphates (like DPG). The less DPG in red blood cells of a mammal, the more cohesion of oxygen to red blood cell (at the same rate). As much as oxygen is glued more tenacious to red blood cells, oxygen could been carried to farther distance and as much as oxygen could be conveyed to farther points of heart, bulk of mammal could be larger at the same rate.

Keywords: mammals size, animals size, organic phosphates, DPG, red blood cell, metabolism

Procedia PDF Downloads 355

Authors: Tsai-chun Lai, Szu-ju Fu, Tzu-lin Lee, Yuh-Lien Chen

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There is much evidence that exposure to fine particulate matter (PM) from air pollution increases the risk of cardiovascular morbidity and mortality. According to previous reports, PM in the air enters the respiratory tract, contacts the alveoli, and enters the blood circulation, leading to the progression of cardiovascular disease. PM pollution may also lead to cardiometabolic disturbances, increasing the risk of cardiovascular disease. The effects of PM on cardiac function and mitochondrial damage are currently unknown. We used mice and rat cardiomyocytes (H9c2) as animal and in vitro cell models, respectively, to simulate an air pollution environment using PM. These results indicate that the apoptosis-related factor PUMA, a regulator of apoptosis upregulated by p53, is increased in mice treated with PM. Apoptosis was aggravated in cardiomyocytes treated with PM, as measured by TUNEL assay and Annexin V/PI. Western blot results showed that CASPASE3 was significantly increased and BCL2 (B-cell lymphoid 2) was significantly decreased under PM treatment. Concurrent exposure to PM increases mitochondrial reactive oxygen species (ROS) production by MitoSOX Red staining. Furthermore, using Mitotracker staining, PM treatment significantly shortened mitochondrial length, indicating mitochondrial fission. The expression of mitochondrial fission-related proteins p-DRP1 (phosphodynamics-related protein 1) and FIS1 (mitochondrial fission 1 protein) was significantly increased. Based on these results, the exposure to PM worsens mitochondrial function and leads to cardiomyocyte apoptosis.

Keywords: particulate matter, cardiomyocyte, apoptosis, mitochondria

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Authors: Made Rahayu Putri Saron, Mochamad Nizar Palefi Ma’ady

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Communication skills are important in everyday life, communication can be done verbally in the form of oral or written and nonverbal in the form of expressions or body movements. Good communication should be able to provide information clearly, and there is feedback from the speaker and listener. However, it is often found that the information conveyed is not clear, and there is no feedback from the listeners, so it cannot be ensured that the communication is effective and understandable. The speaker's understanding of the topic is one of the supporting factors for the listener to be able to accept the meaning of the conversation. However, based on the results of the literature review, it found that the influence factors of person speaking style are as follows: (i) environmental conditions; (ii) voice, articulation, and accent; (iii) gender; (iv) personality; (v) speech disorders (Dysarthria); when speaking also have an important influence on speaker’s speaking style. It can be concluded the factors that support understanding and comfort of the listener are dependent on the nature of the speaker (environmental conditions, voice, gender, personality) or also it the speaker have speech disorders.

Keywords: listener, public speaking, speaking style, understanding, and comfortable factor

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Authors: V. Pérez-Herranz, C. González-Buch, E. M. Ortega, S. Mestre

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In this work new macroporous Ni electrodes modified with Au nanoparticles for hydrogen production have been developed. The supporting macroporous Ni electrodes have been obtained by means of the electrodeposition at high current densities. Then, the Au nanoparticles were synthesized and added to the electrode surface. The electrocatalytic behaviour of the developed electrocatalysts was studied by means of pseudo-steady-state polarization curves, electrochemical impedance spectroscopy (EIS) and hydrogen discharge curves. The size of the Au synthetized nanoparticles shows a monomodal distribution, with a very sharp band between 10 and 50 nm. The characteristic parameters d10, d50 and d90 were 14, 20 and 31 nm respectively. From Tafel polarization data has been concluded that the Au nanoparticles improve the catalytic activity of the developed electrodes towards the HER respect to the macroporous Ni electrodes. EIS permits to obtain the electrochemically active area by means of the roughness factor value. All the developed electrodes show roughness factor values in the same order of magnitude. From the activation energy results it can be concluded that the Au nanoparticles improve the intrinsic catalytic activity of the macroporous Ni electrodes.

Keywords: Au nano particles, hydrogen evolution reaction, porous Ni electrodes, electrochemical impedance spectroscopy

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Authors: L. Ramirez, E. Guillén, J. Sánchez

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Some of the main goals about telecare such as monitoring, treatment, telediagnostic are deployed with the integration of applications with specific appliances. In order to achieve a coherent model to integrate software, hardware, and healthcare systems, different telehealth models with Internet of Things (IoT), cloud computing, artificial intelligence, etc. have been implemented, and their advantages are still under analysis. In this paper, we propose an integrated model based on IoT architecture and cloud computing telehealth center. Analytics module is presented as a solution to control an ideal diagnostic about some diseases. Specific features are then compared with the recently deployed conventional models in telemedicine. The main advantage of this model is the availability of controlling the security and privacy about patient information and the optimization on processing and acquiring clinical parameters according to technical characteristics.

Keywords: analytics, telemedicine, internet of things, cloud computing

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Authors: Yanhua Ma, Lu Zhai, Xinchen Wang, Hongyu Liang

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In this paper, by understanding the development status of the human-machine interface in today's automobile cab, a subjective and objective evaluation system for evaluating the optimization of human-machine interface matching in automobile cab was established. The man-machine interface of the car cab was divided into a software interface and a hard interface. Objective evaluation method of software human factor analysis is used to evaluate the hard interface matching; The analytic hierarchy process is used to establish the evaluation index system for the software interface matching optimization, and the multi-level fuzzy comprehensive evaluation method is used to evaluate hard interface machine. This article takes Dongfeng Sokon (DFSK) C37 model automobile as an example. The evaluation method given in the paper is used to carry out relevant analysis and evaluation, and corresponding optimization suggestions are given, which have certain reference value for designers.

Keywords: analytic hierarchy process, fuzzy comprehension evaluation method, human-machine interface, matching optimization, software human factor analysis

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Authors: Sixing Chen, Shuai Yang

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Online celebrity business, also known as Internet celebrity business (or Wanghong business in Chinese), is an emerging relational C2C business model, and an alternative to traditional C2C transactional business models. There are already millions of these consumers, and this number is growing. In this model, consumer purchase decisions are driven by recommendations and endorsements in videos posted online by celebrities. The purpose of this paper is to determine the relational constructs within consumer relationships in the Internet celebrity business model and to investigate relationships between the constructs and consumer purchase intention. A questionnaire-based study was conducted with consumers who had an awareness of, or prior purchase experience with online celebrities. The results of exploratory factor analysis (EFA) and multiple regression analysis revealed three valid relational constructs: product experience sharing, lifestyle association, and real-time interaction. This study indicated that these constructs had the direct effect on consumer preference and purchase intention. The findings of this study provide insight into a business model in which online shopping is driven by celebrities. They suggest that online celebrities should pay more attention to product experience sharing, life style association and real-time interaction for managing their product promotions. These are the most salient factors with respect to the relational constructs identified in this study.

Keywords: customer relationship, customer to customer, Internet celebrity, online celebrity, online marketing, purchase intention

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Authors: Fahad Alanazi, Andrew Jones

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Digital forensics seeks to achieve the successful investigation of digital crimes through obtaining acceptable evidence from digital devices that can be presented in a court of law. Thus, the digital forensics investigation is normally performed through a number of phases in order to achieve the required level of accuracy in the investigation processes. Since 1984 there have been a number of models and frameworks developed to support the digital investigation processes. In this paper, we review a number of the investigation processes that have been produced throughout the years and introduce a proposed digital forensic model which is based on the scope of the Saudi Arabia investigation process. The proposed model has been integrated with existing models for the investigation processes and produced a new phase to deal with a situation where there is initially insufficient evidence.

Keywords: digital forensics, process, metadata, Traceback, Sauid Arabia

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Authors: Martin K. Steiger, Lukas Heisler, Hans-Georg Brachtendorf

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Deep neural networks and their variants form the backbone of many AI applications. Based on the so-called residual networks, a continuous formulation of such models as ordinary differential equations (ODEs) has proven advantageous since different techniques may be applied that significantly increase the learning speed and enable controlled trade-offs with the resulting error at the same time. For the evaluation of such models, high-performance numerical differential equation solvers are used, which also provide the gradients required for training. However, whether classical gradient-based methods are even applicable or which one yields the best results has not been discussed yet. This paper aims to redeem this situation by providing empirical results for different applications.

Keywords: deep neural networks, gradient-based learning, image processing, ordinary differential equation networks

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Authors: Alice Schittek, Isabelle Roskam, Moira Mikolajczak

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Background: Perfectionistic strivings (PS) and perfectionistic concerns (PC) are associated with an increase in parental burnout (PB), and PB causally increases violence towards the offspring. Objective: To our best knowledge, no study has ever investigated whether perfectionism (PS and PC) predicts violence towards the offspring and whether PB could explain this link. We hypothesized that an increase in PS and PC would lead to an increase in violence via an increase in PB. Method: 228 participants responded to an online survey, with three measurement occasions spaced two months apart. Results: Contrary to expectations, cross-lagged path models revealed that violence towards the offspring prospectively predicts an increase in PS and PC. Mediation models showed that PB is not a significant mediator. The results of all models did not change when controlling for social desirability. Conclusion: The present study shows that violence towards the offspring increases the risk of PS and PC in parents, which highlights the importance of understanding the effect of child maltreatment on the whole family system and not just on children. Results are discussed in light of the feeling of guilt experienced by parents. Considering the insignificant mediation effect, PB research should slowly shift towards more (quasi) causal designs, allowing to identify which significant correlations translate into causal effects. Implications: Clinicians should focus on preventing child maltreatment as well as treating parental perfectionism. Researchers should unravel the effects of child maltreatment on the family system.

Keywords: maltreatment, parental burnout, perfectionistic strivings, perfectionistic concerns, perfectionism, violence

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Authors: Greeshma Sharma, Sushil Chandra, Vijander Singh, Alok Prakash Mittal

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Navigational ability requires spatial representation, planning, and memory. It covers three interdependent domains, i.e. cognitive and perceptual factors, neural information processing, and variability in brain microstructure. Many attempts have been made to see the role of spatial representation in the navigational ability, and the individual differences have been identified in the neural substrate. But, there is also a need to address the influence of planning, memory on navigational ability. The present study aims to evaluate relations of aforementioned factors in the navigational ability. Total 30 participants volunteered in the study of a virtual shopping complex and subsequently were classified into good and bad navigators based on their performances. The result showed that planning ability was the most correlated factor for the navigational ability and also the discriminating factor between the good and bad navigators. There was also found the correlations between spatial memory recall and navigational ability. However, non-verbal episodic memory and spatial memory recall were also found to be correlated with the learning variable. This study attempts to identify differences between people with more and less navigational ability on the basis of planning and memory.

Keywords: memory, planning navigational ability, virtual reality

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Authors: Sarah Potter, Michele Laliberte

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As eating disorders are associated with high levels of chronicity, impairment, and distress, it is paramount to evaluate factors that may improve treatment outcomes in this group. Individuals with eating disorders exhibit elevated levels of perfectionism and emotion dysregulation, as well as reduced self-compassion. These variables are related to eating disorder outcomes, including shape/weight concerns and psychosocial impairment. Thus, these factors may be tenable targets for treatment within eating disorder populations. However, the relative contributions of perfectionism, emotion dysregulation, and self-compassion to the severity of shape/weight concerns and psychosocial impairment remain largely unexplored. In the current study, mediation analyses were conducted to clarify how perfectionism, emotion dysregulation, and self-compassion are linked to shape/weight concerns and psychosocial impairment. The sample was comprised of 85 patients from an outpatient eating disorder clinic. The patients completed self-report measures of perfectionism, self-compassion, emotion dysregulation, eating disorder symptoms, and psychosocial impairment. Specifically, emotion dysregulation was assessed as a mediator in the relationships between (1) perfectionism and shape/weight concerns, (2) self-compassion and shape/weight concerns, (3) perfectionism and psychosocial impairment, and (4) self-compassion and psychosocial impairment. It was postulated that emotion dysregulation would significantly mediate relationships in the former two models. An a priori hypothesis was not constructed in reference to the latter models, as these analyses were preliminary and exploratory in nature. The PROCESS macro for SPSS was utilized to perform these analyses. Emotion dysregulation fully mediated the relationships between perfectionism and eating disorder outcomes. In the link between self-compassion and psychosocial impairment, emotion dysregulation partially mediated this relationship. Finally, emotion dysregulation did not significantly mediate the relationship between self-compassion and shape/weight concerns. The results suggest that emotion dysregulation and self-compassion may be suitable targets to decrease the severity of psychosocial impairment and shape/weight concerns in individuals with eating disorders. Further research is required to determine the stability of these models over time, between diagnostic groups, and in nonclinical samples.

Keywords: eating disorders, emotion dysregulation, perfectionism, self-compassion

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Authors: Babak Darvish Rouhani, Mohd Nazri Mahrin, Fatemeh Nikpay, Pourya Nikfard, Maryam Khanian Najafabadi

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Enterprise Architecture (EA) is a strategy that is employed by enterprises in order to align their business and Information Technology (IT). EA is managed, developed, and maintained through Enterprise Architecture Implementation Methodology (EAIM). The effectiveness of EA implementation is the degree in which EA helps to achieve the collective goals of the organization. This paper analyzes the results of a survey that aims to explore the factors that affect the effectiveness of EAIM and specifically the relationship between factors and effectiveness of the output and functionality of EA project. The exploratory factor analysis highlights a specific set of five factors: alignment, adaptiveness, support, binding, and innovation. The regression analysis shows that there is a statistically significant and positive relationship between each of the five factors and the effectiveness of EAIM. Consistent with theory and practice, the most prominent factor for developing an effective EAIM is innovation. The findings contribute to the measuring the effectiveness of EA implementation project by providing an indication of the measurement implementation approaches which is used by the Enterprise Architects, and developing an effective EAIM.

Keywords: enterprise architecture, enterprise architecture implementation methodology, implementation methodology, factors, EA, effectiveness

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Authors: Xu Wang

Abstract:

This research builds linear regressions of U.S. macroeconomic condition and volatility measures in the investment grade and high yield Credit Default Swap index spreads using monthly data from March 2009 to July 2016, to study the relationship between different dimensions of macroeconomy and overall credit risk quality. The most significant contribution of this research is systematically examining individual and joint effects of macroeconomic condition and volatility on CDX spreads by including macroeconomic time series that captures different dimensions of the U.S. economy. The industrial production index growth, non-farm payroll growth, consumer price index growth, 3-month treasury rate and consumer sentiment are introduced to capture the condition of real economic activity, employment, inflation, monetary policy and risk aversion respectively. The conditional variance of the macroeconomic series is constructed using ARMA-GARCH model and is used to measure macroeconomic volatility. The linear regression model is conducted to capture relationships between monthly average CDX spreads and macroeconomic variables. The Newey–West estimator is used to control for autocorrelation and heteroskedasticity in error terms. Furthermore, the sensitivity factor analysis and standardized coefficients analysis are conducted to compare the sensitivity of CDX spreads to different macroeconomic variables and to compare relative effects of macroeconomic condition versus macroeconomic uncertainty respectively. This research shows that macroeconomic condition can have a negative effect on CDX spread while macroeconomic volatility has a positive effect on determining CDX spread. Macroeconomic condition and volatility variables can jointly explain more than 70% of the whole variation of the CDX spread. In addition, sensitivity factor analysis shows that the CDX spread is the most sensitive to Consumer Sentiment index. Finally, the standardized coefficients analysis shows that both macroeconomic condition and volatility variables are important in determining CDX spread but macroeconomic condition category of variables have more relative importance in determining CDX spread than macroeconomic volatility category of variables. This research shows that the CDX spread can reflect the individual and joint effects of macroeconomic condition and volatility, which suggests that individual investors or government should carefully regard CDX spread as a measure of overall credit risk because the CDX spread is influenced by macroeconomy. In addition, the significance of macroeconomic condition and volatility variables, such as Non-farm Payroll growth rate and Industrial Production Index growth volatility suggests that the government, should pay more attention to the overall credit quality in the market when macroecnomy is low or volatile.

Keywords: autoregressive moving average model, credit spread puzzle, credit default swap spread, generalized autoregressive conditional heteroskedasticity model, macroeconomic conditions, macroeconomic uncertainty

Procedia PDF Downloads 167

Authors: Leila Najeh

Abstract:

This study investigates the motivational factors influencing Tunisian university students learning English through online platforms. Using a mixed-methods approach, data were collected from 112 undergraduate students of English across universities in Tunisia. The study employed an online questionnaire to measure intrinsic and extrinsic motivation, incorporating the Learning Motivation Questionnaire (FFLLM-Q) developed by Gonzales in 2001 and semi-structured interviews to explore students’ perspectives on their online learning experiences. Quantitative analysis revealed a significant correlation between intrinsic motivation and interactive features such as gamification and adaptive content delivery, while extrinsic motivation was strongly linked to career aspirations and academic requirements. Qualitative findings highlighted challenges such as limited interaction with peers and teachers, technical constraints, and a lack of immediate feedback as demotivating factors. Participants expressed a preference for blended learning models, combining the flexibility of online education with the collaborative environment of traditional classrooms. This study underscores the need for tailored online learning solutions to enhance the motivational landscape for Tunisian students, emphasizing the importance of culturally relevant content, accessible platforms, and supportive learning communities. Further research is recommended to evaluate the long-term impact of these interventions on language proficiency and learner autonomy.

Keywords: motivational factor, online foreign language learnig, tunsian students of english, online learning platforms

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Authors: Meity Sompie, Agnes Triasih, Wisje Ponto

Abstract:

Edible coating is thin layers that act as a barrier to the external factors and protect the food products. The addition of the plasticizer to the edible coating is required to overcome film caused by extensive intermolecular forces. The potential development of pigskin with different ages as a raw material for the manufacture of edible films had not been widely publicized. This research was aimed to determine the influence of gelatin concentration and different type of plasticizer on the edible coating characteristics extracted from pigskin gelatin. This study used Completely Randomized Design (CRD) with two factors and three replicates of treatments. The first factor was consisted of pigskin gelatin concentration ( 10, 20, and 30 %) and the second factor was different type of plasticizer (glycerol, sorbitol and PEG). The results show that the interaction between the use of gelatin concentrations and type of plasticizer had significant effect (P< 0.05) on the thickness, tensile strength, elongation, water vapor transmission rate (WVTR), water content and amino acid profile of edible coating. It was concluded that the edible coating from pigskin gelatin with plasticizer gliserol had the best film characteristics, and it can be applied as an edible coating.

Keywords: edible coating, edible film, pigskin gelatin, plasticizer

Procedia PDF Downloads 215

Authors: Okoro Ikechukwu Ralph, Fuat Kara

Abstract:

The discoveries of hydrocarbon reserves has clearly drifted offshore, and in deeper waters - areas where the industry still has limited knowledge; and that were hitherto, regarded as being out of reach. This shift presents significant and increased challenges in technology requirements needed to guarantee safety of personnel, environment and equipment; ensure high reliability of installed equipment; and provide high level of confidence in security of investment and company reputation. Nowhere are these challenges more apparent than on subsea well integrity and production performance. The past two decades has witnessed enormous rise in deep and ultra-deep water offshore field developments for the recovery of hydrocarbons. Subsea installed equipment at the seabed has been the technology of choice for these developments. This paper discusses the role of Subsea Control module (SCM) as a vital factor for deep-water well integrity and production performance. A case study for Deep-water well integrity and production performance is analysed.

Keywords: offshore reliability, production performance, subsea control module, well integrity

Procedia PDF Downloads 512

Authors: Arunas Burinskas, Manuela Tvaronavičienė

Abstract:

Although the new trade theories, unlike the theories of an industrial organisation, see the structure of the market and competition between enterprises through their heterogeneity according to various parameters, they do not pay any particular attention to the analysis of the market structure and its development. In this article, although we relied mainly on models developed by the scholars of new trade theory, we proposed a different approach. In our simulation model, we model market demand according to normal distribution function, while on the supply side (as it is in the new trade theory models), productivity is modeled with the Pareto distribution function. The results of the simulation show that companies with higher productivity (lower marginal costs) do not pass on all the benefits of such economies to buyers. However, even with higher marginal costs, firms can choose to offer higher value-added goods to stay in the market. In general, the structure of the market is formed quickly enough and depends on the skills available to firms.

Keywords: market, structure, simulation, heterogenous firms

Procedia PDF Downloads 149