Search results for: cognitive models

Authors: Armansyah, I. P. Almanar, M. Saiful Bahari Shaari, M. Shamil Jaffarullah

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Finite element approach have been used via three-dimensional models by using Altair Hyper Work, a commercially available software, to describe heat gradients along the welding zones (axially and coronaly) in Friction Stir Welding (FSW). Transient thermal finite element analyses are performed in AA 6061-T6 Aluminum Alloy to obtain temperature distribution in the welded aluminum plates during welding operation. Heat input from tool shoulder and tool pin are considered in the model. A moving heat source with a heat distribution simulating the heat generated by frictions between tool shoulder and work piece is used in the analysis. The developed model was then used to show the effect of various input parameters such as total rate of welding speed and rotational speed on temperature distribution in the work piece.

Keywords: Frictions Stir Welding (FSW), temperature distribution, Finite Element Method (FEM), altair hyperwork

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Authors: Ahmed S. Abdulrasool

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Recently sand wall started to gain more attention as the sand is easy to compact by using vibroflotation technique. An advantage of sand wall is the availability of different additives that can be mixed with sand to increase the stiffness of the sand wall and hence to increase its performance. In this paper, the bearing capacity of circular foundation surrounded by sand wall stabilized with lime is evaluated through laboratory testing. The studied parameters include different sand-lime walls depth (H/D) ratio (wall depth to foundation diameter) ranged between (0.0-3.0). Effect of lime percentages on the bearing capacity of skirted foundation models is investigated too. From the results, significant change is occurred in the behavior of shallow foundations due to confinement of the soil. It has been found that (H/D) ratio of 2 gives substantial improvement in bearing capacity, and beyond (H/D) ratio of 2, there is no significant improvement in bearing capacity. The results show that the optimum lime content is 11%, and the maximum increase in bearing capacity reaches approximately 52% at (H/D) ratio of 2.

Keywords: bearing capacity, circular foundation, clay soil, lime-sand wall

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Authors: Abdallah Bouguettoucha, Derradji Chebli, Sara Aga, Agueniou Fazia

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The objective of this study was to looking for alternative materials (low cost) for the adsorption of textile dyes and optimizes the type which gives optimum adsorption and provides an explanation of the mechanism involved in the adsorption process. Adsorption of Orange II and Methylene blue on H2SO4 traited cone of Pinus brutia, was carried out at different initial concentrations of the dye (20, 50 and 100 mg / L) and at tow initial pH, pH 1 and 10 respectively. The models of Langmuir, Freundlich and Sips were used in this study to analyze the obtained results of the adsorption isotherm. PCB-0M had high adsorption capacities namely 32.8967 mg/g and 128.1651 mg/g, respectively for orange II and methylene blue and further indicated that the removal of dyes increased with increase in the ionic strength of solution, this was attributed to aggregation of dyes in solution. The potential of H2SO4 traited cone of Pinus brutia, an easily available and low cost material, to be used as an alternative biosorbent material for the removal of a dyes, Orange II and Methylene Bleu, from aqueous solutions was therefore confirmed.

Keywords: Methylene blue, orange II, cones of pinus brutia, adsorption

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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: Ci Lin, Tet Yeap, Iluju Kiringa

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This paper introduces the subspace rotation algorithm (SRA) to train the Restricted Hopfield Network (RHN) as an auto-associative memory. Subspace rotation algorithm is a gradient-free subspace tracking approach based on the singular value decomposition (SVD). In comparison with Backpropagation Through Time (BPTT) on training RHN, it is observed that SRA could always converge to the optimal solution and BPTT could not achieve the same performance when the model becomes complex, and the number of patterns is large. The AUTS case study showed that the RHN model trained by SRA could achieve a better structure of attraction basin with larger radius(in general) than the Hopfield Network(HNN) model trained by Hebbian learning rule. Through learning 10000 patterns from MNIST dataset with RHN models with different number of hidden nodes, it is observed that an several components could be adjusted to achieve a balance between recovery accuracy and noise resistance.

Keywords: hopfield neural network, restricted hopfield network, subspace rotation algorithm, hebbian learning rule

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Authors: Anwar Hussain, Ahmed Imran, Farida Faisal, Fatima Sultana

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The present research evaluates a comparative assessment of dividend policy and share price across the South Asian countries including Pakistan, India and Sri-Lanka over the period of 2010 to 2014. Academic writers found that dividend policy and share price relationship is not same in south Asian market due to different reasons. Moreover, Panel Models used = for the evaluation of current study. In addition, Redundant fixed effect Likelihood and Hausman test used for determine of Common, Fixed and Random effect model. Therefore Indian market dividend policies play a fundamental role and significant impact on Market Share Prices. Although, present research found that different as compared to previous study that dividend policy have no impact on share price in Sri-Lanka and Pakistan.

Keywords: dividend policy, share price, South Asian countries, panel data analysis, theories and parameters of dividend

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Authors: R. K. Apalowo, D. Chronopoulos, V. Thierry

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A wave finite element (WFE) and finite element (FE) based computational method is presented by which the dispersion properties as well as the wave interaction coefficients for one-dimensional structural system can be predicted. The structural system is discretized as a system comprising a number of waveguides connected by a coupling joint. Uniform nodes are ensured at the interfaces of the coupling element with each waveguide. Then, equilibrium and continuity conditions are enforced at the interfaces. Wave propagation properties of each waveguide are calculated using the WFE method and the coupling element is modelled using the FE method. The scattering of waves through the coupling element, on which damage is modelled, is determined by coupling the FE and WFE models. Furthermore, the central aim is to evaluate the effect of pressurization on the wave dispersion and scattering characteristics of the prestressed structural system compared to that which is not prestressed. Numerical case studies are exhibited for two waveguides coupled through a coupling joint.

Keywords: Finite Element, Prestressed Structures, Wave Finite Element, Wave Propagation Properties, Wave Scattering Coefficients.

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Authors: Ding Jue, Li Jiahua, Lei Zhidi, Weng Peifen, Li Xiaowei

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With the rapid development of national modern industry, people begin to pay attention to environmental pollution and harm caused by industrial dust. Based on above, a numerical study on the dedusting technology of industrial environment was conducted. The dynamic models of multicomponent particles collision and coagulation, breakage and deposition are developed, and the interaction of water droplet and aerosol particle in 2-Dimension flow field was researched by Eulerian-Lagrangian method and Multi-Monte Carlo method. The effects of the droplet scale, movement speed of droplet and the flow field structure on scavenging efficiency were analyzed. The results show that under the certain condition, 30μm of droplet has the best scavenging efficiency. At the initial speed 1m/s of droplets, droplets and aerosol particles have more time to interact, so it has a better scavenging efficiency for the particle.

Keywords: water droplet, aerosol particle, collision and coagulation, multi-monte carlo method

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Authors: Saqib Aziz, Brad Alexander, Christoph Gengnagel, Stefan Weinzierl

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This paper explores a generative design, simulation, and optimization workflow for the integration of acoustical diffuser and/or absorber geometry with embedded coupled Helmholtz-resonators for full-scale 3D printed building components. Large-scale additive manufacturing in conjunction with algorithmic CAD design tools enables a vast amount of control when creating geometry. This is advantageous regarding the increasing demands of comfort standards for indoor spaces and the use of more resourceful and sustainable construction methods and materials. The presented methodology highlights these new technological advancements and offers a multimodal and integrative design solution with the potential for an immediate application in the AEC-Industry. In principle, the methodology can be applied to a wide range of structural elements that can be manufactured by additive manufacturing processes. The current paper focuses on a case study of an application for a biaxial load-bearing beam grillage made of reinforced concrete, which allows for a variety of applications through the combination of additive prefabricated semi-finished parts and in-situ concrete supplementation. The semi-prefabricated parts or formwork bodies form the basic framework of the supporting structure and at the same time have acoustic absorption and diffusion properties that are precisely acoustically programmed for the space underneath the structure. To this end, a hybrid validation strategy is being explored using a digital and cross-platform simulation environment, verified with physical prototyping. The iterative workflow starts with the generation of a parametric design model for the acoustical geometry using the algorithmic visual scripting editor Grasshopper3D inside the building information modeling (BIM) software Revit. Various geometric attributes (i.e., bottleneck and cavity dimensions) of the resonator are parameterized and fed to a numerical optimization algorithm which can modify the geometry with the goal of increasing absorption at resonance and increasing the bandwidth of the effective absorption range. Using Rhino.Inside and LiveLink for Revit, the generative model was imported directly into the Multiphysics simulation environment COMSOL. The geometry was further modified and prepared for simulation in a semi-automated process. The incident and scattered pressure fields were simulated from which the surface normal absorption coefficients were calculated. This reciprocal process was repeated to further optimize the geometric parameters. Subsequently the numerical models were compared to a set of 3D concrete printed physical twin models, which were tested in a .25 m x .25 m impedance tube. The empirical results served to improve the starting parameter settings of the initial numerical model. The geometry resulting from the numerical optimization was finally returned to grasshopper for further implementation in an interdisciplinary study.

Keywords: acoustical design, additive manufacturing, computational design, multimodal optimization

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Authors: Mitra Sadoughi

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This study presents the knowledge-sharing model based on individual and organizational factors related to faculty members. To achieve this goal, individual and organizational factors were presented through qualitative research in the form of open codes, axial, and selective observations; then, the final model was obtained using structural equation model. Participants included 1,719 faculty members of the Azad Universities, Mazandaran Province, Region 3. The samples related to the qualitative survey included 25 faculty members experienced at teaching and the samples related to the quantitative survey included 326 faculty members selected by multistage cluster sampling. A 72-item questionnaire was used to measure the quantitative variables. The reliability of the questionnaire was 0.93. Its content and face validity was determined with the help of faculty members, consultants, and other experts. For the analysis of quantitative data obtained from structural model and regression, SPSS and LISREL were used. The results showed that the status of knowledge sharing is moderate in the universities. Individual factors influencing knowledge sharing included the sharing of educational materials, perception, confidence and knowledge self-efficiency, and organizational factors influencing knowledge sharing included structural social capital, cognitive social capital, social capital relations, organizational communication, organizational structure, organizational culture, IT infrastructure and systems of rewards. Finally, it was found that the contribution of individual factors on knowledge sharing was more than organizational factors; therefore, a model was presented in which contribution of individual and organizational factors were determined.

Keywords: knowledge sharing, social capital, organizational communication, knowledge self-efficiency, perception, trust, organizational culture

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Authors: Kasirga Yildirak, Ismail Gur

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We propose a model to measure hail risk of an Agricultural Insurance portfolio. Hail is one of the major catastrophic event that causes big amount of loss to an insurer. Moreover, it is very hard to predict due to its strange atmospheric characteristics. We make use of parcel based claims data on apricot damage collected by the Turkish Agricultural Insurance Pool (TARSIM). As our ultimate aim is to compute the loadings assigned to specific parcels, we build a portfolio risk model that makes use of PD and the severity of the exposures. PD is computed by Spherical-Linear and Circular –Linear regression models as the data carries coordinate information and seasonality. Severity is mapped into integer brackets so that Probability Generation Function could be employed. Individual regressions are run on each clusters estimated on different criteria. Loss distribution is constructed by Panjer Recursion technique. We also show that one risk-one crop model can easily be extended to the multi risk–multi crop model by assuming conditional independency.

Keywords: hail insurance, spherical regression, circular regression, spherical clustering

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Authors: Indu Gamage

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Though commonly utilized as a language improvement technique, reading has not been fully employed by both language teachers and learners to develop reading comprehension skills in English as a second language. In a Sri Lankan context, this area has to be delved deep into as the learners’ show more propensity to analyze. Reading comprehension is an area that most language teachers and learners struggle with though it appears easy. Most ESL learners engage in reading tasks without being properly aware of the objective of doing reading comprehension. It is observed that when doing reading tasks, the language learners’ concern is more on the meanings of individual words than on the overall comprehension of the given text. The passiveness with which the ESL learners engage themselves in reading comprehension makes reading a tedious task for the learner thereby giving the learner a sense of disappointment at the end. Certain reading tasks take the form of translations. The active cognitive participation of the learner in the mode of using productive strategies for predicting, employing schemata and using contextual clues seems quite less. It was hypothesized that the learners’ lack of knowledge of the productive strategies of reading was the major obstacle that makes reading comprehension a tedious task for them. This study is based on a group of 30 tertiary students who read English only as a fundamental requirement for their degree. They belonged to the Faculty of Humanities and Social Sciences of the University of Ruhuna, Sri Lanka. Almost all learners hailed from areas where English was hardly utilized in their day to day conversations. The study is carried out in the mode of a questionnaire to check their opinions on reading and a test to check whether the learners are using productive strategies of reading when doing reading comprehension tasks. The test comprised reading questions covering major productive strategies for reading. Then the results were analyzed to see the degree of their active engagement in comprehending the text. The findings depicted the validity of the hypothesis as grounds behind the difficulties related to reading comprehension.

Keywords: reading, comprehension, skills, reading strategies

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Authors: Bruno Vilić Belina, Ivan Župan

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Smart industry concepts and digital transformation are very popular in many industries. They develop their own digital platforms, which have an important role in innovations and transactions. The main idea of smart industry digital platforms is central data collection, industrial data integration, and data usage for smart applications and services. This paper presents the development of a digital platform for building critical infrastructure protection systems in smart industries. Different service contraction modalities in service level agreements (SLAs), customer relationship management (CRM) relations, trends, and changes in business architectures (especially process business architecture) for the purpose of developing infrastructural production and distribution networks, information infrastructure meta-models and generic processes by critical infrastructure owner demanded by critical infrastructure law, satisfying cybersecurity requirements and taking into account hybrid threats are researched.

Keywords: cybersecurity, critical infrastructure, smart industries, digital platform

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Authors: Haowei Chen, Kaiqi Xiong

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This paper aims to answer how malware will propagate in Wireless Mesh Networks (WMNs) and how communication radius and distributed density of nodes affects the process of spreading. The above analysis is essential for devising network-wide strategies to counter malware. We answer these questions by developing an improved dynamical system that models malware propagation in the area where nodes were uniformly distributed. The proposed model captures both the spatial and temporal dynamics regarding the malware spreading process. Equilibrium and stability are also discussed based on the threshold of the system. If the threshold is less than one, the infected nodes disappear, and if the threshold is greater than one, the infected nodes asymptotically stabilize at the endemic equilibrium. Numerical simulations are investigated about communication radius and distributed density of nodes in WMNs, which allows us to draw various insights that can be used to guide security defense.

Keywords: Bluetooth security, malware propagation, wireless mesh networks, stability analysis

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Authors: Ayse Collins

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The Agenda 2030 puts Higher Education Institutions (HEIs) in the situation where they should emphasize ways to promote sustainability accordingly. However, it is still unclear: a) how sustainability is understood, and b) which actions have been taken in both discourse and practice by HEIs regarding the three pillars of sustainability, society, environment, and economy. There are models of sustainable universities developed by different authors from different countries; For Example, The Global Reporting Initiative (GRI) methodology which offers a variety of indicators to diagnose performance. However, these models have never been developed for universities in particular. Any model, in this sense, cannot be completed adequately without defining the appropriate tools to measure, analyze and control the performance of initiatives. There is a need to conduct researches in different universities from different countries to understand where we stand in terms of sustainable higher education. Therefore, this study aims at exploring the actions taken by a university in Ankara, Turkey, since Agenda 2030 should consider localizing its objectives and targets according to a certain geography. This university just announced 2021-2022 as “Sustainability Year.” Therefore, this research is a multi-methodology longitudinal study and uses the theoretical framework of the organization and transition management (TM). It is designed to examine the activities as being strategic, tactical, operational, and reflexive in nature and covers the six main aspects: academic community, administrative staff, operations and services, teaching, research, and extension. The preliminary research will answer the role of the top university governance, perception of the stakeholders (students, instructors, administrative and support staff) regarding sustainability, and the level of achievement at the mid-evaluation and final, end of year evaluation. TM Theory is a multi-scale, multi-actor, process-oriented approach with the analytical framework to explore and promote change in social systems. Therefore, the stages and respective methodology for collecting data in this research is: Pre-development Stage: a) semi-structured interviews with university governance, c) open-ended survey with faculty, students, and administrative staff d) Semi-structured interviews with support staff, and e) analysis of current secondary data for sustainability. Take-off Stage: a) semi-structured interviews with university governance, faculty, students, administrative and support staff, b) analysis of secondary data. Breakthrough stabilization a) survey with all stakeholders at the university, b) secondary data analysis by using selected indicators for the first sustainability report for universities The findings from the predevelopment stage highlight how stakeholders, coming from different faculties, different disciplines with different identities and characteristics, face the sustainability challenge differently. Though similar sustainable development goals ((social, environmental, and economic) are set in the institution, there are differences across disciplines and among different stakeholders, which need to be considered to reach the optimum goal. It is believed that the results will help changes in HEIs organizational culture to embed sustainability values in their strategic planning, academic and managerial work by putting enough time and resources to be successful in coping with sustainability.

Keywords: higher education, sustainability, sustainability auditing, transition management

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Authors: Komol Phaisarn, Anuphan Suttimarn, Vitchanan Keawtong, Kittisak Thongyoun, Chaiyos Jamsawang

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This article is intended to analyze insurance information which contains information on the customer decision when purchasing life insurance pay package. The data were analyzed in order to present new customers with Life Insurance Perfect Pay package to meet new customers’ needs as much as possible. The basic data of insurance pay package were collect to get data mining; thus, reducing the scattering of information. The data were then classified in order to get decision model or decision tree using Algorithm C4.5 (J-48). In the classification, WEKA tools are used to form the model and testing datasets are used to test the decision tree for the accurate decision. The validation of this model in classifying showed that the accurate prediction was 68.43% while 31.25% were errors. The same set of data were then tested with other models, i.e. Naive Bayes and Zero R. The results showed that J-48 method could predict more accurately. So, the researcher applied the decision tree in writing the program used to introduce the product to new customers to persuade customers’ decision making in purchasing the insurance package that meets the new customers’ needs as much as possible.

Keywords: decision tree, data mining, customers, life insurance pay package

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Authors: Ange Weinrabe, James Tran, Ian B. Hickie

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Risk-taking behaviour is common during youth. In the time between adolescence and early adulthood, young people (aged 15-25 years) are more vulnerable to mood disorders, such as anxiety and depression. What impact does an emerging mood disorder have on decision-making in youth at critical decision points in their lives? In this article, we explore the impact of risk and ambiguity on youth decision-making in a clinical setting using a well-known economic experiment. At two time points, separated by six to eight weeks, we measured risky and ambiguous choices concurrently with findings from three psychological questionnaires, the 10-item Kessler Psychological Distress Scale (K10), the 17-item Quick Inventory of Depressive Symptomatology Adolescent Version (QIDS-A17), and the 12-item Somatic and Psychological Health Report (SPHERE-12), for young help seekers aged 16-25 (n=30, mean age 19.22 years, 19 males). When first arriving for care, we found that 50% (n=15) of participants experienced severe anxiety (K10 ≥ 30) and were severely depressed (QIDS-A17 ≥ 16). In Session 2, taking attrition rates into account (n=5), we found that 44% (n=11) remained severe across the full battery of questionnaires. When applying multiple regression analyses of the pooled sample of observations (N=55), across both sessions, we found that participants who rated severely anxious avoided making risky decisions. We suggest there is some statistically significant (although weak) (p=0.09) relation between risk and severe anxiety scores as measured by K10. Our findings may support working with novel tools with which to evaluate youth experiencing an emerging mood disorder and their cognitive capacities influencing decision-making.

Keywords: anxiety, decision-making, risk, adolescence

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Authors: Nitza Davidovitch, Yael Yossel-Eisenbach

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The purpose of the study was to inquire whether there was a change in the shaping of undergraduate students’ digitally-oriented study pattern in the pre-Covid (2016-2017) versus post-Covid period (2022-2023), as affected by three factors: social background characteristics, high school, and academic background characteristics. These two-time points were cauterized by dramatic changes in teaching and learning at institutions of higher education. The data were collected via cross-sectional surveys at two-time points, in the 2016-2017 academic school year (N=443) and in the 2022-2023 school year (N=326). The questionnaire was distributed on social media and it includes questions on demographic background characteristics, previous studies in high school and present academic studies, and questions on learning and reading habits. Method of analysis: A. Statistical descriptive analysis, B. Mean comparison tests were conducted to analyze the variations in the mean score for the digitally-oriented learning pattern variable at two-time points (pre- and post-Covid) in relation to each of the independent variables. C. Analysis of variance was performed to test the main effects and the interactions. D. Applying linear regression, the research aimed to examine the combined effect of the independent variables on shaping students' digitally-oriented learning habits. The analysis includes four models. In all four models, the dependent variable is students’ perception of digitally oriented learning. The first model included social background variables; the second model included scholastic background as well. In the third model, the academic background variables were added, and the fourth model includes all the independent variables together with the variable of period (pre- and post-COVID). E. Factor analysis confirms using the principal component method with varimax rotation; the variables were constructed by a weighted mean of all the relevant statements merged to form a single variable denoting a shared content world. The research findings indicate a significant rise in students’ perceptions of digitally-oriented learning in the post-COVID period. From a gender perspective, the impact of COVID on shaping a digital learning pattern was much more significant for female students. The socioeconomic status perspective is eliminated when controlling for the period, and the student’s job is affected - more than all other variables. It may be assumed that the student’s work pattern mediates effects related to the convenience offered by digital learning regarding distance and time. The significant effect of scholastic background on shaping students’ digital learning patterns remained stable, even when controlling for all explanatory variables. The advantage that universities had over colleges in shaping a digital learning pattern in the pre-COVID period dissipated. Therefore, it can be said that after COVID, there was a change in how colleges shape students’ digital learning patterns in such a way that no institutional differences are evident with regard to shaping the digital learning pattern. The study shows that period has a significant independent effect on shaping students’ digital learning patterns when controlling for the explanatory variables.

Keywords: learning pattern, COVID, socioeconomic status, digital learning

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Authors: Milica Karadzic, Lidija Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Kovacevic, Aleksandra Tepic-Horecki, Zdravko Sumic

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In this paper, the influence of six different phytochemical content (phenols, carotenoids, chlorophyll a, chlorophyll b, chlorophyll a + b and vitamin C) on antioxidant potential of Murai and Levistro lettuce varieties was evaluated. Variable selection was made by generalized pair correlation method (GPCM) as a novel ranking method. This method is used for the discrimination between two variables that almost equal correlate to a dependent variable. Fisher’s conditional exact and McNemar’s test were carried out. Established multiple linear (MLR) models were statistically evaluated. As the best phytochemicals for the antioxidant potential prediction, chlorophyll a, chlorophyll a + b and total carotenoids content stand out. This was confirmed through both GPCM and MLR, predictive ability of obtained MLR can be used for antioxidant potential estimation for similar lettuce samples. This article is based upon work from the project of the Provincial Secretariat for Science and Technological Development of Vojvodina (No. 114-451-347/2015-02).

Keywords: antioxidant activity, generalized pair correlation method, lettuce, regression analysis

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Authors: Marcel Duh, Jadranka Stricevic, David Halozan, Dusan Celan

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Back pain is not only the result of structural or biomechanical abnormalities of the spine but is also associated with cognitive and behavioral aspects of pain and thus represents biopsychosocial problem. Stressors are not only interpersonal conflicts, negative life events, and dangerous situations but also noise. Effects of noise on human beings are psychological (excitement, stress), sensory, and physiological. The harmful effects of noise can be seen in the 40-65 dB range and are manifested as fatigue, irritability, poor sleep and psychological discomfort of the worker. Within 65-90 dB range, body metabolism increases, oxygen consumption is higher, tachycardia and hypertension appear, and the tone of skeletal muscles increases. The purpose of the study was to determine whether the stress caused by noise at the work place increases the incidence of back pain. Measurements of noise levels were carried out in three different wards of social care institution. The measurement on each ward was repeated 3 times (total of 9 measurements) for 8 hours during the morning shift. The device was set up in the room where clients spent most of the day. The staff on the ward replied to the questionnaire consisting of closed type questions about basic demographic information and information about back pain. We find that noise levels as measured in our study had no statistically significant effect on the incidence of back pain (p = 0.90). We also find that health care workers who perceive their work as stressful, have more back pain than those who perceive their job as unstressful, but correlation is statistically insignificant (p = 0.682). With our study, we have proven findings of other authors, that noise level below 65 dB does not have a significant influence on the incidence of back pain.

Keywords: health care workers, musculoskeletal disorder, noise, sick leave

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Authors: Siti Khadijah Che Osmi, Mohammed Ahmad Syed

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Underground tunnels are one of the most popular public facilities for various applications such as transportation, water transfer, network utilities and etc. Experience from the past earthquake reveals that the underground tunnels also become vulnerable components and may damage at certain percentage depending on the level of ground shaking and induced phenomena. In this paper a numerical analysis is conducted in evaluating the sensitivity of two types of circular shallow tunnel lining models to wide ranging changes in the geotechnical design parameter. Critical analysis has been presented about the current methods of analysis, structural typology, ground motion characteristics, effect of soil conditions and associated uncertainties on the tunnel integrity. The response of the tunnel is evaluated through 2D non-linear finite element analysis, which critically assesses the impact of increasing levels of seismic loads. The finding from this study offer significant information on improving methods to assess the vulnerability of underground structures.

Keywords: geotechnical design parameter, seismic response, sensitivity analysis, shallow tunnel

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Authors: Sujay Kotwale, Ramasubba Reddy M.

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Electrocardiogram (ECG) is a non-invasive technique used to study and analyze various heart diseases. Cardiac arrhythmia is a serious heart disease which leads to death of the patients, when left untreated. An early-time detection of cardiac arrhythmia would help the doctors to do proper treatment of the heart. In the past, various algorithms and machine learning (ML) models were used to early-time detection of cardiac arrhythmia, but few of them have achieved better results. In order to improve the performance, this paper implements principal component analysis (PCA) along with XGBoost model. The PCA was implemented to the raw ECG signals which suppress redundancy information and extracted significant features. The obtained significant ECG features were fed into XGBoost model and the performance of the model was evaluated. In order to valid the proposed technique, raw ECG signals obtained from standard MIT-BIH database were employed for the analysis. The result shows that the performance of proposed method is superior to the several state-of-the-arts techniques.

Keywords: cardiac arrhythmia, electrocardiogram, principal component analysis, XGBoost

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Authors: B. N. Asare, O. A. Ajigini

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Information systems (IS) are highly important in the operation of private and public organisations in developing and developed countries. Developing countries are saddled with many project failures during the implementation of information systems. However, successful information systems are greatly needed in developing countries in order to enhance their economies. This paper is highly important in view of the high failure rate of information systems in developing countries which needs to be reduced to minimum acceptable levels by means of recommended interventions. This paper centres on a review of IS development in developing countries. The paper presents evidences of the IS successes and failures in developing countries and posits a model to address the IS failures. The proposed model can then be utilised by developing countries to reduce their IS project implementation failure rate. A comparison is drawn between IS development in developing countries and developed countries. The paper provides valuable information to assist in reducing IS failure, and developing IS models and theories on IS development for developing countries.

Keywords: developing countries, information systems, IS development, information systems failure, information systems success, information systems success model

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Authors: Narendra Babu Bommenahalli Veerabhadrappa

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Teaching sustainability concepts along with profit maximizing philosophy of business in management education is a challenge. This paper explores and evaluates various learning models to inculcate sustainability concepts in management education. The paper explains about a new pedagogy that was tested in a business management school (Indus Business Academy, Bangalore, India) to teach sustainability. The pedagogy was designed by intertwining concepts related to sustainability with digital marketing concepts. As part of this experimental method, students (in groups) were assigned with various topics of sustainability and were asked to work with concepts of digital marketing and thus market the concepts of sustainability. The paper explains as a case study as to how sustainability was integrated with digital marketing tools and how learning towards sustainability was facilitated. It also explains the outcomes of this pedagogical method, in terms of inculcating sustainability concepts amongst management students as well as marketing and proliferation of sustainability concepts to bring about the behavioral changes amongst target audience towards sustainability.

Keywords: management-education, pedagogy, sustainability, behavior

Procedia PDF Downloads 249

Authors: B. Kulaga, A. Cinti, F. J. Mazzocchini

Abstract:

Despite the fact that growing academic attention on dark tourism is a fairly recent phenomenon, among the various reasons for travelling death-related ones, are very ancient. Furthermore, the darker side of human nature has always been fascinated and curious regarding death, or at least, man has always tried to learn lessons from death. This study proposes to describe the phenomenon of dark tourism related to the 2016 earthquake in Central Italy, deadly for 302 people and highly destructive for the rural areas of Lazio, Marche, and Umbria Regions. The primary objective is to examine the motivation-experience relationship in a dark tourism site, using the structural equation model, applied for the first time to a dark tourism research in 2016, in a study conducted after the Beichuan earthquake. The findings of the current study are derived from the calculations conducted on primary data compiled from 350 tourists in the areas mostly affected by the 2016 earthquake, including the town of Amatrice, near the epicenter, Castelluccio, Norcia, Ussita and Visso, through conducting a Likert scale survey. Furthermore, we use the structural equation model to examine the motivation behind dark travel and how this experience can influence the motivation and emotional reaction of tourists. Expected findings are in line with the previous study mentioned above, indicating that: not all tourists visit the thanatourism sites for dark tourism purpose, tourists’ emotional reactions influence more heavily the emotional tourist experience than cognitive experiences do, and curious visitors are likely to engage cognitively by learning about the incident or related issues.

Keywords: dark tourism, emotional reaction, experience, motivation, structural equation model

Procedia PDF Downloads 152

Authors: C. Pallis

Abstract:

Induced-Gravity inflation is a model of chaotic inflation where the inflaton is identified with a Higgs-like modulus whose the vacuum expectation value controls the gravitational strength. Thanks to a strong enough coupling between the inflaton and the Ricci scalar curvature, inflation is attained even for subplanckian values of the inflaton with the corresponding effective theory being valid up to the Planck scale. In its simplest realization, induced-gravity inflation is based on a quatric potential and a quadratic non-minimal coupling and the inflationary observables turn out to be in agreement with the Planck data. Its supersymmetrization can be formulated within no-scale Supergravity employing two gauge singlet chiral superfields and applying a continuous $R$ and a discrete Zn symmetry to the proposed superpotential and Kahler potential. Modifying slightly the non-minimal coupling to Gravity, the model can account for the recent results of BICEP2. These modifications can be also accommodated beyond the no-scale SUGRA considering the fourth order term of the Kahler potential which mixes the inflaton with the accompanying non-inflaton field and small deviations from the prefactor $-3$ encountered in the adopted Kahler potential.

Keywords: cosmology, supersymmetric models, supergravity, modified gravity

Procedia PDF Downloads 722

Authors: K. Benhabib, X. Pierens, V-D Nguyen, G. Mimanne

Abstract:

The main hypothesis of the dynamics of solid phase microextraction (SPME) is that steady-state mass transfer is respected throughout the SPME extraction process. It considers steady-state diffusion is established in the two phases and fast exchange of the analyte at the solid phase film/water interface. An improved model is proposed in this paper to handle with the situation when the analyte (atrazine) is in contact with colloid suspensions (carboxylate latex in aqueous solution). A mathematical solution is obtained by substituting the diffusion coefficient by the mean of diffusion coefficient between analyte and carboxylate latex, and also thickness layer by the mean thickness in aqueous solution. This solution provides an equation relating the extracted amount of the analyte to the extraction a little more complicated than previous models. It also gives a better description of experimental observations. Moreover, the rate constant of analyte obtained is in satisfactory agreement with that obtained from the initial curve fitting.

Keywords: pesticide, solid-phase microextraction (SPME) methods, steady state, analytical model

Procedia PDF Downloads 492

Authors: Alaa Abdullah Altaee

Abstract:

This paper presents an adaptive decision feedback equalizer (ADFE) for multi-Gbps serial links utilizing a fix-step error signal extracted from cross-points of received data symbols. The extracted signal is generated based on violation of received data symbols with minimum detection requirements at the clock and data recovery (CDR) stage. The iterations of the adaptation process search for the optimum feedback tap coefficients to maximize the data eye-opening and minimize the adaptation convergence time. The effectiveness of the proposed architecture is validated using the simulation results of a serial link designed in an IBM 130 nm 1.2V CMOS technology. The data link with variable channel lengths is analyzed using Spectre from Cadence Design Systems with BSIM4 device models.

Keywords: adaptive DFE, CMOS equalizer, error detection, serial links, timing jitter, wire-line communication

Procedia PDF Downloads 126

Authors: Bharatendra Rai

Abstract:

The sequence of words in text data has long-term dependencies and is known to suffer from vanishing gradient problems when developing deep learning models. Although recurrent networks such as long short-term memory networks help to overcome this problem, achieving high text classification performance is a challenging problem. Convolutional recurrent networks that combine the advantages of long short-term memory networks and convolutional neural networks can be useful for text classification performance improvements. However, arriving at suitable hyperparameter values for convolutional recurrent networks is still a challenging task where fitting a model requires significant computing resources. This paper illustrates the advantages of using convolutional recurrent networks for text classification with the help of statistically planned computer experiments for hyperparameter tuning.

Keywords: long short-term memory networks, convolutional recurrent networks, text classification, hyperparameter tuning, Tukey honest significant differences

Procedia PDF Downloads 135

Authors: Sourabh R. Dinde, Rajshekar S. Talikoti

Abstract:

According to the structural point of view Industrial Pallet rack structure can be considered typical steel framed structure. This work presents a general analysis of an industrial pallet rack structure, evaluating the influence of each of the components on the global stability. An analytical study for the sensitivity of pallet rack configuration in linear static equivalent lateral loads. The aim is to braced/unbraced frames were design and their analytical models are to be built in software. The finite element analysis is used to determine axial forces in beam and column, maximum storey displacement and buckling loads on braced/unbraced pallet rack structure. Bracing systems are mostly provided to enhance the stiffness factor of the structures with the seismic loads. Unbraced systems have mostly translational modes of failure and are very flexible due to excessive loads.

Keywords: buckling capacity, cold formed steel, finite element analysis, pallets Rrack, seismic design

Procedia PDF Downloads 329