Search results for: auditor-client relationships

Authors: Soheila Sadeghi

Abstract:

Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

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Authors: Brenda Rodriguez

Abstract:

In this observational study, we investigate a neurotypical peer's impact on both the social and academic success of a child with Down Syndrome in a kindergarten setting. The child with Down Syndrome experiences difficulty articulating words clearly and is paired with a classmate in various academic and social contexts over three weeks. Utilizing both qualitative and quantitative data, we aim to document any classroom interactions that may occur. The findings of this study will contribute to understanding how peer relationships facilitate academic achievement and will advance research on inclusive classroom practices.

Keywords: academic and social success, down syndrome, inclusive classrooms, peer interaction

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Authors: Shivani Khare

Abstract:

It is of paramount concern for economists to uncover the factors that determine human capital development, considered now to be one of the major factors behind economic growth and development. However, no human action is isolated but rather works within the set-up of the society. In recent years, a new field of investigation has come up that analyses the relationships that exist between social and human capital. Along these lines, this paper explores the effect of social capital on the indicators of human capital development – life expectancy at birth, mean years of schooling, and per capita income. The applied part of the analysis is performed using a panel data model for OECD countries and by using a series of chronological periods that within the 2005–2020 time frame.

Keywords: social capital, human capital development, trust, social networks, socioeconomics

Procedia PDF Downloads 138

Authors: Matthew J. Emes, Azadeh Jafari, Maziar Arjomandi

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Velocity fluctuations of shear-generated turbulence are largest in the atmospheric surface layer (ASL) of nominal 100 m depth, which can lead to dynamic effects such as galloping and flutter on small physical structures on the ground when the turbulence length scales and characteristic length of the physical structure are the same order of magnitude. Turbulence length scales are a measure of the average sizes of the energy-containing eddies that are widely estimated using two-point cross-correlation analysis to convert the temporal lag to a separation distance using Taylor’s hypothesis that the convection velocity is equal to the mean velocity at the corresponding height. Profiles of turbulence length scales in the neutrally-stratified ASL, as predicted by Monin-Obukhov similarity theory in Engineering Sciences Data Unit (ESDU) 85020 for single-point data and ESDU 86010 for two-point correlations, are largely dependent on the aerodynamic roughness length. Field measurements have shown that longitudinal turbulence length scales show significant regional variation, whereas length scales of the vertical component show consistent Obukhov scaling from site to site because of the absence of low-frequency components. Hence, the objective of this experimental study is to compare the similarity theory relationships between the turbulence length scales and aerodynamic roughness length with those calculated using the autocorrelations and cross-correlations of field measurement velocity data at two sites: the Surface Layer Turbulence and Environmental Science Test (SLTEST) facility in a desert ASL in Dugway, Utah, USA and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) wind tower in a rural ASL in Jemalong, NSW, Australia. The results indicate that the longitudinal turbulence length scales increase with increasing aerodynamic roughness length, as opposed to the relationships derived by similarity theory correlations in ESDU models. However, the ratio of the turbulence length scales in the lateral and vertical directions to the longitudinal length scales is relatively independent of surface roughness, showing consistent inner-scaling between the two sites and the ESDU correlations. Further, the diurnal variation of wind velocity due to changes in atmospheric stability conditions has a significant effect on the turbulence structure of the energy-containing eddies in the lower ASL.

Keywords: aerodynamic roughness length, atmospheric surface layer, similarity theory, turbulence length scales

Procedia PDF Downloads 124

Authors: Soheila Sadeghi

Abstract:

Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

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Authors: Mohamed Nasraoui

Abstract:

Spatial ore distribution, ore heterogeneity and their links with geological processes involved in Niobium concentration are all factors for consideration when bridging field observations to extraction scheme. Indeed, mineralogy changes of Nb-hosting phases, their textural relationships with hydrothermal or secondary minerals, play a key control over mineral processing. This study based both on filed work and ore characterization presents data from several Nb-deposits related to carbonatite complexes. The results obtained by a wide range of analytical techniques, including, XRD, XRF, ICP-MS, SEM, Microprobe, Spectro-CL, FTIR-DTA and Mössbauer spectroscopy, demonstrate how geometallurgical assessment, at all stage of mine development, can greatly assist in the design of a suitable extraction flowsheet and data reconciliation.

Keywords: carbonatites, Nb-geometallurgy, Nb-mineralogy, mineral processing.

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Authors: Yuliya Leonidovna Kiva-Khamzina

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The legal nature of the contract for educational services causes a lot of controversies. In particular, it raises the question about industry sector relationships, which require making a contract for educational services. The article describes the different types of contracts classifications for services provision from the perspective of civil law, deals with the specifics of the contract on rendering educational services; the author makes the conclusion that the contract for the provision of educational services is a complex institution that includes elements of the civil and administrative law. The following methods were used to conduct the study: dialectical method of cognition, the historical method, systemic analysis, classification.

Keywords: administrative aspect, civil aspect, educational service, industry, legal nature, services provision

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Authors: T. Manzur, S. Iffat, M. A. Noor

Abstract:

In this paper, relationship between different properties of IC concrete and water cement ratio, obtained from a comprehensive experiment conducted on IC using local materials (Burnt clay chips- BC) is presented. In addition, saturated SAP was used as an IC material in some cases. Relationships have been developed through regression analysis. The focus of this analysis is on developing relationship between a dependent variable and an independent variable. Different percent replacements of BC and water cement ratios were used. Compressive strength, modulus of elasticity, water permeability and chloride permeability were tested and variations of these parameters were analyzed with respect to water cement ratio.

Keywords: compressive strength, concrete, curing, lightweight, aggregate, superabsorbent polymer, internal curing

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Authors: Aliasghar Mehdizadeh Dastjerdi, Francisco Camara Pereira

Abstract:

The increasing complexity and demand of transport services strains transportation systems especially in urban areas with limited possibilities for building new infrastructure. The solution to this challenge requires changes of travel behavior. One of the proposed means to induce such change is multimodal travel apps. This paper describes a study of the intention to use a real-time multi-modal travel app aimed at motivating travel behavior change in the Greater Copenhagen Region (Denmark) toward promoting sustainable transport options. The proposed app is a multi-faceted smartphone app including both travel information and persuasive strategies such as health and environmental feedback, tailoring travel options, self-monitoring, tunneling users toward green behavior, social networking, nudging and gamification elements. The prospective for mobility management travel apps to stimulate sustainable mobility rests not only on the original and proper employment of the behavior change strategies, but also on explicitly anchoring it on established theoretical constructs from behavioral theories. The theoretical foundation is important because it positively and significantly influences the effectiveness of the system. However, there is a gap in current knowledge regarding the study of mobility-management travel app with support in behavioral theories, which should be explored further. This study addresses this gap by a social cognitive theory‐based examination. However, compare to conventional method in technology adoption research, this study adopts a reverse approach in which the associations between theoretical constructs are explored by Max-Min Hill-Climbing (MMHC) algorithm as a hybrid causal discovery method. A technology-use preference survey was designed to collect data. The survey elicited different groups of variables including (1) three groups of user’s motives for using the app including gain motives (e.g., saving travel time and cost), hedonic motives (e.g., enjoyment) and normative motives (e.g., less travel-related CO2 production), (2) technology-related self-concepts (i.e. technophile attitude) and (3) use Intention of the travel app. The questionnaire items led to the formulation of causal relationships discovery to learn the causal structure of the data. Causal relationships discovery from observational data is a critical challenge and it has applications in different research fields. The estimated causal structure shows that the two constructs of gain motives and technophilia have a causal effect on adoption intention. Likewise, there is a causal relationship from technophilia to both gain and hedonic motives. In line with the findings of the prior studies, it highlights the importance of functional value of the travel app as well as technology self-concept as two important variables for adoption intention. Furthermore, the results indicate the effect of technophile attitude on developing gain and hedonic motives. The causal structure shows hierarchical associations between the three groups of user’s motive. They can be explained by “frustration-regression” principle according to Alderfer's ERG (Existence, Relatedness and Growth) theory of needs meaning that a higher level need remains unfulfilled, a person may regress to lower level needs that appear easier to satisfy. To conclude, this study shows the capability of causal discovery methods to learn the causal structure of theoretical model, and accordingly interpret established associations.

Keywords: travel app, behavior change, persuasive technology, travel information, causality

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Authors: P. Maheshwari, M. Brindavan

Abstract:

The present research aimed to study the level of socio-emotional skills and perceived self-efficacy of children with learning disability. The study further investigated the relationship between the levels of socio-emotional skills, perceived self-efficacy and academic achievement of children with learning disability. The sample comprised of 40 children with learning disability as their primary condition, belonging to middle or upper middle class, living with both the parents, residing in Mumbai. Purposive or Judgmental and snowball sampling technique was used to select the sample for the study. Proformas in the form of questionnaires were used to obtain the background information of the children with learning disability. A self-constructed Child’s Perceived Self-Efficacy Assessment Scale and Child’s Social and Emotional Skills Assessment Scale was used to measure the level of child’s perceived self-efficacy and their level of social and emotional skill respectively. Academic scores of the child were collected from the child’s parents or teachers and were converted into a percentage. The data was analyzed quantitatively using SPSS. Spearman rho or Pearson Product Moment correlation was used to ascertain the multiple relationships between child’s perceived self-efficacy, child’s social and emotional skills and child’s academic achievement. The findings revealed majority (27) of the children with learning disability perceived themselves having above average level of social and emotional skills while 13 out of 40 perceived their level of social and emotional skills at an average level. Domain wise analyses revealed that, in the domain of self- management (26) and relationship skills (22) more number of the children perceived themselves as having average or below average level of social and emotional skills indicating that they perceived themselves as having average or below average skills in regulating their emotions, thoughts, and behaviors effectively in different situations, establishing and maintaining healthy and rewarding relationships with diverse groups and individuals. With regard to perceived self-efficacy, the majority of the children with learning disability perceived themselves as having above average level of self-efficacy. Looking at the data domain wise it was found that, in the domains of self-regulated learning and emotional self-efficacy, 50% of the children perceived themselves at average or below average level, indicating that they perceived themselves as average on competencies like organizing academic activities, structuring environment to make it conducive for learning, expressing emotions in a socially acceptable manner. Further, the correlations were computed, and significant positive correlations were found between children’s social and emotional skills and academic achievement (r=.378, p < .01), and between children’s social and emotional skills and child’s perceived self-efficacy (r = .724, p < .01) and a positive significant correlation was also found between children’s perceived self-efficacy and academic achievement (r=.332, p < .05). Results of the study emphasize on planning intervention for children with learning disability focusing on improving self-management and relationship skills, self-regulated learning and emotional self-efficacy.

Keywords: learning disability, social and emotional skills, perceived self-efficacy, academic achievement

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Authors: Rachelle Angeli Maranon

Abstract:

This research explored the relationships of a child’s family condition, sex and subjective well-being (SWB) to gain some understanding of the experiences of both transnational and non-transnational families. A descriptive-correlational design was used to study the variables. Participants included 52 male and female children from Iloilo and Kabankalan cities, representing the family conditions in this study. Data were gathered using a semi-structured interview guide. Responses were analyzed using Mann-Whitney U Test. The results showed that the SWB of non-transnational children was significantly higher compared to their transnational counterparts (U = 134, p = .00). Also, analysis between females and males indicated a significant difference only on some aspects (U = 318, p = .71). Some recommendations were suggested to better understand the plight of the left-behind children.

Keywords: left-behind children, mothers, subjective well-being, transnational families

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Authors: John Zanetich

Abstract:

This paper uses a pragmatic research approach to investigate the relationships between Active Development of Tacit Knowledge (ADTK), social media (Facebook) and classroom learning communities. This paper investigates the use of learning communities and social media as the context and means for changing tacit knowledge to explicit and presents a dynamic model of the development of a classroom learning community. The goal of this study is to identify the point that explicit knowledge is converted to tacit knowledge and to test a way to quantify the exchange using social media and learning communities.

Keywords: tacit knowledge, knowledge management, college programs, experiential learning, learning communities

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Authors: Ladznar S. Laja, Rosalio G. Artes, Jr.

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This paper introduced a graph polynomial relating convexity concepts. A graph polynomial is a polynomial representing a graph given some parameters. On the other hand, a subgraph H of a graph G is said to be convex in G if for every pair of vertices in H, every shortest path with these end-vertices lies entirely in H. We define the convex subgraph polynomial of a graph G to be the generating function of the sequence of the numbers of convex subgraphs of G of cardinalities ranging from zero to the order of G. This graph polynomial is monic since G itself is convex. The convex index which counts the number of convex subgraphs of G of all orders is just the evaluation of this polynomial at 1. Relationships relating algebraic properties of convex subgraphs polynomial with graph theoretic concepts are established.

Keywords: convex subgraph, convex index, generating function, polynomial ring

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Authors: Jae Hyun Park, Sangmi Chai, Minkyun Kim

Abstract:

As users spend more time on the Internet, the probability of their personal information being exposed has been growing. This research has a main purpose of investigating factors and examining relationships when Internet users recognize their value of private information with a perspective of an economic asset. The study is targeted on Internet users, and the value of their private information will be converted into economic figures. Moreover, how economic value changes in relation with individual attributes, dealer’s traits, circumstantial properties will be studied. In this research, the changes in factors on private information value responding to different situations will be analyzed in an economic perspective. Additionally, this study examines the associations between users’ perceived risk and value of their personal information. By using the cost-benefit analysis framework, the hypothesis that the user’s sense in private information value can be influenced by individual attributes and situational properties will be tested. Therefore, this research will attempt to provide answers for three research objectives. First, this research will identify factors that affect value recognition of users’ personal information. Second, it provides evidences that there are differences on information system users’ economic value of information responding to personal, trade opponent, and situational attributes. Third, it investigates the impact of those attributes on individuals’ perceived risk. Based on the assumption that personal, trade opponent and situation attributes make an impact on the users’ value recognition on private information, this research will present the understandings on the different impacts of those attributes in recognizing the value of information with the economic perspective and prove the associative relationships between perceived risk and decision on the value of users’ personal information. In order to validate our research model, this research used the regression methodology. Our research results support that information breach experience and information security systems is associated with users’ perceived risk. Information control and uncertainty are also related to users’ perceived risk. Therefore, users’ perceived risk is considered as a significant factor on evaluating the value of personal information. It can be differentiated by trade opponent and situational attributes. This research presents new perspective on evaluating the value of users’ personal information in the context of perceived risk, personal, trade opponent and situational attributes. It fills the gap in the literature by providing how users’ perceived risk are associated with personal, trade opponent and situation attitudes in conducting business transactions with providing personal information. It adds to previous literature that the relationship exists between perceived risk and the value of users’ private information in the economic perspective. It also provides meaningful insights to the managers that in order to minimize the cost of information breach, managers need to recognize the value of individuals’ personal information and decide the proper amount of investments on protecting users’ online information privacy.

Keywords: private information, value, users, perceived risk, online information privacy, attributes

Procedia PDF Downloads 239

Authors: Amanda Aliende da Matta, Maria del Pilar Fogueiras Bertomeu, Valeria de Ormaechea Otalora, Maria Paz Sandin Esteban, Miriam Comet Donoso

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This communication presents proposed questions about the existential in research on the political participation of young women. The study follows a qualitative methodology, in particular, the applied hermeneutic phenomenological (AHP) method, and the general objective of the research is to give an account of the experience of political participation as a young woman. The study participants are women aged 18 to 35 who have experience in political participation. The techniques of data collection are the descriptive story and the phenomenological interview. Hermeneutic phenomenology as a research approach is based on phenomenological philosophy and applied hermeneutics. The ultimate objective of HP is to gain access to the meaning structures of lived experience by appropriating them, clarifying them, and reflectively making them explicit. Human experiences are always lived through existential: fundamental themes that are useful in exploring meaningful aspects of our life worlds. Everyone experiences the world through the existential of lived relationships, the lived body, lived space, lived time, and lived things. The phenomenological research, then, also tacitly asks about the existential. Existentials are universal themes useful for exploring significant aspects of our life world and of the particular phenomena under study. Four main existentials prove especially helpful as guides for reflection in the research process: relationship, body, space, and time. For example, in our case, we may ask ourselves how can the existentials of relationship, body, space, and time guide us in exploring the structures of meaning in the lived experience of political participation as a woman and a young person. The study is still not finished, as we are currently conducting phenomenological thematic analysis on the collected stories of lived experience. Yet, we have already identified some fragments of texts that show the existential in their experiences, which we will transcribe below. 1) Relationality - The experienced I-Other. It regards how relationships are experienced in our narratives about political participation as young women. One example would be: “As we had known each other for a long time, we understood each other with our eyes; we were all a little bit on the same page, thinking the same thing.” 2) Corporeality - The lived body. It regards how the lived body is experienced in activities of political participation as a young woman. One example would be: “My blood was boiling, but it was not the time to throw anything in their face, we had to look for solutions.”; “I had a lump in my throat and I wanted to cry.”. 3) Spatiality - The lived space. It regards how one experiences the lived space in political participation activities as a young woman. One example would be: “And the feeling I got when I saw [it] it's like watching everybody going into a mousetrap.” 4) Temporality - Lived time. It regards how one experiences the lived time in political participation activities as a young woman. One example would be: “Then, there were also meetings that went on forever…”

Keywords: applied hermeneutic phenomenology, existentials, hermeneutics, phenomenology, political participation

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Authors: Chyong-Ru Liu, Wen-Shiung Huang, Wan-Ching Tang, Shan-Pei Chen

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Two of the biggest challenges companies involved in sports and exercise information services face are how to strengthen participation in virtual sports/exercise communities and how to increase the ongoing participatoriness of those communities. In the past, relatively little research has explored mechanisms for strengthening alignment practice and community response from the perspective of self-construal, and as such this study seeks to explore the self-construal of virtual sports/exercise communities, the role it plays in the emotional commitment of forming communities, and the factor that can strengthen alignment practice. Moreover, which factor of the emotional commitment of forming virtual communities have the effect of strengthening interference in the process of transforming customer citizenship behaviors? This study collected 625 responses from the two leading websites in terms of fan numbers in the provision of information on road race and marathon events in Taiwan, with model testing conducted through linear structural equation modelling and the bootstrapping technique to test the proposed hypotheses. The results proved independent construal had a stronger positive direct effect on affective commitment to fellow customers than did interdependent construal, and the influences of affective commitment to fellow customers in enhancing customer citizenship behavior. Public self-consciousness moderates the relationships among independent self-construal and interdependent self-construal on effective commitment to fellow customers. Perceived playfulness moderates the relationships between effective commitment to fellow customers and customer citizenship behavior. The findings of this study provide significant insights for the researchers and related organizations. From the theoretical perspective, this is empirical research that investigated the self-construal theory and responses (i.e., affective commitment to fellow customers, customer citizenship behavior) in virtual sports/exercise communities. We further explore how to govern virtual sports/exercise community participants’ heterogeneity through public self-consciousness mechanism to align participants’ affective commitment. Moreover, perceived playfulness has the effect of strengthening effective commitment to fellow customers with customer citizenship behaviors. The results of this study can provide a foundation for the construction of future theories and can be provided to related organizations for reference in their planning of virtual communities.

Keywords: self-construal theory, public self-consciousness, affective commitment, customer citizenship behavior

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Authors: Selina Lin, Justin M Fan, Vincent Zhang, Cindy Chen, Daniel Lam, Jason Yan, Ning Zhang

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Depression is one of the most common mental disorders in the United States, and past studies have shown a concerning increase in the rates of depression in youth populations over time. Furthermore, depression is an especially important issue for Asian Americans because of the anti-Asian violence taking place during the COVID-19 pandemic. While Asian American adolescents are reluctant to seek help for mental health issues, past research has found a prevalence of depressive symptoms in them that have yet to be fully investigated. There have been studies conducted to understand and observe the impacts of multifarious factors influencing the mental well-being of Asian American adolescents; however, they have been generally limited to qualitative investigation, and very few have attempted to quantitatively evaluate the relationship between depression levels and a comprehensive list of factors for those levels at the same time. To better quantify these relationships, this project investigated the prevalence of depression in Asian American teenagers mainly from the Greater Philadelphia Region, aged 12 to 19, and, with an anonymous survey, asked participants 48 multiple-choice questions pertaining to demographic information, daily behaviors, school life, family life, depression levels (quantified by the PHQ-9 assessment), school and family support against depression. Each multiple-choice question was assigned as a factor and variable for statistical and dominance analysis to determine the most influential factors on depression levels of Asian American adolescents. The results were validated via Bootstrap analysis and t-tests. While certain influential factors identified in this survey are consistent with the literature, such as parent-child relationship and peer pressure, several dominant factors were relatively overlooked in the past. These factors include the parents’ relationship with each other, the satisfaction with body image, sex identity, support from the family and support from the school. More than 25% of participants desired more support from their families and schools in handling depression issues. This study implied that it is beneficial for Asian American parents and adolescents to take programs on parents’ relationships with each other, parent-child communication, mental health, and sexual identity. A culturally inclusive school environment and more accessible mental health services would be helpful for Asian American adolescents to combat depression. This survey-based study paved the way for further investigation of effective approaches for helping Asian American adolescents against depression.

Keywords: Asian American adolescents, depression, dominance analysis, t-test, bootstrap analysis

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Authors: Nishtha Batra

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This study was conducted to identify the effect of perceived stress on emotional regulation, aggression and psychological well-being. Analysis was conducted using correlational and regression models to examine the relationships between perceived stress (independent variable) and psychological factors containing emotional intelligence, psychological well-being and aggression. Subjects N=100, Male students 50 and Female students 50. The data was collected using Cohen's Perceived Stress Scale, Gross’s Emotional Regulation Questionnaire (ERQ), Ryff’s Psychological Well-being scale and Orispina’s aggression scale. Correlation and regression (SPSS version 22) Emotional regulation and psychological well-being had a significant relationship with Perceived stress.

Keywords: perceived stress, psychological well-being, aggression, emotional regulation, students

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Authors: Sibongile Masemola

Abstract:

In 2018, South Africa decriminalised recreational cannabis use and private cultivation, since then, cannabis businesses have been established to meet the demand. However, marketing activities remain limited in this industry, and businesses are unable to disseminate promotional messages, however, as a solution, firms can promote their brands and positioning instead of the actual product (Bick, 2015). Branding is essential to create differences among cannabis firms and to attract and keep customers (Abrahamsson, 2014). Building cannabis firms into brands can better position them in the mind of the consumer so that they become and remain competitive. The aim of this study was to explore how South African cannabis retailers can build brand equity in a stigmatised market, despite significant restrictions on marketing efforts. Keller’s (2001) customer-based brand equity (CBBE) model was used as the as the theoretical framework and explored how cannabis firms build their businesses into brands through developing their brand identity, meaning, performance, and relationships, and ultimately creating brand equity. The study employed a qualitative research method, using semi-structured in-depth interviews among 17 participants to gain insights from cannabis owners and marketers in the recreational cannabis environment. Most findings were presented according to the blocks of CBBE model. Furthermore, a conceptual framework named the stigma-based brand equity (SBBE) model was adapted from Keller’s CBBE model to include an additional building block that accounts for industry-specific characteristics unique to stigmatised markets. Findings revealed the pervasiveness of education and its significance to brand building in a stigmatised industry. Results also demonstrated the overall effect stigma has on businesses and their consumers due to the longstanding negative evaluations of cannabis. Hence, through stigma-bonding, brands can develop deep identity-related psychological bonds with their consumers that will potentially lead to strong brand resonance. This study aims to contribute business-relevant knowledge for firms operating in core-stigmatised markets under controlled marketing regulations by exploring how cannabis firms can build brand equity. Practically, this study presents recommendations for retailers in stigmatised markets on how to destigmatise, build brand identity, create brand meaning, elicit desired brand responses, and develop brand relationships – ultimately building brand equity.

Keywords: branding, brand equity, cannabis, organisational stigma

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Authors: Keigo Ide, Toru Maruyama, Michihiro Ito, Hiroyuki Fujimura, Yoshikatu Nakano, Shoichiro Suda, Sachiyo Aburatani, Haruko Takeyama

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Understanding environmental system is one of the important tasks. In recent years, conservation of coral environments has been focused for biodiversity issues. The damage of coral reef under environmental impacts has been observed worldwide. However, the casual relationship between damage of coral and environmental impacts has not been clearly understood. On the other hand, structure/diversity of marine bacterial community may be relatively robust under the certain strength of environmental impact. To evaluate the coral environment conditions, it is necessary to investigate relationship between marine bacterial composition in coral reef and environmental factors. In this study, the Time Scale Network Analysis was developed and applied to analyze the marine environmental data for investigating the relationship among coral, bacterial community compositions and environmental factors. Seawater samples were collected fifteen times from November 2014 to May 2016 at two locations, Ishikawabaru and South of Sesoko in Sesoko Island, Okinawa. The physicochemical factors such as temperature, photosynthetic active radiation, dissolved oxygen, turbidity, pH, salinity, chlorophyll, dissolved organic matter and depth were measured at the coral reef area. Metagenome and metatranscriptome in seawater of coral reef were analyzed as the biological factors. Metagenome data was used to clarify marine bacterial community composition. In addition, functional gene composition was estimated from metatranscriptome. For speculating the relationships between physicochemical and biological factors, cross-correlation analysis was applied to time scale data. Even though cross-correlation coefficients usually include the time precedence information, it also included indirect interactions between the variables. To elucidate the direct regulations between both factors, partial correlation coefficients were combined with cross correlation. This analysis was performed against all parameters such as the bacterial composition, the functional gene composition and the physicochemical factors. As the results, time scale network analysis revealed the direct regulation of seawater temperature by photosynthetic active radiation. In addition, concentration of dissolved oxygen regulated the value of chlorophyll. Some reasonable regulatory relationships between environmental factors indicate some part of mechanisms in coral reef area.

Keywords: coral environment, marine microbiology, network analysis, omics data analysis

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Authors: Masaki Omata, Shumma Hosokawa

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An experiment to verify the relationships between physiological indexes of an e-learner and the presence or absence of an operation during e-learning is described. Electroencephalogram (EEG), hemoencephalography (HEG), skin conductance (SC), and blood volume pulse (BVP) values were measured while participants performed experimental learning tasks. The results show that there are significant differences between the SC values when reading with clicking on learning materials and the SC values when reading without clicking, and between the HEG ratio when reading (with and without clicking) and the HEG ratio when resting for four of five participants. We conclude that the SC signals can be used to estimate whether or not a learner is performing an active task and that the HEG ratios can be used to estimate whether a learner is learning.

Keywords: e-learning, physiological index, physiological signal, state of learning

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Authors: Hejun Guo, Shenghua Liu

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Five palm oil ether monoesters utilized as novel biodiesels were synthesized and structurally identified in the paper. Investigation was made on the effect of ether species on physicochemical properties of the palm oil ether monoesters. The results showed that density, kinematic viscosity, smoke point, and solidifying point increase linearly with their CH2 group number in certain relationships. Cetane number is enhanced whereas heat value decreases linearly with CH2 group number. In addition, the influencing regularities of volumetric content of the palm oil ether monoesters on the fuel properties were also studied when the ether monoesters are used as diesel fuel additives.

Keywords: biodiesel, palm oil ether monoester, ether species, physicochemical property

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Authors: D. Beckwith

Abstract:

This research explored sexual identity for women with physical disability, both congenital and acquired. It also explored whether exposure to violence or negative risk-taking had played a role in their intimate relationships. This phenomenological research used semi-structured interviews and photo elicitation with the researcher’s insider knowledge adding experiential substance and understanding to the discussion. Findings confirm sexuality for women with physical disability is marginalised and de-gendered making it less of a priority for professionals and policy makers and emphasising the need to more effectively support women with disability in relation to their sexuality, sexual expression and violence.

Keywords: lived-experience, identity, PhotoVoice, sexuality, violence, women with physical disability

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Authors: Miguel Llorens-Marin, Adolfo Hernandez, Maria Puelles-Gallo

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The increasing influence of Online Travel Agencies (OTAs) on hotel bookings and the electronic word-of-mouth (eWOM) contained in them has been featured by many scientific studies as a major factor in the booking decision. The main reason is that nowadays, in the hotel sector, consumers first come into contact with the offer through the web and the online environment. Due to the nature of the hotel product and the fact that it is booked in advance to actually seeing it, there is a lack of knowledge about its actual features. This makes eWOM a major channel to help consumers to reduce their perception of risk when making their booking decisions. This research studies the relationship between aspects of customer influenceability by reading eWOM communications, at the time of booking a hotel, with the propensity to write a review. In other words, to test relationships between the reading and the writing of eWOM. Also investigates the importance of different underlying motivations for writing eWOM. Online surveys were used to obtain the data from a sample of hotel customers, with 739 valid questionnaires. A measurement model and Path analysis were carried out to analyze the chain of relationships among the independent variable (influenceability from reading reviews) and the dependent variable (propensity to write a review) with the mediating effects of additional variables, which help to explain the relationship. The authors also tested the moderating effects of age and gender in the model. The study considered three different underlying motivations for writing a review on a hotel experience, namely hedonic, altruistic and conflicted. Results indicate that the level of influenceability by reading reviews has a positive effect on the propensity to write reviews; therefore, we manage to link the reading and the writing of reviews. Authors also discover that the main underlying motivation to write a hotel review is the altruistic motivation, being the one with the higher Standard regression coefficient above the hedonic motivation. The authors suggest that the propensity to write reviews is not related to sociodemographic factors (age and gender) but to attitudinal factors such as ‘the most influential factor when reading’ and ‘underlying motivations to write. This gives light on the customer engagement motivations to write reviews. The implications are that managers should encourage their customers to write eWOM reviews on altruistic grounds to help other customers to make a decision. The most important contribution of this work is to link the effect of reading hotel reviews with the propensity to write reviews.

Keywords: hotel reviews, electronic word-of-mouth (eWOM), online consumer reviews, digital marketing, social media

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Authors: M. Omer, D. Wilson

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Creating a database scheme is essentially a manual process. From a requirement specification, the information contained within has to be analyzed and reduced into a set of tables, attributes and relationships. This is a time-consuming process that has to go through several stages before an acceptable database schema is achieved. The purpose of this paper is to implement a Natural Language Processing (NLP) based tool to produce a from a requirement specification. The Stanford CoreNLP version 3.3.1 and the Java programming were used to implement the proposed model. The outcome of this study indicates that the first draft of a relational database schema can be extracted from a requirement specification by using NLP tools and techniques with minimum user intervention. Therefore, this method is a step forward in finding a solution that requires little or no user intervention.

Keywords: information extraction, natural language processing, relation extraction

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Authors: Abidemi C. Adegboye, Nosakhare Ikponmwosa, Rogers A. Akinsokeji

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For many resource-rich developing countries, fiscal policy has become a key tool used for short-run fiscal management since it is considered as playing a critical role in injecting part of resource rents into the economies. However, given its instability, reliance on revenue from commodity exports renders fiscal management, budgetary planning and the efficient use of public resources difficult. In this study, the linkage between commodity prices and fiscal operations among a sample of commodity-exporting countries in sub-Saharan Africa (SSA) is investigated. The main question is whether commodity price fluctuations affects the effectiveness of fiscal policy as a macroeconomic stabilization tool in these countries. Fiscal management effectiveness is considered as the ability of fiscal policy to react countercyclically to output gaps in the economy. Fiscal policy is measured as the ratio of fiscal deficit to GDP and the ratio of government spending to GDP, output gap is measured as a Hodrick-Prescott filter of output growth for each country, while commodity prices are associated with each country based on its main export commodity. Given the dynamic nature of fiscal policy effects on the economy overtime, a dynamic framework is devised for the empirical analysis. The panel cointegration and error correction methodology is used to explain the relationships. In particular, the study employs the panel ECM technique to trace short-term effects of commodity prices on fiscal management and also uses the fully modified OLS (FMOLS) technique to determine the long run relationships. These procedures provide sufficient estimation of the dynamic effects of commodity prices on fiscal policy. Data used cover the period 1992 to 2016 for 11 SSA countries. The study finds that the elasticity of the fiscal policy measures with respect to the output gap is significant and positive, suggesting that fiscal policy is actually procyclical among the countries in the sample. This implies that fiscal management for these countries follows the trend of economic performance. Moreover, it is found that fiscal policy has not performed well in delivering macroeconomic stabilization for these countries. The difficulty in applying fiscal stabilization measures is attributable to the unstable revenue inflows due to the highly volatile nature of commodity prices in the international market. For commodity-exporting countries in SSA to improve fiscal management, therefore, fiscal planning should be largely decoupled from commodity revenues, domestic revenue bases must be improved, and longer period perspectives in fiscal policy management are the critical suggestions in this study.

Keywords: commodity prices, ECM, fiscal policy, fiscal procyclicality, fully modified OLS, sub-saharan africa

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Authors: Gechbaia Badri

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In the article, it is studied and realized the perfection issues of service sphere management in Georgia’s reality. As stated above, to transfer the country's economy onto marketing relationships, to form competitive dynamic market is dictated by the time and represents objective necessity. In the last period, the abruptly increasing of changes on science and education caused servicing sphere and producing skills, consumptions based on fields of places and changing role in a structure of the national economy. The main recourse in the new system of the economy became the intellectual capital. The economical progress is significantly determined by developing informational technologies. In the article, it is investigated the service problems of different fields of national economy and are given sentences to settle these problems.

Keywords: service management, service, paradigm, business and management engineering

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Authors: Sarah Niklas, Lynne Chester, Mark Diesendorf

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Geopolitical tensions, climate change and recent movements favouring a transformative shift in institutional power structures have influenced the economics of conventional energy supply for decades. This study takes a multi-dimensional approach to illustrate the potential of renewable energy (RE) technology to provide a pathway to a low-carbon economy driven by ecologically sustainable, independent and socially just energy. This comparative analysis identifies economic, political and social drivers that shaped the adoption of RE policy in two significantly different economies, Germany and Australia, with strong and weak commitments to RE respectively. Two complementary political-economy theories frame the document-based analysis. Régulation Theory, inspired by Marxist ideas and strongly influenced by contemporary economic problems, provides the background to explore the social relationships contributing the adoption of RE within the macro-economy. Varieties of Capitalism theory, a more recently developed micro-economic approach, examines the nature of state-firm relationships. Together these approaches provide a comprehensive lens of analysis. Germany’s energy policy transformed substantially over the second half of the last century. The development is characterised by the coordination of societal, environmental and industrial demands throughout the advancement of capitalist regimes. In the Fordist regime, mass production based on coal drove Germany’s astounding economic recovery during the post-war period. Economic depression and the instability of institutional arrangements necessitated the impulsive seeking of national security and energy independence. During the postwar Flexi-Fordist period, quality-based production, innovation and technology-based competition schemes, particularly with regard to political power structures in and across Europe, favoured the adoption of RE. Innovation, knowledge and education were institutionalized, leading to the legislation of environmental concerns. Lastly the establishment of government-industry-based coordinative programs supported the phase out of nuclear power and the increased adoption of RE during the last decade. Australia’s energy policy is shaped by the country’s richness in mineral resources. Energy policy largely served coal mining, historically and currently one of the most capital-intense industry. Assisted by the macro-economic dimensions of institutional arrangements, social and financial capital is orientated towards the export-led and strongly demand-oriented economy. Here energy policy serves the maintenance of capital accumulation in the mining sector and the emerging Asian economies. The adoption of supportive renewable energy policy would challenge the distinct role of the mining industry within the (neo)-liberal market economy. The state’s protective role of the mining sector has resulted in weak commitment to RE policy and investment uncertainty in the energy sector. Recent developments, driven by strong public support for RE, emphasize the sense of community in urban and rural areas and the emergence of a bottom-up approach to adopt renewables. Thus, political economy frameworks on both the macro-economic (Regulation Theory) and micro-economic (Varieties of Capitalism theory) scales can together explain the strong commitment to RE in Germany vis-à-vis the weak commitment in Australia.

Keywords: political economy, regulation theory, renewable energy, social relationships, energy transitions

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Authors: Golnush Masghati-Amoli, Paul Chin

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Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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Authors: Ayami Umemura

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Without exception, all the bodies dissected in the gross anatomical practices are bodies that have lived irreplaceable lives, laughing and talking with family and friends. While medical education aims to cultivate medical knowledge that is universally applicable to all human bodies, it relies on a unique, irreplaceable, and singular entity. In this presentation, we will explore the ``irreplaceable relationship'' that is cultivated between medical students and anonymous cadavers during gross anatomical practices, drawing on Emmanuel Levinas's ``ethics of the face'' and Martin Buber's discussion of “I-Thou.'' Through this, we aim to present ``a different ethic'' that emerges only in the context of face-to-face relationships, which differs from the generalized, institutionalized, mass-produced ethics like seen in so-called ``ethics codes.'' Since the 1990s, there has been a movement around the world to use gross anatomical practices as an "educational tool" for medical professionalism and medical ethics, and some educational institutions have started disclosing the actual names, occupations, and places of birth of corpses to medical students. These efforts have also been criticized because they lack medical calmness. In any case, the issue here is that this information is all about the past that medical students never know directly. The critical fact that medical students are building relationships from scratch and spending precious time together without any information about the corpses before death is overlooked. Amid gross anatomical practices, a medical student is exposed to anonymous cadavers with faces and touching and feeling them. In this presentation, we will examine a collection of essays written by medical students on gross anatomical practices collected by the Japanese Association for Volunteer Body Donation from medical students across the country since 1978. There, we see the students calling out to the corpse, being called out to, being encouraged, superimposing the carcasses on their own immediate family, regretting parting, and shedding tears. Then, medical students can be seen addressing the dead body in the second person singular, “you.” These behaviors reveal an irreplaceable relationship between the anonymous cadavers and the medical students. The moment they become involved in an irreplaceable relationship between “I and you,” an accidental and anonymous encounter becomes inevitable. When medical students notice being the inevitable takers of voluntary and addressless gifts, they pledge to become “Good Doctors” owing the anonymous persons. This presentation aims to present “a different ethic” based on uniqueness and irreplaceability that comes from the faces of the others embedded in each context, which is different from “routine” and “institutionalized” ethics. That can only be realized ``because of anonymity''.

Keywords: anonymity, irreplaceability, uniqueness, singularlity, emanuel levinas, martin buber, alain badiou, medical education

Procedia PDF Downloads 62