Search results for: inclusive business models

Authors: M. Rilliard

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Based on a Multiliteracies-inspired and sociolinguistically-informed advanced French composition class, this study employed autobiographical narratives from speakers traditionally considered non-legitimate models for L2 teaching purposes of inspiring students to develop an authentic L2 voice and to see themselves as legitimate L2 speakers. Students explored their L2 identities in French through a self-inspired fictional character. Two autobiographical narratives of identity quest by non-traditional French speakers provided them guidance through this process: the novel Le Bleu des Abeilles (2013) and the film Qu’Allah Bénisse la France (2014). Written and French oral productions for different genres, as well as metalinguistic reflections in English, were collected and analyzed. Results indicate that ideas and materials that were relatable to students, namely relatable experiences and relatable language, were most useful to them in developing their L2 voices and achieving authentic and legitimate L2 speakership. These results point towards the benefits of using non-traditional speakers as pedagogical models, as they serve to legitimize students’ sense of their own L2-speakership, which ultimately leads them towards a better, more informed, mastery of the language.

Keywords: foreign language classroom, L2 identity, L2 learning and teaching, L2 writing, sociolinguistics

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Authors: Shailendra Kumar Singh

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In the 21st century, we are living through extraordinary times as we are linguistically blessed to live through an era in which the each sociolinguistic example of living appears to be refreshingly new without any precedence of the past. The word `New Linguistic World Order’ is no longer just the intangible fascination but an indication of the emerging reality that we are living through a time in which the word ‘linguistic purism’ no longer invokes the sense of self categorization and self identification. The contemporary world of today is linguistically rewarding. This is a time in which the very existence of global, powerful and local needs to be revisited in the context of power shift, demographic shift, social psychological shift and technological shift. Hence, the old linguistic world view has to be challenged in the midst of 21st century. The first years of the 21st century have thus far been marked by the rise global economy, technological revolution and demographic shift, now we are witnessing linguistic shift which is leading towards forming a new linguistic world order. On the other hand, with rising powers of China and India in Asia in tandem the notion of alternative west is set to become a lot more interesting linguistically. It comes at a point when the world is moving towards inclusive globalization due to vanishing power corridor of the west and ascending geopolitical impact of emerging superpower and superpower in waiting. Now it is a reality that the western world no longer continues to rise – in fact, it will have more pressure to act in situation when the alternative west is looking for balanced globalization. It is more than likely that demographically strong languages of alternative west will be in advantageous position. The paper challenges our preconceptions about the nature of sociolinguistic nature of world in the 21st century. It investigates what a linguistic world is likely to be in the future in contrast to what was a linguistic world before 21st century. In particular, the paper tries to answer the following questions: (a) What will be the common linguistic thread across world? (b) How unprecedented transformations can be mapped linguistically? (c) Do we need alternative linguistics to define inclusive globalization as the linguistic reality of the contemporary world has already been reshaped by increasingly integrated world economy, linguistic revolution and alternative west? (d) In which ways these issues can be addressed holistically? (e) Why linguistic world order is changing dramatically? (f) Is it true that the linguistic world around is changing faster than we can even really cope? (g) Is it true that what is coming next is linguistically greater than ever? (h) Do we need to prepare ourselves with new theoretical strategies to address emerging sociolinguistic reality?

Keywords: alternative linguistics, new linguistic world order, power shift, demographic shift, social psychological shift, technological shift

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Authors: Kateryna Merkulova, Alessio Castello, Maria Kreuzer

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This research investigates the drivers of long-term relationship building between customers and suppliers within the luxury food supply chain, a topic that remains largely unexplored in the current state of academic literature. This paper identifies for the first time the key elements that influence the formation and maintenance of effective supply chain relationships, which are crucial for navigating the complexities of the luxury food industry. In particular, it explores the critical role of trust in a business-to-business context, specifically emphasizing its significance in the luxury food supply chain. Empirically, this research is contextualized in the region of the French Riviera, which offers a gastronomic playground for food enthusiasts, making it ideally suited to explore the luxury food sector. Qualitative in-depth interviews with stakeholders along the luxury supply chain (i.e., suppliers, chefs, restaurant owners, and fine food shop managers) allow identifying key drivers of trustful business relationships. Triangulating different perspectives of stakeholders within the luxury supply chain adds validity and robustness to the findings. The findings have important theoretical and managerial implications for the effective functioning of long-term supplier-buyer relationships.

Keywords: luxury food, relationship building, B2B, supply chain, trust

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Authors: Sylvie Studente

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Despite the increase in international students migrating to the UK, the transition from home environment to a host institution abroad can be overwhelming for many students due to acculturative stressors. These stressors are reported to peak within the first six months of transitioning into study abroad which has determinantal impacts for Higher Education Institutions. These impacts include; increased drop-out rates and overall decreases in academic performance. Research suggests that belongingness can negate acculturative stressors through providing opportunities for students to form necessary social connections. In response to this universities have focussed on utilising technology to create learning communities with the most commonly deployed being social media, blogs, and discussion forums. Despite these attempts, the application of technology in supporting international students is still ambiguous. With the reported growing popularity of mobile devices among students and accelerations in learning technology owing to the COVID-19 pandemic, the potential is recognised to address this challenge via the use of chatbot technology. Whilst traditionally, chatbots were deployed as conversational agents in business domains, they have since been applied to the field of education. Within this emerging area of research, a gap exists in addressing the educational value of chatbots over and above the traditional service orientation categorisation. The proposed study seeks to extend upon current understandings by investigating the challenges faced by international students in studying abroad and exploring the potential of chatbots as a solution to assist students’ acculturation. There has been growing interest in the application of chatbot technology to education accelerated by the shift to online learning during the COVID-19 pandemic. Although interest in educational chatbots has surged, there is a lack of consistency in the research area in terms of guidance on the design to support international students in HE. This gap is widened when considering the additional challenge of supporting multicultural international students with diverse. Diversification in education is rising due to increases in migration trends for international study. As global opportunities for education increase, so does the need for multiculturally inclusive learning support.

Keywords: chatbots, education, international students, acculturation

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Authors: Akinbo Razak Yinka, Adesanya Kehinde Kazeem, Oladokun Oluwagbenga Peter

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Time series data are sequences of observations collected over a period of time. Such data can be used to predict health outcomes, such as disease progression, mortality, hospitalization, etc. The Statistical approach is based on mathematical models that capture the patterns and trends of the data, such as autocorrelation, seasonality, and noise, while Neural methods are based on artificial neural networks, which are computational models that mimic the structure and function of biological neurons. This paper compared both parametric and non-parametric time series models of patients treated for malaria in Maternal and Child Health Centres in Lagos State, Nigeria. The forecast methods considered linear regression, Integrated Moving Average, ARIMA and SARIMA Modeling for the parametric approach, while Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) Network were used for the non-parametric model. The performance of each method is evaluated using the Mean Absolute Error (MAE), R-squared (R2) and Root Mean Square Error (RMSE) as criteria to determine the accuracy of each model. The study revealed that the best performance in terms of error was found in MLP, followed by the LSTM and ARIMA models. In addition, the Bootstrap Aggregating technique was used to make robust forecasts when there are uncertainties in the data.

Keywords: ARIMA, bootstrap aggregation, MLP, LSTM, SARIMA, time-series analysis

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Authors: Laszlo Szerb, Zsofia Voros

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In this article, we seek to answer why many attempts to empirically link entrepreneurial self-efficacy to growth expectations have failed. While doing so, we reconcile the literature on entrepreneurial self-efficacy and overconfidence. By analyzing GEM APS (Global Entrepreneurship Monitor Adult Population Survey) data, we show that early-stage entrepreneurs’ self-efficacy statements are systematically inflated. Our results also indicate that entrepreneurial overconfidence is fading and its form changes as business owners learn and gather experience. In addition, by using Ajzen’s Theory of Planned Behavior (2006) as a modeling framework, we illustrate that early stage business owners’ overconfidence results in overly high firm growth expectations. However, the changes in the form of overconfidence and the adjustments of expectations on market conditions as a venture ages alter the relationship between overconfidence and growth expectations across the business life-cycle stages. Overall, our study empirically links young entrepreneurs’ overconfidence to their growth expectations at the firm level. This link is important to establish as expected growth was linked to realized growth both on micro and macro levels. Moreover, we detected several moderators of this relationship providing a potential answer to why many studies failed to link entrepreneurial self-efficacy to growth expectations.

Keywords: self-efficacy, overconfidence, entrepreneurship, expected growth

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Authors: Yan Lyu, Yiqun Pan, Zhizhong Huang

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In the design stage of a new building, the energy model of this building is often required for the analysis of the performance on energy efficiency. In practice, a certain degree of geometric simplification should be done in the establishment of building energy models, since the detailed geometric features of a real building are hard to be described perfectly in most energy simulation engine, such as ESP-r, eQuest or EnergyPlus. Actually, the detailed description is not necessary when the result with extremely high accuracy is not demanded. Therefore, this paper analyzed the relationship between the error of the simulation result from building energy models and the geometric simplification of the models. Finally, the following two parameters are selected as the indices to characterize the geometric feature of in building energy simulation: the southward projected area and total side surface area of the building, Based on the parameterization method, the simplification from an arbitrary column building to a typical shape (a cuboid) building can be made for energy modeling. The result in this study indicates that this simplification would only lead to the error that is less than 7% for those buildings with the ratio of southward projection length to total perimeter of the bottom of 0.25~0.35, which can cover most situations.

Keywords: building energy model, simulation, geometric simplification, design, regression

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Authors: Stéphanie Looser, Walter Wehrmeyer

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Given the limited research on Small and Mediumsized Enterprises’ (SMEs) contribution to Corporate Social Responsibility (CSR) and even scarcer research on Swiss SMEs, this paper helps to fill these gaps by enabling the identification of supranational SME parameters and to make a contribution to the evolving field of these topics. Thus, the paper investigates the current state of SME practices in Switzerland and across 15 other countries. Combining the degree to which SMEs demonstrate an explicit (or business case) approach or see CSR as an implicit moral activity with the assessment of their attributes for “variety of capitalism” defines the framework of this comparative analysis. According to previous studies, liberal market economies, e.g. in the United States (US) or United Kingdom (UK), are aligned with extrinsic CSR, while coordinated market systems (in Central European or Asian countries) evolve implicit CSR agendas. To outline Swiss small business CSR patterns in particular, 40 SME owner-managers were interviewed. The transcribed interviews were coded utilising MAXQDA for qualitative content analysis. A secondary data analysis of results from different countries (i.e., Australia, Austria, Chile, Cameroon, Catalonia (notably a part of Spain that seeks autonomy), China, Finland, Germany, Hong Kong (a special administrative region of China), Italy, Netherlands, Singapore, Spain, Taiwan, UK, US) lays groundwork for this comparative study on small business CSR. Applying the same coding categories (in MAXQDA) for the interview analysis as well as for the secondary data research while following grounded theory rules to refine and keep track of ideas generated testable hypotheses and comparative power on implicit (and the lower likelihood of explicit) CSR in SMEs retrospectively. The paper identifies Swiss small business CSR as deep, profound, “soul”, and an implicit part of the day-to-day business. Similar to most Central European, Mediterranean, Nordic, and Asian countries, explicit CSR is still very rare in Swiss SMEs. Astonishingly, also UK and US SMEs follow this pattern in spite of their strong and distinct liberal market economies. Though other findings show that nationality matters this research concludes that SME culture and its informal CSR agenda are strongly formative and superseding even forces of market economies, nationally cultural patterns, and language. In a world of “big business”, explicit “business case” CSR, and the mantra that “CSR must pay”, this study points to a distinctly implicit small business CSR model built on trust, physical closeness, and virtues that is largely detached from the bottom line. This pattern holds for different cultural contexts and it is concluded that SME culture is stronger than nationality leading to a supra-national, monolithic SME CSR approach. Hence, classifications of countries by their market system or capitalism, as found in the comparative capitalism literature, do not match the CSR practices in SMEs as they do not mirror the peculiarities of their business. This raises questions on the universality and generalisability of management concepts.

Keywords: CSR, comparative study, cultures of capitalism, small, medium-sized enterprises

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Authors: Gheyzer Villegas, Edgardo Cedeño, Veruska Mata, Edmundo Chauran

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One of the most significant changes that occurred in global commerce was the emergence of cryptocurrencies and blockchain technology. There is still much debate about the adoption of the economic model based on crypto assets, and myriad international projects and initiatives are being carried out to try and explore the potential that this new field offers. The Hive blockchain is a prime example of this, featuring two use cases: of how trade based on its native currencies can give successful results in the exchange of goods and services and in the financing of social impact projects. Its decentralized management model and visionary administration of its development fund have become a key part of its success.

Keywords: Hive, business, network, blockchain

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Authors: S. O. Oyamakin, A. U. Chukwu,

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We proposed a Hyperbolic Gompertz Growth Model (HGGM), which was developed by introducing a stabilizing parameter called θ using hyperbolic sine function into the classical gompertz growth equation. The resulting integral solution obtained deterministically was reprogrammed into a statistical model and used in modeling the height and diameter of Pines (Pinus caribaea). Its ability in model prediction was compared with the classical gompertz growth model, an approach which mimicked the natural variability of height/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using goodness of fit tests and model selection criteria. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the compliance of the error term to normality assumptions while using testing the independence of the error term using the runs test. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic gompertz growth models better than the source model (classical gompertz growth model) while the results of R2, Adj. R2, MSE, and AIC confirmed the predictive power of the Hyperbolic Monomolecular growth models over its source model.

Keywords: height, Dbh, forest, Pinus caribaea, hyperbolic, gompertz

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Authors: Timothy Kayode Samson, Adedoyin Isola Lawal

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The past five years have shown a sharp increase in public interest in the crypto market, with its market capitalization growing from $100 billion in June 2017 to $2158.42 billion on April 5, 2022. Despite the outrageous nature of the volatility of cryptocurrencies, the use of skewed error innovation distributions in modelling the volatility behaviour of these digital currencies has not been given much research attention. Hence, this study models the volatility of 5 largest cryptocurrencies by market capitalization (Bitcoin, Ethereum, Tether, Binance coin, and USD Coin) using four variants of GARCH models (GJR-GARCH, sGARCH, EGARCH, and APARCH) estimated using three skewed error innovation distributions (skewed normal, skewed student- t and skewed generalized error innovation distributions). Daily closing prices of these currencies were obtained from Yahoo Finance website. Finding reveals that the Binance coin reported higher mean returns compared to other digital currencies, while the skewness indicates that the Binance coin, Tether, and USD coin increased more than they decreased in values within the period of study. For both Bitcoin and Ethereum, negative skewness was obtained, meaning that within the period of study, the returns of these currencies decreased more than they increased in value. Returns from these cryptocurrencies were found to be stationary but not normality distributed with evidence of the ARCH effect. The skewness parameters in all best forecasting models were all significant (p<.05), justifying of use of skewed error innovation distributions with a fatter tail than normal, Student-t, and generalized error innovation distributions. For Binance coin, EGARCH-sstd outperformed other volatility models, while for Bitcoin, Ethereum, Tether, and USD coin, the best forecasting models were EGARCH-sstd, APARCH-sstd, EGARCH-sged, and GJR-GARCH-sstd, respectively. This suggests the superiority of skewed Student t- distribution and skewed generalized error distribution over the skewed normal distribution.

Keywords: skewed generalized error distribution, skewed normal distribution, skewed student t- distribution, APARCH, EGARCH, sGARCH, GJR-GARCH

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Authors: Ertuğrul Ferhat Yilmaz, Ali Riza Perçin

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In the business enterprises implemented modern business enterprise principles, the most important issues are increasing the performance of workers and getting maximum income. Through the twentieth century, rapid development of the sectors of data processing and communication and because of the free trade politics arising of multilateral business enterprises have canceled the economical borders and changed the local rivalry into the spherical rivalry. In this rivalry conditions, the business enterprises have to work active and productive in order to continue their existences. The employees worked at business enterprises have formed the most important factor of product. Therefore, the business enterprises inferring the importance of the human factors in order to increase the profit have used “the performance evolution system” to increase the success and development of the employees. The evolution of the performance is aimed to increase the manpower productive by using the employees in an active way. Furthermore, this system assists the wage politics implemented in business enterprise, determining the strategically plans in business enterprises through the short and long terms, being promoted and determining the educational needs of employees, making decisions as dismissing and work rotation. It requires a great deal of effort to catch the pace of change in the working realm and to keep up ourselves up-to-date. To get the quality in people,to have an effect in workplace depends largely on the knowledge and competence of managers and prospective managers. Therefore,managers need to use the performance evaluation systems in order to base their managerial decisions on sound data. This study aims at finding whether the organizations effectively use performance evaluation systms,how much importance is put on this issue and how much the results of the evaulations have an effect on employees. Whether the organizations have the advantage of competition and can keep on their activities depend to a large extent on how they effectively and efficiently use their employees.Therefore,it is of vital importance to evaluate employees' performance and to make them better according to the results of that evaluation. The performance evaluation system which evaluates the employees according to the criteria related to that organization has become one of the most important topics for management. By means of those important ends mentioned above,performance evaluation system seems to be a tool that can be used to improve the efficiency and effectiveness of organization. Because of its contribution to organizational success, thinking performance evaluation on the axis of efficiency shows the importance of this study on a different angle. In this study, we have explained performance evaluation system ,efficiency and the relation between those two concepts. We have also analyzed the results of questionnaires conducted on the textile workers in Edirne city.We have got positive answers from the questions about the effects of performance evaluation on efficiency.After factor analysis ,the efficiency and motivation which are determined as factors of performance evaluation system have the biggest variance (%19.703) in our sample. Thus, this study shows that objective performance evaluation increases the efficiency and motivation of employees.

Keywords: performance, performance evolution system, productivity, Edirne region

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Authors: David Philpott, Karen Kennedy

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In recognition of an increasingly diverse student population, a Teaching and Learning Framework was developed at Memorial University of Newfoundland. This framework emphasizes work that is engaging, supportive, inclusive, responsive, committed to discovery, and is outcomes-oriented for both educators and learners. The goal of the Teaching and Learning framework was to develop a number of initiatives that builds on existing knowledge, proven programs, and existing supports in order to respond to the specific needs of identified groups of diverse learners: 1) academically vulnerable first year students; 2) students with individual learning needs associated with disorders and/or mental health issues; 3) international students and those from non-western cultures. This session provides an overview of this process. The strategies employed to develop these initiatives were drawn primarily from research on student success and retention (literature review), information on pre-existing programs (environmental scan), an analysis of in-house data on students at our institution; consultations with key informants at all of Memorial’s campuses. The first initiative that emerged from this research was a pilot project proposal for a first-year success program in support of the first-year experience of academically vulnerable students. This program offers a university experience that is enhanced by smaller classes, supplemental instruction, learning communities, and advising sessions. The second initiative that arose under the mandate of the Teaching and Learning Framework was a collaborative effort between two institutions (Memorial University and the College of the North Atlantic). Both institutions participated in a shared conversation to examine programs and services that support an accessible and inclusive environment for students with disorders and/or mental health issues. A report was prepared based on these conversations and an extensive review of research and programs across the country. Efforts are now being made to explore possible initiatives that address culturally diverse and non-traditional learners. While an expanding literature has emerged on diversity in higher education, the process of developing institutional initiatives is usually excluded from such discussions, while the focus remains on effective practice. The proposals that were developed constitute a co-ordination and strengthening of existing services and programs; a weaving of supports to engage a diverse body of students in a sense of community. This presentation will act as a guide through the process of developing projects addressing learner diversity and engage attendees in a discussion of institutional practices that have been implemented in support of overcoming challenges, as well as provide feedback on institutional and student outcomes. The focus of this session will be on effective practice, and will be of particular interest to university administrators, educational developers, and educators wishing to implement similar initiatives on their campuses; possible adaptations for practice will be addressed. A presentation of findings from this research will be followed by an open discussion where the sharing of research, initiatives, and best practices for the enhancement of teaching and learning is welcomed. There is much insight and understanding to be gained through the sharing of ideas and collaborative practice as we move forward to further develop the program and prepare other initiatives in support of diversity and inclusion.

Keywords: eco-scale, green analysis, environmentally-friendly, pharmaceuticals analysis

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Authors: Sean Paulsen, Michael Casey

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In this work we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

Keywords: transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training

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Authors: Panagiotis Karadimos, Leonidas Anthopoulos

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Predicting the actual cost and duration in construction projects concern a continuous and existing problem for the construction sector. This paper addresses this problem with modern methods and data available from past public construction projects. 39 bridge projects, constructed in Greece, with a similar type of available data were examined. Considering each project’s attributes with the actual cost and the actual duration, correlation analysis is performed and the most appropriate predictive project variables are defined. Additionally, the most efficient subgroup of variables is selected with the use of the WEKA application, through its attribute selection function. The selected variables are used as input neurons for neural network models through correlation analysis. For constructing neural network models, the application FANN Tool is used. The optimum neural network model, for predicting the actual cost, produced a mean squared error with a value of 3.84886e-05 and it was based on the budgeted cost and the quantity of deck concrete. The optimum neural network model, for predicting the actual duration, produced a mean squared error with a value of 5.89463e-05 and it also was based on the budgeted cost and the amount of deck concrete.

Keywords: actual cost and duration, attribute selection, bridge construction, neural networks, predicting models, FANN TOOL, WEKA

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Authors: Alfi Al Fahreizy

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Yogyakarta is one of the provinces in Indonesia that often get a power outage because of high load electrical consumption. The authors mapped the electrical energy consumption [GWh] for the province of Yogyakarta in 2014-2025 using LEAP (Long-range Energy Alternatives Planning system) software. This paper use BAU (Business As Usual) scenario. BAU scenario in which the projection is based on the assumption that growth in electricity consumption will run as normally as before. The goal is to be able to see the electrical energy consumption in the household sector, industry , business, social, government office building, and street lighting. The data is the data projected statistical population and consumption data electricity [GWh] 2010, 2011, 2012 in Yogyakarta province.

Keywords: LEAP, energy consumption, Yogyakarta, BAU

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Authors: Yasaman Tohidi, Rouzbeh Riazi, Shidvash Vakilipour, Masoud Mohammadi

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The objective of the present study is to numerically investigate the effect of CO₂ replacement of N₂ in air stream on the flame characteristics of the CH₄ turbulent diffusion flame. The Open source Field Operation and Manipulation (OpenFOAM) has been used as the computational tool. In this regard, laminar flamelet and modified k-ε models have been utilized as combustion and turbulence models, respectively. Results reveal that the presence of CO₂ in air stream changes the flame shape and maximum flame temperature. Also, CO₂ dilution causes an increment in CO mass fraction.

Keywords: CH4 diffusion flame, CO2 dilution, OpenFOAM, turbulent flame

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Authors: Saima Ali, Pathamanathan Rajeev, Imteaz A. Monzur

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In this paper, a brief review of the corrosion mechanism in buried pipe and modes of failure is provided together with the available corrosion models. Moreover, the sensitivity analysis is performed to understand the influence of corrosion model parameters on the remaining life estimation. Further, the probabilistic analysis is performed to propagate the uncertainty in the corrosion model on the estimation of the renaming life of the pipe. Finally, the comparison among the corrosion models on the basis of the remaining life estimation will be provided to improve the renewal plan.

Keywords: corrosion, pit depth, sensitivity analysis, exposure period

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Authors: Nebila Lichiheb, LaToya Myles, William Pendergrass, Bruce Hicks, Dawson Cagle

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Atmospheric transport of hazardous materials in urban areas is increasingly under investigation due to the potential impact on human health and the environment. In response to health and safety concerns, several dispersion models have been developed to analyze and predict the dispersion of hazardous contaminants. The models of interest usually rely on meteorological information obtained from the meteorological models of NOAA’s National Weather Service (NWS). However, due to the complexity of the urban environment, NWS forecasts provide an inadequate basis for dispersion computation in urban areas. A dense meteorological network in Washington, DC, called DCNet, has been operated by NOAA since 2003 to support the development of urban monitoring methodologies and provide the driving meteorological observations for atmospheric transport and dispersion models. This study focuses on the comparison of wind observations from the DCNet station on the U.S. Department of Commerce Herbert C. Hoover Building against the North American Mesoscale (NAM) model outputs for the period 2017-2019. The goal is to develop a simple methodology for modifying NAM outputs so that the dispersion requirements of the city and its urban area can be satisfied. This methodology will allow us to quantify the prediction errors of the NAM model and propose adjustments of key variables controlling dispersion model calculation.

Keywords: meteorological data, Washington D.C., DCNet data, NAM model

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Authors: Zeinab Ranjbar

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Service-oriented architecture in the world today, it is proposed to exchange information and services of interest to those such as IT managers, business managers, designers and system builders scene. The basic architecture of the software used to provide service to all users.the worries of all people (managers, business managers, designers, and system builders scene) effectiveness of this model, how reliable it is in security transactions.To increase the reliability of multi-layer fuzzy logic Architectures used.

Keywords: SOA, service oriented architecture, fuzzy logic, multi layer, SOA security

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Authors: Iman Shabanzadeh

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The purpose of this research is to understand the lived experience of private sector entrepreneurs in facing the sources of freedom and unfreedom and benefiting from opportunities and basic capabilities in the process of realizing entrepreneurial ability in order to get closer to the macro situation of the narrative of human development in Iranian society. Therefore, the main question of the present research is to figure out what sources of freedom and social opportunities and unfreedom entrepreneurs in Iran's society benefit from the process of transforming their potential entrepreneurial abilities into entrepreneurial and business enterprises. In terms of methodology, the current research method will be thematic analysis in the form of semi-structured interviews with entrepreneurs active in small and medium-sized enterprises in Tehran, whose process of establishing and expanding their entrepreneurial activity has been in the last two decades. By examining the possibilities and refusals of advancing these people in the three stages of 'Idea creation and desire for entrepreneurship’, ‘Starting and creating a business’, and finally, ‘Continuing and expanding the business’, the findings of the research show the impact of five main resources for people to realize their potential talents, from the stage of creating an idea to expanding their business. These sources include' family institution,’ ‘education institution,’ ‘social norms and beliefs,’ ‘government and market,’ and ‘personality components of the entrepreneur.’ Finally, the findings are reported in three levels of basic themes (fifteen items), organizing themes (five items), and comprehensive themes (one item) and in the form of a theme network.

Keywords: entrepreneurship, human development, capability, sources of freedom

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Authors: Waziri B. I., Elkhashab M. M.

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Background: One of the most serious consequences of spinal cord injury (SCI) is progressive deterioration of renal function mostly as a result of urine stasis and ascending infection of the paralyzed bladder. This necessitates for investigation of early changes in serum urea and creatinine and associated sex related differences in response to SCI. Methods: A total of 24 adult albino rats weighing above 150g were divided equally into two groups, a control and experimental group (n = 12) each containing an equal number of male and female rats. The experimental group animals were paralyzed by complete transection of spinal cord below T4 level after deep anesthesia with ketamine 75mg/kg. Blood samples were collected from both groups five days post SCI for analysis. Mean values of serum urea (mmol/L) and creatinine (µmol/L) for both groups were compared. P < 0.05 was considered as significant. Results: The results showed significantly higher levels (P < 0.05) of serum urea and creatinine in the male SCI models with mean values of 92.12 ± 0.98 and 2573 ± 70.97 respectively compared with their controls where the mean values for serum urea and creatinine were 6.31 ± 1.48 and 476. 95 ± 4.67 respectively. In the female SCI models, serum urea 13.11 ± 0.81 and creatinine 519.88 ± 31.13 were not significantly different from that of female controls with serum urea and creatinine levels of 11.71 ± 1.43 and 493.69 ± 17.10 respectively (P > 0.05). Conclusion: Spinal cord injury caused a significant increase in serum Urea and Creatinine levels in the male models compared to the females. This indicated that males might have higher risk of renal dysfunction following SCI.

Keywords: albino rats, creatinine, spinal cord injury (SCI), urea

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Authors: Éva Pintér, Péter Bagó, Nikolett Deutsch, Miklós Hetényi

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The process of digital transformation has a profound influence on all sectors of the worldwide economy and the business environment. The influence of blockchain technology can be observed in the digital economy and e-government, rendering it an essential element of a nation's growth strategy. The banking industry is experiencing significant expansion and development of financial technology firms. Utilizing developing technologies such as artificial intelligence (AI), machine learning (ML), and big data (BD), these entrants are offering more streamlined financial solutions, promptly addressing client demands, and presenting a challenge to incumbent institutions. The advantages of digital transformation are evident in the corporate realm, and firms that resist its adoption put their survival at risk. The advent of digital technologies has revolutionized the business environment, streamlining processes and creating opportunities for enhanced communication and collaboration. Thanks to the aid of digital technologies, businesses can now swiftly and effortlessly retrieve vast quantities of information, all the while accelerating the process of creating new and improved products and services. Big data analytics is generally recognized as a transformative force in business, considered the fourth paradigm of science, and seen as the next frontier for innovation, competition, and productivity. Big data, an emerging technology that is shaping the future of the banking sector, offers numerous advantages to banks. It enables them to effectively track consumer behavior and make informed decisions, thereby enhancing their operational efficiency. Banks may embrace big data technologies to promptly and efficiently identify fraud, as well as gain insights into client preferences, which can then be leveraged to create better-tailored products and services. Moreover, the utilization of big data technology empowers banks to develop more intelligent and streamlined models for accurately recognizing and focusing on the suitable clientele with pertinent offers. There is a scarcity of research on big data analytics in the banking industry, with the majority of existing studies only examining the advantages and prospects associated with big data. Although big data technologies are crucial, there is a dearth of empirical evidence about the role of big data analytics (BDA) capabilities in bank performance. This research addresses a gap in the existing literature by introducing a model that combines the resource-based view (RBV), the technical organization environment framework (TOE), and dynamic capability theory (DC). This study investigates the influence of Big Data Analytics (BDA) utilization on the performance of market and risk management. This is supported by a comparative examination of Hungarian mobile banking services.

Keywords: big data, digital transformation, dynamic capabilities, mobile banking

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Authors: Percy Galvez, Anatoly Petukhin, Paul Somerville, Ken Miyakoshi, Kojiro Irikura, Daniel Peter

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Physics-based dynamic rupture modelling is necessary for estimating parameters such as rupture velocity and slip rate function that are important for ground motion simulation, but poorly resolved by observations, e.g. by seismic source inversion. In order to generate a large number of physically self-consistent rupture models, whose rupture process is consistent with the spatio-temporal heterogeneity of past earthquakes, we use multicycle simulations under the heterogeneous rate-and-state (RS) friction law for a 45deg dip-slip fault. We performed a parametrization study by fully dynamic rupture modeling, and then, a set of spontaneous source models was generated in a large magnitude range (Mw > 7.0). In order to validate rupture models, we compare the source scaling relations vs. seismic moment Mo for the modeled rupture area S, as well as average slip Dave and the slip asperity area Sa, with similar scaling relations from the source inversions. Ground motions were also computed from our models. Their peak ground velocities (PGV) agree well with the GMPE values. We obtained good agreement of the permanent surface offset values with empirical relations. From the heterogeneous rupture models, we analyzed parameters, which are critical for ground motion simulations, i.e. distributions of slip, slip rate, rupture initiation points, rupture velocities, and source time functions. We studied cross-correlations between them and with the friction weakening distance Dc value, the only initial heterogeneity parameter in our modeling. The main findings are: (1) high slip-rate areas coincide with or are located on an outer edge of the large slip areas, (2) ruptures have a tendency to initiate in small Dc areas, and (3) high slip-rate areas correlate with areas of small Dc, large rupture velocity and short rise-time.

Keywords: earthquake dynamics, strong ground motion prediction, seismic engineering, source characterization

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Authors: Ziba R. Tehrani, Sanaz Moayer

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In the age of the knowledge-based economy, knowledge management has become a key factor in sustainable competitive advantage. Knowledge management is discovering, acquiring, developing, sharing, maintaining, evaluating, and using right knowledge in right time by right person in organization; which is accomplished by creating a right link between human resources, information technology, and appropriate structure, to achieve organisational goals. Studying knowledge management financial institutes shows the knowledge management in banking system is not different from other industries but because of complexity of bank’s environment, the implementation is more difficult. The bank managers found out that implementation of knowledge management will bring many advantages to financial institutes, one of the most important of which is reduction of threat to lose subsequent information of personnel job quit. Also Special attention to internal conditions and environment of the financial institutes and avoidance from copy-making in designing the knowledge management is a critical issue. In this paper, it is tried first to define knowledge management concept and introduce existing models of knowledge management; then some of the most important models which have more similarities with other models will be reviewed. In second step according to bank requirements with focus on knowledge management approach, most major objectives of knowledge management are identified. For gathering data in this stage face to face interview is used. Thirdly these specified objectives are analysed with the response of distribution of questionnaire which is gained through managers and expert staffs of ‘Karafarin Bank’. Finally based on analysed data, some features of exiting models are selected and a new conceptual model will be proposed.

Keywords: knowledge management, financial institute, knowledge management model, organisational knowledge

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Authors: Shashwat Mookherjee, Shruti Dutta

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This study explores linguistic distinctions among American, Indian, and Irish English dialects and assesses various Language Models (LLMs) in their ability to generate British English translations from these dialects. Using cosine similarity analysis, the study measures the linguistic proximity between original British English translations and those produced by LLMs for each dialect. The findings reveal that Indian and Irish English translations maintain notably high similarity scores, suggesting strong linguistic alignment with British English. In contrast, American English exhibits slightly lower similarity, reflecting its distinct linguistic traits. Additionally, the choice of LLM significantly impacts translation quality, with Llama-2-70b consistently demonstrating superior performance. The study underscores the importance of selecting the right model for dialect translation, emphasizing the role of linguistic expertise and contextual understanding in achieving accurate translations.

Keywords: cross-dialect translation, language models, linguistic similarity, multilingual NLP

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Authors: Malika Fekih, Abdenour Bourabaa, Rafika Hariti, Mohamed Saighi

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In Algeria the global solar radiation and its components is not available for all locations due to which there is a requirement of using different models for the estimation of global solar radiation that use climatological parameters of the locations. Empirical constants for these models have been estimated and the results obtained have been tested statistically. The results show encouraging agreement between estimated and measured values.

Keywords: global solar radiation, empirical model, semi arid areas, climatological parameters

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Authors: Steve Fish, Chris Lambert

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Cumbria is a geo-political county in Northwest England within which the Lake District National Park, a UNESCO World Heritage site is located. Whilst the area has a formidable reputation for natural beauty and historic assets, the innovation ecosystem is described as ‘patchy’ for a number of reasons. The county is one of the largest in England by area and is sparsely populated. This paper describes the needs, development and delivery of an SME business-support programme funded by the European Regional Development Fund, Lancaster University and the University of Cumbria. The Cumbria Innovations Platform (CUSP) Project has been designed to respond to the nuanced needs of SMEs in this locale, whilst promoting the adoption of research and innovation. CUSP utilizes a funnel method to support rural businesses with access to university innovation intervention. CUSP has been built on a three-tier model: Communicate, Collaborate and Create. The paper describes this project in detail and presents results in terms of output indicators achieved, a beneficiary telephone survey and wider economic forecasts. From a pragmatic point-of-view, the paper provides experiences and reflections of those people who are delivering and evaluating knowledge exchange. The authors discuss some of the benefits, challenges and implications for both policy makers and practitioners. Finally, the paper aims to serve as an invitation to others who may consider adopting a similar method of university-industry collaboration in their own region.

Keywords: regional business support, rural business support, university-industry collaboration, collaborative R&D, SMEs, knowledge exchange

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Authors: Hai Hoang, Thanh Xuan Nguyen Thi, Guillaume Galliero

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Coarse-Grained (CG) molecular simulations have shown to be an efficient way to estimate thermophysical (static and dynamic) properties of fluids. Several strategies have been developed and reported in the literature for defining CG molecular models. Among them, those based on a top-down strategy (i.e. CG molecular models related to macroscopic observables), despite being heuristic, have increasingly gained attention. This is probably due to its simplicity in implementation and its ability to provide reasonable results for not only simple but also complex systems. Regarding simple Force-Fields associated with these CG molecular models, it has been found that the four parameters Mie chain model is one of the best compromises to describe thermophysical static properties (e.g. phase diagram, saturation pressure). However, parameterization procedures of these Mie-chain GC molecular models given in literature are generally insufficient to simultaneously provide static and dynamic (e.g. viscosity) properties. To deal with such situations, we have extended the corresponding states by using a quantity associated with the liquid viscosity. Results obtained from molecular simulations have shown that our approach is able to yield good estimates for both static and dynamic thermophysical properties for various real non-associating fluids. In addition, we will show that on simple (e.g. phase diagram, saturation pressure) and complex (e.g. thermodynamic response functions, thermodynamic energy potentials) static properties, results of our scheme generally provides improved results compared to existing approaches.

Keywords: coarse-grained model, mie potential, molecular simulations, thermophysical properties, phase equilibria

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Authors: Fotis I. Giasemis, Alexandros Sopasakis

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This study focuses on detecting traffic anomalies using generative models applied to real-time observations. By integrating a Graph Neural Network with an attention-based mechanism within the Spatiotemporal Generative Adversarial Network framework, we enhance the capture of both spatial and temporal dependencies in traffic data. Leveraging minute-by-minute observations from cameras distributed across Gothenburg, our approach provides a more detailed and precise anomaly detection system, effectively capturing the complex topology and dynamics of urban traffic networks.

Keywords: traffic, anomaly detection, GNN, GAN

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