Search results for: digital business models

Authors: Mohd Radzi Hilmi, Mohd Zulfaezal Che Azemin, Khairidzan Mohd Kamal, Azrin Esmady Ariffin, Mohd Izzuddin Mohd Tamrin, Norfazrina Abdul Gaffur, Tengku Mohd Tengku Sembok

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Purpose: The purpose of this study is to predict optical quality changes after pterygium surgery using tissue redness grading. Methods: Sixty-eight primary pterygium participants were selected from patients who visited an ophthalmology clinic. We developed a semi-automated computer program to measure the pterygium fibrovascular redness from digital pterygium images. The outcome of this software is a continuous scale grading of 1 (minimum redness) to 3 (maximum redness). The region of interest (ROI) was selected manually using the software. Reliability was determined by repeat grading of all 68 images and its association with contrast sensitivity function (CSF) and visual acuity (VA) was examined. Results: The mean and standard deviation of redness of the pterygium fibrovascular images was 1.88 ± 0.55. Intra- and inter-grader reliability estimates were high with intraclass correlation ranging from 0.97 to 0.98. The new grading was positively associated with CSF (p<0.01) and VA (p<0.01). The redness grading was able to predict 25% and 23% of the variance in the CSF and the VA respectively. Conclusions: The new grading of pterygium fibrovascular redness can be reliably measured from digital images and show a good correlation with CSF and VA. The redness grading can be used in addition to the existing pterygium grading.

Keywords: contrast sensitivity, pterygium, redness, visual acuity

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Authors: Elena Valionienė, Genutė Kalvaitienė

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The issue of resilience of an individual, an organisation, or an entire ecosystem of organisations has recently become an integral part of the education system, where the uncertainties that lead to societal development in the short term create economic, social, and psycho-emotional instability. The Maritime Transport Sector (MTS) is no exception, and the aim of the article is to model the possibilities of enhancing the professional, sociocultural, and psycho-emotional resilience of MTS specialists to proactively respond to crises caused by uncertainties. The research consists of theoretical model creation that helps to identify general maritime business resilience factors and critical success factors. This can develop high resilience and achieve business excellence in a highly volatile, uncertain, complex, and ambiguous (VUCA) environment.

Keywords: maritime transport sector, resilience, uncertainties, VUCA

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Authors: Lien T. H. Tran, David A. Holloway

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Corporate governance practices have changed significantly across the world in the past three decades. Spectacular corporate failures during this period have acted as a catalyst for the development of codes and guidelines that have resulted in the global acceptance of a ‘best practice’ model. This study assesses the relevance of such a ‘one size fits all model’ for the developing nation state of Vietnam. The findings of this analytical paper is that there are three key elements (government, international institutions and the nature of business) that are pertinent and central to corporate governance developments in the country. We also find that the quality of corporate governance in Vietnam is at a medium level when compared to international practices. Vietnam still has a long way to go to construct and embed effective corporate governance policies and practices and promote ethical business behaviours and sound decision making at board level.

Keywords: corporate governance, government, international institutions, public companies, Vietnam

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Authors: Tahar Alimi, Rahma Boujebane, Wiem Derouich, Lamia Hadrich Belguith

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Machine translation task of low-resourced languages such as Arabic is a challenging task. Despite the appearance of sophisticated models based on the latest deep learning techniques, namely the transfer learning and transformers, all models prove incapable of carrying out an acceptable translation, which includes Arabic Dialects (AD), because they do not have official status. In this paper, we present a machine translation model designed to translate Arabic multidialectal content into Modern Standard Arabic (MSA), leveraging both new and existing parallel resources. The latter achieved the best results for both Levantine and Maghrebi dialects with a BLEU score of 64.99.

Keywords: Arabic translation, dialect translation, fine-tune, MSA translation, transformer, translation

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Authors: Raj K. Gupta, X. Gary Tan, Andrzej Przekwas

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Bomb blasts from Improvised Explosive Devices (IEDs) account for vast majority of terrorist attacks worldwide. Injuries caused by IEDs result from a combination of the primary blast wave, penetrating fragments, and human body accelerations and impacts. This paper presents a multiscale computational model of coupled blast physics, whole human body biodynamics and injury biomechanics of sensitive organs. The disparity of the involved space- and time-scales is used to conduct sequential modeling of an IED explosion event, CFD simulation of blast loads on the human body and FEM modeling of body biodynamics and injury biomechanics. The paper presents simulation results for blast-induced brain injury coupling macro-scale brain biomechanics and micro-scale response of sensitive neuro-axonal structures. Validation results on animal models and physical surrogates are discussed. Results of our model can be used to 'replicate' filed blast loadings in laboratory controlled experiments using animal models and in vitro neuro-cultures.

Keywords: blast waves, improvised explosive devices, injury biomechanics, mathematical models, traumatic brain injury

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Authors: Sharad Singh, Ajay Kumar Sinha

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Coupled dampers like viscoelastic-frictional dampers for supplemental damping are a newer technique. In this paper, innovative Visco-frictional damping models have been presented and investigated. This paper attempts to couple frictional and fluid viscous dampers into a single unit of supplemental dampers. Visco-frictional damping model is developed by series and parallel coupling of frictional and fluid viscous dampers using Maxwell and Kelvin-Voigat models. The time analysis has been performed using numerical simulation on an SDOF system with varying fundamental periods, subject to a set of 12 ground motions. The simulation was performed using the direct time integration method. MATLAB programming tool was used to carry out the numerical simulation. The response behavior has been analyzed for the varying time period and added damping. This paper compares the response reduction behavior of the two modes of coupling. This paper highlights the performance efficiency of the suggested damping models. It also presents a mathematical modeling approach to visco-frictional dampers and simultaneously suggests the suitable mode of coupling between the two sub-units.

Keywords: hysteretic damping, Kelvin model, Maxwell model, parallel coupling, series coupling, viscous damping

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Authors: Dinh Ngoc Bich Khuyen, Chang Zhu

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Due to the radical changes and complexities within academic institutions, leadership development addressed to academic leaders in the digital age has become more important. Unfortunately, studies on outcome assessment of leadership development and its related factors have not been evaluated rigorously. The current study investigated the contribution of peer interaction and two subscales of motivation to the effectiveness of the leadership development programs perceived by learners in a diverse context. Of 73 participants, the majority of workshop attendees were junior and middle-level leaders from both European universities and Chinese universities who participated in the leadership development programs organized under an EU project. PLS-SEM was employed to validate the instrument and answer the research questions, respectively. The finding reveals that self-growth and peer interaction significantly contribute to perceived effectiveness, whereas networking motivator shows non-significant impact. Besides, the new contribution of these findings is to show that peer interaction fully mediates the relationship between self-growth and perceived effectiveness. To this end, the findings highlight the importance of dispositional factors regarding the quality of the leadership development program in HE contexts and the potential of such program to enhance the knowledge and capacities of academic leaders regarding university governance and leadership.

Keywords: higher education, leadership development, effectiveness, middle-level leaders, junior-level leaders

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Authors: Panprae Bunyapukkna

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The purpose of this research is to analyze the process that most of the Thai film industries commonly use in order to find the right cast to play the role. The result proved that most of the low-budget film productions find the cast by asking from the crew’s friends or friend of friend. Therefore, finding the cast in low-budget film productions normally has only few people shown up for the auditions and sometimes either none of them has acting knowledge or their appearances do not match the character. However, since most of the low-budget film productions do not have much ability to find members of the cast, thus some of them still will be selected. On the other hand, most of the high-budget film productions use modeling companies to find the cast for them. However, most of modeling agencies in Thailand seek and select their cast members from the cast’s appearances or talents rather than the knowledge of acting.

Keywords: casting for film, modeling business, acting, film, performing arts, film business

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Authors: Jovian Cheung, Thomas Kwok, Victor Wong

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Buildings are entwined with smart city developments. Building performance relies heavily on electrical and mechanical (E&M) systems and services accounting for about 40 percent of global energy use. By cohering the advancement of technology as well as energy and operation-efficient initiatives into the buildings, people are enabled to raise building performance and enhance the sustainability of the built environment in their daily lives. Digital transformation in the buildings is the profound development of the city to leverage the changes and opportunities of digital technologies To optimize the building performance, intelligent power quality and energy management system is developed for transforming data into actions. The system is formed by interfacing and integrating legacy metering and internet of things technologies in the building and applying big data techniques. It provides operation and energy profile and actionable insights of a building, which enables to optimize the building performance through raising people awareness on E&M services and energy consumption, predicting the operation of E&M systems, benchmarking the building performance, and prioritizing assets and energy management opportunities. The intelligent power quality and energy management system comprises four elements, namely the Integrated Building Performance Map, Building Performance Dashboard, Power Quality Analysis, and Energy Performance Analysis. It provides predictive operation sequence of E&M systems response to the built environment and building activities. The system collects the live operating conditions of E&M systems over time to identify abnormal system performance, predict failure trends and alert users before anticipating system failure. The actionable insights collected can also be used for system design enhancement in future. This paper will illustrate how intelligent power quality and energy management system provides operation and energy profile to optimize the building performance and actionable insights to revitalize an existing building into a smart building. The system is driving building performance optimization and supporting in developing Hong Kong into a suitable smart city to be admired.

Keywords: intelligent buildings, internet of things technologies, big data analytics, predictive operation and maintenance, building performance

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Authors: Jeonghwan Jeon

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Recently, the industry and academia have been planning development through industry/university cooperation (IUC), and the government has been promoting alternative methods to achieve successful IUC. Representatively, business cultivation involves the lead university (regarding IUC), research and development (R&D), company support, professional manpower cultivation, and marketing, etc., and the scale of support expands every year. Research is performed by many academic researchers to achieve IUC and although satisfaction of their results is high, expectations are not being met and study of the main factor is insufficient. Therefore, this research improves on theirs by analysing the main factors influencing their satisfaction. Each factor is analysed by AHP, and portfolio analysis is performed on the importance and current satisfaction level. This will help improve satisfaction of business participants and ensure effective IUC in the future.

Keywords: industry/university cooperation, satisfaction, portfolio analysis, research and development

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Authors: Dino Carpentras, Paul J. Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is a sub-field of agent-based modeling that focuses on people’s opinions and their evolutions over time. Despite the rapid increase in the number of publications in this field, it is still not clear how to apply these models to real-world scenarios. Indeed, there is no agreement on how people update their opinion while interacting. Furthermore, it is not clear if different topics will show the same dynamics (e.g., more polarized topics may behave differently). These problems are mostly due to the lack of experimental validation of the models. Some previous studies started bridging this gap in the literature by directly measuring people’s opinions before and after the interaction. However, these experiments force people to express their opinion as a number instead of using natural language (and then, eventually, encoding it as numbers). This is not the way people normally interact, and it may strongly alter the measured dynamics. Another limitation of these studies is that they usually average all the topics together, without checking if different topics may show different dynamics. In our work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions in natural language (“agree” or “disagree”). We also measured the certainty of their answer, expressed as a number between 1 and 10. However, this value was not shown to other participants to keep the interaction based on natural language. We then showed the opinion (and not the certainty) of another participant and, after a distraction task, we repeated the measurement. To make the data compatible with opinion dynamics models, we multiplied opinion and certainty to obtain a new parameter (here called “continuous opinion”) ranging from -10 to +10 (using agree=1 and disagree=-1). We firstly checked the 5 topics individually, finding that all of them behaved in a similar way despite having different initial opinions distributions. This suggested that the same model could be applied for different unpolarized topics. We also observed that people tend to maintain similar levels of certainty, even when they changed their opinion. This is a strong violation of what is suggested from common models, where people starting at, for example, +8, will first move towards 0 instead of directly jumping to -8. We also observed social influence, meaning that people exposed with “agree” were more likely to move to higher levels of continuous opinion, while people exposed with “disagree” were more likely to move to lower levels. However, we also observed that the effect of influence was smaller than the effect of random fluctuations. Also, this configuration is different from standard models, where noise, when present, is usually much smaller than the effect of social influence. Starting from this, we built an opinion dynamics model that explains more than 80% of data variance. This model was also able to show the natural conversion of polarization from unpolarized states. This experimental approach offers a new way to build models grounded on experimental data. Furthermore, the model offers new insight into the fundamental terms of opinion dynamics models.

Keywords: experimental validation, micro-dynamics rule, opinion dynamics, update rule

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Authors: Ahmad El Hajjar, Joanna Eid, Salima Bouchemella, Tariq Ouahbi, Benoit Duchemin, Said Taibi

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In our present society, raw earth presents an alternative as an energy-saving building material for dealing with climate and environmental issues. Nevertheless, it has a sensitivity to water, due to the presence of fines, which has a direct effect on its consistency. This can be expressed during desiccation, by shrinkage deformations resulting in cracking that begins once the internal tensile stresses developed, due to suction, exceed the tensile strength of the material. This work deals with the evolution of the strain of clay samples, from the beginning of shrinkage until the initiation of crack, using the DIC (Digital Image Correlation) technique. In order to understand the origin of cracking, desiccation is studied for different boundary conditions and depending on the intrinsic characteristics of the material. On the other hand, a study of restrained shrinkage is carried out on the ring test to investigate the ultimate tensile strength from which the crack begins in the dough of clay. The purpose of this test is to find the type of reinforcement adapted to thwart in the cracking of the material. A microscopic analysis of the damaged area is necessary to link the macroscopic mechanisms of cracking to the various physicochemical phenomena at the microscopic scale in order to understand the different microstructural mechanisms and their impact on the macroscopic shrinkage.

Keywords: clayey soil, shrinkage, strain, cracking, digital image correlation

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Authors: David C. Ni

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Contemporary models for N-body systems are based on temporal, two-body, and mass point representation of Newtonian mechanics. Other mainstream models include 2D and 3D Ising models based on local neighborhood the lattice structures. In Quantum mechanics, the theories of collective modes are for superconductivity and for the long-range quantum entanglement. However, these models are still mainly for the specific phenomena with a set of designated parameters. We are therefore motivated to develop a new construction directly from the complex-variable N-body systems based on the extended Blaschke functions (EBF), which represent a non-temporal and nonlinear extension of Lorentz transformation on the complex plane – the normalized momentum spaces. A point on the complex plane represents a normalized state of particle momentums observed from a reference frame in the theory of special relativity. There are only two key parameters, normalized momentum and nonlinearity for modelling. An algorithm similar to Jenkins-Traub method is adopted for solving EBF iteratively. Through iteration, the solution sets show a form of σ + i [-t, t], where σ and t are the real numbers, and the [-t, t] shows various distributions, such as 1-peak, 2-peak, and 3-peak etc. distributions and some of them are analog to the canonical distributions. The results of the numerical analysis demonstrate continuum-to-discreteness transitions, evolutional invariance of distributions, phase transitions with conjugate symmetry, etc., which manifest the construction as a potential candidate for the unification of statistics. We hereby classify the observed distributions on the finite convergent domains. Continuous and discrete distributions both exist and are predictable for given partitions in different regions of parameter-pair. We further compare these distributions with canonical distributions and address the impacts on the existing applications.

Keywords: blaschke, lorentz transformation, complex variables, continuous, discrete, canonical, classification

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Authors: Muhammad Umar

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Safety and Assets management is considering a backbone of every department. GIS in the Railway become very important to Manage Assets and Security through Digital Maps and Web based GIS Maps. It provides a complete frame of work to the organization for the management of assets. Pakistan Railway is the most common and safest mode of traveling in Pakistan. Due to ever-increasing demand of transporting huge amount of information generated from various sources and this information must be accurate. This creates problems for Passengers and Administration that causes finical and time loss. GIS Solve this problem by Digital Maps & Database. It provides you a real time Spatial and Statistical analysis that helps you to communicate and exchange the information in a sophisticated way to the users. GIS Based Web system provides a facility to different end user to make query at a time as per requirements. This GIS System provides an advancement in an organization for a complete Monitoring, Safety and Decision System for tracks, Stations and Junctions that further use for the Analysis of different areas i.e. analysis of tracks, junctions and Stations in case of reconstruction, Rescue for rail accidents and Natural disasters .This Research work helps to reduce the financial loss and reduce human mistakes helps you provide a complete security and Management system of assets.

Keywords: Geographical Information System (GIS) for assets management, geo spatial database, railway assets management, Pakistan

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Authors: Ulrike Dowie, Ralph Grothmann

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Rational planning decisions are based upon forecasts. Precise forecasting has, therefore, a central role in business. The prediction of customer demand is a prime example. This paper introduces recurrent neural networks to model customer demand and combines the forecast with uncertainty measures to derive decision support of the demand planning department. It identifies and describes the keys to the successful implementation of an AI-based solution: bringing together data with business knowledge, AI methods, and user experience, and applying agile software development practices.

Keywords: agile software development, AI project success factors, deep learning, demand forecasting, forecast uncertainty, neural networks, supply chain management

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Authors: Venugopal Kummamuru

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Corporate Governance (CG) is of utmost importance for running a company ethically. It is essential for the growth and success of the corporation. It is intended to increase the accountability of an organization to the larger context of the business environment. The general principles of CG include and are related to Shareholder recognition, Stakeholder interests, and focus on Corporate Social Responsibility (CSR), Clear Board responsibilities, Ethical behavior, and Business transparency. Network Marketing Organizations (NMOs) focus on marketing through direct-sales using people who are associated with the organization but are not their employees. This paper tries to study the importance of Ethics and CSR in an NMO and suggest a basic guideline for CG in NMO(s). This paper could be used as a basis or starting point for conducting an in-depth research to understand the difference in CG practices between NMO(s) and other organizations and define a standard set of guidelines for CG practice.

Keywords: corporate governance, corporate responsibility, direct selling, network marketing

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Authors: Navid Kaboudi, Ali Shayanfar

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Introduction: Feeding infants with safe milk from the beginning of their life is an important issue. Drugs which are used by mothers can affect the composition of milk in a way that is not only unsuitable, but also toxic for infants. Consuming permeable drugs during that sensitive period by mother could lead to serious side effects to the infant. Due to the ethical restrictions of drug testing on humans, especially women, during their lactation period, computational approaches based on structural parameters could be useful. The aim of this study is to develop mechanistic models to predict the M/P ratio of drugs during breastfeeding period based on their structural descriptors. Methods: Two hundred and nine different chemicals with their M/P ratio were used in this study. All drugs were categorized into two groups based on their M/P value as Malone classification: 1: Drugs with M/P>1, which are considered as high risk 2: Drugs with M/P>1, which are considered as low risk Thirty eight chemical descriptors were calculated by ACD/labs 6.00 and Data warrior software in order to assess the penetration during breastfeeding period. Later on, four specific models based on the number of hydrogen bond acceptors, polar surface area, total surface area, and number of acidic oxygen were established for the prediction. The mentioned descriptors can predict the penetration with an acceptable accuracy. For the remaining compounds (N= 147, 158, 160, and 174 for models 1 to 4, respectively) of each model binary regression with SPSS 21 was done in order to give us a model to predict the penetration ratio of compounds. Only structural descriptors with p-value<0.1 remained in the final model. Results and discussion: Four different models based on the number of hydrogen bond acceptors, polar surface area, and total surface area were obtained in order to predict the penetration of drugs into human milk during breastfeeding period About 3-4% of milk consists of lipids, and the amount of lipid after parturition increases. Lipid soluble drugs diffuse alongside with fats from plasma to mammary glands. lipophilicity plays a vital role in predicting the penetration class of drugs during lactation period. It was shown in the logistic regression models that compounds with number of hydrogen bond acceptors, PSA and TSA above 5, 90 and 25 respectively, are less permeable to milk because they are less soluble in the amount of fats in milk. The pH of milk is acidic and due to that, basic compounds tend to be concentrated in milk than plasma while acidic compounds may consist lower concentrations in milk than plasma. Conclusion: In this study, we developed four regression-based models to predict the penetration class of drugs during the lactation period. The obtained models can lead to a higher speed in drug development process, saving energy, and costs. Milk/plasma ratio assessment of drugs requires multiple steps of animal testing, which has its own ethical issues. QSAR modeling could help scientist to reduce the amount of animal testing, and our models are also eligible to do that.

Keywords: logistic regression, breastfeeding, descriptors, penetration

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Authors: Chisomo Patrick Kumbuyo, Katsuyuki Shimizu, Hiroshi Yasuda, Yoshinobu Kitamura

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This study deals with a way of predicting Malawi rainfall from global sea surface temperature (SST) using a simple multiple regression model. Monthly rainfall data from nine stations in Malawi grouped into two zones on the basis of inter-station rainfall correlations were used in the study. Zone 1 consisted of Karonga and Nkhatabay stations, located in northern Malawi; and Zone 2 consisted of Bolero, located in northern Malawi; Kasungu, Dedza, Salima, located in central Malawi; Mangochi, Makoka and Ngabu stations located in southern Malawi. Links between Malawi rainfall and SST based on statistical correlations were evaluated and significant results selected as predictors for the regression models. The predictors for Zone 1 model were identified from the Atlantic, Indian and Pacific oceans while those for Zone 2 were identified from the Pacific Ocean. The correlation between the fit of predicted and observed rainfall values of the models were satisfactory with r=0.81 and 0.54 for Zone 1 and 2 respectively (significant at less than 99.99%). The results of the models are in agreement with other findings that suggest that SST anomalies in the Atlantic, Indian and Pacific oceans have an influence on the rainfall patterns of Southern Africa.

Keywords: Malawi rainfall, forecast model, predictors, SST

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Authors: Samir Dekali, David Crouzier

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Due to their new physico-chemical properties engineered nanoparticles (ENPs) are increasingly employed in numerous industrial sectors (such as electronics, textile, aerospace, cosmetics, pharmaceuticals, food industry, etc). These new physico-chemical properties can also represent a threat for the human health. Consumers can notably be exposed involuntarily by different routes such as inhalation, ingestion or through the skin. Several studies recently reported a possible biodistribution of these ENPs on the blood-brain barrier (BBB). Consequently, there is a great need for developing BBB in vitro models representative of the in vivo situation and capable of rapidly and accurately assessing ENPs toxic effects and their potential translocation through this barrier. In this study, several in vitro models established with micro-endothelial brain cell lines of different origins (bEnd.3 mouse cell line or a new human cell line) co-cultivated or not with astrocytic cells (C6 rat or C8-B4 mouse cell lines) on Transwells® were compared using different endpoints: trans-endothelial resistance, permeability of the Lucifer yellow and protein junction labeling. Impact of NIST diesel exhaust particles on BBB cell viability is also discussed.

Keywords: nanoparticles, blood-brain barrier, diesel exhaust particles, toxicology

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Authors: Rudainah Alkhazam, Özlem Yaşar Uğurlu

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Immigrant entrepreneurship arises from the start of entrepreneurial activity by immigrants in the country they relocate to. The future prosperity and stability of the refugee-hosting countries depends on the mutual social and economic benefits between the residents and the refugees. Syrian refugees and workers in host countries necessitate efforts to assist their residents and refugees in meeting their daily needs, contributing lawfully to local and possibly regional economies through trade, and instilling hope in their future. This study investigates the effects of Syrian refugee entrepreneurs on host communities' business sectors, focusing on Turkey. Specifically, we examine entrepreneurship in general and its role in the country's economy. Because Turkey is the most popular resettlement destination for Syrian refugees, this study will shed light on the challenges of successful migrant entrepreneurship in Turkey and their role in the business sector. The research relies on a mixed-method approach which helps identify recurring themes, favorable results, and conflicting results across methods, allowing us to draw accurate conclusions. The study will adopt a quantitative method in collecting numerical data from Syrian refugees in Turkey. The self-administered survey would be translated into Arabic to ensure that the respondents understood the questions and possible replies. The research will use survey questionnaires to gather the majority of the data. These surveys would have closed-ended questions with nominal ratio and Likert scales. The data will be analyzed using linear regression and the Statistical Package for Social Sciences (SPSS) to ascertain the role of Syrian entrepreneurs in the business sectors of Turkey. The research will use the findings to make future recommendations. Syrian entrepreneurs, among the migrant entrepreneurs, contribute to the labor market, the majority of whom are young people. This research noted the significant participation of Syrian immigrant women in the entrepreneurship sector. The previous experience of Syrians in the field of trade and running their own business plays a vital role in the success of their business in the host countries. The study shows that Syrian entrepreneurs could integrate effectively into the various Turkish business sectors and could rely on themselves, open and manage their projects, and market them in the Turkish market. Syrian entrepreneurs consider that the investment and labor laws, commercial arrangements, and facilities for obtaining financial resources in Turkey need to be more flexible and available to immigrant entrepreneurs.

Keywords: entrepreneurship, immigration, Syrian, Turkey, refugees, investors, socio-economic benefits, unemployment

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Authors: R. Manjula, Kaustav Bagchi, Sushant Ramesh, Anush Baskaran

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In the past century, the emergence of information technology has had a significant positive impact on human life. While companies tend to be more involved in the completion of projects, the turn of the century has seen importance being given to investment in information security policies. These policies are essential to protect important data from adversaries, and thus following these policies has become one of the most important attributes revolving around information security models. In this research, we have focussed on the factors affecting information security policy compliance in two models : The theory of planned behaviour and the integration of the social bond theory and the involvement theory into a single model. Finally, we have given a proposal of where these theories would be successful.

Keywords: information technology, information security, involvement theory, policies, social bond theory

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Authors: Yanshuang Zhang, Byungho Jeong

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There exists some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in calculating efficiency of decision making units (DMU). Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. This problem can be resolved a super-efficiency model. However, a super efficiency model sometimes causes infeasibility problem. This paper suggests an output oriented super-efficiency model for efficiency evaluation under the consideration of time lag effect. A case example using a long term research project is given to compare the suggested model with the MpO model

Keywords: DEA, Super-efficiency, Time Lag, research activities

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Authors: Bahram Fathi, Karim Alizadeh, Azam Mohammadbagheri

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The aim of this paper is to investigate the role of oil price shocks in explaining business cycles in Iran using a dynamic stochastic general equilibrium approach. This model incorporates both productivity and oil revenue shocks. The results indicate that productivity shocks are relatively more important to business cycles than oil shocks. The model with two shocks produces different values for volatility, but these values have the same ranking as that of the actual data for most variables. In addition, the actual data are close to the ratio of standard deviations to the output obtained from the model with two shocks. The results indicate that productivity shocks are relatively more important to business cycles than the oil shocks. The model with only a productivity shock produces the most similar figures in term of volatility magnitude to that of the actual data. Next, we use the Impulse Response Functions (IRF) to evaluate the capability of the model. The IRF shows no effect of an oil shock on the capital stocks and on labor hours, which is a feature of the model. When the log-linearized system of equations is solved numerically, investment and labor hours were not found to be functions of the oil shock. This research recommends using different techniques to compare the model’s robustness. One method by which to do this is to have all decision variables as a function of the oil shock by inducing the stationary to the model differently. Another method is to impose a bond adjustment cost. This study intends to fill that gap. To achieve this objective, we derive a DSGE model that allows for the world oil price and productivity shocks. Second, we calibrate the model to the Iran economy. Next, we compare the moments from the theoretical model with both single and multiple shocks with that obtained from the actual data to see the extent to which business cycles in Iran can be explained by total oil revenue shock. Then, we use an impulse response function to evaluate the role of world oil price shocks. Finally, I present implications of the findings and interpretations in accordance with economic theory.

Keywords: oil price, shocks, dynamic stochastic general equilibrium, Iran

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Authors: Genady Grabarnik, Serge Yaskolko

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Generative Artificial Intelligence (AI) has significantly expanded its applicability with the incorporation of Large Language Models (LLMs) and become a technology with promise to automate some areas that were very difficult to automate before. The paper describes the introduction of generative Artificial Intelligence into Introductory Computer and Data Science courses and analysis of effect of such introduction. The generative Artificial Intelligence is incorporated in the educational process two-fold: For the instructors, we create templates of prompts for generation of tasks, and grading of the students work, including feedback on the submitted assignments. For the students, we introduce them to basic prompt engineering, which in turn will be used for generation of test cases based on description of the problems, generating code snippets for the single block complexity programming, and partitioning into such blocks of an average size complexity programming. The above-mentioned classes are run using Large Language Models, and feedback from instructors and students and courses’ outcomes are collected. The analysis shows statistically significant positive effect and preference of both stakeholders.

Keywords: introductory computer and data science education, generative AI, large language models, application of LLMS to computer and data science education

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Authors: Amirreza Razzaghipour Sorkhab

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Hearing loss is one of the greatest common chronic health situations of older people. Hearing aids are the common treatment, and they recover the quality of life in older adults. Even so, comparatively few older adults with simple, mild to moderate, adult-onset, sensorineural hearing loss use hearing aids. It shouldn’t be expected that more expensive hearing aids always produce better outcomes. Given the importance of quality pledge, approaches of quantifying hearing aid fitting achievement are needed. Studies showed an important reduction in handicap following 3 weeks of hearing aid use, signifying the feasibility of using the Hearing Hindrance Inventory for the Elderly as an outcome measure for hearing aid success after a brief interval of hearing aid use. The results showed important development of the quality of life after three months of using a hearing aid in all members and improvement of their most important problems, i.e., the communication and exchange of data. Hearing loss can impair the conversation of information and so decreases the quality of life. Hearing aids have progressivemeaningfully over the past decade, chiefly due to the growing of digital technology. The next decade should see an even greater number of innovations to hearing aid technology. Development in digital hearing aids will be driven by investigate advances in the next fields such as wireless technology, hearing science, and cognitive scienceMoreover, emerging trends such as connectivity and individuation will also drive new technology. We hope that the advancement of technology will be enough to meet the needs of people with hearing aids.

Keywords: hearing loss, hearing aid, hearing aid technology, health

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Authors: Vera G. Dianova, Lori P. Montross, Charles M. Burke

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In the digital age, the widespread and frequently excessive use of mobile phones amongst university students is recognized as a significant distractor which interferes with their ability to enter a deep state of concentration during studies and diminishes their prospects of experiencing the enjoyable and instrumental state of flow, as defined and described by psychologist M. Csikszentmihalyi. This study has targeted 50 university students with the aim of teaching them to cultivate their ability to engage in deep work and to attain the state of flow, fostering more effective and enjoyable learning experiences. Prior to the start of the intervention, all participating students completed a comprehensive survey based on a variety of validated scales assessing their inclination toward lifelong learning, frequency of flow experiences during study, frustration tolerance, sense of agency, as well as their love of learning and daily time devoted to non-academic mobile phone activities. Several days after this initial assessment, students received a 90-minute lecture on the principles of flow and deep work, accompanied by a critical discourse on the detrimental effects of excessive mobile phone usage. They were encouraged to practice deep work and strive for frequent flow states throughout the semester. Subsequently, students submitted weekly surveys, including the 10-item CORE Dispositional Flow Scale, a 3-item agency scale and furthermore disclosed their average daily hours spent on non-academic mobile phone usage. As a final step, at the end of the semester students engaged in reflective report writing, sharing their experiences and evaluating the intervention's effectiveness. They considered alterations in their love of learning, reflected on the implications of their mobile phone usage, contemplated improvements in their tolerance for boredom and perseverance in complex tasks, and pondered the concept of lifelong learning. Additionally, students assessed whether they actively took steps towards managing their recreational phone usage and towards improving their commitment to becoming lifelong learners. Employing a mixed-methods approach our study offers insights into the dynamics of concentration, flow, mobile phone usage and attitudes towards learning among undergraduate and graduate university students. The findings of this study aim to promote profound contemplation, on the part of both students and instructors, on the rapidly evolving digital-age higher education environment. In an era defined by digital and AI advancements, the ability to concentrate, to experience the state of flow, and to love learning has never been more crucial. This study underscores the significance of addressing mobile phone distractions and providing strategies for cultivating deep concentration. The insights gained can guide educators in shaping effective learning strategies for the digital age. By nurturing a love for learning and encouraging lifelong learning, educational institutions can better prepare students for a rapidly changing labor market, where adaptability and continuous learning are paramount for success in a dynamic career landscape.

Keywords: deep work, flow, higher education, lifelong learning, love of learning

Procedia PDF Downloads 63

Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

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This paper discusses on power spectral density (PSD) characteristics which are extracted from three-dimensional (3D) electroencephalogram (EEG) models. The EEG signal recording was conducted on 150 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, the values of maximum PSD were extracted as features from the model. These features are analysed using mean relative power (MRP) and different mean relative power (DMRP) technique to observe the pattern among different brain balancing indexes. The results showed that by implementing these techniques, the pattern of brain balancing indexes can be clearly observed. Some patterns are indicates between index 1 to index 5 for left frontal (LF) and right frontal (RF).

Keywords: power spectral density, 3D EEG model, brain balancing, mean relative power, different mean relative power

Procedia PDF Downloads 467

Authors: Vladimir Simovic, Matija Varga, Tonco Marusic

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This research paper shows matrix technology models and examples of information systems in education (in the Republic of Croatia and in the Germany) in support of business, education (when learning and teaching) and e-learning. Here we researched and described the aims and objectives of the main process in education and technology, with main matrix classes of data. In this paper, we have example of matrix technology with detailed description of processes related to specific data classes in the processes of education and an example module that is support for the process: ‘Filling in the directory and the diary of work’ and ‘evaluation’. Also, on the lower level of the processes, we researched and described all activities which take place within the lower process in education. We researched and described the characteristics and functioning of modules: ‘Fill the directory and the diary of work’ and ‘evaluation’. For the analysis of the affinity between the aforementioned processes and/or sub-process we used our application model created in Visual Basic, which was based on the algorithm for analyzing the affinity between the observed processes and/or sub-processes.

Keywords: designing, education management, information systems, matrix technology, process affinity

Procedia PDF Downloads 435

Authors: Ankur Bansal, Shashank Bishnoi

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Degradation of Sewage pipes, sewage pumping station and Sewage treatment plants(STP) is of major concern due to difficulty in their maintenance and the high cost of replacement. Most of these systems undergo degradation due to Biogenic sulphuric acid (BSA) attack. Since most of Waste water treatment system are underground, detection of this deterioration remains hidden. This paper presents a literature review, outlining the mechanism of this attack focusing on critical parameters of BSA attack, along with available models and software to predict the deterioration due to this attack. This paper critically examines the various steps and equation in various Models of BSA degradation, detail on assumptions and working of different softwares are also highlighted in this paper. The paper also focuses on the service life design technique available through various codes and method to integrate the servile life design with BSA degradation on concrete. In the end, various methods enhancing the resistance of concrete against Biogenic sulphuric acid attack are highlighted. It may be concluded that the effective modelling for degradation phenomena may bring positive economical and environmental impacts. With current computing capabilities integrated degradation models combining the various durability aspects can bring positive change for sustainable society.

Keywords: concrete degradation, modelling, service life, sulphuric acid attack

Procedia PDF Downloads 305

Authors: Bharatendra Rai

Abstract:

Cutting tools are widely used in manufacturing processes and drilling is the most commonly used machining process. Although drill-bits used in drilling may not be expensive, their breakage can cause damage to expensive work piece being drilled and at the same time has major impact on productivity. Predicting drill-bit breakage, therefore, is important in reducing cost and improving productivity. This study uses twenty features extracted from two degradation signals viz., thrust force and torque. The methodology used involves developing and comparing decision tree, random forest, and multinomial logistic regression models for classifying and predicting drill-bit breakage using degradation signals.

Keywords: degradation signal, drill-bit breakage, random forest, multinomial logistic regression

Procedia PDF Downloads 347