Search results for: researchers

Authors: Lana Whiskeyjack, Kyle Napier

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The Spirit of the language embodies the motivation for indigenous people to connect with the indigenous language of their lineage. While the concept of the spirit of the language is often woven into the discussion by indigenous language revitalizationists, particularly those who are indigenous, there are few tangible terms in academic research conceptually actualizing the term. Through collaborative work with indigenous language speakers, elders, and learners, this research sets out to identify the spirit of the language, the catalysts of disconnection from the spirit of the language, and the sources of reconnection to the spirit of the language. This work fundamentally addresses the terms of engagement around collaboration with indigenous communities, itself inviting a decolonial approach to community outreach and individual relationships. As indigenous researchers, this means beginning, maintain, and closing this work in the ceremony while being transparent with community members in this work and related publishing throughout the project’s duration. Decolonizing this approach also requires maintaining explicit ongoing consent by the elders, knowledge keepers, and community members when handling their ancestral and indigenous knowledge. The handling of this knowledge is regarded in this work as stewardship, both in the handling of digital materials and the handling of ancestral Indigenous knowledge. This work observes recorded conversations in both nêhiyawêwin and English, resulting from 10 semi-structured interviews with fluent nêhiyawêwin speakers as well as three structured dialogue circles with fluent and emerging speakers. The words were transcribed by a speaker fluent in both nêhiyawêwin and English. The results of those interviews were categorized thematically to conceptually actualize the spirit of the language, catalysts of disconnection to thespirit of the language, and community voices methods of reconnection to the spirit of the language. Results of these interviews vastly determine that the spirit of the language is drawn from the land. Although nêhiyawêwin is the focus of this work, Indigenous languages are by nature inherently related to the land. This is further reaffirmed by the Indigenous language learners and speakers who expressed having ancestries and lineages from multiple Indigenous communities. Several other key differences embody this spirit of the language, which include ceremony and spirituality, as well as the semantic worldviews tied to polysynthetic verb-oriented morphophonemics most often found in indigenous languages — and of focus, nêhiyawêwin. The catalysts of disconnection to the spirit of the language are those whose histories have severed connections between Indigenous Peoples and the spirit of their languages or those that have affected relationships with the land, ceremony, and ways of thinking. Results of this research and its literature review have determined the three most ubiquitously damaging interdependent factors, which are catalysts of disconnection from the spirit of the language as colonization, capitalism, and Christianity. As voiced by the Indigenous language learners, this work necessitates addressing means to reconnect to the spirit of the language. Interviewees mentioned that the process of reconnection involves a whole relationship with the land, the practice of reciprocal-relational methodologies for language learning, and indigenous-protected and -governed learning. This work concludes in support of those reconnection methodologies.

Keywords: indigenous language acquisition, indigenous language reclamation, indigenous language revitalization, nêhiyawêwin, spirit of the language

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Authors: Ayanda P. Deliwe, Storm B. Watson

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The COVID-19 pandemic has disrupted the established practices of higher education institutions (HEIs). Most higher education institutions worldwide had to shift from traditional face-to-face to online learning. The online environment and new online tools are disrupting the way in which higher education is presented. Furthermore, the structures of higher education institutions have been impacted by rapid advancements in information and communication technologies. Emerging technologies should not be viewed in a negative light because, as opposed to the traditional curriculum that worked to create productive and efficient researchers, emerging technologies encourage creativity and innovation. Therefore, using technology together with traditional means will enhance teaching and learning. Emerging technologies in higher education not only change the experience of students, lecturers, and the content, but it is also influencing the attraction and retention of students. Higher education institutions are under immense pressure because not only are they competing locally and nationally, but emerging technologies also expand the competition internationally. Emerging technologies have eliminated border barriers, allowing students to study in the country of their choice regardless of where they are in the world. Higher education institutions are becoming indifferent as technology is finding its way into the lecture room day by day. Academics need to utilise technology at their disposal if they want to get through to their students. Academics are now competing for students' attention with social media platforms such as WhatsApp, Snapchat, Instagram, Facebook, TikTok, and others. This is posing a significant challenge to higher education institutions. It is, therefore, critical to pay attention to emerging technologies in order to see how they can be incorporated into the classroom in order to improve educational quality while remaining relevant in the work industry. This study aims to understand how emerging technologies have been utilised at Nelson Mandela University in presenting teaching and learning activities since April 2020. The primary objective of this study is to analyse how academics are incorporating emerging technologies in their teaching and learning activities. This primary objective was achieved by conducting a literature review on clarifying and conceptualising the emerging technologies being utilised by higher education institutions, reviewing and analysing the use of emerging technologies, and will further be investigated through an empirical analysis of the use of emerging technologies at Nelson Mandela University. Findings from the literature review revealed that emerging technology is impacting several key areas in higher education institutions, such as the attraction and retention of students, enhancement of teaching and learning, increase in global competition, elimination of border barriers, and highlighting the digital divide. The literature review further identified that learning management systems, open educational resources, learning analytics, and artificial intelligence are the most prevalent emerging technologies being used in higher education institutions. The identified emerging technologies will be further analysed through an empirical analysis to identify how they are being utilised at Nelson Mandela University.

Keywords: artificial intelligence, emerging technologies, learning analytics, learner management systems, open educational resources

Procedia PDF Downloads 48

Authors: Robertson Freeman

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The prime objective of this research is to examine income inequality and its effects on household livelihoods in Parker Paint. Many researchers failed to address the potential threat of income inequality on diverse household livelihood indicators, including health, food, housing, transport and many others. They examine and generalize the effects of income differentials on household livelihoods by addressing one indicator of livelihood security. This research fills the loopholes of previous research by examining the effects of income inequality and how it affects the livelihoods of households, taking into consideration livelihood indicators including health, food security, and transport. The researcher employed the mixed research method to analyze the distribution of income and solicit opinions of household heads on the effects of their monthly income on their livelihoods. Age and sex structure, household composition, type of employment and educational status influence income inequality. The level of income, Lorenz curve and the Gini coefficient was mutually employed to calculate and determine the level of income inequality. One hundred eighty-two representing 96% of household heads are employed while 8, representing 4%, are unemployed. However, out of a total number of 182 employed, representing 96%, 27 people representing 14%, are employed in the formal private sector, while 110, representing 58%, are employed in the private informal sector. Monthly average income, savings, investments and unexpected circumstances affect the livelihood of households. Infrastructural development and wellbeing should be pursued by reducing expenditure earmarked in other sectors and channeling the funds towards the provision of household needs. One of the potent tools for consolidating household livelihoods is to initiate livelihood empowerment programs. Government and private sector agencies should establish more health insurance schemes, providing mosquito nets, immunization services, public transport, as well as embarking on feeding programs, especially in the remote areas of Parker paint. To climax the research findings, self-employment, entrepreneurship and the general private sector employment is a transparent double-edged sword. If employed in the private sector, there is the likelihood to increase one’s income. However, this also induces the income gap between the rich and poor since many people are exploited by affluence, thereby relegating the poor from the wealth hierarchy. Age and sex structure, as well as type of employment, should not be overlooked since they all play fundamental roles in influencing income inequality. Savings and investments seem to play a positive role in reducing income inequality. However, savings and investment in this research affect livelihoods negatively. It behooves mankind to strive and work hard to the best of ability in earning sufficient income and embracing measures to retain his financial strength. In so doing, people will be able to provide basic household needs, celebrate the reduction in unemployment and dependence and finally ensure sustainable livelihoods.

Keywords: income, inequality, livelihood, pakerpaint

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Authors: Mehmet Oren, Susan Pedersen, Sevket C. Cetin

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Despite the frequently criticized disadvantages of the traditional used paper and pencil assessment, it is the most frequently used method in our schools. Although assessments do an acceptable measurement, they are not capable of measuring all the aspects and the richness of learning and knowledge. Also, many assessments used in schools decontextualize the assessment from the learning, and they focus on learners’ standing on a particular topic but do not concentrate on how student learning changes over time. For these reasons, many scholars advocate that using simulations and games (S&G) as a tool for assessment has significant potentials to overcome the problems in traditionally used methods. S&G can benefit from the change in technology and provide a contextualized medium for assessment and teaching. Furthermore, S&G can serve as an instructional tool rather than a method to test students’ learning at a particular time point. To investigate the potentials of using educational games as an assessment and teaching tool, this study presents the implementation and the validation of an automated embedded assessment (AEA), which can constantly monitor student learning in the game and assess their performance without intervening their learning. The experiment was conducted on an undergraduate level engineering course (Digital Circuit Design) with 99 participant students over a period of five weeks in Spring 2016 school semester. The purpose of this research study is to examine if the proposed method of AEA is valid to assess student learning in a 3D Educational game and present the implementation steps. To address this question, this study inspects three aspects of the AEA for the validation. First, the evidence-centered design model was used to lay out the design and measurement steps of the assessment. Then, a confirmatory factor analysis was conducted to test if the assessment can measure the targeted latent constructs. Finally, the scores of the assessment were compared with an external measure (a validated test measuring student learning on digital circuit design) to evaluate the convergent validity of the assessment. The results of the confirmatory factor analysis showed that the fit of the model with three latent factors with one higher order factor was acceptable (RMSEA < 0.00, CFI =1, TLI=1.013, WRMR=0.390). All of the observed variables significantly loaded to the latent factors in the latent factor model. In the second analysis, a multiple regression analysis was used to test if the external measure significantly predicts students’ performance in the game. The results of the regression indicated the two predictors explained 36.3% of the variance (R2=.36, F(2,96)=27.42.56, p<.00). It was found that students’ posttest scores significantly predicted game performance (β = .60, p < .000). The statistical results of the analyses show that the AEA can distinctly measure three major components of the digital circuit design course. It was aimed that this study can help researchers understand how to design an AEA, and showcase an implementation by providing an example methodology to validate this type of assessment.

Keywords: educational video games, automated embedded assessment, assessment validation, game-based assessment, assessment design

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Authors: Omwoyo Bosire Onyancha

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The Journal Citation Reports (JCR) of the Thomson Reuters has, for decades, provided the data for bibliometrically assessing the impact of journals. In their criticism of the journal impact factor (JIF), a number of scholars such as Priem, Taraborelli, Groth and Neylon (2010) observe that the “JIF is often incorrectly used to assess the impact of individual articles. It is troubling that the exact details of the JIF are a trade secret, and that significant gaming is relatively easy”. The emergence of alternative metrics (Altmetrics) has introduced another dimension of re-assessing how the impact of journals (and other units such as articles and even individual researchers) can be measured. Altmetrics is premised upon the fact that research is increasingly being disseminated through social network sites such as ResearchGate, Mendeley, Twitter, Facebook, LinkedIn, and ImpactStory, among others. This paper adopts informetrics (including altmetrics) techniques to report on the findings of a study conducted to investigate and compare the social media impact of 274 South Africa Post Secondary Education (SAPSE)-accredited journals, which are recognized and accredited by the Department of Higher Education and Training (DHET) of South Africa (SA). We used multiple sources to extract data for the study, namely Altmetric.com and the Thomson Reuters’ Journal Citation Reports. Data was analyzed in order to determine South African journals’ presence and impact on social media as well as contrast the social media impact with Thomson Reuters’ citation impact. The Spearman correlation test was performed to compare the journals’ social media impact and JCR citation impact. Preliminary findings reveal that a total of 6360 articles published in 96 South African journals have received some attention in social media; the most commonly used social media platform was Twitter, followed by Mendeley, Facebook, News outlets, and CiteULike; there were 29 SA journals covered in the JCR in 2008 and this number has grown to 53 journals in 2014; the journals indexed in the Thomson Reuters performed much better, in terms of their altmetrics, than those journals that are not indexed in Thomson Reuters databases; nevertheless, there was high correlation among journals that featured in both datasets; the journals with the highest scores in Altmetric.com included the South African Medical Journal, African Journal of Marine Science, and Transactions of the Royal Society of South Africa while the journals with high impact factors in JCR were South African Medical Journal, Onderstepoort: Journal of Veterinary Research, and Sahara: Journal of Social Aspects of HIV-AIDS; and that Twitter has emerged as a strong avenue of sharing and communicating research published in the South African journals. Implications of the results of the study for the dissemination of research conducted in South Africa are offered. Discussions based on the research findings as well as conclusions and recommendations are offered in the full text paper.

Keywords: altmetrics, citation impact, journal citation reports, journal impact factor, journals, research, scholarly publishing, social media impact, South Africa

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Authors: Pulkeria Pascoe, Hawa P. Tundui, Marcia Dutra de Barcellos, Hans de Steur, Xavier Gellynck

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A majority of Micro and Small Enterprises (MSEs) experience low or no growth. Understanding their performance remains unfinished and disjointed as there is no consensus on the factors influencing it, especially in developing countries. Using a Resource-Based View (RBV) as the theoretical background, this cross-sectional study employed four regression models to examine the influence of firm-level factors (firm-specific characteristics, firm resources, manager socio-demographic characteristics, and selected management practices) on the overall performance variations among 442 Tanzanian micro and small agri-food processing firms. Study results confirmed the RBV argument that intangible resources make a larger contribution to overall performance variations among firms than that tangible resources. Firms' tangible and intangible resources explained 34.5% of overall performance variations (intangible resources explained the overall performance variability by 19.4% compared to tangible resources, which accounted for 15.1%), ranking first in explaining the overall performance variance. Firm-specific characteristics ranked second by influencing variations in overall performance by 29.0%. Selected management practices ranked third (6.3%), while the manager's socio-demographic factors were last on the list, as they influenced the overall performance variability among firms by only 5.1%. The study also found that firms that focus on proper utilization of tangible resources (financial and physical), set targets, and undertake better working capital management practices performed higher than their counterparts (low and average performers). Furthermore, accumulation and proper utilization of intangible resources (relational, organizational, and reputational), undertaking performance monitoring practices, age of the manager, and the choice of the firm location and activity were the dominant significant factors influencing the variations among average and high performers, relative to low performers. The entrepreneurial background was a significant factor influencing variations in average and low-performing firms, indicating that entrepreneurial skills are crucial to achieving average levels of performance. Firm age, size, legal status, source of start-up capital, gender, education level, and total business experience of the manager were not statistically significant variables influencing the overall performance variations among the agri-food processors under the study. The study has identified both significant and non-significant factors influencing performance variations among low, average, and high-performing micro and small agri-food processing firms in Tanzania. Therefore, results from this study will help managers, policymakers and researchers to identify areas where more attention should be placed in order to improve overall performance of MSEs in agri-food industry.

Keywords: firm-level factors, micro and small enterprises, performance, regression analysis, resource-based-view

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Authors: Tobias Milz, L. Macpherson, Varvara Vetrova

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The law is a fundamental pillar of human societies as it shapes, controls and governs how humans conduct business, behave and interact with each other. Recent advances in computer-assisted technologies such as NLP, data science and AI are creating opportunities to support the practice, research and study of this pervasive domain. It is therefore not surprising that there has been an increase in investments into supporting technologies for the legal industry (also known as “legal tech” or “law tech”) over the last decade. A sub-discipline of particular appeal is concerned with assisted legal research. Supporting law researchers and practitioners to retrieve information from the vast amount of ever-growing legal documentation is of natural interest to the legal research community. One tool that has been in use for this purpose since the early nineteenth century is legal citation indexing. Among other use cases, they provided an effective means to discover new precedent cases. Nowadays, computer-assisted network analysis tools can allow for new and more efficient ways to reveal the “hidden” information that is conveyed through citation behavior. Unfortunately, access to openly available legal data is still lacking in New Zealand and access to such networks is only commercially available via providers such as LexisNexis. Consequently, there is a need to create, analyze and provide a legal citation network with sufficient data to support legal research tasks. This paper describes the development and analysis of a legal citation Network for New Zealand containing over 300.000 decisions from 125 different courts of all areas of law and jurisdiction. Using python, the authors assembled web crawlers, scrapers and an OCR pipeline to collect and convert court decisions from openly available sources such as NZLII into uniform and machine-readable text. This facilitated the use of regular expressions to identify references to other court decisions from within the decision text. The data was then imported into a graph-based database (Neo4j) with the courts and their respective cases represented as nodes and the extracted citations as links. Furthermore, additional links between courts of connected cases were added to indicate an indirect citation between the courts. Neo4j, as a graph-based database, allows efficient querying and use of network algorithms such as PageRank to reveal the most influential/most cited courts and court decisions over time. This paper shows that the in-degree distribution of the New Zealand legal citation network resembles a power-law distribution, which indicates a possible scale-free behavior of the network. This is in line with findings of the respective citation networks of the U.S. Supreme Court, Austria and Germany. The authors of this paper provide the database as an openly available data source to support further legal research. The decision texts can be exported from the database to be used for NLP-related legal research, while the network can be used for in-depth analysis. For example, users of the database can specify the network algorithms and metrics to only include specific courts to filter the results to the area of law of interest.

Keywords: case citation network, citation analysis, network analysis, Neo4j

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Authors: Mahesh Vishwakarma, Sadhana Vishwakarma

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Vocational education includes all kind of education which can help students to acquire skills related to a certain profession, art, or activity so that they are able to exercise that profession, art or activity after acquiring such qualification. However, in this global economy of the modern world, job seekers are expected to have certain soft skills over and above the technical knowledge and skills acquired in their areas of expertise. These soft skills include but not limited to interpersonal communication, understanding, personal attributes, problem-solving, working in team, quick adaptability to the workplace environment, and other. Not only the hands-on, job-related skills, and competencies are now being sought by the employers, but also a complex of attitudinal dispositions and affective traits are being looked by them in their prospective employees. This study was performed to identify the employability skills of technical students from an Industrial Training Centre (ITC) in central India. It also aimed to convey a message to the students currently on the role, that for them to remain relevant in the job market, they would need to constantly adapt to changes and evolving requirements in the work environment, including the use of updated technologies. Five hypotheses were formulated and tested on the employability skills of students as a function of gender, trade, work experience, personal attributes, and IT skills. Data were gathered with the help of center’s training officers who approached 200 recently graduated students from the center and administered the instrument to students. All 200 respondents returned the completed instrument. The instrument used for the study consisted of 2 sections; demographic details and employability skills. To measure the employability skills of the trainees, the instrument was developed by referring to the several instruments developed by the past researchers for similar studies. The 1st section of the instrument of demographic details recorded age, gender, trade, year of passing, interviews faced, and employment status of the respondents. The 2nd section of the instrument on employability skills was categorized into seven specific skills: basic vocational skills; personal attributes; imagination skills; optimal management of resources; information-technology skills; interpersonal skills; adapting to new technologies. The reliability and validity of the instrument were checked. The findings revealed valuable information on the relationship and interdependence of vocational education and employability skills of students in the central Indian scenario. The findings revealed a valuable information on supplementing the existing vocational education programs with few soft skills and competencies so as to develop a superior workforce much better equipped to face the job market. The findings of the study can be used as an example by the management of government and private industrial training centers operating in the other parts of the Asian region. Future research can be undertaken on a greater population base from different geographical regions and backgrounds for an enhanced outcome.

Keywords: employability skills, vocational education, industrial training centers, students

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Authors: Ambali Alade Odebowale, Andargachew Mekonnen Berhe, Haroldo T. Hattori, Andrey E. Miroshnichenko

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Solar thermophotovoltaic systems (STPV) have emerged as a promising solution to overcome the Shockley-Queisser limit, a significant impediment in the direct conversion of solar radiation into electricity using conventional solar cells. The STPV system comprises essential components such as an optical concentrator, selective emitter, and a thermophotovoltaic (TPV) cell. The pivotal element in achieving high efficiency in an STPV system lies in the design of a spectrally selective emitter or absorber. Traditional methods for designing and optimizing selective emitters are often time-consuming and may not yield highly selective emitters, posing a challenge to the overall system performance. In recent years, the application of machine learning techniques in various scientific disciplines has demonstrated significant advantages. This paper proposes a novel nanostructure composed of four-layered materials (SiC/W/SiO2/W) to function as a selective emitter in the energy conversion process of an STPV system. Unlike conventional approaches widely adopted by researchers, this study employs a machine learning-based approach for the design and optimization of the selective emitter. Specifically, a random forest algorithm (RFA) is employed for the design of the selective emitter, while the optimization process is executed using genetic algorithms. This innovative methodology holds promise in addressing the challenges posed by traditional methods, offering a more efficient and streamlined approach to selective emitter design. The utilization of a machine learning approach brings several advantages to the design and optimization of a selective emitter within the STPV system. Machine learning algorithms, such as the random forest algorithm, have the capability to analyze complex datasets and identify intricate patterns that may not be apparent through traditional methods. This allows for a more comprehensive exploration of the design space, potentially leading to highly efficient emitter configurations. Moreover, the application of genetic algorithms in the optimization process enhances the adaptability and efficiency of the overall system. Genetic algorithms mimic the principles of natural selection, enabling the exploration of a diverse range of emitter configurations and facilitating the identification of optimal solutions. This not only accelerates the design and optimization process but also increases the likelihood of discovering configurations that exhibit superior performance compared to traditional methods. In conclusion, the integration of machine learning techniques in the design and optimization of a selective emitter for solar thermophotovoltaic systems represents a groundbreaking approach. This innovative methodology not only addresses the limitations of traditional methods but also holds the potential to significantly improve the overall performance of STPV systems, paving the way for enhanced solar energy conversion efficiency.

Keywords: emitter, genetic algorithm, radiation, random forest, thermophotovoltaic

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Authors: Afsheen Aman, Zainab Bibi, Shah Ali Ul Qader

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Introduction: Xylan is a heteropolysaccharide composed of xylose monomers linked together through 1,4 linkages within a complex xylan network. Owing to wide applications of xylan hydrolytic products (xylose, xylobiose and xylooligosaccharide) the researchers are focusing towards the development of various strategies for efficient xylan degradation. One of the most important strategies focused is the use of heat tolerant biocatalysts which acts as strong and specific cleaving agents. Therefore, the exploration of microbial pool from extremely diversified ecosystem is considerably vital. Microbial populations from extreme habitats are keenly explored for the isolation of thermophilic entities. These thermozymes usually demonstrate fast hydrolytic rate, can produce high yields of product and are less prone to microbial contamination. Another possibility of degrading xylan continuously is the use of immobilization technique. The current work is an effort to merge both the positive aspects of thermozyme and immobilization technique. Methodology: Geobacillus stearothermophilus was isolated from soil sample collected near the blast furnace site. This thermophile is capable of producing thermostable endo-β-1,4-xylanase which cleaves xylan effectively. In the current study, this thermozyme was immobilized within a synthetic and a non-synthetic matrice for continuous production of metabolites using entrapment technique. The kinetic parameters of the free and immobilized enzyme were studied. For this purpose calcium alginate and polyacrylamide beads were prepared. Results: For the synthesis of immobilized beads, sodium alginate (40.0 gL-1) and calcium chloride (0.4 M) was used amalgamated. The temperature (50°C) and pH (7.0) optima of immobilized enzyme remained same for xylan hydrolysis however, the enzyme-substrate catalytic reaction time raised from 5.0 to 30.0 minutes as compared to free counterpart. Diffusion limit of high molecular weight xylan (corncob) caused a decline in Vmax of immobilized enzyme from 4773 to 203.7 U min-1 whereas, Km value increased from 0.5074 to 0.5722 mg ml-1 with reference to free enzyme. Immobilized endo-β-1,4-xylanase showed its stability at high temperatures as compared to free enzyme. It retained 18% and 9% residual activity at 70°C and 80°C, respectively whereas; free enzyme completely lost its activity at both temperatures. The Immobilized thermozyme displayed sufficient recycling efficiency and can be reused up to five reaction cycles, indicating that this enzyme can be a plausible candidate in paper processing industry. Conclusion: This thermozyme showed better immobilization yield and operational stability with the purpose of hydrolyzing the high molecular weight xylan. However, the enzyme immobilization properties can be improved further by immobilizing it on different supports for industrial purpose.

Keywords: immobilization, reusability, thermozymes, xylanase

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Authors: Rohini Sharma, Chandan Kumar Sahoo, Rama Krishna Gupta Potnuru

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Strong competitive forces and requirements to achieve efficiency are forcing the organizations to realize the necessity and inevitability of change. What's more, the trend does not appear to be abating. Researchers have estimated that about two thirds of change project fails. Empirical evidences further shows that organizations invest significantly in the planned change but people side is accounted for in a token or instrumental way, which is identified as one of the important reason, why change endeavours fail. However, whatever be the reason for change, organizational change readiness must be gauged prior to the institutionalization of organizational change. Hence, in this study the influence of employee voice and employee involvement on organizational change readiness via commitment-to-change is examined, as it is an area yet to be extensively studied. Also, though a recent study has investigated the interrelationship between leadership, organizational change readiness and commitment to change, our study further examined these constructs in relation with employee voice and employee involvement that plays a consequential role for organizational change readiness. Further, integrated conceptual model weaving varied concepts relating to organizational readiness with focus on commitment to change as mediator was found to be an area, which required more theorizing and empirical validation, and this study rooted in an Indian public sector organization is a step in this direction. Data for the study were collected through a survey among employees of Rourkela Steel Plant (RSP), a unit of Steel Authority of India Limited (SAIL); the first integrated Steel Plant in the public sector in India, for which stratified random sampling method was adopted. The schedule was distributed to around 700 employees, out of which 516 complete responses were obtained. The pre-validated scales were used for the study. All the variables in the study were measured on a five-point Likert scale ranging from “strongly disagree (1)” to “strongly agree (5)”. Structural equation modeling (SEM) using AMOS 22 was used to examine the hypothesized model, which offers a simultaneous test of an entire system of variables in a model. The study results shows that inter-relationship between employee voice and commitment-to-change, employee involvement and commitment-to-change and commitment-to-change and organizational change readiness were significant. To test the mediation hypotheses, Baron and Kenny’s technique was used. Examination of direct and mediated effect of mediators confirmed that commitment-to-change partially mediated the relation between employee involvement and organizational change readiness. Furthermore, study results also affirmed that commitment-to-change does not mediate the relation between employee involvement and organizational change readiness. The empirical exploration therefore establishes that it is important to harness employee’s valuable suggestions regarding change for building organizational change readiness. Regarding employee involvement, it was found that sharing information and involving people in decision-making, leads to a creation of participative climate, which educes employee commitment during change and commitment-to-change further, fosters organizational change readiness.

Keywords: commitment-to-change, change management, employee voice, employee involvement, organizational change readiness

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Authors: Konstantinos Kottikas, Vlasis Stathakopoulos, Ioannis G. Theodorakis, Efthymia Kottika

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Theorists have argued that Market Orientation is comprised of two facets, namely the Market Driven and the Market Driving components. The present theoretical paper centers on the latter, which to date has been notably under-investigated. The term Market Driving (MD) pertains to influencing the structure of the market, or the behavior of market players in a direction that enhances the competitive edge of the firm. Presently, the main objectives of the paper are the specification of key antecedents and outcomes of Market Driving behavior. Market Driving firms behave proactively, by leading their customers and changing the rules of the game rather than by responding passively to them. Leading scholars were the first to conceptually conceive the notion, followed by some qualitative studies and a limited number of quantitative publications. However, recently, academicians noted that research on the topic remains limited, expressing a strong necessity for further insights. Concerning the key antecedents, top management’s Transformational Leadership (i.e. the form of leadership which influences organizational members by aligning their values, goals and aspirations to facilitate value-consistent behaviors) is one of the key drivers of MD behavior. Moreover, scholars have linked the MD concept with Entrepreneurship. Finally, the role that Employee’s Creativity plays in the development of MD behavior has been theoretically exemplified by a stream of literature. With respect to the key outcomes, it has been demonstrated that MD Behavior positively triggers firm Performance, while theorists argue that it empowers the Competitive Advantage of the firm. Likewise, researchers explicate that MD Behavior produces Radical Innovation. In order to test the robustness of the proposed theoretical framework, a combination of qualitative and quantitative methods is proposed. In particular, the conduction of in-depth interviews with distinguished executives and academicians, accompanied with a large scale quantitative survey will be employed, in order to triangulate the empirical findings. Given that it triggers overall firm’s success, the MD concept is of high importance to managers. Managers can become aware that passively reacting to market conditions is no longer sufficient. On the contrary, behaving proactively, leading the market, and shaping its status quo are new innovative approaches that lead to a paramount competitive posture and Innovation outcomes. This study also exemplifies that managers can foster MD Behavior through Transformational Leadership, Entrepreneurship and recruitment of Creative Employees. To date, the majority of the publications on Market Orientation is unilaterally directed towards the responsive (i.e. the Market Driven) component. The present paper further builds on scholars’ exhortations, and investigates the Market Driving facet, ultimately aspiring to conceptually integrate the somehow fragmented scientific findings, in a holistic framework.

Keywords: entrepreneurial orientation, market driving behavior, market orientation

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Authors: Hossein Hassani, Ali Rezaei

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Heavy metals are naturally occurring elements that have a high atomic weight and a density at least five times greater than that of water. Their multiple industrial, domestic, agricultural, medical, and technological applications have led to their wide distribution in the environment, raising concerns over their potential effects on human health and the environment. Environmental protection against various pollutants, such as heavy metals formed by industries, mines and modern technologies, is a concern for researchers and industry. In order to assess the contamination of soils the distribution and environmental behavior have been investigated. Jajarm bauxite mine, the most important deposits have been discovered in Iran, which is about 22 million tons of reserve, and is the main mineral of the Diaspora. With a view to estimate the heavy metals ratio of the Jajarm bauxite mine area and to evaluate the pollution level, 50 samples have been collected and have been analyzed for the heavy metals of As, Cd, Cu, Hg, Ni and Pb with the help of Inductively Coupled Plasma-Mass Spectrometer (ICP- MS). In this study, we have dealt with determining evaluation criteria including contamination factor (CF), average concentration (AV), enrichment factor (EF) and geoaccumulation index (GI) to assess the risk of pollution from heavy metals(As, Cd, Cu, Hg, Ni and Pb) in Jajarm bauxite mine. In the samples of the studied, the average of recorded concentration of elements for Arsenic, Cadmium, Copper, Mercury, Nickel and Lead are 18, 0.11, 12, 0.07, 58 and 51 (mg/kg) respectively. The comparison of the heavy metals concentration average and the toxic potential in the samples has shown that an average with respect to the world average of the uncontaminated soil amounts. The average of Pb and As elements shows a higher quantity with respect to the world average quantity. The pollution factor for the study elements has been calculated on the basis of the soil background concentration and has been categorized on the basis of the uncontaminated world soil average with respect to the Hakanson classification. The calculation of the corrected pollutant degree shows the degree of the bulk intermediate pollutant (1.55-2.0) for the average soil sampling of the study area which is on the basis of the background quantity and the world average quantity of the uncontaminated soils. The provided conclusion from calculation of the concentrated factor, for some of the samples show that the average of the lead and arsenic elements stations are more than the background values and the unnatural metal concentration are covered under the study area, That's because the process of mining and mineral extraction. Given conclusion from the calculation of Geoaccumulation index of the soil sampling can explain that the copper, nickel, cadmium, arsenic, lead and mercury elements are Uncontamination. In general, the results indicate that the Jajarm bauxite mine of heavy metal pollution is uncontaminated area and extract the mineral from the mine, not create environmental hazards in the region.

Keywords: enrichment factor, geoaccumulation index, heavy metals, Jajarm bauxite mine, pollution

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Authors: Darko Prebežac, Josip Mikulić, Maja Šerić, Damir Krešić

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Camping tourism is recognized as a growing segment of the broader tourism industry, currently evolving from an inexpensive, temporary sojourn in a rural environment into a highly fragmented niche tourism sector. The trends among public-managed campgrounds seem to be moving away from rustic campgrounds that provide only a tent pad and a fire ring to more developed facilities that offer a range of different amenities, where campers still search for unique experiences that go above the opportunity to experience nature and social interaction. In addition, while camping styles and options changed significantly over the last years, coastal camping in particular became valorized as is it regarded with a heightened sense of nostalgia. Alongside this growing interest in the camping tourism, a demand for quality servicing infrastructure emerged in order to satisfy the wide variety of needs, wants, and expectations of an increasingly demanding traveling public. However, camping activity in general and quality of camping experience and campers’ satisfaction in particular remain an under-researched area of the tourism and consumption behavior literature. In this line, very few studies addressed the issue of quality product/service provision in satisfying nature based tourists and in driving their future behavior with respect to potential re-visitation and recommendation intention. The present study thus aims to investigate the drivers of positive and negative campsite experience using the case of Croatia. Due to the well-preserved nature and indented coastline, camping tourism has a long tradition in Croatia and represents one of the most important and most developed tourism products. During the last decade the number of tourist overnights in Croatian camps has increased by 26% amounting to 16.5 million in 2014. Moreover, according to Eurostat the market share of campsites in the EU is around 14%, indicating that the market share of Croatian campsites is almost double large compared to the EU average. Currently, there are a total of 250 camps in Croatia with approximately 75.8 thousands accommodation units. It is further noteworthy that Croatian camps have higher average occupancy rates and a higher average length of stay as compared to the national average of all types of accommodation. In order to explore the main drivers of positive and negative campsite experiences, this study uses principal components analysis (PCA) and an impact-asymmetry analysis (IAA). Using the PCA, first the main dimensions of the campsite experience are extracted in an exploratory manner. Using the IAA, the extracted factors are investigated for their potentials to create customer delight and/or frustration. The results provide valuable insight to both researchers and practitioners regarding the understanding of campsite satisfaction.

Keywords: Camping tourism, campsite, impact-asymmetry analysis, satisfaction

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Authors: Ravi Teja Chitturi Suryaprakash, Chandrashekhar Unakal, Haytham Al-Bayaty, Duraisamy Saravanakumar

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Background and significance: Oral biofilm formation is a well-known causative factor for caries and periodontal diseases. Scientists over the years have been trying to find a solution against the formation of oral biofilms. Though several advances have been made to understand the microbial ecology and how the bio film survives, it is still an enigma to researchers to find a chemical product that not only can inhibit the formation of oral bio film but also not disturb the oral micro flora required for oral health and not to cause damage to the cells of the oral cavity. One such product that has never been investigated much are herbal preparations. Some of the microorganisms important in the formation of biofilm are Streptococcus mutans, Actinomyces naeslundi, Streptococuss oralis and Prevotella intermedia. The aim of this study was to study the antimicrobial property of some herbal extracts available in Trinidad and Tobago against these pathogens. The significance of this study is that identification of biologically effective plant extracts can result in indigenous development of mouth rinses and tooth pastes that the people can benefit from to not only develop effective but also a cheap solution. Methodology: The extracts from the leaves of Plectranthus ambonicus, Ocmium tenuiflorum, Azadirchata indica, Anacardium occidentale, Psidium guajava were prepared by dissolving them in water. The extracts from the roots of Curcuma longa were prepared similarly and the antimicrobial activity of these six plant extracts was determined by the agar well diffusion method using minimum inhibitory concentration (MIC) against Streptococcus mutans, Actinomyces naeslundi, Streptococuss oralis and Prevotella intermedia and compared with chlorhexidine. Results: The six plant extracts showed variable effect on the oral micro-organisms. Ocmium tenuiflorum (16.66 ± 0.44, 14 ± 0.58, 13.33 ± 0.88, 12.83 ± 0.60), Azadirchata indica (17.5 ± 0.28, 14.83 ± 0.17, 15 ± 0.58, 12.83 ± 0.6) and Curcuma longa (16.16 ± 0.44, 13.66 ± 0.88, 12.33 ± 0.88, 11.33 ± 0.67) were found to have highest inhibitory activity against all the four pathogens (Streptococcus mutans, Streptococuss oralis, Actinomyces naeslundi, and Prevotella intermedia) respectively. Conclusion: Although the extracts were not pure compounds we obtained antimicrobial results which determine that they are potent antimicrobial agents. Further derivation of pure compounds from these extracts could be lucrative as it might lead to the development of a cost effective and biologically safe medicine to act against oral biofilms. Acknowledgement: The authors would like to acknowledge the Campus Research and Publication Fund Committee, The University of the West Indies for funding this study and would also like to acknowledge Dr. Leonette Cox, Department of Chemistry, Faculty of Science and Technology, The University of the West Indies, St. Augustine Campus, Trinidad and Tobago for helping to prepare the plant extracts.

Keywords: agar well diffusion method, herbal extracts, minimum inhibitory concentration, oral biofilm forming microorganisms

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Authors: Norbert Magyar, Jozsef Kovacs, Peter Tanos, Balazs Trasy, Tamas Garamhegyi, Istvan Gabor Hatvani

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Water is one of the most important common resources, and as a result of urbanization, agriculture, and industry it is becoming more and more exposed to potential pollutants. The prevention of the deterioration of water quality is a crucial role for environmental scientist. To achieve this aim, the operation of monitoring networks is necessary. In general, these networks have to meet many important requirements, such as representativeness and cost efficiency. However, existing monitoring networks often include sampling sites which are unnecessary. With the elimination of these sites the monitoring network can be optimized, and it can operate more economically. The aim of this study is to illustrate the applicability of the CCDA (Combined Cluster and Discriminant Analysis) to the field of water quality monitoring and optimize the monitoring networks of a river (the Danube), a wetland-lake system (Kis-Balaton & Lake Balaton), and two surface-subsurface water systems on the watershed of Lake Neusiedl/Lake Fertő and on the Szigetköz area over a period of approximately two decades. CCDA combines two multivariate data analysis methods: hierarchical cluster analysis and linear discriminant analysis. Its goal is to determine homogeneous groups of observations, in our case sampling sites, by comparing the goodness of preconceived classifications obtained from hierarchical cluster analysis with random classifications. The main idea behind CCDA is that if the ratio of correctly classified cases for a grouping is higher than at least 95% of the ratios for the random classifications, then at the level of significance (α=0.05) the given sampling sites don’t form a homogeneous group. Due to the fact that the sampling on the Lake Neusiedl/Lake Fertő was conducted at the same time at all sampling sites, it was possible to visualize the differences between the sampling sites belonging to the same or different groups on scatterplots. Based on the results, the monitoring network of the Danube yields redundant information over certain sections, so that of 12 sampling sites, 3 could be eliminated without loss of information. In the case of the wetland (Kis-Balaton) one pair of sampling sites out of 12, and in the case of Lake Balaton, 5 out of 10 could be discarded. For the groundwater system of the catchment area of Lake Neusiedl/Lake Fertő all 50 monitoring wells are necessary, there is no redundant information in the system. The number of the sampling sites on the Lake Neusiedl/Lake Fertő can decrease to approximately the half of the original number of the sites. Furthermore, neighbouring sampling sites were compared pairwise using CCDA and the results were plotted on diagrams or isoline maps showing the location of the greatest differences. These results can help researchers decide where to place new sampling sites. The application of CCDA proved to be a useful tool in the optimization of the monitoring networks regarding different types of water bodies. Based on the results obtained, the monitoring networks can be operated more economically.

Keywords: combined cluster and discriminant analysis, cost efficiency, monitoring network optimization, water quality

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Authors: Marsha D. Loda

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College enrollment is declining and generation Z, today’s college students, are struggling. Before the pandemic, researchers characterized this generational cohort as unique. Gen Z has been called the most achievement-oriented generation, as they enjoy greater economic status, are more racially and ethnically diverse, and better educated than any other generation. However, they are also the most likely generation to suffer from depression and anxiety. Gen Z has grown up largely with usually well-intentioned but overprotective parents who inadvertently kept them from learning life skills, likely impacting their ability to cope with and to effectively manage challenges. The unprecedented challenges resulting from the pandemic up ended their world and left them emotionally reeling. One of the ramifications of this for higher education is how to reengage current Gen Z students in the classroom. This research presents qualitative findings from 24 single-spaced pages of verbatim comments from college students. Research questions concerned what helps them learn and what they abhor, as well as how to engage them with the university outside of the classroom to aid in retention. Students leave little doubt about what they want to experience in the classroom. In order of mention, students want discussion, to engage with questions, to hear how a topic relates to real life and the real world, to feel connections with the professor and fellow students, and to have an opportunity to give their opinions. They prefer a classroom that involves conversation, with interesting topics and active learning. “professor talks instead of lecturing” “professor builds a connection with the classroom” “I am engaged because it feels like a respectful conversation” Similarly, students are direct about what they dislike in a classroom. In order of frequency, students dislike teachers unenthusiastically reading word or word from notes or presentations, repeating the text without adding examples, or addressing how to apply the information. “All lecture. I can read the book myself” “Not taught how to apply the skill or lesson” “Lectures the entire time. Lesson goes in one ear and out the other.” Pertaining to engagement outside the classroom, Gen Z challenges higher education to step outside the box. They don’t want to just hear from professionals in their field, they want to meet and interact with them. Perhaps because of their dependence on technology and pandemic isolation, they seem to reach out for assistance in forming social bonds. “I believe fun and social events are the best way to connect with students and get them involved. Cookouts, raffles, socials, or networking events would all most likely appeal to many students”. “Events… even if they aren’t directly related to learning. Maybe like movie nights… doing meet ups at restaurants”. Qualitative research suggests strategy. This research is rife with strategic implications to improve learning, increase engagement and reduce drop-out rates among Generation Z higher education students. It also compliments existing research on student engagement. With college enrollment declining by some 1.3 million students over the last two years, this research is both timely and important.

Keywords: college enrollment, generation Z, higher education, pandemic, student engagement

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Authors: Ayoola Adekunle Dada, Tolulope Omolola Fateropa

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There is no gain saying the fact that the Nigerian correctional services lack rehabilitation reformation. Owing to this, some so many inmates, including the female, become more emotionally bruised and hardened instead of coming out of the prison reformed. Although female inmates constitute only a small percentage worldwide, the challenges resulting from women falling under the provision of the penal system have prompted ficial and humanitarian bodies to consider female inmateas as vulnerable persons who need particular social work measures that meet their specific needs. Female inmates’condition may become worseinprisondue to the absence of the standard living condition. A survey of 100 female inmates will be used to determine the assessment of the living condition of the female inmates within the contexts in which they occur. Employing field methods from Medical Sociology and Law, the study seeks to make use of the collaboration of both disciplines for a comprehensive understanding of the scenario. Its specific objectives encompassed: (1) To examine access and use of health facilities among the female inmates;(2) To examine the effect of officers/warders attitude towards female inmates;(3)To investigate the perception of the female inmates towards the housing facilities in the centre and; (4) To investigate the feeding habit of the female inmates. Due to the exploratory nature of the study, the researchers will make use of mixed-method, such qualitative methods as interviews will be undertaken to complement survey research (quantitative). By adopting the above-explained inter-method triangulation, the study will not only ensure that the advantages of both methods are exploited but will also fulfil the basic purposes of research. The sampling for this study will be purposive. The study aims at sampling two correctional centres (Ado Ekiti and Akure) in order to generate representative data for the female inmates in South West Nigeria. In all, the total number of respondents will be 100. A cross-section of female inmates will be selected as respondents using a multi-stage sampling technique. 100 questionnaires will be administered. A semi structured (in-depth) interviews will be conducted among workers in the two selected correctional centres, respectively, to gain further insight on the living conditions of female inmates, which the survey may not readily elicit. These participants will be selected purposively in respect to their status in the organisation. Ethical issues in research on human subjects will be given due consideration. Such issues rest on principles of beneficence, non-maleficence, autonomy/justice and confidentiality. In the final analysis, qualitative data will be analyzed using manual content analysis. Both the descriptive and inferential statistics will be used for analytical purposes. Frequency, simple percentage, pie chart, bar chart, curve and cross-tabulations will form part of the descriptive analysis.

Keywords: assessment, health facilities, inmates, perception, living conditions

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Authors: Laxuman Thakuri

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Despite the large number of in-depth case studies focused on policy analysis, institutional arrangement, and collective action of common property resource management; how the local institutions take the pricing decision of forest products in community forest management and what kinds of effects produce it, the answers of these questions are largely silent among the policy-makers and researchers alike. The study examined how the local institutions take the pricing decision of forest products in the lowland community forestry of Nepal and how the decisions affect to equitable distribution of benefits and livelihood improvement which are also objectives of Nepalese community forestry. The study assumes that forest products pricing decisions have multiple effects on equitable distribution and livelihood improvement in the areas having heterogeneous socio-economic conditions. The dissertation was carried out at four community forests of lowland, Nepal that has characteristics of high value species, matured-experience of community forest management and better record-keeping system of forest products production, pricing and distribution. The questionnaire survey, individual to group discussions and direct field observation were applied for data collection from the field, and Lorenz curve, gini-coefficient, χ²-text, and SWOT (Strong, Weak, Opportunity, and Threat) analysis were performed for data analysis and results interpretation. The dissertation demonstrates that the low pricing strategy of high-value forest products was supposed crucial to increase the access of socio-economically weak households, and to and control over the important forest products such as timber, but found counter productive as the strategy increased the access of socio-economically better-off households at higher rate. In addition, the strategy contradicts to collect a large-scale community fund and carry out livelihood improvement activities as per the community forestry objectives. The crucial part of the study is despite the fact of low pricing strategy; the timber alone contributed large part of community fund collection. The results revealed close relation between pricing decisions and livelihood objectives. The action research result shows that positive price discrimination can slightly reduce the prevailing inequality and increase the fund. However, it lacks to harness the full price of forest products and collects a large-scale community fund. For broader outcomes of common property resource management in terms of resource sustainability, equity, and livelihood opportunity, the study suggests local institutions to harness the full price of resource products with respect to the local market.

Keywords: community, equitable, forest, livelihood, socioeconomic, Nepal

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Authors: J. T. Pitale, S. Ghassab, H. Ay, N. Berme

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Biomechanics researchers commonly use marker-based optical motion capture (MoCap) systems to extract human body kinematic data. These systems use cameras to detect passive or active markers placed on the subject. The cameras use triangulation methods to form images of the markers, which typically require each marker to be visible by at least two cameras simultaneously. Cameras in a conventional optical MoCap system are mounted at a distance from the subject, typically on walls, ceiling as well as fixed or adjustable frame structures. To accommodate for space constraints and as portable force measurement systems are getting popular, there is a need for smaller and smaller capture volumes. When the efficacy of a MoCap system is investigated, it is important to consider the tradeoff amongst the camera distance from subject, pixel density, and the field of view (FOV). If cameras are mounted relatively close to a subject, the area corresponding to each pixel reduces, thus increasing the image resolution. However, the cross section of the capture volume also decreases, causing reduction of the visible area. Due to this reduction, additional cameras may be required in such applications. On the other hand, mounting cameras relatively far from the subject increases the visible area but reduces the image quality. The goal of this study was to develop a quantitative methodology to investigate marker occlusions and optimize camera placement for a given capture volume and subject postures using three-dimension computer-aided design (CAD) tools. We modeled a 4.9m x 3.7m x 2.4m (LxWxH) MoCap volume and designed a mounting structure for cameras using SOLIDWORKS (Dassault Systems, MA, USA). The FOV was used to generate the capture volume for each camera placed on the structure. A human body model with configurable posture was placed at the center of the capture volume on CAD environment. We studied three postures; initial contact, mid-stance, and early swing. The human body CAD model was adjusted for each posture based on the range of joint angles. Markers were attached to the model to enable a full body capture. The cameras were placed around the capture volume at a maximum distance of 2.7m from the subject. We used the Camera View feature in SOLIDWORKS to generate images of the subject as seen by each camera and the number of markers visible to each camera was tabulated. The approach presented in this study provides a quantitative method to investigate the efficacy and efficiency of a MoCap camera setup. This approach enables optimization of a camera setup through adjusting the position and orientation of cameras on the CAD environment and quantifying marker visibility. It is also possible to compare different camera setup options on the same quantitative basis. The flexibility of the CAD environment enables accurate representation of the capture volume, including any objects that may cause obstructions between the subject and the cameras. With this approach, it is possible to compare different camera placement options to each other, as well as optimize a given camera setup based on quantitative results.

Keywords: motion capture, cameras, biomechanics, gait analysis

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Authors: Eleanor F. Willard

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The attrition rate on distance learning courses can be high. This research examines how online students often react when faced with poor results. Using q methodology, it was found that the emotional response level and the type of social support sought by students were key influences on their attitude to failure. As educational and psychological researchers, we are adept at measuring learning and achievement, but examining attitudes towards barriers to learning are not so well researched. The distance learning student has differing needs from onsite learners and, as the attrition rate is notoriously high in the online student population, examining learners’ attitude towards adversity and barriers is important. Self-report measures such as questionnaires are useful in terms of ascertaining levels of constructs such as resilience and academic confidence. Interviewing, too, can gain in depth detail of the opinions of such a population, but only in individuals. The aim of this research was to ascertain what the feelings and attitudes of online students were when faced with a setback. This was achieved using q methodology due to its use of both quantitative and qualitative methodology and its suitability for exploratory research. The emphasis with this methodology is the attitudes, not the individuals. The work was focused upon a population of distance learning students who attended a school on site for one week as part of their studies. They were engaged in a psychology masters conversion course and, as such, were graduate students. The Q sort had 30 items taken from the Academic Resilience Scale (ARS-30). The scale items represent three constructs; perseverance, reflecting (including adaptive help-seeking) and negative affect. These are widely acknowledged as being relevant concepts underpinning psychological resilience. The q sort was conducted with 19 students in total. This is done by participants arranging statement cards regarding how similar to themselves they believe each statement to be. This was done after reading a vignette describing an experience of academic failure. Commonalities and differences between the sorts from all participants are then analyzed in terms of correlations and response patterns. Following data collection, the participants' responses were initially analyzed and the key perspectives (factors) to emerge were labelled ‘persevering individuals’ and ‘emotional networkers’. The differences between the two perspectives centre around the level of emotion felt when faced with barriers and the extent that students enlist the help of others inside and outside of the university. The dominant factor to emerge from the sorts of ‘persevering individuals’ demonstrated that many distance learners are tenacious. However, for other students, the level of emotional and social support is pivotal in helping them complete their studies when facing adversity. This was demonstrated by the ‘emotional networkers’ perspective. This research forms a starting point for further work on engaging and retaining online students at university and can potentially provide insight into how universities can lower attrition rates on distance learning courses.

Keywords: academic resilience, distance learning, online learning, q methodology

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Authors: Hugo Lefeuvre, Jerôme Donnard, Michael Descostes, Sophie Billon, Samuel Duval, Tugdual Oger, Herve Toubon, Paul Sardini

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Spectroscopic autoradiography is a method of interest for geological sample analysis. Indeed, researchers may face different issues such as radioelement identification and quantification in the field of environmental studies. Imaging gaseous ionization detectors find their place in geosciences for conducting specific measurements of radioactivity to improve the monitoring of natural processes using naturally-occurring radioactive tracers, but also for the nuclear industry linked to the mining sector. In geological samples, the location and identification of the radioactive-bearing minerals at the thin-section scale remains a major challenge as the detection limit of the usual elementary microprobe techniques is far higher than the concentration of most of the natural radioactive decay products. The spatial distribution of each decay product in the case of uranium in a geomaterial is interesting for relating radionuclides concentration to the mineralogy. The present study aims to provide spectroscopic autoradiography analysis method for measuring the initial energy of alpha particles with a parallel ionization multiplier gaseous detector. The analysis method has been developed thanks to Geant4 modelling of the detector. The track of alpha particles recorded in the gas detector allow the simultaneous measurement of the initial point of emission and the reconstruction of the initial particle energy by a selection based on the linear energy distribution. This spectroscopic autoradiography method was successfully used to reproduce the alpha spectra from a 238U decay chain on a geological sample at the thin-section scale. The characteristics of this measurement are an energy spectrum resolution of 17.2% (FWHM) at 4647 keV and a spatial resolution of at least 50 µm. Even if the efficiency of energy spectrum reconstruction is low (4.4%) compared to the efficiency of a simple autoradiograph (50%), this novel measurement approach offers the opportunity to select areas on an autoradiograph to perform an energy spectrum analysis within that area. This opens up possibilities for the detailed analysis of heterogeneous geological samples containing natural alpha emitters such as uranium-238 and radium-226. This measurement will allow the study of the spatial distribution of uranium and its descendants in geo-materials by coupling scanning electron microscope characterizations. The direct application of this dual modality (energy-position) of analysis will be the subject of future developments. The measurement of the radioactive equilibrium state of heterogeneous geological structures, and the quantitative mapping of 226Ra radioactivity are now being actively studied.

Keywords: alpha spectroscopy, digital autoradiography, mining activities, natural decay products

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Authors: Nicoly Coelho, Eduardo Vieira Vilas Boas, Paulo Orestes Formigoni

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Faced with the remarkable developments in the various segments of modern engineering, provided by the increasing technological development, professionals of all educational areas need to overcome the difficulties generated due to the good understanding of those who are starting their academic journey. Aiming to overcome these difficulties, this article aims at an introduction to the basic study of numerical methods applied to fluid mechanics and thermodynamics, demonstrating the modeling and simulations with its substance, and a detailed explanation of the fundamental numerical solution for the use of finite difference method, using SCILAB, a free software easily accessible as it is free and can be used for any research center or university, anywhere, both in developed and developing countries. It is known that the Computational Fluid Dynamics (CFD) is a necessary tool for engineers and professionals who study fluid mechanics, however, the teaching of this area of knowledge in undergraduate programs faced some difficulties due to software costs and the degree of difficulty of mathematical problems involved in this way the matter is treated only in postgraduate courses. This work aims to bring the use of DFC low cost in teaching Transport Phenomena for graduation analyzing a small classic case of fundamental thermodynamics with Scilab® program. The study starts from the basic theory involving the equation the partial differential equation governing heat transfer problem, implies the need for mastery of students, discretization processes that include the basic principles of series expansion Taylor responsible for generating a system capable of convergence check equations using the concepts of Sassenfeld, finally coming to be solved by Gauss-Seidel method. In this work we demonstrated processes involving both simple problems solved manually, as well as the complex problems that required computer implementation, for which we use a small algorithm with less than 200 lines in Scilab® in heat transfer study of a heated plate in rectangular shape on four sides with different temperatures on either side, producing a two-dimensional transport with colored graphic simulation. With the spread of computer technology, numerous programs have emerged requiring great researcher programming skills. Thinking that this ability to program DFC is the main problem to be overcome, both by students and by researchers, we present in this article a hint of use of programs with less complex interface, thus enabling less difficulty in producing graphical modeling and simulation for DFC with an extension of the programming area of experience for undergraduates.

Keywords: numerical methods, finite difference method, heat transfer, Scilab

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Authors: Rajkumar Ghosh

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Earthquakes pose significant risks to human life and infrastructure, highlighting the importance of effective earthquake mitigation strategies. Traditional earthquake modelling and mitigation efforts have largely focused on the primary fault segments and their slip behaviour. However, earthquakes can exhibit complex rupture dynamics, including out-of-sequence thrust (OOST) events, which occur on secondary or subsidiary faults. This abstract examines the impact of OOST dynamics on earthquake mitigation strategies and their implications for hazard assessment and disaster planning. OOST events challenge conventional seismic hazard assessments by introducing additional fault segments and potential rupture scenarios that were previously unrecognized or underestimated. Consequently, these events may increase the overall seismic hazard in affected regions. The study reviews recent case studies and research findings that illustrate the occurrence and characteristics of OOST events. It explores the factors contributing to OOST dynamics, such as stress interactions between fault segments, fault geometry, and mechanical properties of fault materials. Moreover, it investigates the potential triggers and precursory signals associated with OOST events to enhance early warning systems and emergency response preparedness. The abstract also highlights the significance of incorporating OOST dynamics into seismic hazard assessment methodologies. It discusses the challenges associated with accurately modelling OOST events, including the need for improved understanding of fault interactions, stress transfer mechanisms, and rupture propagation patterns. Additionally, the abstract explores the potential for advanced geophysical techniques, such as high-resolution imaging and seismic monitoring networks, to detect and characterize OOST events. Furthermore, the abstract emphasizes the practical implications of OOST dynamics for earthquake mitigation strategies and urban planning. It addresses the need for revising building codes, land-use regulations, and infrastructure designs to account for the increased seismic hazard associated with OOST events. It also underscores the importance of public awareness campaigns to educate communities about the potential risks and safety measures specific to OOST-induced earthquakes. This sheds light on the impact of out-of-sequence thrust dynamics in earthquake mitigation. By recognizing and understanding OOST events, researchers, engineers, and policymakers can improve hazard assessment methodologies, enhance early warning systems, and implement effective mitigation measures. By integrating knowledge of OOST dynamics into urban planning and infrastructure development, societies can strive for greater resilience in the face of earthquakes, ultimately minimizing the potential for loss of life and infrastructure damage.

Keywords: earthquake mitigation, out-of-sequence thrust, seismic, satellite imagery

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Authors: Muhammad Younas, Sidra Sawati, M. Razzaq Athar

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Organizational development history reveals that it has ever been a challenge to identify and fathom the role of talent management, career development and compensation management towards employees’ retention and organizational performance. Organizations strive hard to measure the impact of all those factors which affect employee retention and organizational performance. Researchers have worked in great deal in order to know the relationship of independent variables i.e. Talent Management, Career Development and Compensation Management on dependent variables i.e. Employee Retention and Organizational Performance. Employees adorned with latest skills with long lasting loyalty play a significant role towards successful achievement of short term as well as long term goals of the organizations. Retention of valuable and resourceful employees for a longer time is equally essential for meeting the set goals. The organizations which spend reasonable chunk of their resources for taking such measures that help to retain their employees through talent management and satisfactory career development always enjoy a competitive edge over their competitors. Human resource is regarded as one of the most precious and difficult resource to management. It has its own needs and requirement. It becomes an easy prey to monotony when lacks career development. Wants and aspirations of this resource are seldom met completely but can be managed through career development and compensation management. In this era of competition, organizations have to take viable steps to management their resources especially human resource. Top management and Managers keep on working for an amenable solution in order to address the challenges relating career development and compensation management as their ultimate goal is to ensure the organizational performance on optimum level. The current study was conducted to examine the impact of Talent Management, Career Development and Compensation Management towards Employees Retention and Organizational Performance with mediating effect of Employees Motivation in Service Sector of Pakistan. The current study is based on Resource Based View (RBV) and Ability Motivation Opportunity (AMO) theories. It explains that by increasing internal resources we can manage employee talent, career development through compensation management and employee motivation more effectively. It will result in effective execution of HRM practices for employee retention enabling an organization to achieve and sustain competitive advantage through optimal performance. Data collection was made through a structured questionnaire which was based upon adopted instruments after testing reliability and validity. A total 300 employees of 30 firms in service sector of Pakistan were sampled through non-probability sampling technique. Regression analysis revealed that talent management, career development and compensation management have significant positive impact on employee retention and perceived organizational performance. The results further showed that employee motivation have a significant mediating effect on employee retention and organizational performance. The interpretation of the findings and limitations, theoretical and managerial implications are also discussed.

Keywords: career development, compensation management, employee retention, organizational performance, talent management

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Authors: Yiea Funk Te, Daniel Mueller, Irena Pletikosa Cvijikj

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Small and medium enterprises (SMEs) play an important role in the economy of many countries. When the overall world economy is considered, SMEs represent 95% of all businesses in the world, accounting for 66% of the total employment. Existing studies show that the current business environment is characterized as highly turbulent and strongly influenced by modern information and communication technologies, thus forcing SMEs to experience more severe challenges in maintaining their existence and expanding their business. To support SMEs at improving their competitiveness, researchers recently turned their focus on applying data mining techniques to build risk and growth prediction models. However, data used to assess risk and growth indicators is primarily obtained via questionnaires, which is very laborious and time-consuming, or is provided by financial institutes, thus highly sensitive to privacy issues. Recently, web mining (WM) has emerged as a new approach towards obtaining valuable insights in the business world. WM enables automatic and large scale collection and analysis of potentially valuable data from various online platforms, including companies’ websites. While WM methods have been frequently studied to anticipate growth of sales volume for e-commerce platforms, their application for assessment of SME risk and growth indicators is still scarce. Considering that a vast proportion of SMEs own a website, WM bears a great potential in revealing valuable information hidden in SME websites, which can further be used to understand SME risk and growth indicators, as well as to enhance current SME risk and growth prediction models. This study aims at developing an automated system to collect business-relevant data from the Web and predict future growth trends of SMEs by means of WM and data mining techniques. The envisioned system should serve as an 'early recognition system' for future growth opportunities. In an initial step, we examine how structured and semi-structured Web data in governmental or SME websites can be used to explain the success of SMEs. WM methods are applied to extract Web data in a form of additional input features for the growth prediction model. The data on SMEs provided by a large Swiss insurance company is used as ground truth data (i.e. growth-labeled data) to train the growth prediction model. Different machine learning classification algorithms such as the Support Vector Machine, Random Forest and Artificial Neural Network are applied and compared, with the goal to optimize the prediction performance. The results are compared to those from previous studies, in order to assess the contribution of growth indicators retrieved from the Web for increasing the predictive power of the model.

Keywords: data mining, SME growth, success factors, web mining

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Authors: S. C. Lin, W. W. Cheng, M. S. Wu

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This study attempted to investigate the connection between teacher professional development program and students’ Learning. This study took Readers’ Theater Teaching Program (RTTP) for professional development as an example to inquiry how participants apply their new knowledge and skills learned from RTTP to their teaching practice and how the impact influence students learning. The goals of the RTTP included: 1) to enhance teachers RT content knowledge; 2) to implement RT instruction in teachers’ classrooms in response to their professional development. 2) to improve students’ ability of reading fluency in professional development teachers’ classrooms. This study was a two-year project. The researchers applied mixed methods to conduct this study including qualitative inquiry and one-group pretest-posttest experimental design. In the first year, this study focused on designing and implementing RTTP and evaluating participants’ satisfaction of RTTP, what they learned and how they applied it to design their English reading curriculum. In the second year, the study adopted quasi-experimental design approach and evaluated how participants RT instruction influenced their students’ learning, including English knowledge, skill, and attitudes. The participants in this study composed two junior high school English teachers and their students. Data were collected from a number of different sources including teaching observation, semi-structured interviews, teaching diary, teachers’ professional development portfolio, Pre/post RT content knowledge tests, teacher survey, and students’ reading fluency tests. To analyze the data, both qualitative and quantitative data analysis were used. Qualitative data analysis included three stages: organizing data, coding data, and analyzing and interpreting data. Quantitative data analysis included descriptive analysis. The results indicated that average percentage of correct on pre-tests in RT content knowledge assessment was 40.75% with two teachers ranging in prior knowledge from 35% to 46% in specific RT content. Post-test RT content scores ranged from 70% to 82% correct with an average score of 76.50%. That gives teachers an average gain of 35.75% in overall content knowledge as measured by these pre/post exams. Teachers’ pre-test scores were lowest in script writing and highest in performing. Script writing was also the content area that showed the highest gains in content knowledge. Moreover, participants hold a positive attitude toward RTTP. They recommended that the approach of professional learning community, which was applied in RTTP was benefit to their professional development. Participants also applied the new skills and knowledge which they learned from RTTP to their practices. The evidences from this study indicated that RT English instruction significantly influenced students’ reading fluency and classroom climate. The result indicated that all of the experimental group students had a big progress in reading fluency after RT instruction. The study also found out several obstacles. Suggestions were also made.

Keywords: teacher’s professional development, program evaluation, readers’ theater, english reading instruction, english reading fluency

Procedia PDF Downloads 357

Authors: Jazim Sohail, Filipe Teixeira-Dias

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Mild traumatic brain injury (mTBI) within non-helmeted contact sports is a growing concern due to the serious risk of potential injury. Extensive research is being conducted looking into head kinematics in non-helmeted contact sports utilizing instrumented mouthguards that allow researchers to record accelerations and velocities of the head during and after an impact. This does not, however, allow the location of the impact on the head, and its magnitude and orientation, to be determined. This research proposes and validates two methods to quantify impact locations from instrumented mouthguard kinematic data, one using rigid body dynamics, the other utilizing machine learning. The rigid body dynamics technique focuses on establishing and matching moments from Euler’s and torque equations in order to find the impact location on the head. The methodology is validated with impact data collected from a lab test with the dummy head fitted with an instrumented mouthguard. Additionally, a Hybrid III Dummy head finite element model was utilized to create synthetic kinematic data sets for impacts from varying locations to validate the impact location algorithm. The algorithm calculates accurate impact locations; however, it will require preprocessing of live data, which is currently being done by cross-referencing data timestamps to video footage. The machine learning technique focuses on eliminating the preprocessing aspect by establishing trends within time-series signals from instrumented mouthguards to determine the impact location on the head. An unsupervised learning technique is used to cluster together impacts within similar regions from an entire time-series signal. The kinematic signals established from mouthguards are converted to the frequency domain before using a clustering algorithm to cluster together similar signals within a time series that may span the length of a game. Impacts are clustered within predetermined location bins. The same Hybrid III Dummy finite element model is used to create impacts that closely replicate on-field impacts in order to create synthetic time-series datasets consisting of impacts in varying locations. These time-series data sets are used to validate the machine learning technique. The rigid body dynamics technique provides a good method to establish accurate impact location of impact signals that have already been labeled as true impacts and filtered out of the entire time series. However, the machine learning technique provides a method that can be implemented with long time series signal data but will provide impact location within predetermined regions on the head. Additionally, the machine learning technique can be used to eliminate false impacts captured by sensors saving additional time for data scientists using instrumented mouthguard kinematic data as validating true impacts with video footage would not be required.

Keywords: head impacts, impact location, instrumented mouthguard, machine learning, mTBI

Procedia PDF Downloads 176

Authors: Shahrzad Zolfagharnassab, Abdul Rashid Mohamed Shariff, Siti Khairunniza Bejo

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Conventional methods for nutrient soil mapping are based on laboratory tests of samples that are obtained from surveys. The time and cost involved in gathering and analyzing soil samples are the reasons that researchers use Predictive Soil Mapping (PSM). PSM can be defined as the development of a numerical or statistical model of the relationship among environmental variables and soil properties, which is then applied to a geographic database to create a predictive map. Kriging is a group of geostatistical techniques to spatially interpolate point values at an unobserved location from observations of values at nearby locations. The main problem with using kriging as an interpolator is that it is excessively data-dependent and requires a large number of closely spaced data points. Hence, there is a need to minimize the number of data points without sacrificing the accuracy of the results. In this paper, an Artificial Neural Networks (ANN) scheme was used to predict macronutrient values at un-sampled points. ANN has become a popular tool for prediction as it eliminates certain difficulties in soil property prediction, such as non-linear relationships and non-normality. Back-propagation multilayer feed-forward network structures were used to predict nitrogen, phosphorous and potassium values in the soil of the study area. A limited number of samples were used in the training, validation and testing phases of ANN (pattern reconstruction structures) to classify soil properties and the trained network was used for prediction. The soil analysis results of samples collected from the soil survey of block C of Sawah Sempadan, Tanjung Karang rice irrigation project at Selangor of Malaysia were used. Soil maps were produced by the Kriging method using 236 samples (or values) that were a combination of actual values (obtained from real samples) and virtual values (neural network predicted values). For each macronutrient element, three types of maps were generated with 118 actual and 118 virtual values, 59 actual and 177 virtual values, and 30 actual and 206 virtual values, respectively. To evaluate the performance of the proposed method, for each macronutrient element, a base map using 236 actual samples and test maps using 118, 59 and 30 actual samples respectively produced by the Kriging method. A set of parameters was defined to measure the similarity of the maps that were generated with the proposed method, termed the sample reduction method. The results show that the maps that were generated through the sample reduction method were more accurate than the corresponding base maps produced through a smaller number of real samples. For example, nitrogen maps that were produced from 118, 59 and 30 real samples have 78%, 62%, 41% similarity, respectively with the base map (236 samples) and the sample reduction method increased similarity to 87%, 77%, 71%, respectively. Hence, this method can reduce the number of real samples and substitute ANN predictive samples to achieve the specified level of accuracy.

Keywords: artificial neural network, kriging, macro nutrient, pattern recognition, precision farming, soil mapping

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Authors: Isabell Koinig, Sandra Diehl

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In recent years, the health-care context has not been left unaffected by technological developments. In recent years, the Internet of Medical Things (IoMT)has not only led to a collaboration between disease management and advanced care coordination but also to more personalized health care and patient empowerment. With more than 40 % of all health technology being IoMT-related by 2020, questions regarding privacy become more prevalent, even more so during COVID-19when apps allowing for an intensive tracking of people’s whereabouts and their personal contacts cause privacy advocates to protest and revolt. There is a widespread tendency that even though users may express concerns and fears about their privacy, they behave in a manner that appears to contradict their statements by disclosing personal data. In literature, this phenomenon is discussed as a privacy paradox. While there are some studies investigating the privacy paradox in general, there is only scarce research related to the privacy paradox in the health sector and, to the authors’ knowledge, no empirical study investigating young people’s attitudes toward data security when using wearables and health apps. The empirical study presented in this paper tries to reduce this research gap by focusing on the area of digital and mobile health. It sets out to investigate the degree of importance individuals attribute to protecting their privacy and individual privacy protection strategies. Moreover, the question to which degree individuals between the ages of 20 and 30 years are willing to grant commercial parties access to their private data to use digital health services and apps are put to the test. To answer this research question, results from 6 focus groups with 40 participants will be presented. The focus was put on this age segment that has grown up in a digitally immersed environment. Moreover, it is particularly the young generation who is not only interested in health and fitness but also already uses health-supporting apps or gadgets. Approximately one-third of the study participants were students. Subjects were recruited in August and September 2019 by two trained researchers via email and were offered an incentive for their participation. Overall, results indicate that the young generation is well informed about the growing data collection and is quite critical of it; moreover, they possess knowledge of the potential side effects associated with this data collection. Most respondents indicated to cautiously handle their data and consider privacy as highly relevant, utilizing a number of protective strategies to ensure the confidentiality of their information. Their willingness to share information in exchange for services was only moderately pronounced, particularly in the health context, since health data was seen as valuable and sensitive. The majority of respondents indicated to rather miss out on using digital and mobile health offerings in order to maintain their privacy. While this behavior might be an unintended consequence, it is an important piece of information for app developers and medical providers, who have to find a way to find a user base for their products against the background of rising user privacy concerns.

Keywords: digital health, privacy, privacy paradox, IoMT

Procedia PDF Downloads 111