Search results for: social learning

Authors: Samia Jamshed Nauman Majeed

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Purpose: Globally, the pandemic of COVID -19 has created a massive distraction for educational reforms influencing learning options, education access, and outcomes of students in more than 190 countries which has carved marks in history. To explore the challenges and complications confronted by students and faculty members while ensuring access to online education, qualitative research was conducted. Methodology: For this purpose, a series of focus group discussions were conducted in different regions of Pakistan, which revealed interesting findings shared by Panelists, which include Vice-Chancellors, Rectors, and Deans of different private and public sector universities of Pakistan. The qualitative research aims to explore the challenges and success factors of online educations by students with diverse backgrounds of higher education institutions to maximize student educational outcomes. Findings: The findings revealed several challenges and opportunities when it comes to online education for students of higher education institutions. Simultaneously, the researchers discovered the key success factors necessary for online education. Lastly, the paper presents the research limitations and future research recommendations to streamline online education in a better way ensuring the students' success. Originality: The pandemic has forced the closure of social, business, and educational activities, which has drastically influence the quality of education with its subsequent impact on the economy. In response, numerous universities across the globe are forced to suspend their educational activities by closing the universities. Though online education has been adopted worldwide by the universities, which brought numerous issues for academia, particularly for underdeveloped countries, and Pakistani higher education reforms are no exception to this.

Keywords: online education, higher education institutions, COVID-19, challenges, key success factors

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Authors: Mateusz Rak

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Objective: The paper aims to present various sources of competitive advantage which may occur when an enterprise strategically applies its concept of corporate philanthropy. Methodology: The review of the literature and available reports on the research regarding corporate philanthropy. Results: Strategic philanthropy is a positive phenomenon. Unfortunately, enterprises in Poland do not see all positive sides of such activities yet. Three kinds of corporate philanthropy may be described. They are to fulfil a social duty, improve the company reputation and gain a competitive edge. Practical implications: Showing enterprises the advantages of taking philanthropic actions, in particular, a large role of strategic philanthropy in gaining a competitive edge in the market as well as how to avoid negative consequences of corporate philanthropy. The paper presents corporate philanthropy on a few layers: as a CSR element, actions generating values in products, actions improving a corporate image in the market, altruist actions of employees.

Keywords: corporate philanthropy, corporate social responsibility, corporate foundations, CSR

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Authors: Jarrod Sio Jyh Lih

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This paper discusses the factors contributing to student achievement in literacy and numeracy in primary schools within Sibu division. The study involved 694 level 1 primary schoolteachers. Using descriptive statistics, the study observed high levels of practice for teacher efficacy, instructional leadership and professional learning communities (PLCs). The differences between gender, teaching experience and academic qualification were analyzed using the t-test and one-way analysis of variance (ANOVA). The study reported significant differences in respondent perceptions based on teaching experience vis-à-vis teacher efficacy. Here, the post hoc Tukey test revealed that efficaciousness grows with experience. A correlation test observed positive and significant correlations between all independent variables. Binary logistic regression was applied to predict the independent variables’ influence on student achievement. The findings revealed that a dimension of instructional leadership – ‘monitoring student progress’ - emerged as the best predictor of student achievement for literacy and numeracy. The result indicated the students were more than 4 times more likely to achieve the national key performance index for both literacy and numeracy when student progress was monitored. In conclusion, ‘monitoring student progress’ had a positive influence on students’ achievement for literacy and numeracy, hence making it a possible course of action for school heads. However, more comprehensive studies are needed to ascertain its consistency within the context of Malaysia.

Keywords: efficacy, instructional, literacy, numeracy

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Authors: Shanshan Zhu, Mohammad Nasim

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Financial fraud continues to be a major threat to financial institutions across the world, causing colossal money losses and undermining public trust. Fraud prevention techniques, based on hard rules, have become ineffective due to evolving patterns of fraud in recent times. Against such a background, the present study probes into distinct methodologies that exploit emergent AI-driven techniques to further strengthen fraud detection. We would like to compare the performance of generative adversarial networks and graph neural networks with other popular techniques, like gradient boosting, random forests, and neural networks. To this end, we would recommend integrating all these state-of-the-art models into one robust, flexible, and smart system for real-time anomaly and fraud detection. To overcome the challenge, we designed synthetic data and then conducted pattern recognition and unsupervised and supervised learning analyses on the transaction data to identify which activities were fishy. With the use of actual financial statistics, we compare the performance of our model in accuracy, speed, and adaptability versus conventional models. The results of this study illustrate a strong signal and need to integrate state-of-the-art, AI-driven fraud detection solutions into frameworks that are highly relevant to the financial domain. It alerts one to the great urgency that banks and related financial institutions must rapidly implement these most advanced technologies to continue to have a high level of security.

Keywords: AI-driven fraud detection, financial security, machine learning, anomaly detection, real-time fraud detection

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Authors: David Cobham

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In higher education, a great degree of importance is placed on the internationalization of the student experience. This is seen as a valuable contributor to elements such as building confidence, broadening knowledge, creating networks and connections, and enhancing employability for current students who will become the next generation of managers in technology and business. The COVID-19 pandemic has affected all areas of people’s lives. The limitations of travel coupled with the fears and concerns generated by the health risks have dramatically reduced the opportunity for students to engage with this agenda. Institutions of higher education have been required to rethink fundamental aspects of their business model from recruitment and enrolment through learning approaches, assessment methods, and the pathway to employment. This paper presents a case study which focuses on student mobility and how the physical experience of being in another country, either to study, to work, to volunteer or to gain cultural and social enhancement, has of necessity been replaced by alternative approaches. It considers trans-national education as an alternative to physical study overseas, virtual mobility and internships as an alternative to international work experience, and adopting collaborative online projects as an alternative to in-person encounters. The paper concludes that although these elements have been adopted to address the current situation, the lessons learned and the feedback gained suggests that they have contributed successfully in new and sometimes unexpected ways and that they will persist beyond the present to become part of the 'new normal' for the future. That being the case, senior leaders of institutions of higher education will be required to revisit their international plans and to rewrite their international strategies to take account of and build upon these changes.

Keywords: higher education management, internationalization, transnational education, virtual mobility

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Authors: Digambar J. Darekar, Sharvari D. Darekar

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Childlessness is a universal problem. It particularly affects the mental health of childless couple. It leads to anxiety, frustration, nervousness, depression, loneliness, helplessness, hopelessness, etc. After reviewing the literature, it is found that mental health of married couples is negatively related to childlessness. To understand emotional and psychological problems of a childless couple, researcher surveyed and interviewed 50 childless couples with the help of medical practitioner and gynecologist. Personal adjustment and mental health inventory and marital adjustment inventory along with semi-structured interview questionnaire was used. On the basis of responses from the subject, distinction is made between the problems of male subjects and female subjects and common problem separately. The researcher found that childlessness leads to the conflict between in-laws, harassment, hopelessness, feeling of emptiness and vacuumed, frustration, lack of hope and desire for life, restlessness, loss of sleep, ideas of committing suicide, increased emotional distance and disturbed marital life. The childlessness leads to sorrow for women and anger for men. Men turns towards addiction and women tend to avoid social contact and face problems of social adjustments. Childless couples are sufferers of personal and marital adjustment problems which in turn affect their mental health adversely.

Keywords: childlessness, marital adjustments, mental health, social adjustment

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Authors: Zehra Gencel Efe, Fatma Susam Ozsayın, Satı Tas

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Background and Aim: It is not possible to teach all the knowledge related to operating room nursing in the nursing education process. Certified courses are organized by the Ministry of Health to compensate the lack of postgraduate training and the theoretical and practical training needs of working nurses. In this study; It is aimed to investigate the participants’ opinions and recommendations attending the certified course of operating room nursing that organized in İKCU AtaturkTraining and Research Hospital. Method: Two operating room nursing courses were organized in 2016. The 1st Operating Room Nursing Certified Course Program was organized between March 07, 2016 and April 6, 2016and the 2nd Operating Room Nursing Certified Course Program was organized between 07 November 2016 - 06 December 2016 at the İKCU Ataturk Training and Research Hospital. The first program was accepted for 29 participants, the second program was accepted for 30 participants. In the collection of the data, the 'Operating Room Nursing Certified Training Program Evaluation Form', 'Operating Room Nursing Certified Training Program Theoretical Training Evaluation Form' were used. Three point Likert-type scale is used for responses in the 'Operating Room Nursing Certified Training Program Evaluation Form’ (1=verygood, 2=good, 3=poor). Data is collected in five areas related to training program, operation room practice, communication, responsibility, experiences of learning. Four point Likert-type scale is used for responses in the 'Operating Room Nursing Certified Training Program Theoretical Training Evaluation Form' (1=verysatisfied, 2=quitesatisfied, 3=satisfied, 4=dissatisfied). Data is collected in two areas include presentation and content. Data were analyzed with SPSS 16 program. Findings and Conclusion: It was found that 93,22% of participants were female in addition, 62,7% had bachelor degree. It was seen that 33,87% of the work group had 1-5 years of experience in their field. It was found that; 88% of trainees participating in the first group to the operating room nursing-certified course program stated the training program was very good, 12% of them stated the training program was good. Nobody was signed the ‘poor’ choice. 81% of the trainees who participated in the 2nd group to the operating room nursing-certified course program stated the training program was very good, 19% of them stated the training program was good. Nobody was signed the ‘poor’ choice. It was found that there was no meaningful difference between the achievement ratios of the trainees and the learning status of the trainees when compared with the t test in the groups with success level of the operating room nursing certified course program according to the learning status of the participants (p ˃ 0,05). The trainees noted that the course was satisfied with theoretical and practical steps but the support services (lunch, coffee breaks etc.) were in adequate.

Keywords: certified courses, nursing certified courses, operating room nursing, training program

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Authors: Yu-Shan Hsu

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This paper studies a two-sector growth model with a technology of social constant returns and with a utility that features either a zero or a positive income effect on the demand for leisure. The purpose is to investigate how the existence of aggregate instability or equilibrium indeterminacy depends on both the intensity of the income effect on the demand for leisure and the value of the labor supply elasticity. The main finding is that when there is a factor intensity reversal between the private perspective and the social perspective, indeterminacy arises even if the utility has a positive income effect on leisure demand. Moreover, we find that a smaller value of the labor supply elasticity increases the range of the income effect on leisure demand and thus increases the possibility of equilibrium indeterminacy. JEL classification: E3; O41

Keywords: indeterminacy, non-separable preferences, income effect, labor supply elasticity

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Authors: Awotidebe Taofeek, Oyinsuyi Oluwafunmbi

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Psychosocial factors play a significant role in physical activity participation in diseased conditions and the general population. However, little is known about the role of exercise self-efficacy (ESE), exercise perceived barriers (EPB), and social support (SOS) in patients with asthma. This study investigated the influence of psychosocial factors on physical activity participation in patients with asthma in ile-ife. This cross-sectional study involved 130 patients with asthma. They were recruited from the Chest Clinic of the Obafemi Awolowo University Teaching Hospitals Complex, Ile-ife using purposive sampling technique. Ethical approval was obtained from the Ethics and Research Committee of the Obafemi Awolowo University Teaching Hospitals Complex, Ile-ife, Nigeria. Socio-demographic characteristics of respondents were recorded. Information on ESE, EPB, and SOS were obtained using Exercise Self-Efficacy, Exercise Benefit, and Barrier and Medical Outcome Social Support Scales respectively. Physical activity level was assessed in the last 7 days using international physical activity questionnaire. Descriptive and inferential statistics were used to analyze the data. Alpha level was set at p<0.5. The mean age of the respondents was 25.15 ± 9.38, and a majority, 110 (84.60%), engaged in low physical activity, 69(53%) had low exercise self-efficacy. However, less than two-third 80 (62.20%) reported high social support, with the majority of 95 (73.10%) reported high exercise perceived barriers. The means of ESE for male and femalerespondents were 29.01 ± 20.62 and 24.35 ± 17.36, respectively. The means of SOS formale and female respondents were 49.52 ± 22.22 and 61.87 ± 22.66, respectively. Themeans of EPB for male and female respondents were 53.37 ± 10.23 and 57.43 ± 9.65, respectively. The respondents were comparable in exercise self-efficacy and physicalactivity level (p>0.05). However, there were significant differences in social support (t=-2.791; p=0.006) and exercise perceived barriers (t=-2.108, p=0.037).Theresultsshowthattherewasasignificantrelationshipbetweenexerciseperceivedbarriersandlowphysicalactivitylevel(r=-0.216;p=0.023).TherewasasignificantassociationbetweenExerciseself-efficacyandmarried individuals(OR=0.967;95%CI=0.936-0.998;p= 0.037). Similarly, However,thereweresignificantassociationsbetweensocialsupport Andagegroup35-54years(OR=1.036;95%CI=1.007-1.067;p=0.014),females(OR= 1.024;95%CI=1.006;p=0.009)andmarriedindividuals(OR=1.049;95%CI=1.020-1.079. p=0.001).Therewasasignificantassociationbetweenexerciseperceivedbarriersand females(OR=1.043;95%CI=1.002-1.085;p=0.040).However, thereweresignificant associationsbetweenexerciseperceivedbarriersandoccupationgroup;civilservants (OR=1.092;95%CI=1.009-1.182;p=0.028),retiree(OR=1.092;95%CI=1.040-1.469;p= 0.016)andstudents(OR=1.110;95%CI=1.040;p=0.002). Inconclusion,agreaterpercentageofpatientswithasthmahadlowphysicalactivityleveland it was associatedwithhighexerciseperceivedbarriers,whileexerciseself-efficacyandsocialsupportwerenot.

Keywords: asthma, psychosocial factors, physical activity, physical fitness

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Authors: John Gibbs, Benjamin Flanders, Dylan Pozorski, Weixuan Liu

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Weight Painting–adjusting the influence a skeletal joint has on a given vertex in a character mesh–is an arduous and time con- suming part of the 3D animation pipeline. This process generally requires a trained technical animator and many hours of work to complete. Our skiNNer plug-in, which works within Autodesk’s Maya 3D animation software, uses Machine Learning and data pro- cessing techniques to create a deep neural network model that can accomplish the weight painting task in seconds rather than hours for bipedal quasi-humanoid character meshes. In order to create a properly trained network, a number of challenges were overcome, including curating an appropriately large data library, managing an arbitrary 3D mesh size, handling arbitrary skeletal architectures, accounting for extreme numeric values (most data points are near 0 or 1 for weight maps), and constructing an appropriate neural network model that can properly capture the high frequency alter- ation between high weight values (near 1.0) and low weight values (near 0.0). The arrived at neural network model is a cross between a traditional CNN, deep residual network, and fully dense network. The resultant network captures the unusually hard-edged features of a weight map matrix, and produces excellent results on many bipedal models.

Keywords: 3d animation, animation, character, rigging, skinning, weight painting, machine learning, artificial intelligence, neural network, deep neural network

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Authors: Goudjil kamel, Boukhatem Ghania, Jlailia Djihene

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This paper delves into the development of a sophisticated desktop application designed to calculate soil bearing capacity and predict limit pressure. Drawing from an extensive review of existing methodologies, the study meticulously examines various approaches employed in soil bearing capacity calculations, elucidating their theoretical foundations and practical applications. Furthermore, the study explores the burgeoning intersection of artificial intelligence (AI) and geotechnical engineering, underscoring the transformative potential of AI- driven solutions in enhancing predictive accuracy and efficiency.Central to the research is the utilization of cutting-edge machine learning techniques, including Artificial Neural Networks (ANN), XGBoost, and Random Forest, for predictive modeling. Through comprehensive experimentation and rigorous analysis, the efficacy and performance of each method are rigorously evaluated, with XGBoost emerging as the preeminent algorithm, showcasing superior predictive capabilities compared to its counterparts. The study culminates in a nuanced understanding of the intricate dynamics at play in geotechnical analysis, offering valuable insights into optimizing soil bearing capacity calculations and limit pressure predictions. By harnessing the power of advanced computational techniques and AI-driven algorithms, the paper presents a paradigm shift in the realm of geotechnical engineering, promising enhanced precision and reliability in civil engineering projects.

Keywords: limit pressure of soil, xgboost, random forest, bearing capacity

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Authors: Wenfu Zheng, Guanghe Zheng

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The discussion on the social sustainability in existing literature is limited to two-dimension epistemology space with only two elements: the human and nature. Using the revelation of the Bible God, the paper adds a moral component to the two-dimension space. With the new variable being introduced, the authors formulate a to three-dimension epistemology space and discuss its implications. Based on the space, the authors explore the hierarchical structure of order principles for a sustainable society. The social order principle system hierarchically consists of three principles: moral, relational, and rational. The justification of every principle is analyzed briefly. The paper concluded that all these order principles are necessary assurance of building a sustainable society.

Keywords: common grace, saving grace, sustainable society, the image of God

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Authors: Stephen Vera, Tabitha Black, Charalambos Cleanthous, Ryan Sain

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A gender comparison of USA commercial pilots’ demographics and views of CRM, social desirability and locus of control were surveyed. The Aviation safety locus of control (ASLOC) was used to measure external (ASLOC-E) or internal (ASLOC-I) aviation safety locus of control. The gender differences were explored using the ASLOC scores as a categorical variable. A differential comparison of crew resource management (CRM), based on the Federal Aviation Administration’s (FAA) guidelines was conducted. The results indicated that the proportion of female to male respondents matches the current ratio of USA commercial pilots. Moreover, there were no significant differences regarding overall education and the total number of communication classes one took. Regarding CRM issues, there were no significant differences on their views regarding the roles of the PIC, stress, time management, and managing a flight team. The females scored significantly lower on aeronautical decision making (ADM) and communications. There were no significant differences on either the Balanced Inventory of Desirable Responding (BIDR) impression management (IM) or self-deceptive enhancement (SDE). Although there were no overall significant differences on the ASLOC, the females did score higher on the internal subscale than did the males. An additional comparison of socially desirable responding indicates that all scores may be invalid, especially from the female respondents.

Keywords: social desirability, safety locus of control, crew resource management, commercial pilots

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Authors: Oluwaseun Ijiwade, Chris Davison, Kelvin Gregory

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In Australia, like other parts of the world, the debate on how to enhance teachers using assessment data to inform teaching and learning of English as an Additional Language (EAL, Australia) or English as a Foreign Language (EFL, United States) have occupied the centre of academic scholarship. Traditionally, this approach was conceptualised as ‘Formative Assessment’ and, in recent times, ‘Assessment for Learning (AfL)’. The central problem is that teacher-made tests are limited in providing data that can inform teaching and learning due to variability of classroom assessments, which are hindered by teachers’ characteristics and assessment literacy. To address this concern, scholars in language education and testing have proposed a uniformed large-scale computer-based assessment program to meet the needs of teachers and promote AfL in language education. In Australia, for instance, the Victoria state government commissioned a large-scale project called 'Tools to Enhance Assessment Literacy (TEAL) for Teachers of English as an additional language'. As part of the TEAL project, a tool called ‘Reading and Vocabulary assessment for English as an Additional Language (RVEAL)’, as a diagnostic language assessment (DLA), was developed by language experts at the University of New South Wales for teachers in Victorian schools to guide EAL pedagogy in the classroom. Therefore, this study aims to provide qualitative evidence for understanding beliefs about the diagnostic language assessment (DLA) among EAL teachers in primary and secondary schools in Victoria, Australia. To realize this goal, this study raises the following questions: (a) How do teachers use large-scale assessment data for diagnostic purposes? (b) What skills do language teachers think are necessary for using assessment data for instruction in the classroom? and (c) What factors, if any, contribute to teachers’ beliefs about diagnostic assessment in a large-scale assessment? Semi-structured interview method was used to collect data from at least 15 professional teachers who were selected through a purposeful sampling. The findings from the resulting data analysis (thematic analysis) provide an understanding of teachers’ beliefs about DLA in a classroom context and identify how these beliefs are crystallised in language teachers. The discussion shows how the findings can be used to inform professional development processes for language teachers as well as informing important factor of teacher cognition in the pedagogic processes of language assessment. This, hopefully, will help test developers and testing organisations to align the outcome of this study with their test development processes to design assessment that can enhance AfL in language education.

Keywords: beliefs, diagnostic language assessment, English as an additional language, teacher cognition

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Authors: Bongs Lainjo

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Educational institutions and authorities that are mandated to run education systems in various countries need to implement a curriculum that considers the possibility and existence of elementary school dropouts. This research focuses on elementary school dropout rates and the ability to replicate various predictive models carried out globally on selected Elementary Schools. The study was carried out by comparing the classical case studies in Africa, North America, South America, Asia and Europe. Some of the reasons put forward for children dropping out include the notion of being successful in life without necessarily going through the education process. Such mentality is coupled with a tough curriculum that does not take care of all students. The system has completely led to poor school attendance - truancy which continuously leads to dropouts. In this study, the focus is on developing a model that can systematically be implemented by school administrations to prevent possible dropout scenarios. At the elementary level, especially the lower grades, a child's perception of education can be easily changed so that they focus on the better future that their parents desire. To deal effectively with the elementary school dropout problem, strategies that are put in place need to be studied and predictive models are installed in every educational system with a view to helping prevent an imminent school dropout just before it happens. In a competency-based curriculum that most advanced nations are trying to implement, the education systems have wholesome ideas of learning that reduce the rate of dropout.

Keywords: elementary school, predictive models, machine learning, risk factors, data mining, classifiers, dropout rates, education system, competency-based curriculum

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Authors: Elena Chernyak

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The status of Russian women has changed dramatically over the course of Russian history and under different leadership and economic, political, and social conditions. The perception of women, their submissive roles, and low social status cause gender conflict that affects society: demographical issues, increased numbers of divorces, alcoholism, drug abuse, and crime. Despite the fact that around the world women are becoming more independent, protected by law, and play more important roles in society, Russian women are still dependent on men financially, socially, and psychologically. This paper critically explores the experience of Russian women over the course of over a thousand year of Russian history and how the position and image of women changed in Russian Empire, Soviet and post-Soviet Russia and what role women play in contemporary Russia. This paper is a result of deep examination of historical and religious literature, mass media, internet sources, and documents. This analysis shows that throughout history, the role and image of women in society have repeatedly varied depending on ideological and social conditions. In particular, the history of Russian women may be divided into five main periods. The first was the period of paganism, when almost all areas of life were open for women and when women were almost equal in social roles with men. During the second period, starting with the beginning of the Mongol invasion in the 13th century, the position of women was diminishing due to social transformation to the patriarchal society in which women started playing subordinate role in family and society. The third period – the period from the fourteenth through the sixteenth centuries - is a period of the total seclusion of Russian women from each part of social life. The fourth, Soviet period started after the Revolution of 1917. During that time, the position of women was drastically changed due to the transformation of traditional gender roles under the Bolshevik government. Woman's role was seen as worker-mothers who had a double duty: a worker and a mother. The final period began after the collapse of the Soviet Union. The restructuring (Perestroika) and post-Restructuring periods have had contradictory consequences and tremendous impact on Russian society. The image of women as partners and equal to men, which was promoted during the Soviet regime, has been replaced with the traditional functionalist views on family and the role of women, in which men and women have different but supposedly complementary roles. Modern Russia, despite publicly stating its commitment to equal rights, during last two decades has been reverting to an older social model with its emphasis on traditional gender roles, patriarchal ideas of dominant masculinity, and adverse attitudes to women, which are further supported and reinforced by the reviving Russian Orthodox Church. As demonstrated in this review, Russian women have never possessed the same rights as men and have always been subordinate to men. During all period of Russian history, patriarchal ideology maintained and reinforced in Russian society has always subjected women to manipulation, oppression, and victimization and portrayed women as not a ‘full human being’.

Keywords: women, Russia, patriarchy, religion, Russian Orthodox Church

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Authors: Kanika Gupta, Ashok Kumar

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Biofilms are dense, highly hydrated cell clusters that are irreversibly attached to a substratum, to an interface or to each other, and are embedded in a self-produced gelatinous matrix composed of extracellular polymeric substances. Research in biofilm field has become very significant, as biofilm has shown high mechanical resilience and resistance to antibiotic treatment and constituted as a significant problem in both healthcare and other industry related to microorganisms. The massive information both stated and hidden in the biofilm literature are growing exponentially therefore it is not possible for researchers and practitioners to automatically extract and relate information from different written resources. So, the current work proposes and discusses the use of text mining techniques for the extraction of information from biofilm literature corpora containing 34306 documents. It is very difficult and expensive to obtain annotated material for biomedical literature as the literature is unstructured i.e. free-text. Therefore, we considered unsupervised approach, where no annotated training is necessary and using this approach we developed a system that will classify the text on the basis of growth and development, drug effects, radiation effects, classification and physiology of biofilms. For this, a two-step structure was used where the first step is to extract keywords from the biofilm literature using a metathesaurus and standard natural language processing tools like Rapid Miner_v5.3 and the second step is to discover relations between the genes extracted from the whole set of biofilm literature using pubmed.mineR_v1.0.11. We used unsupervised approach, which is the machine learning task of inferring a function to describe hidden structure from 'unlabeled' data, in the above-extracted datasets to develop classifiers using WinPython-64 bit_v3.5.4.0Qt5 and R studio_v0.99.467 packages which will automatically classify the text by using the mentioned sets. The developed classifiers were tested on a large data set of biofilm literature which showed that the unsupervised approach proposed is promising as well as suited for a semi-automatic labeling of the extracted relations. The entire information was stored in the relational database which was hosted locally on the server. The generated biofilm vocabulary and genes relations will be significant for researchers dealing with biofilm research, making their search easy and efficient as the keywords and genes could be directly mapped with the documents used for database development.

Keywords: biofilms literature, classifiers development, text mining, unsupervised learning approach, unstructured data, relational database

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: deep learning, artificial neural networks, energy price forecasting, turkey

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Authors: Rabiatu Bonku, Faisal Alkaabneh

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Inspired by a food banks distribution operation for non-profit organization, we study a variant synchronized vehicle routing problem for equitable resource allocation. This research paper introduces a Mixed Integer Programming (MIP) model aimed at addressing the complex challenge of efficiently distributing vital resources, particularly for food banks serving vulnerable populations in urban areas. Our optimization approach places a strong emphasis on social equity, ensuring a fair allocation of food to partner agencies while minimizing wastage. The primary objective is to enhance operational efficiency while guaranteeing fair distribution and timely deliveries to prevent food spoilage. Furthermore, we assess four distinct models that consider various aspects of sustainability, including social and economic factors. We conduct a comprehensive numerical analysis using real-world data to gain insights into the trade-offs that arise, while also demonstrating the models’ performance in terms of fairness, effectiveness, and the percentage of food waste. This provides valuable managerial insights for food bank managers. We show that our proposed approach makes a significant contribution to the field of logistics optimization and social responsibility, offering valuable insights for improving the operations of food banks.

Keywords: food banks, humanitarian logistics, equitable resource allocation, synchronized vehicle routing

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Authors: Harry Einhorn

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This paper aims to explore the integration of Buddhism into educational settings with the goal of fostering the holistic development of children. By incorporating Buddhist principles and practices, educators can create a nurturing environment that cultivates wisdom, compassion, and ethical values in children. The teachings of Buddhism provide valuable insights into mindfulness, compassion, and critical thinking, which can be adapted and applied to educational curricula to enhance children's intellectual, emotional, and moral growth. One of the fundamental aspects of Buddhist philosophy that is particularly relevant to education is the concept of mindfulness. By introducing mindfulness practices, such as meditation and breathing exercises, children can learn to cultivate present-moment awareness, develop emotional resilience, and enhance their ability to concentrate and focus. These skills are essential for effective learning and can contribute to reducing stress and promoting overall well-being in children. Mindfulness practices can also teach children how to manage their emotions and thoughts, promoting self-regulation and creating a positive classroom environment. In addition to mindfulness, Buddhism emphasizes the cultivation of compassion and empathy toward all living beings. Integrating teachings on kindness, empathy, and ethical behavior into the educational framework can help children develop a deep sense of interconnectedness and social responsibility. By engaging children in activities that promote empathy and encourage acts of kindness, such as community service projects and cooperative learning, educators can foster the development of compassionate individuals who are actively engaged in creating a more harmonious and compassionate society. Moreover, Buddhist teachings encourage critical thinking and inquiry, which are crucial skills for intellectual development. By introducing children to fundamental Buddhist concepts such as impermanence, interdependence, and the nature of suffering, educators can engage them in philosophical reflections and broaden their perspectives on life. These teachings promote open-mindedness, curiosity, and a deeper understanding of the interconnectedness of all things. Through the exploration of these concepts, children can develop critical thinking skills and gain insights into the complexities of the world, enabling them to navigate challenges with wisdom and discernment. While integrating Buddhism into education requires sensitivity, cultural awareness, and respect for diverse beliefs and backgrounds, it holds great potential for nurturing the holistic development of children. By incorporating mindfulness practices, fostering compassion and empathy, and promoting critical thinking, Buddhism can contribute to the creation of a more compassionate, inclusive, and harmonious educational environment. This integration can shape well-rounded individuals who are equipped with the necessary skills and qualities to navigate the complexities of the modern world with wisdom, compassion, and resilience. In conclusion, the integration of Buddhism into education offers a valuable framework for cultivating wisdom, compassion, and ethical values in children. By incorporating mindfulness, compassion, and critical thinking into educational practices, educators can create a supportive environment that promotes children's holistic development. By nurturing these qualities, Buddhism can help shape individuals who are not only academically proficient but also morally and ethically responsible, contributing to a more compassionate and harmonious society.

Keywords: Buddhism, education, children, mindfulness

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Authors: Berfu Guley Goren, Ayse Lale Berkoz

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The aim of the study is to analyze the concept of universal design and accessibility to make the city which allows equality and independence for individuals. In the content of the study, literature researches and observations of samples in Istanbul, Turkey are analyzed. As a result proposals are going to be developed to create the cities which are designed for everyone. In globalization process, in cities, population have been increasing dramatically with social and economic activities. Medical developments have been effective in prolonging human life and the disability that comes with aging has also increased in parallel with the disabled population. Nowadays disability is an important phenomenon. Because approximately 1 billion people live with disabilities. The heterogeneous structure formed by the rapid gathering of individuals with different social, economic and physical characteristics in the cities creates great spatial diversity and richness in the cities with different needs brought together. Unlike the cultural and physical wealth in these places and the potential to integrate and diversify the urban people, unfortunately, the designs in practice cause the urban areas to break apart, the urbanities to tear themselves apart, to interfere with their communication and interactions. The social and physical structure of the city is important to feel belonging to the urban society. In most cities when an observation is made, obstructions for people with disabilities can be seen in urban physical structure and design. With these obstructions, people with disabilities cannot live in urban space, and they are desolated in urban life. The city, which offers equal opportunity, the relation between economic development, social justice and built environment must be planned synchronous. Isolation and stigmatization must be abolished by regulations, activities of awareness and universal urban design. Without regard to social, economical and physical features every individual has the same right, which is using the freedom of movement. Supporting freedom of movement of every individual may be ensured by universal design and its principles. So urban spaces are going to be for every individual. For equal opportunity in urban services, urban design must be the focus on every individual including people with disabilities. In built environment practices, democratic suitable spaces should be created. In this respect, urban planners, architects, political decision-makers and other relevant actors should work together and should think very versatile.

Keywords: disability, equality, universal design, urban design

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Authors: M. Kharrat, G. Moreau, Z. Aboura

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The latest advances in the weaving industry, combined with increasingly sophisticated means of materials processing, have made it possible to produce complex 3D composite structures. Mainly used in aeronautics, composite materials with 3D architecture offer better mechanical properties than 2D reinforced composites. Nevertheless, these materials require a good understanding of their behavior. Because of the complexity of such materials, the damage mechanisms are multiple, and the scenario of their appearance and evolution depends on the nature of the exerted solicitations. The AE technique is a well-established tool for discriminating between the damage mechanisms. Suitable sensors are used during the mechanical test to monitor the structural health of the material. Relevant AE-features are then extracted from the recorded signals, followed by a data analysis using pattern recognition techniques. In order to better understand the damage scenarios of interlock composite materials, a multi-instrumentation was set-up in this work for tracking damage initiation and development, especially in the vicinity of the first significant damage, called macro-damage. The deployed instrumentation includes video-microscopy, Digital Image Correlation, Acoustic Emission (AE) and micro-tomography. In this study, a multi-variable AE data analysis approach was developed for the discrimination between the different signal classes representing the different emission sources during testing. An unsupervised classification technique was adopted to perform AE data clustering without a priori knowledge. The multi-instrumentation and the clustered data served to label the different signal families and to build a learning database. This latter is useful to construct a supervised classifier that can be used for automatic recognition of the AE signals. Several materials with different ingredients were tested under various solicitations in order to feed and enrich the learning database. The methodology presented in this work was useful to refine the damage threshold for the new generation materials. The damage mechanisms around this threshold were highlighted. The obtained signal classes were assigned to the different mechanisms. The isolation of a 'noise' class makes it possible to discriminate between the signals emitted by damages without resorting to spatial filtering or increasing the AE detection threshold. The approach was validated on different material configurations. For the same material and the same type of solicitation, the identified classes are reproducible and little disturbed. The supervised classifier constructed based on the learning database was able to predict the labels of the classified signals.

Keywords: acoustic emission, classifier, damage mechanisms, first damage threshold, interlock composite materials, pattern recognition

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Authors: Sohail Ahmad Umer

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Since last few decades a question is raising on the subject of the importance of women in different societies of the world particularly in the developing societies of Asia and Africa. Female population constitutes almost 50% of the total population of the world and is playing a significant role in the economy with male population. In Pakistan, a developing country of Asia with majority of Muslim population, working women role is more focused. Women of rural background who are working as voluntary workers and their working hours are neither recorded nor recognized. Agricultural statistics shows that the female participation rate is below 40% while other sources claim them below 20%. Here in present study, another effort has been made to compare the women role in two different provinces of Pakistan to analyze the participation of women in agricultural activities like sowing, picking, irrigating the fields, harvesting and threshing of crops, caring and feeding of the animals, collecting the firewood and etc,as without these activities the farming would be incomplete. One hundred villages in the district Khushab (Punjab) and one hundred villages in district D.I.Khan (KPK) were selected and 33% of the families of each village have been interviewed to study their input in agriculture work. Another important feature is the social stratification therefore the contribution by different variables like the ownership, tenancy, education and caste has also been studied.

Keywords: caste, social stratification, tenancy, voluntary workers

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Authors: Majid Omidikhankahdani, Maryam Omidikhankahdani

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Chabahar city located southeast of Iran and is one of strategic regional port in Oman sea aim of this study was measuring Chabahar city resident perceptions about tourism positive and negative effect. 322 participants selected via random sampling and fill questionnaire about their attitude toward tourism economic, social cultural and environment positive and negative impact. the result showed perspective of resident tourism have more positive effect than negative effect, also pair sample t test showed significant difference between positive and negative effect of tourism in favor positive effect.

Keywords: tourism economic effect, tourism environment, residents attitude, tourism social-cultural

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Authors: Chung Danbi, Linton Oliver, Whang Yoon-Jae

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Supermodularity, or complementarity, is a popular concept in economics which can characterize many objective functions such as utility, social welfare, and production functions. Further, supermodular dominance captures a preference for greater interdependence among inputs of those functions, and it can be applied to examine which input set would produce higher expected utility, social welfare, or production. Therefore, we propose and justify a consistent testing for a useful implication of supermodular dominance. We also conduct Monte Carlo simulations to explore the finite sample performance of our test, with critical values obtained from the recentered bootstrap method, with and without the selective recentering, and the subsampling method. Under various parameter settings, we confirmed that our test has reasonably good size and power performance. Finally, we apply our test to compare the geographic and distant knowledge spillover in terms of their effects on social welfare using the National Bureau of Economic Research (NBER) patent data. We expect localized citing to supermodularly dominate distant citing if the geographic knowledge spillover engenders greater social welfare than distant knowledge spillover. Taking subgroups based on firm and patent characteristics, we found that there is industry-wise and patent subclass-wise difference in the pattern of supermodular dominance between localized and distant citing. We also compare the results from analyzing different time periods to see if the development of Internet and communication technology has changed the pattern of the dominance. In addition, to appropriately deal with the sparse nature of the data, we apply high-dimensional methods to efficiently select relevant data.

Keywords: supermodularity, supermodular dominance, stochastic dominance, Monte Carlo simulation, bootstrap, subsampling

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Authors: Sara Dalma Galgoczi, Judith Gabriella Kengyel

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Sex scandals are quite an engaging topic to work with, especially with their judgment in society. Most people are interested in other people's lives, specifically in public figures' such as celebrities or politicians, because ordinary people feel like they have the right to know more things about the famous and notorious ones than they would probably willing to share. Intimacy and sexual acts aren't exceptions; moreover, sexuality is one of the central interests of humans ever since. Besides, knowing and having an opinion about any kind of scandal can change even whole social groups or classes estimation of anyone. This study aims to research the social judgment of some Hungarian politicians' sex scandals and asks important questions like diverse public opinions in the light of gender or delegates’ abuse of power. Considering that this study is about collecting and evaluating opinions from the public, and no one before researched and published this exact topic and cases, an online survey was created. In the survey were different sections. We collected data about party-preference, conservativism-liberalism scale; then we used the following questionnaires: from Zero-sum perspective with regard to gender equality (Ruthig, Kehn, Gamblin, Vanderzanden & Jones, 2017), Ambivalent Sexism Inventory (ASI; Glick & Fiske, 1996), Ambivalence Toward Men Inventory (AMI; Glick & Fiske, 1999). Finally, 5 short summaries were presented about five Hungarian politicians' sex scandal cases (3 males, 2 females) from the recent past. These stories were followed by questions about their opinion of the party and attitudes towards the parties' reactions to the cases. We came to the conclusion that people are more permissive with the scandals of men, and benevolent sexism and ambivalence towards men mediate this relation. Men tend to see these cases as part of politicians' private lives more than women. Party preference had a significant effect - people tend to pass a sentence the delegates of the opposing parties, and they rather release the delegates of their preferred party.

Keywords: sex scandal, sexism, social judgement, politician

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Authors: Jesvin Puay-Hwa Yeo, Laavanya Kathiravelu, Sa’Eda Binte Buang

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In the early days, myths and taboos were used by our ancestors to give explanations to the existence of nature and man, as well as to propitiate fortunes and to avoid unluckiness and harm. Myths and taboos are deeply rooted in our cultures and environment, and they form certain characteristics of any society, even in modern societies. With decades of the three main ethnic communities in Singapore – Malay, Indian and Chinese – living together, there has been intermingling and intermixing of traditions and practices. This may mean that what we think is a ‘Malay’ practice is actually one that is a hybrid of the Chinese and Malay. A good example would be the practice of covering all mirrors in a house of mourning. Therefore, the proposed seeks to explore and understand the underlying social influences of Singapore’s oral tradition. As part of a bigger cultural research project: Designing Cultures, the proposed paper focused on using secondary data to contribute to the overall cultural understanding of the integral connections between oral traditions, people and landscapes. The proposed paper will discuss in details the initials findings of the research project, including the two manners that contributed to the intermixing of myths and taboos. The first is the presence of social institutions such as religions, and the second is the presence of cross-cultural minorities such as the Straits Chinese. As well as other observations included the use and influence of Chinese oral traditions such as folklore among the early Chinese immigrants through social institutions.

Keywords: cultural belief, multiracial society, myths, oral tradition

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Authors: Martin Lauzier, Benjamin Lafreniere-Carrier, Nathalie Delobbe

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Supervisor support is one of the main levers to foster transfer of training. Although past and current studies voice its effects, few have sought to identify the factors that may explain why supervisors offer support to their subordinates when they return from training. Based on Goal Orientation Theory and following the principles of supportive supervision, this study aims to improve our understanding of the factors that influence supervisors’ involvement in the transfer process. More specifically, this research seeks to verify the influence of supervisors’ goal orientation on the adoption of post-training support behaviors. This study also assesses the mediating role of the supervisors’ interest in subordinates’ development on this first relationship. Conducted in two organizations (Canadian: N₁ = 292; Belgian: N₂ = 80), the results of this study revealed three main findings. First, supervisors’ who adopt learning mastery goal orientation also tend to adopt more post-training supportive behaviors. Secondly, regression analyses (using the bootstrap method) show that supervisors' interest in developing their subordinates’ skills mediate the relationship between supervisors’ goal orientation and post-training supportive behaviors. Thirdly, the observed mediation effects are consistent in both samples, regardless of supervisors’ gender or age. Overall, this research is part of the limited number of studies that have focused on the determining factors supervisors’ involvement in the learning transfer process.

Keywords: supervisor support, transfer of training, goal orientation, interest in the development of subordinates’ skills

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Authors: Gaurav Kumar Sinha

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The oil refining industry, significant in its energy consumption and carbon emissions, faces increasing pressure to reduce its environmental footprint. This article explores the application of energy efficiency and sustainability analytics as crucial tools for reducing carbon emissions in oil refineries. Through a comprehensive review of current practices and technologies, this study highlights innovative analytical approaches that can significantly enhance energy efficiency. We focus on the integration of advanced data analytics, including machine learning and predictive modeling, to optimize process controls and energy use. These technologies are examined for their potential to not only lower energy consumption but also reduce greenhouse gas emissions. Additionally, the article discusses the implementation of sustainability analytics to monitor and improve environmental performance across various operational facets of oil refineries. We explore case studies where predictive analytics have successfully identified opportunities for reducing energy use and emissions, providing a template for industry-wide application. The challenges associated with deploying these analytics, such as data integration and the need for skilled personnel, are also addressed. The paper concludes with strategic recommendations for oil refineries aiming to enhance their sustainability practices through the adoption of targeted analytics. By implementing these measures, refineries can achieve significant reductions in carbon emissions, aligning with global environmental goals and regulatory requirements.

Keywords: energy efficiency, sustainability analytics, carbon emissions, oil refineries, data analytics, machine learning, predictive modeling, process optimization, greenhouse gas reduction, environmental performance

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Authors: Duncan Wallace, M-Tahar Kechadi

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In recent years, Machine Learning (ML) approaches have been successfully applied to an analysis of patient symptom data in the context of disease diagnosis, at least where such data is well codified. However, much of the data present in Electronic Health Records (EHR) are unlikely to prove suitable for classic ML approaches. Furthermore, as scores of data are widely spread across both hospitals and individuals, a decentralized, computationally scalable methodology is a priority. The focus of this paper is to develop a method to predict outliers in an out-of-hours healthcare provision center (OOHC). In particular, our research is based upon the early identification of patients who have underlying conditions which will cause them to repeatedly require medical attention. OOHC act as an ad-hoc delivery of triage and treatment, where interactions occur without recourse to a full medical history of the patient in question. Medical histories, relating to patients contacting an OOHC, may reside in several distinct EHR systems in multiple hospitals or surgeries, which are unavailable to the OOHC in question. As such, although a local solution is optimal for this problem, it follows that the data under investigation is incomplete, heterogeneous, and comprised mostly of noisy textual notes compiled during routine OOHC activities. Through the use of Deep Learning methodologies, the aim of this paper is to provide the means to identify patient cases, upon initial contact, which are likely to relate to such outliers. To this end, we compare the performance of Long Short-Term Memory, Gated Recurrent Units, and combinations of both with Convolutional Neural Networks. A further aim of this paper is to elucidate the discovery of such outliers by examining the exact terms which provide a strong indication of positive and negative case entries. While free-text is the principal data extracted from EHRs for classification, EHRs also contain normalized features. Although the specific demographical features treated within our corpus are relatively limited in scope, we examine whether it is beneficial to include such features among the inputs to our neural network, or whether these features are more successfully exploited in conjunction with a different form of a classifier. In this section, we compare the performance of randomly generated regression trees and support vector machines and determine the extent to which our classification program can be improved upon by using either of these machine learning approaches in conjunction with the output of our Recurrent Neural Network application. The output of our neural network is also used to help determine the most significant lexemes present within the corpus for determining high-risk patients. By combining the confidence of our classification program in relation to lexemes within true positive and true negative cases, with an inverse document frequency of the lexemes related to these cases, we can determine what features act as the primary indicators of frequent-attender and non-frequent-attender cases, providing a human interpretable appreciation of how our program classifies cases.

Keywords: artificial neural networks, data-mining, machine learning, medical informatics

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