Search results for: students’ learning achievements

Authors: R. A. S. Zacarias

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Interlingual is one of the most complex, and engaging one among the several perspectives in lexicography. This is because it involves contacts and contrasts between two or more languages. Considering the fact that translation equivalence goes beyond a mere fixed relation of correspondence, understanding the differences and similarities between linguistic categories by pairs of languages is the basis for effective translations. One of the theoretical approaches that have proved useful in finding improved solutions for enhance translation equivalents for bilingual dictionaries is contrastive linguistics. This paper presents an applied qualitative research based on exploratory and descriptive approaches. This is achieved through an error analysis of students’ errors as well as by a contrastive analysis of Portuguese and English verb systems.

Keywords: bilingual lexicography, contrastive linguistics, translation equivalent, Portuguese-English

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Authors: Nouf Nasser, Nada Alotaibi, Jazzal Kandiel

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This research study is about the use of artificial intelligence in PhotoRoom. When an individual selects a photo, PhotoRoom automagically removes or separates the background from other parts of the photo through the use of artificial intelligence. This will allow an individual to select their desired background and edit it as they wish. The methodology used was an observation, where various reviews and parts of the app were observed. The review section's findings showed that many people actually like the app, and some even rated it five stars. The conclusion was that PhotoRoom is one of the best photo editing apps due to its speed and accuracy in removing backgrounds.

Keywords: removing background, app, artificial intelligence, machine learning

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Authors: Rica Jell de Laza, Jose Alberto Fernandez, Andrea Marie Mendoza, Qristin Jeuel Regalado

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This study investigates whether participants experience different levels of persuasion depending on the hemisphere of the brain and the tone of voice. The experiment was performed on 96 volunteer undergraduate students taking an introductory course in psychology. The participants took part in a 2 x 3 (Hemisphere: left, right x Tone of Voice: positive, neutral, negative) Mixed Factorial Design to measure how much a person was persuaded. Results showed that the hemisphere of the brain and the tone of voice used did not significantly affect the results individually. Furthermore, there was no interaction effect. Therefore, the hemispheres of the brain and the tone of voice employed play insignificant roles in persuading a person.

Keywords: dichotic listening, brain hemisphere, tone of voice, persuasion

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Authors: Japhet Asanji

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The bases of this research were to explore student’s perception of home background and the acquisition of English Language in Mbonge Municipality by examining how financial status, level of education, marital status and parenting styles of their parents influence English Language Acquisition. Using random sampling techniques, closed-ended questionnaires were administered to 60 students, and the data was analysed using descriptive statistical analysis. The results reaffirm the positive relationship between student’s perception of home background and the acquisition of English language. Contributions, limitations, and direction for further research are also discussed.

Keywords: student, home background, English language acquisition, Cameroon

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Authors: Malathi Iyer, Jayesh Vaidya

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The demographic dividend of India will last for thirty years from now. However, reduction in birth rate, an increase in working population, improvements in medicine and better health practices lead to an ever-expanding elderly population, bringing additional burden to the economy and putting an end to the demographic dividend. To reap the dividend India needs to train the youth for employability. The need of the hour is to improve their life skills which lead the youth to become industrious and have continuous employment. The study will be conducted in perceiving the skill gaps that exist in commerce students for employability. The analysis results indicate the relation between the core study and the right skills for the workforce, with the steps that are taken to open the window for the demographic dividend.

Keywords: demographic dividend, life skills, employability, workforce

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Authors: Lori Lioce, Gary Maddux, Norven Goddard, Ishella Fogle, Bernard Schroer

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This paper presents the integration of technologies into nursing education. The collaborative effort includes the College of Nursing (CoN) at the University of Alabama in Huntsville (UAH) and the UAH Systems Management and Production Center (SMAP). The faculty at the CoN conducts needs assessments to identify education and training requirements. A team of CoN faculty and SMAP engineers then prioritize these requirements and establish improvement/development teams. The development teams consist of nurses to evaluate the models and to provide feedback and of undergraduate engineering students and their senior staff mentors from SMAP. The SMAP engineering staff develops and creates the physical models using 3D printing, silicone molds and specialized molding mixtures and techniques. The collaboration has focused on developing teaching and training, or clinical, simulators. In addition, the onset of the Covid-19 pandemic has intensified this relationship, as 3D modeling shifted to supplied personal protection equipment (PPE) to local health care providers. A secondary collaboration has been introducing students to clinical benchmarking through the UAH Center for Management and Economic Research. As a result of these successful collaborations the Model Exchange & Development of Nursing & Engineering Technology (MEDNET) has been established. MEDNET seeks to extend and expand the linkage between engineering and nursing to K-12 schools, technical schools and medical facilities in the region to the resources available from the CoN and SMAP. As an example, stereolithography (STL) files of the 3D printed models, along with the specifications to fabricate models, are available on the MEDNET website. Ten 3D printed models have been developed and are currently in use by the CoN. The following additional training simulators are currently under development:1) suture pads, 2) gelatin wound models and 3) printed wound tattoos. Specification sheets have been written for these simulations that describe the use, fabrication procedures and parts list. These specifications are available for viewing and download on MEDNET. Included in this paper are 1) descriptions of CoN, SMAP and MEDNET, 2) collaborative process used in product improvement/development, 3) 3D printed models of training and teaching simulators, 4) training simulators under development with specification sheets, 5) family care practice benchmarking, 6) integrating the simulators into the nursing curriculum, 7) utilizing MEDNET as a pandemic response, and 8) conclusions and lessons learned.

Keywords: 3D printing, nursing education, simulation, trainers

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Authors: Fadzayi M.Maruza

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The conversation about diversity in the African academy focuses on the need for an international and ethnically diverse population of scholars and students. Operationalising the concept of cognitive diversity offers us an opportunity to broaden our conception of who can know and who can proclaim knowledge by availing new understandings of what knowledge is and how it is made. Limited attention is paid to the value of diversity generated by cognitive disabilities in the African academy. The inclusion of persons with minds labelled disabled in African academia requires an epistemology of disability to reform the still dominant notion of the expert and scholar as an able-bodied and hyper-rational in African academia. This review wants to explore how cognitive disabilities have been represented in higher education research in Africa or has the African academy reinforced ignorance by promoting an able-bodied academia. The review aims to tackle its exploratory objective by using Malcom Tights framework. The main questions this paper would focus on are: (I)What are the major disability themes and concerns discussed in the disability-related articles? (II)What are the major methods or methodologies used to address the topic in the papers? (III)What are the levels of analysis the papers focus on? (IV)How do higher education researchers define and represent cognitive disabilities in higher education research in Africa? To answer the exploratory questions that are aimed at mapping the disability-related higher education research landscape, Malcolm Tights’ framework is seen as most appropriate. In addition to a thematic categorization, that shall be made after reviewing of published empirical studies on disability in African higher education from the period 2010 – 2017. A synthesis of the findings and implications of African disability studies relating to students with cognitive disabilities in the African Academy will be provided using the categories suggested by Tight as a benchmark. Data for the proposed work shall be taken from well-reputed higher education journals between 2010 and 2017.Using the keyword ‘Disability’ in the titles, abstracts and keywords section of journal articles, a selection of disability-focused higher education articles shall be compiled for analysis regarding cognitive disability. It has to be noted as a limitation that the word Disability might not be sufficient to investigate the topic for there can be many more specific disabilities concerns the researchers would discuss. Therefore, the paper is only intended to give a bird’s eye view of cognitive disability in higher education research and therefore is not comprehensive. The paper is expected to shed some light for me, as a beginning researcher, and other researchers like myself as to what has been the focus of higher education researchers about cognitive disability in the African academy. Keywords: Cognitive diversity, cognitive disability, disability, higher education.

Keywords: cognitive disability, cognitive diversity, disability, higher education

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Authors: Songdi Li, Louise Spry, Tony Woodall

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Nowadays, Corporate Social responsibility (CSR) is becoming a buzz word, and more and more academics are putting efforts on CSR studies. It is believed that CSR could influence Corporate Reputation (CR), and they hold a favourable view that CSR leads to a positive CR. To be specific, the CSR related activities in the reputational context have been regarded as ways that associate to excellent financial performance, value creation, etc. Also, it is argued that CSR and CR are two sides of one coin; hence, to some extent, doing CSR is equal to establishing a good reputation. Still, there is no consensus of the CSR-CR relationship in the literature; thus, a systematic literature review is highly in need. This research conducts a systematic literature review with both bibliometric and content analysis. Data are selected from English language sources, and academic journal articles only, then, keyword combinations are applied to identify relevant sources. Data from Scopus and WoS are gathered for bibliometric analysis. Scopus search results were saved in RIS and CSV formats, and Web of Science (WoS) data were saved in TXT format and CSV formats in order to process data in the Bibexcel software for further analysis which later will be visualised by the software VOSviewer. Also, content analysis was applied to analyse the data clusters and the key articles. In terms of the topic of CSR-CR, this literature review with bibliometric analysis has made four achievements. First, this paper has developed a systematic study which quantitatively depicts the knowledge structure of CSR and CR by identifying terms closely related to CSR-CR (such as ‘corporate governance’) and clustering subtopics emerged in co-citation analysis. Second, content analysis is performed to acquire insight on the findings of bibliometric analysis in the discussion section. And it highlights some insightful implications for the future research agenda, for example, a psychological link between CSR-CR is identified from the result; also, emerging economies and qualitative research methods are new elements emerged in the CSR-CR big picture. Third, a multidisciplinary perspective presents through the whole bibliometric analysis mapping and co-word and co-citation analysis; hence, this work builds a structure of interdisciplinary perspective which potentially leads to an integrated conceptual framework in the future. Finally, Scopus and WoS are compared and contrasted in this paper; as a result, Scopus which has more depth and comprehensive data is suggested as a tool for future bibliometric analysis studies. Overall, this paper has fulfilled its initial purposes and contributed to the literature. To the author’s best knowledge, this paper conducted the first literature review of CSR-CR researches that applied both bibliometric analysis and content analysis; therefore, this paper achieves its methodological originality. And this dual approach brings advantages of carrying out a comprehensive and semantic exploration in the area of CSR-CR in a scientific and realistic method. Admittedly, its work might exist subjective bias in terms of search terms selection and paper selection; hence triangulation could reduce the subjective bias to some degree.

Keywords: corporate social responsibility, corporate reputation, bibliometric analysis, software program

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Authors: Jadwiga Fila, Mateusz Jezowski, Pawel Poszytek

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The outbreak of the global COVID-19 pandemic started the times of crisis full of uncertainty, especially in the field of transnational cooperation projects based on the international mobility of their participants. This is notably the case of Erasmus+ Program for higher education, which is the flagship European initiative boosting cooperation between educational institutions, businesses, and other actors, enabling students and staff mobility, as well as strategic partnerships between different parties. The aim of this abstract is to study whether competences 4.0 are able to empower Erasmus+ project leaders in sustaining their international cooperation in times of global crisis, widespread online learning, and common project disruption or cancellation. The concept of competences 4.0 emerged from the notion of the industry 4.0, and it relates to skills that are fundamental for the current labor market. For the aim of the study presented in this abstract, four main 4.0 competences were distinguished: digital, managerial, social, and cognitive competence. The hypothesis for the study stipulated that the above-mentioned highly-developed competences may act as a protective shield against the pandemic challenges in terms of projects’ sustainability and continuation. The objective of the research was to assess to what extent individual competences are useful in managing projects in times of crisis. For this purpose, the study was conducted, involving, among others, 141 Polish higher education project leaders who were running their cooperation projects during the peak of the COVID-19 pandemic (Mar-Nov 2020). The research explored the self-perception of the above-mentioned competences among Erasmus+ project leaders and the contextual data regarding the sustainability of the projects. The quantitative character of data permitted validation of scales (Cronbach’s Alfa measure), and the use of factor analysis made it possible to create a distinctive variable for each competence and its dimensions. Finally, logistic regression was used to examine the association of competences and other factors on project status. The study shows that the project leaders’ competence profile attributed the highest score to digital competence (4.36 on the 1-5 scale). Slightly lower values were obtained for cognitive competence (3.96) and managerial competence (3.82). The lowest score was accorded to one specific dimension of social competence: adaptability and ability to manage stress (1.74), which proves that the pandemic was a real challenge which had to be faced by project coordinators. For higher education projects, 10% were suspended or prolonged because of the COVID-19 pandemic, whereas 90% were undisrupted (continued or already successfully finished). The quantitative analysis showed a positive relationship between the leaders’ levels of competences and the projects status. In the case of all competences, the scores were higher for project leaders who finished projects successfully than for leaders who suspended or prolonged their projects. The research demonstrated that, in the demanding times of the COVID-19 pandemic, competences 4.0, to a certain extent, do play a significant role in the successful management of Erasmus+ projects. The implementation and sustainability of international educational projects, despite mobility and sanitary obstacles, depended, among other factors, on the level of leaders’ competences.

Keywords: Competences 4.0, COVID-19 pandemic, Erasmus+ Program, international education, project sustainability

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Authors: T. Bryan , V. Kepuska, I. Kostnaic

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A method of data compression and denoising is introduced that is based on atomic decomposition of audio data using “basis vectors” that are learned from the audio data itself. The basis vectors are shown to have higher data compression and better signal-to-noise enhancement than the Gabor and gammatone “seed atoms” that were used to generate them. The basis vectors are the input weights of a Sparse AutoEncoder (SAE) that is trained using “envelope samples” of windowed segments of the audio data. The envelope samples are extracted from the audio data by performing atomic decomposition with Gabor or gammatone seed atoms. This process identifies segments of audio data that are locally coherent with the seed atoms. Envelope samples are extracted by identifying locally coherent audio data segments with Gabor or gammatone seed atoms, found by matching pursuit. The envelope samples are formed by taking the kronecker products of the atomic envelopes with the locally coherent data segments. Oracle signal-to-noise ratio (SNR) verses data compression curves are generated for the seed atoms as well as the basis vectors learned from Gabor and gammatone seed atoms. SNR data compression curves are generated for speech signals as well as early American music recordings. The basis vectors are shown to have higher denoising capability for data compression rates ranging from 90% to 99.84% for speech as well as music. Envelope samples are displayed as images by folding the time series into column vectors. This display method is used to compare of the output of the SAE with the envelope samples that produced them. The basis vectors are also displayed as images. Sparsity is shown to play an important role in producing the highest denoising basis vectors.

Keywords: sparse dictionary learning, autoencoder, sparse autoencoder, basis vectors, atomic decomposition, envelope sampling, envelope samples, Gabor, gammatone, matching pursuit

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Authors: Luis Amador Jimenez, Md. Shohel Amin

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Pavement performance models are based on projections of observed traffic loads, which makes uncertain to study funding strategies in the long run if history does not repeat. Neural networks can be used to estimate deterioration rates but the learning rate and momentum have not been properly investigated, in addition, economic evolvement could change traffic flows. This study addresses both issues through a case study for roads of Montreal that simulates traffic for a period of 50 years and deals with the measurement error of the pavement deterioration model. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. Accumulated equivalent single axle loads (ESALs) are calculated from the predicted AADT and locally observed truck distributions combined with truck factors. A back propagation Neural Network (BPN) method with a Generalized Delta Rule (GDR) learning algorithm is applied to estimate pavement deterioration models capable of overcoming measurement errors. Linear programming of lifecycle optimization is applied to identify M&R strategies that ensure good pavement condition while minimizing the budget. It was found that CAD 150 million is the minimum annual budget to good condition for arterial and local roads in Montreal. Montreal drivers prefer the use of public transportation for work and education purposes. Vehicle traffic is expected to double within 50 years, ESALS are expected to double the number of ESALs every 15 years. Roads in the island of Montreal need to undergo a stabilization period for about 25 years, a steady state seems to be reached after.

Keywords: pavement management system, traffic simulation, backpropagation neural network, performance modeling, measurement errors, linear programming, lifecycle optimization

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Authors: Z. Abdullah, A. R. Hamdan

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Clustering is a process of grouping objects and data into groups of clusters to ensure that data objects from the same cluster are identical to each other. Clustering algorithms in one of the areas in data mining and it can be classified into partition, hierarchical, density based, and grid-based. Therefore, in this paper, we do a survey and review for four major hierarchical clustering algorithms called CURE, ROCK, CHAMELEON, and BIRCH. The obtained state of the art of these algorithms will help in eliminating the current problems, as well as deriving more robust and scalable algorithms for clustering.

Keywords: clustering, unsupervised learning, algorithms, hierarchical

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Authors: Akanksha Bhatnagar, Sandhya Kortegare, Felice Elefant

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Context: Alzheimer's disease (AD) is a neurodegenerative disorder that is characterized by progressive cognitive decline and memory loss. The cause of AD is not fully understood, but it is thought to be caused by a combination of genetic, environmental, and lifestyle factors. One of the hallmarks of AD is the loss of neurons in the hippocampus, a brain region that is important for memory and learning. This loss of neurons is thought to be caused by a decrease in histone acetylation, which is a process that regulates gene expression. Research Aim: The research aim of the study was to develop mall molecule compounds that can enhance the activity of Tip60, a histone acetyltransferase that is important for memory and learning. Methodology/Analysis: The researchers used in silico structural modeling and a pharmacophore-based virtual screening approach to design and synthesize small molecule compounds strongly predicted to target and enhance Tip60’s HAT activity. The compounds were then tested in vitro and in vivo to assess their ability to enhance Tip60 activity and rescue cognitive deficits in AD models. Findings: The researchers found that several of the compounds were able to enhance Tip60 activity and rescue cognitive deficits in AD models. The compounds were also developed to cross the blood-brain barrier, which is an important factor for the development of potential AD therapeutics. Theoretical Importance: The findings of this study suggest that Tip60 HAT activators have the potential to be developed as therapeutic agents for AD. The compounds are specific to Tip60, which suggests that they may have fewer side effects than other HDAC inhibitors. Additionally, the compounds are able to cross the blood-brain barrier, which is a major hurdle for the development of AD therapeutics. Data Collection: The study collected data from a variety of sources, including in vitro assays and animal models. The in vitro assays assessed the ability of compounds to enhance Tip60 activity using histone acetyltransferase (HAT) enzyme assays and chromatin immunoprecipitation assays. Animal models were used to assess the ability of the compounds to rescue cognitive deficits in AD models using a variety of behavioral tests, including locomotor ability, sensory learning, and recognition tasks. The human clinical trials will be used to assess the safety and efficacy of the compounds in humans. Questions: The question addressed by this study was whether Tip60 HAT activators could be developed as therapeutic agents for AD. Conclusions: The findings of this study suggest that Tip60 HAT activators have the potential to be developed as therapeutic agents for AD. The compounds are specific to Tip60, which suggests that they may have fewer side effects than other HDAC inhibitors. Additionally, the compounds are able to cross the blood-brain barrier, which is a major hurdle for the development of AD therapeutics. Further research is needed to confirm the safety and efficacy of these compounds in humans.

Keywords: Alzheimer's disease, cognition, neuroepigenetics, drug discovery

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Authors: Niraimathi Kesavan, Sangeeta Sharma, Deepa Jagan, Sridhar Sukumar, Mohan Ramachandran, Vidhubala Elangovan

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Background: Childhood is a dynamic period for growth and development. Optimum nutrition during this period forms a strong foundation for growth, development, resistance to infections, long-term good health, cognition, educational achievements, and work productivity in a later phase of life. Underprivileged children living in a resource constraint settings like shelter homes are at high risk of malnutrition due to poor quality diet and nutritional inadequacy. In low-income countries, underprivileged children are vulnerable to being deprived of nutritious food, which stands as a major challenge in the health sector. The present aims to assess the dietary intake, nutritional status, and nutritional inadequacy and their association with malnutrition among children residing in shelter homes in rural Tamil Nadu. Methods: The study was a descriptive survey conducted among all the children aged between 8-18 years residing in two selected shelter homes (Anbu illam, a home for female children, and Amaidhi illam, a home for male children), rural Tirunelveli, Tamil Nadu, India. A total of 57 children were recruited, including 18 boys and 39 girls, for the study. Dietary intake was measured using seven days 24 hours recall. The average nutrient intake was considered for further analysis. Results: Of the 57 children, about 60% (n=35) were undernutrition. The mean daily energy intake was 1298 (SD 180) kcal for boys and 952 (SD155) kcal for girls. The total calorie intake was 55-60% below the estimated average requirement (EAR) for adolescent boys and girls in the age group 13-15 years and 16-18 years. Carbohydrates were the major source of energy (boys 53% and girls 51%), followed by fat (boys 31.5% and girls 34.5%) and protein (boys 14% and girls 12.9%). Dairy intake (<200ml/day) was less than the recommendation (500ml/day). Micro-nutrient-rich foods such as fruits, vegetables, and green leafy vegetables in the diet were <200g/day, which was far less than the recommended dietary guidelines of 400g- 600g/day for the age group of 7-18 years. Nearly 26% of girls reported experiencing menstrual problems. The majority (76.9%) of the children exhibited nutrient deficiency-related signs and symptoms. Conclusion: The total energy, minerals, and micro-nutrient intake were inadequate and below the Recommended Dietary Allowance for children and adolescents. The diet predominantly consists of refined cereals, rice, semolina, and vermicelli. Consumption of whole grains, milk, fruits, vegetables, and leafy vegetables was far below the recommended dietary guidelines. Dietary inadequacies among these children pose a serious concern for their overall health status and its consequences in the later phase of life.

Keywords: adolescents, children, dietary intake, malnutrition, nutritional inadequacy, shelter home

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Authors: Stacia E. H. Sitohang, S.Mn., Socrates Rudy Sirait

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The first movie theater in Indonesia was established in December 1900. The movie industry started with international movie penetration. After a while, local movie producers started to rise and created local Indonesian movies. The industry is growing through ups and downs in Indonesia. In 2008, Visinema was founded in Jakarta, Indonesia, by AnggaDwimasSasongko, one of the most respected movie director in Indonesia. After getting achievements and recognition, Visinema chose to grow the company horizontally as opposed to only grow vertically and gain another similar achievement. Visinemachose to build the ecosystem that enables them to obtain many more opportunities and generatebusiness sustainability. The company proceed as an agile company. They created several business subsidiaries to support the company’s Intellectual Property (IP) development. This research was done through interview with the key persons in the company and questionnaire to get market insights regarding Visinema. The is able to transform their IP that initially started from movies to different kinds of business model. Interestingly, Angga chose to use the start up approach to create Visinema. In 2019, the company successfully gained Series A funding from Intudo Ventures and got other various investment schemes to support the business. In early 2020, Covid-19 pandemic negatively impacted many industries in Indonesia, especially the entertainment and leisure businesses. Fortunately, Visinema did not face any significant problem regarding survival during the pandemic, there were nolay-offs nor work hour reductions. Instead, they were thinking of much bigger opportunities and problems. While other companies suffer during the pandemic, Visinema created the first focused Transactional Video On Demand (TVOD) in Indonesia named Bioskop Online. The platform was created to keep the company innovating and adapting with the new online market as the result of the Covid-19 pandemic. Other than a digital platform, Visinemainvested heavily in animation to target kids and family business. They believed that penetrating the technology and animation market is going to be the biggest opportunity in Visinema’s road map. Besides huge opportunities, Visinema is also facing problems. The first is company brand positioning. Angga, as the founder, felt the need to detach his name from the brand image of Visinema to create system sustainability and scalability. Second, the company has to create a strategy to refocus in a particular business area to maintain and improve the competitive advantages. The third problem, IP piracy is a huge structural problem in Indonesia, the company considers IP thieves as their biggest competitors as opposed to other production company. As the recommendation, we suggest a set of branding and management strategy to detach the founder’s name from Visinema’s brand and improve the competitive advantages. We also suggest Visinema invest in system building to prevent IP piracy in the entertainment industry, which later can be another business subsidiary of Visinema.

Keywords: business ecosystem, agile, sustainability, scalability, start Up, intellectual property, digital platform

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Authors: Yasemin Filiz-Kuruel, Emine Koseoglu

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This study aims to evaluate Haskoy district of Beyoglu town of Istanbul. Haskoy is located in Halic region, between Kasimpasa district and Kagithane district. After the conquest of Istanbul, Fatih Sultan Mehmet (the Conqueror) set up his tent here. Therefore, the area gets its name as Haskoy, 'imperial village' that means a village which is special for Sultan. Today, there are shipyard and ateliers in variable sizes in Haskoy. In this study, the legibility of Haskoy streets is investigated comparatively. As a research method, semantic differential scale is used. The photos of the streets, which contain specific criteria, are chosen. The questionnaire is directed to first and third grade architecture students. The spatial evaluation of Haskoy streets is done through the survey.

Keywords: Haskoy, legibility, semantic differential scale, urban streets

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Authors: Gabriela Smeckova

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The entire world is becoming more and more diverse. The reasons why people migrate are different and unique for each family /individual. Professionals delivering services (including speech-language pathologists) must be prepared to work with clients coming from different cultural and/or linguistic backgrounds. Well-educated speech-language pathologists will consider many factors when delivering services. Some of them will be discussed during the presentation (language spoken, beliefs about health care and disabilities, reasons for immigration, etc.). The communication styles of the client can be different than the styles of the speech-language pathologist. The goal is to become culturally responsive in service delivery.

Keywords: culture, cultural competence, culturallly responsive practices, speech-language pathologist, cultural and linguistical variables, communication styles

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Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

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Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

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Authors: M. Vassou, A. Karasimos

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A primary concern in the field of Second Language Acquisition (SLA) research is to determine the innate mechanisms of second language learning and acquisition through the systematic study of a learner's interlanguage. Errors emerge while a learner attempts to communicate using the target-language and can be seen either as the observable linguistic product of the latent cognitive and language process of mental representations or as an indispensable learning mechanism. Therefore, the study of the learner’s erroneous forms may depict the various strategies and mechanisms that take place during the language acquisition process resulting in deviations from the target-language norms and difficulties in communication. Mapping the erroneous utterances of a late adult learner in the process of acquiring Greek as a second language constitutes one of the main aims of this study. For our research purposes, we created an error-tagged learner corpus composed of the participant’s written texts produced throughout a period of a 4- year instructed language acquisition. Error analysis and interlanguage theory constitute the methodological and theoretical framework, respectively. The research questions pertain to the learner's most frequent errors per linguistic category and per year as well as his choices concerning the Greek Article System. According to the quantitative analysis of the data, the most frequent errors are observed in the categories of the stress system and syntax, whereas a significant fluctuation and/or gradual reduction throughout the 4 years of instructed acquisition indicate the emergence of developmental stages. The findings with regard to the article usage bespeak fossilization of erroneous structures in certain contexts. In general, our results point towards the existence and further development of an established learner’s (inter-) language system governed not only by mother- tongue and target-language influences but also by the learner’s assumptions and set of rules as the result of a complex cognitive process. It is expected that this study will contribute not only to the knowledge in the field of Greek as a second language and SLA generally, but it will also provide an insight into the cognitive mechanisms and strategies developed by multilingual learners of late adulthood.

Keywords: Greek as a second language, error analysis, interlanguage, late adult learner

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Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

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Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing

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Authors: Kai Warsoenke, Maik Mackiewicz

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To achieve a high quality of assembled car body structures, tolerancing is used to ensure a geometric accuracy of the single car body parts. There are two main techniques to determine the required tolerances. The first is tolerance analysis which describes the influence of individually tolerated input values on a required target value. Second is tolerance synthesis to determine the location of individual tolerances to achieve a target value. Both techniques are based on classical statistical methods, which assume certain probability distributions. To ensure competitiveness in both saturated and dynamic markets, production processes in vehicle manufacturing must be flexible and efficient. The dimensional specifications selected for the individual body components and the resulting assemblies have a major influence of the quality of the process. For example, in the manufacturing of forming tools as operating equipment or in the higher level of car body assembly. As part of the metrological process monitoring, manufactured individual parts and assemblies are recorded and the measurement results are stored in databases. They serve as information for the temporary adjustment of the production processes and are interpreted by experts in order to derive suitable adjustments measures. In the production of forming tools, this means that time-consuming and costly changes of the tool surface have to be made, while in the body shop, uncertainties that are difficult to control result in cost-intensive rework. The stored measurement results are not used to intelligently design tolerances in future processes or to support temporary decisions based on real-world geometric data. They offer potential to extend the tolerancing methods through data analysis and machine learning models. The purpose of this paper is to examine real-world measurement data from individual car body components, as well as assemblies, in order to develop an approach for using the data in short-term actions and future projects. For this reason, the measurement data will be analyzed descriptively in the first step in order to characterize their behavior and to determine possible correlations. In the following, a database is created that is suitable for developing machine learning models. The objective is to create an intelligent way to determine the position and number of measurement points as well as the local tolerance range. For this a number of different model types are compared and evaluated. The models with the best result are used to optimize equally distributed measuring points on unknown car body part geometries and to assign tolerance ranges to them. The current results of this investigation are still in progress. However, there are areas of the car body parts which behave more sensitively compared to the overall part and indicate that intelligent tolerancing is useful here in order to design and control preceding and succeeding processes more efficiently.

Keywords: automotive production, machine learning, process optimization, smart tolerancing

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Authors: Dmitriy Babenko, Sergey Yegorov, Ilya Korshukov, Aidana Sultanbekova, Valentina Barkhanskaya, Tatiana Bashirova, Yerzhan Zhunusov, Yevgeniya Li, Viktoriya Parakhina, Svetlana Kolesnichenko, Yeldar Baiken, Aruzhan Pralieva, Zhibek Zhumadilova, Matthew S. Miller, Gonzalo H. Hortelano, Anar Turmuhambetova, Antonella E. Chesca, Irina Kadyrova

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Introduction: The rapidly evolving COVID-19 pandemic, along with the re-emergence of pathogens causing acute respiratory infections (ARI), has necessitated the development of novel diagnostic tools to differentiate various causes of ARI. MALDI-MS, due to its wide usage and affordability, has been proposed as a potential instrument for diagnosing SARS-CoV-2 versus non-SARS-CoV-2 ARI. The aim of this study was to investigate the potential of MALDI-MS in conjunction with a machine learning model to accurately distinguish between symptomatic infections caused by SARS-CoV-2 and non-SARS-CoV-2 during both the early and later phases of the pandemic. Furthermore, this study aimed to analyze mass spectrometry (MS) data obtained from nasal swabs of healthy individuals. Methods: We gathered mass spectra from 252 samples, comprising 108 SARS-CoV-2-positive samples obtained in 2020 (Covid 2020), 7 SARS-CoV- 2-positive samples obtained in 2023 (Covid 2023), 71 samples from symptomatic individuals without SARS-CoV-2 (Control non-Covid ARVI), and 66 samples from healthy individuals (Control healthy). All the samples were subjected to RT-PCR testing. For data analysis, we employed the caret R package to train and test seven machine-learning algorithms: C5.0, KNN, NB, RF, SVM-L, SVM-R, and XGBoost. We conducted a training process using a five-fold (outer) nested repeated (five times) ten-fold (inner) cross-validation with a randomized stratified splitting approach. Results: In this study, we utilized the Covid 2020 dataset as a case group and the non-Covid ARVI dataset as a control group to train and test various machine learning (ML) models. Among these models, XGBoost and SVM-R demonstrated the highest performance, with accuracy values of 0.97 [0.93, 0.97] and 0.95 [0.95; 0.97], specificity values of 0.86 [0.71; 0.93] and 0.86 [0.79; 0.87], and sensitivity values of 0.984 [0.984; 1.000] and 1.000 [0.968; 1.000], respectively. When examining the Covid 2023 dataset, the Naive Bayes model achieved the highest classification accuracy of 43%, while XGBoost and SVM-R achieved accuracies of 14%. For the healthy control dataset, the accuracy of the models ranged from 0.27 [0.24; 0.32] for k-nearest neighbors to 0.44 [0.41; 0.45] for the Support Vector Machine with a radial basis function kernel. Conclusion: Therefore, ML models trained on MALDI MS of nasopharyngeal swabs obtained from patients with Covid during the initial phase of the pandemic, as well as symptomatic non-Covid individuals, showed excellent classification performance, which aligns with the results of previous studies. However, when applied to swabs from healthy individuals and a limited sample of patients with Covid in the late phase of the pandemic, ML models exhibited lower classification accuracy.

Keywords: SARS-CoV-2, MALDI-TOF MS, ML models, nasopharyngeal swabs, classification

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Authors: Mozhdeh Shirinzadeh, Richard Stroetmann

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Orthotropic steel deck bridge consists of a deck plate, longitudinal stiffeners under the deck plate, cross beams and the main longitudinal girders. Due to the several advantages, Orthotropic Steel Deck (OSD) systems have been utilized in many bridges worldwide. The significant feature of this structural system is its high load-bearing capacity while having relatively low dead weight. In addition, cost efficiency and the ability of rapid field erection have made the orthotropic steel deck a popular type of bridge worldwide. However, OSD bridges are highly susceptible to fatigue damage. A large number of welded joints can be regarded as the main weakness of this system. This problem is, in particular, evident in the bridges which were built before 1994 when the fatigue design criteria had not been introduced in the bridge design codes. Recently, an Orthotropic-composite slab (OCS) for road bridges has been experimentally and numerically evaluated and developed at Technische Universität Dresden as a part of AIF-FOSTA research project P1265. The results of the project have provided a solid foundation for the design and analysis of Orthotropic-composite decks with dowel strips as a durable alternative to conventional steel or reinforced concrete decks. In continuation, while using the achievements of that project, the application of a modified Ortho-composite deck for an existing typical OSD bridge is investigated. Composite action is obtained by using rows of dowel strips in a clothoid (CL) shape. Regarding Eurocode criteria for different fatigue detail categories of an OSD bridge, the effect of the proposed modification approach is assessed. Moreover, a numerical parametric study is carried out utilizing finite element software to determine the impact of different variables, such as the size and arrangement of dowel strips, the application of transverse or longitudinal rows of dowel strips, and local wheel loads. For the verification of the simulation technique, experimental results of a segment of an OCS deck are used conducted in project P1265. Fatigue assessment is performed based on the last draft of Eurocode 1993-2 (2024) for the most probable detail categories (Hot-Spots) that have been reported in the previous statistical studies. Then, an analytical comparison is provided between the typical orthotropic steel deck and the modified Ortho-composite deck bridge in terms of fatigue issues and durability. The load-bearing capacity of the bridge, the critical deflections, and the composite behavior are also evaluated and compared. Results give a comprehensive overview of the efficiency of the rehabilitation method considering the required design service life of the bridge. Moreover, the proposed approach is assessed with regard to the construction method, details and practical aspects, as well as the economic point of view.

Keywords: composite action, fatigue, finite element method, steel deck, bridge

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Authors: Mehmet Eren Çelik

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Values are notions that help people to decide what is good or not and to direct their attitude. Teaching values has always been very important throughout the history. Values should be thought in younger ages to get more efficiency. Therefore military schools are the last stop to learn values effectively. That’s why values education in military schools has vital importance. In this study the military side of values education is examined. The purpose of the study is to show how important values education is and why military students need values education. First of all what value is and what values education means is clearly explained and values education in schools and specifically in military schools is stated. Then values education in Işıklar Air Force High School exemplifies the given information.

Keywords: Işıklar Air Force High School, military school, values, values education

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Authors: Aliya K. Salahova

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Scientific thinking, characterized by purposeful knowledge-seeking and the harmonization of theory and facts, holds a crucial role in preparing young minds for an increasingly complex and technologically advanced world. This abstract presents a research study aimed at fostering scientific thinking in early childhood, focusing on children aged 5 to 9 years, through experiential learning in Kids Science Labs (STEM). The study utilized a longitudinal exploration design, spanning 240 weeks from September 2018 to April 2023, to evaluate the effectiveness of the Kids Science Labs program in developing scientific thinking skills. Participants in the research comprised 72 children drawn from local schools and community organizations. Through a formative psychology-pedagogical experiment, the experimental group engaged in weekly STEM activities carefully designed to stimulate scientific thinking, while the control group participated in daily art classes for comparison. To assess the scientific thinking abilities of the participants, a registration table with evaluation criteria was developed. This table included indicators such as depth of questioning, resource utilization in research, logical reasoning in hypotheses, procedural accuracy in experiments, and reflection on research processes. The data analysis revealed dynamic fluctuations in the number of children at different levels of scientific thinking proficiency. While the development was not uniform across all participants, a main leading factor emerged, indicating that the Kids Science Labs program and formative experiment exerted a positive impact on enhancing scientific thinking skills in children within this age range. The study's findings support the hypothesis that systematic implementation of STEM activities effectively promotes and nurtures scientific thinking in children aged 5-9 years. Enriching education with a specially planned STEM program, tailoring scientific activities to children's psychological development, and implementing well-planned diagnostic and corrective measures emerged as essential pedagogical conditions for enhancing scientific thinking abilities in this age group. The results highlight the significant and positive impact of the systematic-activity approach in developing scientific thinking, leading to notable progress and growth in children's scientific thinking abilities over time. These findings have promising implications for educators and researchers, emphasizing the importance of incorporating STEM activities into educational curricula to foster scientific thinking from an early age. This study contributes valuable insights to the field of science education and underscores the potential of STEM-based interventions in shaping the future scientific minds of young children.

Keywords: Scientific thinking, education, STEM, intervention, Psychology, Pedagogy, collaborative learning, longitudinal study

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Authors: Veena Rani

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This paper presents the role of academic library in information literacy in the present time. Information is the very important aspect for the growth of any country. In this context information literacy is an essential tool in the development of various fields. Academic library is an essential part of university as well as of an institution. In Academic library we can include university library, college library as well as school library. Academic libraries are playing an important role for information literacy. Academic libraries provide excellent services for the benefit of students, teachers, researchers, and all those who are interested in education. All over the world many of the schemes, policies and services provide for information literacy.

Keywords: information literacy, academic library, tool literacy, higher education

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Authors: Ian O'Loughlin

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Memory networks aim to integrate some of the recent successes in machine learning with a dynamic memory base that can be updated and deployed in artificial reasoning tasks. These models involve training networks to identify, update, and operate over stored elements in a large memory array in order, for example, to ably perform question and answer tasks parsing real-world and simulated discourses. This family of approaches still faces numerous challenges: the performance of these network models in simulated domains remains considerably better than in open, real-world domains, wide-context cues remain elusive in parsing words and sentences, and even moderately complex sentence structures remain problematic. This innovation, employing an array of stored and updatable ‘memory’ elements over which the system operates as it parses text input and develops responses to questions, is a compelling one for at least two reasons: first, it addresses one of the difficulties that standard machine learning techniques face, by providing a way to store a large bank of facts, offering a way forward for the kinds of long-term reasoning that, for example, recurrent neural networks trained on a corpus have difficulty performing. Second, the addition of a stored long-term memory component in artificial reasoning seems psychologically plausible; human reasoning appears replete with invocations of long-term memory, and the stored but dynamic elements in the arrays of memory networks are deeply reminiscent of the way that human memory is readily and often characterized. However, this apparent psychological plausibility is belied by a recent turn in the study of human memory in cognitive science. In recent years, the very notion that there is a stored element which enables remembering, however dynamic or reconstructive it may be, has come under deep suspicion. In the wake of constructive memory studies, amnesia and impairment studies, and studies of implicit memory—as well as following considerations from the cognitive neuroscience of memory and conceptual analyses from the philosophy of mind and cognitive science—researchers are now rejecting storage and retrieval, even in principle, and instead seeking and developing models of human memory wherein plasticity and dynamics are the rule rather than the exception. In these models, storage is entirely avoided by modeling memory using a recurrent neural network designed to fit a preconceived energy function that attains zero values only for desired memory patterns, so that these patterns are the sole stable equilibrium points in the attractor network. So although the array of long-term memory elements in memory networks seem psychologically appropriate for reasoning systems, they may actually be incurring difficulties that are theoretically analogous to those that older, storage-based models of human memory have demonstrated. The kind of emergent stability found in the attractor network models more closely fits our best understanding of human long-term memory than do the memory network arrays, despite appearances to the contrary.

Keywords: artificial reasoning, human memory, machine learning, neural networks

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Authors: Malephole Philomena Sefotho

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Nowadays, it is a fact that the majority of people, worldwide, are bilingual rather than monolingual due to the surge of globalisation and mobility. Consequently, bilingual education is a topical issue of discussion among researchers. Several studies that have focussed on it have highlighted the importance and need for incorporating learners’ linguistic repertoires in multilingual classrooms and move away from the colonial approach which is a monolingual bias – one language at a time. Researchers pointed out that a systematic approach that involves the concurrent use of languages and not a separation of languages must be implemented in bilingual classroom settings. Translanguaging emerged as a systematic approach that assists learners to make meaning of their world and it involves allowing learners to utilize all their linguistic resources in their classrooms. The South African language policy also room for diverse languages use in bi/multilingual classrooms. This study, therefore, sought to explore how teachers apply translanguaging in bilingual classrooms in incorporating learners’ linguistic repertoires. It further establishes teachers’ perspectives in the use of more than one language in teaching and learning. The participants for this study were language teachers who teach at bilingual primary schools in Johannesburg in South Africa. Semi-structured interviews were conducted to establish their perceptions on the concurrent use of languages. Qualitative research design was followed in analysing data. The findings showed that teachers were reluctant to allow translanguaging to take place in their classrooms even though they realise the importance thereof. Not allowing bilingual learners to use their linguistic repertoires has resulted in learners’ negative attitude towards their languages and contributed in learners’ loss of their identity. This article, thus recommends a drastic change to decolonised approaches in teaching and learning in multilingual settings and translanguaging as a decolonial move where learners are allowed to translanguage freely in their classroom settings for better comprehension and making meaning of concepts and/or related ideas. It further proposes continuous conversations be encouraged to bring eminent cultural and linguistic genocide to a halt.

Keywords: bilingualism, decolonisation, linguistic repertoires, translanguaging

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Authors: Nuno Biga

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Continuous processes’ improvement is a permanent challenge for managers of any organization. Lean management means that efficiency gains can be obtained through a systematic framework able to explore synergies between processes, eliminate waste of time, and other resources. Leaderships in organizations determine the efficiency of the teams through their influence on collaborators, their motivation, and consolidation of ownership (group) feeling. The “organization health” depends on the leadership style, which is directly influenced by the intrinsic characteristics of each personality and leadership ability (leadership competencies). Therefore, it’s important that managers can correct in advance any deviation from expected leadership exercises. Top management teams must assume themselves as regulatory agents of leadership within the organization, ensuring monitoring of actions and the alignment of managers in accordance with the humanist standards anchored in a visible Code of Ethics and Conduct. This article is built around an innovative model of “Business Interactive Games” (BI GAMES) that simulates a real-life management environment. It shows that the strategic management of operations depends on a complex set of endogenous and exogenous variables to the intervening agents that require specific skills and a set of critical processes to monitor. BI GAMES are designed for each management reality and have already been applied successfully in several contexts over the last five years comprising the educational and enterprise ones. Results from these experiences are used to demonstrate how serious games in working living labs contributed to improve the organizational environment by focusing on the evaluation of players’ (agents’) skills, empower its capabilities, and the critical factors that create value in each context. The implementation of the BI GAMES simulator highlights that leadership skills are decisive for the performance of teams, regardless of the sector of activity and the specificities of each organization whose operation is intended to simulate. The players in the BI GAMES can be managers or employees of different roles in the organization or students in the learning context. They interact with each other and are asked to decide/make choices in the presence of several options for the follow-up operation, for example, when the costs and benefits are not fully known but depend on the actions of external parties (e.g., subcontracted enterprises and actions of regulatory bodies). Each team must evaluate resources used/needed in each operation, identify bottlenecks in the system of operations, assess the performance of the system through a set of key performance indicators, and set a coherent strategy to improve efficiency. Through the gamification and the serious games approach, organizational managers will be able to confront the scientific approach in strategic decision-making versus their real-life approach based on experiences undertaken. Considering that each BI GAME’s team has a leader (chosen by draw), the performance of this player has a direct impact on the results obtained. Leadership skills are thus put to the test during the simulation of the functioning of each organization, allowing conclusions to be drawn at the end of the simulation, including its discussion amongst participants.

Keywords: business interactive games, gamification, management empowerment skills, simulation living labs

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Authors: Zhidong Zhang, Zhi-Chao Zhang, Georgianna Duarte

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This study investigated the attention problems with the instrument of Achenbach System of Empirically Based Assessment (ASEBA). Two thousand eight hundred and ninety-four adolescents were surveyed by using a stratified sampling method. We examined the relationships between relevant background variables and attention problems. Multiple regression models were applied to analyze the data. Relevant variables such as sports activities, hobbies, age, grade and the number of close friends were included in this study as predictive variables. The analysis results indicated that educational environments and extracurricular activities are important factors which influence students’ attention problems.

Keywords: adolescents, ASEBA, attention problems, educational environments, stratified sampling

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