International Institute of
A Comparative Analysis between Artificial Intelligence and Traditional Learning Methods in Developing Critical Thinking Skills among Secondary Education Students in Peru
Castillo, Luis; Saavedra, Rocio (Peru)
https://doi.org/10.54808/WMSCI2024.01.200
ABSTRACT:
Despite the fact that Artificial Intelligence (AI) holds the promise of improving education in Peru, its implementation presents challenges that must be approached with care to ensure ethical benefits. In the Peruvian context, AI is still in the process of adaptation, and its adoption could have negative effects on secondary education, as traditional methods foster critical thinking. A literature review supports the notion that AI may not adequately contribute to students' critical thinking. Emphasizing the importance of strengthening traditional educational methods that promote soft skills such as critical thinking, communication, and problem-solving among students.
Addressing Today's Software Risks Requires an Assurance Educated Workforce
Woody, Carol S. (United States)
https://doi.org/10.54808/WMSCI2024.01.279
ABSTRACT:
A noticeable gap exists in the current acquisition and engineering workforce’s knowledge, skills, and support resources needed to address software and supply chain risk. The growing reliance on software to handle system functionality and the exponential increase in cyber attacks has increased the need for those charged with software assurance to establish that all of the software used within an acquisition will function as intended and be free from vulnerabilities that create gaps in cybersecurity. However, acquirers, developers, program managers, system engineers, and decision makers typically lack the knowledge for doing so. Determining who should be trained and how they should be trained has been an ongoing discussion for several years. This paper summarizes the current efforts underway to address gaps based on recent publications and panel discussions held by the Software Assurance Supply Chain (SSCA) Forum.
Amazon Virtual Forest – A GameTour of One of the Most Biodiverse Places on the Planet
Garcia, Thiago; Bandeira, Thiago; Ferreira, Willian A.; Santos, Gislaine C.; Bossolan, Nelma R. S.; Beltramini, Leila M. (Brazil)
https://doi.org/10.54808/WMSCI2024.01.26
ABSTRACT:
An interactive GameTour on Amazon Floresta was developed as an educational tool, on the context of the scientific research and dissemination actions of the EIC/CIBFar. Different computational resources were used either in terms of hardware and software. "Floresta Virtual" (in English, Virtual Forest) is more than a PC game, it is a “Tour” associated with a “game”, which is why we call it GameTour. It is an educational tool that allows users to connect with this biome in a playful way, starting an adventure that adds knowledge and emotion. "Virtual Forest" will take the user to explore the Amazon Rainforest and we hope that it will encourage them to collaborate in the defense and protection of this priceless natural treasure. The Amazon Rainforest will be explored through realistic 3D simulation, using digital tools (Unity 3D, Blender, C#, Figma, GIMP) and different optimization techniques (PBR, LOOD). In there, the visitor will meet representatives of the flora and fauna of this biome, in addition to the knowledge extracted from it by different ethnicities of the original peoples. It was developed to be accessed via the WEB, is available for free download and was aimed at basic education students and the wider public. During the navigation the users will be guided by an arrow located at the top of the screen, which will help them to locate different plants, animals and curiosities in this forest. Along the way, the users will be able to participate in “quizzes” and earn bonuses that will encourage them to interact with media elements and test the knowledge acquired. The GameTour was well received by the news agencies, who highlighted the current importance of covering this issue.
An Assessment of Correlations of Student Enrolments Among Traditional Universities of South Africa
Mathenjwa, Samukelisiwe; Ilunga, Masengo; Lugoma, Masikini; Jewell, Linda (South Africa)
https://doi.org/10.54808/WMSCI2024.01.110
ABSTRACT:
This paper analysed student intake, namely enrolments in traditional universities, which operate within the South African context such that they elucidate the level of connection among these institutions of higher learning. The findings of the study showed both the existence of high correlation in specific instances and weak correlations in other instances, considering enrolment as variable. Even cases of no correlations were revealed. The spuriousness of strong correlations was pinpointed and the risk that it could be used erroneously in the causality effect among enrolments in universities was stressed. It was revealed that most pairs of traditional universities were not significantly associated based on the variable under investigation.
An Assessment of Markov Chain as a Predictive Tool for the Global Performance of an Institution of Higher Learning
Lugoma, Masikini; Ilunga, Masengo; WaKalenga, Kalenga (South Africa)
https://doi.org/10.54808/WMSCI2024.01.222
ABSTRACT:
The Markov chain (MC) technique is used to make prediction of the ranking of a university in South Africa. The ranking is approached as a stochastic variable. The data were extracted from Scimago in the prediction process. A university was randomly selected to evaluate the level of prediction of the MC method. The university was relatively low ranked. The MC states for this study were adopted from a previous one, based on performance brackets. The Markov chain displayed a satisfactory level of prediction for the probability of a university moving from one level to another. The distribution of university rankings could be well defined to determine the performance of a university.
Analysis on the Rejection and Device Passivity Problems with Myoelectric Prosthetic Hand Control
Al-Owaidi, Noora; Mora, Marta C.; Ventura, Sebastián (Spain)
https://doi.org/10.54808/WMSCI2024.01.10
ABSTRACT:
Despite recent technological advancements in the field of intelligent prosthetic hands, there remains a high rejection rate among patients. The reasons for this rejection are diverse, ranging from limited functionality, and perplexing interfaces, to discomfort, with most issues being discernible only through subjective self-assessment. Surprisingly, there is a lack of specific methodologies to gauge the superiority of a new prosthetic solution over its predecessors. It is imperative to delve into the complexities of maneuvering myoelectric prosthetic hands to comprehend the challenges faced by users and enhance prosthetic accessories and rehabilitation techniques. These hurdles may lead to either a passive usage or a complete abandonment of the prosthetic device. To surmount these obstacles, the field of prosthetics incessantly seeks more sophisticated technologies to enhance functionality, user-friendliness, and device longevity, and reduce maintenance. This study undertakes a methodical examination of the literature on control issues concerning myoelectric prosthetic hands, encompassing recent advancements in sensor technology, hurdles in signal quality, user training and adaptation, issues with pattern recognition algorithms, user satisfaction and comfort, battery life and maintenance, psychological aspects, expenses, and dexterity, culminating in an exploration of functional challenges, advantages, consequences, and feedback.
Assessing Dimension Complexity Reduction of Student Enrolments among South African Universities of Technology
Lugoma, Masikini; Mathenjwa, Samukelisiwe; Ilunga, Masengo; Ngaka, Mosia (South Africa)
https://doi.org/10.54808/WMSCI2024.01.99
ABSTRACT:
This study analysed student enrolments (as multivariate data) in 9 universities of technology of South Africa (UoT), in attempting to maximize the amount of information in data, using principal component analysis. The findings of the study demonstrated that the data sets corresponding to the universities can be reduced optimally to 4 components, by extracting around 90% of information contained in enrolments. It was also revealed that the first two components accounted for about 60% of variance, with more than a half of universities belonging to the 2nd quadrant, followed by 1st and finally the 3rd quadrant. It was observed that none of the universities appeared in the 4th quadrant. Reduced variables could be beneficial in offsetting the complexity in the determination of government subsidy benefitted by universities and any other government operations involving student enrolment.
Assessment of the Impact of Digital Marketing Strategies on Consumer Behaviour of Specialized Coffee Shops
Vahabzada, Nargiz; Andersone, Ieva (Latvia)
https://doi.org/10.54808/WMSCI2024.01.170
ABSTRACT:
The research aims to analyze the digital marketing strategies that use specialty coffee shops and the impacts on consumer behavior in Latvia and Azerbaijan. Studying the specialty coffee industry in Latvia and Azerbaijan demonstrated several essential points. The Chi-square test reveals a strong tendency in favor of the consumption of specialty coffee by respondents from both nations, showing statistically significant differences between them. Moreover, the engagement with specialty coffee brands in social networks revealed a noteworthy difference between Latvian and Azerbaijani consumers, revealing how strong the influence of social media activity growth on promoting these products. The analysis also identifies social media engagement, customer reviews, website traffic, and online sales as essential indicators of the impact of specialty coffee shops in both Latvia and Azerbaijan. On the other hand, this study also reveals issues relating to coffee shops regarding digital marketing strategy implementation and management, including producing convincing online content with limited output products that usually go past consumers. At the same time, they remain interested due to rapid changes in global technologies.
Aurel_AI: Automating an Institutional Help Desk Using an LLM Chatbot
Ordóñez-Camacho, Diego; Melgarejo-Heredia, Rafael; Abbasi, Mohsen; González-Solis, Lucía (Ecuador)
https://doi.org/10.54808/WMSCI2024.01.81
ABSTRACT:
The Aurel_AI research project focuses on creating a virtual help desk for universities, delivering accurate information about academic programs, regulations, processes, and personnel to both internal and external clients. Traditional call centers often grapple with outdated data, limited knowledge, and high staff turnover, leading to inaccurate responses and long wait times. Generative AI models, particularly Large Language Models (LLMs), offer a promising solution for automated help desks. These models can comprehend poorly structured queries and generate appropriate answers. However, they may encounter “hallucinations” due to insufficient training data. Ensuring accurate and comprehensive information involves specific data collection, validation, and updating methodologies. Techniques like Fine-Tuning and Retrieval-Augmented Generation (RAG) are essential for specific use cases. While both methods have pros and cons, balancing cost-effective infrastructure is crucial for a precise, flexible, and user-friendly system.
Autonomous Navigation of Drones Using Explainable Deep Reinforcement Learning in Complex Environments
Souripalli, Pawan Kumar; Sayed, Laeba Jeelani; Chiddarwar, Shital S. (India)
https://doi.org/10.54808/WMSCI2024.01.44
ABSTRACT:
Autonomous navigation of Unmanned Aerial Vehicles (UAV) in complex environments is still a challenging field. Recognizing UAV real-time perception as a sequential decision-making challenge, researchers increasingly adopt learning-based methods, leveraging machine learning to enhance navigation in complex environments. In this paper, a novel deep reinforcement learning (DRL) model has been proposed for the smooth navigation of the UAV. The paper provides an overview of existing techniques, laying the foundation for our proposed work, which not only addresses certain limitations but also demonstrates superior performance in complex environments. The simulation environment is built using Unreal Engine, and the connections have been established using AirSim APIs. The implementation of the TD3 algorithm is chosen for its exceptional adaptability in continuous action spaces due to its off policy, value-based approach, resulting in improved stability and sample efficiency whereas the implementation of PPO algorithm is due to its on-policy method that leads to stable learning without the need for value function estimation. Our model undergoes training in a customized landscape mountainous environment, and the results, obtained after rigorous training, are thoroughly analyzed. The state-action pairs of our trained TD3 agent are explained using LIME and SHAP techniques. The paper concludes by presenting promising directions for further exploration and advancement in this evolving field.
Bridging Generational Gaps: Reducing Conflict and Enhancing Collaboration in the Workplace
Ozolina, Jana; Saitere, Sanita; Gaile-Sarkane, Elina (Latvia)
https://doi.org/10.54808/WMSCI2024.01.147
ABSTRACT:
This research investigates the complexities inherent in managing generational diversity within contemporary workplaces, with a focus on identifying and mitigating sources of conflict while fostering intergenerational collaboration. By examining employees spanning The Silent Generation, Baby Boomers, Generation X, Millennials, and Generation Z, the study elucidates the influence of divergent values, expectations, and communication styles on workplace dynamics.
The findings suggest that, although managing generational diversity presents considerable challenges, it concurrently offers substantial opportunities for innovation and organizational growth when approached effectively. The study underscores the critical importance of tailored conflict resolution strategies, inclusive communication practices, and targeted training programs designed to bridge generational gaps.
This research provides valuable insights for entrepreneurs and business leaders, emphasizing the potential for enhanced productivity and employee satisfaction through improved intergenerational collaboration. It contributes to the broader discourse on workplace diversity and inclusion, offering practical recommendations for leveraging the strengths of multi-generational teams to drive business success.
Colorectal Cancer Diagnosis with Deep Learning Models
Taşcı, Merve Esra; Elmi, Zahra; Albayrak, Ömer Faruk; Tokat, Mustafa (Turkey)
https://doi.org/10.54808/WMSCI2024.01.92
ABSTRACT:
The third most common disease in the world, colorectal cancer, frequently has the highest death rate. Surgery is a viable treatment option, but after five years, thirty to forty percent of patients have recurrence. Many people who have effectively treated their colorectal cancer also develop metastatic illness. Early detection is crucial since colorectal cancer has a high fatality rate. Deep learning techniques make colorectal cancer screening timelier and more costeffective by enabling early and quicker identification of the disease. A collection of cell pictures was employed in the study to detect colorectal cancer. To demonstrate the capability of deep learning approaches, we used Convolutional Neural Networks (CNN), AlexNet, VGG- 16, ResNet models and our proposed model as Hybrid CNN-LSTM. The accuracy and loss rates provided by the propos models were compared. The highest accuracy rate performance was observed with from the Hybrid CNNLSTM model. The highest loss rate performance was observed with from the CNN model.
Communication, Messages, Dialogues
Vieira Kritz, Maurício (Brazil)
https://doi.org/10.54808/WMSCI2024.01.274
ABSTRACT:
Communication is a cornerstone any social enterprise where knowledge is created and collectively cultivated, like it happens in science and culture. It is also the backbone of social systems or organisations that curate, maintain, and propagate knowledge. However, communication is presently an overloaded concept. This word refers to communication between human beings, as well as, to mass communication, communication with and between machines, among animals and plants. The present text describes yet another effort to better understand what communication is, whether it is an artificial product or a natural phenomenon, and what is its role in learning and knowledge construction, including non-human situations. Grounded on previous work that highlighted the importance of considering Shannon-Weaver channels as an artefact supporting interactions, I particularly examine the role of messages exchanged through a SW channel during communications. I also emphasise the relevance of fathoming the role of the message-set as well as how it is affected by learning, cross-disciplinary communication, and non-spontaneous multi-disciplinary collaborations.
Comparison of Machine Learning and Deep Learning Algorithms in Detecting Fake News
Chang, Li-Jing (United States)
https://doi.org/10.54808/WMSCI2024.01.203
ABSTRACT:
Detecting fake news has become increasingly urgent amid the constant surge of misinformation across social media and other could weaken individuals’ ability to use accurate information to make informed decisions, fake news could impact our lives in several ways. For example, empirical evidence showed that spreading healthcare rumors could worsen existing pandemics. Likewise, false financial information could mislead investors into making poor investment decisions and suffering capital losses. Additionally, fabricated scientific claims can misguide policymakers, leading to poor choices that may have long-term consequences. As another common daily phenomenon, deceptive product reviews could lure customers to make unnecessary purchases. As such, an effective mechanism to identify fake news will be the first step to combating it to alleviate its social and economic impact and provide the much-needed safeguard for information integrity in the digital era.
Dozens of studies have used the following machine learning algorithms to detect fake news: Support Vector Machine (SVM), Logistic Regression (LR), Passive-Aggressive Classifier (PAC), Stochastic Gradient Descent (SGD), Random Forest (RF), Naïve Bayes (NB), decision tree (DT), XGBoost (XGB), AdaBoost (AB), Gradient Boosting (GB), and K-nearest neighbors (KNN). In addition, past studies have also used deep learning algorithms such as BERT, Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Neural Network (NN) to build fake news detection models.
The current study compares these algorithms’ accuracies in detecting fake news. The dataset for the study comes from the ISOT dataset, which has 23,481 fake news and 21,417 real news. The dataset was preprocessed to delete punctuations, links, special characters, and stop words. Other text preprocessing steps included lowercasing and stemming to eliminate unnecessary information and reduce data size.
After that, the data was first trained in machine learning algorithms. The text data was tokenized through the TF-IDF procedure, as past research showed that such a process could improve model performance. The tokenized data was split to train and test sets with an 80:20 ratio, and the training dataset was used to train each machine learning algorithm with a grid search via 10-fold cross-validation. Each trained machine learning model was individually evaluated with the test dataset to see its performance.
Following the training of the machine learning models, the text data was preprocessed for the deep learning models of LSTM and Bi-LSTM to have fixed vocabulary size and sequence length. The preprocessed data was split into train and test datasets with the same 80:20 ratio. Then, the LSTM and Bi-LSTM models were specified to each have input, embedding, dropout, LSTM, dropout, and output layers. The LSTM and Bi-LSTM models were each trained with ten epochs on the train data. The trained models were also evaluated using the test data. Finally, the text data was split into train and test datasets to train and evaluate the BERT deep learning model. The train and test datasets were tokenized and padded to limit the input sequence length. Afterward, the BERT model was trained via the train data with ten epochs. The trained BERT model was later evaluated with the test dataset.
After the machine learning and deep learning models were trained and evaluated, the results were used to compare model performance. The comparison showed BERT as top performer with accuracy rate of 99.95%, followed by Bi-LSTM (99.00%), LSTM (98.81%), SVM (98.65%), LR (98.52%), SGD (98.39%), PAC (98.27%), NN (98.00%), RF (97.96%), AB (97.13%), NB (96.97%), DT (95.90%), XGB (94.00%), GB (92.82%), and KNN (61.10%). Except for KNN, 14 of the 15 algorithms tested have an accuracy rate exceeding 90.0%. The findings showed the BERT model’s accuracy level and the potential of some machine learning models, such as NB and DT.
Comprehensive Management of Agroecosystem Productivity on the Platform of Specialized Farm Management Information Systems
Kopishynska, Olena; Utkin, Yurii; Sliusar, Igor; Galych, Oleksandr; Kovpak, Serhii; Liashenko, Viktor; Barabolia, Olga (Ukraine)
https://doi.org/10.54808/WMSCI2024.01.340
ABSTRACT:
The paper examines the methodological aspects of a comprehensive approach to effective management of crop production agrocenoses and resource utilization on the platform of specialized farm management information systems (FMIS). The conceptual advantages and technological foundations of precision agriculture in the context of the formation of Agriculture 4.0 are analyzed, highlighting the significance of progress in the autonomy of agricultural production at various levels of physical and digital technologies. Based on the experience of modern agricultural enterprises in Ukraine, the capabilities of well-known agroprocess management systems, such as Cropio and Soft.Farm, are analyzed. The ways to improve the algorithms and architecture of FMIS software complexes for effective management of interactions between factors in agrocenoses are demonstrated. Prospective directions include mathematical and scenario-based methods for modeling climatic indicators and crop yields.
Conceptions about the Nature of Science of a Sample of Practicing Chemistry Teachers in the Province of Concepción, Chile
Paredes-Turra, César; Cuellar, Luigi; Huincahue, Jaime (Chile)
https://doi.org/10.54808/WMSCI2024.01.246
ABSTRACT:
The objective of this study is to describe the conceptions about the nature of science of 6 chemistry teachers working in private, subsidized, and municipalized schools in the province of Concepción - Chile, who have participated in a series of teacher training and reflection workshops. The data were collected from a Likert-type questionnaire designed to determine the teachers' image of science. The results show a significant change with respect to their epistemological thinking at the beginning of the workshops, and that together with a metadisciplinary and reflective training, have caused a resignification on the conceptions about the nature of science.
Considerations in Selecting and Applying Project Management Software for Optimizing Resources in IT Projects: Practical and Educational Aspects
Kopishynska, Olena; Utkin, Yurii; Sliusar, Igor; Makhmudov, Khanlar; Kalashnyk, Olena; Romanov, Dmytro; Skryl, Viktor (Ukraine)
https://doi.org/10.54808/WMSCI2024.01.333
ABSTRACT:
The theory of IT project management largely utilizes general methods, methodologies, and conceptual frameworks. However, with the advent of projects often executed under conditions of uncertainty and task variability, other methodologies, such as Agile, have emerged, influencing the further development of project theory itself. The relevance of this work is considered in several dimensions and is related both to the need to study the features of planning and implementing ІТ-projects and to the selection of specialized software for implementing modern and effective planning and management methods and tools for IT projects. The work presents the results of practical cases applying various IT project management systems, such as MS Project, Jira, and Trello, during university education. The theoretical study of the formation of the concept for choosing project support systems is based on summarizing feedback from IT company teams that use different tools, as well as on the analysis of annual reports from analytical companies.
Construction of Immersive Art Space and Its Evaluation Using ECG Data
Nakatsu, Ryohei; Tosa, Naoko; Ueda, Yoshiyuki; Nomura, Michio; Uraoka, Yasuyuki; Kitagawa, Akane; Murata, Koichi; Munaka, Tatsuya; Furuta, Masafumi (Japan)
https://doi.org/10.54808/WMSCI2024.01.38
ABSTRACT:
Many previous studies have shown that art appreciation relaxes the human mind and reduces stress. We also hypothesized that art appreciation positively affects viewers' motivation and creativity and started research to confirm this. Firstly, based on the idea that viewing art in an immersive environment that provides a sense of endless space can maximize the effects of art appreciation, an immersive environment was constructed using a mirror display that functions as both a mirror and a display. As a next step, we measured and analyzed physiological data to support our hypothesis. In this paper, after briefly describing the configuration of the immersive environment, we report on the results of the measurement and analysis of electrocardiographic (ECG) data when art content is compared with geometric figure content and no content using the environment.
Corporate Venture Capital: Case of Latvia
Titova, Anita; Lace, Natalja (Latvia)
https://doi.org/10.54808/WMSCI2024.01.312
ABSTRACT:
This pilot study aimed to identify the factors influencing corporations' willingness to establish Corporate Venture Capital (CVC) funds in regions outside core venture capital (VC) centers. Through content analysis, factors affecting the creation and continuation of CVC funds were identified and their interconnectedness was examined. These insights were applied to analyse the initial attempts of a major Latvian corporation to engage in CVC activities. The evaluation of the fund established by the corporation revealed financial losses and a lack of strategic integration of portfolio companies' business ideas into the corporation's operations. However, the corporation's pioneering efforts in CVC activities in an undeveloped and unsupportive environment were acknowledged as beneficial to the broader ecosystem. Several internal factors were identified as potentially detrimental to the fund's success, including limited interaction between the corporation's staff and the fund's portfolio companies and the corporation's partial state ownership. The study highlighted the undeveloped state of the Latvian CVC market and the still-maturing VC market. Nonetheless, public funding for VC funds was a key catalyst for the corporation’s fund's development. The study suggests that enhancing government policies and incentives is crucial for encouraging CVC activities in regions with undeveloped CVC markets. Further research is needed to identify other potential market players and their obstacles for CVC activities.
Crime Detection Method Using Multiple Anomaly Detection Models and Crowdsourcing
Tamano, Tatsuki; Itano, Ryuya; Tanitsu, Honoka; Koita, Takahiro (Japan)
https://doi.org/10.54808/WMSCI2024.01.51
ABSTRACT:
In recent years, the crime clearance rate has remained at a low level. The constant human monitoring of surveillance camera videos is expected to improve crime arrest rates. However, constantly monitoring of surveillance camera videos requires a large number of workers. There is an existing method for crime detection with a small number of workers that combines a single anomaly detection model with crowdsourcing. However, existing method misses crimes in anomaly detection model layer. Therefore, we propose a new method that prevents the miss of crimes by using multiple anomaly detection models and crowdsourcing. We discuss the expected benefits of our proposed method and future plans for our proposed method.
Embedding Brand Positioning within Strategic Management
Štrausa, Evita; Gaile-Sarkane, Elīna (Latvia)
https://doi.org/10.54808/WMSCI2024.01.124
ABSTRACT:
To explore brand prospects and development, it is essential to implement precise brand positioning closely aligned with the company's strategy. The authors propose embedding brand positioning within the broader context of strategic management. This integration ensures that brand recognition and a well-designed brand image significantly influence customer decision-making, leading to a preference for the brand. By embedding brand positioning within strategic management, it becomes a catalyst for enhanced performance and long-term growth. This paper examines the impact of strategic brand positioning on key outcomes: organizational performance and organizational sustainability. Data collected from top executives of diverse organizations have been utilized to test the relationships within this framework. The authors employ structural equation modeling to estimate the proposed relationships in the conceptual model. The results confirm that top executives perceive positioning as having a significant impact on organizational outcomes, and when brand positioning is embedded in strategic management, the impact is more pronounced and effective. Furthermore, management involvement in strategic brand positioning issues significantly mediates the relationship between strategic brand positioning and outcomes.
Evaluating Decision Tree Model for Prediction of Student Performance in Teaching and Learning: Case of Structural Steel Based Graduate Attribute Assessed Module
Ngonyama, Milton; Ilunga, Masengo; Mathenjwa, Samukelisiwe (South Africa)
https://doi.org/10.54808/WMSCI2024.01.236
ABSTRACT:
This study evaluates preliminarily the capability of decision tree classification machine learning to predict the final score, based on assessment marks. The label is defined by categorical classes, translated into binary entities, whereas the features are constituted by the different assessments. The implementation of the decision tree model is carried out on the structural steel design module, which is part of the engineering technology programme taught at the University of South Africa. Its assessments are strategized within graduate attributes or competencies. The intrinsic characteristic of the model showed that student performance prediction could be handled by the model. This demonstrated a relatively high-performance during data testing, with an accuracy of 0.82. Besides, the confusion matrix was also used to evaluate the level of predicting the true positives and true negatives. The prediction of these specific labels altogether was relatively higher than the counterparts, i.e. false negatives, and false positives as far student performance was concerned. Additionally, the recall and precision were relatively high. It was concluded that the algorithm presented through decision tree algorithm was suitable to predict the final score of students, from different assessments. In this respect, this model could be helpful to academic departments.
Exploring a Hybrid System Combining AI and Human Intervention for Subtitle Creation in Entertainment Content
Kuroiwa, Shun; Oshima, Chihiro; Koita, Takahiro (Japan)
https://doi.org/10.54808/WMSCI2024.01.72
ABSTRACT:
This paper proposes a hybrid approach combining artificial intelligence (AI) and human collaboration to improve the accuracy of anime subtitles. By analyzing AI limitations and identifying areas where human intervention is crucial, we develop a cost-effective localization strategy. Through an experiment using a five-minute anime video, we evaluate AI performance and highlight the necessity of human involvement for accurately transcribing challenging audio segments. This study contributes to advancing AI-driven localization and emphasizes human expertise in overcoming linguistic barriers in the global distribution of content.
Factors Affecting Well-being of Employee: An Empirical Study of Manufacturing Companies
Vorma, Eva; Kamola, Liga; Caune, Janis (Latvia)
https://doi.org/10.54808/WMSCI2024.01.177
ABSTRACT:
Regardless of the sector in which companies operate, today’s Europe businesses are challenged by skills shortages, long-term vacancies and high staff turnover, and companies are increasingly focusing on the well-being of their employees to attract and retain employee. Scientific and employee satisfaction research increasingly demonstrates that well-being is not just about remuneration and is not the only motivator. Employee well-being includes a balanced workload, a safe working environment, work-life balance, and physical and mental health, which underpin employee motivation and productivity. The above aspects of employee well-being are basic needs that need to be met; therefore, one of the biggest challenges for business management in today’s fast-changing world is to ensure the competitiveness and profitability of companies by balancing this with employee well-being; therefore, the different dimensions of well-being and the factors that affect well-being that impact the performance of any employee and the company as a whole should be understood.
From Different Angles to Shared Insights: Economist and Psychologist Accord on Employee Motivation
Ozolina, Jana; Saitere, Sanita; Gaile-Sarkane, Elina (Latvia)
https://doi.org/10.54808/WMSCI2024.01.155
ABSTRACT:
This study examines the concept of work motivation from both economic and psychological standpoints, emphasizing its relevance to business practices. Economists study the factors that drive motivation, including incentives, remuneration, and productivity. They specifically examine how financial rewards impact the behavior of employees. Important ideas encompass Incentive Theory, which suggests that monetary incentives stimulate production, and Cost-Benefit Analysis, which evaluates how employees weigh effort in relation to monetary benefits. Psychologically, motivation involves both emotional and cognitive components. Key principles include the distinction between intrinsic and extrinsic motivation. Intrinsic motivation arises from internal drive and genuine interest in one's job, whereas extrinsic motivation is fueled by external incentives such as monetary rewards. The Self-Determination Theory highlights the significance of autonomy, competence, and relatedness in promoting intrinsic motivation. The authors propose practical applications for businesses:
1. Balanced incentive systems involve the integration of monetary rewards with prospects for individual development, hence augmenting motivation. Compensation packages should incorporate both external and internal components.
2.Creating supportive work environments that foster a healthy work culture and promote autonomy, competence, and relatedness can enhance intrinsic motivation. Employers should prioritize cultivating robust relationships and offering purposeful tasks.
3. Customized strategies: acknowledging the varied motivations of employees, organizations should provide adaptable and individualized incentives and support systems. The combination of economic and psychological knowledge is crucial for comprehending and improving job motivation, resulting in more efficient and fulfilling work settings.
Fuzzy Analytical Hierarchy Process (FAHP) for Evaluating Knowledge Areas of Advanced Certificate in Engineering Taught in South Africa
Maduna, Lusiwe; Ilunga, Masengo; Dube, Zakithi (South Africa)
https://doi.org/10.54808/WMSCI2024.01.105
ABSTRACT:
In order to evaluate the consistency of the knowledge areas (Kas) covered in the advanced certificate in engineering (AdvCertEng) course, this study used the Fuzzy Analytic Hierarchy Process (FAHP) technique. Both technological universities and comprehensive universities in South Africa offer this subject. The primary requirements that an engineering programme should meet for the purposes of creating and implementing FAHP are knowledge areas. The opinions of experts and decision-makers are prone to some subjectivity, imprecision, even some uncertainty and ambiguity, which results in fuzziness. Triangular fuzzy numbers (TFN1) between (1,1,1) and (9,9,9) are used to establish fuzzy pairwise comparisons between criteria on a qualitative level, whilst FAHP is used to calculate the weights of the criterion on a quantitative one. In this investigation, TFNs linked to a fuzzy distance from the crisp values of 1 are employed, and the related FAHP is denoted as FAHP1. The credit weight for each knowledge area is then calculated uniformly using the same method. AdvCertEng's existing knowledge area credit weights were generally confirmed using FAHP1. FAHP and ECSA's credit weights did, however, differ by minuscule amounts.
How Do You Argue in Physics Class? A Systematic Review from 2018-2023
Parra Zeltzer, Victor; Huincahue Arcos, Jaime; Abril Milan, Diana (Chile)
https://doi.org/10.54808/WMSCI2024.01.263
ABSTRACT:
This article examines the evolution of the teaching-learning process in science, focusing on argumentation as an essential component, especially in the field of physics. The growing interest in dialogic argumentation in the scientific community stands out, recognized for its ability to enhance learning and contribute to the social construction of knowledge. The relationship between argumentation skills, critical thinking and problem solving in science teaching is emphasized, using Toulmin's model as a framework to analyze the structure of an argument. The concept of Sense Making is explored in the context of argumentation in physics teaching. The methodology includes a systematic review of the literature of the last five years using the PRISMA methodology, revealing consistency in the publication of articles on argumentation in physics teaching. The role of teacher educators as guides in constructivist activities is addressed, while preservice teachers play a central role in the argumentative process.
Human in Cooperation with AI - Next Level of Intelligent Man-Machine Interaction
Koleva, Nataliya (Bulgaria)
https://doi.org/10.54808/WMSCI2024.01.292
ABSTRACT:
The intensive development of technologies in the last decade has faced Industrial Enterprises (IEs) with serious challenges related to their effective digital transformation and overall adaptation to the new market environment to continue to operate successfully in the conditions of strong global competition. In practice, the transformation of the socio-technical system/IE work is inevitable. It is the main driving force for achieving competitive advantage at present, as well as a leading prerequisite for sustainable business development. An important aspect of building a strategy for the organization and management of transformational processes is the study of their impact on the characteristics of the socio-technical system and the possibilities for its sustainable management and development in the context of the new technological reality. This is because the transformation of the work of the socio-technical system must be carried out so that it does not break the synchrony of functioning between its constituent components – “Human (Man)-Machine-Working Environment”. This required to study and define new standards for their effective interaction thoroughly.
This publication analyzes the key aspects that characterize and define the parameters and effectiveness of “Man-Machine” collaboration in modern digital reality. The focus of attention turns to the evolution of this cooperation through the four industrial revolutions. The main characteristics and challenges in implementing “Man-Machine” cooperation are summarized and its importance for business development is discussed in the context of the concept of sustainability in its various manifestations. In this respect, this publication aims to systematize the main areas of knowledge related to “Man-Machine” interaction, which will serve as the basis of a conceptual framework for its sustainable management in the context of the growing autonomy of the socio-technical system.
Implementing Behavior-Based Access Control in Healthcare Scenario Using FIWARE
Farhadi Ghalati, Nastaran; Nikghadam-Hojjati, Sanaz; Barata, Jose (Portugal)
https://doi.org/10.54808/WMSCI2024.01.18
ABSTRACT:
Distributed healthcare systems require strong security and privacy measures because Electronic Health Records (EHRs) are highly sensitive and regulations are strict. The advancing technologies increase the healthcare sector’s susceptibility to data breaches. This highlights the crucial importance of efficient access control to regulate access in settings with extensive data sharing and multiple users.
Many of these challenges cannot be addressed by traditional access control methods. This paper proposes a novel user centric access control model, Behavioral-Based Access Control (BBAC), inspired by the Internet of Behaviors (IoB) paradigm. BBAC dynamically assigns access levels by capturing and leveraging user behavior patterns. Integrating behavioral modeling and user-adaptive access mechanisms within complex healthcare environments, BBAC facilitates privacy-preserving data sharing. Utilizing a human-centered decision-making process, the model enhances security and privacy by adjusting access permissions based on a combination of user roles, locations, times, and behaviors.
This work details the development of BBAC access control policies implemented through AuthZForce. These policies govern authorization/denial of user access requests within the BBAC framework, effectively combining traditional policy strengths with the additional benefit of user behavior. Our evaluation and implementation demonstrate BBAC’s practicality and efficiency in healthcare scenarios.
Implementing Hybrid (AI and Data Analytics) Solutions for Optimal Performance and Cost Optimization for Image Analysis with GPT-4 Turbo with Vision for Predictive Analysis
Mateev, Mihail (Bulgaria)
https://doi.org/10.54808/WMSCI2024.01.74
ABSTRACT:
Extracting crucial metadata from images and videos to assess real-world systems' state and propose sustainability measures is vital to contemporary predictive analysis systems. This practical application underscores the relevance and importance of this research.
Many technologies are helping to solve this case, but one of the most exciting solutions is related to the latest LLM from OpenAI.
GPT-4 Turbo with Vision, developed by OpenAI, is a significant multi-modal model (LMM) capable of interpreting images and providing text-based answers to queries regarding those images. It combines capabilities in natural language processing and visual comprehension. The research is relevant for the latest GPT-4o. This research covers two essential topics: First, how to implement efficient image analysis and prediction models with GPT-4 Turbo with Vision; second, how to optimize the cost of the solution using a hybrid approach where Artificial Intelligence meets Data Analytics and offers cost-effective, high-efficient solutions for predictive analysis based on GPT-4V, Vector Search, and different methods from Data Analytics.
The proposed approach considers using OpenAI LLM, Data Analytics, and Digital Twins for four aspects of predictive analysis: image analysis, case decomposition, hybrid search, and creation of self-adaptive models to find possible trends and offer preventive actions.
Improving Performance of Local Chatbot with Caching
Jenq, John (United States)
https://doi.org/10.54808/WMSCI2024.01.68
ABSTRACT:
Chatbots and the technology behind them are widely used in many places and in various ways. Retrieval Augmented Generation AI framework has gained its popularity by its linking of large language model with private dataset. It enables one to run AI locally and privately with the most updated information and knowledge. In this report, we aim to improve the local private chatbot response time by using a cache. From our experimental results, the majority of time spent during the query process is in the generation of the response. The response time can be significantly improved when there is a hit on the cache system which enables us to return the response to the user immediately without going through the generation step. In this report, we focus our efforts on improving the turnaround time of the generation step. The cache is organized into categories which can be used for efficient searching. User’s query information such as query string, embedding information, and its response are recorded and stored in the cache. Experiment results are presented and the issues of speed up of request response turnaround time is addressed.
Innovative Web-Based VR for Engineering Education and Work
Tudjarov, Boris (Bulgaria)
https://doi.org/10.54808/WMSCI2024.01.54
ABSTRACT:
The present work is based on the assumption that despite reaching a high level of Web technologies, the Internet environment is still not effectively used in both engineering E-learning and engineering activities. Requirements and expectations for the development of a new generation Web-based arsenal of tools supporting engineering education and work are discussed and defined. The structure and elements of an author's experimental engineering educational site using contemporary 2D and 3D Web technologies are presented. In order to ensure the realization of the defined requirements, the development of following modules of the environment is described: a 3D spiral interactive menu generated on the basis of an XML model (for intuitive user friendly navigation) and a module for calculation of systems of ordinary differential equations (for solving engineering tasks reduced to similar systems). A method for user description of the system of differential equations via JavaScript is proposed. Developed Web application is presented and a concrete example calculated with the application is given. The use of modern 2D and 3D Web technologies in the development of interactive laboratory examples is also demonstrated. The usefulness of the proposed environment is discussed and tasks for the future development are marked in the conclusion.
Methods for Assessment of the Most Appropriate Influencer for Branding
Lapina, Elizabete; Kreicbergs, Toms; Andersone, Ieva (Latvia)
https://doi.org/10.54808/WMSCI2024.01.140
ABSTRACT:
The purpose of the research is to determine the impact of influencer marketing on branding and to develop a logical model so that the implemented influencer marketing campaigns achieve the greatest effectiveness by choosing influencers that meet the brand's goal and do not overpay for the services provided by the company. The logical model of the study was created from the survey results, expert interviews, analysis of influencer marketing campaigns implemented by media and advertising agencies, and analysis by the authors. It clarified what challenges and problems a brand can face when using influencer marketing, and a logical model for calculating the effectiveness of influencers was developed. The research shows that influencer marketing is an effective branding tool that can deliver significant returns when used correctly.
Music in Education and in Therapy
D’Acierno Canonici Cammino, Maria Rosaria (Italy)
https://doi.org/10.54808/WMSCI2024.01.325
ABSTRACT:
This research wants to investigate the importance and evolution of music as the starting point of human communication, even preceding language. It will trace its development in both the Western and the Eastern world, either as an important means of education or as a vehicle to alleviate physical and soul suffering.
By following Steven Mithen’s (2006) study on the Neanderthals, who used music to relieve pain and to promote cognition and social cohesion, we have introduced a music class 1) in a middle school for a group of students (11-13years old) in which 20 children could choose to play an instrument or to learn to sing. 2) Then, quite regularly (once a month) we visited all the children in the wards while receiving medical care, so to alleviate their physical and psychological pain.
If music, as Mithen claims, has been applied since pre-historic era “to calm the distressed and to help the ones injured” as well as to help communication, even in our post-modern civilization the beneficial effects of music might produce good results. These principles were applied by the Greeks and the Islamic people when planning education and medical care. They both linked music to the most noble kind of communication, that is to say poetry. In fact, the Greek poets “were themselves singers, and their works were meant to be chanted by readers and interpreters, so as to be received into appreciation through the ear.” [1].
The jahiliyyah (al-shi’r al-J…hil† pre-Islamic poetry 540-620 a.C), too, links rhythm and words, generating a kind of cantillation, a cantillation, which still strongly emerges during the recitation of the Sacred Qur’…n.
In sum, the main aim of our study is to promote music in every aspect, because music embraces psychological, neurological, cognition as well as educational features; characteristics which elevate our spirit, by directing our mind in a new path far from the present pain. Furthermore, music stimulates physical movement, curiosity, social cohesion, so that our brain increases the number of synapses because of the growth of new interests, that remove, even for a short time, a present hard situation.
Navigating Digital Transformation: Crafting Tailored Data Strategies for Organizational Adaptability
Ethier, Louis; Tomiuk, Daniel; Plaisent, Michel; Bernard, Prosper (Canada)
https://doi.org/10.54808/WMSCI2024.01.210
ABSTRACT:
In the digital transformation era, companies must foster adaptability and invest in modernizing their technological infrastructure. A key component of this shift is developing a robust data strategy, which presents implementation challenges in large organizations. We outline criteria for senior management to consider when crafting a data strategy, covering both offensive and defensive measures. While a hybrid approach is common among successful organizations, there's no one-size-fits-all strategy. Instead, companies should tailor their approach to their unique business needs. Our ongoing project, using Design Science methodology, aims to create a tool aiding senior management in selecting the most suitable strategy. This involves assessing sector-specific requirements, improving data management practices, and ensuring alignment across departments.
Navigating the Digital Frontier: Ukraine's E-governance Curriculum Amidst Crisis and EU Integration
Morze, Nataliia; Makhachashvili, Rusudan; Zvonar, Viktor; Ilich, Liudmyla; Boiko, Mariia (Ukraine)
https://doi.org/10.54808/WMSCI2024.01.4
ABSTRACT:
The study tackles the limits of understanding of EU e-governance principles and practices in Ukraine, since strong EU aspirations of the country are challenged by the warfare threatening the nation existence. The struggle of Ukraine against Russian invasion revealed the benefits of previous digitalization efforts in the public sector. However, civil servants and citizens in the country still feel the urgent need of enhancing digital competence. The public sector developed a clear understanding that further reforms must be aligned with EU experiences and expectations, and a proper expertise is called for. Thus, the research objective is to highlight and disseminate EU experience and best practices of the transition to e-governance. The research project e-DEBUT helps promote EU values of transparency, participatory democracy, and inclusiveness through strengthening the digital community in Ukraine. The study aims to develop an innovative curriculum to enhance skills and competencies of civil servants, enrolled in master’s programs, needed for effective rendering of public e-services in war-time, and transferring knowledge of the tech trends and best e-governance practices of EU countries. The project's meaningful results are: a course syllabus, summer schools’ curricula, and a workshop on the facets of development of e-governance in EU countries and in Ukraine; open digital educational resources and analytical materials; a manual for civil servants on the use of e-governance tools under martial law and through post-war reconstruction of Ukraine. The centerpiece of the study is the development of the study module, covering EU lens on concepts of e-governance and digital state, EU technological trends for e-governance, EU best practices in rendering e-governance for business and citizens, as well as the investigation of the adaptation of EU experience in the use of artificial intelligence and smart city infrastructures to the managerial needs of the country at war.
Negative Effects on Productivity and Life Satisfaction Through Social Media
Binsafwan, Abdulla; AlHameli, Zayed; ElSayary, Areej (United Arab Emirates)
https://doi.org/10.54808/WMSCI2024.01.1
ABSTRACT:
This paper explores how social media, and its use affects productivity and overall life satisfaction, or sometimes mentioned as mental health throughout this paper. Social media has an abundant number of users connecting online each day. Making it integral for our society, especially the UAE. Where this study primarily highlights how employees within job sectors manage to adapt, overcome to fail to pass the obstacle that is social media. Thus, the study aims to find the correlation between social media, productivity and life satisfaction. This paper offers a theoretical framework based on many other concepts, social comparison theory and other literature [3,7]. This paper aims to find how integral the overall use of social media is and how potentially debilitating it could be in a society, more specifically. Job sectors and students throughout the UAE.
Possibilities for the Development of Human Capital Efficiency Assessment Monitoring System in Latvia
Sproge, Ilze; Lace, Natalja; Jekabsone, Sandra; Skribane, Irina (Latvia)
https://doi.org/10.54808/WMSCI2024.01.307
ABSTRACT:
Human capital comprises a complex and broad set of human components as part of society. This includes assets such as education, training, intelligence, skills, health, and other things (talent, intelligence, judgment, wisdom, punctuality) that an individual possesses, increasing productivity. As part of the overall capital, human capital generates tangible values in the enterprise and enhances society's well-being. This is one of the most important factors affecting the labor market, employment, and development in line with the current economic situation. However, it is very difficult to assess the achievements objectively and realize human capital based on the results of the work, as formal information cannot fully provide all the skills and qualities that an individual possesses and the additional values of human capital that a person has acquired in his or her process of action. Since human capital is inseparable from its holder, human beings themselves, the degree of return on its use is determined by the individual's free expression of will, individual interests, material and moral interest, responsibility, worldview, and general cultural level. The study aims to evaluate the human capital evaluation methods and the possibilities of implementing the human capital monitoring system in Latvia. To achieve the study's objective, an analysis of human capital components will be carried out, indicators characterizing human capital and its assessment approaches will be examined, and possibilities to develop the human capital assessment monitoring system in Latvia will be examined.
Practicing Mindfulness for Enhancing Emotional Wellbeing
Oganisjana, Karine; Pelithanthrige, Kaveesha Madhumali; Wijesinghe, Kavya Thathsarani (Latvia)
https://doi.org/10.54808/WMSCI2024.01.300
ABSTRACT:
This paper presents outcomes of research conducted with the purpose of studying the impact of exercising mindfulness on the emotional wellbeing of Master’s students. At once after practicing different mindfulness techniques, they solved their current problems and filled in diaries with an analysis of how mindfulness affected their emotions when dealing with stressors. To meet research ethics requirements, the Master’s students were offered to share the diary-based data anonymously via Google Form questionnaire. Both the quantitative and qualitative data analysis witnessed the positive impact of practicing mindfulness on the Master’s students’ emotional wellbeing. Eight categories were developed during qualitative content analysis of the texts of their comments. Based on their meanings, the categories were related to two groups - with inward directedness (emotional regulation, improved quality of thinking and creativity, mind-body wellbeing, self-competency and mental clarity, self-enrichment and heightened intellectual capacity) and outward directedness (development of interpersonal skills and improvement of acceptance of the present moment and the surrounding world). Higher summative weight of categories of Inward directedness vs. of categories of Outward directedness led to theorization, that owing to exercising mindfulness, students first reached internal emotional regulation and only after that opened to the external world.
Predicting Future Participation of Women in Space by Analyzing Past Trends
McDonald, Amber; Segall, Richard S.; Tsai, Peng-Hung; Berleant, Daniel (United States)
https://doi.org/10.54808/WMSCI2024.01.228
ABSTRACT:
This study uses historical data about space missions to support modeling and analysis of the international participation of women as astronauts. Curve fitting is used to model historical data and extrapolate to make predictions about the rate of future participation as astronauts. Experimental results and related works are discussed.
Predictive Machine Learning in Teaching and Learning for Student Performance in a Structural Steel-Based Graduate Attribute Module: The Use of Logistic Regression Model
Ngonyama, Milton; Ilunga, Masengo; Maduna, Lusiwe; Dube, Zakithi (South Africa)
https://doi.org/10.54808/WMSCI2024.01.241
ABSTRACT:
This study evaluates the capability of logistic regression machine learning to predict the final decision of learners’ assessment grades. The binary classification is used for the label, whereas assessment marks are the features used in the process. The algorithm is implemented on the structural analysis module taught at the diploma level at the University of South Africa and assessed on an engineering graduate attribute. The findings highlighted its suitability for a classification problem involving a label associated with the categorical instances. It was shown that model performance was relatively good, with data testing yielding to the model accuracy of 0.82. The use of the confusion matrix was important to get an insight into predicting satisfactorily correctly student performance. Therefore, the final score of students could be estimated and predicted satisfactorily by regression logistic machine learning (ML), when assessments are used.
Problem Solving in Elementary School Mathematics Lessons, Based on Children's Literature, Using the Online Application MS Forms
Mužar Horvat, Sanela; Vuksanović, Petra (Croatia)
https://doi.org/10.54808/WMSCI2024.01.348
ABSTRACT:
To encourage students to solve problems, we conducted action research with a third grade class. The problem-solving tasks were based on fairy tales and stories from children's literature. The students solved these tasks on tablets using the MS Forms application, where they had the opportunity to receive immediate feedback and prepared hints if they could not find the solutions themselves. To encourage student activity, we divided them into small groups that sometimes competed against each other. It turned out that the students actively participated and were satisfied with such organized lessons. They particularly liked the intergroup competition and the opportunity to solve tasks on tablets. Students were able to solve most mathematical problems using the help option in the MS Forms application. This action research has shown that technology and online applications can be used effectively in presenting, and solving problems in elementary school mathematics lessons. In our case, it turned out that the topics of children's literature and technology were not motivating enough for the students. However, it is important that the math lessons are interesting for the students and encourage them to become active.
Progressive Evaluation of School Science Models – An Example from the Teaching of Chemistry
Paredes-Turra, César; Huincahue, Jaime (Chile)
https://doi.org/10.54808/WMSCI2024.01.252
ABSTRACT:
This research is part of a doctoral training process and seeks to develop a proposal for the progressive evaluation of School Science Models (SSM). This proposal will be carried out for the teaching of stoichiometry, through the implementation of a modeling process with first year high school students in three educational institutions in the province of Concepción, Chile. To develop this research, three teachers who teach their classes through modeling processes will be invited to participate. Consensus will be established with them in relation to the modeling cycle, the progression of MCE and its corresponding evaluation. The objective is to obtain results that contribute to the dialogue and discussion around the evaluation processes present in modeling processes in the didactics of experimental sciences.
Promoting the Quality in Higher Education Institutions: Aspects of an Inclusive Environment
Černiševs, Artūrs; Medne, Aija; Lapiņa, Inga (Latvia)
https://doi.org/10.54808/WMSCI2024.01.117
ABSTRACT:
Higher education institutions are becoming more available to a broader audience, which requires flexibility in processes and teaching techniques to ensure their possibility to meet expectations from various stakeholders. This paper aims to research aspects of inclusive environment and inclusivity in higher education institutions. Acknowledging these key elements is vital for institutions to develop their study and administrative process and to adjust to students' needs. Based on the application of the chosen method, the authors have obtained 15 factors that impact the creation of an inclusive environment in a higher education institution. The main factors are adjusting study content and inclusion of transversal competencies, accessibility to physical and digital infrastructure, and differentiated didactics and evaluation methods. The research is limited to the inclusivity of students and does not address the issues related to the inclusivity of employees.
Psychological Evaluation of the Effect of Exposure to Projector Light While Viewing Art
Kanai, Shun; Kazawa, Go; Tosa, Naoko; Nakatsu, Ryohei; Kitabayashi, Kazuyoshi; Kawata, Hirotaka; Miyata, Manae (Japan)
https://doi.org/10.54808/WMSCI2024.01.32
ABSTRACT:
When projecting art and other contents using a projector, entering the space where the contents are projected is considered adequate. The purpose of this study is to confirm the effectiveness of this method through a psychological experiment. We constructed a space in our laboratory where art can be projected and viewed. Then we asked subjects to view art contents under three viewing conditions (Condition 1: Outside the projection space, sitting on a chair; Condition 2: Inside the space, sitting on a chair; Condition 3: Inside the space, sitting on a floor), and to evaluate the experience in terms of "Impression," "Relaxation," "Motivation," and “Creativity." As a result, Condition 2 was rated higher than the other conditions in "Relaxation," partially confirming the effect of entering the projection space to view the art. At the same time, there was little difference among the conditions for "Impression," "Motivation," and "Creativity." Therefore, further experiments will be conducted to clarify the effects of entering the projection space and viewing art content.
Readiness of the Community for the 4th Industrial Revolution in the Case of Thailand
Chinprateep, Apirada (Thailand)
https://doi.org/10.54808/WMSCI2024.01.319
ABSTRACT:
The primary goal of this research is to prepare for the readiness of the community for the 4th Industrial Revolution. This research will concentrate the case of Thailand as one of the major countries in the South-East Asia Region. We explore readiness of Thailand and the 4th Industrial Revolution, with particular interest in adaptation to readiness for the 4th Industrial Revolution and Post-Covid Era.
Role of the Bridge Maker in Innovation Ecosystems
Banga, Kristaps; Gaile-Sarkane, Elīna (Latvia)
https://doi.org/10.54808/WMSCI2024.01.132
ABSTRACT:
This research explores the crucial role of bridge makers in fostering the success of open innovations within innovation ecosystems. Emphasizing governance structures, this study highlights the importance of creating synergies among participants through effective intermediaries. Bridge makers act as connectors, facilitators, and integrators, crucial for fostering collaboration among diverse stakeholders, aligning interests, and overcoming barriers to innovation. By integrating the bridge maker role into ecosystem strategies, stakeholders can ensure that the connections formed are not only numerous but also robust, inclusive, and capable of driving long-term innovation and collaboration.
Given the fragmented nature of recent literature on the role of bridge makers, and the various terminologies used to describe similar roles, this research aims to provide a clear definition and comprehensive understanding of the bridge maker’s role. The objective is to analyze different aspects and names attributed to this role within the context of innovation ecosystems.
This paper concludes by discussing future research avenues that can build on the developed role typology, shedding further light on the process of open innovation ecosystem genesis. By incorporating the bridge maker role into the various ecosystem models, this research suggests that enhanced connectivity and synergy can be achieved, benefiting the entire ecosystem.
Sense-Making in Embodied AI – Towards Autopoietic Chemical AI
Rubin, Sergio; Stano, Pasquale; Roli, Andrea; Damiano, Luisa (Italy)
https://doi.org/10.54808/WMSCI2024.01.85
ABSTRACT:
Experimental Epistemology (EE) – i.e., the branch of cybernetic epistemology founded by Warren McCulloch [1] to experimentally explore “embodiments of mind” – still has significant potential to be expressed in AI. This is the basic premise of our work, which recognizes in one of EE's most interesting affiliations, namely Humberto Maturana and Francisco Varela’s [2] autopoietic approach to the description of the living organization, a framework useful to improve contemporary Embodied AI's modeling of natural cognition. Our main goal is to incorporate the autopoietic theoretical model of the biological organization in EAI’s synthetic models of natural cognitive systems, in order to artificially generate forms of autonomy and sense-making similar to those of living systems. The core novelty of our research program relies on the hypothesis that, to be effective, this operation cannot be realized in software or hardware, and requires wetware modeling. We plan to use Synthetic Biology (SB)’s techniques to develop wetware models of minimal living-like systems, such as closed chemical reactions based on chemical organization theory and active inference (i.e., the free energy principle), to test whether they can implement sensory-motor loops arising from selfproduction and agent-environment interactions, and generating minimal forms of autonomous (chemically-)embodied cognition.
Service Robot in Tourism Industry: An Interdisciplinary View and Need
Im, Yunwoo; Nakabasami, Chieko (Japan)
https://doi.org/10.54808/WMSCI2024.01.217
ABSTRACT:
Globally, the demographic issue of labor shortages persists. The tourism industry is highly dependent on labor because tourism products (services) cannot be mass-produced or standardized through mechanization, making the capabilities of the service providers crucial. This study addresses the persistent labor shortages in the tourism industry and the potential role of service robots as a solution. This study assesses the potential for the ongoing introduction of service robots and proposes the need for interdisciplinary research on the conceptual aspects of tourism studies and robotic technology. A key value in the tourism industry is customer satisfaction and repeat visits, which can be analyzed through human-robot interaction (HRI). HRI is being studied as an important concept in many industries and academic fields, and this research employs topic modeling to verify its practical application. This paper discusses the technological explorations necessary in tourism and argues for the necessity of interdisciplinary inquiry. It can also be suggested as foundational data for tourism managers considering the introduction of service robots. They can select robots with the appropriate technological level required for the tourism industry, which can reduce economic risk.
Smart Alert System for Potted Plants That Optimizes Water Consumption
Ulloa Rubio, Bertha; Baltodano Nontol, Luz Alicia; Gaytan Reyna, Karina Liliana; Carrera Ruiz, Kewin Miguel (Peru)
https://doi.org/10.54808/WMSCI2024.01.60
ABSTRACT:
In this research, the importance of environmental variables was analyzed with the alternatives offered by the Internet of Things, in terms of elementary processes of daily life such as monitoring a potted plant. The objective of the prototype was to develop an intelligent alert system to monitor the various variables of the environment, for this, work was carried out in four main phases: sensors that monitored the temperature and humidity of the weather, a light sensor that detected solar intensity, soil moisture sensor that monitored soil moisture time and the air quality sensor determined the carbon dioxide in the environment. The microcontroller was integrated to detect the variables of the sensors that were linked to the industrial platform connected to the cloud for the Internet of Things, which allowed to visualization of the graphs in real time and also worked with the analysis of the database. Finally, the result was a platform connected to different applications to carry out alert activities with calls and text messages to the cell phone of the owner of the pot with plant.
Strategic Decisions in Firms Driven by Collective Work Experience from the Upper Echelons Theory Perspective
Pīpiķe, Rasma; Gaile-Sarkane, Elīna (Latvia)
https://doi.org/10.54808/WMSCI2024.01.163
ABSTRACT:
This study examines more in-depth aspects of forming collective work experiences in top management teams (TMTs) and its impact on firm performance from an Upper Echelons Theory (UET) perspective, emphasizing diversity management strategies.
Using a mixed-methods approach, including ten in-depth interviews with business professionals in Latvia representing all spectrums of fields and a survey of 765 Latvian companies, the study highlights the significant impact of diverse work experience on decision-making processes, innovation, and financial outcomes.
The results show that most Latvian business professionals consider collective work experience essential for innovation and financial growth. Critical aspects of the TMT collective work experience, such as diverse professional backgrounds, continuous learning, effective teamwork, and human resource management professional involvement in the TMT, have been identified as improvements for strategic decision-making and organizational success.
The study highlights the need for tailored strategies in TMT composition to use diversity effectively. In addition, the authors aim to develop a mathematical model to optimize TMT effectiveness by fully exploiting the potential of diverse collective work experiences and providing insights into improving management structures and performance in different economic contexts. Therefore, this article is one step further in finding measurable criteria to search measurable criteria to establish the mathematical model for improved use of diversity management.
The Case Studies Model Updated: Using Films in the Methodological Training of Pre-Service EFL Teachers
Puskás, Andrea (Slovakia)
https://doi.org/10.54808/WMSCI2024.01.269
ABSTRACT:
The paper focuses on the application of an updated Case Studies Model in higher education, more specifically, the training of pre-service English as a Foreign Language teachers. The Case Studies Model has been updated according to the needs of the twenty-first century and applied when designing a new course for a Master’s level programme for pre-service EFL teachers at the Department of English Language and Literature, Faculty of Education at J. Selye University in Slovakia, the course of Methodology of Teaching English as a Foreign Language 4 (MET4). The paper discusses the principles of designing the MET4 course and presents the findings of a case study. In addition to the general syllabus, five films dealing with educational topics and challenges were incorporated in the MET4 course content. Pre-service teachers were asked to watch the films and provide written feedback based on structured questions. The paper presents the most important findings of the case study, but most importantly, it outlines some ideas for implementing films in the training of future EFL teachers in order to encourage opinion-exchange, in-depth analysis of crucial issues in education and to increase student engagement. Important implications and possible future directions are highlighted as well.
The Effect of Social Media on Anxiety and Stress
AlAhbabi, Alyazia; AlTeneiji, Alyazia; AlShaer, Amira; AlJaberi, Ghaya; ElSayary, Areej (United Arab Emirates)
https://doi.org/10.54808/WMSCI2024.01.193
ABSTRACT:
This research paper investigates the relationship between social media usage, anxiety levels, and stress levels among young adults aged 18-25. The aim is to gain a comprehensive understanding of the potential impact of social media on anxiety and stress in this population. Data was collected through a survey administered to 132 participants, and statistical analyses were conducted to examine the associations between social media usage hours per day and anxiety and stress levels. The findings reveal that a significant proportion of young adults spend a substantial amount of time on social media, with a sizable percentage exceeding recommended usage limits. The results also indicate a positive correlation between social media usage and both anxiety and stress levels, suggesting that as individuals increase their engagement with social media, their reported anxiety and stress levels tend to be higher. These findings contribute to the existing literature on the psychological effects of social media and have implications for promoting mental wellbeing among young adults. The study underscores the importance of addressing social media usage and its potential impact on mental health in interventions and strategies to promote overall well-being in this population.
The Effects of Social Media on Self-Esteem
Al Ahbabi, Alyazia; Al Teneiji, Alyazia; Al Shaer, Amira; Al Jaberi, Ghaya; ElSayary, Areej (United Arab Emirates)
https://doi.org/10.54808/WMSCI2024.01.185
ABSTRACT:
This research project examines the impact of social media use on self-esteem among university students aged 18-25 in the United Arab Emirates, a country with one of the highest social media penetration rates globally. Utilizing an observational cross-sectional survey design, the study employed the Social Media Use Integration Scale and the Rosenberg Self-Esteem Scale to assess social media usage patterns and self-esteem levels. Analysis revealed a significant negative correlation between social media use and self-esteem, underscoring the complex nature of this relationship. The study acknowledges limitations such as reliance on self-reports and small sample sizes, suggesting future research should incorporate larger, more diverse samples and longitudinal designs to explore the enduring effects of social media on self-esteem. This research contributes to the broader goal of promoting well-being in the digital age, aligning with the United Nations’ Sustainable Development Goals, and provides a foundation for further investigation into moderating factors that influence the relationship between social media use and self-esteem.
The Impact of Digitalization on the Development of Small and Medium Sized Enterprises in India
Erina, Jana; Kunnamkara, Amal (Latvia)
https://doi.org/10.54808/WMSCI2024.01.285
ABSTRACT:
This research examines the impact of digitalization on the development of small and medium enterprises (SMEs) in Kerala, India. Digitalization, a key driver of today's business transformation, improves productivity, efficiency, and customer experience, which are critical for SMEs in developing countries like India. This research aims to assess how digital technologies impact the growth and competitiveness of SMEs in Kerala. Using qualitative and quantitative data processing methods, including literature analysis and a survey questionnaire, the research analyzes data using SPSS descriptive statistics, reliability testing, and factor analysis.
The methodology involves developing a survey questionnaire distributed to 81 leading SME owners and heads of various departments from Kerala. The data obtained from 60 respondents shows a significant understanding of the benefits and challenges of digitalization. The factor analysis identified eight key factors influencing the digitalization of SMEs, including innovation, leadership, technology management, workforce efficiency, and global knowledge transfer.
The research results showed the importance of using digital technologies to improve user experience and mobile security and expand market reach, thereby improving the overall performance of SMEs in India's dynamic economy.
What Does Newton's Second Law Say? A Comparison between Principia and University and School Physics Texts in Chile
Parra Zeltzer, Victor; Huincahue Arcos, Jaime; Abril Milan, Diana (Chile)
https://doi.org/10.54808/WMSCI2024.01.256
ABSTRACT:
Traditional teaching focuses on memorizing formulas and problem solving, especially in mechanics, crucial in secondary education and teacher training. The difficulty of understanding Newton's second law is discussed, attributing it to erroneous preconceptions about force and acceleration. It is suggested to teach the law from Newton's original formulation for a deeper and more contextualized understanding. The present work addresses the perception of physics students, especially in Chile, about the discipline, where it is considered boring, difficult and disconnected from everyday life. A comparative analysis is carried out on how Newton's second law is taught in university and schoolbooks in Chile, observing differences in the mathematical formulation and conceptual approach. The importance of promoting a reflective and contextualized approach in teaching physics is highlighted to develop problem-solving skills and connect concepts with reality. In summary, a change in physics teaching focused on a deep understanding of concepts and the contextualized application of fundamental laws, such as Newton's second law, is advocated to promote meaningful and lasting learning.
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