Edelweiss Applied Science and Technology

Enhancing linguistic research through AI-powered reference management: A proposal for a voice-controlled academic assistant

2024-10-10T11:33:47+00:00

In today’s digital age, the amount of available research literature is growing exponentially, making it more challenging for researchers to efficiently manage and cite relevant sources. This issue is particularly pronounced in fields like linguistics, where scholars must contend with interdisciplinary sources spanning linguistics, psychology, and computer science. This paper proposes the development of an AI-powered, voice-controlled academic assistant aimed at enhancing the research experience for linguists by streamlining the literature review and citation process. The assistant would use natural language processing (NLP) and machine learning to allow researchers to search for, retrieve, and cite references using voice commands, thereby eliminating many of the tedious aspects of academic research. This proposal outlines the current state of voice-controlled technology, discusses how these technologies can be implemented in academic workflows, and presents a roadmap for the development of a linguist-friendly reference management system. By addressing key technical, ethical, and practical concerns, this paper offers a compelling vision for the future of linguistic research, powered by AI.

Digital competency among the aged entrepreneurs under the silver economy with soft power in Thailand

2024-10-10T12:45:33+00:00

The rise of the elderly in Thailand experiencing a significant demographic transformation resulted in a growing senior population to become a super-aged society by 2030. This affacted the demand for “silver economy in Thailand. The objectives are to study (1) the overview of digital competency among the aged entrepreneurs under the silver economy with soft power; and (2) the mechanism for digital competency empowerment among the aged entrepreneurs under the silver economy with soft power in Thailand. Mixed-research method was employed by quantitative (survey questionnaire) and qualitative (Focus group discussion and interview) with a total of 100 samples and 15 key informants involved: the government workers, the aged entrepreneurs, the private & industrial workers, the digital competency expertise, the elderly expertise, and the community leaders. Two main results reflected the objectives accordingly: 1) the overview of digital competency summarized from survey questionnaire found most of the positive factors as follow; 1.1) positive attitude toward digital competency even of their quite low educational background; 1.2) their positive practical existing skilled in digital competency : digital communication, digital media production, privacy, security, analytic thinking skills that can be well applied with their silver economy’s activities. 2) the mechanism for digital competency empowerment among the aged entrepreneurs found most urgent needs in more closed collaboration among all relevant sectors, starting from the lead government sector, private sector, and the local sectors to help expanding all kinds of empowerment activities. Deepen links by driving more inter-sectoral mechanism, resources sharing, regular consultation for internship, apprenticeship, on-site training, employment, market outlet and other schemes with equity, quality and sustainable practices.

Factors influencing the effectiveness of music communication in Disney animated films

2024-10-16T12:45:46+00:00

This study takes Disney animated film music as the subject of music communication. It discusses the key factors that influence the communication effect of Disney animated film music on listeners in the new media era. This study uses the theoretical framework of Technology Acceptance Theory and quantitative research methods. They are combined with the Technology Acceptance Model (TAM), which provides an in-depth understanding of the influence of Disney animated film music on the cognitive effect, emotional attitude effect, and behavioral effect of listeners. The findings reveal several essential factors influencing the communication effects of Disney animated film music, including listeners' cognitive level, the music, the emotional resonance of the music, and attitudes and behaviors of music communication. These findings not only optimize the communication strategy and audience experience of Disney animated film music but also provide a theoretical basis and practical reference for communication suggestions to improve the communication effect of Disney animated film music.

Navigating educational transformation: Understanding learning styles’ preferences of Egyptian students in the post-pandemic era

2024-10-26T11:42:38+00:00

This study investigated the Learning style preferences of Egyptian EFL learners post-COVID-19. It aims to examine differences emerging in multimodal and bimodal learning preferences based on demographic variables of age and gender and consider the cultural educational context in Egypt during and post the pandemic era. Utilizing the VARK Model, Mayor’s Multimodal Learning Theory, and the Connectivism Learning Theory a survey comprising 19 questions was disseminated to 211 Egyptian EFL students from various age groups. Findings reveal a predominant preference for multimodal learning, particularly visual and read/write styles, with significant variations between genders. Female learners exhibited a stronger inclination towards kinesthetic styles, while males preferred visual methods. Younger learners and female students showed a stronger preference toward the multimodal approach that integrates technology-mediated learning, whereas older students and male learners were in favor of the more traditional modes of learning. The study highlights the importance of integrating traditional instruction wit multimedia resources, particularly for younger learners who thrive in interactive settings. Recommendations include encouraging collaboration between public and private educational sectors, increase the community services and initiatives for community-based learning to address the diverse needs of unprivileged learners. The study advocates for an innovative and holistic teaching approach to enhance engagement and motivation, achieve quality education, and cultivate an informed, skilled generation capable of contributing to the sustainable future of Egypt 2030.

Machine learning-based models for forecasting radio refractivity over the coastal area of South Africa

2024-11-16T09:21:44+00:00

Surface refractivity is a crucial parameter that determines the bending of radio signals as they propagate within the troposphere. It is greatly influenced by the atmospheric weather conditions and changes rapidly, especially in the coastal areas. This research utilized 50 years (1974-2023) surface temperature, pressure, and humidity data from six coastal stations in South Africa to forecast radio refractivity in the Mediterranean climate. Five machine learning models: Gated Recurrent Unit (GRU), Light Gradient Boosting Machine (LightGBM), Long-Short Term Memory (LSTM), Prophet, and Random Forest were trained for future prediction of surface refractivity at any coastal area in South Africa. The stations latitude, longitude, altitude, surface refractivity and date were applied as the input parameters to train the models. The models were optimized through the randomized searchCV hyperparameter tuning to improve their efficiency. The LightGBM outperformed other models with RMSE and adjusted determination coefficients of 1.67 and 0.96, respectively. The model is recommended for future prediction of surface refractivity needed for the improvement of point-to-point wireless communication, terrestrial radio and television transmissions, and mobile communication networks in the coastal sub-tropical regions.