Industry Professionals Research Articles

Digital Dissemination of African Films in China: A Case Study of the Bilibili Platform

Cultural communication is of great significance to countries in shaping their national image and enhancing their national soft power. However, due to the influence of African politics and economy, African films always face the situation of insufficient production capacity in the film industry, internationalization experience, and film professionals. As a result, its culture has been discounted in the process of dissemination. In particular, African films have for many years relied only on video and other channels of dissemination, making it difficult to compete with the production and wide dissemination of films from Europe and the United States. Therefore, African films have only accounted for 4% of the African film market share in their home countries.

Developing Maritime Management Curricula: Aligning Industry-Specific Needs with Sustainability and Emerging Technologies

The maritime industry is rapidly evolving due to technological advancements and increased emphasis on sustainability. This research aims to develop a specialized maritime management curriculum that aligns with the needs of the port, shipping, and logistics sectors while incorporating emerging technologies and sustainability practices. Through qualitative research involving 5 maritime professionals, 5 lecturers, and 5 graduates, this study investigates the current gaps in maritime education and the essential competencies needed in modern maritime professions. Using descriptive analysis, the research provides insights into the integration of applied management studies, technical skills, and innovation into the curriculum. The study identifies key areas where existing curricula fall short, including the underrepresentation of technological and sustainability competencies. By examining the experiences of industry professionals and educational experts, a new curriculum framework is proposed, aiming to enhance graduate readiness for modern challenges. The curriculum effectiveness is evaluated using key performance indicators (KPIs), with a 9/10 score on alignment with industry needs. Comprehensive tables illustrate the scoring across various curriculum components, including technology integration, sustainability, and managerial skills. The findings suggest that the proposed curriculum model can significantly improve the employability of graduates, ensuring that they are equipped to meet the dynamic requirements of the maritime industry. Continuous curriculum development, with feedback from industry stakeholders, is recommended to maintain alignment with evolving industry needs.

FASECO: A Framework for Advanced Support of E-Commerce and digital transformation in SMEs with natural language processing-enhanced analysis

ObjectivesThe primary aim of this study is to develop a framework that identifies the factors, organizational processes, and mechanisms that facilitate the successful integration of e-commerce within the digital transformation journey of Small and medium-sized enterprises (SMEs). The FASECO framework seeks to enhance strategic alignment, IT infrastructure, customer experience, and data analytics in SMEs, and is compared with existing theoretical frameworks to provide a holistic solution. Methods/ApproachThe research employs a mixed-methods approach, starting with an extensive literature review on digital transformation and e-commerce integration in SMEs, followed by qualitative semi-structured interviews with 13 industry professionals. The data is analysed using thematic analysis, significantly enhanced by Natural Language Processing (NLP) tools, which allowed for the extraction of deeper insights into e-commerce adoption challenges and organizational dynamics that traditional methods might overlook. ResultsThe study reveals that effective e-commerce integration in SMEs requires robust IT infrastructure, strategic alignment, personalized customer experiences, and data-driven decision-making. The FASECO framework supports SMEs by providing a comprehensive structure that bridges the gap between strategy and technology, enhancing their digital maturity and competitiveness. The framework’s holistic approach and detailed comparison with existing models underscore its effectiveness. ConclusionsThe FASECO framework offers a novel approach tailored to SMEs for digital transformation and e-commerce integration, highlighting the critical role of strategic and technological alignment in achieving digital maturity and competitive advantage. The use of NLP techniques in this study enhanced the analysis of qualitative data, providing deeper insights into organizational processes. Future research should explore the adaptation of this model for micro-SMEs and the integration of emerging technologies.

Cooling and Lubricating Strategies for INCONEL® Alloys Machining: A Comprehensive Review on Recent Advances

Abstract INCONEL® alloys are Ni-based superalloys with superior mechanical properties for extremely high temperature (T) applications. These alloys present significant challenges: they are difficult-to-cut materials due to the low thermal conductivity (k), severe work hardening and elevated surface hardness. They are widely used in applications that require good dimensional stability; however, built-up edge (BUE) followed by premature Tool Wear (TW) are the most common problems when applying conventional machining (CM) and hybrid machining processes, i.e. Additive Manufacturing (AM) followed by milling, resulting in a meagre final product finishing. Regarding cooling/lubricating environments, a miscellanea of methods can effectively be applied to INCONEL® alloys, depending on their advantages and disadvantages. It is imperative to refine the machining parameters to enhance the performance outcomes of the process, particularly concerning the quality and cost-effectiveness of the product. This current review intends to offer a systematic summary and analysis of the progress taken within the field of INCONEL® CM and the various cooling/lubricating methods over the past decade, filling a gap found in the literature in this field of knowledge. A Systematic Literature Review (SLR) approach was employed in this study, aiming to identify pertinent papers within the cooling and lubricating strategies for INCONEL® alloys machining. The most recent solutions found in the industry and the prospects from researchers will be presented, providing significant insights for academic researchers and industry professionals. It was found that selecting cooling methods for INCONEL® machining requires careful consideration of various factors. Each lubrication environment utilized in traditional INCONEL® machining methods offer unique advantages and challenges regarding the different outcomes: TW, Tool-Life (TL) and/or surface quality assessment; nevertheless, cryogenic cooling by CO2(l) and N2(l) highlights as the better cooling environment to improve the machined surface quality.

Assessing the Environmental Impact of Demountable Space-Dividing Walls: A Scenario Analysis Approach in a Semi-Detached Case Study Dwelling

The transition towards sustainable construction is crucial, and demountable building elements are frequently advocated for achieving this goal. While these elements offer relocatability during refurbishments, their adoption may increase initial environmental impact due to higher material use and steel connections. To address this, a quantitative assessment of demountable building elements in refurbishment scenarios at the building level is needed, filling a gap in the existing literature. This study bridges the gap by comparing the total environmental impact of demountable and traditional space-dividing walls in refurbishment scenarios for a semi-detached dwelling. Using a life cycle assessment, seven space-dividing wall types, including metal studs, wood structures, and masonry walls, are evaluated under four refurbishment scenarios spanning a 60-year building lifespan. The results reveal that traditional metal stud walls have a lower environmental impact in scenarios with limited refurbishments. In contrast, demountable walls become more environmentally beneficial only when refurbishing at least 60% of the wall area with three or more refurbishments. This conclusion was further validated through sensitivity analysis on the refurbishment rate, refurbished area, and impact assessment method. In this study, the assumed environmental benefits of demountable walls are challenged, providing a robust evaluation in a specific building typology and offering insights for policymakers and industry professionals on the environmental implications of incorporating demountable building elements.

From incipience to status quo: Development from theatre to streaming

This paper highlights the profound impact of streaming platforms on the profitability and distribution of mainstream films. Through digital innovations that have since transformed the entertainment industry, consumers have turned to video streaming services such as YouTube and Netflix, advancing accessible and affordable content instead of traditional theatrical releases. This transition, fueled by changes in consumer behaviour and accelerated by the COVID-19 pandemic, has reshaped the film industry’s financial and cultural basis, with streaming platforms offering a viable and often preferable alternative to cinemas. Using a mixed-methods approach, the study analyses historical box office trends and industry professionals’ opinions to investigate the rise of streaming and the oscillating state of theatres. While box office revenues remain volatile, especially for mid-budget and independent films, streaming continues to grow: hitting a projected global market value over $184.3 billion by 2027. Insights from this research are crucial for future filmmakers, industry professionals, business leaders, and entrepreneurs to navigate the rapidly changing landscape of film distribution.

Canvassing Taboo: African Sexuality as Post-Cultural Discourse in the Kenyan Disconnect 2 and Nafsi Films

Sexuality narratives in the Kenyan film industry play a crucial role in directly and indirectly shaping narrative interests, addressing stakeholder concerns, and delivering effective messaging. Locally, these narratives are closely monitored, regulated, and classified due to their sensitive nature, compounded by their evolving nature as newer sexuality concepts integrate with traditional paradigms. This study aims to explore the social conceptualization of African Sexuality as a Post-Cultural Discourse in the Kenyan films Disconnect 2 and Nafsi. Utilizing film analysis and key informant interviews with industry professionals, the research reveals that post-cultural sexuality narratives are presented as non-threatening sexual ideals and practices that can coexist harmoniously with traditional sexual paradigms. Recommendations include establishing a structured hierarchy for sexual narratives in film production to depict both traditional and post-cultural themes effectively. By incorporating consequences within the post-cultural discourse, audiences can better engage with and understand the complex sexual ideologies presented in these films.

Preface: 6th International Conference on Information Science and Electronic Technology (ISET 2024)

We are pleased to announce that the 2024 6th International Conference on Information Science and Electronic Technology (ISET 2024) was successfully held in Venice, Italy during September 07-08, 2024. The objective of this conference is to provide a platform for researchers, engineers, academicians as well as industrial professionals from all over the world to present their research results and development activities in information science, computer applications, mechatronics, electrical engineering, and electronic technology. This conference provides opportunities for the delegates to exchange new ideas and application experiences face to face, to establish business or research relations, and to find global partners for future collaboration. There were over 50 participants attended ISET 2024. During the conference, the conference model was divided into three sessions, including oral presentations, keynote speeches, and Q&A discussion. Their insightful speeches had triggered heated discussion in the conference. Every participant praised this conference for disseminating useful and insightful knowledge. We would like to acknowledge all of those who have supported ISET 2024. Each individual and institutional help were very important for the success of this conference. Especially we would like to thank the organizing committee for their valuable advices in the organization and helpful peer review of the papers. The Conference Scientific Committee Venice, Italy

Advancing engineering design problem-exploring practice: interviews with industry professionals

Studies highlight that conceptualising and identifying a new engineering design problem (EDP) is vital, as the solution can benefit society. However, this essential activity, referred to as engineering design problem-exploring (EDPE), is lacking in practice in engineering design. Design engineers appear to focus on providing an engineering design solution (EDS) while their role in EDPE is rarely practised. A new EDP drives innovations and inventions, and there is a need to encourage, advance and sustain the practice of identifying new EDPs. The aim of this study is to empirically highlight the underlying determinants of the scarce practice of EDPE and suggest how to advance and sustain the practice. Interviews were conducted with 32 professionals within the engineering design community, comprising 28 practitioners and four specialists – a lecturer, an inventor, and two expert trainers in creativity and problem-solving. The results of the analyses informed the suggested approaches in this study to advance and sustain the EDPE practice.

Innovative Marketing Strategies in the Competitive Economic Environment in Sustainable Development Goals (SDGs): A Case Study of Top Glove Manufacturers in Malaysia

Objective: The aim is to identify the key marketing strategies implemented by the manufacturers to achieve growth and sustainable development goals (SDGs) market leadership by glove-producing companies in Malaysia in the highly competitive global marketplace. Theoretical Framework: This paper contributes to the existing literature on the marketing strategies practiced in the manufacturing industries, mainly focusing on the glove manufacturing industry in Malaysia, which ranks as the global supplier of hand gloves in the industrial and medical categories. Taken in total, this work provides a refined appreciation of marketing and innovation’s relationship within a particular sector, and it does so by examining how those Malaysian glove makers who contest global markets leverage creativity in their marketing strategies in response to supply chain interruptions, approving bodies, and shifts in international buying trends. Methodology: Following a case study approach, this study focuses on large glove manufacturers in Malaysia; Top Glove is a crucial player. Hence, secondary sources will be adopted during the data collection stage. Perceptual data is also gathered from workers of key executives, marketing managers, and other industry professionals, which gives a picture of these business entities' marketing campaigns and strategic decision-making procedures. Industry journals, company reports, and market study papers validate secondary data. Results and Discussion: This study reveals that policymakers, manufacturing businesses, and marketing scholars can learn about the necessity of niche-based policies and friendly legal environments to boost innovation and competitiveness within manufacturing industries. It provides recommendations on creating a favorable climate for employing innovative marketing strategies and the possible enlargement of home-based businesses internationally. Originality/Value: Based on the findings and insights gathered from the research on innovative marketing strategies in the competitive global economic environment, particularly focusing on the case study of top glove manufacturers in Malaysia, several recommendations can be proposed to guide businesses in enhancing their marketing approaches and organizational performance

Application of Internet of Things and Artificial Intelligence for Risk Mitigation of Accidents in Construction Sites: A Case Study of Brazilian Construction Companies

The construction industry constantly faces challenges related to workplace safety. Managing work safety is crucial to ensuring worker protection and successful project completion. In this context, this study investigates the applicability of Internet of Things technologies and Artificial Intelligence models, such as YOLO, to enhance safety on construction sites. The research identifies significant cultural resistance to the adoption of disruptive technologies in the Brazilian construction sector, and interviews with industry professionals reveal a low level of awareness and interest in these technological innovations. Through case studies and quantitative analyses, the study demonstrates YOLO's potential in identifying risks, such as detecting PPE and structural hazards. The results highlight the need to overcome conservative barriers and invest in technological solutions to increase safety and efficiency in construction.

Visionary constructs: revolutionizing students internships through BIM and extended reality synergy

ABSTRACT This study investigates the integration of Building Information Modeling (BIM) and Extended Reality (XR) technologies in construction education, focusing on their application in internship programs. Traditional internships often face limitations such as restricted exposure to complex scenarios and geographical constraints. To address these challenges, this research examines how BIM-XR technologies can bridge the gap between theoretical knowledge and practical application in the Architecture, Engineering, and Construction (AEC) disciplines. A mixed-methods approach was employed, combining qualitative data from interviews with students, educators, and industry professionals alongside quantitative survey data. This comprehensive methodology enabled an in-depth assessment of BIM-XR's impact on student learning outcomes and operational efficiency. The findings revealed that BIM-XR integration significantly enhances educational experiences by providing immersive simulations that help students visualize complex construction processes. This leads to better preparedness for real-world challenges, increased engagement, and more effective internships. Additionally, BIM-XR offers practical benefits for industry practices, such as improved project planning, real-time decision-making, and enhanced stakeholder collaboration. However, the study also highlights challenges, including the steep learning curve, limited access to necessary technologies, and high implementation costs. These limitations point to the need for comprehensive training programs, affordable technology options, and institutional support to ensure broader adoption. Looking ahead, the study suggests that further integration of BIM-XR with emerging technologies like Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) could further enhance educational outcomes and industry practices.

Barriers to implement energy efficiency strategies to heating, ventilation, air conditioning of airside system in commercial buildings in Sri Lanka

At present, debates on climate change, fossil fuel depletion, and energy saving highlight the need for a sustainable built environment to reduce energy consumption and emission trends. The Heating, Ventilation, and Air Conditioning (HVAC) system is a priority due to its significant share of a building’s electricity consumption. While energy efficiency strategies for central air conditioning systems focus on both waterside and airside components, implementing airside efficiency strategies is notably lacking in Sri Lanka. This is a concern because airside inefficiencies lead to excessive energy use, higher operational costs, and compromised indoor air quality. Thus, the study aims to address this gap by identifying the barriers to implementing energy efficiency strategies for HVAC airside systems in Sri Lankan commercial buildings. To explore these barriers, a qualitative research approach was employed, involving interviews with 17 industry experts. The study identified 27 barriers, with key barriers being a lack of technical expertise, rapid technological advancements, misalignment with organisational objectives, limited financial resources, inadequate training and technical knowledge, and insufficient regulatory support. The insights gained from this study can assist industry professionals in enhancing HVAC energy performance and encourage further academic research on this sub-branch of HVAC systems in the Sri Lankan context.

Research on Proprietary Intellectual Property Management and Marketing Model of Film and Television Companies: A Case Study Based on Warner Bros

This research explores the proprietary intellectual property (IP) management and marketing model in the film and television industry, with a particular focus on Warner Bros. The study aims to elucidate the complex strategies employed by Warner Bros. in the management, monetization, and marketing of its exclusive IPs, demonstrating the company's innovative approaches in this competitive landscape. The research is structured sequentially and examines Warner Bros.' IP management model, revenue streams, and marketing strategies. By closely examining these key elements, the study aims to identify the fundamental factors that contribute to Warner Bros.' success in intellectual property management, revenue generation, and marketing prowess. The insights derived from this comprehensive analysis are intended to provide valuable lessons and insights for industry professionals and researchers within the broader entertainment sector, offering a deeper understanding of the strategic intricacies and successful practices employed by Warner Bros. in navigating the complexities of the entertainment industry's IP-driven landscape.

Organizational Factors Influencing Data Analytics Adoption in SMEs

Small and medium-sized enterprises (SMEs) can use analytics tools to use data for strategic decision-making, but their adoption remains limited because of several issues. This study conducts a systematic literature review spanning the years 2018 to 2024 to investigate how the adoption of data analytics factors influences the widespread utilization of Technology-Organization-Environment (TOE) and Diffusion of Innovation (DOI) frameworks within SMEs. After a rigorous selection procedure, 25 relevant publications were found on Web of Science and Google Scholar, providing insight into significant factors impacting adoption initiatives. The study highlights the significance of top management support, organizational readiness, rivalry, and relative advantage in fostering successful adoption campaigns within SMEs. By arranging and categorizing these variables, this study offers important perspectives to scholars and industry professionals, empowering them to formulate informed choices and tactical plans for the implementation of data analytics in SMEs.

Pathway of Online Impulsive Buying Tendency Research (2007-2024): Bibliometric Analysis

The goals of this study were to assess the body of knowledge about the propensity for online impulsive purchasing, to rectify the shortcomings of past reviews, and to provide academics and industry professionals with an up-to-date, thorough overview of the state of research in the field of online impulse buying tendency. We employed bibliometric analysis approaches to analyze the body of literature on online impulsive purchasing propensity. It was useful for summarizing data through significant contributions, the most prolific writer, the most powerful organization, output within a specific time frame, the rise of keywords, and so on. Article searches were conducted using the Scopus database from 2007 until 2024. The number of studies undertaken in this sector has significantly increased in recent years, as evidenced by bibliometric studies, with China and the United States being the leading contributors. The literature frequently mentioned hedonistic consumption habits, the impact of social media, website design, and promotion. Future studies should look more closely at how emerging technologies like virtual reality and artificial intelligence affect impulsive purchasing behaviour. More comprehensive insights could also be obtained by conducting in-depth studies on cultural variations and the ways in which cultural elements influence impulsive internet purchases.

Towards Ethical AI Moderation in Multiplayer Games

AI is increasingly being used to moderate player behaviour in online multiplayer games, working to identify and respond to toxic and problematic conduct with greater efficiency and accuracy than existing automated systems. However, little work has explored the application of AI moderation in the gaming ecosystem, despite growing ethical concerns about AI applications in other domains. In this study, we conducted 2 expert workshops and interviewed 26 players and industry professionals on their understandings, perceptions and experiences with AI moderation in multiplayer games. Applying a metaphorical frame via template analysis, we outline four metaphors that capture participants' views on the roles of AI and automation in moderation: the Unreliable Police Force, the Unscrupulous Governor, the Uncaring Judge, and the Untiring Assistant. We discuss these roles as exacerbating a top-down, punitive online justice system and identify ethical concerns around transparency, fairness and inclusion, privacy, and human-AI collaboration. To address these concerns, we put forward a set of ethical design considerations and alternative roles for AI moderation in multiplayer games.

A lean approach to comparing the mooring systems of Suezmax tankers

AbstractMooring Suezmax tankers is a process requiring skilled ship crews and terminal workers to accomplish the time-consuming, hazardous task of securing the ship to a jetty to load or discharge oil cargoes. The advent of new equipment technologies has enabled industry professionals to view the mooring process from a new perspective. A lean approach is applied to analysing alternative mooring processes of Suezmax tankers. A reduction in mooring time of about 30 min is noted when replacing steel wire with high modulus synthetic fibre (HMSF) ropes. Further, a potential time saving of 57 min is noted if automated mooring is used instead of steel wire, and 27 min compared with HMSF. The automated mooring concept reduces the manpower required to perform the mooring process, both on board and ashore. If HMSF lines replace steel wires, a significant reduction is noted in ship and crew time costs incurred with mooring maintenance onboard during sailing. A single case study addresses the two research questions: (1) What is the mooring process of Suezmax tankers? (2) How can the mooring process of Suezmax tankers be enhanced?

Predicting Lactobacillus delbrueckii subsp. bulgaricus-Streptococcus thermophilus interactions based on a highly accurate semi-supervised learning method.

Lactobacillus delbrueckii subsp. bulgaricus (L. bulgaricus) and Streptococcus thermophilus (S. thermophilus) are commonly used starters in milk fermentation. Fermentation experiments revealed that L. bulgaricus-S. thermophilus interactions (LbStI) substantially impact dairy product quality and production. Traditional biological humidity experiments are time-consuming and labor-intensive in screening interaction combinations, an artificial intelligence-based method for screening interactive starter combinations is necessary. However, in the current research on artificial intelligence based interaction prediction in the field of bioinformatics, most successful models adopt supervised learning methods, and there is a lack of research on interaction prediction with only a small number of labeled samples. Hence, this study aimed to develop a semi-supervised learning framework for predicting LbStI using genomic data from 362 isolates (181 per species). The framework consisted of a two-part model: a co-clustering prediction model (based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) dataset) and a Laplacian regularized least squares prediction model (based on K-mer analysis and gene composition of all isolates datasets). To enhance accuracy, we integrated the separate outcomes produced by each component of the two-part model to generate the ultimate LbStI prediction results, which were verified through milk fermentation experiments. Validation through milk fermentation experiments confirmed a high precision rate of 85% (17/20; validated with 20 randomly selected combinations of expected interacting isolates). Our data suggest that the biosynthetic pathways of cysteine, riboflavin, teichoic acid, and exopolysaccharides, as well as the ATP-binding cassette transport systems, contribute to the mutualistic relationship between these starter bacteria during milk fermentation. However, this finding requires further experimental verification. The presented model and data are valuable resources for academics and industry professionals interested in screening dairy starter cultures and understanding their interactions.

Machine learning applications of network security enhancement: review

Machine learning (ML) is being used to improve intrusion detection mechanisms and identification in cyber security. Network data volume scaling (with the help of Machine learning) — Automated analysis and pattern recognition for large amounts of network-data, thereby detection of anomalies / potentially malicious activities that escape current rule-based techniques. By training ML models on historical data, these models can learn benign network behavior as well the anomalies in them that may result from malicious activities. The purpose of this essay/report is to begin taking a look under the hood at how ML can be used for security threat detection and analysis in-networking on an ongoing basis. This paper covers the automation of ML algorithms to enhance network security. Given the current state of electronic threats and their evolution, traditional security methods are typically insufficient. ML can analyze large volumes of data, learn patterns from it and this makes it suitable to complement network defense mechanisms. It then discusses different ML applications in network cybersecurity: intrusion detection, anomaly detection, spam and malware analysis; which the paper characterizes. It analyzes the potential, benefits and constrains of major ML methods in network security like supervised learning; unsupervised learning and reinforcement-learning. Finally, this paper represents recent progress in the use and impact of ML techniques along with case studies.The paper discusses the existing difficulties in the field such as the necessity for datasets and the vulnerability of machine learning models to adversarial attacks.T he paper also highlights avenues for exploration by focusing on developing scalable security solutions based on machine learning that are resilient and flexible.The goal of this examination is to offer both researchers and industry professionals valuable perspectives into the opportunities and obstacles linked to utilizing machine learning, in the domain of network security. ML methods have potential to improve network security by addressing the challenges posed by the increasing cyber threats that traditional security measures struggle to combat effectively over time. One key strength of ML lies in its capacity to analyze datasets and identify intricate patterns efficiently. The research paper delves into applications of ML in enhancing network security. The list covers security tools like Intrusion Detection Systems (IDS) examining malware and phishing attempts as well as anomalies in network activity and user behavior analysis (UEBA). The study explores both supervised and unsupervised learning methods. How they are used for quick threat detection and response in real time scenarios.You will find case studies and recent developments that showcase the implementation and effectiveness of these strategies.In addition the article delves into the obstacles linked to using machine learning techniques in network security including the necessity, for datasets, The paper's goal is to give an enlightening summary to scholars and practitioners about how machine learning can be applied to network security in order to provide solutions that are robust, adaptive, and scalable. To this end, it touches on several relevant aspects. One is the threat posed by adversarial attacks on the sorts of models that are likely to be used in this context. Another is the imperative, deriving from both adversarial threat and model drift, that models needed in this context be available in a form usable for continuous update. Keywords: Network Security, machine learning (ML), Intrusion Detection Systems (IDS), entity behavior analytics (UEBA).