bluuebunny/crossref_metadata_2025 huggingface dataset:
The development of website-based encyclopedia media on laboratory equipment material for laboratory engineering courses
Authors: AR Nurfitri , Jamilah Jamilah , Syahriani Syahriani , Syamsul Syamsul
Published: December 2024

The importance of mastering laboratory equipment for Biology Education students encourages the development of a website-based encyclopedia as an interactive and easily accessible learning resource. This study aims to determine the characteristics of the media, the level of validity, and the level of practicality of the website-based encyclopedia on the material of introduction to laboratory equipment as support for laboratory engineering courses in the Biology Education Study Program, UIN Alauddin Makassar. The study was a research and development (R&D) based on the ADDIE development model, which included five steps: analyze, design, develop, implement, and evaluate. The results showed that the website-based encyclopedia media on laboratory equipment introduction material for the laboratory engineering course in the Biology Education Study Program UIN Alauddin Makassar has first-rate characteristics with an average expert validator rating of 100%. The media has a validity level of 3.66 means a very valid category. The media's level of practicality, as assessed by both students and lecturers, fell into the very high criteria, with a rating of 3.57 from students and 3.62 from lecturers. Therefore, the website-based encyclopedia media for introducing laboratory equipment is suitable and recommended for integration into the learning process.
RANCANG BANGUN SISTEM INFORMASI MANAJEMEN PROYEK PADA CV.GRAHA RAYA CONSULTANT
Authors: Fauzan Amri Muhammad , Aditya Harahap Calvin
Published: December 2024

Project Management Information System is needed to support the effectiveness of project management at CV. Graha Raya Consultant. Currently, the company faces challenges in managing scattered project information and inefficient coordination processes. This study aims to design and implement a web-based project management information system that can assist in monitoring, managing data, and reporting projects. The methodology used is the waterfall-based software development method. This system is expected to help improve efficiency in project management and minimize errors caused by manual recording. The test results show that the information system developed is able to meet the company's needs and facilitate management in supervising each stage of the project.
PENGARUH VARIASI SUDUT NOZZLE DAN JUMLAH SUDU TERHADAP KINERJA TURBIN PELTON
Authors: Koswara Engkos , Dewi Jannati Eidelwei , Rachmat Asep , Fudholi Ahmad , Zauhari Azi
Published: December 2024

In Indonesia, one of the government's programmes is village electricity. For remote villages in mountainous areas, the construction of micro-hydro power plants is one of the answers to the government programme. Power generation in this way is very suitable for our country, given the natural conditions consisting of many mountains that have streams of river water. In turbines we recognise various types of turbines used, we can use francis, kaplan and pelton turbines.  The use of these turbines depends on the potential head owned, Pelton turbines that use the principle of impulse require a relatively high head. In this study, it will be studied how the effect of nozzle angle variation and the number of blades on the performance of pelton turbines.
The test results show that the tilt angle 65° produces higher rotation at 900-910 rpm while the tilt 90° produces lower rotation around 800-880 rpm. While the effect of the number of blades used is not so significant in the performance of pelton turbines, it can be seen in the use of the number of blades 9 and 18 at the tilt 65° nominal rotation that occurs around 900-910 rpm.
IMPLEMENTASI SISTEM PELAYANAN IZIN USAHA SECARA TERPADU TERHADAP KUALITAS PELAYANAN PUBLIK PADA DPMPTSP KOTA MEDAN
Authors: Muhammad Ikhsan  , Novlianun Dly  , Nelly Agustina Siregar  , Maisyarah
Published: December 2024

This study aims to analyze the implementation of an integrated business licensing service system and its impact on the quality of public services at the Investment Office and One-Stop Integrated Services (DPMPTSP) of Medan City. The research employed a qualitative descriptive method with data collection through observation, interviews, and documentation. The results showed that the implementation of an integrated system has significantly improved service quality through faster processing times, increased transparency, and reduced bureaucratic complexity. The system implementation has successfully integrated various licensing services into a single platform, resulting in more efficient and effective public service delivery. However, some challenges were identified, including the need for continuous system updates and staff training to maintain optimal service quality.
OPTIMALISASI TEKNOLOGI SPAM UNTUK MENDUKUNG PELAYANAN AIR BERSIH DI KAWASAN STRATEGIS BANDARA INTERNASIONAL JAWA BARAT
Authors: HERYADIANA ASEP DIAN , Rachmat Agus , Kadir Yushar
Published: December 2024

The increasing demand for clean water services in Majalengka Regency, especially in the strategic area of West Java International Airport (BIJB), necessitates optimal performance from PDAM Majalengka. This study aims to evaluate and optimize SPAM technology implementation to enhance water distribution services. Using quantitative analysis through surveys and statistical testing with SPSS, findings indicate that key factors such as water pressure, continuity, quality, pricing, and complaint handling significantly influence customer satisfaction. Recommendations include upgrading distribution networks, optimizing existing water sources, and adopting advanced SPAM technologies to meet future demands.
O estudo de tempos na determinação da capacidade produtiva
Authors: Oliveira Erick Magno Garcia de , Brito Heitor Cardoso de
Published: December 2024

O modal rodoviário se destaca como o mais significativo no transporte de cargas no país, sendo imprescindível que as empresas estejam aptas a satisfazer as exigências do setor. O principal objetivo do estudo foi determinar a capacidade produtiva do processo de recapagem em uma empresa do ramo de reforma de pneus, por meio do estudo de tempos e da aplicação de fundamentos da teoria das restrições. Para realizar o estudo, foram executadas seis etapas para determinação do tempo padrão, sendo elas: a divisão da operação em elementos, determinação do número de ciclos a serem cronometrados, avaliação da velocidade do operador, determinação do tempo normal, determinação das tolerâncias e determinação do tempo padrão. Os tempos padrão das operações foram usados para determinar as suas capacidades de produção e identificar o gargalo e a máxima capacidade do sistema. O principal resultado obtido foi a identificação do elemento gargalo “Aplicação de Cola.
Библиометрический анализ применения граничных вычислений в киберфизических системах промышленного интернета вещей (IIoT)
Authors: Жукабаева Т. , Жолшиева Л. , Қарабаев Н. , Ахметжанова Ш.
Published: December 2024

С развитием промышленного интернета вещей (IIoT) автоматизация систем взаимодействия человека и машины достигла нового уровня исследований, способствуя интеграции интеллектуальных технологий в промышленность и энергетический сектор. Современные технологические инновации, включая граничные вычисления и туманные вычисления, значительно ускоряют развитие производственных процессов. Цель этой работы — всесторонний обзор научной литературы, связанной с определенным набором терминов, возникающих из интеграции IIoT и граничных вычислений. В работе представлен библиометрический анализ слияния граничных вычислений и IIoT. Основное внимание уделяется преобладающим тенденциям, ведущим авторам, ключевым публикациям и продуктивности исследований за последние 5 лет. Работа выявляет заметные паттерны и тенденции, исследуя научные статьи и используя инструмент bibliometrix, подчеркивая роль передовых технологий, таких как ИИ и блокчейн, в улучшении систем IIoT. Данные показывают значительное увеличение результатов исследований, подчеркивая необходимость эффективного использования граничных вычислений для решения задач обработки данных и улучшения безопасности систем. Этот библиометрический анализ раскрывает актуальные области исследований и перспективные направления развития граничных вычислений в рамках IIoT.
СРАВНИТЕЛЬНЫЙ АНАЛИЗ ЭФФЕКТИВНОСТИ НЕЙРОННЫХ СЕТЕЙ ПРИ НИЗКОМ ЗНАЧЕНИИ ОТНОШЕНИЯ С/Ш
Authors: Медетов Б. , Нурланкызы А. , Ахмедиярова А. , Жетписбаева А. , Жексебай Д.
Published: December 2024

Данная работа посвящена сравнительному анализу эффективности нейронных сетей CNN и RNN при низкомзначении отношения С/Ш.  Проведенное исследование в рамках данной работы показало, что сверочные нейронные сети RNN демонстрируют более высокую эффективность в задачах распознавания речевого сигнала при низком уровне отношения С/Ш. Так, нейронная сеть RNN показала стабильное превосходство над CNN при низких значениях отношения С/Ш. Выявлено, что при отношении С/Ш = 6 дБ, точность распознавания с использованием RNN составила 82% для казахского языка, в то время как CNN показала результат в районе 77%.
Кроме того, результаты показали, что эффективность нейронных сетей CNN и RNN зависит от языка, на котором они обучались. Нейронные сети, обученные на казахском языке, показали лучшие результаты при распознавании казахской речи, но также успешно справлялись с распознаванием русского языка. Это подчеркивает важность учета языковых особенностей при разработке и обучении нейронных сетей, что может улучшить их производительность в многоязычных средах.
В рамках данного исследования установлено, что разные языки демонстрируют различные результаты при низком уровне С/Ш. Например, несмотря на родственную связь между казахским и кыргызскими языками, нейронная сеть RNN более успешно справлялся с распознаванием русского языка. Это может свидетельствовать о большом сходстве фонетических признаков между казахским и русским языками, чем между казахским и кыргызским. Данный результат требует дальнейшего детального исследования и анализа для выявления фонетических особенностей, влияющих на точность распознавания речевого сигнала.
МЕТОДЫ ДВОЙНОГО ЭКСПОНЕНЦИАЛЬНОГО СГЛАЖИВАНИЯ И ВРЕМЕННЫХ ОКОН ДЛЯ ПРЕДИКТИВНОГО МОНИТОРИНГА ЛВС: АНАЛИЗ, СРАВНЕНИЕ И ПРИМЕНЕНИЕ
Authors: Мырзатай А.А. , Рзаева Л.Г. , Жұмаділла Б. , Мұханова А.А. , Ускенбаева Г.А.
Published: December 2024

Данная статья посвящена исследованию методов предиктивного мониторинга локальных вычислительных сетей (ЛВС), с акцентом на сравнительный анализ и практическое применение методов двойного экспоненциального сглаживания (DES) и временных окон (WTC). Предметом исследования является поиск наиболее эффективного подхода к прогнозированию отказов в ЛВС путем детального анализа их ключевых характеристик, таких как принципы работы, преимущества, недостатки и сферы применения. В статье подчеркивается важность адаптации этих методов к специфическим условиям эксплуатации сети, что является ключевым аспектом повышения точности прогнозов и обеспечения стабильности работы ЛВС. Методы DES и WTC были выбраны не случайно: DES, как метод анализа временных рядов, демонстрирует высокую эффективность в прогнозировании долгосрочных трендов, в то время как WTC обеспечивает более глубокий анализ локальных изменений и краткосрочных аномалий. Проведенный сравнительный анализ позволил выявить их сильные и слабые стороны, а также оптимальные параметры для повышения эффективности.В статье представлены рекомендации по внедрению данных подходов в реальные условия работы сетей, что способствует раннему обнаружению потенциальных неисправностей и минимизации простоев. Кроме того, исследование уделяет внимание вопросам интеграции предиктивных методов в существующие системы мониторинга ЛВС, включая возможности их использования в сочетании с современными инструментами машинного обучения. Это позволяет предложить гибкие решения, которые могут быть адаптированы под различные эксплуатационные сценарии и потребности организаций.Выводы исследования являются актуальными для организаций, заинтересованных в модернизации своей сетевой инфраструктуры и переходе к проактивному управлению сетями. Такие подходы повышают не только надежность, но и экономическую эффективность за счет оптимизации обслуживания и предотвращения внеплановых простоев. Таким образом, работа вносит вклад в развитие технологий предиктивного анализа и демонстрирует их практическую ценность.
Co-Designing the SnowApp Climate Service for Winter Tourism Industry in Northern Finland
Authors: Mettiäinen Ilona , Coath Martin , Contreras Roxana , Toivonen Jusu , Moore John C.
Published: December 2024

Snowmaking and snow storing are increasingly used as climate adaptation strategies in ski resorts all over the world, including in the Arctic. While the decrease of the number of snow cover days is slower than in the Alps, snow security is decreasing particularly at the beginning of the skiing season in October-November. As there is up to 30-times difference between minimum and optimal conditions in the energy and water consumption in snowmaking, it makes sense to optimize the timing of snowmaking to ensure that snowmaking will not turn into maladaptation. Climate services are user-friendly ways of providing relevant climate information for end-users. Our team co-designed a climate service prototype for winter tourism centers in Northern Finland in 2017-2020 by a transdisciplinary co-design process involving climate science, modelling, tourism research, and practitioners including snowmaking professionals and environmental experts from a pilot enterprise. The versatile co-design methods utilized included e.g. visual methods and workshops, and co-evaluation of the prototype. The resulting climate service prototype SnowApp provides a reliable 4-week forecast on snowmaking conditions and hence it is a decision-support tool for ski resort management. The prototype is applicable in other geographical locations, too, and for other snow dependent businesses.
Urban Public Transportation Service Evaluation and Design Based on Service Encounter Discovery and Peak-End Rule
Authors: Lee Ching-Hung , Wang Zhichao , Feng Sujing , Li Fan , Zhang Wanting , Chen Chun-Hsien
Published: December 2024

This study introduces a human-centered and transdisciplinary engineering-centered “4D” design model, comprising Discovering Service Touchpoints, Defining Service Sore Points, Depicting User Experience, and Design Idea Development phases, which are based on service encounter discovery and peal-end rule. The systematic travel experiment involving 30 volunteers across six city tours was conducted to analyze user behaviors and needs. Emotional change curves are utilized to optimize peak and end of travel experiences. The findings validate the 4D model for redefining service encounters and leveraging the peak-end rule for the improvement of public transport services.
Text-Mining of E-Participation Platforms: Applying Topic Modeling on Join and iVoting in Taiwan
Authors: Sontheimer Moritz , Fahlbusch Jonas , Korjakow Tim , Chou Shuo-Yan
Published: December 2024

E-participation platforms have emerged as digital tool to facilitate citizen engagement through online deliberation, voting and oversight processes. The digital add-on for participatory democracy (Carole Pateman) can be found in different countries around the world. In Asia, the rollout of two platforms in Taiwan, namely iVoting and Join, has captured the attention of Western media outlets. However, there is little literature on the exact content debated and agreed on these platforms up to this point. Utilising recent advancements in NLP, we explore the content of the proposals that were made. In our study, we combine new approaches of text mining with political analysis on Taiwan’s e-participation platforms. The dataset, which includes 14,118 proposals from 2015 to 2022, has resulted in a distinct topic model being constructed for each platform. With the help of our method, we were able to cluster the proposals thematically and show which concerns were articulated and with how much approval. Based on a random sampling of 110 proposals, we were able to determine that our method assigns 81.82% of the proposals to the corresponding cluster. This can also significantly overcome language barriers, as we employed a translation pipeline within the text-mining process from Chinese into English. Our method is adaptable to e-participation platforms in various languages, providing decision-makers with a more comprehensive tool to understand citizens’ needs and enabling the formulation of more informed and effective policies.
Using Immersive Technologies and Digital Twins in a Real World with Non-Orthogonal Coordinate Systems
Authors: Beisheim Nicolai , Kayapinar Haydar , Amann Sebastian , Frank Robér , Jiang Xianbiao , Linde Markus
Published: December 2024

The paper describes the use of immersive technologies and Digital Twins in the architecture, engineering, and construction (AEC) industry. Immersive technologies have immense potential to improve interdisciplinary collaboration as they utilize a visual representation of virtual objects in their real-world perspective. This immersion facilitates effective communication between all parties involved, e.g. to identify errors during the planning and construction of buildings. A specific example of such interdisciplinary collaboration is kitchen planning. The architect draws the house and room plans, the kitchen planner plans the kitchen according to the homeowner’s wishes and the craftsmen then carry out their installations according to the plans for electricity, water, and heating. All plans are based on flat floors and perpendicular walls. However, this is rarely the case in a real building. The challenge with the exact visual representation of virtual objects in the real world using AR therefore lies in the positioning of objects such as a cupboard in relation to the non-orthogonal coordinate systems that result for each room from the real floors and walls. The paper presents an assistance system that integrates immersive technologies and Digital Twins. It is a solution approach for the transformation of object properties based on orthogonal coordinate systems into the non-orthogonal coordinate systems prevalent in reality. With the assistance system, the kitchen planner can create his plans using virtual reality (VR), customers can experience their kitchen virtually and the craftsmen can then be guided using augmented reality (AR), e.g. by precisely localising drilling positions for cabinets.
Leveraging Data Ecosystems in Model-Based Systems Engineering for Ecological, Circular Added Value
Authors: Graessler Iris , Pottebaum Jens , Holland Martin , Wiechel Dominik , Dickopf Thomas , Stjepandić Josip
Published: December 2024

There are numerous initiatives and lighthouse projects around Gaia-X to create the basics of open, trustworthy data ecosystems. One of the challenges in building these data ecosystems is to convince everyone involved of the advantages of multilateral data sharing. A prerequisite is also a common understanding of the rights of use and access to the data. Data sovereignty means that the data provider decides which data with which usage and access rights he wants to make accessible to which user group. Standardised digital representations by, for instance, the Asset Administration Shell (AAS enable creation of such data ecosystems, interlinking the physical and digital space. In the paper at hand, a conceptual approach named Decide4Eco is presented with the aim to enable systematic and flexible decision-making support for product planning and development concerning the sustainability of a product and the entire value chain. Methods of sustainability assessment are expanded to include predictive AI-based effects analyses.
AdaBoost-Based Transfer Learning Approach for Highly-Customized Product Quality Prediction in Smart Manufacturing
Authors: Chien Chun-Hua , Trappey Amy J.C.
Published: December 2024

Predicting product quality is a crucial element in smart manufacturing. Then, the development of robust learning models is essential based on historical data relevant to their respective products and production processes. The challenge of quality prediction models lies in the limited availability of production batches and their associated historical data in highly customized products like large power transformers, precision machine tools, and other industrial equipment. Despite the small dataset, ensuring the quality of the final product remains paramount. This study introduces an innovative transfer learning approach integrating adaptive machine learning and non-linear regression. The goal is to accurately predict the quality of highly customized products using datasets limited by the constraints of the primary suppliers with smaller production scales. The research employs a case study and dataset from the production of large power transformers. The input data for training and testing the predictive model include key power transformer parameters, such as core loss values and power loss. The approach utilizes transfer learning that transfers knowledge gained from one task (e.g., predicting the quality outcome of 50 kVA transformers) to a similar task (e.g., predicting the quality outcomes of 25 kVA and 100 kVA transformers). The proposed method enhances the model’s performance and generalization capabilities. Subsequently, the model is fine-tuned rapidly without compromising accuracy. This paper contributes to a comparative analysis with previous research, demonstrating the effectiveness and superiority of the proposed method. Manufacturers can leverage this approach to predict the quality of complex, small-batch, and highly customized industrial products. Ultimately, this method aids in improving production quality and reducing costs.
Explore Transdisciplinary Collaborations for Smart Device Development: Advancing Health-Related Smartwatch Designs for Social Impact
Authors: Trappey Amy J.C. , Shen Angus K.C. , Yu Mandy C.J.
Published: December 2024

This study explores transdisciplinary collaborations in smartwatch technology, with focus on health-related smart watch innovations. Among other leading brands, Apple Watch is a key player in this fast-growing market. Apple Watch has secured a remarkable position, boasting its market share to 37%. Specifically, it commands a 45% market share in the High-Level Operating System (HLOS) smartwatch sector, where advanced healthcare functions are focused. Utilizing advanced patent analysis techniques, including their technological clustering, maturity analysis, and technology function matrix (TFM), this research depicts technological innovations of smart watch, emphasizing on main features of mobile payment, watch bands, and physiological symptom monitoring based on robust domain ontology schema map. The study underscores the roles of transdisciplinary engineering in societal impact on disease care, reflecting on societal implications of smartwatch’s functional innovations. Considerations include issues of accessibility, sustainability, and popularization of health-related smart watch technologies. Through these transdisciplinary innovations, we explore opportunities for positive cares of societal changes (e.g., aging populations, elderlies live alone, and insufficient healthcare professionals per capita). Furthermore, the study discusses collaborative strategies between smartwatch and healthcare industries, highlighting roles of smaller companies in promoting diversity and innovation through strategic alliances. By mapping technological landscape and patent portfolios, this study identifies partnerships enhancing Apple Watch and its alliance’s competitiveness as a case study. This paper contributes to a comprehensive understanding of strategic positioning and alliances of technological innovations, particularly for the advanced of health-related digital smart solutions.
Construction of Green Technology Innovation Efficiency Indicators and Regional Comparative Analysis: Based on SBM-DEA Model
Authors: Lee Ching-Hung , Feng Sujing , Zhong Peng , Li Fan , Zhang Wanting , Chen Chun-Hsien
Published: December 2024

In the last four decades of reform, China’s economy has achieved historic success, propelled by rapid industrialization. However, this growth has adversely affected the environment. Addressing this, China is actively pursuing a balanced model of development that harmonizes economic and environmental interests. This study adopts transdisciplinary engineering approach. We first construct the green technology innovation efficiency indicators based on literature review and then adopt the super-efficiency SBM-DEA model considering undesirable outputs to measure the industrial green technology innovation efficiency values of 30 provincial administrative regions in China from 2008 to 2020. Sub-regionally, the eastern, central, and western areas differ significantly from one another; developed coastal provinces and certain central and western provinces have greater levels of efficiency.
A Transdisciplinary Engineering and Systems Approach for Decarbonizing UK Home Heating
Authors: Wise Freya , Cooper Adam , Eckert Claudia
Published: December 2024

At present, only around 10% of the heat pumps required to reach our critical 2050 climate goals are being installed in the UK. The government has set ambitious targets to phase out gas boilers by 2035, replacing them with heat pumps. This paper argues that instead of viewing the low carbon heating transition as a simple techno-economic issue, solved by a technology swap, we need a transdisciplinary systems approach to address this complex socio-technical challenge. Drawing on previous research and the literature we identify the current level of heat pump uptake and consider some of the barriers to the low carbon heating transition including technical aspects, installers skill shortages, financial barriers and informational challenges. We find that these barriers are mostly addressed in silos without considering the interrelationship between different aspects. Heat pumps should be considered in the context of a whole house approach to retrofit and barriers need to be overcome to make the technology more attractive to households. In this paper we call for a systemic, transdisciplinary approach to the low carbon heating transition to accelerate uptake: combining an understanding of social, engineering and policy perspectives. Key to this are systems-based methods and transdisciplinary approaches that enable engineering and engineers to be part of the solution. We present the benefits of this approach and suggest some principles for further research.
Eye-Tracking Insights into Traffic Controllers’ Situation Awareness Levels and Workload Conditions
Authors: Wong Martin , Yu Xiaoqing , Chen Chun-Hsien , Xia Ziqing
Published: December 2024

Traffic control systems, encompassing both air traffic control (ATC) and vessel traffic service (VTS), play a pivotal role in ensuring the safety and efficiency of transportation across aviation and maritime domains. High situation awareness (SA), which includes the ability to perceive information (Level 1 SA), comprehend the meaning (Level 2 SA), and predict future states (Level 3 SA), is crucial for traffic controllers to manage their respective traffic environments effectively under various workload conditions. Eye-tracking (ET) is a prominent physiological method to quantitatively assess operators’ cognitive workload and situation awareness as eye movements are closely related to one’s attention and information-processing mechanisms. This study aims to investigate the effects of SA levels and workload conditions on traffic controllers’ eye movement patterns using ET technology. Using ATC as a case study, experiments were conducted to collect eye movement data of 26 participants while they monitored aircraft on a simulated radar screen and answered freeze-probe queries of different SA levels (Level 1 and Level 2). Workload conditions were varied by the number of aircraft participants needed to monitor. Two-way repeated measures ANOVA showed significant main effects and interaction effects of SA and workload levels on certain ET metrics (e.g., total fixation duration, average fixation duration). This study contributes insights that could enhance the existing knowledge of SA levels in traffic control tasks and reinforce the evidence base linking eye movements and cognitive processes. Applying these insights to maintain optimal SA could reduce human error and elevate safety standards across different transportation sectors.
Towards a Unified Approach Between Petri Net Modelling, WCM and Digital Twin for Reconfigurable Manufacturing System
Authors: Thonke Igor , Szejka Anderson Luis , Canciglieri Junior Osiris
Published: December 2024

Today’s industry needs to be able to produce customized products in small batches with agility, low cost, and acceptable quality levels. The constant introduction of new products requires a rapid response to changes in the market and the implementation of innovative strategies. Manufacturing systems have evolved to meet market demands, considering crucial variables such as complexity, innovation, and responsiveness. Automation, using intelligent devices and various types of control, proposes models and solutions to make industrial operations more flexible. Petri Net modelling, a graphical technique that provides a clear and concise visual representation of complex systems, may intuitively map production line processes. Integrating world-class manufacturing (WCM) principles enhances the framework’s effectiveness. In this context, this article proposes a conceptual framework that combines reconfigurable manufacturing systems (RMS) concepts modelled by Petri Nets, the assignment of weights inspired by WCM, and simulation using the Digital Twin (DT). The framework offers a new horizon for achieving operational efficiency and continuous adaptation. Using simulation in a virtual environment it took a proactive approach to validate the framework’s effectiveness. This crucial step makes it possible to compare the results obtained virtually with the actual processes on the production lines. Applying this simulation verifies the model’s robustness and provides crucial insights for ongoing adjustments.
A Transdisciplinary Approach to Optimising Distribution Efficiency: Integrating Human Factors for Sustainable Routing
Authors: Trigos Federico , Osorio María Lucila
Published: December 2024

Intensified competition, heightened customer demands, and mounting pressure for cost savings and carbon footprint reduction characterise the dynamic landscape of contemporary business. Thus, the efficiency of distribution channels plays a pivotal role in meeting the evolving needs of diverse stakeholders. Management’s concern for the seamless flow of products to customers is underscored by imperatives to lower costs, enhance customer satisfaction, adhere to policies and regulations, and sustain personnel wellbeing and motivation. Operational research initiatives such as the Vehicle Routing Problem (VRP) have partially addressed these challenges. However, a comprehensive solution must transcend mathematical optimisation techniques to incorporate the intricate interplay between human resources, sales, customer service, and logistics. Going beyond traditional quantitative solutions, the contribution of this research is twofold: 1) a transdisciplinary framework designed to address the optimisation of distribution channels holistically by recognising the importance of negotiation among key stakeholders. Thus, the VRP solution, while indispensable, serves as a facilitative tool for negotiation, and 2) an industrial case is included to illustrate the application of the transdisciplinary framework, offering practical insights and managerial recommendations for implementing optimised routing strategies for the benefit of stakeholders. This research promotes social change by fostering a collaborative environment beyond mathematical efficiency by integrating environmental and human elements into the decision-making process.
Digital Transformation in Industry X.0: Competency Management in Organizational Environment
Authors: Mottin De Andrade José Mauricio , Rocha Loures Eduardo de Freitas , Szejka Anderson Luis , Canciglieri Junior Osiris
Published: December 2024

The Digital Transformation demands constant societal updating, accompanied by technological evolution to develop new projects, products, and services. Organizations, aware of the need to adapt to these changes, seek to understand emerging technologies’ meanings, concepts, and premises. However, this process is challenging, given the complexity of reconciling the external environment with the internal conditions of organizations and understanding, assimilating, and adopting innovations. Studies and scientific papers have addressed technical issues and explored critical success factors, barriers, limitations, and restrictions, proposing tools, models, frameworks, and methodologies to overcome organizational gaps. However, the lack of a direct connection between technologies and people’s skills and capabilities can hinder the digital transformation journey in organizations. In this context, this paper proposes a multi-criteria approach to correlating the evaluation criteria of Industry X.0 enabling technologies with human resources skills in the organizational environment. This research is applied to a Brazilian Electronics Manufacturing Industry case using the AHP method and TOPSIS Multi-Criteria Decision Making (MCDM). The findings show the possibility of a technical/social correlation, which can help managers better allocate internal resources according to the digital transformation technologies to be implemented in their products.
Novel Approaches for Scaling up Engineering-Based Inclusive Innovation
Authors: Joshi Pallavi , Kale Dinar , Wield David
Published: December 2024

Given their obvious need, why is it so hard for new pro-poor, engineering-based inclusive innovation (EII) to become more mainstream? Can new trajectories emerge that are more inclusive and environmentally sustainable? Those interested in these questions have studied the role of science and engineering in development but have faced a range of constraints. These include the poverty of those who might benefit most but also institutional barriers to the inclusion of some actors with knowledge and experience of scaling innovations towards the mainstream. This paper presents new theories and a set of case studies of attempts to scale and mainstream innovations. We have gathered data from and analysed scaling up case studies from different sectors and geographies. The paper advocates for the advantages of evolutionary approaches to development engineering that take account of institutional variety over static, neo-classical and one-size-fits-all approaches. We show that one size fits all does not apply to scaling up for engineering-based inclusive innovations. We illustrate that engineering innovations not replicated on a large scale have not necessarily failed. We conclude by arguing that it is possible to go beyond market failure approaches towards a more agile framework for the delivery of innovations and suggest that our results resonate with broader changes in the greening of the global economy.
Patent Landscape of ADS Transdisciplinary Technologies and Their Impacts on a Country’s Automotive Industry Development
Authors: Lin Yuga Y.C. , Trappey Amy J.C. , Shen Ovid T.C.
Published: December 2024

As autonomous driving system (ADS) continues to evolve, adopting Society of Automotive Engineers (SAE) levels 4∼5 concepts, the advances of driving automation/autonomy technologies include to fulfill modern vehicle market demands. ADS solutions require large integrations of multiple engineering disciplines, such as mechanical engineering, electrical engineering, computer science, and cognitive science for ADS’ human-machine interactions. Many ADS developers are actively engaged in R&D in interdisciplinary technologies, such as the domains of perception systems, communication systems, automatic route/path planning, and autonomous driving safety systems. Despite the rapid progress in ADS, there are challenges in various ADS domains to allow its popular- and safe-adoptions on the road! Therefore, this research conducts a comprehensive patent analysis for ADS domains. We first define the domain ontology schema (based on ADS literatures and experts’ verifications). Then, advanced patent search strategies (combing semantic and keyword Boolean search methods) and macro- and micro-levels patent analyses are conducted to present global ADS patent landscape. Overall, this study integrates multiple ADS transdisciplinary knowledge domains and patent analytical methods with various viewpoints. The analytical result provides a viable technological direction(s) for global ADS R&D teams to accelerate high-level autonomous vehicle development. Finally, based on the patent data resources, we also zoom in the ADS patenting landscape of Taiwan’s automotive companies and their main suppliers in ITC components. This research provides evident-based recommendations on the innovation and patenting strategies to increase their competitiveness in the ADS solution.
School Run to Net Zero: A Transition Engineering Labs Use Case Report
Authors: Ahrens Florian , Boulton Jack , Cherubini Paolo , Krumdieck Susan
Published: December 2024

The dominant transport mode for school journeys is safe, comfortable and affordable private automobiles. The transport system consists of well-engineered roads. Carers know that the car is usually the safest and most convenient option for the school run. Traffic congestion, air pollution, loss of exercise and increased risk to pedestrians and cyclists are thoroughly researched externality costs of the automobile school run. Net zero emission targets impose additional tensions for schools and local authorities to make rapid changes. Travel demand management research has been aiming to keep motorised vehicles away from schools, and to encourage physically active modes for the school run. But changing the infrastructure, travel behaviour and culture of a school community presents a wicked problem that requires transdisciplinary systems approaches from engineering and social science. This article reports on the Transition Engineering co-design process with incumbent stakeholders. The result is a novel learning and teaching programme which also achieved safe and sustainable school transport. The programme enables students to engineer the changes they require, communicate their needs to decision makers, and achieve net zero with fair provision. The school culture shifted to finding their own way to net zero school transport, contributing to wider community travel demand management efforts. The protocol of the design process, the co-design results, and a reflection on the preliminary stakeholder feedback are presented. The article addresses the wider challenge of how transdisciplinary transition engineering can deliver safety and sustainability of incumbent engineered systems, while navigating real-world social and economic dynamics.
Needs Analysis for Time-Based Management in Next Generation Air Traffic Management System
Authors: Toratani Daichi , Nakamura Yoichi , Oka Megumi
Published: December 2024

In order to cope with the increased demand for air transportation, air traffic system modernization projects have been undertaken in many countries. In future air traffic, the concept of time-based management (TBM) is being considered to improve the efficiency of air traffic flow. However, TBM is currently only a concept and it is not clear how it should be implemented in practice. This study therefore identifies the potential needs of stakeholders for time-based management. We created a stakeholder value network (SVN) for the stakeholders involved in the next generation air traffic management system and identified the primary stakeholders. We also conducted systemized interviews based on the Kano model with the primary stakeholders to identify their needs. By analyzing the SVN and interview results, the discussion was conducted on the potential needs of the primary as well as secondary stakeholders for a future control system to realize TBM.
Reframing Higher Education Management: A Transdisciplinary Digital Framework for University Administration
Authors: Coronel Roberto , Trigos Federico
Published: December 2024

Universities, while central to knowledge dissemination, face challenges in integrating their academic expertise into operational processes, often showing resistance to new technologies. This results in technological debt and inefficiencies in management systems, inadequately addressing the demands of digitalisation and affecting the quality of education and support services. There is a gap in the academic literature between theoretical models and their practical application in university administration, with existing methods not meeting the needs of modern educational environments. The contribution of this paper is the development of a transdisciplinary management framework designed to enhance the administration of academic institutions. This framework, derived from a comprehensive literature review, critiques traditional approaches, introduces a novel data model, explores its practical applications, and integrates digital strategies. A distinctive aspect of this review is the conceptualisation of academic quality as a quantitative construct, positioning it as both a deliverable and a critical axis for a digital transformation in Higher Education Institutions. This framework aims to standardise and modernise administrative processes in higher education, ensuring they align with the expectations of all stakeholders, including university staff, faculty, students, and the broader society. By implementing it, universities can make significant strides towards more effective and efficient administration, indirectly contributing to societal advancement. It focuses on improving institutional management and suggests a pathway towards a more accessible and high-quality educational landscape. This initiative exemplifies the potential of technological innovation in administrative practices, leveraging engineering principles to impact society positively.
Clarification of Correlations on Perceptions for Offshore Wind Energy and Other Environmental Issues
Authors: Mishima Kuniko , Mishima Nozomu
Published: December 2024

Renewable energy, especially offshore wind energy is one of the big focuses in aiming zero-carbon society in the world and in Japan, as well. In progressing such projects, social acceptance of the local community is one of the important problems. Recently, it is said that conventional NIMBY (not in my backyard) model is not enough in explaining resident’s perceptions and promote social acceptance. Even in ongoing offshore wind farm projects, in fact, there are small number of opponents and large number of uninterested. This paper tried to know why people oppose, agree or have no interests on the projects, and also tried to quantify the correlations of perceptions on offshore wind energy versus other social issues such as climate change, resource depletion etc. Since such information will show the concerns of people who are opposing to or having no interests on wind energies, it would be helpful in explaining the significance of the projects to the local communities. The authors carried out an internet survey to investigate people’s perceptions regarding offshore wind energy. Throughout the survey, the correlations between the other social issues and the attitude against offshore wind energy have been clarified. For most of the problems, residents’ perceptions and non-residents’ perceptions had similarities. However, for other social problems such as “aging population” etc., and other energy issues such as “energy price” also had different influence on residents and non-residents. The information can be the fundamental data in order to know what are the key points to be explained and how to build win-win relations between business stakeholders and local communities. The authors would like to contribute in establishing wide social acceptance to progress the project and achieve carbon neutral society.
Argument for Convergence: Sustainability Diaspora to Corrective Transdiscipline
Authors: Krumdieck Susan , Doughty Stephen , Rodriguez-Navas Guillermo , Whiteside Alan , Roderick Ian
Published: December 2024

Future energy scenarios usually show pathways to green energy futures are possible. However, since the 2015 Paris Agreement, scientific scenarios show human activity is accelerating toward catastrophic failures and loss. A group of transdisciplinary thinkers discussed the history of sustainability and contemplated how a disruptive shift could occur in time for energy decarbonisation and climate stabilisation. How have transitions occurred in the past, particularly those that involved corrective transdisciplines like fire safety, emergency management, food safety, or waste management? After man-made disasters, engineering and operations fundamentally change through duty of care. Corrective shifts in economic, policy and cultural paradigms seem to follow the evolution of engineering practice. Over time, the prevention of harm and loss is manifested in technological enterprise, infrastructures, energies, and behaviour. The only way the whole-system transition changes the trajectory from danger of catastrophic failure to survivable and thrive-able future is that a corrective transdiscipline evolves now. We followed a logic process, framing an argument, developing a supporting theory, and brainstorming the methods involved. The argument is that since 1970 millions of people have gained awareness of future risks, and a sufficient number have focused their working careers on sustainability. The sustainability-active people are not having sufficient impact to cause a corrective transition, because they have become a diaspora. Our reasoning follows that just transition will eventuate when the diaspora converges to a corrective transdiscipline and create training and research programmes which are valued by industry and policy.
Unravelling the ECHR: Components of Legal Case Analysis
Authors: Mumford Jack , Atkinson Katie , Bench-Capon Trevor
Published: December 2024

We report on a study undertaken to analyse AI performance on two tasks involved in automating processing of cases from the European Court of Human Rights: classification of legal case outcomes and keyword prediction. Results show variation across Articles and Court levels, and challenge the common viewpoint that larger legal corpora combined with larger models will be sufficient for effective automated legal reasoning. Legal summarisation, as reflected with keyword prediction, proved more challenging than outcome classification. Our results suggest the need for improved case law retrieval and understanding of contextual factors for effective automated legal decision support.
Robots in the Middle: Evaluating LLMs in Dispute Resolution
Authors: Tan Jinzhe , Westermann Hannes , Pottanigari Nikhil Reddy , Šavelka Jaromír , Meeùs Sébastien , Godet Mia , Benyekhlef Karim
Published: December 2024

Mediation is a dispute resolution method featuring a neutral third-party (mediator) who intervenes to help the individuals resolve their dispute. In this paper, we investigate to what extent large language models (LLMs) are able to act as mediators. We investigate whether LLMs are able to analyze dispute conversations, select suitable intervention types, and generate appropriate intervention messages. Using a novel, manually created dataset of 50 dispute scenarios, we conduct a blind evaluation comparing LLMs with human annotators across several key metrics. Overall, the LLMs showed strong performance, even outperforming our human annotators across key dimensions. Specifically, in 62% of the cases, the LLMs chose intervention types that were rated as better than or equivalent to those chosen by humans. Moreover, in 84% of the cases, the intervention messages generated by the LLMs were rated as better than or equal to the intervention messages written by humans. LLMs likewise performed favourably on metrics such as impartiality, understanding and contextualization. Our results demonstrate the potential of integrating AI in online dispute resolution (ODR) platforms.