bluuebunny/crossref_metadata_2025 huggingface dataset:
Pembangunan Industri Dengan Sektor Lain
Authors: Alif Finno Fidzaky  , Verinda Yelanita  , Muhammad Yasin
Published: June 2024

This research examines the interaction between industrial development and other sectors in the economy. The main objective of this research is to identify the impact of industrial development on the agricultural, service and infrastructure sectors and understand the synergies that can be created between sectors. The methodology used includes secondary data analysis from government reports and case studies from several developing countries. The research results show that industrial development has great potential to encourage overall economic growth if it is well integrated with other sectors. Increased productivity in the industrial sector is often followed by growth in the services and infrastructure sectors, but this can lead to imbalances with the agricultural sector if it is not balanced with appropriate policies. This research suggests the need for a holistic approach in development planning that involves all sectors to achieve sustainable economic development.
FUNCTIONAL OUTCOME OF MINIMALLY INVASIVE PERCUTANEOUS PLATE OSTEOSYNTHESIS AMONG PATIENTS WITH PROXIMAL TIBIA FRACTURES
Authors: SAEED M , INAM M , HAQ SU
Published: June 2024

Proximal tibia fractures are complex injuries that pose significant challenges in orthopaedic surgery. Minimally invasive percutaneous plate osteosynthesis (MIPPO) has been increasingly adopted as a treatment method due to its potential benefits in reducing soft tissue damage and promoting faster recovery. Objective: To assess the functional outcome of minimally invasive percutaneous plate osteosynthesis (MIPPO) among patients with proximal tibia fractures. Methods: A prospective cohort study was conducted in a tertiary care hospital over a period of two years, from January 2021 to December 2022. Thirty-five patients presenting with proximal tibia fractures were treated using the MIPPO technique. The Schatzker classification was used to categorize the fractures. Functional outcomes were assessed using the Knee Society Score (KSS) at six months postoperatively. Data were analyzed using descriptive statistics and chi-square tests to determine the significance of outcomes. Results: The most frequent type of fracture, according to Schatzker's classification, was type I, followed by type II and type III. An excellent outcome was observed in 21 patients (60%), good outcomes in 8 patients (22.9%), fair outcomes in 5 patients (14.3%), and poor outcomes in 1 patient (2.9%). Postoperative complications included infection in 2 patients (5.7%). Conclusion: Minimally invasive percutaneous plate osteosynthesis (MIPPO) is a safe and effective technique for managing proximal tibia fractures, yielding excellent functional outcomes in most patients.
Progress on the connection performance of steel-engineered bamboo beam-column connections under cyclic loads: a review
Authors:   School of Urban Planning and Municipal Engineering, Xi’an Polytechnic University, Xi'an, 710048, China, Liu Yang ,   State Key Laboratory of Green Building in Western China, Xian University of Architecture & Technology, Xi'an,710055, China,   The key laboratory of well stability and fluid & rock mechanics in Oil and gas reservoir of Shaanxi Province, Xi’an Shiyou University, Xi’an, 710065, China., Liu Kun ,   School of Urban Planning and Municipal Engineering, Xi’an Polytechnic University, Xi'an, 710048, China., Wang Wentao ,   Department of Civil and Environmental Engineering, University of Michigan, MI, 48109, USA; School of Civil and Environmental Engineering, Harbin Institute of Technology, Shenzhen, Shenzhen 518055, PR China *Corresponding Author: Yang Liu. Email: yangliu@xpu.edu.cn., Fan Linlin ,   School of Urban Planning and Municipal Engineering, Xi’an Polytechnic University, Xi'an, 710048, China., Li Binbin ,   State Key Laboratory of Green Building in Western China, Xian University of Architecture & Technology, Xi'an,710055, China.
Published: June 2024

Bamboo is a great building material due to its low carbon and environmental friendless. The connection performance of beam-column joints had an impact on the seismic performance of the whole structure. The beam-column connection performance is critical in earthquakes. Steel-engineered timber connections have good seismic properties, and the properties of bamboo and timber are very similar. Therefore, the form of wood structure connection can be used in bamboo structures. The type of member materials used and the connection forms applied determine the structure elastic behavior. Common engineered bamboo has been introduced, and the current connection form of engineered timber has been summarized in this paper. Secondly, research on the indicators of connection performance under cyclic loads has been introduced, including damage forms, strength, ductility, and energy dissipation capacity. Thirdly, the traits of various types of connections are presented, and this paper could be taken as a reference for future studies on connections in steel-engineered bamboo structures.
Ferns of Chandrabadani and surrounding areas in Tehri district, Uttarakhand
Authors: Joshi Pushpesh , Kumar Brijesh , Dwivedi Himanshu , Pande H.
Published: June 2024

The present paper deals with ferns of Chandrabadani and surrounding areas of Tehri District. A total of 35 species belonging to 23 genera under 12 families, have been collected from the study area and are being reported in the present communication.
Processo de criação na indústria criativa
Authors: Czrnhak Thomás , Pinheiro Cristiano Max Pereira , Mohr Thomas , Bez Marta Rosecler
Published: June 2024

O presente artigo objetiva relatar o processo de design de um serious game de literatura e literacia, destinado a uma turma de quinze alunos de até seis anos, com a obra O Mágico de Oz sendo tomada como referência. Apoiou-se em metodologia de relato ex post facto. Os achados da experiência podem contribuir para o design de jogos educacionais de literatura projetados a crianças de ensino primário ressaltando a importância dos fatores de assimilação e familiaridade, abordagem a priori de conteúdo instrucional, cooperação entre pares e dosagem de grau de facilidade de uso.
Diagnóstico de Temas para o Desenvolvimento de Conteúdos com Ênfase em Sustentabilidade e Moda para o Suporte de Novos Profissionais da Área
Authors: Lopes da Silva Dal Bosco Glória , Everling Marli Teresinha
Published: June 2024

Atualmente observa-se movimentos progressivos no campo da moda que buscam alternativas contra a cultura do fast fashion, do consumo excessivo, do descarte quase imediato, para aquisição de cada vez mais novas peças, que ficarão obsoletas na mesma rapidez que as primeiras adquiridas, o problema enfatiza a identificação dos pontos necessários a serem trabalhados por novos profissionais, sendo o objetivo geral diagnosticar temas relevantes para a produção de conteúdo, orientado para novos profissionais, tendo em vista à moda e sustentabilidade. A abordagem utilizada é o design para a sustentabilidade. A metodologia abrange pesquisa bibliográfica, em livros, periódicos, on-line, anais de congresso, artigos e afins sobre os temas empreendendo para a sustentabilidade; práticas de consumo na sociedade atual no mercado de moda; desperdício de recursos; fibras têxteis,  características sustentáveis, ações e iniciativas voltadas à produção e consumo consciente. Também foi aplicada pesquisa de campo, para identificar temas que interessam a estudantes em design de moda voltado à questão da sustentabilidade. Os resultados foram estruturados como diagnóstico acerca de temas relevantes a serem tratados pelos novos profissionais de design de moda.
Palavras Chave: cenário têxtil; consumo consciente; moda sustentável.
Pancasila sebagai Sistem Etika
Authors: Arya Wibawa Atmanegara  , Ayunda Cinta Dinanti  , Utama Muhammad Daffa Adika , Randika Aryasatya Adipermana  , Salman Sahid Sabiq  , Sulthan Ariq Haikal  , Yayang Furi Furnamasari
Published: June 2024

Pancasila and ethics are intertwined because they both teach positive values. Pancasila ethics are based on Pancasila values, such as divinity, humanity, unity, populism, and justice. From these values, the Pancasila ethical system emerged which serves as a guideline for individual behavior in social life in Indonesia. The Pancasila ethical system continues to be developed in its implementation, so that every step and effort of the Indonesian people in achieving common goals can be directed correctly. This research uses a qualitative approach with literature study methods or literature research. This research focuses on written works, including research results that have been published. The main source of data for this article is the results of research published through google scholar. Data collection is carried out using the keywords "Pancasila" and "ethical system". Data analysis was carried out qualitatively with the stages of data reduction, data presentation, and conclusion drawn. The findings of this research are that the application of Pancasila as an ethical system is moral guidance that can be actualized into concrete actions, involving various aspects of life. Pancasila as a state ethical system also needs to be applied as the foundation of morality and state integrity that is hidden in every individual citizen so that he can master spiritual and mental attitudes in community life. Critical-analytical studies are also needed to find out if the element of subjectivity is fanatical and avoidable
Desain Pembelajaran yang Inspiratif dan Pengembangan Kurikulum yang Responsif bagi Kompetensi Pendidik
Authors: Hasni Walidatil , Aprima Septi Gia , Fadriati Fadriati
Published: June 2024

This study aims to explore an in-depth understanding of curriculum development, learning design, and educator competencies in the context of education in the era of independent learning. Qualitative research methods are used to gain a comprehensive understanding through in-depth analysis of the relevant text and material context. Data were collected through literature study, observation, and interviews. The results showed that effective learning design requires teacher involvement in designing learning that is relevant to student needs, as well as being able to integrate educational technology and innovative learning strategies. In addition, this study also highlights the importance of developing a curriculum that is responsive to changing times and pays attention to the needs of individual students. Educator competencies that include material understanding, pedagogical skills, and managerial abilities are also key factors in ensuring the effectiveness of curriculum implementation. The findings of this research make an important contribution in enriching the understanding of how curriculum development, learning design, and educator competencies can support each other in improving the quality of education in the era of independent learning
Prescription pattern of antibiotics in dermatology: A Profile from a tertiary care teaching hospital, Kerala
Authors: Lal Laona , Nair Parvathy
Published: June 2024

Background: Antibiotics are commonly used in dermatology for infectious and inflammatory diseases. A study on the pattern of prescriptions will help in establishing fundamental data to enhance the utilization pattern of medications, elevate the standard of treatment, and enable prescribers to identify issues associated with drug usage, including adverse drug reactions, antibiotic resistance, drug interactions, and polypharmacy.

Aim and Objective: The aim of the study was to describe the prescription pattern of antibiotics given to inpatients with dermatological disorders.

Materials and Methods: This was a record-based descriptive study where the case records of 240 inpatients of the dermatology department of a tertiary care teaching hospital during the period from January 2019 to January 2022 were studied. The demographic profile, pattern of skin diseases reported, and pattern in antibiotic drugs usage were recorded with the help of a predesigned pro forma.

Results: The mean age of the study population was 52.04 ± 16.91 years with male to female ratio 2.62:1. The most common skin disease diagnosed was Psoriasis (17.91%). Out of the 518 antibiotics prescribed to the patients in the study, the most preferred route of antibiotic administration was oral (48.84%). The most common oral antibiotic was cloxacillin (37.94%) while the most common parenteral antibiotic prescribed was cefotaxime (83%). Fusidic acid (78%) and mupirocin (16%) were commonly prescribed among the topical antibiotics. Amoxicillin-clavulanic acid combination (76%) was commonly prescribed among the fixed drug combinations. Among the topical antibiotics, 8.78% were prescribed as fixed-dose combination with steroids. Antibiotics (29%) constitute the major class of drugs among prescriptions followed by steroids (14%) and antacids (11%). Most of the prescribed antibiotics belonged to the Access group of antibiotics according to AWaRe classification of antibiotics (63.2%).

Conclusion: The most common class of antibiotics prescribed was beta-lactam group of antibiotics. The study will help in formulating guidelines for rational prescription of antibiotics with special reference to dermatological cases and create awareness among physicians for effective therapeutic outcome. This will avoid the burden of antimicrobial resistance and pave pathway for the strengthening of economy.
Dünya Yönetişim Göstergeleri Yardımıyla Ülkelerin Gelişmişlik Seviyelerinin Karar Ağacı Yöntemiyle Tahmin Edilmesi
Authors: Özkan Batuhan , Kaya Hakan
Published: June 2024

Ülkelerin gelişmişlik düzeylerini anlamak ve değerlendirmek, karmaşık ve çok boyutlu bir süreçtir. Ekonomik, sosyal ve politik faktörlerin birbirine entegre olduğu bir ortamda uluslararası kalkınma göstergeleri bu ülkelerin performansını ölçmede ve karşılaştırmada önemli bir rol oynamaktadır. Bu çalışmanın amacı, dünya yönetişim göstergeleri aracılığıyla ülkelerin gelişmişlik düzeylerinin belirlenmesidir. Bu bağlamda analizlerde makine öğrenmesi yöntemlerinden biri olan karar ağacı yöntemi kullanılmıştır. Çalışmanın örneklemini 187 ülke oluşturmaktadır. Veri setini, 2020 yılına ait Dünya Gelişmişlik Göstergeleri (DGG) ve Dünya Çapında Yönetişim Göstergeleri (DÇYG) oluşturmaktadır. Gelişmişlik göstergesi olarak ülkelerin Gayrisafi Yurt İçi Hasıla (GSYH) değerleri kullanılmıştır. GSYH değerleri ATLAS yöntemine göre yüksek, üst-orta, alt-orta ve düşük gelir seviyesine sahip ülkeler olmak üzere dört farklı sınıfa ayrılmıştır. Yapılan analizler neticesinde karar ağacı tahmin modeline ait doğruluk değerinin %80,85 olduğu görülmüştür. Bir başka ifadeyle yönetişim göstergeleri kullanılarak ülkelere ait gelişmişlik düzeyleri hakkındaki tahminler yüksek doğrulukla tahmin edilmiştir. Model tahminin bu denli yüksek olması neticesinde yönetişim göstergeleri ile ülkelerin gelişmişlik seviyeleri arasında bir ilişki olduğu çalışmanın sonuçları arasında ifade edilmiştir. Yüksek gelir grubuna ait ülkelerin sınıflandırılmasında özel sektörün gelişmesine izin veren ve teşvik eden Düzenleyici Kalite (DK) boyutunun etkin olduğu görülmüştür. Yüksek ve üst-orta gelire seviyesine sahip ülkelerin sınıflandırılmasında İfade Özgürlüğü ve Hesap Verebilirlik (İÖ) değişkeni, alt-orta ve düşük gelir grubuna ait ülkeler için ise Siyasi Istikrar (Sİ) ve Hukukun Üstünlüğü (HÜ) değişkenlerinin etkili olduğu görülmüştür.
The Role of Collaborative Virtual Reality Engagement in Stroke Survivors' Rehabilitation
Authors: Marques Bernardo , Oliveira Sérgio , Ferreira Hugo , Amorim Paula , Dias Paulo , Sousa Santos Betriz
Published: June 2024

Stroke stands out as a significant contributor to disability and mortality rates among individuals worldwide. Despite their important role, conventional rehabilitation methods often struggle to maintain motivation due to their repetitive nature, leading to potential social and mental health repercussions. This work advocates for the integration of Virtual Reality (VR) serious games in a collaborative, multi-user setting, informed by a Human-Centered Design (HCD) methodology with stroke survivors and healthcare professionals from a rehabilitation center. Through immersive, task-specific exercises in dynamic virtual environments, we strongly believe that stroke survivors can engage in shared experiences, fostering motivation and social interaction. We report our initial efforts toward the creation of a collaborative VR framework and delve into the next steps of the proposed research line. With this, we hope to transform existing approaches and better complement traditional rehabilitation methods for improving the overall quality of life for stroke survivors.
The Ethics of Immersion: A Scoping Review of VR and AR Technologies
Authors: Zallio Matteo , Huang Taihe , Osaki Yutaka , Hong Shiqi , Chang Xiaomin , Liu Wei , Ohashi Takumi
Published: June 2024

Immersive technologies such as augmented reality (AR), virtual reality (VR), mixed reality (MR), and extended reality (XR) are rapidly evolving, presenting significant opportunities for enhancing user experiences. Nevertheless, their widespread adoption introduces substantial ethical challenges that necessitate thorough exploration. This research conducts a comprehensive investigation into the ethical considerations associated with these technologies, employing a methodical literature review and synthesis approach. Utilizing the PRISMA-ScR framework alongside the KJ method, this study analyzes 34 pertinent articles, uncovering 189 unique ethical concepts that are subsequently organized into 15 coherent categories. The analysis illuminates critical ethical concerns, including the protection of user rights within virtual spaces, the dichotomy between real and virtual worlds, the imperative for inclusive and equitable access, the necessity to ensure user safety and well-being, and the call for the establishment of robust ethical governance frameworks. The derived findings propose a future research agenda that accentuates the importance of navigating ethical dichotomies, enhancing inclusivity, advocating for user-centric development practices, instituting strong governance measures, and bolstering ethical awareness. By tackling these identified ethical dimensions, the present study seeks to promote a judicious and ethical advancement of immersive technologies, aiming to enable society to leverage their profound benefits responsibly while adhering to ethical standards and mitigating potential risks.
Mitigating Orbital Debris via Responsible System Design
Authors: Heilala Janne , Texeira Kalea
Published: June 2024

The escalating space debris problem threatens satellite operations and space sustainability. This study proposes an intelligent debris removal spacecraft integrating reconfigurable surfaces, optimization algorithms, and ethical design principles. The architecture adapts to diverse debris shapes, ensuring precision targeting and capture efficacy. The development integrates sustainability criteria for responsible manufacturing and end-of-life deorbiting. Quantitative trajectory analysis and case studies of successful projects inform refined workflows. With machine learning enabling responsive debris characterization and risk probabilities alongside stakeholder participation driving conscientious design choices, the system pioneers a contingency-based approach to space preservation. The research underscores technical ingenuity balanced with environmental foresight as instrumental for the principled advancement of aerospace engineering for shared posterity.
Application of Large Language Models in Stochastic Sampling Algorithms for Predictive Modeling of Population Behavior
Authors: Xu Yongjian , Nandi Akash , Markopoulos Evangelos
Published: June 2024

Agent-based modeling of human behavior is often challenging due to restrictions associated with parametric models. Large language models (LLM) play a pivotal role in modeling human-based systems because of their capability to simulate a multitude of human behavior in contextualized environments; this makes them effective as a mappable natural language representation of human behavior. This paper proposes a Monte Carlo type stochastic simulation algorithm that leverages large language model agents in a population survey simulation (Monte-Carlo based LLM agent population simulation, MCLAPS). The proposed architecture is composed of a LLM-based demographic profile data generation model and an agent simulation model which theoretically enables complex modelling of a range of different complex social scenarios. An experiment is conducted with the algorithm in modeling quantitative pricing data, where 9 synthetic Van Westendorp Price Sensitivity Meter datasets are simulated across groups corresponding to pairings of 3 different demographics and 3 different product types. The 9 sub-experiments show the effectiveness of the architecture in capturing key expected behavior within a simulation scenario, while reflecting expected pricing values.
Predictive functions of artificial intelligence for risk assessment in remote hybrid work
Authors: Simoncelli Giuditta , Luca Bernardi Mario , De Angelis Laura , Anastasi Sara , Bonafede Michela , Artenio Emanuele , Pecori Riccardo
Published: June 2024

Remote hybrid work risk assessment is an obligation for the employer according to Occupational Safety and Health (OSH) regulations. Risk management requires the cooperation of the worker, who is now responsible for recognizing and managing hazards, necessitating specific technical training. Generative Artificial Intelligence (AI) technologies can support the knowledge needs of both workers and employers as effective tools for prevention in occupational health and safety, respecting privacy regulations and avoiding remote control of workers. Researchers from INAIL, Universitas Mercatorum, and the University of Sannio are developing an AI-based assistant for assessing risk in remote and hybrid work, facing challenges in assistant training due to limited availability of data on incidents and illnesses related to remote work. The generative AI prototype will be able to evaluate the relationship between remote work activities and types of injuries, using domestic injury data to identify patterns and high-risk areas. By integrating Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), the hybrid model will enable a dynamic and comprehensive analysis of hazards, contributing to a better understanding of risk factors in hybrid work contexts.
A Novel Agent-Based Framework for Conversational Data Analysis and Personal AI Systems
Authors: Kurylek Bartosz , Camara Arthur , Nandi Akash , Markopoulos Evangelos
Published: June 2024

This paper introduces a novel agent-based framework that leverages conversational data to enhance Large Language Models (LLMs) with personalized knowledge, enabling the creation of Artificial Personal Intelligence (API) systems. The proposed framework addresses the challenge of collecting and analysing unstructured conversational data by utilizing LLM agents and embeddings to efficiently process, organize, and extract insights from conversations. The system architecture integrates knowledge data aggregation and agent-based conversational data extraction. The knowledge data aggregation method employs LLMs and embeddings to create a dynamic, multi-level hierarchy for organizing information based on conceptual similarity and topical relevance. The agent-based component utilizes an LLM Agent to handle user queries, extracting relevant information and generating specialized theme datasets for comprehensive analysis. The framework's effectiveness is demonstrated through empirical analysis of real-world conversational data and a user survey. However, limitations such as the need for further testing of scalability and performance under large-scale, real-world conditions and potential biases introduced by LLMs are acknowledged. Future research should focus on extensive real-world testing and the integration of additional conversational qualities to further enhance the framework's capabilities, ultimately enabling more personalized and context-aware AI assistance.
Equilateral Active Learning (EAL): A novel framework for predicting autism spectrum disorder based on active fuzzy federated learning
Authors: Daliri Arman , Khoshbakhti Maryam , Karimi Samadi Mahdi , Rahiminia Mohammad , Zabihimayvan Mahdieh , Sadeghi Reza
Published: June 2024

Autism Spectrum Disorder has a significant impact on society, and psychologists face a crucial challenge in identifying individuals with this condition. However, there is no definitive medical test for autism, and artificial intelligence can assist in diagnosis. A recent study outlines a framework for diagnosing autism spectrum disorders using Equilateral Active Learning (EAL). EAL incorporates three commonly used machine learning techniques: active learning, federated learning, and fuzzy deep learning. The framework integrates four robust datasets of children, teenagers, young adults, and adults using federated and fuzzy deep learning. Using EAL, autism spectrum disorder can be diagnosed with 90% accuracy, which is comparable to several machine learning methods, including statistical, traditional, modern, and fuzzy approaches.
Towards Safer Routes: Exploring the Potential of Artificial Intelligence and Augmented Reality in Children's School Commuting Environment Design
Authors: Hei Jinghao
Published: June 2024

Augmented reality technology is characterised by its mobile, practical, multimodal, and data-driven trend. This paper presents a design framework that employs AI and augmented reality technologies to address an entire process of intelligent perception and design intervention for mitigating risks in children's school commuting environments. For intelligent perception section, 617 accident news texts were used for training purposes utilising natural language processing (NLP) and machine learning techniques. As a result, 6 influential characteristics related to children's school commuting environment (Time, road type, surrounding features, area functional type, user, age type and connection type). The prediction model holds 3 severity degrees and covers 6 types of incidents. For design intervention section, design strategies and techniques are defined based on various degrees. The prototype is designed using a mobile augmented reality device and a smart watch as design touchpoints.
Improving product design efficiency through integrated AI tools: an empirical study
Authors: Zhong Yubin , Ou Jiawei , Zheng Kaiqiao , Luximon Yan , Luo Jing
Published: June 2024

In recent years, the rapid development of artificial intelligence models has spawned a variety of artificial intelligence tools, especially those related to image generation. These tools have revolutionized the field of design. This study focuses on the overall process of product design, breaking it down into multiple parts to evaluate the functionality and utility of a range of AI tools. The goal is to test and determine if these tools can effectively facilitate and streamline the product design process.After identifying effective AI tools, conduct comprehensive testing to get the operations and parameters in these AI tools that are more consistent with the product design workflow. The study integrates these optimization operations into the entire product design process, resulting in a fundamental approach. This approach Outlines how these AI tools can work together to improve the efficiency and quality of the entire product design process, aiming to match or exceed the capabilities of human designers. In addition, preliminary experiments have verified the effectiveness of the method, showing that the design efficiency and quality are improved after adopting the integrated AI tool method in the product design process.Main research contents:1 Evaluate various AI tools in multiple parts of the product design process to identify effective solutions.2 Test the parameters and operating procedures of the identified AI tools to achieve the best results.3 Establish basic methods in combination with selected AI tools and conduct experiments to obtain preliminary results.Main research methods:1. In-depth understanding of product design process through in-depth interviews and field observation.2 Use data analysis and professional evaluation to evaluate the effectiveness of AI tools.3. Control variable method was used to design experiments to verify the effectiveness of the established method.
Understanding Emotional Needs across Stroke Rehabilitation Phases for Affective Design
Authors: Lyu Yixuan , Chen Yue
Published: June 2024

Despite significant physical and psychological challenges, stroke patients often face overlooked emotional needs in rehabilitation. Such emotional needs can be satisfied by the innovative design of rehabilitation equipment, but the specific patient needs across recovery phases (acute, stable, and maintenance) remain unclear for targeted emotional design. This study aims to identify pain points and emotional needs in each recovery phase through observations and interviews with 31 participants and 60 hours of data. Acute-phase patients struggled with both communication challenges and psychological barriers from disability and identity shifts. Stable-phase patients experienced loneliness, self-blame, and boredom during intense therapy. Maintenance-phase patients, while physically improving, felt hospital fatigue, desired social interactions and entertainment, and worried about reintegration. Based on these findings, we also discuss emotional design implications and examples tailored for each stage.
Sit back, relax, and sniff some lavender!: Investigating the Impact of Scent on Passengers in Air Taxis
Authors: Xiao Shengdi , Li Jingjing , Dmitrenko Dmitrijs
Published: June 2024

Air taxi services (ATS) have emerged as a potential solution to tackle congestion and pollution issues associated with traditional taxis. However, the perception of passengers on innovative experiences remains under-studied. Extensive literature has established that scents possess a strong influence on human emotions and can contribute to relaxation. To bridge this research gap, we adopted the Wizard-of-Oz Study method, widely employed in human factors research, to investigate (1) the scent preferences of individuals regarding ATS and (2) the influence of scents on passengers in air taxis. We show that there was a statistically significant difference between male and female responses to lavender(p<0.001*) and peppermint(p=0.001*) flavours in liking. However, males and females responded statistically significantly differently in terms of relaxation only to peppermint scent(p=0.042*), and not to lavender(p=0.063). Our findings have the possibility to provide a guide to the development of experience design on the ATS.
Semantic Decision Support for Action Forces with Risk Stratification from Estimated Physiological Strain, Cognitive-Emotional Stress and Situation Awareness
Authors: Haid Florian , Schneeberger Michael , Carballo Leyenda Belén , A Rodríguez-marroyo Jose , Ladstätter Stefan , Weber Anna , Almer Alexander , Mosbacher Jochen , Paletta Lucas
Published: June 2024

In the life-threatening work of action forces, a decision support system (DSS) must provide a software application that should improve a mission decision maker's capability to make decisions. This requires analysing large amounts of data and to present and visualize the best possible options available. In case of first responders, where errors in decision-making can have fatal consequences, timely identification of increased risk of physiological collapse, insufficient cognitive readiness and lack of situation awareness is mandatory. This paper therefore introduces our Semantic Decision Support System (SDSS) that can apply intelligent analytics on data from wearable biosignal sensors, to provide feedback in terms of risk stratification. It also includes a recommender engine that identifies the best next action at team management level. Its novelty lies specifically in the combination of various multimodal data streams each being equipped with assessment modules, risk stratification and recommender engines in order to finally combine various aspects of decision support that is based on psychophysiological measurement technologies. All relevant data is systematically merged into an advanced expert dashboard, providing a comprehensive platform for the continuous real-time monitoring and visualization of critical information. This capability enables the ongoing assessment of risk levels associated with a diverse group of action forces. The centralized dashboard serves as a powerful tool, enabling careful surveillance and prompt response to emerging risks across a broad spectrum of operational scenarios.
How to manage the safety of service robots operating in coexistence with demented patients
Authors: Thomessen Trygve
Published: June 2024

The developing elderly wave is expected to give a considerable demand for robotic solutions in the elderly care, especially in the nursing homes, to compensate for the lack of human resources required to maintain the quality of the elderly care services. Thus, social service robots are expected to fill an important role in the future, by providing services like logistics, remote medical consultations, entertainment, physical training etc. However, new challenges appear when introducing service robots in an environment where residents with impaired cognitive skills, coexist with service robots. This, especially, since the patients cannot take care of themselves, and are formally NOT responsible for any unfortunate safety conflicts. Thus, compared to operating in e.g. a normal restaurant, a service robot in a in a nursing home requires additional attention to the risks mitigation to ensure a safe operation. This includes analysis of both additional physical risks in addition to new, interperceptual risks. This paper addresses the complexity of fulfilling the required safety of service robots operating in nursing homes, and an extended risk mitigation methods is suggested in order to minimize the unavoidable, residual risk.
Democratization in Industry via Multi-Agent Systems, The case of a production company
Authors: Gheibi Noushin , Boeschen Stefan
Published: June 2024

Democracy is typically a question of political government. Nevertheless, in recent years, the forms of democratic development have changed in the course of the governance debate. According to Council of Europe, E-democracy tools use technology to boost key democratic values like participation, inclusivity, efficiency, effectiveness, transparency, openness and accountability within the democratic system. Alongside civil society, companies are playing an increasingly important role in the establishment of collective order. The difficult aspects of this development can be seen in the concentration of market power and the circumvention of employee co-determination. At the same time, however, Small and Medium Enterprises (SME) sometimes take on the role of pioneers. One key example is about AI-based decision support systems in order to realize new decision-making and co-determination opportunities. This raises the question of what potential for democratization and, if so, in what form, is actually emerging here. On the one hand, this article raises the question of how aspects of a “democratization” in companies can be realized and presents a conceptual approach for analysing such ambitions. On the other hand, specific challenges of a “democratization” via digital tools will be worked out by analysing the case study of a SME. An important result is that forms of democratization via multi-agent systems are only perceived as democratic if they are introduced and procedurally anchored within the company through social processes that are perceived as legitimate.
The Effects of Short-term Meditation on the Creativity of Novice Designers: A Pilot Design Task Study using TTCT-Figural Assessment
Authors: Li Yaning , Zhang Yu , Yang Yumeng , Zihan Tang , Hu Zhenxian , Xie Chengxi , Pan Ziao , Chen Chengye , Qi Tuoda , Zhu Zhixian , He Qian , Li Shumin , Yin Yuan , Han Ji , Childs Peter , Cascini Gaetano , Li Meng
Published: June 2024

Creativity is long regarded as one of the fundamental traits that indicates design capability. The concept of creativity encompasses the capacity to produce innovative and novel concepts or ideas, to devise or articulate imagination and intellect, and to stimulate the potential of imagination and ingenuity embodying their capacity to conceive, craft, and develop innovative ideas for products. Previous studies have revealed the connection and functionality between meditation and creativity. However, general creativity measurements, which studies to date have mainly focused on, might not be able to demonstrate the performance of designers in a creative process adequately.Therefore, this study applied a design task-based evaluation with traditional TTCT assessment, which might be more suitable to describe the creative performance of novice designers. The study aims to explore: (1) the relationship between short-term meditation and creativity; (2) the effects of short-term meditation on the design qualities in design tasks of novice designers.42 first-year design students were recruited and were divided into meditation group (n=24) and control group (n=18). Participants conducted a demographic survey and the Torrance Tests of Creative Thinking (TTCT, in its figural variant) firstly. The meditation group was then given a 110-minute audio tape-based meditation intervention, and the control group was given a 110-minute audio tape intervention, which is a recording of scientific articles. Both interventions were performed twice a week on the weekends. After that, TTCT was given to the participants again. Then each participant received an interview on the changes in mood state and creativity. After the TTCT on the second day, the participants completed the Design with Morphological Table Task (DwMT) to assess their design qualities in a product design task. Through data analysis, TTCT results indicate that short-term meditation can significantly improve the creativity of novice designers and the meditation group outperformed the control group significantly in fluency and elaboration. DwMT results show that the meditation group significantly provided better design qualities than the control group.
Decision-making augmentation system for solving the problem of risk reduction
Authors: M. Yemelyanov Alexander
Published: June 2024

The decision-making augmentation system for solving the problem under risk and uncertainty is demonstrated. This system helps decide on the most satisficing alternative for solving the problem of risk reduction. Satisficing alternative is an alternative that satisfies requirements for risk reduction and is sufficient for the decision-maker. The process of solving the problem is self-regulating, where the problem goal, initially set up as an uncertain “sufficient risk reduction”, should be clarified in the process of problem-solving to reflect the formation of the mental model, while the activity goal should be accordingly modified by adding corresponding objectives as criteria for success to reflect the formation of the level of motivation. This iterative process ultimately leads to the most satisficing solution to the problem. Given human limitations in computational capacity due to the size of working memory, the augmentation system supports computation on various levels, encompassing motivation, self-efficacy, and risk reduction. This system is implemented in ED2® mobile web apps, addressing both reactive and proactive risk reduction for present or future risk events, respectively.
Measuring Flow: Perceived Emotions & Arousal-Valence
Authors: Kannegieser Ehm , Ratz Johannes
Published: June 2024

Deep focus states, like Immersion and Flow are important parameters when it comes to an enjoyable experience during learning activities. To measure these mental states usually self-assessment questionnaires, answered by the subject after the experience, are used. Because of the shortcomings of this method, the ultimate goal is to establish an alternative measuring method through correlations of physiological sensor data. Exploring the Physiology of deep focus, in the course of prior studies, physiological data of participants was recorded during activities and inspected for correlations with Flow and Immersion. By broadening the experimental scope, this paper explores the effect of participant's emotions on reaching states of deep focus.
Evaluation of Voice vs. Text Communication Modes in Simulated UAM Operations.
Authors: Strybel Thomas , Battiste Vernol , L. Vu Kim-Phuong , Marayong Panadda , Ahuja Stacey , Schmitz Maegan , Cheung Justin , Culver Chloe , Alfaroarevalo Andrew , Shankar Praveen
Published: June 2024

Urban Air Mobility (UAM) is a system that is expected to operate within and around metropolitan environments, utilizing electric, vertical takeoff and landing (e-VTOL) aircraft, to create on-demand, highly automated passenger and cargo-carrying air transportation services. Many stakeholders are developing such systems, although several barriers to UAM operation remain. Two barriers being addressed in our simulation facility are pilot training and air traffic management operations. Although the UAM industry is focused on autonomous operations, the initial UAM operations will have ground or onboard pilots, yet the forecasted pilot shortage will be problematic. Completely autonomous systems will result from an evolution, of pilot-based operations, to onboard operators flying with automated assistance and finally completely autonomous vehicles. We are currently investigating and evaluating concepts for simplified vehicle operations and air traffic management using a virtual UAM eVTOL vehicle in a CAVE virtual environment. In the first test of the UAM vehicle (e.g., Strybel et al., 2021) pilots and reported that the simulation was sufficiently realistic for tests of UAM operations. Here we report on a subsequent investigation of communication modes for pilots flying UAM routes over the San Francisco metropolitan area. The routes consisted of stops at six vertiports, either at airports or other locations, for picking up/dropping off passengers. UAM pilots communicated with air traffic control and vertiport managers using either voice or text messaging. Voice communications were consistent with current day air traffic control operations. Text communications were via a custom message pad application that enabled standard messages to/from ATC (requests and responses) via touch input. Six certified pilots flew two routes using each mode of communication. We evaluated the impacts of these communication modes on pilot performance (flight time and communication latency) and subjective responses (workload and subjective feedback). Feedback regarding the messaging application and simulation facilities were also collected and will be described in the presentation.
Random Gazes, Telling Eyes: Exploring Gaze Transition Entropy as a Performance Indicator in Evaluating Instructional Designs
Authors: De Bruyne Jonas , De Leersnijder Laetitia , Talsma Durk , Demanet Jelle , Saldien Jelle , Bombeke Klaas
Published: June 2024

This study explores gaze transition entropy (GTE) as an objective performance measure in industrial assembly training. GTE can be defined as a metric of randomness in gaze patterns over time, with low entropy indicating predictable and structured patterns and high entropy indicating unpredictable and irregular patterns. Using mobile eye-tracking glasses, 28 participants completed a cable assembly task while gaze patterns were analyzed across specific areas of interest (AOIs). Preliminary findings from six participants show decreased GTE with increased task familiarity and task experience. Additionally, preliminary trends suggest a positive relation between GTE and self-reported hesitation, indicating its potential as an objective gauge of uncertainty. Furthermore, a theoretical variation on gaze transition entropy where the effect of consecutive fixations at the same object is factored out is explored. This research offers insights into the potential of using gaze transition entropy to objectively assess hesitation and proficiency in training, providing a potential avenue for enhancing instructional content within instructional design using objective evidence. Further refinement and exploration of gaze transition entropy could significantly impact training quality assessment across diverse domains and can enable promising applications in other fields as well.
Does penalty help people learn to detect phishing emails?
Authors: Singh Kuldeep , Aggarwal Palvi , Gonzalez Cleotilde
Published: June 2024

Phishing attacks are increasingly prevalent and pose a significant threat to organizations worldwide. Many organizations implement phishing training programs to educate employees on how to recognize and avoid phishing attacks. Incentives are often used in these training programs to motivate employees to participate and engage with the material. However, the impact of incentives on the effectiveness of these training programs is not well understood. Similarly, how often such training should be provided, remains an additional factor in improving detection ability. Past research has provided evidence that frequency impacts the susceptibility to phishing emails. However, the interaction of frequency and incentives in phishing training is not well known. Key questions persist: Do individuals exhibit greater attention and motivation to detect phishing emails when penalties are imposed? How does exposure to more phishing emails contribute to evading penalties? This paper manipulates the frequency of phishing emails during the training phase and incentive structure for classifying emails. Experiments were conducted using a Phishing Training Task (PTT) i.e. an interactive software platform that emulates key tasks associated with email response decision making to test the impact of learning factors on phishing detection. The results indicate that imposing penalties for incorrect decisions does not have a significant effect on the detection performance for most of the conditions. Thus, our results suggest providing a symmetric incentive structure may not improve the phishing detection ability. These findings highlight the importance of experimenting with additional incentive structures in phishing training programs. This paper will provide guidelines to use cognitive models to design effective incentive structures.
Planning the perfect heist: An adversarial cyber game
Authors: Buckley Oliver , Montanarini Jake , Quinlan Helen
Published: June 2024

This paper introduces "Heist: An Adversarial Cyber Security Board Game", designed to enhance cyber security knowledge through interactive gameplay. Players engage in asymmetrical team-based play, simulating a 'cyber heist' on a sci-fi hotel. The unique setup integrates technical, social, and organisational strategies, enabling diverse cyber security approaches using a deck-building mechanic.Heist development emphasised CyBOK knowledge areas, resulting in core mechanics focused on deck building, promoting critical thinking and collaboration. Players deploy specialists to attack or defend, with attackers aiming to tarnish the hotel's reputation while the defender seeks to identify them through digital evidence. The game strikes a balance between strategy and learning, broadening participation in cyber security and deepening players' understanding of tactics.Playtesting sessions informed refinements, enhancing educational impact and entertainment value. Heist exemplifies an innovative approach to cyber security education, merging theory and practical application in an immersive board game format. It showcases the potential of educational games for complex subjects like cyber security.