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Unlocking the potential of public opinions for niche development using acceptance mining

Methodological Innovations 2023年第1期16卷 78-90页

作者： Digmayer, Claas Jakobs, Eva-Maria Department of Textlinguistics and Technical Communication Human-Computer Interaction Center RWTH Aachen University Aachen Germany

This paper proposes a combination of text mining and acceptance research as a methodological approach (“acceptance mining”) to facilitate the development of innovative technologies in niches. At the example of recharging infrastructures for electric vehicles, the approach is explored on a sample of over 20,000 user comments collected from social media and discussion forums. The results indicate that acceptance mining provides valuable insights into the demands of the public during all phases of niche development which allow shaping niches in socially acceptable ways. In particular, the method reveals requirements and risks of niche-development measures such as shielding, nurturing, and empowering niches as perceived by the public. The results are discussed regarding the potentials of acceptance mining for developing innovations in niches as well as its limitations and possibilities for optimization. Acceptance mining and its application to a case study are especially of interest for researchers and practitioners involved in niche development;the study results provide valuable insights for professionals engaged in developing recharging infrastructures for electric vehicles. © The Author(s) 2023.

关键词： Acceptance mining combination of quantitative and qualitative methods development of technological innovations in niches social acceptance of niche development technology development text mining

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Don’t You Worry ’bout a Thing? Identification and Quantification of Relevant Privacy Parameters Within the Acceptance of AAL Technology 7th

Don’t You Worry ’bout a Thing? Identification and Quanti...

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7th and 8th International Conference on Information and communication Technologies for Ageing Well and e-Health, ICT4AWE 2021 and ICT4AWE 2022

作者： Maidhof, Caterina Offermann, Julia Ziefle, Martina Chair of Communication Science Human Computer Interaction Center RWTH Aachen University Campus Boulevard Aachen Germany

ISBN: (纸本)9783031374951

To combat healthcare challenges Ambient Assisted Living (AAL) technologies offer the opportunity to support an independent life in older age. Although the potential and advantages of such technology are acknowledged, perceived barriers in particular referred to privacy still represent a hurdle for their acceptance. Applying a two-step empirical approach, this study aimed at the identification and quantification of relevant privacy parameters for the acceptance of visual AAL technology. First, a qualitative study investigated the participants’ cognitive privacy representations in a scenario in which AAL was installed in their own home to support life in older age. 12 participants (age range: 23–81 years) shared their opinions within semi-structured interviews. Based on these findings, an online survey (N = 134) study was applied in a second step in order to quantify the identified privacy parameters. Overall, the paper presents the qualitative key findings as well as the descriptive results of the quantitative study. The results show the usefulness of both methods to a) identify and understand thought processes of potential users regarding privacy requirements as well as b) to get insights into the relevance and meaning of the identified privacy parameters. The qualitative and quantitative findings are useful to inform technical designers as well as lawmakers to consider the privacy parameters during technology or law development. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Parameter estimation

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Design of Indonesian Culture Game Assets to Assist the Promotion of Culture Tourism 10

Design of Indonesian Culture Game Assets to Assist the Promo...

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10th International Conference on computer, Control, Informatics and its Applications, IC3INA 2023

作者： Gunadi, Nathania Felicia Pinasthika, Lalitya Talitha Prakasa, Esa Universitas Multimedia Nusantara Visual Communication Design Faculty of Art and Design Serpong Indonesia Human-Computer Interaction and Visualisation Research Center for Data and Information Sciences Bandung Indonesia

ISBN: (纸本)9798350394870

Bali is one of the islands in Indonesia which is famous for its cultural and natural wealth. Unfortunately, there is a gap in tourism between the nine regencies in Bali which are centered on South Bali. This phenomenon has the potential to impede the overall progress of tourism in Bali. Previous research has indicated that there are various strategies available to address this issue, with one potential approach being the utilisation of promotional media. One novel approach involves leveraging the popularity of games, given the significant player base in Indonesia. The Ministry of Tourism and Creative Economy also saw an opportunity to develop this promotional media as a substitute for conventional promotional media. Seeing the problems and potentials that exist, the author decided to research the design of game assets that can help increase the target's curiosity about the tourism culture in Bali. The research was conducted using a mixed research design method consisting of qualitative and quantitative data search methods. After conducting research on the target, it turned out that the potential for tourism in Bali is indeed high, but there is a gap in knowledge about tourist attractions in Bali. The target, who is a game player, is willing and able to invest time and energy to explore the information contained in the game. To create a game with high engagement so that the target is willing to invest effort and even money, it turns out that an appropriate story, immersion, visual, and challenging design is needed. © 2023 IEEE.

关键词： Tourism

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How context and design shape human-robot trust and attributions

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Paladyn 2021年第1期12卷 74-86页

作者： Biermann, Hannah Brauner, Philipp Ziefle, Martina Chair for Communication Science and Human-Computer Interaction Center RWTH Aachen University Campus-Boulevard 57 Aachen52074 Germany

In increasingly digitized working and living environments, human-robot collaboration is growing fast with human trust toward robotic collaboration as a key factor for the innovative teamwork tosucceed. This article explores the impact of design factors of the robotic interface (anthropomorphic vs functional) and usage context (production vs care) on human-robot trust and attributions. Theresults of a scenario-based survey with N = 228 N=228 participants showed a higher willingness to collaborate with production robots compared to care. Context and design influenced the trust attributed to the robots: robots with a technical appearance in production were trusted more than anthropomorphic robots or robots in the care context. The evaluation of attributions by means of a semanticdifferential showed that differences in robot design were less pronounced for the production context in comparison to the care context. In the latter, anthropomorphic robots were associated with positive attributes. The results contribute to a better understanding of the complex nature of trust in automation and can be used to identify and shape use case-specific risk perceptions as well as perceived opportunities to interacting with collaborative robots. Findings of this study are pertinent to research (e.g., experts in human-robot interaction) and industry, with special regard given tothe technical development and design. © 2021 Hannah Biermann et al., published by De Gruyter.

关键词： Risk perception

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The role of data governance in a high-level approach of data migration to open data

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Business Information Review 2024年第3期41卷 94-103页

作者： Yulfitri, Alivia Sensuse, Dana Indra Sumirat Hidayat, Deden Suryono, Ryan Randy Kautsarina Purwaningsih, Erisva Hakiki Prabuwono, Anton Satria Faculty of Computer Science Universitas Indonesia Depok Indonesia Faculty of Computer Science Universitas Esa Unggul West Jakarta Indonesia Research Center for Data and Information Sciences National Research and Innovation Agency (BRIN) Central Jakarta and Bandung Indonesia Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Lampung Indonesia Information and Communications Technology Human Resources Development Agency Ministry of Communication and Information Technology of the Republic of Indonesia Jakarta Central Jakarta Indonesia Faculty of Computing and Information Technology in Rabigh King Abdulaziz University Jeddah Saudi Arabia

Data quality issues are still a challenge in data migration. Existing methods mainly focus on technical issues. However, the problem of data quality is not only a technical problem, but the main one is the non-technical aspect. This paper aims to identify the role of data governance in the data migration process. The qualitative research method uses two primary references, namely the high-level data migration approach from Kazimir et al. and the DAMA-DMBOK framework. Both are highly compatible with data migration processes focusing on data quality and referencing governance roles. The case study was conducted in a central government working on data migration to the new One Data application. The results show that eight data governance roles are involved in 20 migration processes (65%). Non-technical activities related to data quality involve more than half of the data migration process. This paper proposes the role of data governance for non-technical aspects of the migration process. This paper presents a case study of the high-level data migration process and how data governance comes into play. This research can help the government and practitioners overcome problems that often occur in data migration, especially related to data quality. © The Author(s) 2024.

关键词： DAMA-DMBOK framework data governance data migration Indonesia’s one data Kazimir et al.’s approach open data

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What does ChatGPT know about natural science and engineering?

arXiv

引用

arXiv 2023年

作者： Balhorn, Lukas Schulze Weber, Jana M. Buijsman, Stefan Hildebrandt, Julian R. Ziefle, Martina Schweidtmann, Artur M. Delft University of Technology Delft Netherlands Human-Computer Interaction Center Chair of Communication Science RWTH Aachen University Aachen Germany

ChatGPT is a powerful language model from OpenAI that is arguably able to comprehend and generate text. ChatGPT is expected to have a large impact on society, research, and education. An essential step to understand ChatGPT’s expected impact is to study its domain-specific answering capabilities. Here, we perform a systematic empirical assessment of its abilities to answer questions across the natural science and engineering domains. We collected 594 questions from 198 faculty members across 5 faculties at Delft University of Technology. After collecting the answers from ChatGPT, the participants assessed the quality of the answers using a systematic scheme. Our results show that the answers from ChatGPT are on average perceived as "mostly correct". Two major trends are that the rating of the ChatGPT answers significantly decreases (i) as the complexity level of the question increases and (ii) as we evaluate skills beyond scientific knowledge, e.g., critical attitude. Copyright © 2023, The Authors. All rights reserved.

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An energy-aware routing scheme based on a virtual relay tunnel in flying ad hoc networks

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Alexandria Engineering Journal 2024年 91卷 249-260页

作者： Hosseinzadeh, Mehdi Ali, Saqib Mohammed, Adil Hussein Lansky, Jan Mildeova, Stanislava Yousefpoor, Mohammad Sadegh Yousefpoor, Efat Hassan Ahmed, Omed Rahmani, Amir Masoud Mehmood, Asif Institute of Research and Development Duy Tan University Da Nang Viet Nam School of Medicine and Pharmacy Duy Tan University Da Nang Viet Nam Department of Information Systems College of Economics and Political Science Sultan Qaboos University Al Khoudh Muscat Oman Department of Communication and Computer Engineering Faculty of Engineering Cihan University-Erbil Kurdistan Region Iraq Department of Computer Science and Mathematics Faculty of Economic Studies University of Finance and Administration Prague Czech Republic Department of Computer Engineering Dezful Branch Islamic Azad University Dezful Iran Department of Information Technology University of Human Development Sulaymaniyah Iraq Future Technology Research Center National Yunlin University of Science and Technology Yunlin Taiwan Department of Biomedical Engineering Gachon University Gyeonggi-do Seongnam-si13120 Korea Republic of

Flying ad hoc networks (FANETs) tackle diverse challenges, for example, dynamic topological structure, high mobility of nodes, low density, and energy restrictions. These challenges make problems in designing reliable and stable routing in FANETs. Hence, the design of a routing algorithm is essential for transferring data between drones. In this paper, an energy-aware routing scheme based on a virtual relay tunnel (EARVRT) is proposed in flying ad hoc networks. EARVRT includes a virtual relay tunnel (VRT) that manages relay nodes in the route discovery process and lowers network overhead. Moreover, three metrics, namely route energy, hop counts, and a new metric called path correlation are regarded in the path selection operation. Note that correlation is defined with regard to two scales, including the cosine similarity of two nodes and their distance. EARVRT is evaluated according to delay, network longevity, consumed energy, and packet delivery rate. Then, our scheme is compared with three methods, namely LoCaL, O-LAR, and PSO-GLFR. These results show the superiority and success of EARVRT in comparison with other algorithms. © 2024 The Author(s)

关键词： Drones

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XAI-FUNGI: Dataset resulting from the user study on comprehensibility of explainable AI algorithms

arXiv

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arXiv 2024年

作者： Bobek, Szymon Korycińska, Paloma Krakowska, Monika Mozolewski, Maciej Rak, Dorota Zych, Magdalena Wójcik, Magdalena Nalepa, Grzegorz J. Jagiellonian Human-Centered AI Lab Mark Kac Center for Complex Systems Research Institute of Applied Computer Science Jagiellonian University Krakow Poland Institute of Information Studies Faculty of Management and Social Communication Jagiellonian University Krakow Poland

This paper introduces a dataset that is the result of a user study on the comprehensibility of explainable artificial intelligence (XAI) algorithms. The study participants were recruited from 149 candidates to form three groups representing experts in the domain of mycology (DE), students with a data science and visualization background (IT) and students from social sciences and humanities (SSH). The main part of the dataset contains 39 transcripts of interviews during which participants were asked to complete a series of tasks and questions related to the interpretation of explanations of decisions of a machine learning model trained to distinguish between edible and inedible mushrooms. The transcripts were complemented with additional data that includes visualizations of explanations presented to the user, results from thematic analysis, recommendations of improvements of explanations provided by the participants, and the initial survey results that allow to determine the domain knowledge of the participant and data analysis literacy. The transcripts were manually tagged to allow for automatic matching between the text and other data related to particular fragments. In the advent of the area of rapid development of XAI techniques, the need for a multidisciplinary qualitative evaluation of explainability is one of the emerging topics in the community. Our dataset allows not only to reproduce the study we conducted, but also to open a wide range of possibilities for the analysis of the material we gathered. Copyright © 2024, The Authors. All rights reserved.

关键词： Adversarial machine learning

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User-centric evaluation of explainability of AI with and for humans: a comprehensive empirical study

arXiv

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arXiv 2024年

This study is located in the human-centered Artificial Intelligence (HCAI) and focuses on the results of a user-centered assessment of commonly used eXplainable Artificial Intelligence (XAI) algorithms, specifically investigating how humans understand and interact with the explanations provided by these algorithms. To achieve this, we employed a multi-disciplinary approach that included state-of-the-art research methods from social sciences to measure the comprehensibility of explanations generated by a state-of-the-art lachine learning model, specifically the Gradient Boosting Classifier (XGBClassifier). We conducted an extensive empirical user study involving interviews with 39 participants from three different groups, each with varying expertise in data science, data visualization, and domain-specific knowledge related to the dataset used for training the machine learning model. Participants were asked a series of questions to assess their understanding of the model’s explanations. To ensure replicability, we built the model using a publicly available dataset from the UC Irvine Machine Learning Repository, focusing on edible and non-edible mushrooms. Our findings reveal limitations in existing XAI methods and confirm the need for new design principles and evaluation techniques that address the specific information needs and user perspectives of different classes of AI stakeholders. We believe that the results of our research and the cross-disciplinary methodology we developed can be successfully adapted to various data types and user profiles, thus promoting dialogue and address opportunities in HCAI research. To support this, we are making the data resulting from our study publicly available. Copyright © 2024, The Authors. All rights reserved.

关键词： Adversarial machine learning

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Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

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computer Modeling in Engineering & Sciences 2024年第10期141卷 893-916页

作者： Sonali Das Saroja Kumar Rout Sujit Kumar Panda Pradyumna Kumar Mohapatra Abdulaziz S.Almazyad Muhammed Basheer Jasser Guojiang Xiong Ali Wagdy Mohamed Department of Computer Science&Engineering Gandhi Institute for TechnologyBPUTBhubaneswar752054India Department of Information Technology Vardhaman College of Engineering(Autonomous)Hyderabad501218TelanganaIndia Department of Electronic&Communication Engineering Vedang Institute of TechnologyBhubaneswar752010India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computing and Information Systems School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Research Centre for Human-Machine Collaboration(HUMAC) School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects *** depends on the type of leukemia and the extent to which cancer has established throughout the *** leukemia in the initial stage is vital to providing timely patient *** image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive *** can be simple to generalize computer vision(CV)-based and image-processing techniques and eradicate human *** researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its *** study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical *** projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical *** MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature ***,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia *** hyperparameter tuning process using MPA helps enhance leukemia cancer classification *** results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

关键词： Leukemia cancer medical imaging image classification deep learning marine predators algorithm

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