Reviewerly/exHarmony huggingface dataset:
Towards an Automatic Prompt Optimization Framework for AI Image Generation

Generative AI experienced a boom in 2022 with highlights such as the releases of Stable Diffusion for image generation and ChatGPT for conversational text generation. Although millions of images have been generated using products such as DALL-E 2, DreamStudio, and Midjourney, the learning curve for developing good text prompts that can lead to high-quality images remains steep, especially for inexperienced and less-technical users. Although various prompt engineering guides and tutorials have been developed to provide tips and guidance on prompt writing, there has been scant research on automatic prompt improvement algorithms and methods. In this paper, we present an automatic prompt optimization framework based on NLP analysis of a large prompt database and various machine learning models. A product based on our framework was developed and deployed for two months and real data were collected to evaluate our framework.
AI Explainability, Interpretability, Fairness, and Privacy: An Integrative Review of Reviews

This integrative review incorporates findings from reviews on AI explainability, interpretability, fairness, and privacy to synthesize and understand the concepts. There is synergy between these concepts. Increasing explainability, interpretability, and privacy might help increase fairness. Explainability is necessary to ensure AI is interpretable, fair, and private AI. AI cannot be fair if it is incomprehensible or does not involve consent. Explainable and interpretable AI affords transparency to help counteract biases. This review integrates knowledge and applicability of results of significant studies to inform practice. Human and non-human coding was used for interpretation and analysis. A total of 42 reviews were included in the integrative review. The four domains converged often regarding the need for human-centeredness, trustworthiness, and transparency. Although real-world implementation was a persistent theme for all domains, global models, transfer learning, neural and genetic networks, and machine and federated learning were the strategies most mentioned. These strategies rely on metaphorical and deductive logic that risks underfitting, overfitting, and untethering from real-world grounding and complexity. The review significantly contributes to new thinking by integrating all conceptual findings. Overall, consensus definitions are needed on all terms, as are multi-disciplinary and multi-perspectival analyses.
Digital Information Provision on Gastronomic Tourism

In this paper we present the design and implementation of a multimodal solution for the promotion of gastronomic tourism in the municipal area of Heraklion city. The provided solution is comprised of standalone information systems accompanied by a mobile app for the presentation of thematic routes. By facilitating a rich knowledge base and a collection of audiovisual material, the applications allow the visitor to explore dimensions of tangible and intangible cultural heritage connected to gastronomy and plan a personalised experience orchestrated by their mobile device while on the move in the municipal area.
Apply CNN Style Transformation on Industry 4.0

This project uses AI (artificial intelligence) rendering technology to realize how to present a photo in different forms of style. In a python environment, we establish a style transfer, inputting an original image for the software to recognize, then putting in a rendered style image for the software to perform the program. After 500 cycles are executed, the style will not have a stable form as the AI is evolving. By the time it reaches 1000 images, the algorithm has already remembered the common points of the images and grasped its own style, indicated by the gradual convergence of the loss function. The software will then produce different styles of rendered images.
Mapping the Factors Affecting Online Education During the Pandemic in Greece: Understanding the Importance of Designing Experiences Through Different Cultural and Philosophical Approaches

Due to the Covid-19 pandemic, education in many countries transferred abruptly online. Students, teachers, and parents - who were also working from home - had to adjust to the new reality. To understand this new reality and the experiences of the students, teachers, and parents about online education we conducted a qualitative study using interviews and contextual inquiry. The data collected were thematically analyzed and discussed based on the different perspectives. The article presents a conceptual mapping of the online education experience of students, teachers, and parents in Greece and proposes a conceptual design framework as well as a set of guiding questions to support the design process for a better user experience of cross-cultural online educational platforms in similar contexts.
A Fundamental Study on Discrimination of Dominant Hand Based on Motion Analysis of Hand Movements by Image Analysis Using Deep Learning

Recent advances in image analysis technology using deep learning have made it possible to analyze human motion more easily. Traditionally, such analysis has involved attaching physical markers and optically or electromagnetically measuring the marker positions, or manually labeling images with labels for joint positions. These methods take time to prepare for measurement, making it difficult to measure without causing psychological stress to the subject. In addition, it was not possible to analyze movements in daily life environments in a simple manner. Therefore, by using an image analysis method based on deep learning, it is possible to analyze human behavior in an effortless way, and is expected to be applied to behavior analysis, where the preparation for measurement has a considerable influence on the results. In this report, hand movements of healthy adults were subjected to analysis as a preliminary study. The results of analysis of video recordings of dominant and nondominant hand finger tapping showed that it is possible to discriminate between dominant and nondominant hands based on tapping speed, as in previous studies.
Coordinated Motor Display System of ARM-COMS for Evoking Emotional Projection in Remote Communication

The authors have proposed a coordinated motor display system for called ARM-COMS (ARm-supported eMbodied COMmunication Monitor System) that detects the orientation of the subject's head by face tracking through image processing technology and physically moves the monitor to mimic the subject. The idea behind this is that the remote subject's avatar behaves as if it functions during video communication and interacts with the local subject. In addition, ARM-COMS responds appropriately with voice even when the remote subject's head movements cannot be detected. Furthermore, ARM-COMS is a highly responsive system by responding to local subject's voice. This paper introduces the basic concepts of ARM-COMS, describes how it was developed, and describes how the basic procedures were implemented in a prototype system. Then this paper introduces the results of teleconferencing experiments using ARM-COMS, and describes the findings obtained from the results, including the effect of physical interaction through ARM-COMS, camera shake problem, and evoking emotional projection in remote communication.
Visual Guidance in Game Level Design

With the development of game consoles and game computers, the number of players is increasing, and game maps and scenes are becoming larger and larger, allowing players to freely engage in activities within the map, which in today's game industry is called an open world. We are going to study visual guidance in game level design, with the focus on how players should follow the path envisioned by the level designer when they enter the actual game map. We will also study the method and flow when designing game levels.
ChromicCanvas: Interactive Canvas Using Chromic Fiber

This study aims to realize a simple and flexible method of expression by combining chromic materials and digital fabrication tools. Focusing on UV embroidery thread among chromic materials, we propose "ChromicCanvas," an interactive drawing system that allows users to draw with various colors and drawing patterns. The prototype consists of canvases created with embroidery thread and pen and stamp-type devices for switching the shape and color tone to be drawn. This paper describes the preliminary verification of UV embroidery threads, the prototype device developed, and evaluation experiments.
The Viability of User-Centered and Human-Centered Design Practices with Natural User Interfaces (NUIs)

User centered Design (UCD) and Human-centered Design (HCD) are philosophies and methodologies that consider human needs first in the design of products, services, processes, and systems. They also involve users in the design process through observation, interviews, testing, workshops, and as co-designers. UCD and HCD emerged in the mid-century when computers interfaces were difficult to use and the profession of HCI was just emerging. Are UCD and HCD future-proof practices or does rapidly evolving technology require new design philosophies and methodologies? This paper examines how these practices apply to future interfaces, specifically Natural User Interfaces (NUIs). NUIs are interfaces that go beyond the desktop paradigm. NUIs by their definition use a wide variety of modalities and technologies including augmented and virtual reality, robotics, and wearables. They simply allow humans to interact with computer-enabled devices in ways that are more natural for humans. While NUIs are easier for humans to learn and use, they are more complicated and challenging to design because they have more capabilities than current interfaces and are more responsive to humans. They utilize more automatic behaviors. Technologies like robots and medical devices have safety concerns. What design philosophy or methodologies are needed to support good usability design in the future when NUIs will be much more common? Do UCD and HCD suffice?
Cognitive Mapping for AI-Augmented Interactive Print

Interaction design has evolved in recent decades, being improved by artificial intelligence, ubiquitous computing, internet of things and tangible materials. While some research regards combining print media with interaction as an opportunity for development, the quantity of relevant publications is underwhelming, as it can be regarded as a difficult and risky approach. We noted a lack of scientific focus on interactive print probably due to dispersed knowledge of areas that contribute to understanding this phenomenon. To fill this deficit, we propose a first combination of main concepts and their respective connections, to draw a more enlightening framework of understanding and which will aid future research. We intend to know what are the relations between print media, interaction, understood by its materiality and tangibility, HCI and the challenges of AI and ML. How has each wave of HCI affected this set of concepts? How can research regarding interactive print enhanced by AI and ML move forward? Taking on the challenge of articulating concepts and definitions, we produced a cognitive map to better understand interactive print. Our cognitive map reveals the need to deepen research between all areas that surround interaction design and print media that still have social, cultural and educational relevance. The map contributes with a possible network of connections to elaborate theoretical frameworks at the intersection of these areas and opens a space of opportunities for designers to act.
Behavioral Biometrics Authentication in Critical Infrastructure Using Siamese Neural Networks

Cybersecurity is a crucial issue in today’s critical infrastructure to ensure a secure connection between the administrator and the session. Detecting insiders is a difficult task for cybersecurity professionals, as insiders are hard to detect and identify and thus require advanced techniques to prevent their activities. These users may be current or former employees with access to the organization’s data. A methodology for authenticating users of critical infrastructure systems using deep learning networks is proposed in this paper. Behavioral biometric data or user behavioral characteristics are converted into an image and used in the proposed methodology for authentication. The keystroke data obtained from the login password is transformed into a more acceptable format for deep neural networks. Siamese neural networks can be used for image similarity detection to distinguish a real user from an insider. In the current investigation, numerical keystroke data has been transformed into graphical representations. The transformed data are then subjected to comparative analysis, leading to the determination of similarities between the biometric keystroke profiles. The experiments have shown there is a tendency for the accuracy of a Siamese neural network with a triplet loss function to decrease with increasing margin size. The results obtained are promising, showing that using a deep learning-based approach to analyze images derived from user keystroke data can improve intrusion detection accuracy and perform user authentication more efficiently.
Ux in Immersive Reality: The Power of the Users

Repeated exposure to a sign can generate habits with it and, consequently, less attention to it. In order to prevent this, it is possible to make use of new accessories that make the signage more dynamic. On the other hand, the individual's behavior tends to change when he/she is in a dangerous situation, which makes the same individual behave differently in terms of a warning when there is a stressor load or not. For this purpose, an immersive virtual environment was generated, in which different warning variables can be set, as well as different types of hazard presence to evaluate the user's actions. This paper presents the evaluation of the users of the immersive environment. The results show that most users have different feedback to the signage depending on the degree of risk exposure. This study is of great importance for the prevention of occupational hazards, as well as for the creators and developers of games and extended realities.
Live Classification of Similar Arm Motion Sequences Using Smartwatches

This work provides an approach to monitoring the activities of people with dementia. Classification of daily activities helps automate caregivers' documentation of activities and can provide information about disease progression and disease-related changes. The prototype developed combines smartwatch technology with a neural network to classify activities in real time. A smartwatch offers the opportunity to integrate sensor technology into a patient's daily life without disruption. To identify promising combinations of sensor data, accelerometer, gyroscope, gravity, and attitude data are sampled 20 Hz (Hz) and sent to a recurrent neural network called Long Short-Term Memory (LSTM) for real-time classification. In this work, we systematically compare how well an LSTM works in combination with different sensor combinations in detecting different activities. Using triaxial user acceleration, gravity, position, and gyroscope data, the trained model achieves over 90% accuracy. The implemented real-time classification provides a direct statement at which time and with which probability one of the four activities was carried out. This approach performs significantly better than previous tests using classification algorithms and also stands out from similar approaches in the literature. We achieve flexible, location-independent classification of very similar activities based on smartwatch sensor data. In doing so, the classification of the novel prototype is performed in real-time. This also provides room for interpretation of how the knowledge gained can be used to detect motor skills in the care of patients with neurological diseases.
Development of a Domain Specific Sentiment Lexicon (DSSL) for Evaluating the Quality of Experience (QoE) of Cloud Gaming

Domain-specific reviews created by the user on cloud gaming platforms offer valuable and cost effective information of high ecological validity. While the user generated content (UGC) has been used widely across many fields successfully in evaluating user experience and satisfaction, it has received proportionally less attention in the field of measuring the quality of experience (QoE) of cloud gaming. Besides, it remains an open question how well the UGC can be applied to measure the QoE of cloud gaming. In view of the poor performance of general purpose emotion lexicons (GPEL) in the modeling user experience of a specific product, this paper proposed a method of measuring the QoE of cloud gaming grounded on a Domain Specific Sentiment Lexicon (DSSL). This DSSL provides a structural distribution of the sentiment on 62 indicators. Its high criterion validity and discriminative power demonstrated the potential of transforming DSSL into a psychometric scale of QoE of cloud gaming.
Why are Some Makerspaces not so Male-Dominated

Makerspaces have been shown to play a significant role in promoting innovation and entrepreneurship by providing users with the tools and resources to produce and create products. Nonetheless, the makerspace movement has been scrutinized for exhibiting severe gender disparity, often causing women to feel excluded from participation. As a result, many women are deprived of the tools and educational opportunities commonly available in a typical makerspace. This study utilizes a qualitative research method to investigate makerspaces located across the United States. The results of our research indicate that some makerspaces do not exhibit the gender bias that is often associated with the movement, and we explore the factors that may be contributing to these makerspaces’ success at gender balance. Our findings reveal that women in leadership, inclusive policies and regulations, women-focused activities, and safe and accessible facilities are instrumental in attracting a more diverse demographic. This study holds the potential to inform the design of innovation spaces that prioritize inclusivity and foster a greater sense of community among makers of all genders.
Utilizing Different Voice Value to Understand Voice Assistant Users’ Enjoyment

This study aims to understand if various voice assistants' (VAs') voice parameters (i.e. pitch range and speech rate.) that may have effect on users' enjoyment and preference. VAs follows various voices as Siri has five kinds of recordings in the English (American) channel. For the reason that Siri has diversified voices, this research aims to use a non-binary voice (i.e. ios 15.4, recording 5) as a sample and use AUTO-TUNE software to modify their pitch ranges and speech rates. Through a web-based survey conducted on Qualtrics, participants—recruited from Amazon Mechanical Turk (MTurk)—were asked their feelings after listening to 4 patterns, which included higher pitch range, lower pitch range, higher speech rate, and lower speech rate. I ask about their enjoyment of listening to those patterns across five different categories: motivation, goal, proof, evaluation, and potential. In a sample size of 114, this study discusses how the responses differ between the different categories and how they link to various VA voice parameters. In this study, I demonstrate that various VA voice parameters have no significant effect on users' motivation, goals, proof, and evaluation. Users' potential is slightly affected by the changeable voice parameters of this human-computer interaction however it is still not significant. With this study, I indicate that the pitch range and speech rate of the voice assistant, Siri iOS 15.4 recording 5, has no effect on the enjoyment of their user's experience.
MetaWelt: Embodied in Which Body? Simplex Didactics to Live the Web 3.0

Nowadays, the increasing use of technologies such as cloud computing, the Internet of Things (IoT), and virtual and augmented reality is blurring the line between real and virtual contexts, leading to the concept of an “on-life” reality. Facebook's recent rebranding to Meta underscores the company's commitment to building a metaverse, a decentralized hybrid ecosystem that combines digital and physical elements. As VR technology becomes more mainstream, it is being incorporated into educational platforms, leading to questions about how teaching will adapt to a new virtual environment where the body's role in learning is different. This study aims to demonstrate how the theories of simplexity and simple didactics can serve as a foundational framework for exploring the potential of virtual reality (VR) in the field of education.
Best Practice for Inclusive Journey Mapping and Diversity in User Participation

This work investigates how co-creation workshops, in which user journeys and personas are developed jointly with workshop participants, can be made as inclusive as possible for a wide range of participants and thus personas and journeys. The discussion is based on five recent research projects with 28 workshops in total and more than 78 participants, resulting in 31 user journeys and 25 personas. The lessons learned have been summarized as best-practice recommendations for the implementation of inclusive persona work and journey mapping. It is shown that both physical and virtual journey mapping workshops may result in a great diversity of personas and variety of journeys, provided that the participants are highly diverse, that universally designed tools and aids are used, and that inclusive techniques and protocols are followed.
A Comparison Between Performing a Heuristic Evaluation Based on a Formal Process Using a System and the Traditional Way: A Case Study

The heuristic evaluation belongs to the usability inspection methods and is considered one of the most popular methods since it allows the discovery of over 75% of the total usability problems involving only 3 to 5 usability experts. However, certain problems and challenges have been identified during their execution. One of the identified problems is the lack of validation scenarios that demonstrate the contributions and benefits of incorporating systems that provide support for heuristic evaluation. Although there are case studies that could support the problems described above, the literature has shown that these are quite scarce and, for the most part, are software products that are used as support tools for certain elements to be evaluated, such as, for example, visual clarity of the system, page links validations and readability. For this reason, since there are no validation scenarios that demonstrate the contributions and benefits of the automation of heuristic evaluations through software products, the result is that there is a low level of confidence in usability evaluators to use a system that supports the heuristic evaluation process, for so the inspection continues to be carried out manually. As a part of previous research, a software product was implemented to support the five steps (planning, training, evaluation, discussion, and report) of a previously selected formal process to perform heuristic evaluations. To test the previously developed software product, a case study that demonstrates the contributions and benefits of incorporating the web application developed as a support tool for heuristic evaluation was proposed, and it has been of the utmost importance since it has allowed performing a comparative analysis between the evaluation when is performed by using the selected formal process through a template contained in an MS Excel format document, and by using the web application developed as a result of the aforementioned previous research. The results demonstrated that a higher average result was obtained, for the team that used the implemented system, in all the established criteria. The interpretation of the results can be summarized with the fact that the system obtained a better perception by the team who used it than the results obtained by the team that used the evaluation template.