Reviewerly/exHarmony huggingface dataset:
Stochastic adaptive CL-BFGS algorithms for fully complex-valued dendritic neuron model

This paper proposes two stochastic variance reduced gradient algorithms based on adaptive complex-valued limited-memory BFGS (ACL-BFGS) algorithm, which are established on the calculation of Wirtinger gradient for fully complex-valued dendritic neuron model (FCDNM). Basically, the explicit expression of Wirtinger gradient is derived to enable the quasi-Newton algorithm for the training of FCDNM. A stochastic variance reduction strategy is adopted such that the number of samples per batch is increased during the optimization process to ensure the effectiveness of the stochastic algorithm. The stochastic ACL-BFGS algorithm with variance reduction (SACL-BFGS) can be efficiently applied for the training of FCDNM. Furthermore, by generalizing the A3 accumulative multi-step quasi-Newton method, the A3-SACL-BFGS algorithm is presented to achieve fast convergence. The experimental results on some benchmark prediction and classification problems conclusively imply that the proposed SACL-BFGS and A3-SACL-BFGS algorithms for FCDNM are clearly superior to complex-valued backpropagation (CBP), CL-BFGS and ACL-BFGS algorithms.
Disseminated gold mineralization under varied redox conditions: Constraints from microscopic observation, geochemistry, and thermodynamic modeling on fluid-rock interactions in lamprophyres, Zhenyuan gold deposit

The controls of fluid redox states on disseminated gold mineralization remain ambiguous. To address this, this study compared the hydrothermal alteration and auriferous pyrite geochemistry in lamprophyres, Zhenyuan gold deposit, which were infiltrated by fluids with varied redox states. Vein-A, vein-B, and vein-C were distinguished and they contain different sulfur-bearing minerals, i.e. pyrite, pyrite and barite, and barite, respectively. This suggests the gradual oxidzing formation conditions from vein-A to vein-C. Alteration halos enveloping vein-A and vein-B develop disseminated pyrite. In the vein-A halos, alteration minerals transit from pyrite to Fe‑carbonates outwards, which was well replicated by the thermodynamic simulation of the successive reaction of H2O-CO2-H2S-Au-bearing fluid with lamprophyres. The precipitation of pyrite grains in vein-B halos is farther from vein-B, suggesting progressive fluid-rock interaction (FRI) first induced the reduction of oxidized S followed by the pyrite precipitation. Additionally, δ34S values of pyrite are more scattered in vein-B halos (−8.0 to 4.7‰) than in vein-B, vein-A, and vein-A halos, implying the sulfate-sulfide disequilibrium. Pyrite in vein-B halos displays higher As concentrations than that in vein-A halos due to the strong redox dependence of As partition from fluids to pyrite. Au and Au/As of halo-hosted pyrite grains decrease outwards, and pyrite in vein-B halos has low Au and Au/As (below 93.93 ppm and 0.005, respectively) compared to that in vein-A halos (below 1597.08 ppm and 0.031, respectively). It is thus suggested that Au concentrations in ore fluids decreased during outwards FRI, and the lack of pyrite grains in proximal alteration zones results in lower gold concentration in pyrite under relatively oxidized conditions. This study reveals that the fluid redox conditions can affect As concentrations and spatial distribution of pyrite in alteration halos, which directly controls invisible gold precipitation.
Augmented Reality for AI-driven Inspection? – A Comparative Usability Study

Inspection in Aerospace industry can, as well as many other industrial applications, benefit from using Augmented Reality (AR) due to its ability to superimpose helpful digital information in 3D, leading to fewer errors and decreased mental demand. However, each AR device has advantages and disadvantages, and not all AR devices are suitable for use in industrial settings. We compare a tripod-fitted-adjustable-arm tablet-based AR solution (Apple iPad Pro) to head-mounted AR (Microsoft HoloLens 2) and a traditional, computer screen-based human-machine interface (HMI), all three designed to guide operators based on previously performed AI-based image analysis. Following an iterative design process with three formative evaluations, a final field test in a real industrial shop floor engaging 6 professional inspectors revealed an overall preference for the tripod-fitted iPad variant which receiving the best scores in most dimensions covered in both a usability-focused SUS questionnaire (score 71) and a NASA-RTLX form focused on perceived workload. More specifically, the tripod-fitted iPad was considered more usable (SUS) than the classic computer display HMI (M=5.83, SD=4.92, p=0.034, N=6); the temporal demand (NASA-RTLX) was considered lower using the iPad compared to both HoloLens 2 and the HMI (M=6.67, SD=4.08, p=0.010; M=10.83, SD=9.70, p=0.040, N=6), respectively.
Use case for the Application of the Industrial Metaverse Approach for Engineering Design Review

The metaverse is an immersive virtual space that enables users to meet each other virtually as an avatar and to interact with the virtual environment whatever their location. The metaverse approach is mainly based on the virtual reality (VR) technology enhanced with multiplayer capability. VR enables, due to its high immersive and interactive capabilities, a realistic experience of complex and abstract technical systems which leads to the support of the human cognitive abilities in observing their behavior. The advantages of VR have been recognized by the industry in the last few years. As a result, numerous industrial companies worldwide have founded initiatives with research institutions and start-ups to investigate the application of VR and the metaverse. This paper presents and discusses the implementation and the application of an industrial metaverse approach based on VR for the design review of a pharmaceutical vial filling machine.
Towards Validating a Chatbot Usability Scale

A chatbot usability questionnaire (CUQ) was designed to measure the usability of chatbots. Study objectives: 1) to test the construct validity of CUQ (i.e. does it differentiate between chatbots that we rank as having poor, average or good usability), 2) to assess the intra-rater reliability of CUQ (i.e. do participants provide the same answers/scores when assessing the usability of the same chatbots two weeks apart), and 3) to undertake exploratory factor analysis to study the underlying factors that CUQ measures. Three chatbots were selected by co-authors that were regarded as having good, average and poor usability. Participants used each of the chatbots and completed the CUQ scale for each. Participants repeated this process two weeks later to facilitate the measurement intra-rater variability. Paired t-tests were used to compare CUQ scores from each of the three chatbots. Exploratory factor analysis was used to identify the factors within the CUQ. Paired t-tests and correlation was used to measure intra-rater reliability. There was a total of 156 CUQ survey completions (26 participants completed the CUQ for 3 different chatbots and for 2 rounds: 26 * 3 * 2 = 156). Intra-rater reliability was supported as there was a good correlation between how participants completed the CUQ for the same chatbot at approximately two weeks apart (r > 0.7). As a form of construct validity, the CUQ scores for each of the three chatbots were statistically significant (p < 0.05). Factor analysis shows that the CUQ measures four factors 1) personality, 2) user experience, 3) error handling and 4) onboarding of the chatbot.
Design and Evaluation of Voice User Interfaces: What Should One Consider?

Voice user interfaces (VUI) come in various forms of software or hardware, are controlled by voice, and can help the user in their daily life. Despite VUIs being readily available on smartphones, they have a low adoption rate. This can be attributed to challenges such as the misunderstanding of voice commands as well as privacy and data security concerns. Still, there are intensive VUI users, but they also raise concerns that may be independent of culture. Hence, we will discuss in our paper the various areas that should be considered when developing VUIs to increase user acceptance and foster a positive user experience (UX). We propose exploring the context of use and UX aspects to understand users' needs while using VUIs. All of our suggestions can help VUI developers to design better VUIs.
Designing with the more-than-human: Temporalities of thinking with care

This one-day workshop brings together HCI researchers, designers, and practitioners to engage with more-than-human temporalities in the context of designing with care. We invite participants to experiment and think with more-than-human time experiences as a starting point to integrate emergent methodologies and practices for more-than-human discourses in design. By using living and once-living media (e.g., fungi, plant and insect specimens, biodesigned artefacts) as starting points for investigating more-than-human temporalities, participants will discuss how a pluralistic temporal approach can offer to the discourse of designing-with nonhuman entities, and how this aligns with emerging HCI research trajectories and concerns.
Generating multi-level explanations for process outcome predictions

Process mining focuses on the analysis of event log data to build various process analytical capabilities. Predictive process analytics has emerged as one of such key capabilities and it uses machine learning techniques to construct process prediction models. In recent years, deep neural networks have gained increasing interest in process prediction since they can handle multi-dimensional sequential inputs with minimal information loss. However, they are considered black-box models and existing studies in explaining deep neural network-based process predictions rely on only event-level features for explanation. In this paper, we propose a new approach for generating explanations for process outcome predictions at multiple levels. The approach is underpinned by three different prediction models: a transparent model for generating global explanations based on case-level features, an attention-based deep neural network for generating local explanations based on event-level features, and a novel eXplainable Dual-learning Deep network (XD2-net) for generating local explanations based on case-level features. Using three publicly available datasets, we have tested the applicability of the approach and further examined the multi-level explanations generated by the approach through an elaborate case study. Unlike others, the design of our approach promotes the idea of leveraging the complementary capabilities of different models and utilizing their strengths, rather than focusing on model performance competition. This will contribute towards generating more comprehensive explanations that meet the needs of different end users and purposes in the future.
Designing with Biosignals: Challenges, Opportunities, and Future Directions for Integrating Physiological Signals in Human-Computer Interaction

Biosensing technologies are a rapidly increasing presence in our daily lives. These sensor-based technologies measure physiological processes including heart rate, breathing, skin conductance, brain activity and more. Researchers are exploring biosensing from perspectives including: engineering, human-computer interaction, medicine, mental health, consumer products, and interactive art. These technologies can enhance our interactions allowing connection to our bodies and others around us across diverse application areas. However, designing with biosignals in Human-Computer Interaction presents new challenges pertaining to User Experience, Input/Output, interpretation of signals, representation, and ethics. There is an urgent need to build a scholarly community that includes the diverse perspectives of researchers, designers, industry practitioners and policymakers. The goal of this workshop is to leverage the knowledge of this community aiming to map out the research landscape of emerging challenges and opportunities, and to build a research agenda for future directions.
Virtual reality platforms to support decision-making in multilevel educational systems

The authors endeavor to develop an approach toward designing academic digital shadows and twins for efficient management of educational processes in training professionals in the real-time mode, as well as for strategic and immediate decisions. They suggest a model for direct management of multilevel educational processes and development of individual educational trajectories (IET) through using digital twins (DT) within the educational process in the years 3–4, master’s programs, and within the framework of continuing professional education. The general concept of DT application in educational organization is developed, i. e. student-oriented model with IET as a core. The authors also examine IET as an instrument of mobile and rapid re-engineering of educational processes scaled t o t he a ctual n eeds o f t he e conomy a nd e mployers’ c urrent d emands; as well as general approaches to IET support, in particular, through online educational technologies and virtual educational platforms and resources. The virtual reality platforms may be used in distance learning when developing IET in multilevel educational systems. The authors compare several virtual reality platforms, metauniverses, their tools and applications in educational processes.
On derivative-free extended Kalman filtering and its Matlab-oriented square-root implementations for state estimation in continuous-discrete nonlinear stochastic systems

Recent research in nonlinear filtering and signal processing has suggested an efficient derivative-free Extended Kalman filter (EKF) designed for discrete-time stochastic systems. Such approach, however, has failed to address the estimation problem for continuous-discrete models. In this paper, we develop a novel continuous-discrete derivative-free EKF methodology by deriving the related moment differential equations (MDEs) and sample point differential equations (SPDEs). Additionally, we derive their Cholesky-based square-root MDEs and SPDEs and obtain several numerically stable derivative-free EKF methods. Finally, we propose the MATLAB-oriented implementations for all continuous-discrete derivative-free EKF algorithms derived. They are easy to implement because of the built-in fashion of the MATLAB numerical integrators utilized for solving either the MDEs or SPDEs in use, which are the ordinary differential equations (ODEs). More importantly, these are accurate derivative-free EKF implementations because any built-in MATLAB ODE solver includes the discretization error control that bounds the discretization error arisen and makes the implementation methods accurate. Besides, this is done in automatic way and no extra coding is required from users. The new filters are particularly effective for working with stochastic systems with highly nonlinear and/or nondifferentiable drift and observation functions, i.e. when the calculation of Jacobian matrices are either problematical or questionable. The performance of the novel filtering methods is demonstrated on several numerical tests.
Situating computational empowerment in formal education: A multi-perspective view

Digital literacy and respective education are of growing interest in our increasingly digitalized world. Recent works stress the importance of aiming beyond the acquisition of corresponding technical competences and call for fostering children’s empowerment and participation in digitalization. Computational Empowerment (CE) pursues that goal through a creative and reflexive participatory design approach. However, remaining conceptual vagueness with regard to what CE entails may hinder its implementation in formal education. This paper addresses this gap, with the aim to demonstrate what is needed to advance CE’s position in this context. To this end, we elaborate on our understanding of CE’s vision, approach and impact. We then examine CE in the context of formal education, and contrast it with selected contemporary educational theory and practice. Specifically, we position CE in relation to an established learning framework (Bloom’s revised taxonomy), educational policy (DigComp) and practices in the classroom. This is complemented by an analysis of four different projects: we present lessons learned in the context of pedagogical interventions and take a closer look at the accompanying empowerment processes. As a result, this paper provides a foundation to make CE’s ideas more tangible and, thus, actionable, for researchers, policy makers and educators.
Smooth representation learning from multi-view data

Multi-view subspace clustering has aroused more and more attention due to its ability to explore data correlation from multiple views without stressful label annotations. Although a plethora of methods have been developed, they are powerless considering the original data may not be separable into subspaces. In this paper, we target to achieve a smooth representation from multi-view data which is committed to facilitating the downstream clustering task. Our assumption is that samples in the same cluster always tend to be densely connected. In detail, the proposed method can maintain the graph geometric structure by performing graph filtering to obtain the smooth representation. Furthermore, we unify the smooth representation learning and the subsequent multi-view clustering in a joint framework, hence the “multi-view clustering-friendly” representation can be expected. As a result, the smooth representation learning of each view and the achieving of multi-view clustering can be boosted in a mutual reinforcement manner towards an overall optimal solution. Extensive experiments on common multi-view datasets are conducted to demonstrate the effectiveness of our mode, compared to other SOTAs over the clustering performance.
A pre-correction method for oblique projection of grating fringes in a phase measuring profilometry system

In a phase measuring profilometry system, while the camera optical axis is perpendicular to the reference plane and the projector is installed obliquely, the sinusoidal characteristic of the grating fringes is lost (i.e., non-uniform pitch and amplitude), thus affecting the measurement accuracy. In this paper, a universal correction method for grating fringes is proposed, in the case where the projector optical axis is not perpendicular to the reference plane. This method includes pose correction (i.e., uniform pitch) and light intensity correction (i.e., uniform amplitude) of grating fringes. The pose transformation model, which is used to convert the pixel coordinates from the projector coordinates system into the camera coordinates system, is established by projecting a single image. Next, the digital grating fringes pattern with pre-corrected pose can be obtained, according to the established pose transformation model and the projector resolution. Regarding the light intensity correction, after capturing a projected blank pattern with pre-corrected pose, the light intensity correction coefficients on the reference plane are quantified by iteration method, and they can be used to correct the light intensity of grating fringes. The experimental results show that the presented method can effectively realize the sinusoidal correction of grating fringes.
Design Ideation with AI - Sketching, Thinking and Talking with Generative Machine Learning Models

Generative machine learning models provide opportunities to support design work in various parts of the design process. This study investigates how generative machine learning and large language models may play a part in creative design processes of ideation, early prototyping and sketching. A workshop was conducted in which design practitioners and design researchers developed design concepts for a provided design case, with the help of GPT-3. The findings point to three main themes, including i) the practical usefulness and limitations of the system in design ideation processes, ii) how the form of user interaction shapes users' expectations of the system's capabilities and potentials, and iii), how the broader discourse around AI both limits and enables how co-creative processes involving human and AI unfolds. The discussion outlines design implications and alternative framings of this kind of co-creative design practices based on post-human perspectives on design and technology use.
Being, Having, Doing, and Interacting: A Personal Informatics Approach to Understanding Human Need Satisfaction in Everyday Life

A grand challenge for computing is to better understand fundamental human needs and their satisfaction. In this work, we design a personal informatics technology probe that scaffolds reflection on how time-use satisfies Max-Neef’s fundamental needs of being, having, doing, and interacting via self-aspects, relationships and organizations, activities, and environments. Through a combination of a think-aloud study (N = 10) and a week-long in situ deployment (N = 7), participants used the probe to complete self- aspect elicitation and Day Reconstruction Method tasks. Participants then interacted with network visualizations of their daily lives, and discovered insights about their lives. During the study, we collected a dataset of 662 activities annotated with need satisfaction ratings. Despite challenges in operationalizing a theory of need through direct elicitation from individuals, personal informatics systems show potential as a participatory and individually meaningful approach for understanding need satisfaction in everyday life.
Physica: Interactive Tangible Physics Simulation based on Tabletop Mobile Robots Towards Explorable Physics Education

In this paper, we introduce Physica, a tangible physics simulation system and approach based on tabletop mobile robots. In Physica, each tabletop robot can physically represent distinct simulated objects that are controlled through an underlying physics simulation, such as gravitational force, molecular movement, and spring force. It aims to bring the benefits of tangible and haptic interaction into explorable physics learning, which was traditionally only available on screen-based interfaces. The system utilizes off-the-shelf mobile robots (Sony Toio) and an open-source physics simulation tool (Teilchen). Built on top of them, we implement the interaction software pipeline that consists of 1) an event detector to reflect tangible interaction by users, and 2) target speed control to minimize the gap between the robot motion and simulated moving objects. To present the potential for physics education, we demonstrate various application scenarios that illustrate different forms of learning using Physica. In our user study, we investigate the effect and the potential of our approach through a perception study and interviews with physics educators.
Recapturing Product as Material Supply: Hoverboards as Garbatrage

The volatility of modern economics, and marketing paired with highly extended and globalized supply chains produces goods with explicit market inefficiencies. This pictorial explores a design process, "Garbatrage," wherein designers exploit the difference in value between parts in waste product and those used in new products. Drawing upon our own material re-use of hoverboards, we inductively outline a framework to help designers consider the micro- and macro-economic context of material recapture of waste components, necessary to make for more circular economies and sustainable supply chains at scale. We then apply this framework to identify other potential targets for Garbatrage. We conclude with opportunities for design to make the practice of Garbatrage more widely adoptable.