Reviewerly/exHarmony huggingface dataset:
Power transformations of relative count data as a shrinkage problem

Here we show an application of our recently proposed information-geometric approach to compositional data analysis (CoDA). This application regards relative count data, which are, e.g., obtained from sequencing experiments. First we review in some detail a variety of necessary concepts ranging from basic count distributions and their information-geometric description over the link between Bayesian statistics and shrinkage to the use of power transformations in CoDA. We then show that powering, i.e., the equivalent to scalar multiplication on the simplex, can be understood as a shrinkage problem on the tangent space of the simplex. In information-geometric terms, traditional shrinkage corresponds to an optimization along a mixture (or m-) geodesic, while powering (or, as we call it, exponential shrinkage) can be optimized along an exponential (or e-) geodesic. While the m-geodesic corresponds to the posterior mean of the multinomial counts using a conjugate prior, the e-geodesic corresponds to an alternative parametrization of the posterior where prior and data contributions are weighted by geometric rather than arithmetic means. To optimize the exponential shrinkage parameter, we use mean-squared error as a cost function on the tangent space. This is just the expected squared Aitchison distance from the true parameter. We derive an analytic solution for its minimum based on the delta method and test it via simulations. We also discuss exponential shrinkage as an alternative to zero imputation for dimension reduction and data normalization.
GUESR: A Global Unsupervised Data-Enhancement with Bucket-Cluster Sampling for Sequential Recommendation

Sequential Recommendation is a widely studied paradigm for learning users' dynamic interests from historical interactions for predicting the next potential item. Although lots of research work has achieved remarkable progress, they are still plagued by the common issues: data sparsity of limited supervised signals and data noise of accidentally clicking. To this end, several works have attempted to address these issues, which ignored the complex association of items across several sequences. Along this line, with the aim of learning representative item embedding to alleviate this dilemma, we propose GUESR, from the view of graph contrastive learning. Specifically, we first construct the Global Item Relationship Graph (GIRG) from all interaction sequences and present the Bucket-Cluster Sampling (BCS) method to conduct the sub-graphs. Then, graph contrastive learning on this reduced graph is developed to enhance item representations with complex associations from the global view. We subsequently extend the CapsNet module with the elaborately introduced target-attention mechanism to derive users' dynamic preferences. Extensive experimental results have demonstrated our proposed GUESR could not only achieve significant improvements but also could be regarded as a general enhancement strategy to improve the performance in combination with other sequential recommendation methods.
Persuasive Strategies and Emotional States: Towards Emotion-Adaptive Persuasive Technologies Design

Technologies have been shown to alter how people feel and create outlets for expressing positive and/or negative emotions. This indicates that persuasive systems, which rely on persuasive strategies (PS) to motivate behaviour change, have the potential to elicit emotions in users. However, there is no empirical evidence on whether or not PS evoke emotions and how to tailor PS based on emotional states. Therefore, we conduct a large-scale study of 660 participants to investigate if and how individuals respond emotionally to various PS and why. Our results show that some PS (such as Reward, Reduction, and Rehearsal) evoke positive emotion only, while others (such as Self-monitoring, Reminder, and Suggestion) evoke both positive and negative emotions at varying degrees and for different reasons. Our research links emotion theory with behaviour change models to develop practical guidelines for designing emotion-adaptive persuasive systems that employ appropriate PS to motivate behaviour change while regulating users’ emotion.
Optimization of the multivariate polynomial public key for quantum safe digital signature

Kuang, Perepechaenko, and Barbeau recently proposed a novel quantum-safe digital signature algorithm called Multivariate Polynomial Public Key or MPPK/DS. The key construction originated with two univariate polynomials and one base multivariate polynomial defined over a ring. The variable in the univariate polynomials represents a plain message. All but one variable in the multivariate polynomial refer to noise used to obscure private information. These polynomials are then used to produce two multivariate product polynomials, while excluding the constant term and highest order term with respect to the message variable. The excluded terms are used to create two noise functions. Then four produced polynomials, masked with two randomly chosen even numbers over the ring, form the Public Key. The two univariate polynomials and two randomly chosen numbers, behaving as an encryption key to obscure public polynomials, form the Private Key. The verification equation is derived from multiplying all of the original polynomials together. MPPK/DS uses a special safe prime to prevent private key recovery attacks over the ring, forcing adversaries to solve for private values over a sub-prime field and lift the solutions to the original ring. Lifting entire solutions from the sub-prime field to the ring is designed to be difficult based on security requirements. This paper intends to optimize MPPK/DS to reduce the signature size by a fifth. We added extra two private elements to further increase the complexity of the private key recovery attack. However, we show in our newly identified optimal attack that these extra private elements do not have any effect on the complexity of the private recovery attack due to the intrinsic feature of MPPK/DS. The optimal key-recovery attack reduces to a Modular Diophantine Equation Problem or MDEP with more than one unknown variables for a single equation. MDEP is a well-known NP-complete problem, producing a set with many equally-likely solutions, so the attacker would have to make a decision to choose the correct solution from the entire list. By purposely choosing the field size and the order of the univariate polynomials, we can achieve the desired security level. We also identified a new deterministic attack on the coefficients of two univariate private polynomials using intercepted signatures, which forms a overdetermined set of homogeneous cubic equations. To the best of our knowledge, the solution to such a problem is to brute force search all unknown variables and verify the obtained solutions. With those optimizations, MPPK/DS can offer extra security of 384 bit entropy at 128 bit field with a public key size being 256 bytes and signature size 128 or 256 bytes using SHA256 or SHA512 as the hash function respectively.
Between Development, Growth and Survival: Some Current Features of Iran’s Model of Socio-Economic Development

In recent years, conservative forces in Iran have lambasted their moderate and pragmatic rivals for their inability to solve the country’s economic issues and improve the living standards of its populace. However, since Ebrahim Raisi won the presidential election in 2021, Iranian conservatives have had their own chance to tackle the country’s internal challenges, being the last of the political forces without direct influence on the economic decision-making system for a long time. Nevertheless, their failed attempts to foster economic growth under sanctions pressure may prove critical to the Islamic Republic. Not only the conservative part of the establishment but the entire political system may risk losing what remains of its credibility with the Iranian people, who could perceive it as incapable of eff ectively managing the economy. Furthermore, the government’s success in resolving the current socio-economic development issues is also pivotal to the political future of E. Raisi. His failure would deprive him of any opportunity to claim the post of the next supreme leader of Iran. Meanwhile, the accumulated structural problems of the Iranian economy and the external sanctions pressure can render achieving economic progress a daunting, if not insurmountable, task. This paper seeks to elucidate why there is signifi cant social tension in Iran, resulting in periodic outbursts of protest, and why the economic situation is deemed a crisis, despite the relative resilience of the Iranian economy to external and internal challenges, as well as the macroeconomic performance dynamics, which are not necessarily inferior to those of Iran’s regional neighbors. To answer this question, the paper analyzes the main economic challenges facing the country’s leadership and the extent to which the goals and priorities of the implemented “resistance economy” doctrine provide an adequate response to them. As a theoretical tool, the author employs the ideas of M. Todaro, A. Sen, S. Smith, J. Foster, and C. Handy, justifying the need for any state to transcend the simple parameters of economic growth in formulating its development strategy and think more comprehensively, focusing primarily on creating a social and economic environment that is comfortable for its citizens. As a result, the author concludes that the model of the Iranian economy that has been formed in an aggressive environment prioritizes the survival of the existing political system, approaching the issue of economic growth as secondary and failing to satisfy some popular needs beyond the basic ones. It is incapable of ensuring comprehensive sustainable socio-economic development, which over time leads to the accumulation of internal tension in Iranian society.
GitUI: A Community-Based Platform to Democratize User Interfaces

Customization empowers users to tailor user interfaces to their needs. Although beneficial, its adoption is limited by the required effort, skills, and creativity. Following the success of open software repositories, we present a novel community-based customization system where users can: 1) customize UIs for the self and others – using a customization toolkit; 2) use and further adapt public customization templates – found in an online repository; or 3) request customization assistance. We explored this concept in the context of Web technologies by developing GitUI. GitUI was iteratively developed and evaluated over two deployment phases. In a two-phase study (n=9), experts and non-experts 1) used, for two weeks, the customization toolkit; and 2) explored the repository. Results suggest that community-based customization is feasible. People are motivated to customize for others and enjoy the convenience of public templates. We present challenges and opportunities for future research seeking to democratize customization.
3DMovieMap: an Interactive Route Viewer for Multi-Level Buildings

We present an interactive route viewer system, 3DMovieMap, which generates and shows navigation movies walking through multi-level buildings, such as a science museum, airport, and university building. Movie map systems can provide users with visual cues by synthesizing navigation movies based on their inputs of routes. However, existing systems are limited to flat areas such as city areas. We aim to extend Movie Map to generate navigation movies for multi-level buildings. The 3DMovieMap system generates a movie map from an equirectangular movie via a visual Simultaneous Localization and Mapping technology. Users select waypoints on the floor maps. 3DMovieMap calculates the shortest path that visits these points and generates a navigation movie along the route. We created four movie maps of buildings and asked two participants to use our system and provide feedback for further improvements. We will be releasing an open dataset of equirectangular movies captured in a science museum.
Crownboard: A One-Finger Crown-Based Smartwatch Keyboard for Users with Limited Dexterity

Mobile text entry is difficult for people with motor impairments due to limited access to smartphones and the need for precise target selection on touchscreens. Text entry on smartwatches, on the other hand, has not been well explored for the population. Crownboard enables people with limited dexterity enter text on a smartwatch using its crown. It uses an alphabetical layout divided into eight zones around the bezel. The zones are scanned either automatically or manually by rotating the crown, then selected by pressing the crown. Crownboard decodes zone sequences into words and displays word suggestions. We validated its design in multiple studies. First, a comparison between manual and automated scanning revealed that manual scanning is faster and more accurate. Second, a comparison between clockwise and shortest-path scanning identified the former to be faster and more accurate. In the final study with representative users, only 30% participants could use the default Qwerty. They were 9% and 23% faster with manual and automated Crownboard, respectively. All participants were able to use both variants of Crownboard.
New Insights into User-Defined Smart Ring Gestures with Implications for Gesture Elicitation Studies

We conduct a replication of a previously published gesture elicitation study, which collected and examined user-defined gestures performed with smart rings. Our findings reveal that only 50% of the gestures elicited during our replication match those proposed by the participants of the original study, although our sample of participants had the same characteristics as the sample from the original study, and our participants spent the same amount of time to propose gestures and rated the goodness of their gesture-to-function mappings at the same level as the participants of the original study. Furthermore, the new gestures elicited in our replication present different articulation characteristics in terms of their structure, complexity, symmetry, and locale, compared to the gestures from the original study. Our results have implications for the theory and practice of gesture elicitation studies, for which we provide several recommendations for researchers and practitioners.
A Generative Framework for Designing Interactions to Overcome the Gaps between Humans and Imperfect AIs Instead of Improving the Accuracy of the AIs

My research focuses on improving human-machine collaboration in the context of machine learning, particularly by recognizing the limitations and potential for errors in machine learning techniques and designing effective interactions for filling the gaps between humans and them. To this end, I have explored the application of machine learning in a variety of domains, such as malware analysis, music recommendation, conversation analysis, photo editing, and video-based learning. I also worked on clarifying the limitations of the current technologies by using adversarial approaches and qualitative methods. My thesis is planned to synthesize what I learned from these projects into design principles for constructing interactions that take full advantage of imperfect machine learning models. I particularly put emphasis on deriving principles that do not depend on the fine-tuning of the models, thereby providing a generative framework allowing researchers and practitioners to design a range of effective intelligent interactions without incurring significant computational and data collection costs.
Using plot tasks when teaching Python programming

The article deals with the problem of increasing the internal motivation of schoolchildren when studying programming. The traditional techniques that increase motivation include appealing to the life experience of students, creating a problem situation, solving plot tasks, modeling real events in the educational process (role-playing games). One of the requirements for tasks with applied content is the correspondence of the plot to the age characteristics of students. The fulfillment of this requirement will be possible if the situation described in the plot of the task is socially significant for adolescents, takes into account their interests and current trends in adolescent communication. The article provides examples of plot tasks, the use of which is expedient when teaching programming to basic school students. These tasks allow students to get acquainted with the "list" and "dictionary" data structures, with a pseudo-random number generator, and with creating their own modules in Python.
Effects of Seated Postural Sway on Visually Induced Motion Sickness: A Multiple Regression and RUSBoost Classification Approach

AbstractAbstractThe purpose of this study was to propose a model for estimating individual susceptibility to motion sickness by correlating measures of seated postural sway before exposure to a roller coaster movie displayed in a head-mounted display (HMD) with subjective ratings of visually induced motion sickness (VIMS). The participants were required to watch the content for 15 min, and seated center of pressure (sCOP) was measured using a force platform for 5 min before viewing. We developed a VIMS estimating model from 16 subjects and verified it on 15 subjects. SSQ scores for VIMS were strongly correlated with the area of sCOP, the main-to-minor ratio of the sCOP ellipse, and the total length of sCOP, respectively (r = 0.706, r = 0.555, and r = 0.622). When verifying the estimation model, the observed SSQ scores differed by 32.628 ± 29.749 from the expected SSQ scores, and both score sets were positively correlated (r = 0.622). The classification results between nil and mild, moderate, and severe groups for VIMS showed an accuracy of 0.74 using random under-sampling boost (RUSBoost).Keywords: Visually induced motion sicknesshead-mounted displaypostural swaybalance boardseated center of pressure Disclosure statementNo potential conflict of interest was reported by the author(s).Authors' contributionsSangin Park: conceptualization, investigation, methodology, writing—original draft, visualization, software, and data curation. Sungchul Mun: conceptualization, investigation, analysis, and interpretation of results, writing—review and editing, and supervision.Data availability statementThe data generated and analyzed in this study are available from the corresponding author upon reasonable request.Additional informationFundingThis work was supported by the Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korean government (MSIT) (No. 2022-0-00137, XR User Interaction Evaluation and Employing Its Technology).Notes on contributorsSangin ParkSangin Park received his PhD degree in Emotion Engineering from Sangmyung University in 2016. He is currently a post-doctoral researcher at Hanyang University. His research area includes brain–computer interface, non-contact measurement, neuroscience, artificial intelligence, and emotion engineering.Sungchul MunSungchul Mun received his Ph.D. degree in HCI and Robotics from KIST in 2015. He was a research fellow at Seoul Institute of Technology in 2020. He is currently an assistant professor at Department of Industrial Engineering, Jeonju University. His research area includes machine learning, HCI, and data science.
BREATHTURES: A First Step Towards Breathing Gestures as Distinct Input Modality

The use of breath as interaction modality has sparked some interest recently in HCI. Research in this field actively explored breathing interaction (e.g., guidance and feedback) in different contexts. So far, very little systems can be found that systematically use defined breathing gestures as distinct input modality. In this work, we describe the design, development and implementation of five distinct breathing gestures (BREATHTURES), that can be applied as defined input modality to interact with an application. We present a qualitative user study (n=7) focusing on usability and user experience of the developed BREATHTURES when applied in a game-like application. Results indicate an overall positive rating in terms of fun and usability. Some BREATHTURES were perceived harder to perform and to detect than others. Further iterations of our work will require refined BREATHTURE detection. Overall, our work demonstrates the design, implementation and application of pre-defined breathing gestures as distinct input modality.
Squeez’In: Private Authentication on Smartphones based on Squeezing Gestures

In this paper, we proposed Squeez'In, a technique on smartphones that enabled private authentication by holding and squeezing the phone with a unique pattern. We first explored the design space of practical squeezing gestures for authentication by analyzing the participants' self-designed gestures and squeezing behavior. Results showed that varying-length gestures with two levels of touch pressure and duration were the most natural and unambiguous. We then implemented Squeez'In on an off-the-shelf capacitive sensing smartphone, and employed an SVM-GBDT model for recognizing gestures and user-specific behavioral patterns, achieving 99.3% accuracy and 0.93 F1-score when tested on 21 users. A following 14-day study validated the memorability and long-term stability of Squeez'In. During usability evaluation, compared with gesture and pin code, Squeez'In achieved significantly faster authentication speed and higher user preference in terms of privacy and security.
Accidentally Evil: On Questionable Values in Smart Home Co-Design

An ongoing mystery of HCI is how do well-intentioned designers consistently enable products with unintentionally evil consequences. Using “questionable values” as a lens, we retell and analyze four design scenarios for smart homes that were created by participants with an IoT toolkit we designed. The selected design scenarios reveal practices that violate principles of responsible smart home design. Through our analysis we show (1) how participants explore sensor-driven objectification of the home then leverage data for surveillance, nudging, and control over others; (2) how the dominant technosolutionist narratives of efficiency and productivity ground such questionable values; (3) and how the materiality of mass-produced sensors pre-mediates questionable design scenarios. We discuss how to attend to and utilize questionable values in design: Making space for questionable values will empower design researchers to better “look around corners”, anticipating tomorrow's concerns and forestalling the worst of their harms.
A Human-Computer Collaborative Editing Tool for Conceptual Diagrams

Editing (e.g., editing conceptual diagrams) is a typical office task that requires numerous tedious GUI operations, resulting in poor interaction efficiency and user experience, especially on mobile devices. In this paper, we present a new type of human-computer collaborative editing tool (CET) that enables accurate and efficient editing with little interaction effort. CET divides the task into two parts, and the human and the computer focus on their respective specialties: the human describes high-level editing goals with multimodal commands, while the computer calculates, recommends, and performs detailed operations. We conducted a formative study (N = 16) to determine the concrete task division and implemented the tool on Android devices for the specific tasks of editing concept diagrams. The user study (N = 24 + 20) showed that it increased diagram editing speed by 32.75% compared with existing state-of-the-art commercial tools and led to better editing results and user experience.