Reviewerly/exHarmony huggingface dataset:
Conversation N: Visualization Installation Design Based on Voice Interaction

Deep learning allows machines to have human-like learning and thinking capabilities, but its internals are often considered a black box about which we know very little. As AI (Artificial intelligence) penetrates deeper into life, the development of AI is maybe uncontrollable under the influence of human data. Questions about privacy, autonomy, fairness, and the potential for misuse of technology will become even more pressing. In the unstoppable process of technological development, art and design can often reveal science’s mysteries and even predict technology’s development. In this paper, through the research of algorithmic bias and AI ethics, we design an interactive installation with audience participation. Based on voice dialogue technology, the Installation uses visualization based on two-dimensional screens and physical Installation to demonstrate how AI constantly changes and generates a certain form in the learning process, hoping to trigger thinking about the subjectivity between humans and artificial intelligence. It summarizes what AI believes audiences think about AI on some issues.
WhatsApp and the Platformization in Brazil: a dense description of agents articulated in control practices mediated by the platform

Abstract This article aims to describe the structured control system based on the use of WhatsApp in Brazil, locating the relationships between influence strategies of the public debate carried out by national agents and the data market and algorithmic modulation strategies of Meta Plataforms Inc., a company of technology that owns the platform. Starting from the concept of platformization and an analytical approach influenced by the Actor-Network Theory, WhatsApp is positioned in the analysis as a non-human sociotechnical member of a relationships network that involves economic and political objectives of human actors, leveling both in importance and understanding that the insertion of the platform profoundly changes the practices and forms of social organization in the country. The goal is to understand the conjectural conditions that make WhatsApp an important element in the lives of Brazilian people and what is Meta’s market model role for the control techniques that emerge with this use.
Video Analytics in Business Marketing for Shopping Malls in Ecuador

Introduction: Video analytics has become an important tool for improving business performance, personnel management, and security in different environments, including shopping centres. However, its use also poses a threat to users’ privacy. Aim: In this context the aim of the article is to determine the architecture of video analytics in shopping malls as a business marketing strategy and the vulnerability of users’ privacy. Method: A descriptive methodology with a qualitative approach was used to design a prototype focused on the optimisation of customer business processes and decision making in shopping centres in Ecuador, from problem identification and information requirements management to prototype design, implementation, and training of the model with accurate data. Results: The technological solution is based on the OMIA platform, which generates relevant Key Performance Index (KPI) based on the automatic processing of images from video surveillance systems. Conclusion: It is important that the implementation of the model is trained, supervised, optimised, and regulated to guarantee the privacy and security of information and users under the Organic Law on Data Protection in Ecuador.
Comparing Samsung and Apple Top-End Mobile Cameras by Using NR-IQA Metrics

In this work, we compare the picture quality provided by two popular smartphone brands: Samsung and Apple. We use the top-end model of both brands in 2022: Galaxy S22 Ultra for Samsung and iPhone 13 Pro for Apple, and we built a dataset consisting of seven different environments. For each of these environments, we captured pictures with both devices under the same conditions in two camera categories: first, using the device’s native camera and then using the camera provided by the Instagram App. Since these pictures are in a compressed form, and therefore there is no reference image to compare them to, we use “No-Reference Image Quality Assessment” (NR-IQA) metrics to provide values to measure the quality of its pictures. Experimental results with some of the most used NR-IQA metrics show that Samsung device has best images for most of the environments when using the device’s native camera, but Apple provides best results for the Instagram App.
Features of Persuasive AI in the Workplace

Artificial Intelligence (AI) technologies can act as persuaders when implemented in workplace tools and infrastructure. How users process and react to interacting with features of such AI technologies in the workplace remains ill-understood. Literature in human-AI interaction suggests that cues in the user interface can dictate how users process information communicated by an AI and how receptive they are to being persuaded to change or reinforce their behaviors. Literature from human-AI interaction and an existing systematic framework of the study and design of persuasive technology from human-computer interaction can be applied to examining how users interact with persuasive AI in workplace tools and infrastructure. This paper aims to illustrate the application of such a systematic framework for persuasive technology to the study of persuasive AI technologies in the workplace context. Adapted from the persuasive technology framework, an illustrative vignette of a widely used workplace AI-powered tool is offered to further demonstrate features and principles of systems that include a persuasive AI component.
Developing a VR Application for an Omnidirectional Treadmill

Users of virtual reality (VR) applications often must travel between locations in virtual spaces. An omnidirectional treadmill is a device that allows users to walk in all directions in a virtual space without physically moving the position of their body in the real world. The obvious advantage of an omnidirectional treadmill is that users can walk large distances in VR without concern they will collide with objects in their real physical space. Much research investigating the use of omnidirectional treadmills in VR has focused on comparing treadmills to other forms of navigation, and exploring various aspects of the user experience, such as symptoms of cybersickness. This paper describes our work in progress to develop and evaluate a VR application for the Infinadeck omnidirectional treadmill. Our goals are to create a VR application highlighting the benefits of the treadmill, develop the application in stages so that many students at our University can contribute, and increase understanding of how to develop pleasurable omnidirectional treadmill experiences.
A Signature Information Generation Method for Judging the Illegality of Cloud-Based Webtoons

Recently, platforms that service digital contents such as movies, dramas, and webtoons are switching from downloading methods to streaming methods, and illegal content servicing methods are also changing from downloading to streaming. These streaming-based copyright infringement crimes avoid the blocking and investigation by law enforcement agencies through methods such as using overseas servers or disguising the IP of operating servers using cloud services, etc., which requires an appropriate measures to respond to them. In this paper, we propose a signature information generation method through which the illegality of distributed digital contents can be quickly checked. Using this method, there is an advantage in quickly finding illegally distributed digital contents based on a cloud server, which can prompt to block illegal distribution sites.
HIØF Easy Navigator: An Augmented Reality App Which Guides a User to Reach Their Destination

New students often have trouble finding classrooms, laboratories, libraries, or other places inside a new study place. At Østfold University College (HIØF), they provide paper maps to the students to find locations inside the university which are difficult to understand and hard to use. To solve this problem, we have developed an app named “HIØF Easy Navigator”. The application guides new students to find the inside location here at HIØF, Norway. We also conducted a survey of eight students to check the user experience and opinions of paper maps and the HIØF Easy Navigator. Our findings demonstrate that the app is easier to use than paper maps to locate locations inside the university.
Toward HCXAI, Beyond XAI: Along with the Case of Referring Expression Comprehension Under the Personal Context

The goal of eXplainable AI (XAI) is to increase the transparency and trustworthiness of AI algorithms to humans by clarifying their internal decision-making process. As AI technology continues to permeate various aspects of our daily lives, including the workplace, the importance of XAI has grown and some XAI methodologies have increased our understanding of AI algorithm’s inner logic. However, the achievement of explainability of AI models did not make them user-centered in real life and users still need to be aware of the internal mechanism of AI models to interact with them effectively. In this regard, the paper argues there is a need to move beyond XAI towards Human-Centered eXplainable AI (HCXAI) to ensure human-centered usage in our daily lives. As the steps heading for HCXAI, the paper suggests researching intuitive human behaviors first and then training AI models to comprehend these natural human behaviors. When users interact with AI models trained in this way, they will not need to think consciously about the model’s working mechanism anymore. The paper elaborates on this approach further with a practical case that can be encountered in our daily lives; the vision and language model for referring expression comprehension under the personal context.
Media richness effectiveness: Humanoid robots with or without voice, or just a tablet kiosk?

Abstract Humanoid robots can serve as in‐store communication medium, providing functional as well as hedonic value. Previous studies have demonstrated their proficiency in providing functional value, such as guiding customers, advertising products, or carrying groceries. However, in a retailing context, engaging customers often requires more than meeting their basic functional needs. This study is the first to examine the potential of humanoid service robots (HSRs) in providing hedonic value as well, comparing their performance to that of more traditional in‐store media in entertaining customers. Based on media richness effectiveness theory , the role of robot voice is also investigated. An experimental field study was performed administering a fun quiz to passers‐by at an airport store considering three conditions (via tablet, robot with voice, or robot without voice). The results show that the quiz via a humanoid robot (as compared to via a tablet kiosk) provides customers more functional and hedonic value. While functional value favorably affects loyalty intentions mainly via enhanced store image, hedonic value has a direct and indirect effect mainly via store attitude. Adding voice to the HSR does not seem to provide significant added value. Data on actual purchase behavior also hint at superiority of the robot over a traditional tablet kiosk.
Describing Conditional Independence Statements Using Undirected Graphs

This paper investigates the capability of undirected graphs (UGs) to represent a set of Conditional Independence (CI) statements derived from a given probability distribution of a random vector. While it is established that certain axioms can govern this set, providing sufficient conditions for UGs to capture specific CI statements, our focus is on covariance and concentration graphs. These remain the only known families of UGs capable of describing CI statements. We explore the issue of complete representation of CI statements through their corresponding covariance and concentration graphs. Two parameters are defined, one each from the covariance and concentration graphs, to determine the limitations concerning the cardinality of the conditioning subset that the graph can represent. We establish a relationship between these parameters and the cardinality of the separators in each graph, providing a straightforward computational method to evaluate them. In conclusion, we enhance the aforementioned procedure and introduce criteria to ascertain, without additional computations, whether the graphs can fully represent a given set of CI statements. We demonstrate that either the concentration or the covariance graph forms a cycle, and when considered in conjunction, they can represent the entire relation. These criteria also enable us, in specific cases, to deduce the covariance graph from the concentration graph and vice versa.
A multimodal analysis of (de)legitimation through argumentation in extremist discourse: The case of <i>Dabiq</i>

Abstract Even after the demise of its territorial caliphate in 2019, ISIS persists as a potent threat, adapting to new technologies and maintaining its status as an active insurgency. Amidst the backdrop of the terror group’s demonstrated resilience, this paper examines its practice of (de)legitimation and language of persuasion through a multimodal argumentation analysis. It combines the argumentation strategies ( topoi ) proposed by Discourse-Historical Approach (DHA) and tools from Social Semiotics with argumentation theories, achieved through a comprehensive enthymematic deconstruction of arguments in ISIS’s e-magazine, Dabiq . The findings reveal four interrelated sets of plausibly inferable premises, namely, advantage and disadvantage; threat and obligation; negative consequence and history; and authority and Shariah law. These premises fall within broad social, political, historical, and religious categories and are deliberately crafted to lend support to ISIS’s desired conclusions, aimed at systematically altering the addressees’ state of knowledge and eventually eliciting acceptance from the intended public.
Sign Language Gesture Vocalizer

There are about 70 million silent people in the world. There are kids that have autism that is not verbal. It is extremely difficult for people with speech impairments and normal people to communicate. Thus, the system is developing a glove-based gadget that will translate sign language (ASL) to speech. Not everyone is able to comprehend sign language. These sensors record the user's movements in real time. These sensors provide data, which is gathered by an Arduino Nano microcontroller and transmitted over Bluetooth to a PC. With the help of this prototype, silent people can now speak and learn multiple languages
The Development Status, Technical Characteristics, and Competitive Dynamics of Blockchain-critical Technologies in China and the USA: From a Patent Perspective

As an emerging technology, blockchain has attracted significant attention from countries worldwide. Based on patent measurement analysis methods, this paper conducts an in-depth study of invention patents related to crucial blockchain technologies in China and the United States from 2016 to 2022. The study found that the overall trend of the number of patents first increases and then declines, and the layout of the USA in this field is earlier than that of China, but the total number of patents in China exceeds that of the USA; the number of Chinese invention patents located in the core area of the international patent classification (IPC) large group exceeds that of the USA, and there are differences in the types of active technologies between China and the USA; the technology life cycle of China and the USA in this field as a whole has entered the declining period, but segmented technology areas such as privacy protection and cross-chain technology are still in the growth period.
YOUNG UNIVERSITIES OF RUSSIA: CREATION AND FORMATION, THE ROLE OF THE STAFF AND INDIVIDUAL IN THE FORMATION OF THE BEST UNIVERSITY TRADITIONS AND PRACTICES

The article highlights the issues of creation and development of young universities. Important historical aspects of the formation and development of higher education are noted, both in European countries and in Russia. The classification of university development factors is presented and considered. Two groups of factors are singled out: purely external (political, material, financial) and factors, the sources of resources for the formation of which are both external and internal capabilities of universities (socio-cultural, intellectual factors). The products produced by universities are defined: individual intellectual capital and socially significant social capital, scientific knowledge, culture. It has been established that culture is created and transmitted to university students by their faculty and leaves the university together with graduates, creating a reputation for the university in the external environment. At the same time, leaving the university, culture, at the same time, remains at the university. In this case, it performs the function of a factor in its development.
A meta-learning network method for few-shot multi-class classification problems with numerical data

Abstract The support vector machine (SVM) method is an important basis of the current popular multi-class classification (MCC) methods and requires a sufficient number of samples. In the case of a limited number of samples, the problem of over-learning easily occurs, resulting in unsatisfactory classification. Therefore, this work investigates an MCC method that requires only a small number of samples. During model construction, raw data are converted into two-dimensional form via preprocessing. Via feature extraction, the learning network is measured and the loss function minimization principle is considered to better solve the problem of learning based on a small sample. Finally, three examples are provided to illustrate the feasibility and effectiveness of the proposed method.
Potential determinants of research output: comparing economics and business

This article uses cross-country unbalanced panel data of up to 146 countries from 1996–2015 to be the first study to identify potential determinants of a country’s relative research output in Economics versus Business. This identification is important for students, professionals, universities, university departments, and research-funding agencies facing choices between profiles oriented towards economics and business. Consider the following concrete example. The finding that some distinct countries’ characteristics hinder Economics relative to Business research is valuable information for a prospective professional when choosing her career path. We do a thorough literature review to single out country characteristics having the potential to determine the flourishing of economics research vis-à-vis business research and come out with the following three hypotheses: higher policy-related data availability, higher income inequality, and lower ethnic fractionalization relatively favour economics. The regressions’ results confirm these hypotheses, and the findings are robust to two alternative fixed effects specifications, three alternative definitions of economics and business, two alternative measures of research output (publications and citations), the inclusion of meaningful control variables, and the consideration of developed and developing countries. Yet, the association between ethnic fractionalization and relative research output is limited to developing countries.
Effective task scheduling based on interactive autodidactic school algorithm for cloud computing

The topic of load balanced task scheduling has emerged as a prominent and intricate area of study within the realm of Cloud computing. Swarm intelligence-based meta-heuristic algorithms are commonly considered more suitable for the purposes of Cloud scheduling and load balancing. These algorithms employ a combination of local and global search strategies in order to ascertain the ideal location. To achieve an optimal mapping strategy for task allocation to resources, it is imperative to find a suitable equilibrium between local and global search techniques, since this approach has demonstrated significant efficacy. This research introduces a new approach to task scheduling using the Autodidactic Interactive School Optimization Algorithm (IASOA). The objective of this method is to decrease the time required for job execution while also enhancing throughput. The assessment of the suggested methodology has been executed, and a comparative analysis has been performed with five established algorithms in relation to makespan and throughput. The tests were subsequently extended to encompass a comparative analysis of the suggested methodology alongside four other established meta-heuristic scheduling methodologies. The study of the simulated experimentation reveals that the proposed approach yielded noteworthy advantages in makespan and throughput, with improvements of up to 10% and 60% respectively.
STUDY OF THE QUALITY OF MEMORY OF MUSICAL WORKS’ NOTE TEXT BY STUDENTS OF FACULTIES OF ARTS IN THE PROCESS OF INSTRUMENTAL TRAINING

The article substantiates the criteria for the quality of memorizing the notational text of musical works by students of arts faculties during instrumental training, among which is the perfection of the reproduction of pitch signs of musical works’ notational text in the course of classroom/home work on it; the degree of reproduction of the metro-rhythmic features of the sheet music of musical works in the process of classroom/home work on it and the degree of achievement of error-free reproduction of the musical works’ sheet music by students of arts faculties in the process of their integral performance in conditions of public performances. The expediency of setting indicators according to these criteria when perceiving the sheet music text of musical works during their first reading, when performing it by heart the day before and during the final form of reporting (credit or exam) is emphasized. Technologies for diagnosing the quality of memorizing the sheet music of musical works have been developed and the levels of the studied phenomenon have been delineated (high level, medium level, low level and very low level). It was experimentally proven that the general level of quality of memorization of sheet music texts by students of arts faculty is unsatisfactory, which requires the development of effective methods for targeted improvement of the studied phenomenon.Key words: memorization of the sheet music text of musical works, students of arts faculties, instrumental training, criteria, indicators, ascertainment experiment.
Adaptive feature extraction method for capsule endoscopy images

The traditional feature-extraction method of oriented FAST and rotated BRIEF (ORB) detects image features based on a fixed threshold; however, ORB descriptors do not distinguish features well in capsule endoscopy images. Therefore, a new feature detector that uses a new method for setting thresholds, called the adaptive threshold FAST and FREAK in capsule endoscopy images (AFFCEI), is proposed. This method, first constructs an image pyramid and then calculates the thresholds of pixels based on the gray value contrast of all pixels in the local neighborhood of the image, to achieve adaptive image feature extraction in each layer of the pyramid. Subsequently, the features are expressed by the FREAK descriptor, which can enhance the discrimination of the features extracted from the stomach image. Finally, a refined matching is obtained by applying the grid-based motion statistics algorithm to the result of Hamming distance, whereby mismatches are rejected using the RANSAC algorithm. Compared with the ASIFT method, which previously had the best performance, the average running time of AFFCEI was 4/5 that of ASIFT, and the average matching score improved by 5% when tracking features in a moving capsule endoscope.