Designing an Algorithm for Students Impact on Social Adaptive Behavior in Political Education Context

This study aimed to discuss the social adjustment behaviors of university students. The social adjustment behaviors of university students not only relate to their healthy development but also significantly affect social development., the ideological and political education model combines with the impact on social adaptation behaviors of university students. It optimizes the article algorithm design and creates a theoretical model in the field of social adaptation of university students. The articles limitation is that it was made with a sample of 966 subjects. The methodology involved statistical analysis of students social adaptation status, understanding the average and standard deviation of each dimension and the basic situation of their social adaptation. The average social adjustment index of university students was found to be m=3.68. Changes were observed in the interpersonal relationships of university students in all dimensions of adaptation to the future, learning adaptation, psychological adaptation, and environmental adaptation before and after graduation. In conclusion, this article depends on the analysis of the current state of students adaptation to society, the main personal and environmental factors in the life of university students, and based on the results of analysis and research, provides recommendations for relevant improvements

Tensor-based Intrinsic Subspace Representation Learning for Multi-view Clustering

As a hot research topic, many multi-view clustering approaches are proposed over the past few years. Nevertheless, most existing algorithms merely take the consensus information among different views into consideration for clustering. Actually, it may hinder the multi-view clustering performance in real-life applications, since different views usually contain diverse statistic properties. To address this problem, we propose a novel Tensor-based Intrinsic Subspace Representation Learning (TISRL) for multi-view clustering in this paper. Concretely, the rank preserving decomposition is proposed firstly to effectively deal with the diverse statistic information contained in different views. Then, to achieve the intrinsic subspace representation, the tensor-singular value decomposition based low-rank tensor constraint is also utilized in our method. It can be seen that specific information contained in different views is fully investigated by the rank preserving decomposition, and the high-order correlations of multi-view data are also mined by the low-rank tensor constraint. The objective function can be optimized by an augmented Lagrangian multiplier based alternating direction minimization algorithm. Experimental results on nine common used real-world multi-view datasets illustrate the superiority of TISRL

Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020

On behalf of the Program Committee, a very warm welcome to the Seventh Italian Conference on Computational Linguistics (CLiC-it 2020). This edition of the conference is held in Bologna and organised by the University of Bologna. The CLiC-it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after six years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Steadfast in versatility : the substrate of a multi-modal practice

The research is about inventing ways to produce spaces of inspiration that catalyse curiosity and generous, resilient creativity which goes beyond the local, national or regional borders, enhancing public space, while operating in the transforming context of Estonia. The work evidences certain ‘joyful’ approaches to publicness in design activity, in which the search for functional realities not only incorporates but immerses itself in and builds upon other disciplines as well as on institutional, ideological and structural processes. When practice’s activities propagate through a multiplicity of expressions (simultaneous drawing, model-making, installations, construction supervision, texts, and so on), the set of ‘devices’ with, upon and within which the designer operates could be called the practice’s substratum (substrate). The research poses a question that to evolve a practice, is it necessary to transform its structure, purpose or agenda, or is it a question of how to renew its substrate? A closer look at an existing practice reveals how a practice’s substratum might shift in response to a contextual change. A multi-modal versatile practice bears within it the capacity to facilitate (positive) or to resist (negative) societal change. The research points to the potential for some specific open-ended ‘protocols’ to emerge from the observations offered

Augmented analyses: supporting the study of ubiquitous computing systems

Ubiquitous computing is becoming an increasingly prevalent part of our everyday lives. The reliance of society upon such devices as mobile phones, coupled with the increasing complexity of those devices is an example of how our everyday human-human interaction is affected by this phenomenon. Social scientists studying human-human interaction must now take into account the effects of these technologies not just on the interaction itself, but also on the approach required to study it. User evaluation is a challenging topic in ubiquitous computing. It is generally considered to be difficult, certainly more so than in previous computational settings. Heterogeneity in design, distributed and mobile users, invisible sensing systems and so on, all add up to render traditional methods of observation and evaluation insufficient to construct a complete view of interactional activity. These challenges necessitate the development of new observational technologies. This thesis explores some of those challenges and demonstrates that system logs, with suitable methods of synchronising, filtering and visualising them for use in conjunction with more traditional observational approaches such as video, can be used to overcome many of these issues. Through a review of both the literature of the field, and the state of the art of computer aided qualitative data analysis software (CAQDAS), a series of guidelines are constructed showing what would be required of a software toolkit to meet the challenges of studying ubiquitous computing systems. It outlines the design and implementation of two such software packages, \textit{Replayer} and \textit{Digital Replay System}, which approach the problem from different angles, the former being focussed on visualising and exploring the data in system logs and the latter focussing on supporting the methods used by social scientists to perform qualitative analyses. The thesis shows through case studies how this technique can be applied to add significant value to the qualitative analysis of ubiquitous computing systems: how the coordination of system logs and other media can help us find information in the data that would otherwise be inaccessible; an ability to perform studies in locations/settings that would otherwise be impossible, or at least very difficult; and how creating accessible qualitative data analysis tools allows people to study particular settings or technologies who could not have studied them before. This software aims to demonstrate the direction in which other CAQDAS packages may have to move in order to support the study of the characteristics of human-computer and human-human interaction in a world increasingly reliant upon ubiquitous computing technology

Women in Artificial intelligence (AI)

This Special Issue, entitled "Women in Artificial Intelligence" includes 17 papers from leading women scientists. The papers cover a broad scope of research areas within Artificial Intelligence, including machine learning, perception, reasoning or planning, among others. The papers have applications to relevant fields, such as human health, finance, or education. It is worth noting that the Issue includes three papers that deal with different aspects of gender bias in Artificial Intelligence. All the papers have a woman as the first author. We can proudly say that these women are from countries worldwide, such as France, Czech Republic, United Kingdom, Australia, Bangladesh, Yemen, Romania, India, Cuba, Bangladesh and Spain. In conclusion, apart from its intrinsic scientific value as a Special Issue, combining interesting research works, this Special Issue intends to increase the invisibility of women in AI, showing where they are, what they do, and how they contribute to developments in Artificial Intelligence from their different places, positions, research branches and application fields. We planned to issue this book on the on Ada Lovelace Day (11/10/2022), a date internationally dedicated to the first computer programmer, a woman who had to fight the gender difficulties of her times, in the XIX century. We also thank the publisher for making this possible, thus allowing for this book to become a part of the international activities dedicated to celebrating the value of women in ICT all over the world. With this book, we want to pay homage to all the women that contributed over the years to the field of AI

Designing Affective Loop Experiences

There is a lack of attention to the emotional and the physical aspects of communication in how we up to now have been approaching communication between people in the field of Human Computer Interaction (HCI). As de-signers of digital communication tools we need to consider altering the un-derlying model for communication that has been prevailing in HCI: the in-formation transfer model. Communication is about so much more than trans-ferring information. It is about getting to know yourself, who you are and what part you play in the communication as it unfolds. It is also about the experience of a communication process, what it feels like, how that feeling changes, when it changes, why and perhaps by whom the process is initiated, altered, or disrupted. The idea of Affective Loop experiences in design aims to create new expressive and experiential media for whole users, embodied with the social and physical world they live in, and where communication not only is about getting the message across but also about living the experi-ence of communication- feeling it. An Affective Loop experience is an emerging, in the moment, emotional experience where the inner emotional experience, the situation at hand and the social and physical context act together, to create for one complete em-bodied experience. The loop perspective comes from how this experience takes place in communication and how there is a rhythmic pattern in com-munication where those involved take turns in both expressing themselves and standing back interpreting the moment. To allow for Affective Loop experiences with or through a computer system, the user needs to be allowed to express herself in rich personal ways involv-ing our many ways of expressing and sensing emotions – muscles tensions, facial expressions and more. For the user to become further engaged in inter-action, the computer system needs the capability to return relevant, either diminishing, enforcing or disruptive feedback to those emotions expressed by the user so that the she wants to continue express herself by either strengthening, changing or keeping her expression. We describe how we used the idea of Affective Loop experiences as a con-ceptual tool to navigate a design space of gestural input combined with rich instant feedback. In our design journey, we created two systems, eMoto and FriendSense

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse