Intelligent Virtual Environment Research Articles

Extending the Framework for Developing Intelligent Virtual Environments (FIVE) with Artifacts for Modeling Internet of Things Devices and a New Decentralized Federated Learning Based on Consensus for Dynamic Networks.

One of the main lines of research in distributed learning in recent years is the one related to Federated Learning (FL). In this work, a decentralized Federated Learning algorithm based on consensus (CoL) is applied to Wireless Ad-hoc Networks (WANETs), where the agents communicate with other agents to share their learning model as they are available to the wireless connection range. When deploying a set of agents, it is essential to study whether all the WANET agents will be reachable before the deployment. The paper proposes to explore it by generating a simulation close to the real world using a framework (FIVE) that allows the easy development and modification of simulations based on Unity and SPADE agents. A fruit orchard with autonomous tractors is presented as a case study. The paper also presents how and why the concept of artifact has been included in the above-mentioned framework as a way to highlight the importance of some devices used in the environment that have to be located in specific places to ensure the full connection of the system. This inclusion is the first step to allow Digital Twins to be modeled with this framework, now allowing a Digital Shadow of those devices.

A study on perceptions of students on intelligent virtual learning environment during and post COVID-19

A study on perceptions of students on intelligent virtual learning environment during and post COVID-19

A study on perceptions of students on intelligent virtual learning environment during and post COVID-19

A study on perceptions of students on intelligent virtual learning environment during and post COVID-19

An Intelligent Virtual Environment for Designers with Reduced Motor Abilities

Conventional CAD modelling software demands substantial utilisation of input modalities like the keyboard and mouse for creating 3-dimensional (3D) models. The dexterity measures involved in controlling input modalities could pose challenges to users with motor disabilities—including the inability to move their limbs, particularly their upper and lower arms, and fingers, due to traumatic damage or congenital problems. In order to meet these challenges, this paper proposes a virtual reality (VR)-based medium to help users with motor disabilities build simple 3D models for architectural design. The concept of operating buttons using head-gaze in the VR environment has been utilised to perform scaling—a 3D object manipulation method—to create simplified building models. Moreover, navigation in the VR space using tilting of the head has been employed with the user seated on a revolving chair, thus eliminating the need for any limbic movement. Unity game engine was used to develop two variations of the VR model with a different button layout for creating simple cuboidal volumes mimicking buildings in the virtual environment. Both variations have been tested with 32 individuals against a specific performance indicator (i.e., task completion time) and self-reported metrics, such as the perception of effort applied and degree of visual clutter, followed by retrospective participant feedback sessions. One of the VR application's variants (i.e., variant 1) produced promising results regarding overall usability and effort demand. This paper also proposes a methodological framework for an AI-based, intelligent, and adaptive VR application interface that caters to the user's abilities and pain points in real-time. In the future, this framework could be instrumental in creating a comprehensive gaze-based VR tool for 3D modelling having multiple functions to help users with motor disabilities.

How does artificial intelligence empower EFL teaching and learning nowadays? A review on artificial intelligence in the EFL context.

The booming Artificial Intelligence (AI) provides fertile ground for AI in education. So far, few reviews have been deployed to explore how AI empowers English as Foreign Language (EFL) teaching and learning. This study attempts to give a brief yet profound overview of AI in the EFL context by summarizing and delineating six dominant forms of AI application, including Automatic Evaluation Systems, Neural Machine Translation Tools, Intelligent Tutoring Systems (ITSs), AI Chatting Robots, Intelligent Virtual Environment, and Affective Computing (AC) in ITSs. The review furthermore uncovers a current paucity of research on applying AC in the EFL context and exploring pedagogical and ethical implications of AI in the EFL context. Ultimately, challenges from technical and teachers' perspectives, as well as future research directions, are illuminated, hopefully proffering new insights for the future study.

An intelligent virtual reality technology in the teaching of art creation and design in colleges and universities

The popularization of virtual reality technology has become a brand-new carrier of knowledge and information dissemination and a new tool for art creation and design teaching in Colleges and universities. In this paper, first of all, from the three aspects of the definition and characteristics of virtual reality technology, the integration of virtual reality technology into art design teaching, and the significance of using virtual reality technology in art design teaching, the reform of art creation and design teaching in Colleges and Universities under virtual reality technology is discussed. In order to carry out the application research, this paper then chooses to carry on the simulation modeling teaching of the bamboo forest in the intelligent virtual reality environment, making full use of the intelligent modeling tools, rendering tools and mapping tools to complete the teaching application examples of the art modeling design in Colleges and universities. In the specific teaching of art creation and design in Colleges and universities, the creation and design modeling of individual bamboos, the creation and design modeling of bamboos forest, and the creation and design modeling of different lighting effects and scene rendering are carried out respectively. Finally, from the advantages of intelligent virtual reality technology in art creation and design of colleges and universities, the expansion and promotion of teaching resources, and the synergistic effect of teaching results, we analyze the strategies of art creation and design teaching in Colleges and Universities under the background of intelligent virtual reality technology in detail.

Intelligent Interaction with Virtual Geographical Environments Based on Geographic Knowledge Graph

The core of intelligent virtual geographical environments (VGEs) is the formal expression of geographic knowledge. Its purpose is to transform the data, information, and scenes of a virtual geographic environment into “knowledge” that can be recognized by computer, so that the computer can understand the virtual geographic environment more easily. A geographic knowledge graph (GeoKG) is a large-scale semantic web that stores geographical knowledge in a structured form. Based on a geographic knowledge base and a geospatial database, intelligent interactions with virtual geographical environments can be realized by natural language question answering, entity links, and so on. In this paper, a knowledge-enhanced Virtual geographical environments service framework is proposed. We construct a multi-level semantic parsing model and an enhanced GeoKG for structured geographic information data, such as digital maps, 3D virtual scenes, and unstructured information data. Based on the GeoKG, we propose a bilateral LSTM-CRF (long short-term memory- conditional random field) model to achieve natural language question answering for VGEs and conduct experiments on the method. The results prove that the method of intelligent interaction based on the knowledge graph can bridge the distance between people and virtual environments.

MAMbO5: a new ontology approach for modelling and managing intelligent virtual environments based on multi-agent systems

An intelligent virtual environment simulates a physical world inhabited by autonomous intelligent entities. Multi-agent systems have been usually employed to design systems of this kind. One of the key aspects in the design of intelligent virtual environments is the use of appropriate ontologies which offer a richer and more expressive representation of knowledge. In this sense, this paper proposes an ontology comprising concepts for modelling intelligent virtual environments enhanced with concepts for describing agent-based organisational features. This new ontology, called MAMbO5, is used as an input of the JaCalIVE framework, which is a toolkit for the design and implementation of agent-based intelligent virtual environments.

ON-SMMILE: Ontology Network-based Student Model for MultIple Learning Environments

Currently, many educational researchers focus on the extraction of information about the learning progress to properly assist students. We present ON-SMMILE, a student-centered and flexible student model which is represented as an ontology network combining information related to (i) students and their knowledge state, (ii) assessments that rely on rubrics and different types of objectives, (iii) units of learning and (iv) information resources previously employed as support for the student model in intelligent virtual environment for training/instruction and here extended. The aim of this work is to design and build methodologically, throughout ontological engineering, the ON-SMMILE model to be used as support of future works closely linked to supervision of student's learning as competence-based recommender system. For this purpose, our model is designed as a set of ontological resources that have been extended, standardized, interrelated and adapted to be used in multiple learning environments. In this paper, we also analyze the available approaches based on instructional design which can be added to ontology network to build the proposed model. As a case study, a chemical experiment in a virtual environment and its instantiation are described in terms of ON-SMMILE.

The JaCalIVE framework for MAS in IVE: A case study in evolving modular robotics

Abstract This paper presents a framework specially designed for the execution and adaptation of Intelligent Virtual Environments. This framework, called JaCalIVE, facilitates the development of this kind of environments managing in an efficient and realistic way the evolution of parameters for the adaptation of the physical world. The framework includes a design method and a physical simulator which is in charge of giving the Intelligent Virtual Environment the look of the real or physical world, allowing to simulate physical phenomena such as gravity or collision detection. The paper also includes a case study which illustrates the use of the proposed framework as an evolutive algorithm which allows the automatic adaptation of modular robots.

A Study on Role Behaviors in Virtual Environment

With the constant development of the study on intelligent virtual environment, it has become a hot research topic of the current virtual environment field that researches and analyses on initiative perception of role behaviors in virtual environment are carried out through computer technology. In this paper, the author classifies features of role behaviors in virtual environment through SOM algorithm and trains the computer to carry out automatic behavior identification so as to establish a role behaviors cognition model in virtual environment based on SOM algorithm, providing a new method and a reference for the automatic identification of role behaviors in virtual environment.

Using Emotions in Intelligent Virtual Environments: The EJaCalIVE Framework

Nowadays, there is a need to provide new applications which allow the definition and implementation of safe environments that attends to the user needs and increases their wellbeing. In this sense, this paper introduces the EJaCalIVE framework which allows the creation of emotional virtual environments that incorporate agents, eHealth related devices, human actors, and emotions projecting them virtually and managing the interaction between all the elements. In this way, the proposed framework allows the design and programming of intelligent virtual environments, as well as the simulation and detection of human emotions which can be used for the improvement of the decision-making processes of the developed entities. The paper also shows a case study that enforces the need of this framework in common environments like nursing homes or assisted living facilities. Concretely, the case study proposes the simulation of a residence for the elderly. The main goal is to have an emotion-based simulation to train an assistance robot avoiding the complexity involved in working with the real elders. The main advantage of the proposed framework is to provide a safe environment, that is, an environment where users are able to interact safely with the system.

Assessment of software defect detection efficiency and cost through an intelligent collaborative virtual environment

The use of collaborative virtual environments facilitates communication, coordination and cooperation within a group of people. In the field of information and communications technology (ICT), collaborative virtual environments have been developed to support the learning of programming. In this work, we report an empirical study (controlled experiment) which assess the efficiency and cost of detecting defects in instrumented programs with and without the support of an intelligent collaborative virtual environment (ICVE). The ICVE was used as part of a programming course at undergraduate level. The results suggest an equivalent efficiency in defect detection for both types of participants, those who used the ICVE (3.76 observed defects per hour) and those who worked in a traditional manner (4.07 observed defects per hour). With regard to cost, it was observed that participants who used the ICVE completed the activities within a slightly shorter time frame (49.25 minutes) than those who worked without the environment (52.90 minutes); however, the difference was not significant. It was observed that with regard to efficiency and cost, for this type of task (the detection of defects), working virtually through an ICVE versus working ad hoc (in a tradition manner, at the same time and in the same place) yields equivalent results. When collaborative work cannot be done in a traditional way, the use an ICVE is an alternative approach equally effective.

Using emotions for the development of human-agent societies

Human-agent societies refer to applications where virtual agents and humans coexist and interact transparently into a fully integrated environment. One of the most important aspects in this kind of applications is including emotional states of the agents (humans or not) in the decision-making process. In this sense, this paper presents the applicability of the JaCalIVE (Jason Cartago implemented intelligent virtual environment) framework for developing this kind of society. Specifically, the paper presents an ambient intelligence application where humans are immersed into a system that extracts and analyzes the emotional state of a human group. A social emotional model is employed to try to maximize the welfare of those humans by playing the most appropriate music in every moment.

Extending MAM5 Meta-Model and JaCalIV E Framework to Integrate Smart Devices from Real Environments.

This paper presents the extension of a meta-model (MAM5) and a framework based on the model (JaCalIVE) for developing intelligent virtual environments. The goal of this extension is to develop augmented mirror worlds that represent a real and virtual world coupled, so that the virtual world not only reflects the real one, but also complements it. A new component called a smart resource artifact, that enables modelling and developing devices to access the real physical world, and a human in the loop agent to place a human in the system have been included in the meta-model and framework. The proposed extension of MAM5 has been tested by simulating a light control system where agents can access both virtual and real sensor/actuators through the smart resources developed. The results show that the use of real environment interactive elements (smart resource artifacts) in agent-based simulations allows to minimize the error between simulated and real system.

Design and implementation of an intelligent virtual environment for improving speaking and listening skills

In this paper, we present an intelligent architecture, called intelligent virtual environment for language learning, with embedded pedagogical agents for improving listening and speaking skills of non-native English language learners. The proposed architecture integrates virtual environments into the Intelligent Computer-Assisted Language Learning. This architecture supports visual, auditory, and haptic channels of interaction. It allows pedagogical ideas about language skills to be implemented and validated with a minimum design time. Moreover, we design a computational model to evaluate learner's proficiency level, and an automatic adaptation mechanism which adjusts to the learner's learning curve. We have implemented two scenarios based on the proposed architecture to teach learners how to communicate in public places such as airports and TV stores. Inputs to this system include learner's speech and hand motion, and outputs include graphical scenes, force feedback, and speech by a few embodied agents. Throughout interactions, agents discover the proficiency level of the learner and customize the level of communication complexity accordingly. The system is tested on 10 subjects. Experimental results show 14% increase in the number of proper replies, 3% decrease in grammatical errors, 16% decrease in pronunciation duration, and 11% increase in learners' proficiency level within three trials.

Applying a student modeling with non-monotonic diagnosis to Intelligent Virtual Environment for Training/Instruction

We present a student modeling approach that has been designed to be part of an Intelligent Virtual Environment for Training and/or Instruction (IVET). In order to provide the proper tutoring to a student, an IVET needs to keep and update dynamically a student model taking into account the student’s behaviour in the Virtual Environment. For that purpose, the proposed student model employs a student ontology, a pedagogic diagnosis module and a Conflict Solver module. The goal of the pedagogic diagnosis module is to infer which learning objectives have been acquired or not by the student. Nevertheless, the diagnosis process can be complicated by the fact that while learning the student will not only acquire new knowledge, but he/she may also forget some previously acquired knowledge, or he/she may have some oversights that could mislead the tutor about the true state of the student’s knowledge. All of these situations will lead to contradictions in the student model that must be solved so that the diagnosis can continue. Thus, our approach consists in applying diagnosis rules until a contradiction arises. At that moment, a conflict solver module is responsible of classifying and solving the contradiction. Next, the student ontology is updated according to the resolution adopted by the Conflict Solver and the diagnosis can continue. This paper mainly focuses on the design of the proper mechanisms of the student model to deal with the non monotonic nature of the pedagogic diagnosis.

Fuzzy method for pre-diagnosis of breast cancer from the Fine Needle Aspirate analysis

BackgroundAcross the globe, breast cancer is one of the leading causes of death among women and, currently, Fine Needle Aspirate (FNA) with visual interpretation is the easiest and fastest biopsy technique for the diagnosis of this deadly disease. Unfortunately, the ability of this method to diagnose cancer correctly when the disease is present varies greatly, from 65% to 98%. This article introduces a method to assist in the diagnosis and second opinion of breast cancer from the analysis of descriptors extracted from smears of breast mass obtained by FNA, with the use of computational intelligence resources - in this case, fuzzy logic.MethodsFor data acquisition of FNA, the Wisconsin Diagnostic Breast Cancer Data (WDBC), from the University of California at Irvine (UCI) Machine Learning Repository, available on the internet through the UCI domain was used. The knowledge acquisition process was carried out by the extraction and analysis of numerical data of the WDBC and by interviews and discussions with medical experts. The PDM-FNA-Fuzzy was developed in four steps: 1) Fuzzification Stage; 2) Rules Base; 3) Inference Stage; and 4) Defuzzification Stage. Performance cross-validation was used in the tests, with three databases with gold pattern clinical cases randomly extracted from the WDBC. The final validation was held by medical specialists in pathology, mastology and general practice, and with gold pattern clinical cases, i.e. with known and clinically confirmed diagnosis.ResultsThe Fuzzy Method developed provides breast cancer pre-diagnosis with 98.59% sensitivity (correct pre-diagnosis of malignancies); and 85.43% specificity (correct pre-diagnosis of benign cases). Due to the high sensitivity presented, these results are considered satisfactory, both by the opinion of medical specialists in the aforementioned areas and by comparison with other studies involving breast cancer diagnosis using FNA.ConclusionsThis paper presents an intelligent method to assist in the diagnosis and second opinion of breast cancer, using a fuzzy method capable of processing and sorting data extracted from smears of breast mass obtained by FNA, with satisfactory levels of sensitivity and specificity. The main contribution of the proposed method is the reduction of the variation hit of malignant cases when compared to visual interpretation currently applied in the diagnosis by FNA. While the MPD-FNA-Fuzzy features stable sensitivity at 98.59%, visual interpretation diagnosis provides a sensitivity variation from 65% to 98% (this track showing sensitivity levels below those considered satisfactory by medical specialists). Note that this method will be used in an Intelligent Virtual Environment to assist the decision-making (IVEMI), which amplifies its contribution.

Based on Bayesian Network of Artificial Fish of Auditory System Research

The intelligent virtual environment in an artificial fish of virtual auditory system is designed in this paper. Firstly, the model of artificial fish of auditory system in intelligent virtual environment (IVE) is built. Secondly, two-layer of artificial fish of auditory perception is designed according to the biological mechanism of auditory. The first layer is based on the design of the low frequency signal. The second layer is based on the design of the high frequency signal. And using the bayesian network(BN) to realize the acoustic signals of artificial fish to learn and memory algorithm. Get a satisfactory result through animation simulation.

Modelo de un Personaje en un Entorno Virtual Inteligente

In this paper, a character reference model, based on its perception and reasoning, with the objective of achieving visual realism in an Intelligent Virtual Environment (IVE) is proposed. The necessary steps for obtaining the model are: i) to identify the characteristics of the objects and of the virtual character of the IVE; ii) design of the IVE model; iii) specification of the Artificial Intelligence technique (AI); iv) defining the physical level and semantic system for the integration of the character with the environment; v) validation of the proposed model in a prototype; and vi) evaluation of the results. The proposed model allows generating an appropriate dynamics between the character en the elements of the virtual environment, which is required in several applications.