Educational magic toys developed with augmented reality technology for early childhood education

Shaping children's experience, enhancing their imagination and affecting their behaviors, toys have great importance. Recently, toys have gained a digital characteristic and many children have tended to use them. For this reason, educational magic toys (EMT) were developed with augmented reality technology in this study. It is called as EMT because virtual objects such as story animations, 3D objects and flash animations appear on the toys. EMT has included puzzles, flash cards and match cards to teach animals, fruits, vegetables, vehicles, objects, professions, colors, numbers and shapes for average 5–6 age children in Early Childhood Education. The aim of this study is to reveal teachers' and children's opinions on EMT, to determine children's behavioral patterns and their cognitive attainment, and the relationship between them while playing EMT. Mix method was used and the sample consisted of 30 teachers and 33 children aged 5–6 in early childhood education. As data collection tools, a survey, an observation and interview form were used. This study revealed that teachers and children liked EMT activity. In addition, children interactively played with these toys but not had high cognitive attainment. From this point, we can say that these toys can be effectively used in early childhood education. However, collaborative and interactive learning with these toys should be provided. Moreover, this study will provide an important contribution, present a new educational AR application, and fill the gap in the educational technology field.     

Monitoring children’s developmental progress using augmented toys and activity recognition

Previous research has established the connection between the way in which children interact with objects and the potential early identification of children with autism. Those findings motivate our own work to develop "smart toys," objects embedded with wireless sensors that are safe and enjoyable for very small children, that allow detailed interaction data to be easily recorded. These sensor-enabled toys provide opportunities for autism research by reducing the effort required to collect and analyze a child’s interactions with objects. In the future, such toys may be a useful part of clinical and in-home assessment tools. In this paper, we discuss the design of a collection of smart toys that can be used to automatically characterize the way in which a child is playing. We use statistical models to provide objective, quantitative measures of object play interactions. We also developed a tool to view rich forms of annotated play data for later analysis. We report the results of recognition experiments on more than fifty play sessions conducted with adults and children as well as discuss the opportunities for using this approach to support video annotation and other applications.     

Daily prediction of ICU readmissions using feature engineering and ensemble fuzzy modeling

This research is focused on the prediction of ICU readmissions using fuzzy modeling and feature selection approaches. There are a number of published scores for assessing the risk of readmissions, but their poor predictive performance renders them unsuitable for implementation in the clinical setting. In this work, we propose the use of feature engineering and advanced computational intelligence techniques to improve the performance of current models. In particular, we propose an approach that relies on transforming raw vital signs, laboratory results and demographic information into more informative pieces of data, selecting a subset of relevant and non–redundant variables and applying fuzzy ensemble modeling to the feature–engineered data for deriving important nonlinear relations between variables. Different criteria for selecting the best predictor from the ensemble and novel evaluation measures are explored. In particular, the area under the sensitivity curve and area under the specificity curve are investigated. The ensemble approach combined with feature transformation and feature selection showed increased performance, being able to predict early readmissions with an AUC of 0.77 ± 0.02. To the best of our knowledge, this is the first computational intelligence technique allowing the prediction of readmissions in a daily basis. The high balance between sensitivity and specificity shows its strength and suitability for the management of the patient discharge decision making process.     

Dependability issues in visual–haptic interfaces

Dependability of a system is commonly referred to its reliability, its availability and its maintenability (RAM), but when this concept is applied to user interfaces there is no common agreement on what aspects of user–system interaction are related to a satisfactory RAM level for the whole system. In particular, when dealing with haptic systems, interface dependability may become a crucial issue in medical and in military domains when life-critical systems are to be manipulated or where costly remote control operations are to be performed, like in industrial processes control or in aerospace/automotive engineering and manufacturing. This paper discusses the role of dependability in haptic user interfaces, aiming to the definition of a framework for the assessment of the usability and dependability properties of haptic systems and their possible correlations. The research is based on the analysis of a visual–haptic-based simulator targeted to maintenance activity training for aerospace industry which is taken as a case study. As a result, we propose a novel framework able to collect and then process relevant interaction data during the execution of haptic tasks, enabling to analyze dependability vs. usability correlations.     

A Multi-agent Based Evaluation Framework and Its Applications

The evaluation system is significant for assessment of technologies, experiments, energy cost and effectiveness, especially for the complicated engineering systems, such as energy systems, weapon systems and spacecraft systems. However, as engineering systems become more and more distributed and heterogeneous, evaluation frameworks need to be more universal, distributed and interactive. In this paper, we compare several typical evaluation frameworks and propose a novel evaluation framework based on multi-agent technology. We provide two case studies, indoor comfort system and technology assessment of spacecraft systems, respectively. The results show that the proposed framework can work efficiently.      

老年人玩具设计中的人文关怀

我国人口老龄化进程加快,由此带来了一系列需要研究的新问题;老年人的休闲生活、健身益脑方式、老年人的心理健康千预等问题引发广泛关注;老年人玩具开发设计的特殊性要求。设计师需要更加重视老年人玩具设计中的人文关怀。文章通过老年人的生理心理需求出发。对老年人玩具市场进行分析。提出老年人玩具设计中人文关怀的设计原则。     

Interactivity, interfaces, and smart toys

Although computers can represent a medium for children's social and intellectual development, some researchers believe that using computers before age seven subtracts from important developmental tasks and other types of learning. Those opposed to computers believe that computer-based activities are less effective in developing understanding and skills than are artifacts that young children can handle. These anxieties extend to technologies such as smart toys. Our recently completed research project, Computers and Children's Electronic Toys, investigated how children use smart toys. Cachet combines recent interest in mobile learning, tangible interfaces, and the home use of technologies. This research aimed mainly to explore interactivity and interfaces in the context of smart toys that children could use alone or in conjunction with a computer.     

Cyber–physical systems: Extending pervasive sensing from control theory to the Internet of Things

Essentially, the emerging term “Cyber–Physical Systems (CPS)” is an architectural paradigm in which the pervasive sensing technologies represent a fundamental part. Originally defined in the computer sciences domain, the term Cyber–Physical Systems has been adapted to very different domains such as the control theory or electronic engineering. Even, some authors understand CPS as a particular scenario of the Internet of Things (IoT) based on pervasive sensing. Furthermore, recently, some works propose a definition for CPS including all the features described in the different domains. In this paper we provide a comprehensive analysis of the nature and characteristics of the different proposals, discuss the recent attempts to standardize CPS, and review the state-of-the-art on CPS for each technological domain. We compare those different proposals on CPS, discuss about some related terms and technologies and conclude by describing the main research challenges in the area.     

Distributed representation learning and intelligent retrieval of knowledge concepts for conceptual design

Data-driven conceptual design is rapidly emerging as a powerful approach to generate novel and meaningful ideas by leveraging external knowledge especially in the early design phase. Currently, most existing studies focus on the identification and exploration of design knowledge by either using common-sense or building specific-domain ontology databases and semantic networks. However, the overwhelming majority of engineering knowledge is published as highly unstructured and heterogeneous texts, which presents two main challenges for modern conceptual design: (a) how to capture the highly contextual and complex knowledge relationships, (b) how to efficiently retrieve of meaningful and valuable implicit knowledge associations. To this end, in this work, we propose a new data-driven conceptual design approach to represent and retrieve cross-domain knowledge concepts for enhancing design ideation. Specifically, this methodology is divided into three parts. Firstly, engineering design knowledge from the massive body of scientific literature is efficiently learned as information-dense word embeddings, which can encode complex and diverse engineering knowledge concepts into a common distributed vector space. Secondly, we develop a novel semantic association metric to effectively quantify the strength of both explicit and implicit knowledge associations, which further guides the construction of a novel large-scale design knowledge semantic network (DKSN). The resulting DKSN can structure cross-domain engineering knowledge concepts into a weighted directed graph with interconnected nodes. Thirdly, to automatically explore both explicit and implicit knowledge associations of design queries, we further establish an intelligent retrieval framework by applying pathfinding algorithms on the DKSN. Next, the validation results on three benchmarks MTURK-771, TTR and MDEH demonstrate that our constructed DKSN can represent and associate engineering knowledge concepts better than existing state-of-the-art semantic networks. Eventually, two case studies show the effectiveness and practicality of our proposed approach in the real-world engineering conceptual design.     

DHIQA: Quality assessment of dehazed images based on attentive multi-scale feature fusion and rank learning

Haze is a ubiquitous atmospheric phenomenon that seriously influences the visibility of images. To this end, numerous image dehazing models have been proposed to improve the visual quality of hazy images. However, the quality assessment of dehazed images has fallen behind. Traditional IQA methods for dehazed images rely on complex handcrafted features that may not accurately evaluate the quality of dehazed images. In this paper, we present a novel no-reference image quality assessment network for dehazed images (called DHIQA). Firstly, we propose a multi-scale feature fusion network that considers typical dehazed distortion-related features, such as contrast, dark channel, edge, etc. Then, inspired by the contrast sensitivity function of the Human Visual System (HVS), we propose a contrast attentive module to enhance the effectiveness of the proposed IQA network. Moreover, in addition to the absolute quality score of dehazed images, their rankings are also important for quality assessment. Thus, we propose a new ranking loss, which takes both the absolute quality score and their rankings into consideration. Extensive experimental results on six publicly available dehazed IQA databases show that the proposed model achieves superior performance compared to current state-of-the-art metrics.     

Long-term knowledge acquisition using contextual information in a memory-inspired robot architecture

In this paper, we present a novel cognitive framework allowing a robot to form memories of relevant traits of its perceptions and to recall them when necessary. The framework is based on two main principles: on the one hand, we propose an architecture inspired by current knowledge in human memory organisation; on the other hand, we integrate such an architecture with the notion of context, which is used to modulate the knowledge acquisition process when consolidating memories and forming new ones, as well as with the notion of familiarity, which is employed to retrieve proper memories given relevant cues. Although much research has been carried out, which exploits Machine Learning approaches to provide robots with internal models of their environment (including objects and occurring events therein), we argue that such approaches may not be the right direction to follow if a long-term, continuous knowledge acquisition is to be achieved. As a case study scenario, we focus on both robot–environment and human–robot interaction processes. In case of robot–environment interaction, a robot performs pick and place movements using the objects in the workspace, at the same time observing their displacement on a table in front of it, and progressively forms memories defined as relevant cues (e.g. colour, shape or relative position) in a context-aware fashion. As far as human–robot interaction is concerned, the robot can recall specific snapshots representing past events using both sensory information and contextual cues upon request by humans.     

老年玩具开发设计研究

在新世纪全球人口老龄化的趋势下,我国老年人口的比例与数量正逐年增长,老龄化问题研究的滞后带来了一系列新的问题,其中包括老年玩具的开发问题。研究证明,老年玩具对于老年人休闲娱乐、健脑健身,预防老年痴呆等疾病有着重要作用,但我国专为老年人设计的玩具产品几乎空白,很需要在这一方面进行必要的调查研究,探讨出老年玩具产品开发设计的基本方法。     

Dynamic Fuzzy Rating Tracker (DYFRAT): a novel methodology for modeling real-time dynamic cognitive processes in rating scales

Rating scales (such as, Likert scales, Guttman scales, Feelings thermometers, etc.) represent simple tools for measuring attitudes, judgements and subjective preferences in human rating contexts. Because rating scales show some useful properties (e.g., measurement uniformity, considerable flexibility, statistically appealing), they represent popular and reliable instruments in socio-behavioral sciences. However, standard rating scales suffer also from some relevant limitations. For example, they fail in measuring vague and imprecise information and, above all, they are only able to capture the final outcome of the cognitive process of rating (i.e., the rater's response). To overcome these limitations, some fuzzy versions of these scales (e.g., fuzzy conversion scales, fuzzy rating scales) have been proposed over the years. However, also these more sophisticated scales show some important shortcomings (e.g., difficulty in fuzzy variables construction and potential lack of ecological validity). In this paper, we propose a novel methodology (DYFRAT) for modeling human rating evaluations from a fuzzy-set perspective. In particular, DYFRAT captures the fuzziness of human ratings by modeling some real-time biometric events that occur during the cognitive process of rating in an ecological measurement setting. Moreover, in order to show some important characteristics of the proposed methodology, we apply DYFRAT to some empirical rating situations concerning decision making and risk assessment scenarios.     

A robust study of reliability-based optimization methods under eigen-frequency

Nowadays, the search in reliability-based design optimization is becoming an important engineering design activity. Traditionally for these problems, the objective function is to minimize a cost function while satisfying the reliability constraints. The reliability constraints are usually formulated as constraints on the probability of failure. This paper focuses on the study of a particular problem with the failure mode on vibration of structure. The difficulty in evaluating reliability constraints comes from the fact that modern reliability analysis methods are themselves formulated as an optimization problem. Solving such nested optimization problems is extremely expensive for large-scale multidisciplinary systems which are likewise computationally intensive. With this in mind research, we propose in this paper a new method to treat reliability-based optimization methods under frequencies constraint. The goal of this development has resolved just one problem of optimization and reduced the cost of computation. Aircraft wing design typically involves multiple disciplines such as aerodynamics and structure; this numerical example demonstrated the different advantages of the proposed method.     

Play and learning in the digital future

Video games are vastly improved; they include embedded computers and new, improved expressions in graphics and music. Soon games and toys will become communication tools that connect with one another through internal embedded technology. Eventual convergence of the visual cyber community and the physical world would let users move toward a new stage of play and a new way of learning. Developing the future digital toys and games so that the toys and their users work in a harmonious way is a task with far-reaching implications for everyone involved in the learning process, but especially for children. In this effort, the Toys of Tomorrow consortium at the MIT Media Laboratory is researching children's play and learning. Here, we comment briefly on the increasingly profitable and influential game and entertainment industry, introduce the various MIT research projects, and discuss how we expect their results to affect our world and enhance the learning process     

RiskM: A multi-perspective modeling method for IT risk assessment

Stakeholder involvement and participation are widely recognized as being key success factors for IT risk assessment. A particular challenge facing current IT risk assessment methods is to provide accessible abstractions on matters of IT risk that attend to both managerial and technical perspectives of the stakeholders involved. In this paper, we investigate whether a conceptual modeling method can address essential requirements in the IT risk assessment domain, and which structural and procedural features such a method entails. The research follows a design research process in which we describe a research artifact, and evaluate it to assess whether it meets the intended goals. In the paper, we specify requirements and assumptions underlying the method construction, discuss the structural specification of the method and its design rationale, present a prototypical application scenario, and provide an initial method evaluation. The results indicate that multi-perspective modeling methods satisfy requirements specific to the IT risk assessment domain, and that such methods, in fact, provide abstractions on matters of IT risk accessible to both a technical and a managerial audience.     

Semantic tagging and linking of software engineering social content

Social online communities and platforms play a significant role in the activities of software developers either as an integral part of the main activities or through complimentary knowledge and information sharing. As such techniques become more prevalent resulting in a wealth of shared information, the need to effectively organize and sift through the information becomes more important. Top-down approaches such as formal hierarchical directories have shown to lack scalability to be applicable to these circumstanes. Light-weight bottom-up techniques such as community tagging have shown promise for better organizing the available content. However, in more focused communities of practice, such as software engineering and development, community tagging can face some challenges such as tag explosion, locality of tags and interpretation differences, to name a few. To address these challenges, we propose a semantic tagging approach that benefits from the information available in Wikipedia to semantically ground the tagging process and provide a methodical approach for tagging social software engineering content. We have shown that our approach is able to provide high quality tags for social software engineering content that can be used not only for organizing such content but also for making meaningful and relevant content recommendation to the users both within a local community and also across multiple social online communities. We have empirically validated our approach through four main research questions. The results of our observations show that the proposed approach is quite effective in organizing social software engineering content and making relevant, helpful and novel content recommendations to software developers and users of social software engineering communities.     

Walking in a cube: novel metaphors for safely navigating large virtual environments in restricted real workspaces

Immersive spaces such as 4-sided displays with stereo viewing and high-quality tracking provide a very engaging and realistic virtual experience. However, walking is inherently limited by the restricted physical space, both due to the screens (limited translation) and the missing back screen (limited rotation). In this paper, we propose three novel locomotion techniques that have three concurrent goals: keep the user safe from reaching the translational and rotational boundaries; increase the amount of real walking and finally, provide a more enjoyable and ecological interaction paradigm compared to traditional controller-based approaches. We notably introduce the "Virtual Companion", which uses a small bird to guide the user through VEs larger than the physical space. We evaluate the three new techniques through a user study with travel-to-target and path following tasks. The study provides insight into the relative strengths of each new technique for the three aforementioned goals. Specifically, if speed and accuracy are paramount, traditional controller interfaces augmented with our novel warning techniques may be more appropriate; if physical walking is more important, two of our paradigms (extended Magic Barrier Tape and Constrained Wand) should be preferred; last, fun and ecological criteria would favor the Virtual Companion.     

Dealing with heterogeneous information in engineering evaluation processes

Before selecting a design for a large engineering system several design proposals are evaluated studying different key aspects. In such a design assessment process, different criteria need to be evaluated, which can be of both of a quantitative and qualitative nature, and the knowledge provided by experts may be vague and/or incomplete. Consequently, the assessment problems may include different types of information (numerical, linguistic, interval-valued). Experts are usually forced to provide knowledge in the same domain and scale, resulting in higher levels of uncertainty. In this paper, we propose a flexible framework that can be used to model the assessment problems in different domains and scales. A fuzzy evaluation process in the proposed framework is investigated to deal with uncertainty and manage heterogeneous information in engineering evaluation processes.