Assisstive technology application for enhancing social and language skills of young children with autism

In this paper we present an assistive system designed for supporting young children affected by autism in their process of learning pronunciation and meaning of new words. The system is built-up of a mobile application and objects identifiers which in our case were Estimote Beacon sensors. The system requires active participation of a parent who selects words to learn, records pronunciation of object names, selects illustrations, and activates and turns off the application. The entire process is designed to extend parents’ care and to support autistic children with an instant repetition of pronounced object’s names when those items are met during playing or moving around the house. An experimental part of our project consists of a report where we compare collected results of two autistic children using our application installed on a smart watch and on a smart phone. In both reported cases autistic children made a visible progress in speed of learning new words when compared to an equivalent period of time without assistive application support.

     

Classification algorithm based on pairwise comparison of features

We propose an alternative approach to classification that differs from known approaches in that instead of comparing the tuple of values of a test object’s features with similar tuples of features for objects in the training set, in this approach we make independent pairwise comparisons of every pair of feature values for the objects being compared. Here instead of using the notion of a “nearest neighbors” for test object, we introduce the notion of “admissible proximity” for each feature value in the test object. In this approach, we propose an alternative algorithm for classification that has a number of significant practical features. The algorithm’s quality was evaluated on sample problems taken from the well-known UCI repository and related to various aspects of human activity. The results show that the algorithm is competitive compared to known classification algorithms.     

“双一流”背景下高等教育信息化教学改革与实践研究

教育信息化建设既是深化教育教学改革的重要内容,也是推动教学方式转变、提高人才培养质量的重要发展趋势。党中央、国务院在《中国教育现代化2035》把教育教学信息化作为实现教育现代化的重要战略任务之一,提出"大力推进教育信息化""促进信息技术与教育教学深度融合,支持学校充分利用信息技术开展人才培养模式和教学方法改革,逐步实现信息化教与学应用师生全覆盖"。在此背景下,中国各高校高度重视并积极推进信息化教学改革与实践,建设特色智慧校园,为"双一流"建设提供支撑。教育信息化建设既是深化教育教学改革的重要内容,也是推动教学方式转变、提高人才培养质量的重要发展趋势。疫情防控期间,高校的信息化工作都不同程度地面临着一定的压力,但同时也促使信息化部门对未来的工作做出思考。     

Mona Lisa alive

This paper presents a novel approach for creating self-moving objects using hollow-face illusion. Given a clip of character animation, our approach generates a static object. Looking at the object at different views, a similar deformation can be observed. To accomplish this challenging mission, we give qualitative and quantitative analysis of hollow-face illusion. Methodology in computer vision and human perception are utilized to design the algorithm. A static object is first generated to satisfy the relative motion illusion constraints. The illusion is then strengthened by back projecting the object to the 3D face space. Considering both “bottom-up” visual signal and “top-down” knowledge, the intended illusion can be generated. Experiments have shown the effectiveness of our algorithm. For example, expression varying illusion on an oil painting can be created by our method. The self-moving objects can be used in applications such as design, entertainment, advertisement, and public safety.     

A comprehensive study of parameters in physical environment that impact students’ focus during lecture using Internet of Things

We describe and analyze the impact of several parameters of the physical environment in a classroom on students’ focus, where the term “focus” refers to the students’ subjective feeling of their ability to concentrate on a lecture at a given moment. The primary goal is to identify those parameters that significantly affect students’ focus during the lectures. We had measured several parameters in a real classroom environment using different low-cost smart devices. The research is based on the dataset collected from 14 recorded lectures attended by 197 students. We had measured five parameters of the physical environment and extracted 22 features from the lecturer’s voice. After analyzing collected measurements, we had identified eight parameters that have shown to have statistically different values for “focused” and “not focused” segments. We used obtained dataset to test different classifiers and their ability to correctly classify “focused” against “not focused” segments of the lectures. We found out that AdaBoost M1 classifier had the best overall recognition accuracy (86.78%). After performing additional series of trials we identified three parameters that could be removed from the original dataset without changing classifier’s accuracy, which left us five uncorrelated parameters that have shown to have significant impact on students’ focus.     

Vocational education approach: New TEL settings—new prospects for teachers’ instructional activities?

This study focuses on vocational education teachers’ instructional activities in a new technology-enhanced learning (TEL) setting. A content analysis is applied to investigate teachers’ and students’ interactions in a 3D game context. The findings illustrate that when teachers’ and students’ interactions are mediated by a game, teachers seem to apply different discussion activities to empower vocational learning than they do in traditional classroom settings. Additionally, the present study shows that teachers spontaneously develop new ways of supporting vocational learning processes. In more detail, two main types of instructional activities were identified: a “knowledge-providing” approach and a “joint problem-solving” approach. Additionally, findings illustrate how teachers using different types of instructional approaches are followed up with different processes by students. The article is concluded with a general discussion of the emerging challenges regarding the technological and pedagogical development of vocational education and teachers’ instructional activities in new TEL settings based on a more long-term design-based research project (ongoing since 2004).     

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.     

A support infrastructure for the smart kindergarten

Continuing progress in microelectronics has allowed the embedding of sensing, processing, and wireless communications capabilities in familiar physical objects. This enables the creation of smart environments, where communication and computation technologies facilitate interactions between people and their surroundings, instead of just person-to-person or person-to-server communication. In a collaborative project underway at the University of California, Los Angeles, called Smart Kindergarten (SmartKG), we are exploring these technologies in a sensor-instrumented environment for early childhood education. Spatially dense but unobtrusive sensors continuously capture interactions among students, teachers, and common classroom objects. The sensors deliver observations wirelessly to a wired infrastructure for analysis and storage. Two crucial building blocks of this environment are Sylph, a sensor middleware infrastructure, and iBadge, a lightweight sensor-instrumented badge worn by students and teachers.     

Design and implementation of a framework for building distributed smart object systems

A smart object system encompasses the synergy between computationally augmented everyday objects and external applications. This paper presents a software framework for building smart object systems following a declarative programming approach centered around custom written documents that glue the smart objects together. More specifically, in the proposed framework, applications’ requirements and smart objects’ services are objectified through structured documents. A runtime infrastructure provides the spontaneous federation between smart objects and applications through structural type matching of these documents. There are three primary advantages of our approach: firstly, it allows developers to write applications in a generic way without prior knowledge of the smart objects that could be used by the applications. Secondly, smart object management (locating, accessing, etc.) issues are completely handled by the infrastructure; thus application development becomes rapid and simple. Finally, the programming abstraction used in the framework allows extension of functionalities of smart objects and applications very easily. We describe an implemented prototype of our framework and show examples of its use in a real life scenario to illustrate its feasibility.     

Object-oriented virtual environment for visualization of flexible multibody systems

An object-oriented event-driven virtual environment (VE) for viewing the simulation results of flexible multibody systems (FMS) is developed. The VE interfaces with the following output devices: immersive stereoscopic screen(s) and stereo speakers; and a variety of input devices including, head tracker, wand, joystick, mouse, microphone, and keyboard. The VE incorporates the following types of primitive software objects: user-interface objects, support objects, geometric entities, and finite elements. Each object encapsulates a set of properties, methods, and events that define its behavior, appearance, and functions. A “container” object allows grouping many objects into one object, which inherits the properties of its “children” objects. The VE allows real-time viewing and “fly-through” of photo-realistic models, vibrational mode-shapes, and animation of the dynamic motion of FMS. An application of this VE is presented for visualization of the dynamic analysis results of a large deployable space structure — NASA’s Next Generation Space Telescope.     

Networking,Storytelling and Knowledge Production in First-Year Writing

As writing teachers, we seek to validate the knowledge that students bring to the classroom while introducing and cultivating new methods, strategies, techniques and technologies that may serve them now and in the future. In this article we describe an approach we take that integrates curricular and extracurricular co-apprenticeship strategies using public writing models in conjunction with social networking tools. With publication as a final goal, we urge students to move from expressing personal problems to addressing social issues, using a private, non-commercial learning network NoDiff <http://NoDiff.com> as a safe zone for skills development, knowledge production and social inquiry. In taking this approach, we resist dichotomies that place professional skills training in strict opposition to critical pedagogy. We argue that many of the so-called “extracurricular” composing activities that most of today's students engage in lay the groundwork for both professional and civic participation. Acknowledging that we as composition teachers are also beginners in the world of 21^st century communication, we emphasize both (1) the continual transference of skills and knowledge among teachers and learners; and (2) the importance of providing what is often lacking in skills-based ‘new literacy’ training, namely a critical pedagogical approach to learning as social engagement and critical intervention.     

Robust facial expression recognition of a speaker using thermal image processing and updating of fundamental training data

We previously developed a method for the facial expression recognition of a speaker. For facial expression recognition, we selected three static images at the timing positions of just before speaking and while speaking the phonemes of the first and last vowels. Then, only the static image of the front-view face was used for facial expression recognition. However, frequent updates of the training data were time-consuming. To reduce the time for updates, we found that the classifications of “neutral”, “happy”, and “others” were efficient and accurate for facial expression recognition. Using the proposed method with updated training data of “happy” and “neutral” after an interval such as approximately three and a half years, the facial expressions of two subjects were discriminable with 87.0 % accuracy for the facial expressions of “happy”, “neutral”, and “others” when exhibiting the intentional facial expressions of “angry”, “happy”, “neutral”, “sad”, and “surprised”.     

Effects of time affordance and operation mode on a smart microwave oven touch-sensitive user Interface design

Smart homes have revolutionized our daily lives. With today’s fast-paced lifestyle, pursuing a high quality of life has become many people’s goal and motivation. The purpose of this study is to investigate the user interface design of smart microwave ovens pertinent to time affordance and operation mode. A 2?×?3 mixed factorial design was planned to help explore whether different time affordances (i.e., high and low) and operation modes (i.e., traditional, touch, and smart) may affect users’ task performance and subjective evaluation. Using the convenience sampling method, 24 adults were recruited to participate in the experiment. The experimental data were collected pertinent to task performance, the system usability scale, and through questionnaires created using a 7-point Likert scale, and semi-structured interviews. The generated results revealed that: (1) there was a significant difference in the time affordance. Multiple time information cues can help reduce uncertainty, providing high time affordance to the participants. (2) There were significant differences among different operation modes. A simple and intuitive “smart” type is in line with user expectations. (3) The overall analysis of task performance and satisfaction consistently showed that high time affordance is better than low time affordance in all aspects, and the “smart” type had the best task performance. (4) The user interface design should be followed by users’ experience and the features of the touch product. Partially smart and custom function adjustments may effectively improve the user’s control of smart products.

     

Planar Numerical Signature Theory Applied to Object Recognition

Geometric invariants play a crucial role in the field of object recognition where the objects of interest are affected by a group of transformations. However, designing robust algorithms that are tolerant to noise and image occlusion remains an open problem. In particular, numerical signature-invariants in terms of joint invariants, as an approximation to the differential signature-invariants, suffer instability, bias, noise and indeterminacy in the resulting signatures. This paper addresses some of these issues in respect of planar signatures. To improve the stability in the Euclidean case, we replace Heron’s formula by the “accurate area” and then we demonstrate that the proposed algorithm is, not only numerically stable but is also, in terms of mean square error, a closer approximation (by at least a factor of three) compared with the original formulation of Calabi. To reduce noise in the resulting curves “the n-difference technique” and “the m-mean signature method” are introduced and we show that these methods are capable of minimizing noise by more than 90 %. The n-difference technique can also be applied to eliminate indeterminacy in the outputs. For the equiaffine case, we improve and extend the required formulation for the implementation of Signature theory for any planar meshes with a general position property. Moreover, we introduce a general formulation for the full conic sections to determine an equiaffine-invariant numerical approximation to the equiaffine arc length, measured along the given curve between any two points of the mesh. Finally, we demonstrate the discriminative power of the concept of discrete signature analysis for distinguishing normal and abnormal regions in the medical imaging domain.     

Fusion of thermal infrared and visible spectra for robust moving object detection

The detection of moving objects is a crucial step for many video surveillance applications whether using a visible camera (VIS) or an infrared (IR) one. In order to profit from both types, several fusion methods were proposed in the literature: low-level fusion, medium-level fusion and high-level fusion. The first one is the most used for moving objects’ detection in IR and VIS spectra. In this paper, we present an overview of the different moving object detection methods in IR and VIS spectra and a state of the art of the low-level fusion techniques. Moreover, we propose a new method for moving object detection using low-level fusion of IR and VIS spectra. In order to evaluate quantitatively and qualitatively our proposed method, three series of experiments were carried out using two well-known datasets namely “OSU Color-Thermal Database” and “INO-Database”; the results of these evaluations show promising results and demonstrate the effectiveness of the proposed method.     

Using Distributable User Interfaces in CSCL In-Situ Classrooms

Distributable user interfaces enable users to distribute user interface interaction objects (i.e. panels, buttons, input fields, checkboxes, etc.) across different displays using a set of distribution primitives to manipulate them in real time. This work presents how this kind of user interfaces facilitates the computer supported collaborative learning in modern classrooms. These classrooms provide teachers and students with display ecosystems consisting of stationary displays, such as smart projectors and smart TVs as well as mobile displays owned by teachers and students, such as smartphones, tablets, and laptops. The distribution of user interface interaction objects enables teachers to modify the user interface interaction objects that are available to students in real time to control and promote the collaboration and participation among them during learning activities. We propose the development of this type of applications using an extension of the CAMELEON reference framework that supports the definition of UI distribution models. The Essay exercise is presented as a case of study where teachers control the collaboration among students by distributing user interface interaction objects.     

An attribute-based ant colony system for adaptive learning object recommendation

Teachers usually have a personal understanding of what “good teaching” means, and as a result of their experience and educationally related domain knowledge, many of them create learning objects (LO) and put them on the web for study use. In fact, most students cannot find the most suitable LO (e.g. learning materials, learning assets, or learning packages) from webs. Consequently, many researchers have focused on developing e-learning systems with personalized learning mechanisms to assist on-line web-based learning and to adaptively provide learning paths. However, although most personalized learning mechanism systems neglect to consider the relationship between learner attributes (e.g. learning style, domain knowledge) and LO’s attributes. Thus, it is not easy for a learner to find an adaptive learning object that reflects his own attributes in relationship to learning object attributes. Therefore, in this paper, based on an ant colony optimization (ACO) algorithm, we proposed an attributes-based ant colony system (AACS) to help learners find an adaptive learning object more effectively. Our paper makes three critical contributions: (1) It presents an attribute-based search mechanism to find adaptive learning objects effectively; (2) An attributes-ant algorithm was proposed; (3) An adaptive learning rule was developed to identify how learners with different attributes may locate learning objects which have a higher probability of being useful and suitable; (4) A web-based learning portal was created for learners to find the learning objects more effectively.     

Haptic modules for palpatory diagnosis training of medical students

We have developed and evaluated a novel tool based on haptics and virtual reality technology for augmenting the teaching of palpatory diagnosis. This novel tool can act as an automated expert and an animated textbook to illuminate palpatory diagnosis concepts by touch on a laptop PC and by using affordable haptic interfaces that can be housed in a medical student resource library. It can be used for unlimited student practice for improving skills from Osteopathic Manipulative Medicine laboratory and also as a repeatable and objective measure of palpatory skill to track student progress. The system was evaluated by 22 osteopathic medical students (16 first- and 6 second-year). The majority of the participating students (>90.9 %) thought that future practice with the system may help them develop their palpatory skills. The majority (>77.3 %) of the students also thought that the instructions on the module screens were clear. When the students were asked about the user interface, most of the students (>86.4 %) responded that it was clear and easy to interpret. Evaluation results also showed that when the students were asked whether they would like to use the modules in the future for training at least 90.9 % of them answered “Yes” or “Maybe.” The achievement of purpose ratings for individual modules changed between 6.27 and 8.82 on a 10-point scale. This project has the potential to be extended from osteopathic medicine to allopathic medicine, veterinary medicine, physical therapy, massage therapy, and chiropractic schools.     

Smarter universities: A vision for the fast changing digital era

In this paper we analyze the current situation of education in universities, with particular reference to the European scenario. Specifically, we observe that recent evolutions, such as pervasive networking and other enabling technologies, have been dramatically changing human life, knowledge acquisition, and the way works are performed and people learn. In this societal change, universities must maintain their leading role. Historically, they set trends primarily in education but now they are called to drive the change in other aspects too, such as management, safety, and environment protection. The availability of newer and newer technology reflects on how the relevant processes should be performed in the current fast changing digital era. This leads to the adoption of a variety of smart solutions in university environments to enhance the quality of life and to improve the performances of both teachers and students. Nevertheless, we argue that being smart is not enough for a modern university. In fact, universities should better become smarter. By “smarter university” we mean a place where knowledge is shared between employees, teachers, students, and all stakeholders in a seamless way. In this paper we propose, and discuss a smarter university model, derived from the one designed for the development of smart cities.