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Body language of robot arms, have rarely been explored as a medium of conveying robot intentions. An explorative study was done focusing on two questions: one, if robot arm postures can convey robot intentions, and two, if participants coming in contact with this robot arm for the first time can associate any meaning to the postures without watching the robot in action, or working with it. Thirty...
We propose a high capacity reversible ternary embedding-watermarking algorithm based on a modification of full-context-prediction-errors (MFCPE) wherein the binary bit stream is converted to the ternary stream then error histogram shifting is utilized to embed the ternary stream. Unlike the existing predictor methods, we provide a full context prediction with a modification of each pixel at most by...
Similarity metric and distance metric are widely used in many research areas and applications. In this paper, for a given similarity metric, we will introduce a family of distance metrics of Minkowski type. We will then show general solutions to construct normalized similarity metric and normalized distance metric from a similarity metric and a distance metric. Applying the general solutions to a...
In this paper, we propose a new approach based on belief functions for multi-criteria decision-making (MCDM) support which is inspired by the technique for order preference by similarity to ideal solution (TOPSIS). This new approach, called BF-TOPSIS (Belief Function based TOPSIS), includes four distinct methods with different computational complexities. BF-TOPSIS offers the advantage of avoiding...
Bayesian Networks provide an established approach to classification of objects in various types of activities. These range from technical via medical to economical applications. Heterogeneous sources provide observed declarations, which are evaluated by calculating the probabilities of resulting classes based on an underlying Bayesian Network model. Applying this classification process at different...
The complex source (CS) approach has long been used to obtain exact and approximate solutions for problems of beam-waves diffraction. However, the straightforward CS formulation may be applied only when the incident beam is diverging as it hits the scatterer, but not when it is converging. The present paper extends the CS method in the context of beam diffraction by wedges and cones, and present somewhat...
This paper tackles the object assignment problem in a multiple target tracking context. Multi-target association consists in defining at each time step the relations between two sets. One set is related to the newly detected objects and the other to the already known ones. In this paper, the Dempster-Shafer theory, also known as belief functions is used. The contribution lies in the development of...
In this paper, we consider the key dimensions of learning analytics applications in adaptive learning. We then review recent publications on the topic and map them to the dimensions of the reference model. Twenty one peer-reviewed articles are identified and analyzed. The findings of the review suggest that interesting work has been carried out during the last years on the topic. Yet, there is a clear...
Retrieving, recalling, processing, organising and storing information are integral parts of the human information seeking process and many socio-cognitive theories suggest that the approach of the seekers is closely related to their cognitive processing styles and abilities. The aim of this study is to investigate the impact of wholistic-analytic cognitive style to players' behaviour in the context...
Improving the accessibility to the information stored in the Electronic Health Records (EHRs) and the usability of the Hospital Information Systems (HISs), is an important issue to solve currently, due to the great impact that they have in the quality of the attention given to the patients. Having the most useful information for the present assistance act easily and quickly available means better...
Situation identification has become a major issue for situation-aware ubiquitous learning environments. The identification process aims to infer learner's situation by aggregating detected context information pieces. Most recent situation identification approaches are basically focused on crisp ontological modelling and reasoning. Given the fact that crisp ontology is not able to deal with context...
People often under or over-estimate their performance on interactive learning experiences with virtual agents, especially when it comes to interpersonal skills such as empathy. To generate more accurate self-assessment of performance, we propose the use of in-action reflective learning opportunities during interactive learning experiences with virtual agents. We conducted a user study in which third-year...
A multi-context mechanism is newly reported to solve large-scale optimization problems (separable and nonseparable) within a general cooperative co-evolution (CC) framework. The basic CC is widely used to decompose a large-scale problem into several less difficult subproblems. When any two subproblems have no interaction, for example, when the problem is separable, the basic CC is effective. However,...
Preference modelling based on Atanassov's intuitionistic fuzzy sets are gaining increasing relevance in the field of group decision making as they provide experts with a flexible and simple tool to express their preferences on a set of alternative options, while allowing, at the same time, to accommodate experts' preference uncertainty, which is inherent to all decision making processes. A key issue...
Formal Concept Analysis (FCA) and its fuzzy extension have been widely used to arrange data into a lattice that is an effective data structure useful to address several aims, such as: data mining, ontology learning and merging, and so on. In literature it is possible to distinguish two main approaches to address fuzzy FCA implementation: the one-sided threshold and the fuzzy closure one. This work...
In many applications domains, time modeling has a fundamental role. Allen temporal relations are one of the most used and known formalisms for modeling and handling temporal data. However, classical Allen relations deal only with crisp time information, but time is often subjective and fuzzy. This paper discusses a disjunctive view of temporal relations between fuzzy time intervals. This approach...
Ordinal input variables are common in many supervised and unsupervised machine learning problems. We focus on ordinal classification problems, where the target variable is also categorical and ordinal. In order to represent categorical input variables for measuring distances or applying continuous mapping functions, they have to be transformed to numeric values. This paper evaluates five different...
Masses of sensors, actuators are being deployed in our daily environments to provide innovative services for such spaces as parking lots, buildings,, railway networks. Yet, to realize the full potentials of these sensor network infrastructures, services need to be developed. Service development raises a number of challenges due to existing approaches that are often low level, network/hardware-centric...
Mobile devices are increasingly becoming a melting pot of different types of data ranging from sensitive corporate documents to commercial media to personal content produced and shared via online social networks. While it is desirable for such diverse content to be accessible from the same device via a unified user experience and through a rich plethora of mobile apps, ensuring that this data remains...
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