Kirandziska, Vesna
Preferred name
Kirandziska, Vesna
Official Name
Kirandziska, Vesna
Main Affiliation
Email
vesna.kirandziska@finki.ukim.mk
13 results
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Item type:Publication, Behavior Models of Emotion-Featured Robots: A Survey(Springer Science and Business Media LLC, 2020-07-08); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Assistive robotics as therapy for autistic children(2016) ;Tanevska, Ana; Assistive technology encompasses in its domain all rehabilitative tech, be it software or hardware, that works on improving quality of life for physically and mentally disabled people. Unlike creating assistive devices for people with physical disabilities, developing treatments for people with cognitive impairments is a very difficult task, due to the fact that cognitive disorders manifest differently from one group of people to another. One such specific group are children with Autism Spectrum Disorder (ASD). ASD is a condition that affects normal socio-emotional development in early childhood and causes difficulties with learning. One kind of treatment that has proven itself as particularly effective for young autistic children is robotassisted therapy (RAT), which involves a robotic element – this can be robotic toys, robotic platforms, humanoid robots – with the purpose of making the learning process easier for these children. This paper elaborates on several different approaches for implementing robots in autism therapy, gives an overview on several RAT studies done in the world, and presents our work done in implementing a NAO humanoid robot in a research experiment with children on the autism spectrum. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Comparing emotion recognition from voice and facial data using time invariant features(2016-03-02); ; Madevska Bogdanova, AnaThe problem of emotion recognition is a challenging problem. It is still an open problem from the aspect of both intelligent systems and psychology. In this paper, both voice features and facial features are used for building an emotion recognition system. A Support Vector Machine classifiers are built by using raw data from video recordings. In this paper, the results obtained for the emotion recognition are given, and a discussion about the validity and the expressiveness of different emotions is presented. A comparison between the classifiers build from facial data only, voice data only and from the combination of both data is made here. The need for a better combination of the information from facial expression and voice data is argued. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Effects and usage of emotion aware robots that perceive human voice(2013-07-22); Emotion perception is the process of perceiving other people’s emotions based on their facial expression, movement, voice and other biosignals they emit. But, because of the vague definition of emotions, their function and manifestation are not strictly defined. Consequently, in Information Computer Technology (ICT) automatic emotion perception is hard problem that is still open. The questions that arise are weather there can exist an automatic calculation of people’s emotions, how precise they are and witch are the most important human features that can be included in the perception process. Here, evidence that the robot emotion perception resembles the human emotion perception will be given. This paper also presents a discussion about our and similar robots that classify human emotions in positively and negatively evaluated emotions. Making robots that perceive emotions arises many social and psychological questions. Some of these questions are considered in this paper. Evidence that the robot emotion perception resembles the human emotion perception will be given. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Robot-assisted therapy: considering the social and ethical aspects when working with autistic children(2016) ;Tanevska, Ana; When implementing robot-assisted therapy (RAT) for children with autism it is not enough to simply plan for the technology that will be used. This paper elaborates on the social and ethical implications that need to be taken into consideration when working with autistic children. A particular set of protocols is presented, and we discuss how we implemented those steps in an autism study with the NAO humanoid robot. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Lab assessments in undergraduate course in Compilers for students with no prior knowledge in assembly(IEEE, 2014-05-26); ; ; Compilers is an important course in the curricula of Computer Science Faculties. A problem that we have faced while organizing the course at our institution was lack of prior knowledge of some students in the area of assembly programming and microprocessors. Due to the fact that the number of classes for the course was limited, we were not able to teach the necessary material on assembly programming. In this paper we present our idea for the lab project to be done by students through the course, that should enable them to grasp all necessary concepts in Compilers without a need of assembly programming. The idea was tested a few of years in a row, and most of the students managed to finish the project, and achieved better results in the final exams. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A concept for building more humanlike social robots and their ethical consequence(2014-07-01); Human – computer interaction is a vast area of research that targets two very different groups of subjects: the humans as a biology originated group, and the machines – as human made products. One specific part of this interaction is the human – robot interaction. This paper discusses the challenges that arise in the human – robot interaction. Special accent is put on creating social robots, in particular on creating more human-like empathic robots. Here a concept for creating such robots is proposed, where data from human-human interaction is used for feature selection. As an example of the stated concept a robot has been added the ability to perceive human emotions. In this research the robot uses human sound data as source for perceiving human emotions. Additionally, a biologically driven custom algorithm is used in this research for emotion evaluation classification. The proposed approach is analyzed and evaluated using experimental results done from real data. Also, the influence of the emotion aware robots on humans is explained in more detail. At the end, a discussion about the importance of sharing life with these emotion aware robots today and in the future is argued. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Comparison of emotion evaluation perception using human voice signals of robots and humans(2013); Emotion perception is the process of perceiving other people’s emotions. It can be based on their facial expression, movement, voice and other biosignals people emit. The evaluation of human’s emotion is one characteristic of emotions. One of the research areas in Robotics is adapting humanistic behavior in robots. Today many robots are constructed. Some of them can even perceive emotions. In this paper a custom built emotion aware robot that perceives emotion evaluation is used to investigate the similarity and differences of the robot's and human's emotion perception. Voice signals from real human were recorded and the information for the emotion evaluation was obtained from our robot, but also from a set of human evaluators. This paper presents the results of the experiments done. The experimental results show the difficulty of the problem of emotion evaluation perception in general. The significance of human voice signals in emotion evaluation is also investigated. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Improved MDS-based algorithm for nodes localization in wireless sensor networks(IEEE, 2013-07-01) ;Risteska Stojkoska, BiljanaWith the recent development of technology, wireless sensor networks (WSN) are becoming an important part of many applications. Knowing the exact location of each sensor in the network is very important issue. Therefore, the localization problem is a growing field of interest. Adding GPS receivers to each sensor node is costly solution and inapplicable on nodes with limited resources. Additionally, it is not suitable for indoor environments. In this paper, we propose an algorithm for nodes localization in WNS based on multidimensional scaling (MDS) technique. Our approach improves MDS by distance matrix refinement. Using extensive simulations we investigated in details our approach regarding different network topologies, various network parameters and performance issues. The results from simulations show that our improved MDS (IMDS) algorithm outperforms well known MDS-MAP algorithm [1] in terms of accuracy.
