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Subject: classificationWoS Q: Q3

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    Article
    Citation - WoS: 7
    Citation - Scopus: 7
    Classification of Intermediate and Novice Surgeons' Skill Assessment Through Performance Metrics
    (Sage Publications inc, 2019) Topalli, Damla; Cagiltay, Nergiz Ercil
    Background. Endoscopic surgeries have become an alternative for open procedures whenever possible. For such types of operations, surgeons are required to gain several skills, whose development needs hands-on practice. Accordingly, gaining these skills today is a challenge for surgical education programs. Despite the development of several technology-enhanced training environments, there are still problems to better integrate these technologies into educational programs. For an appropriate integration, it is critical to assess the skill levels and adapt the training content according to the trainees' requirements. In the literature, there exist several methods for assessing these skill levels. However, there are still problems in practice for objective and repetitive assessment. Methods. The present study aims to estimate the skill levels of participants in surgical training programs in an objective manner by collecting experimental data from residents in an endoscopic surgical simulation environment and gathering performance metrics. Results. It is shown that, by comparing the results of a number of classification algorithms for the best accuracy estimation and feature set, the "novice" and "intermediate" skill levels can be estimated with an accuracy of 86%. Conclusions. The outcomes help surgical educators and instructional system designers to better assess the skill levels of the trainees and guide them accordingly. In addition, objective assessments as highlighted in this study can be beneficial when designing technology-enhanced adaptive learning environments.
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    Article
    Citation - WoS: 10
    Citation - Scopus: 15
    An Rfid Based Indoor Tracking Method for Navigating Visually Impaired People
    (Tubitak Scientific & Technological Research Council Turkey, 2010) Oktem, Rusen; Aydin, Elif
    This paper tackles the RFID based tracking problem in an obscured indoor environment. The proposed solution is an integral part of a navigation aid for guiding visually impaired people in a store. It uses RF signal strengths and is based on the Bayes Decision Theory. An observation vector is formed by received radio signal strength indication values, transmitted from three transmitters at distinct frequencies in the UHF band. The indoor area is divided into square grids, where each grid is considered as a class. The problem of tracking is expressed as classifying the observed radio signal strengths to the most likely class. A classification rule is formulated by incorporating a priori assumptions appropriate for the studied model. The proposed approach is tested in a laboratory environment. The results prove that the proposed approach is promising in tracking especially when the tracked person is guided by a system.