Acoustic based navigation of cooperative marine robots with advanced filter techniques. - In: IFAC-PapersOnLine, ISSN 2405-8963, Bd. 49 (2016), 23, S. 335-340
http://dx.doi.org/10.1016/j.ifacol.2016.10.426
Validation study on cardiac output and index determination in impendence cardiography on postoperative cardiac patients in critical care. - In: Proceedings of 2016 International Conference on Robotics, Automation and Sciences - ICORAS 2016, (2016), insges. 5 S.
https://doi.org/10.1109/ICORAS.2016.7872620
The correlation of features in detecting cardiovascular vulnerable plaque. - In: Proceedings of 2016 International Conference on Robotics, Automation and Sciences - ICORAS 2016, (2016), insges. 4 S.
https://doi.org/10.1109/ICORAS.2016.7872621
Automated detection of microaneurysm for fundus images. - In: IEEE-EMBS Conferences on Biomedical Engineering and Sciences, ISBN 978-1-4673-7791-1, (2016), S. 600-605
https://doi.org/10.1109/IECBES.2016.7843520
Aktive Stereoskopie mittels Farbmusterkodierung. - In: 22. Workshop Farbbildverarbeitung, (2016), S. 183-196
Multispektraler CMOS-Sensor und dessen Eignungsbewertung für Lichtanwendungen. - In: 22. Workshop Farbbildverarbeitung, (2016), S. 9-21
Description of flower colors for image based plant species classification. - In: 22. Workshop Farbbildverarbeitung, (2016), S. 145-154
IoT-aware Context Respectful Counseling Agent. - In: 2016 IEEE International Conference on Systems, Man, and Cybernetics, (2016), S. 004729-004736
Many IT workers suffer from stress in doing their work despite a few counselors to help them. To cope with this, a context respectful counseling agent, CRECA is proposed. For example, CRECA extracts emotional words from clients utterances to detect their changes and provides clients with dialogue summary. To continue the conversation towards clients' further reflection, CRECA is extended. Using self-disclosure type prompts or questions, CRECA restricts or relates client's wishes or goals with eventual and emotional words in dialogue sentences, focusing on emotional backgrounded eventual word. Moreover, CRECA is equipped with a voice generation tool for Japanese language called OpenJtalk. Further, this is enhanced to display an avatar mimicking the natural Japanese conversation behavior called nodding ("unazuki") expressing entire approval necessary for our original CRECA modeling called Rogers counseling, the agent nods at appropriate times during the dialog. Integrating all these features with an Internet connected robot and multiple sensors, this paper totally introduces a concept of IoT-aware Context Respectful Counseling Agent (IoT-aware CRECA), which enables the robot extremely human-counselor-like.
https://doi.org/10.1109/SMC.2016.7844978
SVM integrated case based restarting GA for further improving solar flare prediction. - In: 2016 IEEE International Conference on Systems, Man, and Cybernetics, (2016), S. 004716-004723
Solar activity has various influences on the global environment. Specifically, it may have serious impacts on the Earth such as satellite damage, etc. and power plant failures causing more serious disaster. For a precise forecast of larger scale solar flares causing serious disaster, it is important to improve the space weather forecast, a daily forecast of the solar flare. In our work so far, a machine-learning algorithm called Support Vector Machine (SVM) was used. We extended this technology by integrating Case Based Genetic Algorithm (CBGA) for a more precise forecast. It was shown experimentally that triple mutation rate on the slowdown of evolution in our CBGA improves considerably (e.g. another 5%) more than original mutation rate in the True Skill Statistics TSS. For further obtaining the optimality towards more imbalanced data analysis applicable to the recognition of serious disaster or medical disease, Restart CBGA is proposed with its expected effect. Here GA integrating SVM is restarted using highly optimized but diversified solutions in the case base as initial individuals. Further this restart CBGA is repetitively and evolutionary performed, evolving and maintaining the case base by the result of each (restarted) GA.
https://doi.org/10.1109/SMC.2016.7844976
A dictionary-based sentiment classification method considering subject-predicate relation. - In: 2016 IEEE International Conference on Systems, Man, and Cybernetics, (2016), S. 004217-004222
In order to achieve enhanced credibility of social networking services such as twitter, it is necessary to (1) identify the topic and to (2) check, if the majority of the tweets having the same topic show the same opinion. Therefore, it is indicated to improve the accuracy for analyzing the caller's emotional expression of the "emotional polarity classification", which is used for opinion classification. For this reason, a semantic orientation acquisition technique is proposed, which integrates "another part-of-speech based semantic orientation dictionary" and a subject predicate relationship considered semantic orientation dictionary of phrases (semantic orientation table). As a feature of the proposed method, a semantic orientation of an adjective or predicate due to its greatest impact on identification semantic orientation of each tweet or document is determined. In addition, the dictionary is created by using tweets. Usual methods have problems with the opinion classification (90 % of the tweets are judged negative), but the proposed method has a more correct to negative judge rate of 60%. An integrated semantic orientation dictionary of phrases is used to improve precision of the classification.
https://doi.org/10.1109/SMC.2016.7844894