Model-Checking Assisted Protocol Design for Ultra-reliable Low-Latency Wireless Networks

This file was created by the TYPO3 extension bib --- Timezone: CEST Creation date: 2024-09-08 Creation time: 03-11-58 --- Number of references 11 inproceedings DombrowskiSRDS16 Model-Checking Assisted Protocol Design for Ultra-reliable Low-Latency Wireless Networks 2016 9 27 307--316 fault tolerance;formal verification;protocols;wireless channels;EchoRing protocol;fault-tolerant methods;formal model-based verification;model-checking assisted protocol;probabilistic model checking;reliability constraints;safety-critical industrial applications;salient features;token loss;token-based system;ultrareliable low-latency wireless networks;unprecedented latency;wireless networking community;wireless protocols;wireless token-passing systems;Automata;Model checking;Payloads;Probabilistic logic;Protocols;Reliability;Wireless communication;Model checking;Probabilistic timed automata;Token passing;Wireless Industrial Networks;tool-assisted protocol design;validation cps,hodrian http://ieeexplore.ieee.org/document/7794360/ Proc. of IEEE 35th Symposium on Reliable Distributed Systems IEEE Budapest, Hungary IEEE 35th Symposium on Reliable Distributed Systems (SRDS) 10.1109/SRDS.2016.048 1 ChristianDombrowski SebastianJunges Joost-PieterKatoen JamesGross inproceedings 2016-ackermann-healthcom-eeg-emotion EEG-based Automatic Emotion Recognition: Feature Extraction, Selection and Classification Methods 2016 9 14 159--164 Automatic emotion recognition is an interdisciplinary research field which deals with the algorithmic detection of human affect, e.g. anger or sadness, from a variety of sources, such as speech or facial gestures. Apart from the obvious usage for industry applications in human-robot interaction, acquiring the emotional state of a person automatically also is of great potential for the health domain, especially in psychology and psychiatry. Here, evaluation of human emotion is often done using oral feedback or questionnaires during doctor-patient sessions. However, this can be perceived as intrusive by the patient. Furthermore, the evaluation can only be done in a non-continuous manner, e.g. once a week during therapy sessions. In contrast, using automatic emotion detection, the affect state of a person can be evaluated in a continuous non-intrusive manner, for example to detect early on-sets of depression. An additional benefit of automatic emotion recognition is the objectivity of such an approach, which is not influenced by the perception of the patient and the doctor. To reach the goal of objectivity, it is important, that the source of the emotion is not easily manipulable, e.g. as in the speech modality. To circumvent this caveat, novel approaches in emotion detection research the potential of using physiological measures, such as galvanic skin sensors or pulse meters. In this paper we outline a way of detecting emotion from brain waves, i.e., EEG data. While EEG allows for a continuous, real-time automatic emotion recognition, it furthermore has the charm of measuring the affect close to the point of emergence: the brain. Using EEG data for emotion detection is nevertheless a challenging task: Which features, EEG channel locations and frequency bands are best suited for is an issue of ongoing research. In this paper we evaluate the use of state of the art feature extraction, feature selection and classification algorithms for EEG emotion classification using data from the de facto standard dataset, DEAP. Moreover, we present results that help choose methods to enhance classification performance while simultaneously reducing computational complexity. /fileadmin/papers/2016/2016-ackermann-healthcom-emorec.pdf http://ieeehealthcom2016.com/ Online IEEE 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom) Munich, Germany 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom) September 14-17, 2016 en 978-1-5090-3370-6 1 PascalAckermann ChristianKohlschein Jó AgilaBitsch Link KlausWehrle SabinaJeschke inproceedings 2016-FICloud-Jakobs Standardisation of e-merging IoT-Applications: Past, Present and a Glimpse into the Future. 2016 8 Online IEEE Proc. International Workshop on Standardising the IoT and its Applications (SITA 2016), 2016, Vienna, Austria. EN 1 KaiJakobs article 2015-cheng-piap-jmu Psychologist in a Pocket: Lexicon Development and Content Validation of a Mobile-Based App for Depression Screening JMIR Mhealth Uhealth 2016 7 20 4 3 e88 piap http://mhealth.jmir.org/2016/3/e88/ http://www.ncbi.nlm.nih.gov/pubmed/27439444 Online en 2291-5222 10.2196/mhealth.5284 1 Paula Glenda FerrerCheng Roann MunozRamos Jó AgilaBitsch Link Stephan MichaelJonas TimIx Portia Lynn QuetulioSee KlausWehrle inproceedings 2016-Jakobs-Sinergie Trust in Open Standardisation?! 2016 6 Online CUEIM Comunicazione srl Management in a Digital World: Decisions, Production, Communication. Proceedings 28th Sinergie Annual Conference. 2016, Udine, Italy EN 1 KaiJakobs proceedings 2016-Jakobs-EURAS Co-opetition and Open Innovation. Proc. 21st EURAS Annual Standardisation Conference, 2016, Montpellier, France 2016 5 Online Mainz EN 978-3-95886-103-9 1 KaiJakobs AnneMione Anne-FrancoiseCutting-Decelle SophieMignon inproceedings 2016-ramos-inpact-lexicon How Do I Say "Sad?" Building a Depression-Lexicon for Psychologist in a Pocket 2016 4 30 1--6 29% Acceptance rate /fileadmin/misc/2016/2016-ramos-inpact-lexicon.pdf http://inpact-psychologyconference.org/2016/conference-program/ Online Clara Pracana and Michael Wang World Institute for Advanced Research and Science

Lisbon, Portugal

Proceedings of the International Psychological Applications Conference and Trends (InPACT 2016) Lisbon, Portugal International Psychological Applications Conference and Trends (InPACT 2016) April 30 -- May 2, 2016 en 978-989-99389-6-0 1 Roann MunozRamos Paula Glenda FerrerCheng Jó AgilaBitsch Link Stephan MichaelJonas inproceedings 2016-ramos-inpact-feeling-meh Feeling Meh: Psychologist in a pocket app for depression screening 2016 4 30 1--4 29% Acceptance rate /fileadmin/misc/2016/2016-ramos-inpact-feeling-meh.pdf http://inpact-psychologyconference.org/2016/conference-program/ Online Clara Pracana and Michael Wang World Institute for Advanced Research and Science

Lisbon, Portugal

Proceedings of the International Psychological Applications Conference and Trends (InPACT 2016) Lisbon, Portugal International Psychological Applications Conference and Trends (InPACT 2016) April 30 -- May 2, 2016 en 978-989-99389-6-0 1 Roann MunozRamos Paula Glenda FerrerCheng Jó AgilaBitsch Link Stephan MichaelJonas article 2015-Jakobs-PIK YOLO oder die Kunst der Internet-Kommunikation PIK – Praxis der Informationsverarbeitung und Kommunikation 2016 38 4 129-133 DE 1865-8342 HelenBolke-Hermanns KaiJakobs book 2016-Jakobs-IGI Effective Standardization Management in Corporate Settings. 2016 IGI Global, Hershey, USA EN 978-1-4666-9737-9 1 KaiJakobs proceedings 2016-Jakobs-SIIT Proc. 9th International Conference on Standardization and Innovation in Information Technology (IEEE SIIT), 2015, Mountain View, USA 2016 IEEE EN 978-1-4673-9532-8 1 KaiJakobs