The Experts below are selected from a list of 119757 Experts worldwide ranked by ideXlab platform
Odej Kao - One of the best experts on this subject based on the ideXlab platform.
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IFTM - Unsupervised Anomaly Detection for Virtualized Network Function Services
2018 IEEE International Conference on Web Services (ICWS), 2018Co-Authors: Florian Schmidt, Vincent Hennig, Anton Gulenko, Marcel Wallschläger, Alexander Acker, Feng Liu, Odej KaoAbstract:Telecommunication system providers move their IP multimedia subsystems to virtualized services in the cloud. For such systems, dedicated hardware solutions provided a reliability of 99.999% in the past. Although virtualization offers more cost efficient usage of such services, it comes with higher complexity for providing reliable running software components due to the fragile computation stack. In order to hide the impact of such problematic behaviors, automatic mechanisms may help to detect degraded state anomalies in order to execute remediation actions. This work introduces IFTM as a framework for unsupervised anomaly detection in a distributed environment based on real-time monitoring data. The proposed approach consists of two key concepts using an automatic Identity Function and threshold learning to distinguish between normal and abnormal system behaviors. The evaluation is performed on a testbed running an open source implementation of the IP multimedia subsystem (Clearwater) executed on a replicated Openstack cloud environment. Results show the applicability of IFTM with high detection rates (98%) and low number of false alarms.
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ICWS - IFTM - Unsupervised Anomaly Detection for Virtualized Network Function Services
2018 IEEE International Conference on Web Services (ICWS), 2018Co-Authors: Florian Schmidt, Vincent Hennig, Anton Gulenko, Marcel Wallschläger, Alexander Acker, Feng Liu, Odej KaoAbstract:Telecommunication system providers move their IP multimedia subsystems to virtualized services in the cloud. For such systems, dedicated hardware solutions provided a reliability of 99.999% in the past. Although virtualization offers more cost efficient usage of such services, it comes with higher complexity for providing reliable running software components due to the fragile computation stack. In order to hide the impact of such problematic behaviors, automatic mechanisms may help to detect degraded state anomalies in order to execute remediation actions. This work introduces IFTM as a framework for unsupervised anomaly detection in a distributed environment based on real-time monitoring data. The proposed approach consists of two key concepts using an automatic Identity Function and threshold learning to distinguish between normal and abnormal system behaviors. The evaluation is performed on a testbed running an open source implementation of the IP multimedia subsystem (Clearwater) executed on a replicated Openstack cloud environment. Results show the applicability of IFTM with high detection rates (98%) and low number of false alarms.
Florian Schmidt - One of the best experts on this subject based on the ideXlab platform.
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IFTM - Unsupervised Anomaly Detection for Virtualized Network Function Services
2018 IEEE International Conference on Web Services (ICWS), 2018Co-Authors: Florian Schmidt, Vincent Hennig, Anton Gulenko, Marcel Wallschläger, Alexander Acker, Feng Liu, Odej KaoAbstract:Telecommunication system providers move their IP multimedia subsystems to virtualized services in the cloud. For such systems, dedicated hardware solutions provided a reliability of 99.999% in the past. Although virtualization offers more cost efficient usage of such services, it comes with higher complexity for providing reliable running software components due to the fragile computation stack. In order to hide the impact of such problematic behaviors, automatic mechanisms may help to detect degraded state anomalies in order to execute remediation actions. This work introduces IFTM as a framework for unsupervised anomaly detection in a distributed environment based on real-time monitoring data. The proposed approach consists of two key concepts using an automatic Identity Function and threshold learning to distinguish between normal and abnormal system behaviors. The evaluation is performed on a testbed running an open source implementation of the IP multimedia subsystem (Clearwater) executed on a replicated Openstack cloud environment. Results show the applicability of IFTM with high detection rates (98%) and low number of false alarms.
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ICWS - IFTM - Unsupervised Anomaly Detection for Virtualized Network Function Services
2018 IEEE International Conference on Web Services (ICWS), 2018Co-Authors: Florian Schmidt, Vincent Hennig, Anton Gulenko, Marcel Wallschläger, Alexander Acker, Feng Liu, Odej KaoAbstract:Telecommunication system providers move their IP multimedia subsystems to virtualized services in the cloud. For such systems, dedicated hardware solutions provided a reliability of 99.999% in the past. Although virtualization offers more cost efficient usage of such services, it comes with higher complexity for providing reliable running software components due to the fragile computation stack. In order to hide the impact of such problematic behaviors, automatic mechanisms may help to detect degraded state anomalies in order to execute remediation actions. This work introduces IFTM as a framework for unsupervised anomaly detection in a distributed environment based on real-time monitoring data. The proposed approach consists of two key concepts using an automatic Identity Function and threshold learning to distinguish between normal and abnormal system behaviors. The evaluation is performed on a testbed running an open source implementation of the IP multimedia subsystem (Clearwater) executed on a replicated Openstack cloud environment. Results show the applicability of IFTM with high detection rates (98%) and low number of false alarms.
Meinrad Busslinger - One of the best experts on this subject based on the ideXlab platform.
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Reporter gene insertions reveal a strictly B lymphoid-specific expression pattern of Pax5 in support of its B cell Identity Function.
Journal of immunology (Baltimore Md. : 1950), 2007Co-Authors: Martin Fuxa, Meinrad BusslingerAbstract:The transcription factor Pax5 is essential for B cell commitment and development. Although the detail Pax5 expression pattern within the hemopoietic system is still largely unknown, we previously reported that Pax5 is monoallelically transcribed in pro-B and mature B cells. In this study, we have investigated the expression of Pax5 at single-cell resolution by inserting a GFP or human Cd2 indicator gene under the translational control of an internal ribosomal entry sequence into the 3' untranslated region of Pax5. These insertions were noninvasive, as B cell development was normal in Pax5(ihCd2/ihCd2) and Pax5(ihGFP/iGFP) mice. Transheterozygous Pax5(ihCd2/iGFP) mice coexpressed GPF and human CD2 at similar levels from pro-B to mature B cells, thus demonstrating biallelic expression of Pax5 at all stages of B cell development. No reporter gene expression could be detected in plasma cells and non-B cells of hemopoietic system. Moreover, the vast majority of common lymphoid progenitors and pre-pro-B in the bone marrow of Pax5(ihGFP/iGFP) mice did not yet express GFP, indicating that Pax5 expression is fully switched on only during the transition form uncommitted pre-pro-B cells to committed pro-B cells. Hence, the transcriptional initiation and B cell-specific expression of Pax5 is entirely consistent with its B cell lineage commitment Function.
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Reporter Gene Insertions Reveal a Strictly B Lymphoid-Specific Expression Pattern of Pax5 in Support of Its B Cell Identity Function
Journal of Immunology, 2007Co-Authors: Martin Fuxa, Meinrad BusslingerAbstract:The transcription factor Pax5 is essential for B cell commitment and development. Although the detailed Pax5 expression pattern within the hemopoietic system is still largely unknown, we previously reported that Pax5 is monoallelically transcribed in pro-B and mature B cells. In this study, we have investigated the expression of Pax5 at single-cell resolution by inserting a GFP or human Cd2 indicator gene under the translational control of an internal ribosomal entry sequence into the 3′ untranslated region of Pax5 . These insertions were noninvasive, as B cell development was normal in Pax5 ihCd2 / ihCd2 and Pax5 iGFP / iGFP mice. Transheterozygous Pax5 ihCd2 / iGFP mice coexpressed GFP and human CD2 at similar levels from pro-B to mature B cells, thus demonstrating biallelic expression of Pax5 at all stages of B cell development. No reporter gene expression could be detected in plasma cells and non-B cells of the hemopoietic system. Moreover, the vast majority of common lymphoid progenitors and pre-pro-B cells in the bone marrow of Pax5 iGFP / iGFP mice did not yet express GFP, indicating that Pax5 expression is fully switched on only during the transition from uncommitted pre-pro-B cells to committed pro-B cells. Hence, the transcriptional initiation and B cell-specific expression of Pax5 is entirely consistent with its B cell lineage commitment Function.
Xiao-rong Peng - One of the best experts on this subject based on the ideXlab platform.
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Mature Human White Adipocytes Cultured under Membranes Maintain Identity, Function, and Can Transdifferentiate into Brown-like Adipocytes
Cell Reports, 2019Co-Authors: Matthew J. Harms, Sunjae Lee, Cheng Zhang, Bengt Kull, Stefan Hallén, Anders Thorell, Ida Alexandersson, Carolina E. Hagberg, Xiao-rong PengAbstract:Mature Human White Adipocytes Cultured under Membranes Maintain Identity, Function, and Can Transdifferentiate into Brown-like Adipocytes
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Mature Human White Adipocytes Cultured under Membranes Maintain Identity, Function, and Can Transdifferentiate into Brown-like Adipocytes
Elsevier, 2019Co-Authors: Matthew J. Harms, Sunjae Lee, Cheng Zhang, Bengt Kull, Stefan Hallén, Anders Thorell, Ida Alexandersson, Carolina E. Hagberg, Xiao-rong PengAbstract:Summary: White adipose tissue (WAT) is a central factor in the development of type 2 diabetes, but there is a paucity of translational models to study mature adipocytes. We describe a method for the culture of mature white adipocytes under a permeable membrane. Compared to existing culture methods, MAAC (membrane mature adipocyte aggregate cultures) better maintain adipogenic gene expression, do not dedifferentiate, display reduced hypoxia, and remain Functional after long-term culture. Subcutaneous and visceral adipocytes cultured as MAAC retain depot-specific gene expression, and adipocytes from both lean and obese patients can be cultured. Importantly, we show that rosiglitazone treatment or PGC1α overexpression in mature white adipocytes induces a brown fat transcriptional program, providing direct evidence that human adipocytes can transdifferentiate into brown-like adipocytes. Together, these data show that MAAC are a versatile tool for studying phenotypic changes of mature adipocytes and provide an improved translational model for drug development. : Mature adipocytes are notoriously difficult to culture. Here, Harms et al. describe a robust method for the long-term culture of mature white adipocytes under permeable membranes, which preserves adipocyte Identity and Function. Using this approach, they also show that human mature white adipocytes can transdifferentiate into brown-like adipocytes. Keywords: adipocyte, white adipose, WAT, brown adipose, BAT, transdifferentiation, UCP1, culture, MAA
Vincent Hennig - One of the best experts on this subject based on the ideXlab platform.
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IFTM - Unsupervised Anomaly Detection for Virtualized Network Function Services
2018 IEEE International Conference on Web Services (ICWS), 2018Co-Authors: Florian Schmidt, Vincent Hennig, Anton Gulenko, Marcel Wallschläger, Alexander Acker, Feng Liu, Odej KaoAbstract:Telecommunication system providers move their IP multimedia subsystems to virtualized services in the cloud. For such systems, dedicated hardware solutions provided a reliability of 99.999% in the past. Although virtualization offers more cost efficient usage of such services, it comes with higher complexity for providing reliable running software components due to the fragile computation stack. In order to hide the impact of such problematic behaviors, automatic mechanisms may help to detect degraded state anomalies in order to execute remediation actions. This work introduces IFTM as a framework for unsupervised anomaly detection in a distributed environment based on real-time monitoring data. The proposed approach consists of two key concepts using an automatic Identity Function and threshold learning to distinguish between normal and abnormal system behaviors. The evaluation is performed on a testbed running an open source implementation of the IP multimedia subsystem (Clearwater) executed on a replicated Openstack cloud environment. Results show the applicability of IFTM with high detection rates (98%) and low number of false alarms.
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ICWS - IFTM - Unsupervised Anomaly Detection for Virtualized Network Function Services
2018 IEEE International Conference on Web Services (ICWS), 2018Co-Authors: Florian Schmidt, Vincent Hennig, Anton Gulenko, Marcel Wallschläger, Alexander Acker, Feng Liu, Odej KaoAbstract:Telecommunication system providers move their IP multimedia subsystems to virtualized services in the cloud. For such systems, dedicated hardware solutions provided a reliability of 99.999% in the past. Although virtualization offers more cost efficient usage of such services, it comes with higher complexity for providing reliable running software components due to the fragile computation stack. In order to hide the impact of such problematic behaviors, automatic mechanisms may help to detect degraded state anomalies in order to execute remediation actions. This work introduces IFTM as a framework for unsupervised anomaly detection in a distributed environment based on real-time monitoring data. The proposed approach consists of two key concepts using an automatic Identity Function and threshold learning to distinguish between normal and abnormal system behaviors. The evaluation is performed on a testbed running an open source implementation of the IP multimedia subsystem (Clearwater) executed on a replicated Openstack cloud environment. Results show the applicability of IFTM with high detection rates (98%) and low number of false alarms.
