846 research outputs found
Using WSDM and Web Service Ping for QoS based Web Service Selection
By using the standard Web Service Distributed Management (WSDM) and Web Service Ping, we introduce a lightweight solution to the Web Service QoS problem. The Management of Web Services (MOWS) part of WSDM is used to publish Web Service's QoS parameters. Management using Web Services (MUWS), the second part of WSDM, is used to monitor IT resources' QoS. Examples are server's QoS, application server's QoS and network's QoS. Web Service Ping can be used as a simple diagnostic tool for Web Service's latency and Web Service's availability across organizational boundaries. Therefore, we propose to introduce a standardized Web Service Ping operation into all Web Services. All QoS data retrieved by using MOWS, MUWS and Web Service Ping, can be used for Web Service selection. We introduced a new Web Service selection architecture, the Delegation Web Service as selector. Compared to Web Service Broker as selector, consumer as selector and QoS enhanced UDDI as selector, the Delegation Web Service as selector offers a better solution for implementing Web Service load balancing and can increase the security of and for Web Services
The TYC Dataset for Understanding Instance-Level Semantics and Motions of Cells in Microstructures
Segmenting cells and tracking their motion over time is a common task in
biomedical applications. However, predicting accurate instance-wise
segmentation and cell motions from microscopy imagery remains a challenging
task. Using microstructured environments for analyzing single cells in a
constant flow of media adds additional complexity. While large-scale labeled
microscopy datasets are available, we are not aware of any large-scale dataset,
including both cells and microstructures. In this paper, we introduce the
trapped yeast cell (TYC) dataset, a novel dataset for understanding
instance-level semantics and motions of cells in microstructures. We release
dense annotated high-resolution brightfield microscopy images, including
about k instance masks. We also release curated video clips composed
of high-resolution microscopy images to facilitate unsupervised
understanding of cell motions and morphology. TYC offers ten times more
instance annotations than the previously largest dataset, including cells and
microstructures. Our effort also exceeds previous attempts in terms of
microstructure variability, resolution, complexity, and capturing device
(microscopy) variability. We facilitate a unified comparison on our novel
dataset by introducing a standardized evaluation strategy. TYC and evaluation
code are publicly available under CC BY 4.0 license.Comment: Accepted at ICCV 2023 Workshop on BioImage Computing. Project page
(with links to the dataset and code):
https://christophreich1996.github.io/tyc_dataset
Lamred : location-aware and privacy preserving multi-layer resource discovery for IoT
The resources in the Internet of Things (IoT) network are distributed among different parts of the network. Considering huge number of IoT resources, the task of discovering them is challenging. While registering them in a centralized server such as a cloud data center is one possible solution, but due to billions of IoT resources and their limited computation power, the centralized approach leads to some efficiency and security issues. In this paper we proposed a location aware and decentralized multi layer model of resource discovery (LaMRD) in IoT. It allows a resource to be registered publicly or privately, and to be discovered in a decentralized scheme in the IoT network. LaMRD is based on structured peer-to-peer (p2p) scheme and follows the general system trend of fog computing. Our proposed model utilizes Distributed Hash Table (DHT) technology to create a p2p scheme of communication among fog nodes. The resources are registered in LaMRD based on their locations which results in a low added overhead in the registration and discovery processes. LaMRD generates a single overlay and it can be generated without specific organizing entity or location based devices. LaMRD guarantees some important security properties and it showed a lower latency comparing to the cloud based and decentralized resource discovery
Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy
Time-lapse fluorescent microscopy (TLFM) combined with predictive
mathematical modelling is a powerful tool to study the inherently dynamic
processes of life on the single-cell level. Such experiments are costly,
complex and labour intensive. A complimentary approach and a step towards in
silico experimentation, is to synthesise the imagery itself. Here, we propose
Multi-StyleGAN as a descriptive approach to simulate time-lapse fluorescence
microscopy imagery of living cells, based on a past experiment. This novel
generative adversarial network synthesises a multi-domain sequence of
consecutive timesteps. We showcase Multi-StyleGAN on imagery of multiple live
yeast cells in microstructured environments and train on a dataset recorded in
our laboratory. The simulation captures underlying biophysical factors and time
dependencies, such as cell morphology, growth, physical interactions, as well
as the intensity of a fluorescent reporter protein. An immediate application is
to generate additional training and validation data for feature extraction
algorithms or to aid and expedite development of advanced experimental
techniques such as online monitoring or control of cells.
Code and dataset is available at
https://git.rwth-aachen.de/bcs/projects/tp/multi-stylegan.Comment: revised -- accepted to MICCAI 2021. (Tim Prangemeier and Christoph
Reich --- both authors contributed equally
Differentiable JPEG: The Devil is in the Details
JPEG remains one of the most widespread lossy image coding methods. However,
the non-differentiable nature of JPEG restricts the application in deep
learning pipelines. Several differentiable approximations of JPEG have recently
been proposed to address this issue. This paper conducts a comprehensive review
of existing diff. JPEG approaches and identifies critical details that have
been missed by previous methods. To this end, we propose a novel diff. JPEG
approach, overcoming previous limitations. Our approach is differentiable
w.r.t. the input image, the JPEG quality, the quantization tables, and the
color conversion parameters. We evaluate the forward and backward performance
of our diff. JPEG approach against existing methods. Additionally, extensive
ablations are performed to evaluate crucial design choices. Our proposed diff.
JPEG resembles the (non-diff.) reference implementation best, significantly
surpassing the recent-best diff. approach by dB (PSNR) on average. For
strong compression rates, we can even improve PSNR by dB. Strong
adversarial attack results are yielded by our diff. JPEG, demonstrating the
effective gradient approximation. Our code is available at
https://github.com/necla-ml/Diff-JPEG.Comment: Accepted at WACV 2024. Project page:
https://christophreich1996.github.io/differentiable_jpeg
A forensically-enabled IAAS cloud computing architecture
Current cloud architectures do not support digital forensic investigators, nor comply with today’s digital forensics procedures largely due to the dynamic nature of the cloud. Whilst much research has focused upon identifying the problems that are introduced with a cloud-based system, to date there is a significant lack of research on adapting current digital forensic tools and techniques to a cloud environment. Data acquisition is the first and most important process within digital forensics – to ensure data integrity and admissibility. However, access to data and the control of resources in the cloud is still very much provider-dependent and complicated by the very nature of the multi-tenanted operating environment. Thus, investigators have no option but to rely on cloud providers to acquire evidence, assuming they would be willing or are required to by law. Furthermore, the evidence collected by the Cloud Service Providers (CSPs) is still questionable as there is no way to verify the validity of this evidence and whether evidence has already been lost. This paper proposes a forensic acquisition and analysis model that fundamentally shifts responsibility of the data back to the data owner rather than relying upon a third party. In this manner, organisations are free to undertaken investigations at will requiring no intervention or cooperation from the cloud provider. The model aims to provide a richer and complete set of admissible evidence than what current CSPs are able to provide
Magnetic Field Inhomogeneities and Their Influence on Transmission and Background at the KATRIN Main Spectrometer
The goal of the KATRIN experiment is to measure the absolute mass of the electron-antineutrino with a sensitivity of 200 meV by analyzing the shape of the tritium-beta-decay energy spectrum. The energy analysis is done with a large scale MAC-E filter (magnetic adiabatic collimation and electrostatic filter) with a magnetic field of 0.3 mT in the analyzing plane. This work investigates small disturbances of the magnetic field influencing the transmission and background properties of the setup
Ergebnisse der zytoreduktiven Chirurgie und hyperthermen intraperitonealen Chemotherapie in der Behandlung des peritoneal metastasierten Magenkarzinoms
Einleitung: Das peritoneal metastasierte Magenkarzinom hat unter herkömmlicher Therapie mit systemischer Chemotherapie und bestmöglichen unterstützenden Behandlungsmaßnahmen (engl.: best supportive care) eine infauste Prognose. Hierbei werden Überlebenszeiten von 4-6 Monaten im Median erreicht. Bei der Behandlung durch zytoreduktive Chirurgie (CRS) und hypertherme intraperitoneale Chemotherapie (HIPEC) konnte bereits in mehreren Studien gezeigt werden, dass für ausgewählte Patienten Langzeitüberleben erreicht werden kann. Insbesondere das Ausmaß der präoperativen Tumorausdehnung und der nach CRS verbleibende Tumorrest scheinen für das Überleben eine herausragende Bedeutung zu spielen. Standardisierte Auswahlkriterien wurden bisher jedoch nicht etabliert. In der vorgelegten Arbeit werden unsere Erfahrungen mit CRS und HIPEC beim peritoneal metastasiertem Magenkarzinom beleuchtet und Überlebenszeiten sowie das Auftreten von postoperativen Komplikationen in Abhängigkeiten von prognostischen Faktoren untersucht.
Methoden: Die Daten von, den im Zeitraum von 2008 bis 2015 an der Charité Campus Mitte Universitätsmedizin Berlin aufgrund eines peritoneal metastasierten Magenkarzinoms mit CRS und HIPEC behandelten Patienten, wurden gesammelt und retrospektiv analysiert. Die präoperative Bestimmung der Ausdehnung der Metastasierung erfolgte mittels Peritoneal Carcinomatosis Index (PCI). Die nach CRS verbleibende Tumorlast wurde über den Completeness of Cytoreduction Score (CC-Score) ermittelt. Die Klassifikation der postoperativen Mortalität erfolgte nach Clavien-Dindo und die Schätzung der Überlebenszeiten nach Kaplan-Meier. Die statistische Aufarbeitung des Datensatzes erfolgte mit IBM SPSS´Statstics 20.0 (IBM Business Machines Corp. Armonk NY, USA).
Ergebnisse: Wir konnten 47 Patienten in unsere Studie einschließen. Postoperative Komplikationen traten bei 19 Patienten (40 %) auf und es wurde eine mediane Überlebenszeit von 10 (0-60) Monaten erreicht. Das Auftreten von Komplikationen zeigte sich abhängig von der Anzahl der Organresektionen und Anastomosen sowie der OP-Zeit. Einfluss auf das Überleben hatten postoperative Komplikationen, das OP Jahr, das pT-Stadium und der PCI. Der PCI und das Auftreten von postoperativen Komplikationen konnten in einer multivariaten Analyse als hochgradig signifikante Einflussfaktoren für das Gesamtüberleben bestätigt werden. Patienten bei denen keine postoperativen Komplikationen auftraten, hatten einen Überlebensvorteil von 16 (0-60) gegenüber 9 (0-24) Monaten (p=0,012). Patienten mit einem PCI≤13 hatten mit 13 (0-60) Monaten eine beinahe doppelt so lange mediane Überlebenszeit wie Patienten welche einen PCI>13 aufwiesen und nur 7 (0-38) Monate überlebten (p=0,018).
Schlussfolgerung: Da für ausgewählte Patienten auch beim peritoneal metastasierten Magenkarzinom Langzeitüberleben nach der Therapie mit CRS und HIPEC erreicht werden kann, müssen international vereinheitlichte Auswahlkriterien etabliert werden mit denen diese Patienten ausfindig gemacht werden können. Der hochsignifikante Einfluss des präoperativ bestimmbaren PCI auf das Überleben unserer Patienten bestätigt die Ergebnisse anderer Autoren und sollte als Auswahlkriterium etabliert werden. Introduction: The prognosis of peritoneal metastasis from gastric cancer under therapy
with systemic chemotherapy and best supportive care is poor with median overall
survival of 4-6 months. Long time survival could be achieved for selected patients in
several studies when treated by cytoreductive surgery (CRS) and hyperthermic
intraperitoneal Chemotherapy (HIPEC). The preoperative extent of tumorburden and
the completeness of CRS appear to be the most important factors for survival. No
standardized selection criterias for the therapy with CRS and HIPEC have been
established yet. In this study our experiences with patients with peritoneal metastasized
gastric cancer treated by CRS and HIPEC were analysed. Postoperative complications
and survival and their dependence on prognostic factors were tested.
Methods: Data of patients with peritoneal metastases from gastric cancer who were
treated by CRS and HIPEC at Charité Universitätsmedizin Berlin Campus Mitte from
2008 until 2015 were gathererd and retrospectively analysed. The preoperatively
determined extension of peritoneal metastases was measured by Peritoneal
Carcinomatosis Index (PCI). The postoperative remaining tumorburden was quantified
by the Completness of Cytoreduction Score (CC-Score). The postoperative
complications were classified by Clavien-Dindo and surival was estimated by Kaplan-
Meier. The statistical evaluation of data was ensued by IBMâ SPSS´Statsticsâ 20.0
(IBM Business Machines Corp. Armonk NY, USA).
Results: We could include 47 patients in our study. Median PCI was 10,5 (1-32). In
thirty patients (63,8 %) a CC-Score=0 could be achieved. Postoperative complications
occured in 19 patients (40 %) and a median survival of 10 (0-60) months was achieved.
The occurance of complications was dependant on the amount of organ resections and
anastomosis and duration time of operation. Postoperative complications, the year of
operation, pT stage and PCI had influence on survival. PCI and the occurance of
postoperative complications were confirmed as highly significant influencing factors on
overall survival in multivariate analysis. Patients without complications had a survival
benefit of 16 (0-60) vs. 9 (0-24) months (p=0,012). The survival of patients with PCI≤13
was 13 months (0-60) and therefore almost twice as high as survival of patients with
PCI>13 whose survival was 7 months (0-38) (p=0,018).
Conclusion: Since long term survival can be achieved for selected patients with
peritoneal metastases treated by CRS and HIPEC, international and unified selection
criterias have to be established to identify these patients. The highly significant influence on survival of preoperatively determinable PCI, also confirmed by other
authors, should be established as selection criteria
An Instance Segmentation Dataset of Yeast Cells in Microstructures
Extracting single-cell information from microscopy data requires accurate
instance-wise segmentations. Obtaining pixel-wise segmentations from microscopy
imagery remains a challenging task, especially with the added complexity of
microstructured environments. This paper presents a novel dataset for
segmenting yeast cells in microstructures. We offer pixel-wise instance
segmentation labels for both cells and trap microstructures. In total, we
release 493 densely annotated microscopy images. To facilitate a unified
comparison between novel segmentation algorithms, we propose a standardized
evaluation strategy for our dataset. The aim of the dataset and evaluation
strategy is to facilitate the development of new cell segmentation approaches.
The dataset is publicly available at
https://christophreich1996.github.io/yeast_in_microstructures_dataset/ .Comment: IEEE EMBC 2023 (in press), Christoph Reich and Tim Prangemeier - both
authors contributed equall
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