Monitoring Networked Applications With Incremental Quantile Estimation

Networked applications have software components that reside on different computers. Email, for example, has database, processing, and user interface components that can be distributed across a network and shared by users in different locations or work groups. End-to-end performance and reliability metrics describe the software quality experienced by these groups of users, taking into account all the software components in the pipeline. Each user produces only some of the data needed to understand the quality of the application for the group, so group performance metrics are obtained by combining summary statistics that each end computer periodically (and automatically) sends to a central server. The group quality metrics usually focus on medians and tail quantiles rather than on averages. Distributed quantile estimation is challenging, though, especially when passing large amounts of data around the network solely to compute quality metrics is undesirable. This paper describes an Incremental Quantile (IQ) estimation method that is designed for performance monitoring at arbitrary levels of network aggregation and time resolution when only a limited amount of data can be transferred. Applications to both real and simulated data are provided.Comment: This paper commented in: [arXiv:0708.0317], [arXiv:0708.0336], [arXiv:0708.0338]. Rejoinder in [arXiv:0708.0339]. Published at http://dx.doi.org/10.1214/088342306000000583 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Rejoinder: Monitoring Networked Applications With Incremental Quantile Estimation

Rejoinder: Monitoring Networked Applications With Incremental Quantile Estimation [arXiv:0708.0302]Comment: Published at http://dx.doi.org/10.1214/088342306000000592 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Transitions in the morphological features, habitat use, and diet of young-of-the-year goosefish (Lophius americanus)

This study was designed to improve our understanding of transitions in the early life history and the distribution, habitat use, and diets for young-of-the-year (YOY) goosefish (Lophius americanus) and, as a result, their role in northeastern U.S. continental shelf ecosystems. Pelagic juveniles (>12 to ca. 50 mm total length [TL]) were distributed over most portions of the continental shelf in the Middle Atlantic Bight, Georges Bank, and into the Gulf of Maine. Most individuals settled by 50−85 mm TL and reached approximately 60−120 mm TL by one year of age. Pelagic YOY fed on chaetognaths, hyperiid amphipods, calanoid copepods, and ostracods, and benthic YOY had a varied diet of fishes and benthic crustaceans. Goosefish are widely scattered on the continental shelf in the Middle Atlantic Bight during their early life history and once settled, are habitat generalists, and thus play a role in many continental shelf habi

Adding Contextual Information to Intrusion Detection Systems Using Fuzzy Cognitive Maps

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.In the last few years there has been considerable increase in the efficiency of Intrusion Detection Systems (IDSs). However, networks are still the victim of attacks. As the complexity of these attacks keeps increasing, new and more robust detection mechanisms need to be developed. The next generation of IDSs should be designed incorporating reasoning engines supported by contextual information about the network, cognitive information and situational awareness to improve their detection results. In this paper, we propose the use of a Fuzzy Cognitive Map (FCM) in conjunction with an IDS to incorporate contextual information into the detection process. We have evaluated the use of FCMs to adjust the Basic Probability Assignment (BPA) values defined prior to the data fusion process, which is crucial for the IDS that we have developed. The experimental results that we present verify that FCMs can improve the efficiency of our IDS by reducing the number of false alarms, while not affecting the number of correct detections

Using the Pattern-of-Life in Networks to Improve the Effectiveness of Intrusion Detection Systems

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.As the complexity of cyber-attacks keeps increasing, new and more robust detection mechanisms need to be developed. The next generation of Intrusion Detection Systems (IDSs) should be able to adapt their detection characteristics based not only on the measureable network traffic, but also on the available high- level information related to the protected network to improve their detection results. We make use of the Pattern-of-Life (PoL) of a network as the main source of high-level information, which is correlated with the time of the day and the usage of the network resources. We propose the use of a Fuzzy Cognitive Map (FCM) to incorporate the PoL into the detection process. The main aim of this work is to evidence the improved the detection performance of an IDS using an FCM to leverage on network related contextual information. The results that we present verify that the proposed method improves the effectiveness of our IDS by reducing the total number of false alarms; providing an improvement of 9.68% when all the considered metrics are combined and a peak improvement of up to 35.64%, depending on particular metric combination

Predicting the movements of permanently installed electrodes on an active landslide using time-lapse geoelectrical resistivity data only

If electrodes move during geoelectrical resistivity monitoring and their new positions are not incorporated in the inversion, then the resulting tomographic images exhibit artefacts that can obscure genuine time-lapse resistivity changes in the subsurface. The effects of electrode movements on time-lapse resistivity tomography are investigated using a simple analytical model and real data. The correspondence between the model and the data is sufficiently good to be able to predict the effects of electrode movements with reasonable accuracy. For the linear electrode arrays and 2D inversions under consideration, the data are much more sensitive to longitudinal than transverse or vertical movements. Consequently the model can be used to invert the longitudinal offsets of the electrodes from their known baseline positions using only the time-lapse ratios of the apparent resistivity data. The example datasets are taken from a permanently installed electrode array on an active lobe of a landslide. Using two sets with different levels of noise and subsurface resistivity changes, it is found that the electrode positions can be recovered to an accuracy of 4 % of the baseline electrode spacing. This is sufficient to correct the artefacts in the resistivity images, and provides for the possibility of monitoring the movement of the landslide and its internal hydraulic processes simultaneously using electrical resistivity tomography only

Hypothalamic Vitamin D Improves Glucose Homeostasis and Reduces Weight

Despite clear associations between vitamin D deficiency and obesity and/or type 2 diabetes, a causal relationship is not established. Vitamin D receptors (VDRs) are found within multiple tissues, including the brain. Given the importance of the brain in controlling both glucose levels and body weight, we hypothesized that activation of central VDR links vitamin D to the regulation of glucose and energy homeostasis. Indeed, we found that small doses of active vitamin D, 1α,25-dihydroxyvitamin D3 (1,25D3) (calcitriol), into the third ventricle of the brain improved glucose tolerance and markedly increased hepatic insulin sensitivity, an effect that is dependent upon VDR within the paraventricular nucleus of the hypothalamus. In addition, chronic central administration of 1,25D3 dramatically decreased body weight by lowering food intake in obese rodents. Our data indicate that 1,25D3-mediated changes in food intake occur through action within the arcuate nucleus. We found that VDR colocalized with and activated key appetite-regulating neurons in the arcuate, namely proopiomelanocortin neurons. Together, these findings define a novel pathway for vitamin D regulation of metabolism with unique and divergent roles for central nervous system VDR signaling. Specifically, our data suggest that vitamin D regulates glucose homeostasis via the paraventricular nuclei and energy homeostasis via the arcuate nuclei

Dissemination and implementation science training needs: Insights from practitioners and researchers

INTRODUCTION: Dissemination and implementation research training has great potential to improve the impact and reach of health-related research; however, research training needs from the end user perspective are unknown. This paper identifies and prioritizes dissemination and implementation research training needs. METHODS: A diverse sample of researchers, practitioners, and policymakers was invited to participate in Concept Mapping in 2014–2015. Phase 1 (Brainstorming) gathered participants' responses to the prompt: To improve the impact of research evidence in practice and policy settings, a skill in which researchers need more training is… The resulting statement list was edited and included subsequent phases. Phase 2 (Sorting) asked participants to sort each statement into conceptual piles. In Phase 3 (Rating), participants rated the difficulty and importance of incorporating each statement into a training curriculum. A multidisciplinary team synthesized and interpreted the results in 2015–2016. RESULTS: During Brainstorming, 60 researchers and 60 practitioners/policymakers contributed 274 unique statements. Twenty-nine researchers and 16 practitioners completed sorting and rating. Nine concept clusters were identified: Communicating Research Findings, Improve Practice Partnerships, Make Research More Relevant, Strengthen Communication Skills, Develop Research Methods and Measures, Consider and Enhance Fit, Build Capacity for Research, and Understand Multilevel Context. Though researchers and practitioners had high agreement about importance (r =0.93) and difficulty (r =0.80), ratings differed for several clusters (e.g., Build Capacity for Research). CONCLUSIONS: Including researcher and practitioner perspectives in competency development for dissemination and implementation research identifies skills and capacities needed to conduct and communicate contextualized, meaningful, and relevant research

Early surgery versus initial conservative treatment in patients with traumatic intracerebral haemorrhage [STITCH(Trauma)] : the first randomized trial

Acknowledgements This project was funded by the NIHR Health Technology Assessment programme (project number 07/37/16). The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the HTA programme, NIHR, NHS or the Department of Health.Peer reviewedPublisher PD

Training scholars in dissemination and implementation research for cancer prevention and control: A mentored approach

Abstract Background As the field of D&I (dissemination and implementation) science grows to meet the need for more effective and timely applications of research findings in routine practice, the demand for formalized training programs has increased concurrently. The Mentored Training for Dissemination and Implementation Research in Cancer (MT-DIRC) Program aims to build capacity in the cancer control D&I research workforce, especially among early career researchers. This paper outlines the various components of the program and reports results of systematic evaluations to ascertain its effectiveness. Methods Essential features of the program include selection of early career fellows or more experienced investigators with a focus relevant to cancer control transitioning to a D&I research focus, a 5-day intensive training institute, ongoing peer and senior mentoring, mentored planning and work on a D&I research proposal or project, limited pilot funding, and training and ongoing improvement activities for mentors. The core faculty and staff members of the MT-DIRC program gathered baseline and ongoing evaluation data regarding D&I skill acquisition and mentoring competency through participant surveys and analyzed it by iterative collective reflection. Results A majority (79%) of fellows are female, assistant professors (55%); 59% are in allied health disciplines, and 48% focus on cancer prevention research. Forty-three D&I research competencies were assessed; all improved from baseline to 6 and 18 months. These effects were apparent across beginner, intermediate, and advanced initial D&I competency levels and across the competency domains. Mentoring competency was rated very highly by the fellows––higher than rated by the mentors themselves. The importance of different mentoring activities, as rated by the fellows, was generally congruent with their satisfaction with the activities, with the exception of relatively greater satisfaction with the degree of emotional support and relatively lower satisfaction for skill building and opportunity initially. Conclusions These first years of MT-DIRC demonstrated the program’s ability to attract, engage, and improve fellows’ competencies and skills and implement a multicomponent mentoring program that was well received. This account of the program can serve as a basis for potential replication and evolution of this model in training future D&I science researchers