Experience report: anomaly detection of cloud application operations using log and cloud metric correlation analysis

Failure of application operations is one of the maincauses of system-wide outages in cloud environments. Thisparticularly applies to DevOps operations, such as backup,redeployment, upgrade, customized scaling, and migration that areexposed to frequent interference from other concurrent operations,configuration changes, and resources failure. However, currentpractices fail to provide a reliable assurance of correct execution ofthese kinds of operations. In this paper, we present an approach toaddress this problem that adopts a regression-based analysistechnique to find the correlation between an operation’s activity logsand the operation activity’s effect on cloud resources. Thecorrelation model is then used to derive assertion specifications,which can be used for runtime verification of running operations andtheir impact on resources. We evaluated our proposed approach onAmazon EC2 with 22 rounds of rolling upgrade operations whileother types of operations were running and random faults wereinjected. Our experiment shows that our approach successfullymanaged to raise alarms for 115 random injected faults, with aprecision of 92.3%.

A novel bipolar time-spread echo hiding based watermarking method for stereo audio signals

In this paper, a novel bipolar time-spread (TS) echo hiding based watermarking method is proposed for stereo audio signals, to overcome the low robustness problem in the traditional TS echo hiding method. At the embedding, echo signals with opposite polarities are added to both channels of the host audio signal. This improves the imperceptibility of the watermarking scheme, since added watermarks have similar effects in both channels. Then decoding part is developed, in order to improve the robustness of the watermarking scheme against common attacks. Since these novel embedding and decoding methods utilize the advantage of two channels in stereo audio signals, it significantly reduces the interference of host signal at watermark extraction which is the main reason for error detection in the traditional TS echo hiding based watermarking under closed-loop attack. The effectiveness of the proposed watermarking scheme is theoretically analyzed and verified by simulations under common attacks. The proposed echo hiding method outperforms conventional TS echo hiding based watermarking when their perceptual qualities are similar.

Patient safety ethics and human error management in ED contexts part I : development of the global patient safety movement

In recent years there has been increasing recognition internationally that health care is not as safe as it ought to be and that patient safety outcomes need to be improved. To this end patient safety has become the focus of a world-wide endeavour aimed at reducing the incidence and impact of preventable human errors and related adverse events in health care domains. The emergency department has been identified as a significant site of preventable human errors and adverse events in the health care system, raising important questions about the nature of human error management and patient safety ethics in rapidly changing environments. In this article (the first of a two-part discussion on the subject) an overview of the incidence and impact of preventable adverse events in ED contexts is explored. The development of a ‘culture of safety’ in other hazardous industries and the ‘lessons learned’ and applied to the health care industry are also briefly examined. In a second article (to be presented as Part II), some of the ethical tensions that have arisen in the context of implementing patient safety processes and their possible implications for ED contexts are explored.

Patient safety ethics and human error management in ED contexts Part II : Accountability and the challenge to change

In recent years there has been increasing recognition internationally that health care is not as safe as it ought to be and that patient safety outcomes need to be improved. To this end, patient safety has become the focus of a world-wide endeavour – endorsed by the World Health Organisation – to reduce the incidence and impact of preventable human errors and related adverse events in health care domains. The emergency department has been identified as a significant site of preventable human errors and adverse events in the health care system, raising important questions about the nature of human error management and patient safety ethics in rapidly changing environments, of which the Emergency Department is a prime example. In Part I of this article series, an overview of the incidence and impact of preventable adverse events in Emergency Department contexts and the development of the global patient safety movement was presented. In this second article brief attention is given to examining some of the ethical tensions that have arisen in response to the patient safety movement and their possible implications for Emergency Department contexts and staff.

An efficient hybrid algorithm for fire flame detection

Proposing efficient methods for fire protection is becoming more and more important, because a small flame of fire may cause huge problems in social safety. In this paper, an effective fire flame detection method is investigated. This fire detection method includes four main stages: in the first step, a linear transformation is applied to convert red, green, and blue (RGB) color space through a 3∗3 matrix to a new color space. In the next step, fuzzy c-mean clustering method (FCM) is used to distinguish between fire flame and non-fire flame pixels. Particle Swarm Optimization algorithm (PSO) is also utilized in the last step to decrease the error value measured by FCM after conversion. Finally, we apply Otsu threshold method to the new converted images to make a binary picture. Empirical results show the strength, accuracy and fast-response of the proposed algorithm in detecting fire flames in color images.

A complex relationship among chemical concentration, detection threshold and suprathreshold intensity of bitter compounds

Detection thresholds and psychophysical curves were established for caffeine, quinine-HCl (QHCl), and propylthiouracil (PROP) in a sample of 33 subjects (28 female mean age 24 ± 4). The mean detection threshold (±standard error) for caffeine, QHCl, and PROP was 1.2 ± 0.12, 0.0083 ± 0.001, and 0.088 ± 0.07 mM, respectively. Pearson product–moment analysis revealed no significant correlations between detection thresholds of the compounds. Psychophysical curves were constructed for each bitter compound over 6 concentrations. There were significant correlations between incremental points of the individual psychophysical curves for QHCl and PROP. Regarding caffeine, there was a specific concentration (6 mM) below and above which the incremental steps in bitterness were correlated. Between compounds, analysis of psychophysical curves revealed no correlations with PROP, but there were significant correlations between the bitterness of caffeine and QHCl at higher concentrations on the psychophysical curve (P < 0.05). Correlation analysis of detection threshold and suprathreshold intensity within a compound revealed a significant correlation between PROP threshold and suprathreshold intensity (r = 0.46–0.4, P < 0.05), a significant negative correlation for QHCl (r = –0.33 to –0.4, P < 0.05), and no correlation for caffeine. The results suggest a complex relationship between chemical concentration, detection threshold, and suprathreshold intensity.

Lung nodules detection by ensemble classification

A method is presented that achieves lung nodule detection by classification of nodule and non-nodule patterns. It is based on random forests which are ensemble learners that grow classification trees. Each tree produces a classification decision, and an integrated output is calculated. The performance of the developed method is compared against that of the support vector machine and the decision tree methods. Three experiments are performed using lung scans of 32 patients including thousands of images within which nodule locations are marked by expert radiologists. The classification errors and execution times are presented and discussed. The lowest classification error (2.4%) has been produced by the developed method.

Implementation of a medication guideline to improve medication safety for patients

Although the incidence of medication error remains unknown, in Australian hospitals, they are thought to occur in 5-20 % of drug administrations 1. Not surprisingly, international debate has focused on the mechanisms to improve the safety of patients. Thus a new National Inpatient Medication Chart (NIMC) was endorsed to improve communication and reduce medication errors 2. This study aimed to investigate the documentation practices of clinicians following the implementation of a medication guideline and NIMC.
A pre and post-test design was used to evaluate the adoption of and adherence to the medication guideline at Western Health, an 850 bed healthcare network in Australia. Audits of inpatient medication charts (N=265) were conducted at 3 months prior to and repeated 4 months (N=290) after implementation. The pre-test data was used to formulate an interdisciplinary organizational strategy that included mandatory education for all clinical staff, practice reminders, decision prompts, a telephone hotline for support, an intranet information website and electronically distributed Frequently Asked Questions.
Pre and post implementation audits highlighted areas of potential medication error. The post-test showed an overall trend towards improvement in documentation. There were significant improvements in 4 critical practices: Drug name clear (p=0.0003); Drug dose clear (p=0.0002); Prescribed frequency equals documented frequency (p=0) and; No signature by administrator (p=0).
The majority of documentation errors showed poor attention to detail and would be considered a slip or lapse in skill based judgment 3. Although this study was designed to evaluate documentation practices, future research should include observation methods to increase our understanding of the context behind the judgments such as work place interruptions, skill mix and knowledge levels. While evidence based guidelines enable work, they are not the actual work or substance of patient care. Organisational systems can assist in preventing unconscious aberrations that lead to error.

Medical error and decision making : learning from the past and present in intensive care

Background : Human error occurs in every occupation. Medical errors may result in a near miss or an actual injury to a patient that has nothing to do with the underlying medical condition. Intensive care has one of the highest incidences of medical error and patient injury in any specialty medical area; thought to be related to the rapidly changing patient status and complex diagnoses and treatments.

Purpose : The aims of this paper are to: (1) outline the definition, classifications and aetiology of medical error; (2) summarise key findings from the literature with a specific focus on errors arising from intensive care areas; and (3) conclude with an outline of approaches for analysing clinical information to determine adverse events and inform practice change in intensive care.

Data source : Database searches of articles and textbooks using keywords: medical error, patient safety, decision making and intensive care. Sociology and psychology literature cited therein.

Findings : Critically ill patients require numerous medications, multiple infusions and procedures. Although medical errors are often detected by clinicians at the bedside, organisational processes and systems may contribute to the problem. A systems approach is thought to provide greater insight into the contributory factors and potential solutions to avoid preventable adverse events.

Conclusion : It is recommended that a variety of clinical information and research techniques are used as a priority to prevent hospital acquired injuries and address patient safety concerns in intensive care.

Nurses' role in medication safety

Aim To explore the nurses role in the process of medication management and identify the challenges associated with safe medication management in contemporary clinical practice.
Background Medication errors have been a long-standing factor affecting consumer safety. The nursing profession has been identified as essential to the promotion of patient safety.
Evaluation A review of literature on medication errors and the use of electronic prescribing in medication errors.
Key issues Medication management requires a multidisciplinary approach and interdisciplinary communication is essential to reduce medication errors. Information technologies can help to reduce some medication errors through eradication of transcription and dosing errors. Nurses must play a major role in the design of computerized medication systems to ensure a smooth transition to such as system.
Conclusion The nurses roles in medication management cannot be over-emphasized. This is particularly true when designing a computerized medication system.
Implication for nursing management The adoption of safety measures during decision making that parallel those of the aviation industry safety procedures can provide some strategies to prevent medication error. Innovations in information technology offer potential mechanisms to avert adverse events in medication management for nurses.

Secure localization with attack detection in wireless sensor networks

Rapid technological advances have enabled the development of low-cost sensor networks for various monitoring tasks, where it is important to estimate the positions of a number of regular sensor nodes whose locations cannot be known apriori. We address the problem of localizing the regular nodes with range-based location references obtained from certain anchor nodes referred to as beacons, particularly in an adverse environment where some of the beacons may be compromised. We propose an innovative modular solution featuring two lightweight modules that are for dedicated functionalities, respectively, but can also be closely integrated. First, we harness simple geometric triangular rules and an efficient voting technique to enable the attack detection module, which identifies and filters out malicious location references. We then develop a secure localization module that computes and clusters certain reference points, and the position of the concerned regular node is estimated with the centroid of the most valuable reference points identified. Extensive simulations show that our attack detection module can detect compromised beacons effectively, and the secure localization module can subsequently provide a dependable localization service in terms of bounded estimation error. The integrated system turns out to be tolerant of malicious attacks even in highly challenging scenarios.

Multifactorial influences on and deviations from medication administration safety and quality in the acute medical/surgical context

Background and Aims: Although numerous factors influence medication administration, our understanding of the interplay of these factors on medication quality and safety is limited. The aim of this study was to explore the multifactorial influences on medication quality and safety in the context of a single checking policy for medication administration in acute care.

Approach: An exploratory/descriptive study using non-participant observation and follow-up interview was used to identify factors influencing medication quality and safety in medication administration episodes (n = 30). Observations focused on nurses’ interactions with patients during medication administration, and the characteristics of the environment in which these took place. Confirmation of observed data occurred on completion of the observation period during short semi-structured interviews with participant nurses.

Findings: Findings showed nurses developed therapeutic relationships with patients in terms of assessing patients before administering medications and educating patients about drugs during medication administration. Nurses experienced more frequent distractions when medications were stored and prepared in a communal drug room according to ward design. Nurses deviated from best-practice guidelines during medication administration.

Implications: Nurses’ abilities and readiness to develop therapeutic relationships with patients increased medication quality and safety, thereby protecting patients from potential adverse events. Deviations from best-practice medication administration had the potential to decrease medication safety. System factors such as ward design determining medication storage areas can be readily addressed to minimise potential error.

Conclusions: Nurses displayed behaviours that increased medication administration quality and safety; however, violations of practice standards were observed. These findings will inform future intervention studies to improve medication quality and safety.

Activity recognition and abnormality detection with the switching hidden semi-Markov model

This paper addresses the problem of learning and recognizing human activities of daily living (ADL), which is an important research issue in building a pervasive and smart environment. In dealing with ADL, we argue that it is beneficial to exploit both the inherent hierarchical organization of the activities and their typical duration. To this end, we introduce the Switching Hidden Semi-Markov Model (S-HSMM), a two-layered extension of the hidden semi-Markov model (HSMM) for the modeling task. Activities are modeled in the S-HSMM in two ways: the bottom layer represents atomic activities and their duration using HSMMs; the top layer represents a sequence of high-level activities where each high-level activity is made of a sequence of atomic activities. We consider two methods for modeling duration: the classic explicit duration model using multinomial distribution, and the novel use of the discrete Coxian distribution. In addition, we propose an effective scheme to detect abnormality without the need for training on abnormal data. Experimental results show that the S-HSMM performs better than existing models including the flat HSMM and the hierarchical hidden Markov model in both classification and abnormality detection tasks, alleviating the need for presegmented training data. Furthermore, our discrete Coxian duration model yields better computation time and generalization error than the classic explicit duration model.

Wireless instantaneous neurotransmitter concentration system-based amperometric detection of dopamine, adenosine, and glutamate for intraoperative neurochemical monitoring - laboratory investigation

Object  In a companion study, the authors describe the development of a new instrument named the Wireless Instantaneous Neurotransmitter Concentration System (WINCS), which couples digital telemetry with fast-scan cyclic voltammetry (FSCV) to measure extracellular concentrations of dopamine. In the present study, the authors describe the extended capability of the WINCS to use fixed potential amperometry (FPA) to measure extracellular concentrations of dopamine, as well as glutamate and adenosine. Compared with other electrochemical techniques such as FSCV or high-speed chronoamperometry, FPA offers superior temporal resolution and, in combination with enzyme-linked biosensors, the potential to monitor nonelectroactive analytes in real time.

Methods  The WINCS design incorporated a transimpedance amplifier with associated analog circuitry for FPA; a microprocessor; a Bluetooth transceiver; and a single, battery-powered, multilayer, printed circuit board. The WINCS was tested with 3 distinct recording electrodes: 1) a carbon-fiber microelectrode (CFM) to measure dopamine; 2) a glutamate oxidase enzyme–linked electrode to measure glutamate; and 3) a multiple enzyme–linked electrode (adenosine deaminase, nucleoside phosphorylase, and xanthine oxidase) to measure adenosine. Proof-of-principle analyses included noise assessments and in vitro and in vivo measurements that were compared with similar analyses by using a commercial hardwired electrochemical system (EA161 Picostat, eDAQ; Pty Ltd). In urethane-anesthetized rats, dopamine release was monitored in the striatum following deep brain stimulation (DBS) of ascending dopaminergic fibers in the medial forebrain bundle (MFB). In separate rat experiments, DBS-evoked adenosine release was monitored in the ventrolateral thalamus. To test the WINCS in an operating room setting resembling human neurosurgery, cortical glutamate release in response to motor cortex stimulation (MCS) was monitored using a large-mammal animal model, the pig.

Results   The WINCS, which is designed in compliance with FDA-recognized consensus standards for medical electrical device safety, successfully measured dopamine, glutamate, and adenosine, both in vitro and in vivo. The WINCS detected striatal dopamine release at the implanted CFM during DBS of the MFB. The DBS-evoked adenosine release in the rat thalamus and MCS-evoked glutamate release in the pig cortex were also successfully measured. Overall, in vitro and in vivo testing demonstrated signals comparable to a commercial hardwired electrochemical system for FPA.

Conclusions  By incorporating FPA, the chemical repertoire of WINCS-measurable neurotransmitters is expanded to include glutamate and other nonelectroactive species for which the evolving field of enzyme-linked biosensors exists. Because many neurotransmitters are not electrochemically active, FPA in combination with enzyme-linked microelectrodes represents a powerful intraoperative tool for rapid and selective neurochemical sampling in important anatomical targets during functional neurosurgery.

Corner Inlet and Nooramunga Habitat Mapping Project – Part 2 : High resolution mapping and change detection analysis using 2011 Rapid Eye Satellite Image compared to 2009 ALOS Satellite Image

Building on a habitat mapping project completed in 2011, Deakin University was commissioned by Parks Victoria (PV) to apply the same methodology and ground-truth data to a second, more recent and higher resolution satellite image to create habitat maps for areas within the Corner Inlet and Nooramunga Marine and Coastal Park and Ramsar area. A ground-truth data set using in situ video and still photographs was used to develop and assess predictive models of benthic marine habitat distributions incorporating data from both RapidEye satellite imagery (corrected for atmospheric and water column effects by CSIRO) and LiDAR (Light Detection and Ranging) bathymetry. This report describes the results of the mapping effort as well as the methodology used to produce these habitat maps.

Overall accuracies of habitat classifications were good, with error rates similar to or better than the earlier classification (>73 % and kappa values > 0.58 for both study localities). The RapidEye classification failed to accurately detect Pyura and reef habitat classes at the Corner Inlet locality, possibly due to differences in spectral frequencies. For comparison, these categories were combined into a ‘non-seagrass’ category, similar to the one used at the Nooramunga locality in the original classification. Habitats predicted with highest accuracies differed from the earlier classification and were Posidonia in Corner Inlet (89%), and bare sediment (no-visible seagrass class) in Nooramunga (90%). In the Corner Inlet locality reef and Pyura habitat categories were not distinguishable in the repeated classification and so were combined with bare sediments. The majority of remaining classification errors were due to the misclassification of Zosteraceae as bare sediment and vice versa. Dominant habitats were the same as those from the 2011 classification with some differences in extent. For the Corner Inlet study locality the no-visible seagrass category remained the most extensive (9059 ha), followed by Posidonia (5,513 ha) and Zosteraceae (5,504 ha). In Nooramunga no-visible seagrass (6,294 ha), Zosteraceae (3,122 ha) and wet saltmarsh (1,562 ha) habitat classes were most dominant.

Change detection analyses between the 2009 and 2011 imagery were undertaken as part of this project, following the analyses presented in Monk et al. (2011) and incorporating error estimates from both classifications. These analyses indicated some shifts in classification between Posidonia and Zosteraceae as well as a general reduction in the area of Zosteraceae. Issues with classification of mixed beds were apparent, particularly in the main Posidonia bed at Nooramunga where a mosaic of Zosteraceae and Posidonia was seen that was not evident in the ALOS classification. Results of a reanalysis of the 1998-2009 change detection illustrating effects of binning of mixed beds is also provided as an appendix.

This work has been successful in providing baseline maps at an improved level of detail using a repeatable method meaning that any future changes in intertidal and shallow water marine habitats may be assessed in a consistent way with quantitative error assessments. In wider use, these maps should also allow improved conservation planning, advance fisheries and catchment management, and progress infrastructure planning to limit impacts on the Inlet environment.