Using Context Information to Re-architect a System

Successful software systems cope with complexity by organizing classes into packages. However, a particular organization may be neither straightforward nor obvious for a given developer. As a consequence, classes can be misplaced, leading to duplicated code and ripple effects with minor changes effecting multiple packages. We claim that contextual information is the key to rearchitecture a system. Exploiting contextual information, we propose a technique to detect misplaced classes by analyzing how client packages access the classes of a given provider package. We define locality as a measure of the degree to which classes reused by common clients appear in the same package. We then use locality to guide a simulated annealing algorithm to obtain optimal placements of classes in packages. The result is the identification of classes that are candidates for relocation. We apply the technique to three applications and validate the usefulness of our approach via developer interviews.

Towards Energy Consumption Measurement in a Cloud Computing Wireless Testbed

The evolution of the Next Generation Networks, especially the wireless broadband access technologies such as Long Term Evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX), have increased the number of "all-IP" networks across the world. The enhanced capabilities of these access networks has spearheaded the cloud computing paradigm, where the end-users aim at having the services accessible anytime and anywhere. The services availability is also related with the end-user device, where one of the major constraints is the battery lifetime. Therefore, it is necessary to assess and minimize the energy consumed by the end-user devices, given its significance for the user perceived quality of the cloud computing services. In this paper, an empirical methodology to measure network interfaces energy consumption is proposed. By employing this methodology, an experimental evaluation of energy consumption in three different cloud computing access scenarios (including WiMAX) were performed. The empirical results obtained show the impact of accurate network interface states management and application network level design in the energy consumption. Additionally, the achieved outcomes can be used in further software-based models to optimized energy consumption, and increase the Quality of Experience (QoE) perceived by the end-users.

Effective compression ratio-A new measurement of the quality of thorax compression during CPR

PURPOSE: Computer-based feedback systems for assessing the quality of cardiopulmonary resuscitation (CPR) are widely used these days. Recordings usually involve compression and ventilation dependent variables. Thorax compression depth, sufficient decompression and correct hand position are displayed but interpreted independently of one another. We aimed to generate a parameter, which represents all the combined relevant parameters of compression to provide a rapid assessment of the quality of chest compression-the effective compression ratio (ECR). METHODS: The following parameters were used to determine the ECR: compression depth, correct hand position, correct decompression and the proportion of time used for chest compressions compared to the total time spent on CPR. Based on the ERC guidelines, we calculated that guideline compliant CPR (30:2) has a minimum ECR of 0.79. To calculate the ECR, we expanded the previously described software solution. In order to demonstrate the usefulness of the new ECR-parameter, we first performed a PubMed search for studies that included correct compression and no-flow time, after which we calculated the new parameter, the ECR. RESULTS: The PubMed search revealed 9 trials. Calculated ECR values ranged between 0.03 (for basic life support [BLS] study, two helpers, no feedback) and 0.67 (BLS with feedback from the 6th minute). CONCLUSION: ECR enables rapid, meaningful assessment of CPR and simplifies the comparability of studies as well as the individual performance of trainees. The structure of the software solution allows it to be easily adapted to any manikin, CPR feedback devices and different resuscitation guidelines (e.g. ILCOR, ERC).

MR imaging in Crohn's disease: correlation of MR motility measurement with histopathology in the terminal ileum

BACKGROUND: The objective of the study was to correlate MR-detectable motility alterations of the terminal ileum with biopsy-documented active and chronic changes in Crohn's disease. METHODS: This IRB approved retrospective analysis of 43 patients included magnetic resonance enterography (MRE) and terminal ileum biopsies (<2 weeks apart). Motility was measured at the terminal ileum using coronal 2D trueFISP pulse sequences (1.5T MRI,TR 83.8,TE1.89) and dedicated motility assessment software. Motility grading (hypermotility, normal, hypomotility, complete arrest) was agreed by two experienced readers. Motility was compared and correlated with histopathology using two-tailed Kruskal-Wallis test and paired Spearman Rank-Order Correlation tests. KEY RESULTS: Motility abnormalities were present in 27/43 patients: nine hypomotility and 18 complete arrest. Active disease was diagnosed on 15 biopsies: eight moderate and seven severe inflammatory activity. Chronic changes were diagnosed on 17 biopsies: 13 moderate and four severe cases. In four patients with normal motility alterations on histopathology were diagnosed. Histopathology correlated with presence (P = 0.0056 for hypomotility and P = 0.0119 for complete arrest) and grade (P < 0.0001; P = 0.0004) of motility alterations. A significant difference in the motility was observed in patients with active or chronic CD compared with patients without disease (P < 0.001; P = 0.0024). CONCLUSIONS & INFERENCES: MR-detectable motility changes of the terminal ileum correlate with histopathological findings both in active and chronic CD. Motility changes may indicate the presence pathology, but do not allow differentiation of active and chronic disease.

Dual energy versus single energy MDCT: measurement of radiation dose using adult abdominal imaging protocols

RATIONALE AND OBJECTIVES: The aim of this study was to measure the radiation dose of dual-energy and single-energy multidetector computed tomographic (CT) imaging using adult liver, renal, and aortic imaging protocols. MATERIALS AND METHODS: Dual-energy CT (DECT) imaging was performed on a conventional 64-detector CT scanner using a software upgrade (Volume Dual Energy) at tube voltages of 140 and 80 kVp (with tube currents of 385 and 675 mA, respectively), with a 0.8-second gantry revolution time in axial mode. Parameters for single-energy CT (SECT) imaging were a tube voltage of 140 kVp, a tube current of 385 mA, a 0.5-second gantry revolution time, helical mode, and pitch of 1.375:1. The volume CT dose index (CTDI(vol)) value displayed on the console for each scan was recorded. Organ doses were measured using metal oxide semiconductor field-effect transistor technology. Effective dose was calculated as the sum of 20 organ doses multiplied by a weighting factor found in International Commission on Radiological Protection Publication 60. Radiation dose saving with virtual noncontrast imaging reconstruction was also determined. RESULTS: The CTDI(vol) values were 49.4 mGy for DECT imaging and 16.2 mGy for SECT imaging. Effective dose ranged from 22.5 to 36.4 mSv for DECT imaging and from 9.4 to 13.8 mSv for SECT imaging. Virtual noncontrast imaging reconstruction reduced the total effective dose of multiphase DECT imaging by 19% to 28%. CONCLUSION: Using the current Volume Dual Energy software, radiation doses with DECT imaging were higher than those with SECT imaging. Substantial radiation dose savings are possible with DECT imaging if virtual noncontrast imaging reconstruction replaces precontrast imaging.

The role of diameter versus volume as the best prognostic measurement of abdominal aortic aneurysms

Accurate measurement of abdominal aortic aneurysms is necessary to predict rupture risk and, more recently, to follow aneurysm sac behavior following endovascular repair. Up until this point, aneurysm diameter has been the most common measurement utilized for these purposes. Although aneurysm diameter is predictive of rupture, accurate measurement is hindered by such factors as aortic tortuosity and interobserver variability, and it does not account for variations in morphology such as saccular aneurysms. Additionally, decreases in aneurysm diameter do not completely describe the somewhat complex remodeling seen following endovascular repair of aortic aneurysms. Measurement of aneurysm volume has the advantage of describing aneurysm morphology in a multidimensional fashion, but it has not been readily available or easily measured until recently. This has changed with the introduction of commercially available software tools that permit quicker and easier to perform volume measurements. Whether it is time for volume to replace, or compliment, diameter is the subject of the current debate.

The Cost-Effectiveness of Monitoring Strategies for Antiretroviral Therapy of HIV Infected Patients in Resource-Limited Settings: Software Tool.

BACKGROUND The cost-effectiveness of routine viral load (VL) monitoring of HIV-infected patients on antiretroviral therapy (ART) depends on various factors that differ between settings and across time. Low-cost point-of-care (POC) tests for VL are in development and may make routine VL monitoring affordable in resource-limited settings. We developed a software tool to study the cost-effectiveness of switching to second-line ART with different monitoring strategies, and focused on POC-VL monitoring. METHODS We used a mathematical model to simulate cohorts of patients from start of ART until death. We modeled 13 strategies (no 2nd-line, clinical, CD4 (with or without targeted VL), POC-VL, and laboratory-based VL monitoring, with different frequencies). We included a scenario with identical failure rates across strategies, and one in which routine VL monitoring reduces the risk of failure. We compared lifetime costs and averted disability-adjusted life-years (DALYs). We calculated incremental cost-effectiveness ratios (ICER). We developed an Excel tool to update the results of the model for varying unit costs and cohort characteristics, and conducted several sensitivity analyses varying the input costs. RESULTS Introducing 2nd-line ART had an ICER of US$1651-1766/DALY averted. Compared with clinical monitoring, the ICER of CD4 monitoring was US$1896-US$5488/DALY averted and VL monitoring US$951-US$5813/DALY averted. We found no difference between POC- and laboratory-based VL monitoring, except for the highest measurement frequency (every 6 months), where laboratory-based testing was more effective. Targeted VL monitoring was on the cost-effectiveness frontier only if the difference between 1st- and 2nd-line costs remained large, and if we assumed that routine VL monitoring does not prevent failure. CONCLUSION Compared with the less expensive strategies, the cost-effectiveness of routine VL monitoring essentially depends on the cost of 2nd-line ART. Our Excel tool is useful for determining optimal monitoring strategies for specific settings, with specific sex-and age-distributions and unit costs.

False normal Lung Clearance Index in infants with cystic fibrosis due to software algorithms.

BACKGROUND Lung clearance index (LCI), a marker of ventilation inhomogeneity, is elevated early in children with cystic fibrosis (CF). However, in infants with CF, LCI values are found to be normal, although structural lung abnormalities are often detectable. We hypothesized that this discrepancy is due to inadequate algorithms of the available software package. AIM Our aim was to challenge the validity of these software algorithms. METHODS We compared multiple breath washout (MBW) results of current software algorithms (automatic modus) to refined algorithms (manual modus) in 17 asymptomatic infants with CF, and 24 matched healthy term-born infants. The main difference between these two analysis methods lies in the calculation of the molar mass differences that the system uses to define the completion of the measurement. RESULTS In infants with CF the refined manual modus revealed clearly elevated LCI above 9 in 8 out of 35 measurements (23%), all showing LCI values below 8.3 using the automatic modus (paired t-test comparing the means, P < 0.001). Healthy infants showed normal LCI values using both analysis methods (n = 47, paired t-test, P = 0.79). The most relevant reason for false normal LCI values in infants with CF using the automatic modus was the incorrect recognition of the end-of-test too early during the washout. CONCLUSION We recommend the use of the manual modus for the analysis of MBW outcomes in infants in order to obtain more accurate results. This will allow appropriate use of infant lung function results for clinical and scientific purposes.

Impact of Software Settings on Multiple-Breath Washout Outcomes

BACKGROUND AND OBJECTIVES Multiple-breath washout (MBW) is an attractive test to assess ventilation inhomogeneity, a marker of peripheral lung disease. Standardization of MBW is hampered as little data exists on possible measurement bias. We aimed to identify potential sources of measurement bias based on MBW software settings. METHODS We used unprocessed data from nitrogen (N2) MBW (Exhalyzer D, Eco Medics AG) applied in 30 children aged 5-18 years: 10 with CF, 10 formerly preterm, and 10 healthy controls. This setup calculates the tracer gas N2 mainly from measured O2 and CO2concentrations. The following software settings for MBW signal processing were changed by at least 5 units or >10% in both directions or completely switched off: (i) environmental conditions, (ii) apparatus dead space, (iii) O2 and CO2 signal correction, and (iv) signal alignment (delay time). Primary outcome was the change in lung clearance index (LCI) compared to LCI calculated with the settings as recommended. A change in LCI exceeding 10% was considered relevant. RESULTS Changes in both environmental and dead space settings resulted in uniform but modest LCI changes and exceeded >10% in only two measurements. Changes in signal alignment and O2 signal correction had the most relevant impact on LCI. Decrease of O2 delay time by 40 ms (7%) lead to a mean LCI increase of 12%, with >10% LCI change in 60% of the children. Increase of O2 delay time by 40 ms resulted in mean LCI decrease of 9% with LCI changing >10% in 43% of the children. CONCLUSIONS Accurate LCI results depend crucially on signal processing settings in MBW software. Especially correct signal delay times are possible sources of incorrect LCI measurements. Algorithms of signal processing and signal alignment should thus be optimized to avoid susceptibility of MBW measurements to this significant measurement bias.