Ranking Software Artifacts

Reengineering and integrated development plat- forms typically do not list search results in a particularly useful order. PageRank is the algorithm prominently used by the Google internet search engine to rank the relative importance of elements in a set of hyperlinked documents. To determine the relevance of objects, classes, attributes, and methods we propose to apply PageRank to software artifacts and their relationship (reference, inheritance, access, and invocation). This paper presents various experiments that demonstrate the usefulness of the ranking algorithm in software (re)engineering.

Ranking of parameters of pain hypersensitivity according to their discriminative ability in chronic low back pain

Low back pain is associated with plasticity changes and central hypersensitivity in a subset of patients. We performed a case-control study to explore the discriminative ability of different quantitative sensory tests in distinguishing between 40 cases with chronic low back pain and 300 pain-free controls, and to rank these tests according to the extent of their association with chronic pain. Gender, age, height, weight, body mass index, and psychological measures were recorded as potential confounders. We used 26 quantitative sensory tests, including different modalities of pressure, heat, cold, and electrical stimulation. As measures of discrimination, we estimated receiver operating characteristics (ROC) and likelihood ratios. Six tests seemed useful (in order of their discriminative ability): (1) pressure pain detection threshold at the site of most severe pain (fitted area under the ROC, 0.87), (2) single electrical stimulation pain detection threshold (0.87), (3) single electrical stimulation reflex threshold (0.83), (4) pressure pain tolerance threshold at the site of most severe pain (0.81), (5) pressure pain detection threshold at suprascapular region (0.80), and (6) temporal summation pain threshold (0.80). Pressure and electrical pain modalities seemed most promising and may be used for diagnosis of pain hypersensitivity and potentially for identifying individuals at risk of developing chronic low back pain over time.

Routine procedures in NICUs: factors influencing pain assessment and ranking by pain intensity

BACKGROUND: Pain associated with routine procedures in NICUs is often inadequately managed. Barriers to more appropriate pain management are nurses' and physicians' knowledge and the challenges of collaborative decision-making. Few studies describe the differing perceptions of procedural pain intensity among nurses and physicians in NICUs which could complicate common decision-making. This study set out to explore the factors influencing pain intensity assessment and to gain insight into a possible pain intensity classification of routine procedures in the NICU. METHOD: A survey was conducted among 431 neonatal health care professionals from 4 tertiary level NICUs. Each routine procedure was assessed on a 10-point visual analogue scale (VAS) assuming absence of analgesia. RESULTS: Multiple ANCOVA models showed that nurses rated 19 of the 27 procedures as significantly more painful than did physicians (p<0.05). We found no differences in pain assessment based on professional experience, gender or age. Of the 27 procedures listed, 70% were rated as painful and 44% were judged very painful. Ranking and classification of the pain intensity of routine procedures were drawn up. The general ranking of the median across all procedures shows that "insertion of a thoracic drain" is assessed as the most painful procedure. CONCLUSIONS: The majority of routine procedures in an NICU are considered to be painful. Nurses generally rate procedures as more painful than do physicians. This difference in assessment deserves exploration in regard to its impact on collaborative decision-making in neonate pain management.

Ranking of tests for pain hypersensitivity according to their discriminative ability in chronic neck pain

BACKGROUND AND OBJECTIVES Quantitative sensory testing (QST) is widely used to investigate peripheral and central sensitization. However, the comparative performance of different QST for diagnostic or prognostic purposes is unclear. We explored the discriminative ability of different quantitative sensory tests in distinguishing between patients with chronic neck pain and pain-free control subjects and ranked these tests according to the extent of their association with pain hypersensitivity. METHODS We performed a case-control study in 40 patients and 300 control subjects. Twenty-six tests, including different modalities of pressure, heat, cold, and electrical stimulation, were used. As measures of discrimination, we estimated receiver operating characteristic curves and likelihood ratios. RESULTS The following quantitative sensory tests displayed the best discriminative value: (1) pressure pain threshold at the site of the most severe neck pain (fitted area under the receiver operating characteristic curve, 0.92), (2) reflex threshold to single electrical stimulation (0.90), (3) pain threshold to single electrical stimulation (0.89), (4) pain threshold to repeated electrical stimulation (0.87), and (5) pressure pain tolerance threshold at the site of the most severe neck pain (0.86). Only the first 3 could be used for both ruling in and out pain hypersensitivity. CONCLUSIONS Pressure stimulation at the site of the most severe pain and parameters of electrical stimulation were the most appropriate QST to distinguish between patients with chronic neck pain and asymptomatic control subjects. These findings may be used to select the tests in future diagnostic and longitudinal prognostic studies on patients with neck pain and to optimize the assessment of localized and spreading sensitization in chronic pain patients.

A connection between two nonparametric tests for perfect ranking in balanced ranked set sampling

In this note, we show that an extension of a test for perfect ranking in a balanced ranked set sample given by Li and Balakrishnan (2008) to the multi-cycle case turns out to be equivalent to the test statistic proposed by Frey et al. (2007). This provides an alternative interpretation and motivation for their test statistic.

A Parametric Test of Perfect Ranking in Balanced Ranked Set Sampling

Many techniques based on data which are drawn by Ranked Set Sampling (RSS) scheme assume that the ranking of observations is perfect. Therefore it is essential to develop some methods for testing this assumption. In this article, we propose a parametric location-scale free test for assessing the assumption of perfect ranking. The results of a simulation study in two special cases of normal and exponential distributions indicate that the proposed test performs well in comparison with its leading competitors.

Model for ranking freshwater fish farms according to their risk of infection and illustration for viral haemorrhagic septicaemia

We developed a model to calculate a quantitative risk score for individual aquaculture sites. The score indicates the risk of the site being infected with a specific fish pathogen (viral haemorrhagic septicaemia virus (VHSV); infectious haematopoietic necrosis virus, Koi herpes virus), and is intended to be used for risk ranking sites to support surveillance for demonstration of zone or member state freedom from these pathogens. The inputs to the model include a range of quantitative and qualitative estimates of risk factors organised into five risk themes (1) Live fish and egg movements; (2) Exposure via water; (3) On-site processing; (4) Short-distance mechanical transmission; (5) Distance-independent mechanical transmission. The calculated risk score for an individual aquaculture site is a value between zero and one and is intended to indicate the risk of a site relative to the risk of other sites (thereby allowing ranking). The model was applied to evaluate 76 rainbow trout farms in 3 countries (42 from England, 32 from Italy and 2 from Switzerland) with the aim to establish their risk of being infected with VHSV. Risk scores for farms in England and Italy showed great variation, clearly enabling ranking. Scores ranged from 0.002 to 0.254 (mean score 0.080) in England and 0.011 to 0.778 (mean of 0.130) for Italy, reflecting the diversity of infection status of farms in these countries. Requirements for broader application of the model are discussed. Cost efficient farm data collection is important to realise the benefits from a risk-based approach.