Impact of Metric Selection on Wireless DeAuthentication DoS Attack Performance

DeAuthentication Denial of Service attacks in Public Access WiFi operate by exploiting the lack of authentication of management frames in the 802.11 protocol. Detection of these attacks rely almost exclusively on the selection of appropriate thresholds. In this work the authors demonstrate that there are additional, previously unconsidered, metrics which also influence DoS detection performance. A method of systematically tuning these metrics to optimal values is proposed which ensures that parameter choices are repeatable and verifiable.

Development and assessment of a robust optimization metric for WAMPAC modeling

A PMU based WAMS is to be placed on a weakly coupled section of distribution grid, with high levels of distributed generation. In anticipation of PMU data a Siemens PSS/E model of the electrical environment has been used to return similar data to that expected from the WAMS. This data is then used to create a metric that reflects optimization, control and protection in the region. System states are iterated through with the most desirable one returning the lowest optimization metric, this state is assessed against the one returned by PSS/E under normal circumstances. This paper investigates the circumstances that trigger SPS in the region, through varying generation between 0 and 110% and compromising the network through line loss under summer minimum and winter maximum conditions. It is found that the optimized state can generally tolerate an additional 2 MW of generation (3% of total) before encroaching the same thresholds and in one instance moves the triggering to 100% of generation output.

Dense spectrum of resonances and spin-1/2 particle capture in a near-black-hole metric

We show that a spin-1/2 particle in the gravitational field of a massive body of radius R which slightly exceeds the Schwarzschild radius rs, possesses a dense spectrum of narrow resonances. Their lifetimes and density tend to infinity in the limit R → rs. We determine the cross section of the particle capture into these resonances and show that it is equal to the spin-1/2 absorption cross section for a Schwarzschild black hole. Thus black-hole properties may emerge in a non-singular static metric prior to the formation of a black hole.

LD Score regression distinguishes confounding from polygenicity in genome-wide association studies

Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.

Efficient RkNN Retrieval with Arbitrary Non-Metric Similarity Measures

A RkNN query returns all objects whose nearest k neighbors
contain the query object. In this paper, we consider RkNN
query processing in the case where the distances between
attribute values are not necessarily metric. Dissimilarities
between objects could then be a monotonic aggregate of dissimilarities
between their values, such aggregation functions
being specified at query time. We outline real world cases
that motivate RkNN processing in such scenarios. We consider
the AL-Tree index and its applicability in RkNN query
processing. We develop an approach that exploits the group
level reasoning enabled by the AL-Tree in RkNN processing.
We evaluate our approach against a Naive approach
that performs sequential scans on contiguous data and an
improved block-based approach that we provide. We use
real-world datasets and synthetic data with varying characteristics
for our experiments. This extensive empirical
evaluation shows that our approach is better than existing
methods in terms of computational and disk access costs,
leading to significantly better response times.

A comparison between accelerated hypofractionation and stereotactic ablative radiotherapy (SABR) for early-stage non-small cell lung cancer (NSCLC): Results of a propensity score-matched analysis

BACKGROUND AND PURPOSE: Stereotactic ablative radiotherapy (SABR) has become standard for inoperable early-stage non-small cell lung cancer (NSCLC). However, there is no randomized evidence demonstrating benefit over more fractionated radiotherapy. We compared accelerated hypofractionation (AH) and SABR using a propensity score-matched analysis.

MATERIALS AND METHODS: From 1997-2007, 119 patients (T1-3N0M0 NSCLC) were treated with AH (48-60Gy, 12-15 fractions). Prior to SABR, this represented our institutional standard. From 2008-2012, 192 patients (T1-3N0M0 NSCLC) were treated with SABR (48-52Gy, 4-5 fractions). A total of 114 patients (57 per cohort) were matched (1:1 ratio, caliper: 0.10) using propensity scores.

RESULTS: Median follow-up (range) for the AH cohort was 36.3 (2.5-109.1) months, while that for the SABR group was 32.5 (0.3-62.6)months. Three-year overall survival (OS) and local control (LC) rates were 49.5% vs. 72.4% [p=0.024; hazard ratio (HR): 2.33 (1.28, 4.23), p=0.006] and 71.9% vs. 89.3% [p=0.077; HR: 5.56 (1.53, 20.2), p=0.009], respectively. On multivariable analysis, tumour diameter and PET staging were predictive for OS, while the only predictive factor for LC was treatment cohort.

CONCLUSIONS: OS and LC were improved with SABR, although OS is more closely related to non-treatment factors. This represents one of the few studies comparing AH to SABR for early-stage lung cancer.

American Society of Anesthesiologists Score: Still Useful After 60 Years? Results of the EuSOS Study

OBJECTIVE: The European Surgical Outcomes Study described mortality following in-patient surgery. Several factors were identified that were able to predict poor outcomes in a multivariate analysis. These included age, procedure urgency, severity and type and the American Association of Anaesthesia score. This study describes in greater detail the relationship between the American Association of Anaesthesia score and postoperative mortality. METHODS: Patients in this 7-day cohort study were enrolled in April 2011. Consecutive patients aged 16 years and older undergoing inpatient non-cardiac surgery with a recorded American Association of Anaesthesia score in 498 hospitals across 28 European nations were included and followed up for a maximum of 60 days. The primary endpoint was in-hospital mortality. Decision tree analysis with the CHAID (SPSS) system was used to delineate nodes associated with mortality. RESULTS: The study enrolled 46,539 patients. Due to missing values, 873 patients were excluded, resulting in the analysis of 45,666 patients. Increasing American Association of Anaesthesia scores were associated with increased admission rates to intensive care and higher mortality rates. Despite a progressive relationship with mortality, discrimination was poor, with an area under the ROC curve of 0.658 (95% CI 0.642 - 0.6775). Using regression trees (CHAID), we identified four discrete American Association of Anaesthesia nodes associated with mortality, with American Association of Anaesthesia 1 and American Association of Anaesthesia 2 compressed into the same node. CONCLUSION: The American Association of Anaesthesia score can be used to determine higher risk groups of surgical patients, but clinicians cannot use the score to discriminate between grades 1 and 2. Overall, the discriminatory power of the model was less than acceptable for widespread use.

In postmenopausal women with osteoporosis, denosumab significantly improved trabecular bone score (TBS), an index of trabecular microarchitecture

Background/Purpose: The trabecular bone score (TBS), a novel graylevel texture index determined from lumbar spine DXA scans, correlates with 3D parameters of trabecular bone microarchitecture known to predict fracture. TBS may enhance the identification of patients at increased risk for vertebral fracture independently of bone mineral density (BMD) (Boutroy JBMR 2010; Hans JBMR 2011). Denosumab treatment for 36 months decreased bone turnover, increased BMD, and reduced new vertebral fractures in postmenopausal women with osteoporosis (Cummings NEJM 2009). We explored the effect of denosumab on TBS over 36 months and evaluated the association between TBS and lumbar spine BMD in women who had DXA scans obtained from eligible scanners for TBS evaluation in FREEDOM. Methods: FREEDOM was a 3-year, randomized, double-blind trial that enrolled postmenopausal women with a lumbar spine or total hip DXA T-score __2.5, but not __4.0 at both sites. Women received placebo or 60 mg denosumab every 6 months. A subset of women in FREEDOM participated in a DXA substudy where lumbar spine DXA scans were obtained at baseline and months 1, 6, 12, 24, and 36. We retrospectively applied, in a blinded-to-treatment manner, a novel software program (TBS iNsightR v1.9, Med-Imaps, Pessac, France) to the standard lumbar spine DXA scans obtained in these women to determine their TBS indices at baseline and months 12, 24, and 36. From previous studies, a TBS _1.35 is considered as normal microarchitecture, a TBS between 1.35 and _1.20 as partially deteriorated, and 1.20 reflects degraded microarchitecture. Results: There were 285 women (128 placebo, 157 denosumab) with a TBS value at baseline and _1 post-baseline visit. Their mean age was 73, their mean lumbar spine BMD T-score was _2.79, and their mean lumbar spine TBS was 1.20. In addition to the robust gains in DXA lumbar spine BMD observed with denosumab (9.8% at month 36), there were consistent, progressive, and significant increases in TBS compared with placebo and baseline (Table & Figure). BMD explained a very small fraction of the variance in TBS at baseline (r2_0.07). In addition, the variance in the TBS change was largely unrelated to BMD change, whether expressed in absolute or percentage changes, regardless of treatment, throughout the study (all r2_0.06); indicating that TBS provides distinct information, independently of BMD. Conclusion: In postmenopausal women with osteoporosis, denosumab significantly improved TBS, an index of lumbar spine trabecular microarchitecture, independently of BMD.