N-gram density based malware detection

N-gram analysis is an approach that investigates the structure of a program using bytes, characters or text strings. This research uses dynamic analysis to investigate malware detection using a classification approach based on N-gram analysis. The motivation for this research is to find a subset of Ngram features that makes a robust indicator of malware. The experiments within this paper represent programs as N-gram density histograms, gained through dynamic analysis. A Support Vector Machine (SVM) is used as the program classifier to determine the ability of N-grams to correctly determine the presence of malicious software. The preliminary findings show that an N-gram size N=3 and N=4 present the best avenues for further analysis.

High-energy monoenergetic proton beams from two stage acceleration with a slow laser pulse

We present a new regime to generate high-energy quasimonoenergetic proton beams in a "slow-pulse" regime, where the laser group velocity vg<c is reduced by an extended near-critical density plasma. In this regime, for properly matched laser intensity and group velocity, ions initially accelerated by the light sail (LS) mode can be further trapped and reflected by the snowplough potential generated by the laser in the near-critical density plasma. These two acceleration stages are connected by the onset of Rayleigh-Taylor-like (RT) instability. The usual ion energy spectrum broadening by RT instability is controlled and high quality proton beams can be generated. It is shown by multidimensional particle-in-cell simulation that quasimonoenergetic proton beams with energy up to hundreds of MeV can be generated at laser intensities of 1021W/cm².

Discrete Conditional Phase-type Model Utilising a Multiclass Support Vector Machine for the Prediction of Retinopathy of Prematurity

Retinopathy of prematurity (ROP) is a rare disease in which retinal blood vessels of premature infants fail to develop normally, and is one of the major causes of childhood blindness throughout the world. The Discrete Conditional Phase-type (DC-Ph) model consists of two components, the conditional component measuring the inter-relationships between covariates and the survival component which models the survival distribution using a Coxian phase-type distribution. This paper expands the DC-Ph models by introducing a support vector machine (SVM), in the role of the conditional component. The SVM is capable of classifying multiple outcomes and is used to identify the infant's risk of developing ROP. Class imbalance makes predicting rare events difficult. A new class decomposition technique, which deals with the problem of multiclass imbalance, is introduced. Based on the SVM classification, the length of stay in the neonatal ward is modelled using a 5, 8 or 9 phase Coxian distribution.

K&C局部损伤混凝土材料模型在精细有限元模拟中的应用

This paper presents a study on concrete fracture and the associated mesh sensitivity using the finite element (FE) method with a local concrete model in both tension (Mode I) and compression.To enable the incorporation of dynamic loading, the FE model is developed using a transient dynamic analysis code LS-DYNA Explicit.A series of investigations have been conducted on typical fracture scenarios to evaluate the model performances and calibration of relevant parameters.The K&C damage model was adopted because it is a comprehensive local concrete model which allows the user to change the crack band width, fracture energy and rate dependency of the material.Compressive localisation modelling in numerical modelling is also discussed in detail in relation to localisation.An impact test specimen is modelled.

Effect of position of near addition in an asymmetric refractive multifocal intraocular lens on quality of vision

Purpose
To evaluate the impact of the position of an asymmetric multifocal near segment on visual quality.

Setting
Cathedral Eye Clinic, Belfast, United Kingdom.

Design
Retrospective comparative case series.

Methods
Data from consecutive patients who had bilateral implantation of the Lentis Mplus LS-312 multifocal intraocular lens were divided into 2 groups. One group received inferonasal near-segment placement and the other, superotemporal near-segment placement. A +3.00 diopter (D) reading addition (add) was used in all eyes. The main outcome measures included uncorrected distance visual acuity (UDVA), uncorrected near visual acuity (UNVA), contrast sensitivity, and quality of vision. Follow-up was 3 months.

Results
Patients ranged in age from 43 to 76 years. The inferonasal group comprised 80 eyes (40 patients) and the superotemporal group, 76 eyes (38 patients). The mean 3-month spherical equivalent was −0.11 D ± 0.49 (SD) in the inferonasal group and −0.18 ± 0.46 D in the superotemporal group. The mean postoperative UDVA was 0.14 ± 0.10 logMAR and 0.18 ± 0.15 logMAR, respectively. The mean monocular UNVA was 0.21 ± 0.14 logRAD and 0.24 ± 0.13 logRAD, respectively. No significant differences were observed in the higher-order aberrations, total Strehl ratio (point-spread function), or modulation transfer function between the groups. Dysphotopic symptoms measured with a validated quality-of-vision questionnaire were not significantly different between groups.

Conclusion
Positioning of the near add did not significantly affect objective or subjective visual function parameters.

A Fast Algorithm for Sparse Support Vector Machines for Mobile Computing Applications

This research presents a fast algorithm for projected support vector machines (PSVM) by selecting a basis vector set (BVS) for the kernel-induced feature space, the training points are projected onto the subspace spanned by the selected BVS. A standard linear support vector machine (SVM) is then produced in the subspace with the projected training points. As the dimension of the subspace is determined by the size of the selected basis vector set, the size of the produced SVM expansion can be specified. A two-stage algorithm is derived which selects and refines the basis vector set achieving a locally optimal model. The model expansion coefficients and bias are updated recursively for increase and decrease in the basis set and support vector set. The condition for a point to be classed as outside the current basis vector and selected as a new basis vector is derived and embedded in the recursive procedure. This guarantees the linear independence of the produced basis set. The proposed algorithm is tested and compared with an existing sparse primal SVM (SpSVM) and a standard SVM (LibSVM) on seven public benchmark classification problems. Our new algorithm is designed for use in the application area of human activity recognition using smart devices and embedded sensors where their sometimes limited memory and processing resources must be exploited to the full and the more robust and accurate the classification the more satisfied the user. Experimental results demonstrate the effectiveness and efficiency of the proposed algorithm. This work builds upon a previously published algorithm specifically created for activity recognition within mobile applications for the EU Haptimap project [1]. The algorithms detailed in this paper are more memory and resource efficient making them suitable for use with bigger data sets and more easily trained SVMs.

Using a Discrete Hidden Markov Model Kernel for lip-based biometric identification

In this paper, a novel and effective lip-based biometric identification approach with the Discrete Hidden Markov Model Kernel (DHMMK) is developed. Lips are described by shape features (both geometrical and sequential) on two different grid layouts: rectangular and polar. These features are then specifically modeled by a DHMMK, and learnt by a support vector machine classifier. Our experiments are carried out in a ten-fold cross validation fashion on three different datasets, GPDS-ULPGC Face Dataset, PIE Face Dataset and RaFD Face Dataset. Results show that our approach has achieved an average classification accuracy of 99.8%, 97.13%, and 98.10%, using only two training images per class, on these three datasets, respectively. Our comparative studies further show that the DHMMK achieved a 53% improvement against the baseline HMM approach. The comparative ROC curves also confirm the efficacy of the proposed lip contour based biometrics learned by DHMMK. We also show that the performance of linear and RBF SVM is comparable under the frame work of DHMMK.

Pupillary and visual thresholds in young children as an index of population vitamin A status

A prototype scotopic sensitivity machine was used to evaluate pupillary and visual thresholds for 295 Indonesian children aged 1-5 y, most of whom were initially vitamin A-deficient. Subjects were tested 6 and 9 mo after receiving a high dose of vitamin A. A group of 136 older children was tested at 6 mo after dosing; all subjects underwent testing at 9 mo. After testing at 9 mo, children randomly received either a second high dose of vitamin A or placebo and were tested a final time 2 wk later. Children with abnormal pupillary thresholds had significantly higher relative dose responses (RDRs) (P < 0.01) and significantly lower serum retinol values (P = 0.05) than did normal children. The mean pupillary threshold rose (eg, retinal sensitivity fell) as vitamin A status deteriorated between 6 and 9 mo after initial dosing, and was significantly different from a group of normal American children tested previously (P < 0.001). After placebo-controlled dosing, the decline in pupillary and visual thresholds (rise in retinal sensitivity) was significant for children receiving vitamin A but not for children receiving placebo.

Responsiveness of dark-adaptation threshold to vitamin A and beta-carotene supplementation in pregnant and lactating women in Nepal.

BACKGROUND: Impaired dark adaptation occurs commonly in vitamin A deficiency. OBJECTIVE: We sought to examine the responsiveness of dark-adaptation threshold to vitamin A and beta-carotene supplementation in Nepali women. DESIGN: The dark-adapted pupillary response was tested in 298 pregnant women aged 15-45 y in a placebo-controlled trial of vitamin A and beta-carotene; 131 of these women were also tested at 3 mo postpartum. Results were compared with those for 100 nonpregnant US women of similar age. The amount of light required for pupillary constriction was recorded after bleaching and dark adaptation. RESULTS: Pregnant women receiving vitamin A had better dark-adaptation thresholds (-1.24 log cd/m(2)) than did those receiving placebo (-1.11 log cd/m(2); P: = 0. 03) or beta-carotene (-1.13 log cd/m(2); P: = 0.05) (t tests with Bonferroni correction). Dark-adaptation threshold was associated with serum retinol concentration in pregnant women receiving placebo (P: = 0.001) and in those receiving beta-carotene (P: = 0.003) but not in those receiving vitamin A. Among women receiving placebo, mean dark-adaptation thresholds were better during the first trimester (-1.23 log cd/m(2)) than during the second and third trimesters (-1.03 log cd/m(2); P: = 0.02, t test). The mean threshold of nonpregnant US women (-1.35 log cd/m(2)) was better than that of all 3 Nepali groups (P: < 0.001, t test, for all 3 groups). CONCLUSIONS: During pregnancy, pupillary dark adaptation was strongly associated with serum retinol concentration and improved significantly in response to vitamin A supplementation. This noninvasive testing technique is a valid indicator of population vitamin A status in women of reproductive age.

Comparison of anterior ocular biometry between optical low-coherence reflectometry and anterior segment optical coherence tomography in an adult Chinese population.

PURPOSE: To evaluate the agreement between optical low-coherence reflectometry (OLCR) and anterior segment optical coherence tomography (AS-OCT) for biometry of the anterior segment. SETTING: State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China. DESIGN: Evaluation of diagnostic technology. METHODS: A series of OLCR (Lenstar LS 900) and AS-OCT measurements of the anterior segment were taken for consecutive subjects aged 35 years and older in a population-based study. The differences and correlations between the 2 methods of ocular biometry were assessed. Agreement was calculated as the 95% limits of agreement (LoA). RESULTS: The mean age of the 776 subjects was 55.2 years ± 12.0 (SD); 54.6% were women. The mean central corneal thickness (CCT) was smaller with OLCR than with AS-OCT (537.84 ± 31.46 μm versus 559.39 ± 32.02 μm) as was anterior chamber depth (ACD) (2.60 ± 0.37 mm versus 2.72 ± 0.37 mm) and anterior chamber width (ACW) (11.76 ± 0.47 mm versus 12.04 ± 0.55 mm) (all P<.001). The 95% LoA between the 2 instruments were -44.80 to 1.71 μm for CCT, -0.17 to -0.06 mm for ACD, and -1.28 to 0.72 mm for ACW. CONCLUSION: Optical low-coherence reflectometry and AS-OCT yielded potentially interchangeable ACD measurements, while the CCT and ACW measurements acquired by the 2 devices showed clinically significant differences.

Modelling the fresh properties of self-compacting concrete using support vector machine approach

The main objective of the study presented in this paper was to investigate the feasibility using support vector machines (SVM) for the prediction of the fresh properties of self-compacting concrete. The radial basis function (RBF) and polynomial kernels were used to predict these properties as a function of the content of mix components. The fresh properties were assessed with the slump flow, T50, T60, V-funnel time, Orimet time, and blocking ratio (L-box). The retention of these tests was also measured at 30 and 60 min after adding the first water. The water dosage varied from 188 to 208 L/m3, the dosage of superplasticiser (SP) from 3.8 to 5.8 kg/m3, and the volume of coarse aggregates from 220 to 360 L/m3. In total, twenty mixes were used to measure the fresh state properties with different mixture compositions. RBF kernel was more accurate compared to polynomial kernel based support vector machines with a root mean square error (RMSE) of 26.9 (correlation coefficient of R2 = 0.974) for slump flow prediction, a RMSE of 0.55 (R2 = 0.910) for T50 (s) prediction, a RMSE of 1.71 (R2 = 0.812) for T60 (s) prediction, a RMSE of 0.1517 (R2 = 0.990) for V-funnel time prediction, a RMSE of 3.99 (R2 = 0.976) for Orimet time prediction, and a RMSE of 0.042 (R2 = 0.988) for L-box ratio prediction, respectively. A sensitivity analysis was performed to evaluate the effects of the dosage of cement and limestone powder, the water content, the volumes of coarse aggregate and sand, the dosage of SP and the testing time on the predicted test responses. The analysis indicates that the proposed SVM RBF model can gain a high precision, which provides an alternative method for predicting the fresh properties of SCC.

k-fold Subsampling based Sequential Backward Feature Elimination

We present a new wrapper feature selection algorithm for human detection. This algorithm is a hybrid featureselection approach combining the benefits of filter and wrapper methods. It allows the selection of an optimalfeature vector that well represents the shapes of the subjects in the images. In detail, the proposed featureselection algorithm adopts the k-fold subsampling and sequential backward elimination approach, while thestandard linear support vector machine (SVM) is used as the classifier for human detection. We apply theproposed algorithm to the publicly accessible INRIA and ETH pedestrian full image datasets with the PASCALVOC evaluation criteria. Compared to other state of the arts algorithms, our feature selection based approachcan improve the detection speed of the SVM classifier by over 50% with up to 2% better detection accuracy.Our algorithm also outperforms the equivalent systems introduced in the deformable part model approach witharound 9% improvement in the detection accuracy

Are People Changing Address Less? An Analysis of Migration within England and Wales, 1971–2011, by Distance of Move

Expectations of migration and mobility steadily increasing in the longer term, which have a long currency in migration theory and related social science, are at odds with the latest US research showing a marked decline in internal migration rates. This paper reports the results of research that investigates whether England and Wales have experienced any similar change in recent decades. Using the Office for National Statistics Longitudinal Study (ONS-LS) of linked census records, it examines the evidence provided by its 10-year migration indicator, with particular attention to a comparison of the first and latest decades available, 1971-1981 and 2001-2011. This suggests that, as in the USA, there has been a marked reduction in the level of shorter-distance (less than 10km) moving that has involved almost all types of people. In contrast to this and to US experience, however, the propensity of people to make longer-distance address changes between decennial censuses has declined much less, largely corroborating the results of a companion study tracking the annual trend in rates of between-area migration since the 1970s (Champion and Shuttleworth, 2016).

Electron-impact excitation of Fe 4+ : an intermediate-coupling R -matrix calculation

For a number of years, there has been a major effort to calculate electron-impact excitation data for every ion stage of iron embodied by the ongoing efforts of the IRON project by Hummer et al (1993 Astron. Astrophys. 279 298). Due to the complexity of the targets, calculations for the lower stages of ionization have been limited to either intermediate-coupling calculations within the ground configurations or LS -coupling calculations of the ground and excited configurations. However, accurate excitation data between individual levels within both the ground and excited configurations of the low charge-state ions are urgently required for applications to both astrophysical and laboratory plasmas. Here we report on the results of the first intermediate-coupling R -matrix calculation of electron-impact excitation for Fe 4+ for which the close-coupling (CC) expansion includes not only those levels of the 3d 4 ground configuration, but also the levels of the 3d 3 4s, 3d 3 4p, 3d 3 4d and 3d 2 4s 2 excited configurations. With 359 levels in the CC expansion and over 2400 scattering channels for many of the J Π partial waves, this represents the largest electron–ion scattering calculation to date and it was performed on massively parallel computers using a recently developed set of relativistic parallel R -matrix programs.

Photoionization cross-sections for Fe II

The LS R-matrix method was used to compute new photoionization cross sections for Fe II. Results are compared with available experimental data and with previous calculations of the cross section. We also present the first fine-structure photoionization data for this ion obtained with the fully-relativistic DARC codes.