Binary image steganographic techniques classification based on multi-class steganalysis

In this paper, we propose a new multi-class steganalysis for binary image. The proposed method can identify the type of steganographic technique used by examining on the given binary image. In addition, our proposed method is also capable of differentiating an image with hidden message from the one without hidden message. In order to do that, we will extract some features from the binary image. The feature extraction method used is a combination of the method extended from our previous work and some new methods proposed in this paper. Based on the extracted feature sets, we construct our multi-class steganalysis from the SVM classifier. We also present the empirical works to demonstrate that the proposed method can effectively identify five different types of steganography.

Can ginger ameliorate chemotherapy-induced nausea? Protocol of a randomized double blind, placebo-controlled trial

Background Preliminary research shows ginger may be an effective adjuvant treatment for chemotherapy-induced nausea and vomiting but significant limitations need to be addressed before recommendations for clinical practice can be made. Methods/Design In a double–blinded randomised-controlled trial, chemotherapy-naïve patients will be randomly allocated to receive either 1.2 g of a standardised ginger extract or placebo per day. The study medication will be administrated as an adjuvant treatment to standard anti-emetic therapy and will be divided into four capsules per day, to be consumed approximately every 4 hours (300 mg per capsule administered q.i.d) for five days during the first three cycles of chemotherapy. Acute, delayed, and anticipatory symptoms of nausea and vomiting will be assessed over this time frame using a valid and reliable questionnaire, with nausea symptoms being the primary outcome. Quality of life, nutritional status, adverse effects, patient adherence, cancer-related fatigue, and CINV-specific prognostic factors will also be assessed. Discussion Previous trials in this area have noted limitations. These include the inconsistent use of standardized ginger formulations and valid questionnaires, lack of control for anticipatory nausea and prognostic factors that may influence individual CINV response, and the use of suboptimal dosing regimens. This trial is the first to address these issues by incorporating multiple unique additions to the study design including controlling for CINV-specific prognostic factors by recruiting only chemotherapy-naïve patients, implementing a dosing schedule consistent with the pharmacokinetics of oral ginger supplements, and independently analysing ginger supplements before and after recruitment to ensure potency. Our trial will also be the first to assess the effect of ginger supplementation on cancer-related fatigue and nutritional status. Chemotherapy-induced nausea and vomiting are distressing symptoms experienced by oncology patients; this trial will address the significant limitations within the current literature and in doing so, will investigate the effect of ginger supplementation as an adjuvant treatment in modulating nausea and vomiting symptoms. Trial registration

Detection and quantification of tear phospholipids and cholesterol in contact lens deposits : the effect of contact lens material and lens care solution

PURPOSE. To examine the deposition of tear phospholipids and cholesterol onto worn contact lenses and the effect of lens material and lens care solution. METHODS. Lipids were extracted from tears and worn contact lenses using 2:1 chloroform: Methanol and the extract washed with aqueous ammonium acetate, before analysis by electrospray ionization tandem mass spectrometry (ESI-MS/MS). RESULTS. Twenty-three molecular lipids from the sphingomyelin (SM) and phosphatidylcholine (PC) classes were detected in tears, with total concentrations of each class determined to be 5 ± 1 pmol/μL (~3.8 μg/mL) and 6 ± 1 pmol/μL (~ 4.6μg/mL), respectively. The profile of individual phospholipids in both of these classes was shown to be similar in contact lens deposits. Deposition of representative polar and nonpolar lipids were shown to be significantly higher on senofilcon A contact lenses, with ~59 ng/lens SM, 195 ng/lens PC, and 9.9 μg/lens cholesterol detected, whereas balafilcon A lens extracts contained ~19 ng/lens SM, 19 ng/lens PC, and 3.9 μg/lens cholesterol. Extracts from lenses disinfected and cleaned with two lens care solutions showed no significant differences in total PC and SM concentrations; however, a greater proportion of PC than SM was observed, compared with that in tears. CONCLUSIONS. Phospholipid deposits extracted from worn contact lenses show a molecular profile similar to that in tears. The concentration of representative polar and nonpolar lipids deposited onto contact lenses is significantly affected by lens composition. There is a differential efficacy in the removal of PC and SM with lens care solutions.

Features-pooling blind jpeg image steganalysis

In this research, we introduce a new blind steganalysis in detecting grayscale JPEG images. Features-pooling method is employed to extract the steganalytic features and the classification is done by using neural network. Three different steganographic models are tested and classification results are compared to the five state-of-the-art blind steganalysis.

Fault diagnosis of low speed bearing based on acoustic emission signal and multi-class relevance vector machine

This study presents an acoustic emission (AE) based fault diagnosis for low speed bearing using multi-class relevance vector machine (RVM). A low speed test rig was developed to simulate the various defects with shaft speeds as low as 10 rpm under several loading conditions. The data was acquired using anAEsensor with the test bearing operating at a constant loading (5 kN) andwith a speed range from20 to 80 rpm. This study is aimed at finding a reliable method/tool for low speed machines fault diagnosis based on AE signal. In the present study, component analysis was performed to extract the bearing feature and to reduce the dimensionality of original data feature. The result shows that multi-class RVM offers a promising approach for fault diagnosis of low speed machines.

The identification and rapid extraction of hydrocarbons from Nicotiana glauca : A potential advanced renewable biofuel source

Declining fossil fuels reserves, a need for increased energy security and concerns over carbon emissions from fossil fuel use are the global drivers for alternative, renewable, biosources of fuels and chemicals. In the present study the identification of long chain (C29–C33) saturated hydrocarbons from Nicotiana glauca leaves is reported. The occurrence of these hydrocarbons was detected by gas chromatography–mass spectrometry (GC–MS) and identification confirmed by comparison of physico-chemical properties displayed by the authentic standards available. A simple, robust procedure was developed to enable the generation of an extract containing a high percentage of hydrocarbons (6.3% by weight of dried leaf material) higher than previous reports in other higher plant species consequently, it is concluded that N. glauca could be a crop of greater importance than previously recognised for biofuel production. The plant can be grown on marginal lands, negating the need to compete with food crops or farmland, and the hydrocarbon extract can be produced in a non-invasive manner, leaving remaining biomass intact for bioethanol production and the generation of valuable co-products.

Random Gabor based templates for facial expression recognition in images with facial occlusion

Robust facial expression recognition (FER) under occluded face conditions is challenging. It requires robust algorithms of feature extraction and investigations into the effects of different types of occlusion on the recognition performance to gain insight. Previous FER studies in this area have been limited. They have spanned recovery strategies for loss of local texture information and testing limited to only a few types of occlusion and predominantly a matched train-test strategy. This paper proposes a robust approach that employs a Monte Carlo algorithm to extract a set of Gabor based part-face templates from gallery images and converts these templates into template match distance features. The resulting feature vectors are robust to occlusion because occluded parts are covered by some but not all of the random templates. The method is evaluated using facial images with occluded regions around the eyes and the mouth, randomly placed occlusion patches of different sizes, and near-realistic occlusion of eyes with clear and solid glasses. Both matched and mis-matched train and test strategies are adopted to analyze the effects of such occlusion. Overall recognition performance and the performance for each facial expression are investigated. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the high robustness and fast processing speed of our approach, and provide useful insight into the effects of occlusion on FER. The results on the parameter sensitivity demonstrate a certain level of robustness of the approach to changes in the orientation and scale of Gabor filters, the size of templates, and occlusions ratios. Performance comparisons with previous approaches show that the proposed method is more robust to occlusion with lower reductions in accuracy from occlusion of eyes or mouth.

Prenylated Alkylbisphenols from Grevillea whiteana

Eleven new bisresorcinols including four mixtures each of two isomers and one resorcinol/phloroglucinol derivative, together with five known resorcinols have been isolated from the ethyl acetate extract of sterns of Grevillea whiteana. The new Compounds were identified as 4-(3-hydroxy-3-methylbutyl)grebustol-B (10a), 4'-(3-hydroxy-3-methylbutyl)grebustol-B (10b), 4-(4-hydroxy-3-methylbutyl)grebustol-B (2a) and 4'-(4-hydroxy-3-methylbutyl) rebustol-B (2b), 2,2-dimethyldihydropyrano grebustol-B (11a) and iso-2,2-dimethyldihydropyranogrebustol-B (11b), 2,2-dimethyl-3 xi-hydroxydihydropyranogrebustol-B (7a) and iso-2,2-dimethyl-3 xi-hydroxydihydropyranogrebustol-B (7b), 15-(2-(4-hydroxy-3-methylbutyl)-resorcinol-5-yl)-1-(phloroglucinolyl )-9(Z)pentadecen-one (whiteanone) (4), 5,5'-(hexadecan-diyl)bisresorcinol (12) and 2-methyl-5,5'-(8(Z)hexadecen-1,16-diyl)bisresorcinol (9). This is the first record of pyranobisresorcinols in the genus and the first report of a phloroglucinol terminal Phenolic unit in any Grevillea species.

Prenylated bisresorcinols from Grevillea floribunda

Seven new bisresorcinol derivatives, together with four known resorcinols. have been isolated from the ethyl acetate extract of the sterns of Grevillea floribunda. Five of the new compounds (floribol A-E) were characterized as bisnorstriatol derivatives Substituted at C-2 of both resorcinol units with variously modified prenyl (3-methylbut-2-enyl) units. The remaining two new compounds are similarly Substituted derivatived of grebustol-B. (c) 2008 Phytochemical Society of Europe Published by Elsevier B.V. All rights reserved.

Treatment plan complexity metrics for predicting IMRT pre-treatment quality assurance results

The planning of IMRT treatments requires a compromise between dose conformity (complexity) and deliverability. This study investigates established and novel treatment complexity metrics for 122 IMRT beams from prostate treatment plans. The Treatment and Dose Assessor software was used to extract the necessary data from exported treatment plan files and calculate the metrics. For most of the metrics, there was strong overlap between the calculated values for plans that passed and failed their quality assurance (QA) tests. However, statistically significant variation between plans that passed and failed QA measurements was found for the established modulation index and for a novel metric describing the proportion of small apertures in each beam. The ‘small aperture score’ provided threshold values which successfully distinguished deliverable treatment plans from plans that did not pass QA, with a low false negative rate.

Prostate radiotherapy treatment plan quality : effects of hip prostheses

Introduction This study aimed to examine the geometric and dosimetric results when radiotherapy treatment plans are designed for prostate cancer patients with hip prostheses. Methods Ten EBRT treatment plans for localised prostate cancer, in the presence of hip prostheses, were analysed and compared with a reference set of 196 treatment plans for localised prostate cancer in patients without prostheses. Crowe et al.’s TADA code [1] was used to extract treatment plan parameters and evaluate doses to target volumes and critical structures against recommended goals [2] and constraints [3, 4]. Results The need to avoid transmitting the radiation beam through the hip prostheses limited the range of gantry angles available for use in both the rotational (VMAT) and the non-rotational (3DCRT and IMRT) radiotherapy treatments. This geometric limitation (exemplified in the VMAT data shown in Fig. 1) reduced the overall quality of the treatment plans for patients with prostheses compared to the reference plans. All plans with prostheses failed the PTV dose homogeneity requirement [2], whereas only 4 % of the plans without prostheses failed this test. Several treatment plans for patients with hip prostheses also failed the QUANTEC requirements that less than 50 % of the rectum receive 50 Gy and less than 35 % of the rectum receive 60 Gy to keep the grade 3 toxicity rate below 10 % [3], or the Hansen and Roach requirement that less than 25 % of the bladder receive 75 Gy [4]. Discussion and conclusions The results of this study exemplify the difficulty of designing prostate radiotherapy treatment plans, where beams provide adequate doses to targeted tissues while avoiding nearby organs at risk, when the presence of hip prostheses limits the available treatment geometries. This work provides qualitative evidence of the compromised dose distributions that can result, in such cases.

Accelerometer data reduction : a comparison of four reduction algorithms on select outcome variables

Purpose Accelerometers are recognized as a valid and objective tool to assess free-living physical activity. Despite the widespread use of accelerometers, there is no standardized way to process and summarize data from them, which limits our ability to compare results across studies. This paper a) reviews decision rules researchers have used in the past, b) compares the impact of using different decision rules on a common data set, and c) identifies issues to consider for accelerometer data reduction. Methods The methods sections of studies published in 2003 and 2004 were reviewed to determine what decision rules previous researchers have used to identify wearing period, minimal wear requirement for a valid day, spurious data, number of days used to calculate the outcome variables, and extract bouts of moderate to vigorous physical activity (MVPA). For this study, four data reduction algorithms that employ different decision rules were used to analyze the same data set. Results The review showed that among studies that reported their decision rules, much variability was observed. Overall, the analyses suggested that using different algorithms impacted several important outcome variables. The most stringent algorithm yielded significantly lower wearing time, the lowest activity counts per minute and counts per day, and fewer minutes of MVPA per day. An exploratory sensitivity analysis revealed that the most stringent inclusion criterion had an impact on sample size and wearing time, which in turn affected many outcome variables. Conclusions These findings suggest that the decision rules employed to process accelerometer data have a significant impact on important outcome variables. Until guidelines are developed, it will remain difficult to compare findings across studies

Ozone-Induced Dissociation on a Modified Tandem Linear Ion-Trap : Observations of Different Reactivity for Isomeric Lipids

Ozone-induced dissociation (OzID) exploits the gas-phase reaction between mass-selected lipid ions and ozone vapor to determine the position(s) of unsaturation In this contribution, we describe the modification of a tandem linear ion-trap mass spectrometer specifically for OzID analyses wherein ozone vapor is supplied to the collision cell This instrumental configuration provides spatial separation between mass-selection, the ozonolysis reaction, and mass-analysis steps in the OzID process and thus delivers significant enhancements in speed and sensitivity (ca 30-fold) These improvements allow spectra revealing the double-bond position(s) within unsaturated lipids to be acquired within 1 s significantly enhancing the utility of OzID in high-throughput lipidomic protocols The stable ozone concentration afforded by this modified instrument also allows direct comparison of relative reactivity of isomeric lipids and reveals reactivity trends related to (1) double-bond position, (2) substitution position on the glycerol backbone, and (3) stereochemistry For cis- and trans-isomers, differences were also observed in the branching ratio of product ions arising from the gas-phase ozonolysis reaction, suggesting that relative ion abundances could be exploited as markers for double-bond geometry Additional activation energy applied to mass-selected lipid ions during injection into the collision cell (with ozone present) was found to yield spectra containing both OzID and classical-CID fragment ions This combination CID-OzID acquisition on an ostensibly simple monounsaturated phosphatidylcholine within a cow brain lipid extract provided evidence for up to four structurally distinct phospholipids differing in both double-bond position and sn-substitution U Am Soc Mass Spectrom 2010, 21, 1989-1999) (C) 2010 American Society for Mass Spectrometry

Matching image sets via adaptive multi convex hull

Traditional nearest points methods use all the samples in an image set to construct a single convex or affine hull model for classification. However, strong artificial features and noisy data may be generated from combinations of training samples when significant intra-class variations and/or noise occur in the image set. Existing multi-model approaches extract local models by clustering each image set individually only once, with fixed clusters used for matching with various image sets. This may not be optimal for discrimination, as undesirable environmental conditions (eg. illumination and pose variations) may result in the two closest clusters representing different characteristics of an object (eg. frontal face being compared to non-frontal face). To address the above problem, we propose a novel approach to enhance nearest points based methods by integrating affine/convex hull classification with an adapted multi-model approach. We first extract multiple local convex hulls from a query image set via maximum margin clustering to diminish the artificial variations and constrain the noise in local convex hulls. We then propose adaptive reference clustering (ARC) to constrain the clustering of each gallery image set by forcing the clusters to have resemblance to the clusters in the query image set. By applying ARC, noisy clusters in the query set can be discarded. Experiments on Honda, MoBo and ETH-80 datasets show that the proposed method outperforms single model approaches and other recent techniques, such as Sparse Approximated Nearest Points, Mutual Subspace Method and Manifold Discriminant Analysis.

Improved image set classification via joint sparse approximated nearest subspaces

Existing multi-model approaches for image set classification extract local models by clustering each image set individually only once, with fixed clusters used for matching with other image sets. However, this may result in the two closest clusters to represent different characteristics of an object, due to different undesirable environmental conditions (such as variations in illumination and pose). To address this problem, we propose to constrain the clustering of each query image set by forcing the clusters to have resemblance to the clusters in the gallery image sets. We first define a Frobenius norm distance between subspaces over Grassmann manifolds based on reconstruction error. We then extract local linear subspaces from a gallery image set via sparse representation. For each local linear subspace, we adaptively construct the corresponding closest subspace from the samples of a probe image set by joint sparse representation. We show that by minimising the sparse representation reconstruction error, we approach the nearest point on a Grassmann manifold. Experiments on Honda, ETH-80 and Cambridge-Gesture datasets show that the proposed method consistently outperforms several other recent techniques, such as Affine Hull based Image Set Distance (AHISD), Sparse Approximated Nearest Points (SANP) and Manifold Discriminant Analysis (MDA).