Regular Sample Research Articles

Performance Analysis of Data Hiding in MPEG-4 AAC Audio

A high capacity data hiding technique was developed for compressed digital audio. As perceptual audio coding has become the accepted technology for storage and transmission of audio signals, compressed audio information hiding enables robust, imperceptible transmission of data within audio signals, thus allowing valuable information to be attached to the content, such as the song title, lyrics, composer's name, and artist or property rights related data. This paper describes simultaneous low bitrate encoding and information hiding for highly compressed audio signals. The information hiding is implemented in the quantization process of the audio content which improves robustness, signal quality, and security. The imperceptibility of the embedded data is ensured based on the masking property of the human auditory system (HAS). The robustness and security are evaluated by various attacking algorithms. Tests with an extended MPEG4 advanced audio coding (AAC) encoder confirm that the method is robust to the regular and singular groups method (RS) and sample pair analysis (SPA) attacks as well as other statistical steganalysis method attacks.

The Utilization of a Biopsy Needle to Obtain Small Muscle Tissue Specimens to Analyze the Gene and Protein Expression

Recent analytical methods such as real-time polymerase chain reaction (PCR) and Western blotting have now enabled us to analyze the gene and protein expression from small amounts of tissue. A fine needle muscle biopsy is thus expected to obtain a minimally sufficient amount of skeletal muscle to make a successful analysis. As a result, we used this fine needle muscle biopsy technique to obtain muscle tissue specimens from the vastus lateral muscle in 40 participants. The amount of tissue obtained by the fine needle was 5.2 +/- 3.2 mg (mean +/- standard deviation). The total RNA extracted was 3.0 +/- 1.4 microg and the total protein extracted was 2203 +/- 1541 microg. Furthermore, the skeletal muscle tissue specimens obtained by the regular needle technique and blood sample were used as the control. Those specimens were used to measure the gene expression of beta-myosin heavy chain slow (beta-MHC slow) by real-time PCR and the protein expression of monocalboxylate transporter 1 (MCT-1) by Western blotting. Beta-MHC slow gene expression was detected in both samples obtained by a fine and a regular needle biopsy, but not in a blood sample. Furthermore, the MCT-1 protein was detected in samples obtained by a fine needle muscle biopsy. These results indicated that the fine needle muscle biopsy is therefore a useful technique to obtain skeletal muscle specimens at least to analyze the gene and protein expression.

A newly identified splice site mutation inZMPSTE24causes restrictive dermopathy in the Middle East

Restrictive dermopathy (RD) is a severe neonatal inherited skin syndrome of which children die shortly after birth. Clinical features include intrauterine growth retardation, taut translucent and easily eroded skin, multiple joint ankylosis and distinct facial features. RD is usually caused by homozygous or compound heterozygous mutations in ZMPSTE24, predicted to cause loss of function of the encoded zinc metalloproteinase STE24. ZMPSTE24 is essential for the processing of the nuclear intermediate filament protein prelamin A. We report two distantly related children from the United Arab Emirates with RD. Remarkably, they lived up to 2 months, suggesting some residual function of the mutant protein. We sought to confirm the diagnosis by thorough microscopic analysis of patient skin, to identify the causative mutation and to study its functional consequences. A skin biopsy was obtained and processed for light and electron microscopy. Peripheral blood leucocytes were used for DNA and RNA isolation, and detection of prelamin A by immunofluorescence. Analysis of the skin confirmed the earlier reported densely packed collagen bundles and lack of elastin fibres. In both patients a homozygous splice site mutation c.627+1G>C in ZMPSTE24 was identified. Analysis of the ZMPSTE24 mRNA revealed an in-frame exon 5 skipping. Accumulation of prelamin A could be detected at the nuclear envelope of patient blood lymphocytes. We thus report the first splice site mutation in ZMPSTE24, which is likely to be a founder mutation in the United Arab Emirates. The accumulation of prelamin A at the nuclear periphery is consistent with defective ZMPSTE24 function. Interestingly, a regular blood sample can be used to investigate prelamin A accumulation.

Message estimation for universal steganalysis using multi-classification support vector machine

To prevent misusing of the steganography from the terrorists, effective steganalysis schemes which discriminate the stego-images from suspicious images are necessary. Some steganalysis methods can accurately estimate the length of embedded messages but they are only useful in the pre-defined condition. Active steganalysis methods are powerful in length estimation such as regular singular (RS) and sample pairs analysis (SPA) steganalysis schemes, but they would become invalid in frequency domain. Passive steganalysis methods may discriminate stego-images from suspicious images in spatial and frequency domains such as Lyu and Fraid's steganalysis scheme, but they could not estimate the length of hidden messages. Although length estimation has been discussed in the active steganalysis methods for a while, it is a novel study in passive steganalysis method. We improve the Lyu and Fraid's universal steganalysis scheme and design an efficient length estimation policy in passive steganalysis methods. Experimental results demonstrate the efficiency and practicability of the proposed universal steganalysis scheme.

Some Results on the Spatial Breakdown Point of Robust Point Estimates of the Variogram

The effect of outliers on estimates of the variogram depends on how they are distributed in space. The ‘spatial breakdown point’ is the largest proportion of observations which can be drawn from some arbitrary contaminating process without destroying a robust variogram estimator, when they are arranged in the most damaging spatial pattern. A numerical method is presented to find the spatial breakdown point for any sample array in two dimensions or more. It is shown by means of some examples that such a numerical approach is needed to determine the spatial breakdown point for two or more dimensions, even on a regular square sample grid, since previous conjectures about the spatial breakdown point in two dimensions do not hold. The ‘average spatial breakdown point’ has been used as a basis for practical guidelines on the intensity of contaminating processes that can be tolerated by robust variogram estimators. It is the largest proportion of contaminating observations in a data set such that the breakdown point of the variance estimator used to obtain point estimates of the variogram is not exceeded by the expected proportion of contaminated pairs of observations over any lag. In this paper the behaviour of the average spatial breakdown point is investigated for cases where the contaminating process is spatially dependent. It is shown that in two dimensions the average spatial breakdown point is 0.25. Finally, the ‘empirical spatial breakdown point’, a tool for the exploratory analysis of spatial data thought to contain outliers, is introduced and demonstrated using data on metal content in the soils of Sheffield, England. The empirical spatial breakdown point of a particular data set can be used to indicate whether the distribution of possible contaminants is likely to undermine a robust variogram estimator.

The Effects of the Tensile Properties of Cup-stand Materials on Clothing Pressure and Comfort of Push-up Type Brassieres

This study aims to clarify the influence of cup-stand materials on clothing pressure, compressive feeling, silhouette evaluation and physiological responses (heart rate and blood pressure). We conducted wearing tests of pushup type brassieres of which cup-stand materials have different tensile resistances. This includes a regular type brassiere with a short cup-stand as control sample. Clothing pressure and compressive feeling that measured and evaluated in a sitting position depended on the tensile properties of the total bottom section of brassieres. Brassieres where compressive feeling was lower were more comfortable. Variable coefficients in clothing pressure during a stepping exercise depended on the tensile properties of the cup-stand section. When wearing brassieres with lower tensile resistance at the cup-stand section subjects had lower physiological responses (the heart rate and double product : heart rate×systolic pressure) during and after exercise. A decrease in body size when wearing the push-up brassieres was larger than that of the regular sample, therefore we concluded that the push-up effect depended on the length of the cup-stand. The brassieres with higher tensile resistance and a longer cup-stand could obtain a better silhouette evaluation, but the evaluations of all push-up type brassieres were better than that of the regular one. Within the push-up type brassieres used, a brassiere without bust-under tape (hem type) at the cup-stand section had the lowest clothing pressure and the subjects had the lowest physiological responses. It was also most comfortable.

Self-Report Problem Scales and Subscales and Behavioral Ratings Provided by Peers

The relationship between children's self-reported problems on the Personality Inventory for Youth (PIY) and peer descriptors derived from the Pupil Evaluation Inventory was examined in a regular education sample of 156 children in fourth through eighth grade. The relative contributions of the PIY scales and subscales to the prediction of peer ratings were compared. Peer ratings of withdrawn, disruptive, and prosocial behaviors were substantially correlated to self-report problem scales made up of logically related content. The addition of more content-specific PIY subscales contributed to the prediction made by PIY scales of peer-reported disruptive behaviors and withdrawal.

Identifying Cognitively Gifted Minority Students in Preschool

Preschool children were administered a screening battery consisting of nine different cognitive tasks. The participants were tracked in the public school database. Based on the children’s first-grade educational status, 2 groups were formed: one consisting of children who were in regular education and the other composed of children who were in the gifted/talented program. The children’s preschool screening scores, summed over both the identification-tasks subset and the generating-tasks subset, enabled the identification of high-performing outliers from the regular education sample who performed very well compared to the school-identified gifted sample. However, a majority of minority students among the high-performing outliers were only identified with the generating measure. The superior first-grade achievement performance of 5 of these 7 and the finding that 3 of the 7 had been placed in the gifted program in second grade, attested to the effectiveness of this measure for identifying cognitively gifted minority preschoolers.

Enhancement of n-Hexane Cracking Activity over Modified ZSM-12 Zeolites

A series of ZSM-12 samples were prepared by calcining them at different temperatures that are much higher than what is normally used. The catalytic activities of these samples were tested using cracking of n-hexane at 400 °C. It was found that the cracking activities of samples calcined at certain temperatures were unusually high: 3−4 times greater than that of the regular sample, which was calcined at 550 °C. Interestingly, this enhanced activity was observed at two separate, relatively narrow, ranges of temperatures: one around 650 °C and the other around 800 °C. Brönsted and Lewis acid sites attributed to extraframework cationic aluminum were quantified with Fourier transform infrared of adsorbed pyridine. The Lewis/Brönsted ratios of the enhanced-activity samples were high compared those of the low-activity samples; the trend in variation of the Lewis/Brönsted ratios of the samples with calcination temperature closely mirrored the trend observed for the catalytic activities. This is an indication that there is a synergistic interaction between the Brönsted and Lewis acid sites that is responsible for the enhanced cracking activity.

The range of protists in Mono Lake, a hypersaline soda lake in the eastern sierras

In spite of the controversies surrounding the environmental deterioration of Mono Lake, and the significant amount of research being done on this remarkably productive body of water, nobody has ever attempted to survey the protists that live beneath its surface. Beginning in July of 2003, we have been trying to remedy this situation and we spent 2 months there studying the protistan species that reside in its waters and since then have been receiving regular sample collections for analysis. Based on the metazoan eukaryotes that live in this lake, which include only Artemia monica, Ephydra hians, rare rotifers and a nematode, we were warned to expect the lake to be depauperate of protists as well. However, we are happy to report that, while not as rich in species as most freshwater lakes, Mono Lake does support a robust population of phagotrophic and heterotrophic protozoa in addition to its many species of unicellular algae, including diatoms. It contains ciliate species representing at least the genera Cyclidium, Frontonia, Lacrymaria, Litonotus, Euplotes and Aspidisca, and the stalked suctorian Tokophrya. Additionally, there are species representing the heliozoa, helioflagellates, choanoflagellates, Pseudobodo, Cercomonas and Chilomastix, among other flagellates. The gymnamoebae are represented by Vanella, Nuclearia, Mayorella and Hartmanella, and, from the Heterolobosea, probable Vahlkampfia and Gruberella species. Micrographs of many of these species will be presented. Work on these species is still very much in its preliminary stages and a more detailed analysis and identification of the protists found in this extreme environment is advancing.This work was partially supported by an NSF grant (MCB 99‐77901) to Robert Jellison.

Analysis of errors of derived slope and aspect related to DEM data properties

One of the obvious sources of errors in digital terrain analysis (DTA) algorithms is that introduced by raster data structure employed by a digital elevation model (DEM). Because of its regular sample space and orientation, the DTA results often show significant octant ‘bias’, presenting obvious visual and numerical error patterns. Moreover, other DEM data properties may also introduce errors in slope and aspect computation, such as data precision and spatial resolution (i.e. grid interval). This paper reports an investigation on the accuracy of algorithms that derive slope and aspect measures from grid DEM. A quantitative methodology has been developed for objective and data-independent assessment of errors generated from the algorithms that extract surface morphological parameters such as slope and aspect from grid DEM. The generic approach is to use artificial surfaces that can be described by a mathematical model, thus the ‘true’ output value can be pre-determined to avoid uncertainty caused by uncontrollable data errors. Two mathematical surfaces were generated based on ellipsoid (representing convex slopes) and Gauss synthetic surface (representing complex slopes), and the theoretical ‘true’ value of the slope and aspect at any given point on the surfaces could be computed using mathematical inference. Based on these models, tests were made on the results from a number of algorithms for slope and aspect computation. Analysis has been undertaken to find out the spatial and statistical patterns of error distribution so that the influence of data precision, grid resolution, grid orientation and surface complexity can be quantified.

Analysis of errors of derived slope and aspect related to DEM data properties

One of the obvious sources of errors in digital terrain analysis (DTA) algorithms is that introduced by raster data structure employed by a digital elevation model (DEM). Because of its regular sample space and orientation, the DTA results often show significant octant ‘bias’, presenting obvious visual and numerical error patterns. Moreover, other DEM data properties may also introduce errors in slope and aspect computation, such as data precision and spatial resolution (i.e. grid interval). This paper reports an investigation on the accuracy of algorithms that derive slope and aspect measures from grid DEM. A quantitative methodology has been developed for objective and data-independent assessment of errors generated from the algorithms that extract surface morphological parameters such as slope and aspect from grid DEM. The generic approach is to use artificial surfaces that can be described by a mathematical model, thus the ‘true’ output value can be pre-determined to avoid uncertainty caused by uncontrollable data errors. Two mathematical surfaces were generated based on ellipsoid (representing convex slopes) and Gauss synthetic surface (representing complex slopes), and the theoretical ‘true’ value of the slope and aspect at any given point on the surfaces could be computed using mathematical inference. Based on these models, tests were made on the results from a number of algorithms for slope and aspect computation. Analysis has been undertaken to find out the spatial and statistical patterns of error distribution so that the influence of data precision, grid resolution, grid orientation and surface complexity can be quantified.

Resource classification – a case study from the Joffre-hosted iron ore of BHP Billiton's Mount Whaleback operations

It is recognised by the current JORC (1999) code that resource classification involves the interaction of numerous qualitative and quantitative criteria such as data quality, geological continuity and grade continuity. No prescribed criteria and rules will work for all situations or even between different ore types within the same deposit. Also, these criteria and rules are sometimes applied without a clear understanding of their appropriateness, accuracy or correct implementation. For these reasons, case studies are useful to evaluate and compare criteria commonly used to assist in resource classification. In this paper, blasthole data from a selected area of Joffre Member hosted ore of the Brockman Iron Formation at the Mount Whaleback orebody are used as the basis of a case study for the above-mentioned purposes.Iron grade, in percent, is interpolated from a blasthole dataset into a block model using ordinary kriging. Samples are then removed from this blasthole dataset to produce a random sample grid, a semi-random sample grid and a regular sample grid. Block iron grades are obtained using nearest neighbour,inverse distance squared and ordinary kriging estimation methods and sequential gaussian simulation, using these three blasthole data subsets as inputs. This provides three groups of estimates and one group of simulations with the ordinary kriging estimate based on the complete blasthole dataset being considered to represent the true estimate of iron grades. Also generated during this process are measurements of the expected error for each block grade. These measures of error range from the simple, such as drill spacing, through to more advanced methodologies such as kriging efficiency and simulation. The grade and error determined from estimation and simulation are then compared to the true grade and true error using graphs and statistics. In order of increasing accuracy, the block grade determination methods were nearest neighbour, inverse distance weighting, ordinary kriging and finally the average of multiple simulations. Simulation in some instances doubled the accuracy of individual block grades when compared to nearest neighbour and inverse distance weighting estimates. It was found that many methodologies for determining the error of individual block grades performed equally well with only methods such as average drillhole spacing and classification by search ellipse pass number performing poorly. An approach on how to convert the above-mentioned error determinations of individual blocks into a meaningful JORC classification is also discussed.Although advanced non-linear resource estimates are applicable, most iron ore mines are still using relatively straightforward methods. The use of blasthole data and some simple linear estimation methods and simple linear-based error estimates makes this study repeatable for most iron ore sites and their resource geologists. This style of investigation is recommended as a useful approach for the competent person to apply to their deposit and thus better select, implement and understand the criteria used for resource classification and provide more consistency and confidence in the resource classification process.

Augmenting inventories with basal area points to achieve desired precision

An approximation to the variances of the regression and mean of ratios estimators for double sampling is presented that can be used to determine how many basal area points are needed to augment an existing inventory to achieve a desired precision. The approximation may also be used to determine the effective regular sample size to achieve equal precision to a double sample.

Spartan Gibbs Random Field Models for Geostatistical Applications

The inverse problem of determining the spatial dependence of random fields (inference of the spatial model) from experimental samples is a central issue in geostatistics. We propose a computationally efficient approach based on Spartan Gibbs random fields. Their probability density function depends on a small set of parameters that can be determined by matching sample constraints with corresponding model constraints based on the stochastic moments. We investigate a specific Spartan probability density with spatial dependence derived from generalized gradient and Laplacian operators, and we derive permissibility conditions for the model parameters. The optimal values of the model parameters are determined by minimizing a normalized metric measuring the "distance" between stochastic moments and the respective sample constraints. The computational complexity of the minimization depends on the number of parameters but not on the sample size. The computational complexity of the constraint calculation increases linearly with the sample size. In contrast, the classical variogram calculation is considerably less efficient and its complexity increases as the square of the sample size. We propose a numerical approach for inferring the Spartan model parameters and illustrate it using simulated (synthetic) samples for regular (lattice) and irregular sample distributions. Based on our analysis, Spartan Gibbs random fields provide computationally efficient spatial models, which are especially useful if the sample size is large or reliable estimation of the variogram is not possible. Estimation of the field values at unsampled positions, conditional simulations, anisotropic spatial dependence, and non-Gaussian probability densities are briefly discussed.

Artificial Neural Networks as a Method of Spatial Interpolation for Digital Elevation Models

This paper examines the performance of artificial neural networks (ANNs) as a method of spatial interpolation, when presented with irregular and regular samples of elevation data. The results of the ANN interpolation are compared with results obtained by kriging. Tests of spatial bias in the systematic errors contained in each of the neural network-derived DEMs were conducted using four attributes: slope, aspect, average direction and average distance from the nearest sampled value. Based on RMS and other evaluation measures, the accuracy of estimated DEMs from regular and irregular sample distributions using neural networks is lower than the accuracy level derived from kriging. The accuracy level of the ANN interpolators also decreases as the range of elevation values in DEMs increases. As reported in the literature, ANNs are approximate interpolators, and the pattern of under-prediction and over-prediction of elevation values in this study revealed that all estimated values fell within the range of sample elevations. Neural networks cannot predict values outside the range of elevation values contained in the sample, a property shared by other interpolators such as inverse weighted distance.

ESTABLISHMENT OF NEOCHETINA SPP.: THEIR PATTERN OF LOCAL DISPERSAL AND AGE STRUCTURE AT THE RELEASE SITE

Study on the distribution pattern and age structure ofNeochetina spp. (Coleoptera: Curculionidae) at the release site was conducted to know a) the distribution pattern of the weevil, b) its establishment status, c) its survival rate in the field, and d) relationship between the attack of the weevil and the fungus, Altemaria eichhorniae Nag Rag & Ponappa (Hyphomycetes), in causing damage to water hyacinth. This study was conducted at Situ Bagendit lake, Garut, West Java. A release and recapture method was employed to study the mode and rate of dispersal of the weevils under field conditions. Regular sample collection at two-month interval was done to evaluate the pattern of distribution and to assess the age structure under field condition. Another two months regular observation was done to assess damage severity due to adult weevils and the fungus, A. eichhorniae, on water hyacinth. Results showed, that the weevils seem to disperse actively to all directions following the presence of water hyacinth. The data also showed that the dispersal rate of the weevils was about a few meters a week. Under field conditions at Situ Bagendit lake, the weevils were about evenly distributed throughout water hyacinth mass. The density of the weevils fluctuated from time to time, but the trend slightly increased. The survival rate of the weevils at Situ Bagendit lake was estimated not more than 5%. It was suspected that various limiting factors such as various predators have caused the low population increase under field conditions. The population increase through time confirmed that the weevils have established at Situ Bagendit lake. Field data showed that there were no interaction between the damage severity of the weed caused by both weevils and the fungus.

Coal handleability — rapid on-site assessments

A handleability monitor was designed to provide a simple, rapid, on-site assessment of the whole or part consignment of a coal blend in its “as-received” condition. The monitor was evaluated at a number of coal-handling plants, which handle both metallurgical and power station coals from a variety of sources worldwide. The results can be used to predict which coals could routinely pass through a handling plant at line capacity without causing blockage or delay. Despite extensive analysis of the data, it was not possible to correlate the handleability index to the regular sample analysis of moisture, ash and size analyses of the coal blends.

Nanoliter solvent extraction combined with microspot MALDI TOF mass spectrometry for the analysis of hydrophobic biomolecules.

A nanoliter solvent extraction technique combined with microspot matrix-assisted laser desorption/ionization (MALDI) mass spectrometry is presented. This method involves the use of a nanoliter droplet containing organic solvents at the tip of a small capillary for extraction. The droplet is formed inside a microliter aqueous sample containing the analyte of interest. After extraction, the droplet is deposited onto a MALDI target precoated with a thin matrix layer. Since the nanoliter droplet never touches the sample container wall, any possible extraction of contaminants adsorbed on the plastic or glassware is avoided. In addition, there is no need to concentrate the organic phase after the extraction, thus avoiding any possible loss during the concentration step. The nanoliter volume can be readily deposited onto a MALDI target, producing a high analyte concentration within a microspot. Combined with microspot MALDI, this technique allows for very sensitive analysis of the extracted analyte. The performance of this technique is illustrated in several applications involving the detection of hydrophobic peptides or phospholipids. It is shown that very hydrophobic analytes can be extracted from small-volume samples containing a large amount of salts and/or more hydrophilic analytes, which tend to give dominant signals in conventional MALDI experiments. Nanoliter extraction of analyte from samples containing less than 100 nM hydrophobic analyte and over 1 microM easily ionized hydrophilic species is demonstrated. Finally, using the analysis of the ionophore valinomycin as an example, it is demonstrated that the technique is a more reliable tool for probing metal-peptide complexes than regular MALDI sample preparations.

Quality inferential control of an industrial high density polyethylene process

Abstract The melt index (MI) is an important quality variable of control in polyolefin processes. However, it is difficult to measure this variable at frequent and regular sample intervals. A practical on-line inferential scheme is proposed in this paper for predicting the MI using secondary on-line measurements. This on-line MI inferential estimation scheme is combined with a quality control system that utilizes a two-degree of freedom cascaded model predictive controller. The proposed system has been successfully evaluated, under regulatory as well as tracking conditions, on an industrial polyolefin operation.