Design of experiments for bivariate binary responses modelled by Copula functions

Optimal design for generalized linear models has primarily focused on univariate data. Often experiments are performed that have multiple dependent responses described by regression type models, and it is of interest and of value to design the experiment for all these responses. This requires a multivariate distribution underlying a pre-chosen model for the data. Here, we consider the design of experiments for bivariate binary data which are dependent. We explore Copula functions which provide a rich and flexible class of structures to derive joint distributions for bivariate binary data. We present methods for deriving optimal experimental designs for dependent bivariate binary data using Copulas, and demonstrate that, by including the dependence between responses in the design process, more efficient parameter estimates are obtained than by the usual practice of simply designing for a single variable only. Further, we investigate the robustness of designs with respect to initial parameter estimates and Copula function, and also show the performance of compound criteria within this bivariate binary setting.

A mask-based approach for the geometric calibration of thermal-infrared cameras

Accurate and efficient thermal-infrared (IR) camera calibration is important for advancing computer vision research within the thermal modality. This paper presents an approach for geometrically calibrating individual and multiple cameras in both the thermal and visible modalities. The proposed technique can be used to correct for lens distortion and to simultaneously reference both visible and thermal-IR cameras to a single coordinate frame. The most popular existing approach for the geometric calibration of thermal cameras uses a printed chessboard heated by a flood lamp and is comparatively inaccurate and difficult to execute. Additionally, software toolkits provided for calibration either are unsuitable for this task or require substantial manual intervention. A new geometric mask with high thermal contrast and not requiring a flood lamp is presented as an alternative calibration pattern. Calibration points on the pattern are then accurately located using a clustering-based algorithm which utilizes the maximally stable extremal region detector. This algorithm is integrated into an automatic end-to-end system for calibrating single or multiple cameras. The evaluation shows that using the proposed mask achieves a mean reprojection error up to 78% lower than that using a heated chessboard. The effectiveness of the approach is further demonstrated by using it to calibrate two multiple-camera multiple-modality setups. Source code and binaries for the developed software are provided on the project Web site.

Agrobacterium-mediated transformation of indica rice cultivars using binary and superbinary vectors

The Agrobacterium-mediated transformation system was extended to two indica cultivars: a widely cultivated breeding line IR-64 and an elite basmati cultivar Karnal Local. Root tips and shoot tips of seedlings, and scutellar-calli derived from mature seeds showed high-efficiency Agrobacterium tumefaciens infection and stable transformation. In addition to the superbinary vector pTOK233 in Agrobacterium strain LBA4404, almost equally high levels of transformation were achieved with a relatively much smaller (13.1 kb) binary vector (pCAMBIA1301) in a supervirulent host strain AGL1. In both cases, as well as in both cultivars, while 60–90% of the infected explants produced calli resistant to the selectable agent hygromycin, 59–75% of such calli tested positive for GUS. A high level (400 μM) of acetosyringone in the preinduction medium for Agrobacterium and a higher level (500 μM) in the cocultivation medium was necessary for an enhancement in transformation frequency of the binary vector to levels comparable to a superbinary. Hygromycin-resistant calli could be produced from all the explants used. Transformants could be regenerated for both cultivars using the superbinary and binary vector, but only for calli of scutellar origin. In addition to the molecular confirmation of hpt and gus gene transfer and transcription, absence of gene sequences outside the transferred DNA (T-DNA) region confirmed absence of any long T-DNA transfer.

Achieving quality improvement in the mask manufacturing industry by using Six Sigma technique

The Six Sigma technique is one of the quality management strategies and is utilised for improving the quality and productivity in the manufacturing process. It is inspired by the two major project methodologies of Deming’s "Plan – Do – Check – Act (PDCA)" Cycle which consists of DMAIC and DMADV. Those two methodologies are comprised of five phases. The DMAIC project methodology will be comprehensively used in this research. In brief, DMAIC is utilised for improving the existing manufacturing process and it involves the phases Define, Measure, Analyse, Improve, and Control. Mask industry has become a significant industry in today’s society since the outbreak of some serious diseases such as the Severe Acute Respiratory Syndrome (SARS), bird flu, influenza, swine flu and hay fever. Protecting the respiratory system, then, has become the fundamental requirement for preventing respiratory deceases. Mask is the most appropriate and protective product inasmuch as it is effective in protecting the respiratory tract and resisting the virus infection through air. In order to satisfy various customers’ requirements, thousands of mask products are designed in the market. Moreover, masks are also widely used in industries including medical industries, semi-conductor industries, food industries, traditional manufacturing, and metal industries. Notwithstanding the quality of masks have become the prioritisations since they are used to prevent dangerous diseases and safeguard people, the quality improvement technique are of very high significance in mask industry. The purpose of this research project is firstly to investigate the current quality control practices in a mask industry, then, to explore the feasibility of using Six Sigma technique in that industry, and finally, to implement the Six Sigma technique in the case company to develop and evaluate the product quality process. This research mainly investigates the quality problems of musk industry and effectiveness of six sigma technique in musk industry with the United Excel Enterprise Corporation (UEE) Company as a case company. The DMAIC project methodology in the Six Sigma technique is adopted and developed in this research. This research makes significant contribution to knowledge. The main results contribute to the discovering the root causes of quality problems in a mask industry. Secondly, the company was able to increase not only acceptance rate but quality level by utilising the Six Sigma technique. Hence, utilising the Six Sigma technique could increase the production capacity of the company. Third, the Six Sigma technique is necessary to be extensively modified to improve the quality control in the mask industry. The impact of the Six Sigma technique on the overall performance in the business organisation should be further explored in future research.

Real, complex, and binary semantic vectors

This paper presents a combined structure for using real, complex, and binary valued vectors for semantic representation. The theory, implementation, and application of this structure are all significant. For the theory underlying quantum interaction, it is important to develop a core set of mathematical operators that describe systems of information, just as core mathematical operators in quantum mechanics are used to describe the behavior of physical systems. The system described in this paper enables us to compare more traditional quantum mechanical models (which use complex state vectors), alongside more generalized quantum models that use real and binary vectors. The implementation of such a system presents fundamental computational challenges. For large and sometimes sparse datasets, the demands on time and space are different for real, complex, and binary vectors. To accommodate these demands, the Semantic Vectors package has been carefully adapted and can now switch between different number types comparatively seamlessly. This paper describes the key abstract operations in our semantic vector models, and describes the implementations for real, complex, and binary vectors. We also discuss some of the key questions that arise in the field of quantum interaction and informatics, explaining how the wide availability of modelling options for different number fields will help to investigate some of these questions.

Optical techniques for real-time binary multiplication

An optical system which performs the multiplication of binary numbers is described and proof-of-principle experiments are performed. The simultaneous generation of all partial products, optical regrouping of bit products, and optical carry look-ahead addition are novel features of the proposed scheme which takes advantage of the parallel operations capability of optical computers. The proposed processor uses liquid crystal light valves (LCLVs). By space-sharing the LCLVs one such system could function as an array of multipliers. Together with the optical carry look-ahead adders described, this would constitute an optical matrix-vector multiplier.

Semi-binary based video features for activity representation

Efficient and effective feature detection and representation is an important consideration when processing videos, and a large number of applications such as motion analysis, 3D scene understanding, tracking etc. depend on this. Amongst several feature description methods, local features are becoming increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational complexity, their performance is still too limited for real world applications. Furthermore, rapid increases in the uptake of mobile devices has increased the demand for algorithms that can run with reduced memory and computational requirements. In this paper we propose a semi binary based feature detectordescriptor based on the BRISK detector, which can detect and represent videos with significantly reduced computational requirements, while achieving comparable performance to the state of the art spatio-temporal feature descriptors. First, the BRISK feature detector is applied on a frame by frame basis to detect interest points, then the detected key points are compared against consecutive frames for significant motion. Key points with significant motion are encoded with the BRISK descriptor in the spatial domain and Motion Boundary Histogram in the temporal domain. This descriptor is not only lightweight but also has lower memory requirements because of the binary nature of the BRISK descriptor, allowing the possibility of applications using hand held devices.We evaluate the combination of detectordescriptor performance in the context of action classification with a standard, popular bag-of-features with SVM framework. Experiments are carried out on two popular datasets with varying complexity and we demonstrate comparable performance with other descriptors with reduced computational complexity.

Identifying steganographic payload location in binary image

In this paper, we propose a steganalysis method that is able to identify the locations of stego bearing pixels in the binary image. In order to do that, our proposed method will calculate the residual between a given stego image and its estimated cover image. After that, we will compute the local entropy difference between these two versions of images as well. Finally, we will compute the mean of residual and mean of local entropy difference across multiple stego images. From these two means, the locations of stego bearing pixels can be identified. The presented empirical results demonstrate that our proposed method can identify the stego bearing locations of near perfect accuracy when sufficient stego images are supplied. Hence, our proposed method can be used to reveal which pixels in the binary image have been used to carry the secret message.

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.

Blind steganalysis : a countermeasure for binary image steganography

In this paper, we propose a new blind steganalytic method to detect the presence of secret messages embedded in black and white images using the steganographic techniques. We start by extracting several sets of matrix, such as run length matrix, gap length matrix and pixel difference. We also apply characteristic function on these matrices to enhance their discriminative capabilities. Then we calculate the statistics which include mean, variance, kurtosis and skewness to form our feature sets. The presented empirical works demonstrate our proposed method can effectively detect three different types of steganography. This proves the universality of our proposed method as a blind steganalysis. In addition, the experimental results show our proposed method is capable of detecting small amount of the embedded message.

Estimating hidden message length in binary image embedded by using boundary pixels steganography

In this paper, we propose a new steganalytic method to detect the message hidden in a black and white image using the steganographic technique developed by Liang, Wang and Zhang. Our detection method estimates the length of hidden message embedded in a binary image. Although the hidden message embedded is visually imperceptible, it changes some image statistic (such as inter-pixels correlation). Based on this observation, we first derive the 512 patterns histogram from the boundary pixels as the distinguishing statistic, then we compute the histogram difference to determine the changes of the 512 patterns histogram induced by the embedding operation. Finally we propose histogram quotient to estimate the length of the embedded message. Experimental results confirm that the proposed method can effectively and reliably detect the length of the embedded message.

pGreen : a versatile and flexible binary Ti vector for Agrobacterium-mediated plant transformation

Binary Ti vectors are the plasmid vectors of choice in Agrobacterium-mediated plant transformation protocols. The pGreen series of binary Ti vectors are configured for ease-of-use and to meet the demands of a wide range of transformation procedures for many plant species. This plasmid system allows any arrangement of selectable marker and reporter gene at the right and left T-DNA borders without compromising the choice of restriction sites for cloning, since the pGreen cloning sites are based on the well-known pBluescript general vector plasmids. Its size and copy number in Escherichia coli offers increased efficiencies in routine in vitro recombination procedures. pGreen can replicate in Agrobacterium only if another plasmid, pSoup, is co-resident in the same strain. pSoup provides replication functions in trans for pGreen. The removal of RepA and Mob functions has enabled the size of pGreen to be kept to a minimum. Versions of pGreen have been used to transform several plant species with the same efficiencies as other binary Ti vectors. Information on the pGreen plasmid system is supplemented by an Internet site (http://www.pgreen.ac.uk) through which comprehensive information, protocols, order forms and lists of different pGreen marker gene permutations can be found.

A guide to Agrobacterium binary Ti vectors

Agrobacterium-based plasmid vectors allow the transformation of a wide range of plant species by capitalizing on a natural bacterial system to introduce DNA into the nuclear genome of plants. It is often a complex task to consider fully all the possible plasmid vectors and Agrobacterium strains available, and it can thus be difficult to take full advantage of these research tools. This practical guide is a survey of the many binary Ti plasmid vectors and Agrobacterium strains available, and aims to help researchers to make an informed decision about the system that is best suited to their needs...

Confronting the ‘resource curse or cure’ binary

The use of the curse or cure dichotomy to frame a discussion around the impacts of mining is an oversimplification, not least in the emphasis on one or the other (as opposed to curse and cure). It is, however, a potent trope for engaging critically with the consequences of mining not only in narrow economic terms but also in regard to political, social and environmental costs and benefits. Further, as Goodman and Worth (2008: 201) point out, to engage with the resource curse or cure question is to also engage more broadly with “the internal contradictions of capitalist development” as evident, for example, in divisions “between those who benefit from and those who bear the costs of accumulation” and the many conflicts—political, social, economic, environmental—attending resource extraction. It is in this sense that this volume mobilises the ‘resource curse or cure?’ motif.