Compliant cryptologic protocols

Literally, the word compliance suggests conformity in fulfilling official requirements. The thesis presents the results of the analysis and design of a class of protocols called compliant cryptologic protocols (CCP). The thesis presents a notion for compliance in cryptosystems that is conducive as a cryptologic goal. CCP are employed in security systems used by at least two mutually mistrusting sets of entities. The individuals in the sets of entities only trust the design of the security system and any trusted third party the security system may include. Such a security system can be thought of as a broker between the mistrusting sets of entities. In order to provide confidence in operation for the mistrusting sets of entities, CCP must provide compliance verification mechanisms. These mechanisms are employed either by all the entities or a set of authorised entities in the system to verify the compliance of the behaviour of various participating entities with the rules of the system. It is often stated that confidentiality, integrity and authentication are the primary interests of cryptology. It is evident from the literature that authentication mechanisms employ confidentiality and integrity services to achieve their goal. Therefore, the fundamental services that any cryptographic algorithm may provide are confidentiality and integrity only. Since controlling the behaviour of the entities is not a feasible cryptologic goal,the verification of the confidentiality of any data is a futile cryptologic exercise. For example, there exists no cryptologic mechanism that would prevent an entity from willingly or unwillingly exposing its private key corresponding to a certified public key. The confidentiality of the data can only be assumed. Therefore, any verification in cryptologic protocols must take the form of integrity verification mechanisms. Thus, compliance verification must take the form of integrity verification in cryptologic protocols. A definition of compliance that is conducive as a cryptologic goal is presented as a guarantee on the confidentiality and integrity services. The definitions are employed to provide a classification mechanism for various message formats in a cryptologic protocol. The classification assists in the characterisation of protocols, which assists in providing a focus for the goals of the research. The resulting concrete goal of the research is the study of those protocols that employ message formats to provide restricted confidentiality and universal integrity services to selected data. The thesis proposes an informal technique to understand, analyse and synthesise the integrity goals of a protocol system. The thesis contains a study of key recovery,electronic cash, peer-review, electronic auction, and electronic voting protocols. All these protocols contain message format that provide restricted confidentiality and universal integrity services to selected data. The study of key recovery systems aims to achieve robust key recovery relying only on the certification procedure and without the need for tamper-resistant system modules. The result of this study is a new technique for the design of key recovery systems called hybrid key escrow. The thesis identifies a class of compliant cryptologic protocols called secure selection protocols (SSP). The uniqueness of this class of protocols is the similarity in the goals of the member protocols, namely peer-review, electronic auction and electronic voting. The problem statement describing the goals of these protocols contain a tuple,(I, D), where I usually refers to an identity of a participant and D usually refers to the data selected by the participant. SSP are interested in providing confidentiality service to the tuple for hiding the relationship between I and D, and integrity service to the tuple after its formation to prevent the modification of the tuple. The thesis provides a schema to solve the instances of SSP by employing the electronic cash technology. The thesis makes a distinction between electronic cash technology and electronic payment technology. It will treat electronic cash technology to be a certification mechanism that allows the participants to obtain a certificate on their public key, without revealing the certificate or the public key to the certifier. The thesis abstracts the certificate and the public key as the data structure called anonymous token. It proposes design schemes for the peer-review, e-auction and e-voting protocols by employing the schema with the anonymous token abstraction. The thesis concludes by providing a variety of problem statements for future research that would further enrich the literature.

Vision-based classification of solder joint defects

Inspection of solder joints has been a critical process in the electronic manufacturing industry to reduce manufacturing cost, improve yield, and ensure product quality and reliability. The solder joint inspection problem is more challenging than many other visual inspections because of the variability in the appearance of solder joints. Although many research works and various techniques have been developed to classify defect in solder joints, these methods have complex systems of illumination for image acquisition and complicated classification algorithms. An important stage of the analysis is to select the right method for the classification. Better inspection technologies are needed to fill the gap between available inspection capabilities and industry systems. This dissertation aims to provide a solution that can overcome some of the limitations of current inspection techniques. This research proposes two inspection steps for automatic solder joint classification system. The “front-end” inspection system includes illumination normalisation, localization and segmentation. The illumination normalisation approach can effectively and efficiently eliminate the effect of uneven illumination while keeping the properties of the processed image. The “back-end” inspection involves the classification of solder joints by using Log Gabor filter and classifier fusion. Five different levels of solder quality with respect to the amount of solder paste have been defined. Log Gabor filter has been demonstrated to achieve high recognition rates and is resistant to misalignment. Further testing demonstrates the advantage of Log Gabor filter over both Discrete Wavelet Transform and Discrete Cosine Transform. Classifier score fusion is analysed for improving recognition rate. Experimental results demonstrate that the proposed system improves performance and robustness in terms of classification rates. This proposed system does not need any special illumination system, and the images are acquired by an ordinary digital camera. In fact, the choice of suitable features allows one to overcome the problem given by the use of non complex illumination systems. The new system proposed in this research can be incorporated in the development of an automated non-contact, non-destructive and low cost solder joint quality inspection system.

A new approach for finding an appropriate combination of texture parameters for classification

This paper suggests an approach for finding an appropriate combination of various parameters for extracting texture features (e.g. choice of spectral band for extracting texture feature, size of the moving window, quantization level of the image, and choice of texture feature etc.) to be used in the classification process. Gray level co-occurrence matrix (GLCM) method has been used for extracting texture from remotely sensed satellite image. Results of the classification of an Indian urban environment using spatial property (texture), derived from spectral and multi-resolution wavelet decomposed images have also been reported. A multivariate data analysis technique called ‘conjoint analysis’ has been used in the study to analyze the relative importance of these parameters. Results indicate that the choice of texture feature and window size have higher relative importance in the classification process than quantization level or the choice of image band for extracting texture feature. In case of texture features derived using wavelet decomposed image, the parameter ‘decomposition level’ has almost equal relative importance as the size of moving window and the decomposition of images up to level one is sufficient and there is no need to go for further decomposition. It was also observed that the classification incorporating texture features improves the overall classification accuracy in a statistically significant manner in comparison to pure spectral classification.

The nonconceptual gateway to early word learning

My research investigates why nouns are learned disproportionately more frequently than other kinds of words during early language acquisition (Gentner, 1982; Gleitman, et al., 2004). This question must be considered in the context of cognitive development in general. Infants have two major streams of environmental information to make meaningful: perceptual and linguistic. Perceptual information flows in from the senses and is processed into symbolic representations by the primitive language of thought (Fodor, 1975). These symbolic representations are then linked to linguistic input to enable language comprehension and ultimately production. Yet, how exactly does perceptual information become conceptualized? Although this question is difficult, there has been progress. One way that children might have an easier job is if they have structures that simplify the data. Thus, if particular sorts of perceptual information could be separated from the mass of input, then it would be easier for children to refer to those specific things when learning words (Spelke, 1990; Pylyshyn, 2003). It would be easier still, if linguistic input was segmented in predictable ways (Gentner, 1982; Gleitman, et al., 2004) Unfortunately the frequency of patterns in lexical or grammatical input cannot explain the cross-cultural and cross-linguistic tendency to favor nouns over verbs and predicates. There are three examples of this failure: 1) a wide variety of nouns are uttered less frequently than a smaller number of verbs and yet are learnt far more easily (Gentner, 1982); 2) word order and morphological transparency offer no insight when you contrast the sentence structures and word inflections of different languages (Slobin, 1973) and 3) particular language teaching behaviors (e.g. pointing at objects and repeating names for them) have little impact on children's tendency to prefer concrete nouns in their first fifty words (Newport, et al., 1977). Although the linguistic solution appears problematic, there has been increasing evidence that the early visual system does indeed segment perceptual information in specific ways before the conscious mind begins to intervene (Pylyshyn, 2003). I argue that nouns are easier to learn because their referents directly connect with innate features of the perceptual faculty. This hypothesis stems from work done on visual indexes by Zenon Pylyshyn (2001, 2003). Pylyshyn argues that the early visual system (the architecture of the "vision module") segments perceptual data into pre-conceptual proto-objects called FINSTs. FINSTs typically correspond to physical things such as Spelke objects (Spelke, 1990). Hence, before conceptualization, visual objects are picked out by the perceptual system demonstratively, like a finger pointing indicating ‘this’ or ‘that’. I suggest that this primitive system of demonstration elaborates on Gareth Evan's (1982) theory of nonconceptual content. Nouns are learnt first because their referents attract demonstrative visual indexes. This theory also explains why infants less often name stationary objects such as plate or table, but do name things that attract the focal attention of the early visual system, i.e., small objects that move, such as ‘dog’ or ‘ball’. This view leaves open the question how blind children learn words for visible objects and why children learn category nouns (e.g. 'dog'), rather than proper nouns (e.g. 'Fido') or higher taxonomic distinctions (e.g. 'animal').

Evaluation of spectral and texture features for object-based vegetation species classification using Support Vector Machines

The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.

Empirical comparison of machine learning algorithms for image texture classification with application to vegetation management in power line corridors

This paper reports on the empirical comparison of seven machine learning algorithms in texture classification with application to vegetation management in power line corridors. Aiming at classifying tree species in power line corridors, object-based method is employed. Individual tree crowns are segmented as the basic classification units and three classic texture features are extracted as the input to the classification algorithms. Several widely used performance metrics are used to evaluate the classification algorithms. The experimental results demonstrate that the classification performance depends on the performance matrix, the characteristics of datasets and the feature used.

Color and texture feature fusion using kernel PCA with application to object-based vegetation species classification

A good object representation or object descriptor is one of the key issues in object based image analysis. To effectively fuse color and texture as a unified descriptor at object level, this paper presents a novel method for feature fusion. Color histogram and the uniform local binary patterns are extracted from arbitrary-shaped image-objects, and kernel principal component analysis (kernel PCA) is employed to find nonlinear relationships of the extracted color and texture features. The maximum likelihood approach is used to estimate the intrinsic dimensionality, which is then used as a criterion for automatic selection of optimal feature set from the fused feature. The proposed method is evaluated using SVM as the benchmark classifier and is applied to object-based vegetation species classification using high spatial resolution aerial imagery. Experimental results demonstrate that great improvement can be achieved by using proposed feature fusion method.

Entertaining the E Word : Barrie Kosky's On Ecstasy [A Review]

A review of Barrie Kosky's essay, On Ecstasy : Most of us describe the E word as a pleasant, out of this world experience—a type of boundless, artificial joy, deliberately induced by some kind of technicoloured drug. For others, it is that “lovey dovey” feeling. A spinning ceiling. Anything Lindt. For sensualist and soup connoisseur Barrie Kosky, it is easier than this. Being On Ecstasy involves, quite simply, his grandmother's chicken specialty—something warm and golden, surrendered with vegetables and a side of transcendental bliss. “A soup that took you to the beginning and end of time itself. A dazzling, pure, clear rhapsody” (7).

Obesity screening for young Japanese males and females using skin fold measurements : the classification revisited

Anthropometric assessment is a simple, safe, and cost-efficient method to examine the health status of individu-als. The Japanese obesity classification based on the sum of two skin folds (Σ2SF) was proposed nearly 40 years ago therefore its applicability to Japanese living today is unknown. The current study aimed to determine Σ2SF cut-off values that correspond to percent body fat (%BF) and BMI values using two datasets from young Japa-nese adults (233 males and 139 females). Using regression analysis, Σ2SF and height-corrected Σ2SF (HtΣ2SF) values that correspond to %BF of 20, 25, and 30% for males and 30, 35, and 40% for females were determined. In addition, cut-off values of both Σ2SF and HtΣ2SF that correspond to BMI values of 23 kg/m2, 25 kg/m2 and 30 kg/m2 were determined. In comparison with the original Σ2SF values, the proposed values are smaller by about 10 mm at maximum. The proposed values show an improvement in sensitivity from about 25% to above 90% to identify individuals with ≥20% body fat in males and ≥30% body fat in females with high specificity of about 95% in both genders. The results indicate that the original Σ2SF cut-off values to screen obese individuals cannot be applied to young Japanese adults living today and modification is required. Application of the pro-posed values may assist screening in the clinical setting.

Assigning metabolic equivalent (MET) values to the 2002 Census Occupational Classification System

Background: The Current Population Survey (CPS) and the American Time Use Survey (ATUS) use the 2002 census occupation system to classify workers into 509 separate occupations arranged into 22 major occupational categories. Methods: We describe the methods and rationale for assigning detailed MET estimates to occupations and present population estimates (comparing outputs generated by analysis of previously published summary MET estimates to the detailed MET estimates) of intensities of occupational activity using the 2003 ATUS data comprised of 20,720 respondents, 5,323 (2,917 males and 2,406 females) of whom reported working 6+ hours at their primary occupation on their assigned reporting day. Results: Analysis using the summary MET estimates resulted in 4% more workers in sedentary occupations, 6% more in light, 7% less in moderate, and 3% less in vigorous compared to using the detailed MET estimates. The detailed estimates are more sensitive to identifying individuals who do any occupational activity that is moderate or vigorous in intensity resulting in fewer workers in sedentary and light intensity occupations. Conclusions: Since CPS/ATUS regularly captures occupation data it will be possible to track prevalence of the different intensity levels of occupations. Updates will be required with inevitable adjustments to future occupational classification systems.