Structural damage detection method using frequency response functions

Structural damage detection using measured dynamic data for pattern recognition is a promising approach. These pattern recognition techniques utilize artificial neural networks and genetic algorithm to match pattern features. In this study, an artificial neural network–based damage detection method using frequency response functions is presented, which can effectively detect nonlinear damages for a given level of excitation. The main objective of this article is to present a feasible method for structural vibration–based health monitoring, which reduces the dimension of the initial frequency response function data and transforms it into new damage indices and employs artificial neural network method for detecting different levels of nonlinearity using recognized damage patterns from the proposed algorithm. Experimental data of the three-story bookshelf structure at Los Alamos National Laboratory are used to validate the proposed method. Results showed that the levels of nonlinear damages can be identified precisely by the developed artificial neural networks. Moreover, it is identified that artificial neural networks trained with summation frequency response functions give higher precise damage detection results compared to the accuracy of artificial neural networks trained with individual frequency response functions. The proposed method is therefore a promising tool for structural assessment in a real structure because it shows reliable results with experimental data for nonlinear damage detection which renders the frequency response function–based method convenient for structural health monitoring.

Cryptographic hash functions

Cryptographic hash functions are an important tool of cryptography and play a fundamental role in efficient and secure information processing. A hash function processes an arbitrary finite length input message to a fixed length output referred to as the hash value. As a security requirement, a hash value should not serve as an image for two distinct input messages and it should be difficult to find the input message from a given hash value. Secure hash functions serve data integrity, non-repudiation and authenticity of the source in conjunction with the digital signature schemes. Keyed hash functions, also called message authentication codes (MACs) serve data integrity and data origin authentication in the secret key setting. The building blocks of hash functions can be designed using block ciphers, modular arithmetic or from scratch. The design principles of the popular Merkle–Damgård construction are followed in almost all widely used standard hash functions such as MD5 and SHA-1.

On hash functions using checksums

We analyse the security of iterated hash functions that compute an input dependent checksum which is processed as part of the hash computation. We show that a large class of such schemes, including those using non-linear or even one-way checksum functions, is not secure against the second preimage attack of Kelsey and Schneier, the herding attack of Kelsey and Kohno and the multicollision attack of Joux. Our attacks also apply to a large class of cascaded hash functions. Our second preimage attacks on the cascaded hash functions improve the results of Joux presented at Crypto’04. We also apply our attacks to the MD2 and GOST hash functions. Our second preimage attacks on the MD2 and GOST hash functions improve the previous best known short-cut second preimage attacks on these hash functions by factors of at least 226 and 254, respectively. Our herding and multicollision attacks on the hash functions based on generic checksum functions (e.g., one-way) are a special case of the attacks on the cascaded iterated hash functions previously analysed by Dunkelman and Preneel and are not better than their attacks. On hash functions with easily invertible checksums, our multicollision and herding attacks (if the hash value is short as in MD2) are more efficient than those of Dunkelman and Preneel.

On the Collision and Preimage Resistance of Certain Two-Call Hash Functions

In this paper we present concrete collision and preimage attacks on a large class of compression function constructions making two calls to the underlying ideal primitives. The complexity of the collision attack is above the theoretical lower bound for constructions of this type, but below the birthday complexity; the complexity of the preimage attack, however, is equal to the theoretical lower bound. We also present undesirable properties of some of Stam’s compression functions proposed at CRYPTO ’08. We show that when one of the n-bit to n-bit components of the proposed 2n-bit to n-bit compression function is replaced by a fixed-key cipher in the Davies-Meyer mode, the complexity of finding a preimage would be 2 n/3. We also show that the complexity of finding a collision in a variant of the 3n-bits to 2n-bits scheme with its output truncated to 3n/2 bits is 2 n/2. The complexity of our preimage attack on this hash function is about 2 n . Finally, we present a collision attack on a variant of the proposed m + s-bit to s-bit scheme, truncated to s − 1 bits, with a complexity of O(1). However, none of our results compromise Stam’s security claims.

On Randomizing Hash Functions to Strengthen the Security of Digital Signatures

Halevi and Krawczyk proposed a message randomization algorithm called RMX as a front-end tool to the hash-then-sign digital signature schemes such as DSS and RSA in order to free their reliance on the collision resistance property of the hash functions. They have shown that to forge a RMX-hash-then-sign signature scheme, one has to solve a cryptanalytical task which is related to finding second preimages for the hash function. In this article, we will show how to use Dean’s method of finding expandable messages for finding a second preimage in the Merkle-Damgård hash function to existentially forge a signature scheme based on a t-bit RMX-hash function which uses the Davies-Meyer compression functions (e.g., MD4, MD5, SHA family) in 2 t/2 chosen messages plus 2 t/2 + 1 off-line operations of the compression function and similar amount of memory. This forgery attack also works on the signature schemes that use Davies-Meyer schemes and a variant of RMX published by NIST in its Draft Special Publication (SP) 800-106. We discuss some important applications of our attack.

Cryptographic Hash Functions

In the modern era of information and communication technology, cryptographic hash functions play an important role in ensuring the authenticity, integrity, and nonrepudiation goals of information security as well as efficient information processing. This entry provides an overview of the role of hash functions in information security, popular hash function designs, some important analytical results, and recent advances in this field.

Archival analysis of service desk research: New perspectives on design and delivery

ur analysis of service desk studies shows the extent to which researchers have neglected important aspects of service desk design and delivery. The observations are made through an archival analysis of 58 peer reviewed publications in top tier outlets. Our analysis led to the development of a generic framework which identified three themes in service desk design: (1) user groups, (2) support models, and; (3) technology types And two themes in service desk delivery: (1) direction of delivery, and; (2) executive support level. This paper makes a twofold contribution to service desk research. First, it provides an understanding of service desk functions and the challenges faced by organisations in delivering those functions. Second, it identifies established and emerging areas in the service desk field. This archival analysis is the first attempt to systematically analyse the service desk literature.

A new twist on mode indicator functions

Mode indicator functions (MIFs) are used in modal testing and analysis as a means of identifying modes of vibration, often as a precursor to modal parameter estimation. Various methods have been developed since the MIF was introduced four decades ago. These methods are quite useful in assisting the analyst to identify genuine modes and, in the case of the complex mode indicator function, have even been developed into modal parameter estimation techniques. Although the various MIFs are able to indicate the existence of a mode, they do not provide the analyst with any descriptive information about the mode. This paper uses the simple summation type of MIF to develop five averaged and normalised MIFs that will provide the analyst with enough information to identify whether a mode is longitudinal, vertical, lateral or torsional. The first three functions, termed directional MIFs, have been noted in the literature in one form or another; however, this paper introduces a new twist on the MIF by introducing two MIFs, termed torsional MIFs, that can be used by the analyst to identify torsional modes and, moreover, can assist in determining whether the mode is of a pure torsion or sway type (i.e., having a rigid cross-section) or a distorted twisting type. The directional and torsional MIFs are tested on a finite element model based simulation of an experimental modal test using an impact hammer. Results indicate that the directional and torsional MIFs are indeed useful in assisting the analyst to identify whether a mode is longitudinal, vertical, lateral, sway, or torsion.

Information-theoretic analysis of brain white matter fiber orientation distribution functions

We propose a new information-theoretic metric, the symmetric Kullback-Leibler divergence (sKL-divergence), to measure the difference between two water diffusivity profiles in high angular resolution diffusion imaging (HARDI). Water diffusivity profiles are modeled as probability density functions on the unit sphere, and the sKL-divergence is computed from a spherical harmonic series, which greatly reduces computational complexity. Adjustment of the orientation of diffusivity functions is essential when the image is being warped, so we propose a fast algorithm to determine the principal direction of diffusivity functions using principal component analysis (PCA). We compare sKL-divergence with other inner-product based cost functions using synthetic samples and real HARDI data, and show that the sKL-divergence is highly sensitive in detecting small differences between two diffusivity profiles and therefore shows promise for applications in the nonlinear registration and multisubject statistical analysis of HARDI data.

Early mathematical learning: Number processing skills and executive function at 5 and 8 years of age

This research investigated differences and associations in performance in number processing and executive function for children attending primary school in a large Australian metropolitan city. In a cross-sectional study, performance of 25 children in the first full-time year of school, (Prep; mean age = 5.5 years) and 21 children in Year 3 (mean age = 8.5 years) completed three number processing tasks and three executive function tasks. Year 3 children consistently outperformed the Prep year children on measures of accuracy and reaction time, on the tasks of number comparison, calculation, shifting, and inhibition but not on number line estimation. The components of executive function (shifting, inhibition, and working memory) showed different patterns of correlation to performance on number processing tasks across the early years of school. Findings could be used to enhance teachers’ understanding about the role of the cognitive processes employed by children in numeracy learning, and so inform teachers’ classroom practices.

Impulsivity-related cognition in alcohol dependence: Is it moderated by DRD2/ANKK1 gene status and executive dysfunction?

Perceived impaired control over alcohol use is a key cognitive construct in alcohol dependence that has been related prospectively to treatment outcome and may mediate the risk for problem drinking conveyed by impulsivity in non-dependent drinkers. The aim of the current study was to investigate whether perceived impaired control may mediate the association between impulsivity-related measures (derived from the Short-form Eysenck Personality Questionnaire-Revised) and alcohol-dependence severity in alcohol-dependent drinkers. Furthermore, the extent to which this hypothesized relationship was moderated by genetic risk (Taq1A polymorphism in the DRD2/ANKK1 gene cluster) and verbal fluency as an indicator of executive cognitive ability (Controlled Oral Word Association Test) was also examined. A sample of 143 alcohol-dependent inpatients provided an extensive clinical history of their alcohol use, gave 10ml of blood for DNA analysis, and completed self-report measures relating to impulsivity, impaired control and severity of dependence. As hypothesized, perceived impaired control (partially) mediated the association between impulsivity-related measures and alcohol-dependence severity. This relationship was not moderated by the DRD2/ANKK1 polymorphism or verbal fluency. These results suggest that, in alcohol dependence, perceived impaired control is a cognitive mediator of impulsivity-related constructs that may be unaffected by DRD2/ANKK1 and neurocognitive processes underlying the retrieval of verbal information

The kallikrein-related peptidase family: Dysregulation and functions during cancer progression

Cancer is the second leading cause of death with 14 million new cases and 8.2 million cancer-related deaths worldwide in 2012. Despite the progress made in cancer therapies, neoplastic diseases are still a major therapeutic challenge notably because of intra- and inter-malignant tumour heterogeneity and adaptation/escape of malignant cells to/from treatment. New targeted therapies need to be developed to improve our medical arsenal and counter-act cancer progression. Human kallikrein-related peptidases (KLKs) are secreted serine peptidases which are aberrantly expressed in many cancers and have great potential in developing targeted therapies. The potential of KLKs as cancer biomarkers is well established since the demonstration of the association between KLK3/PSA (prostate specific antigen) levels and prostate cancer progression. In addition, a constantly increasing number of in vitro and in vivo studies demonstrate the functional involvement of KLKs in cancer-related processes. These peptidases are now considered key players in the regulation of cancer cell growth, migration, invasion, chemo-resistance, and importantly, in mediating interactions between cancer cells and other cell populations found in the tumour microenvironment to facilitate cancer progression. These functional roles of KLKs in a cancer context further highlight their potential in designing new anti-cancer approaches. In this review, we comprehensively review the biochemical features of KLKs, their functional roles in carcinogenesis, followed by the latest developments and the successful utility of KLK-based therapeutics in counteracting cancer progression.

Implications of gain functions in fisheries management

The appealing concept of optimal harvesting is often used in fisheries to obtain new management strategies. However, optimality depends on the objective function, which often varies, reflecting the interests of different groups of people. The aim of maximum sustainable yield is to extract the greatest amount of food from replenishable resources in a sustainable way. Maximum sustainable yield may not be desirable from an economic point of view. Maximum economic yield that maximizes the profit of fishing fleets (harvesting sector) but ignores socio-economic benefits such as employment and other positive externalities. It may be more appropriate to use the maximum economic yield that which is based on the value chain of the overall fishing sector, to reflect better society's interests. How to make more efficient use of a fishery for society rather than fishing operators depends critically on the gain function parameters including multiplier effects and inclusion or exclusion of certain costs. In particular, the optimal effort level based on the overall value chain moves closer to the optimal effort for the maximum sustainable yield because of the multiplier effect. These issues are illustrated using the Australian Northern Prawn Fishery.

Robust estimating functions and bias correction for longitudinal data analysis

Robust methods are useful in making reliable statistical inferences when there are small deviations from the model assumptions. The widely used method of the generalized estimating equations can be "robustified" by replacing the standardized residuals with the M-residuals. If the Pearson residuals are assumed to be unbiased from zero, parameter estimators from the robust approach are asymptotically biased when error distributions are not symmetric. We propose a distribution-free method for correcting this bias. Our extensive numerical studies show that the proposed method can reduce the bias substantially. Examples are given for illustration.

Organisational age cultures: The interplay of chief executive officers age and attitudes toward younger and older employees

This article investigates the interactive effects of chief executive officer (CEO) age and CEO attitudes toward younger and older employees on organisational age cultures. Data was collected from 66 CEOs of small and medium-sized businesses and 274 employees. Results were consistent with expectations based on organisational culture and upper echelons theories. The relationship between CEO age and organisational age culture for younger employees was negative for CEOs with a less positive attitude toward younger employees and positive for those with a more positive attitude toward younger employees. The relationship between CEO age and organisational age culture for older employees was positive for CEOs with a more positive attitude toward older employees and non-significant for those with a less positive attitude toward older employees. The findings provide initial support for the existence of organisational age cultures, suggesting that these cultures can be predicted by the interplay of CEO age and age-related attitudes.