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Growth environment of plants was investigated by analyzing the elemental concentration in leaves of the plants. Camellia was selected as the sample and the leaves of the camellias were collected from Miyagi and Chiba prefectures. The species of elements and their concentrations in the leaves were measured by the in-air PIXE system at Tohoku University. More than 10 elements were detected from the leaves. The concentrations of Mn, Fe, and Rb in the leaves were strongly affected by the place where the tree grew. On the other hand, the concentration of P, S, K, and Ca were less affected by the place of the tree. The determination of the place of the tree was also performed by evaluating the similarity of the elemental concentration in the leaves quantitatively. The difference due to the place was clearly identified and the sampling place was successfully determined by using the elemental concentrations in the leaves.

The biometric verification task is to determine whether or not an input and a template belong to the same individual. In the context of automatic fingerprint verification the task consists of three steps: feature extraction, where features (typically minutiae) are extracted from each fingerprint, scoring, where the degree of match between the two sets of features is determined, and decision, where the score is used to accept or reject the hypothesis that the input and template belong to the same individual. The paper focuses on the final decision step, which is a binary classification problem involving a single score variable. The commonly used decision method is to learn a score threshold from a labeled set of inputs and templates, by first determining the receiver operating characteristic (ROC) of the task. The ROC method works well when there is a well-registered fingerprint image. The paper shows that when there is uncertainty due to fingerprint quality, e.g. the input is a latent print or a partial print, the decision method can be improved by using the likelihood ratio of match/non match. The likelihood ratio is obtained by modeling the distributions of same finger and different finger scores using parametric distributions. The parametric forms considered are Gaussian and Gamma distributions whose parameters are learnt from labeled training samples. The performances of the likelihood and ROC methods are compared for varying numbers of minutiae points available for verification. Using either Gaussian or Gamma parametric distributions, the likelihood method has a lower error rate than the ROC method when few minutiae points are available. Likelihood and ROC methods converge to the same accuracy as more minutiae points are available.

The paper describes an integrated recognition-by-parts architecture for reliable and robust face recognition. Reliability and robustness are characteristic of the ability to deploy full-fledged and operational biometric engines, and handling adverse image conditions that include among others uncooperative subjects, occlusion, and temporal variability, respectively. The architecture proposed is model-free and non-parametric. The conceptual framework draws support from discriminative methods using likelihood ratios. At the conceptual level it links forensics and biometrics, while at the implementation level it links the Bayesian framework and statistical learning theory (SLT). Layered categorization starts with face detection using implicit rather than explicit segmentation. It proceeds with face authentication that involves feature selection of local patch instances including dimensionality reduction, exemplar-based clustering of patches into parts, and data fusion for matching using boosting driven by parts that play the role of weak-learners. Face authentication shares the same implementation with face detection. The implementation, driven by transduction, employs proximity and typicality (ranking) realized using strangeness and p-values, respectively. The feasibility and reliability of the proposed architecture are illustrated using FRGC data. The paper concludes with suggestions for augmenting and enhancing the scope and utility of the proposed architecture.

In this paper, an effective method based on the color quaternion wavelet transform (CQWT) for image forensics is proposed. Compared to discrete wavelet transform (DWT), the CQWT provides more information, such as the quaternion’s magnitude and phase measures, to discriminate between computer generated (CG) and photographic (PG) images. Meanwhile, we extend the classic Markov features into the quaternion domain to develop the quaternion Markov statistical features for color images. Experimental results show that the proposed scheme can achieve the classification rate of 92.70%, which is 6.89% higher than the classic Markov features.

Cyber security is the term used to describe the processes and technologies designed to protect computers, networks, data and programs from unauthorized access, damage or attack. Many businesses pay lots of attention to security concerns. For these reasons this research has been undertaken. Ad-hoc networks are crucial enablers of next-generation communications. Such networks can be formed and reconfigured dynamically and they can be mobile, standalone or internetworked with other networks. Mobile Ad-hoc Networks (MANETs) are established by a group of autonomous nodes that communicate with each other by establishing a multi-hop radio network and maintaining connectivity in an infrastructure-less manner. The security of the connections between devices and networks is crucial. The important challenges of supporting multimedia applications in an ad-hoc network are the security issues. In this chapter, a new and efficient media-aware security framework will be designed for facilitating various multimedia applications in ad-hoc networks over the Internet.

Genetic variation detected by new molecular techniques provides a powerful but somewhat controversial tool for assisting, in identifying the source of forensic specimens. A DNA match between a forensic specimen and a suspect has little probative value without an appreciation of the extent of variation within the population of possible culprits. Genetic sequences that are highly variable are, in principle, the most powerful for establishing the genetic identity of samples, but differences between human populations in the frequency of genes and the non-random pattern of human mating create difficulties in accurately quantifying the likelihood of a match at random. If gene frequencies are generally low and the variation between subpopulations significant but ignored, the probability of a match is likely to be overestimated (Wahlund phenomenon), favouring the suspect. Associations between genes at different loci (linkage disequilibrium) can also seriously influence estimates of the match probability, especially in populations recently formed as an aggregate of several distinct groups.

One method of taking cognisance of these difficulties, ‘the ceiling principle’, was designed to give an upper estimate of the match probability and hence favour the suspect. While this method generally produces a conservative estimate, it does not have some basic properties considered fundamental in scientific estimation - the most important of which is that one cannot attach to the probability an estimate of uncertainty or error. The fixation index F_ST, which measures the extent of genetic variation between groups, is a far more powerful way of correcting for population substructure. However, no method is satisfactory if the extent of variation (at the genetic sequences being utilised) in the relevant forensic population is not well understood, and this is the greatest impediment to the application of DNA variation. Also, extremely low probabilities of a match at random have little meaning if the rate of errors in other parts of the process (such as mixing samples, laboratory mistakes, etc) is significantly greater. The controversy that this particular application of molecular biology in the forensic setting has made highlights the necessity of inter-disciplinary co-operation between several distinct subdisciplines of both the scientific and legal professions if the introduction of new technologies and methodologies is to proceed efficiently and fairly.