Automatic recognition and annotation of gene expression patterns of fly embryos
Gene expression patterns obtained by in situ mRNA hybridization provide important information about different genes during Drosophila embryogenesis. So far, annotations of these images are done by manually assigning a subset of anatomy ontology terms to an image. This time-consuming process depends heavily on the consistency of experts.



We develop a system to automatically annotate a fruitfly's embryonic tissue in which a gene has expression. We formulate the task as an image pattern recognition problem. For a new fly embryo image, our system answers two questions: (1) Which stage range does an image belong to? (2) Which annotations should be assigned to an image? We propose to identify the wavelet embryo features by multi-resolution 2D wavelet discrete transform, followed by min-redundancy max-relevance feature selection, which yields optimal distinguishing features for an annotation. We then construct a series of parallel bi-class predictors to solve the multi-objective annotation problem since each image may correspond to multiple annotations.



The complete annotation prediction results are available at: http://www.cs.niu.edu/~jzhou/papers/fruitfly and http://research.janelia.org/peng/proj/fly_embryo_annotation/. The datasets used in experiments will be available upon request to the correspondence author.

title: Automatic detection of premature ventricular contraction using quantum neural networks
abstract: Premature ventricular contractions (PVCs) are ectopic heart beats originating from ventricular area. It is a common form of heart arrhythmia. Electrocardiogram (ECG) recordings have been widely used to assist cardiologists to diagnose the problem. In this paper, we study the automatic detection of PVC using a fuzzy artificial neural network named Quantum Neural Network (QNN). With the quantum neurons in the network, trained QNN can model the levels of uncertainty arising from complex classification problems. This fuzzy feature is expected to enhance the reliability of the algorithm, which is critical for the applications in the biomedical domain. Experiments were conducted on ECG records in the MIT-BIH Arrhythmia Database. Results showed consistently higher or same reliability of QNN on all the available records compared to the backpropagation network. QNN, however, has a relatively higher resource requirement for training.

title: Toward automatic annotation of in situ mRNA expression patterns of drosophila embryos
abstract: The in situ mRNA hybridization gene expression pattern images of Drosophila melanogaster in the course of embryogenesis provide spatial-temporal information of the expression patterns of a target gene. This information is critical for understanding the roles of genes during the development of embryos. Currently, the annotation of these images is often done by manually assigning a subset of image ontology terms to the images. This approach is time consuming and depends heavily on the consistency of the experts. Alternatively, if the annotation process can be automated or semi-automated, efficiency and consistency are likely to be greatly enhanced. We formulate this task as a pattern classification problem, and present preliminary results. We consider both the template-based global matching and the multi-objective classification based on neural networks (e.g. multi-layer perceptron). We develop a method to combine them to optimize efficiency and accuracy. This method has been applied to the gene expression pattern image database generated by the Berkeley Drosophila Genome Project.

title: Verification - a method of enhancing the recognizers of isolated and touching handwritten numerals
abstract: This paper investigates verification schemes and their applications to the recognition of both isolated and touching handwritten numerals. Definitions and functionality analyses of the verifiers are given. The measurement of precision rate is used to assess the system reliability in a class-specific manner. Verification-enhanced systems are proposed with extensive experiments conducted on both isolated and touching numerals. Two databases for touching numerals are built/organized to serve as standard data sets. Experimental results indicate a substantial improvement in system precision rates by the verification scheme, which proves the effectiveness of the proposed systems and justifies the important role of verifiers in OCR systems.

title: Data driven approach to designing minimum hamming distance polychotomizer
abstract: A polychotomous classifier assigns an observation to one of the K categories with K > = 3. Multiple binary classifiers (K = 2) such as the popular Support Vector Machines can be combined to achieve multi-class classification. Commonly used approaches include the one-vs-others scheme and the one-vs-one (pairwise coupling) scheme. While literature reported better performance from pairwise coupling than one-vs-others, the number of base learners required by pairwise coupling is quadratic in K. Alternatively, error correcting output codes (ECOC) provides a more general framework for designing polychotomizers. It associates each class with a codeword, which provides the capability to unify the traditional schemes. However, the design of an effective "coding matrix" remains an open problem. We study one kind of ECOC polychotomizer that decodes using minimum hamming distance. We propose a novel data-driven way to design the codewords based on inter-cluster distance. It provides a systematic way to extend the traditional schemes and construct effective polychotomizers. Experiments are conducted on synthetic data and real world applications including UCI repository problems and CENPARMI handwritten numerals. Experiments show that the proposed scheme can achieve competitive accuracy compared with both traditional schemes, and the number of base learners is typically much less than the requirement of the pairwise scheme.

title: Recognition of handwritten numerals by Quantum Neural Network with fuzzy features
abstract: This paper describes a new kind of neural network – Quantum Neural Network (QNN) – and its application to the recognition of handwritten numerals. QNN combines the advantages of neural modelling and fuzzy theoretic principles. Novel experiments have been designed for in-depth studies of applying the QNN to both real data and confusing images synthesized by morphing. Tests on synthesized data examine QNN's fuzzy decision boundary with the intention to illustrate its mechanism and characteristics, while studies on real data prove its great potential as a handwritten numeral classifier and the special role it plays in multi-expert systems. An effective decision-fusion system is proposed and a high reliability of 99.10% has been achieved.

title: An improved ellipse propagation model for location estimation in facilitating ubiquitous computing
abstract: Positioning is a crucial technology for ubiquitous computing. A directional propagation model - the ellipse propagation model (EPM) is proposed by our research group for locating a mobile station (MS) within a radio cellular network with an accuracy that can enable a number of location based services to realize ubiquitous computing. By using a geometric algorithm, the location of the mobile station can be estimated. However, since one parameter in our geometric algorithm is fixed, errors may be induced as the surrounding environment changes. In view of this, we would like to propose a new algorithm - the iterative algorithm to provide the positioning based on EPM. With the technical support of two local mobile phone operators, we have conducted a series of experiments using real data and experiment results showed that the proposed iterative algorithm outperforms the geometric algorithm by a good margin of 18% in terms of average error.

title: Towards Automatic Assembly of Privacy-Preserved Intrusion Signatures
abstract: Intrusion signatures are used to detect and/or prevent fast-spreading worms or exploits, and usually, constructing these signatures is an automatic process without human intervention for the sake of speed. In principle, the automatic signature construction process can produce not only true-positive intrusion signatures but also false-positive ones, the latter of which poses a grave problem because they can be misused to disclose privacy information. Manual signature checking (for a whitelist) can solve the problem, but it slows down the reaction time for an attack dramatically. In this paper, we propose a mechanism to generate signatures automatically while preserving the privacy information. Essentially, we transform the original feature values within an audit trail instance into feature ranges, and then use these feature ranges to construct a privacy-preserved intrusion signature. Our current focus is on the methods constructing feature ranges, and for this purpose, several methods are proposed to discover feature ranges. The experimental results are quite encouraging: the transformation from values to ranges leads not only to the preservation of privacy but also to the enhancement of the detection performance.

title: Electronic Payment Systems with Fair On-line Verification
abstract: Electronic payment systems have been intensively studied in recent years. Generally speaking, e-payment systems can be classified into two categories, i.e., the systems with on-line verification and the systems with off-line verification. The former establishes security under the principle of preventionbefore-the-fact while the latter’s security is based on the principle of detectionafter-the-fact. On-line systems are less risky, thus more likely to be adopted by the business community. A critical issue for on-line systems is how to make a transaction fair to each transacting party such that neither party can gain advantages over the other party in a transaction. This can be addressed with a fundamental technique of fair on-line verification. In this paper, we propose a solution to fair on-line verification for electronic payment systems, in which the customer gives verifiable encryption (by a TTP’s public key) of the digital money to the shop for on-line verification, instead of giving shop the money itself. The paper not only shows the principle of applying verifiable encryption to e-payment systems, but also focuses on building up a concrete payment system.

title: Undeniable Mobile Billing Schemes
abstract: An undeniable mobile billing system allows a mobile network service provider to bill its subscribers with trustworthy evidences. Chen, Jan and Chen proposed such a billing system by introducing a trusted third party - Observer and exploiting a hash chain mechanism. In their system, the Observer provides call time evidence to both cellular carriers and subscribers for billing. In this paper, we first identify some vulnerabilities in their mobile billing system. Then, we propose an undeniable billing scheme based on a proper combination of digital signature and hash chain mechanism. The proposed scheme can achieve authentication, non-repudiation, and fairness, which are desirable security requirements for an undeniable mobile billing system.

title: An Efficient Public-Key Framework
abstract: Public-key certificates play an important role in binding the public key with the identity of the owner of the corresponding private key. A certificate might be revoked before its scheduled expiry date by the issuing CA. Efficient and timely distribution of certificate revocation information is a big challenge facing the PKI providers. Existing certificate revocation schemes place a considerable processing, communication, and storage overheads on the CA as well as the relying parties. To improve the current situation, we propose a revocation-free public-key framework, in which the maximum lifetime of a certificate is divided into short periods and the certificate could expire at the end of any period under the control of the certificate owner (or his manager in a corporate environment). The verifier can check the status of such a certificate without retrieving the revocation information from the CA. The new framework is especially useful for applications on wireless devices that are unable to make simultaneous connections. The new framework could be easily integrated into existing PKI products that support X.509-based certificates.