Jarrod Trevathan

Bio: Jarrod Trevathan is an academic researcher from Griffith University. The author has contributed to research in topics: Common value auction & Bidding. The author has an hindex of 16, co-authored 95 publications receiving 880 citations. Previous affiliations of Jarrod Trevathan include James Cook University.

Neural Network-based Handwritten Signature Verification

Abstract: Handwritten signatures are considered as the most natural method of authenticating a person’s identity (compared to other biometric and cryptographic forms of authentication). The learning process inherent in Neural Networks (NN) can be applied to the process of verifying handwritten signatures that are electronically captured via a stylus. This paper presents a method for verifying handwritten signatures by using a NN architecture. Various static (e.g., height, slant, etc.) and dynamic (e.g., velocity, pen tip pressure, etc.) signature features are extracted and used to train the NN. Several Network topologies are tested and their accuracy is compared. The resulting system performs reasonably well with an overall error rate of 3:3% being reported for the best case.

Detecting shill bidding in online English auctions

Abstract: Shill bidding is where spurious bids are introduced into an auction to drive up the final price for the seller, thereby defrauding legitimate bidders. While shilling is recognized as a problem, presently there is little or no established means of defense against shills. This chapter presents an algorithm to detect the presence of shill bidding in online auctions. It observes bidding patterns over a series of auctions, providing each bidder a score indicating the likelihood of his/her potential involvement in shill behavior. The algorithm has been tested on data obtained from a series of realistic simulated auctions, and commercial online auctions. The algorithm is able to prune the search space required to detect which bidders are likely to be shills. This has significant practical and legal implications for commercial online auctions where shilling is considered a major threat. This chapter presents a framework for a feasible solution, which acts as a detection mechanism and a deterrent.

Artificial Intelligence in Sports Prediction

Abstract: This paper presents an extension of earlier work in the use of artificial intelligence for prediction of sporting outcomes. An expanded model is described, as well as a broadening of the area of application of the original work. The model used is a form of multi-layer perceptron and it is presented with a number of features which attempt to capture the quality of various sporting teams. The system performs well and compares favourably with human tipsters in several environments. A study of less rigid "World Cup" formats appears, along with extensive live testing results in a major international tipping competition.

Neural Network-based Hwritten Signature Verification.

Abstract: Handwritten signatures are considered as the most natural method of authenticating a person’s identity (compared to other biometric and cryptographic forms of authentication). The learning process inherent in Neural Networks (NN) can be applied to the process of verifying handwritten signatures that are electronically captured via a stylus. This paper presents a method for verifying handwritten signatures by using a NN architecture. Various static (e.g., height, slant, etc.) and dynamic (e.g., velocity, pen tip pressure, etc.) signature features are extracted and used to train the NN. Several Network topologies are tested and their accuracy is compared. The resulting system performs reasonably well with an overall error rate of 3:3% being reported for the best case.

SEMAT — The Next Generation of Inexpensive Marine Environmental Monitoring and Measurement Systems

Abstract: There is an increasing need for environmental measurement systems to further science and thereby lead to improved policies for sustainable management. Marine environments are particularly hostile and extremely difficult for deploying sensitive measurement systems. As a consequence the need for data is greatest in marine environments, particularly in the developing economies/regions. Expense is typically the most significant limiting factor in the number of measurement systems that can be deployed, although technical complexity and the consequent high level of technical skill required for deployment and servicing runs a close second. This paper describes the Smart

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

[서평]「Applied Cryptography」

Abstract: The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

Underwater sensor network applications: a comprehensive survey

Abstract: There is no escaping fact that a huge amount of unexploited resources lies underwater which covers almost 70% of the Earth. Yet, the aquatic world has mainly been unaffected by the recent advances in the area of wireless sensor networks (WSNs) and their pervasive penetration in modern day research and industrial development. The current pace of research in the area of underwater sensor networks (UWSNs) is slow due to the difficulties arising in transferring the state-of-the-art WSNs to their underwater equivalent. Maximum underwater deployments rely on acoustics for enabling communication combined with special sensors having the capacity to take on harsh environment of the oceans. However, sensing and subsequent transmission tend to vary as per different subsea environments; for example, deep sea exploration requires altogether a different approach for communication as compared to shallow water communication. This paper particularly focuses on comprehensively gathering most recent developments in UWSN applications and their deployments. We have classified the underwater applications into five main classes, namely, monitoring, disaster, military, navigation, and sports, to cover the large spectrum of UWSN. The applications are further divided into relevant subclasses. We have also shown the challenges and opportunities faced by recent deployments of UWSN.