Automatic Data Collection Design for Neural Networks Detection of Occupational Frauds

Automated data collection is necessary to alleviate problems inherent in data collection for investigation of management frauds. Once we have gathered a realistic data, several methods then exist for proper analysis and detection of anomalous transactions. However, in Nigeria, collecting fraudulent data is relatively difficult and the human labour involved is expensive and risky. This paper examines some formal procedures for data collection and proposes designing an automatic data collection system for detection of occupational frauds using artificial neural networks.

The Design of an Online Petri Net Based Token (Ludo) Game

The behavior of Petri nets with exponentially distributed firing times can be represented by labeled directed "slate" graphs in which labels describe the probabilities of transition firings (displacement of tokens) between vertices of the graph. The interactive firing of transitions in subsequent markings is known as token game. This development is analogous to that of games of strategy, in which each player is assigned a set of possible strategies (actions or moves) and each possible combination of strategies, one for each player, produces an outcome. That is, player's fortunes are intertwined and determined by chance events. The design of an interactive Petri net-based token (ludo) game is presented in which transition firing is determined by dice cast. Programming is considered and developed in Visual Basic 6.0 programming language, which is an object-oriented, event-driven and visual programming environment

Software Design Modelling with Functional Petri Nets

Petri Nets use two basic primitives: events and conditions to view or model a system. Events are the actions that take place in the system. The occurrence of events is controlled by the "state" of the system, which can be described as a set of conditions. An immediate application of such a model is in the control structures of conventional programming languages. Control structures are the backbone of every programming language. In this paper, an equivalent functional Petri Net (FPN) model is developed for each of the three constructs of structured programs and a FPN Software prototype proposed for the conventional programming construct: if-then-else statement. The motivating idea is essentially to show that FPNs could be used as an alternative approach for program design

Automatic Data Collection Design for Real-Time Detection of Oil-Spillage Disasters in Nigeria

Oil-spillage disaster is a phenomenon that has thrived and come to stay especially in the Niger Delta region in Nigeria where crude oil is produced both on-shored and off-shored resulting in the loss of billions of crude oils and corresponding loss of income every year. Such disasters can occur at any point within the entire oil-pipeline topology, which is geographically dispersed across the country spanning from the extreme south-south through south-east and south-west to the north central. A major cause of oil spillage disaster is oil-pipeline vandalism, which has recently become one of the primary means of defrauding the Nation by oil bunkers and even angry youths of the host communities. Currently in Nigeria oil spillage disaster is monitored manually under the auspices of the National Emergency Management Agency (NEMA) and involves huge human labor as gathering of useful data has proven to be difficult and untimely using traditional data collection methods given the peculiarity of the operational terrain. An automated data collection design (ADCD) for real-time data collection on oil spillages in the on-shore, mangrove, thick forest and off-shore areas of the Nation offers the much needed solution. This paper examined some current procedures for data collection and highlighted inherent pitfalls. It further presented a robust architecture and model for real-time detection of oil-spillage and discussed incorporated contemporary technological requirements. The major advantages and disadvantages of the proposed system were also discussed

Credit Risk Evaluation System: An Artificial Neural Network Approach

Decisions concerning credits granting are one of the most crucial issues in an everyday banks’ policy. Well-allocated credits may become one of the biggest sources of profits for any financial organizations. On the other hand, this kind of bank’s activity is connected with high risk as big amount of bad decisions may even cause bankruptcy. The key problem consists of distinguishing good (that surely repay) and bad (that likely default) credit applicants. Credit risk evaluation is an important and interesting management science problem in financial analysis. The main idea in credit risk evaluation investigations consists of building classification rules that properly assess bank customers as good or bad. In this paper, we proposed an architecture which uses the theory of artificial neural networks and business rules to correctly determine whether a customer is good or bad. In the first step, by using clustering algorithm, clients are segmented into groups with similar features. In the second step, decision trees are built based on classification rules defined for each group of clients. To avoid redundancy, different attributes are taken into consideration during each phase of classification. The proposed approach allows for using different rules within the same data set, and for defining more accurately clients with high risk. Preliminary result indicates that the model presented is promising and reasonable

Petri Net Modeling of Computer Virus Life Cycle

Virus life cycle, which refers to the stages of development of a computer virus, is presented as a suitable area for the application of Petri nets. Petri nets a powerful modeling tool in the field of dynamic system analysis is applied to model the virus life cycle. Simulation of the derived model is also presented. The intention of this paper essentially is to show that similar procedure can be used to derive anti-viral programs based on the Petri net framework.