Process Comprehension for Interoperable CNC Manufacturing

Over the last 40 years manufacturing industry has enjoyed a rapid growth with the support of various computer-aided systems (CAD, CAPP, CAM etc.) known as CAx. Since the first Numerically Controlled (NC) machine appeared in 1952, there have been many advances in CAx resource capabilities. The information integration and interoperability between different manufacturing resources has become an important and popular research area over the last decade. Computer Numerically Controlled (CNC) machines are an important link in the manufacturing chain and the major contributor to the production capacity of manufacturing industry today. However, most of the research has focused on the information integration of upper systems in the CAD/CAPP /CAM/CNC manufacturing chain, leaving the shop floor as an isolated information island. In particular, there is limited opportunity to capture and feed shopfloor knowledge back to the upper systems. Furthermore, the part programs for the machines are not exchangeable due to the. machine specific postprocessors. Thus there is a further need to consider information interoperability between different CNC machine and other systems. This research investigates the reverse transformation of the CNC part programmes into higher level of process information, entitled process comprehension, to enable the shopfloor interoperability. A novel framework of universal process comprehension is specified and designed. The framework provides a reverse direction of information flow from the CNC machine to upper CAx systems, enabling the interoperability and recycling of the shopfloor knowledge. A prototype implementation of the framework is realised and utilised to demonstrate the functionalities through three industrially inspired test components. The major contribution of this research to knowledge is the new vision of the shopfloor interoperability associated with process knowledge capture and reuse. The research shows that process comprehension of part programmes can provide an effective solution to the issues of the shopfloor interoperability and knowledge reuse in manufacturing industries.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Fraud Prevention using Automated Audit Systems: A Strategic Imperative

This study examines a mathematical model to determine the timing and consequently volume of transactions to be audited in a continuous audit system to detect potentially fraudulent transactions. The interactions between the audit system and a potential fraudster are modeled as Continuous Time Markov Chain and the transition probabilities from one state to another are determined using game theoretic approach. We believe that such a model has the potential to be deployed in an audit system to detect potentially fraudulent or malicious transactions. In this research, the information system is modeled as a continuous time Markov chain (CTMC), where the transition from one state to another occurs due to actions of a person with malicious intent. The present state of the system depends only on the past state. At each state, the fraudster can either continue with the next step in the fraud or can cease and desist from the fraud. The interaction between the actions of the audit module and fraudster is modeled as a two-player simultaneous zero-sum game and the probability of transition from one state to another is derived from the payoff table. This payoff will be decided by the outcome of a game theoretic model. A sensitivity analysis showed that when an organization has strong anti-fraud controls, the probability of fraud decreases and the need for frequent audit decreases. The limitations of the model are that, the game theory model assumes a zero-sum game where the payoffs are known and certain. Keywords: Continuous Audit Systems, Game Theory, Audit Timing, Fraud prevention, Sensitivity analysis

Multi-Person Brain Activity Recognition via Comprehensive EEG Signal Analysis

An electroencephalography (EEG) based brain activity recognition is a fundamental field of study for a number of significant applications such as intention prediction, appliance control, and neurological disease diagnosis in smart home and smart healthcare domains. Existing techniques mostly focus on binary brain activity recognition for a single person, which limits their deployment in wider and complex practical scenarios. Therefore, multi-person and multi-class brain activity recognition has obtained popularity recently. Another challenge faced by brain activity recognition is the low recognition accuracy due to the massive noises and the low signal-to-noise ratio in EEG signals. Moreover, the feature engineering in EEG processing is time-consuming and highly re- lies on the expert experience. In this paper, we attempt to solve the above challenges by proposing an approach which has better EEG interpretation ability via raw Electroencephalography (EEG) signal analysis for multi-person and multi-class brain activity recognition. Specifically, we analyze inter-class and inter-person EEG signal characteristics, based on which to capture the discrepancy of inter-class EEG data. Then, we adopt an Autoencoder layer to automatically refine the raw EEG signals by eliminating various artifacts. We evaluate our approach on both a public and a local EEG datasets and conduct extensive experiments to explore the effect of several factors (such as normalization methods, training data size, and Autoencoder hidden neuron size) on the recognition results. The experimental results show that our approach achieves a high accuracy comparing to competitive state-of-the-art methods, indicating its potential in promoting future research on multi-person EEG recognition.Comment: 10 page

Determinants of Capital Structure of Firms in Pre-Post Financial Crisis: Evidence from China

This paper examines the impact of the global financial crisis of 2007-08 on 897 Chinese listed non-financial firms by examining changes in their capital structure from 2003 to 2012. Panel data technique has been used and it is found that there is noticeable change on both firm level and macroeconomic level determinants of the capital structure after the financial crisis. Regression analysis has provided very significant results. In full period regression, liquidity has shown no change in both pre-post financial crisis time periods, while tax, non-debt tax shield, tangibility, economic development and inflation have shown a very significant and distinct change after crisis.  But at the same time volatility has shown a very significant change in long term and in total leverage while profitability and size has shown significant change just in short term leverage after crisis. Growth potential has shown significant change only in total leverage after crisis. Analysis shows that pecking order theory has more explanations than static trade-off theory and market timing theory after the financial crisis for Chinese listed non-financial firms. KEY WORDS: leverage; financial crisis; pecking order theory; capital structure; non-financial Chinese firm

Sustainability, Profitability and Outreach Tradeoffs: Evidences from Microfinance Institutions in East Africa

The aim of the study was to examine the presence of tradeoffs between sustainability, profitability and outreach to the poor. The study was conducted in East African using a panel data of 47 Microfinance institutions for four years period. Using Welfarists approach the study found out that profitability focus has a negative impact on outreach to the poor, implying the presence of tradeoffs. The results on financial sustainability did not show presence tradeoffs with the outreach measures. Under Institutionalist view, the study found out that outreach to the poor has a positive relationship with both sustainability and profitability measures. The study concludes that, the possibility of tradeoffs exists between outreach to the poor with profitability measures as compared to the outreach with financial sustainability. The presence of tradeoffs between financial performance and outreach to the poor also depends on the variables used and estimation model specification. Some variables which indicated the existence of tradeoffs under Welfarists views did do not show such impact under Institutionalist views. The study recommends that Microfinance institutions in East Africa should focus on financial sustainability in order to reduce their subsidy dependence, ensure survival and growth in the future. To the policy makers the study recommends that sustainability does not compromise the outreach to the poor. The government should review their policies governing Microfinance institutions to ensure that the institutions are directed towards sustainability. The government should also allow institutions to mobilize savings and offer other financial services to broaden their activities and the outreach to the poor. Keywords: Sustainability, Profitability, Outreach, Microfinance Institutions, East Africa