Governance challenges in the global games industry

Current governance challenges facing the global games industry are heavily dominated by online games. Whilst much academic and industry attention has been afforded to Virtual Worlds, the more pressing contemporary challenges may arise in casual games, especially when found on social networks. As authorities are faced with an increasing volume of disputes between participants and platform operators, the likelihood of external regulation increases, and the role that such regulation would have on the industry – both internationally and within specific regions – is unclear. Kelly (2010) argues that “when you strip away the graphics of these [social] games, what you are left with is simply a button [...] You push it and then the game returns a value of either Win or Lose”. He notes that while “every game developer wants their game to be played, preferably addictively, because it’s so awesome”, these mechanics lead not to “addiction of engagement through awesomeness” but “the addiction of compulsiveness”, surmising that “the reality is that they’ve actually sort-of kind-of half-intentionally built a virtual slot machine industry”. If such core elements of social game design are questioned, this gives cause to question the real-money options to circumvent them. With players able to purchase virtual currency and speed the completion of tasks, the money invested by the 20% purchasing in-game benefits (Zainwinger, 2012) may well be the result of compulsion. The decision by the Japanese Consumer Affairs agency to investigate the ‘Kompu Gacha’ mechanic (in which players are rewarded for completing a set of items obtained through purchasing virtual goods such as mystery boxes), and the resultant verdict that such mechanics should be regulated through gambling legislation, demonstrates that politicians are beginning to look at the mechanics deployed in these environments. Purewal (2012) states that “there’s a reasonable argument that complete gacha would be regulated under gambling law under at least some (if not most) Western jurisdictions”. This paper explores the governance challenged within these games and platforms, their role in the global industry, and current practice amongst developers in the Australian and United States to address such challenges.

Condition-based prognosis of machine health

Modern machines are complex and often required to operate long hours to achieve production targets. The ability to detect symptoms of failure, hence, forecasting the remaining useful life of the machine is vital to prevent catastrophic failures. This is essential to reducing maintenance cost, operation downtime and safety hazard. Recent advances in condition monitoring technologies have given rise to a number of prognosis models that attempt to forecast machinery health based on either condition data or reliability data. In practice, failure condition trending data are seldom kept by industries and data that ended with a suspension are sometimes treated as failure data. This paper presents a novel approach of incorporating historical failure data and suspended condition trending data in the prognostic model. The proposed model consists of a FFNN whose training targets are asset survival probabilities estimated using a variation of Kaplan-Meier estimator and degradation-based failure PDF estimator. The output survival probabilities collectively form an estimated survival curve. The viability of the model was tested using a set of industry vibration data.

Machine prognostics based on health state probability estimation

The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation and can also improve productivity and enhance system’s safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. Although a variety of prognostic methodologies have been reported recently, their application in industry is still relatively new and mostly focused on the prediction of specific component degradations. Furthermore, they required significant and sufficient number of fault indicators to accurately prognose the component faults. Hence, sufficient usage of health indicators in prognostics for the effective interpretation of machine degradation process is still required. Major challenges for accurate longterm prediction of remaining useful life (RUL) still remain to be addressed. Therefore, continuous development and improvement of a machine health management system and accurate long-term prediction of machine remnant life is required in real industry application. This thesis presents an integrated diagnostics and prognostics framework based on health state probability estimation for accurate and long-term prediction of machine remnant life. In the proposed model, prior empirical (historical) knowledge is embedded in the integrated diagnostics and prognostics system for classification of impending faults in machine system and accurate probability estimation of discrete degradation stages (health states). The methodology assumes that machine degradation consists of a series of degraded states (health states) which effectively represent the dynamic and stochastic process of machine failure. The estimation of discrete health state probability for the prediction of machine remnant life is performed using the ability of classification algorithms. To employ the appropriate classifier for health state probability estimation in the proposed model, comparative intelligent diagnostic tests were conducted using five different classifiers applied to the progressive fault data of three different faults in a high pressure liquefied natural gas (HP-LNG) pump. As a result of this comparison study, SVMs were employed in heath state probability estimation for the prediction of machine failure in this research. The proposed prognostic methodology has been successfully tested and validated using a number of case studies from simulation tests to real industry applications. The results from two actual failure case studies using simulations and experiments indicate that accurate estimation of health states is achievable and the proposed method provides accurate long-term prediction of machine remnant life. In addition, the results of experimental tests show that the proposed model has the capability of providing early warning of abnormal machine operating conditions by identifying the transitional states of machine fault conditions. Finally, the proposed prognostic model is validated through two industrial case studies. The optimal number of health states which can minimise the model training error without significant decrease of prediction accuracy was also examined through several health states of bearing failure. The results were very encouraging and show that the proposed prognostic model based on health state probability estimation has the potential to be used as a generic and scalable asset health estimation tool in industrial machinery.

A voting mechanism for named entity translation in English-Chinese question answering

In this paper, we describe a voting mechanism for accurate named entity (NE) translation in English–Chinese question answering (QA). This mechanism involves translations from three different sources: machine translation,online encyclopaedia, and web documents. The translation with the highest number of votes is selected. We evaluated this approach using test collection, topics and assessment results from the NTCIR-8 evaluation forum. This mechanism achieved 95% accuracy in NEs translation and 0.3756 MAP in English–Chinese cross-lingual information retrieval of QA.

Interactive conference voting

We describe and analyze opinion polling results from interactive voting procedures undertaken before and after presentations during the Outcome Measures in Rheumatoid Arthritis Clinical Trials Conference (OMERACT II) in Ottawa, Canada, June 30-July 2, 1994. The scoring procedure was a matched voting design; when a participant used the same keypad at the beginning and end of voting, change within a participant could be estimated. Participants, experienced in the rheumatic diseases included clinicians, researchers, methodologists, regulators, and representatives of the pharmaceutical industry. Patients under consideration were those with any rheumatic diseases. Questions were constructed to evaluate the change in voting behavior expected from the content of the presentation. Statistically significant and substantively important changes were evident in most questions.

Robot control of a 3,500 tonne mining machine

The mining industry is highly suitable for the application of robotics and automation technology since the work is arduous, dangerous and often repetitive. This paper describes the development of an automation system for a physically large and complex field robotic system - a 3,500 tonne mining machine (a dragline). The major components of the system are discussed with a particular emphasis on the machine/operator interface. A very important aspect of this system is that it must work cooperatively with a human operator, seamlessly passing the control back and forth in order to achieve the main aim - increased productivity.

Applications of real-time machine vision to the control of mining equipment

The mining industry presents us with a number of ideal applications for sensor based machine control because of the unstructured environment that exists within each mine. The aim of the research presented here is to increase the productivity of existing large compliant mining machines by retrofitting with enhanced sensing and control technology. The current research focusses on the automatic control of the swing motion cycle of a dragline and an automated roof bolting system. We have achieved: * closed-loop swing control of an one-tenth scale model dragline; * single degree of freedom closed-loop visual control of an electro-hydraulic manipulator in the lab developed from standard components.