Exploration of an oculometer-based model of pilot workload

Potential relationships between eye behavior and pilot workload are discussed. A Honeywell Mark IIA oculometer was used to obtain the eye data in a fixed base transport aircraft simulation facility. The data were analyzed to determine those parameters of eye behavior which were related to changes in level of task difficulty of the simulated manual approach and landing on instruments. A number of trends and relationships between eye variables and pilot ratings were found. A preliminary equation was written based on the results of a stepwise linear regression. High variability in time spent on various instruments was related to differences in scanning strategy among pilots. A more detailed analysis of individual runs by individual pilots was performed to investigate the source of this variability more closely. Results indicated a high degree of intra-pilot variability in instrument scanning. No consistent workload related trends were found. Pupil diameter which had demonstrated a strong relationship to task difficulty was extensively re-exmained

A New Proposal for Collection and Generation of Information on Financial Institutions' Risk: the case of derivatives

This article aims at providing a new alternative for the collection of information on risks taken by financial institutions, which enables the calculation of risk tools usually used in risk management, such as VaR and stress tests. This approach should help risk managers, off-site supervision and academics in assessing the potential risks in financial institutions principally due to derivatives positions. The basic idea, for linear financial instruments, like the traditionally used by the management risk systems, is to reduce positions in risk factors and then mapping by vertices. For the nonlinear financial instruments all of the positions in different types of options – European, Americans, exotic, etc.– are represented as plain vanilla European options or replicated by portfolios of plain vanilla European options. The methodology was applied to Brazil, within the worst scenarios during the period from 1994 to 2004, and the paper demonstrates that the proposed approach captured the risks satisfactorily in the analyzed portfolios, including the risk existent in the strategies involving options, given an accepted error margin. This approach could be useful for regulators, risk managers; financial institutions and risk management modeling as it can be used as an input in general risk management models.

Dynamic scheduling in a multi-product manufacturing system

To remain competitive in global marketplace, manufacturing companies need to improve their operational practices. One of the methods to increase competitiveness in manufacturing is by implementing proper scheduling system. This is important to enable job orders to be completed on time, minimize waiting time and maximize utilization of equipment and machineries. The dynamics of real manufacturing system are very complex in nature. Schedules developed based on deterministic algorithms are unable to effectively deal with uncertainties in demand and capacity. Significant differences can be found between planned schedules and actual schedule implementation. This study attempted to develop a scheduling system that is able to react quickly and reliably for accommodating changes in product demand and manufacturing capacity. A case study, 6 by 6 job shop scheduling problem was adapted with uncertainty elements added to the data sets. A simulation model was designed and implemented using ARENA simulation package to generate various job shop scheduling scenarios. Their performances were evaluated using scheduling rules, namely, first-in-first-out (FIFO), earliest due date (EDD), and shortest processing time (SPT). An artificial neural network (ANN) model was developed and trained using various scheduling scenarios generated by ARENA simulation. The experimental results suggest that the ANN scheduling model can provided moderately reliable prediction results for limited scenarios when predicting the number completed jobs, maximum flowtime, average machine utilization, and average length of queue. This study has provided better understanding on the effects of changes in demand and capacity on the job shop schedules. Areas for further study includes: (i) Fine tune the proposed ANN scheduling model (ii) Consider more variety of job shop environment (iii) Incorporate an expert system for interpretation of results. The theoretical framework proposed in this study can be used as a basis for further investigation

Spring Reverberation: A Physical Perspective

Spring-based artificial reverberation was one of the earliest attempts at compact replication of room-like reverberation for studio use. The popularity and unique sound of this effect have given it a status and desirability apart from its original use. Standard methods for modeling analog audio effects are not well suited to modeling spring reverberation, due to the complex and dispersive nature of its mechanical vibration. Therefore, new methods must be examined. A typical impulse responses of a spring used for reverberation is examined, and important perceptual parameters identified. Mathematical models of spring vibration are considered, with the purpose of drawing conclusions relevant to their application in an audio environment. These models are used to produce new results relevant to the design of digital systems for the emulation of spring reverberation units. The numerical solution of these models via the finite difference method is considered. A set of measurements of two typical spring reverberation units are presented. 1

A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor

Toward future 'mixed reality' learning spaces for STEAM education

Digital technology is becoming more integrated and part of modern society. As this begins to happen, technologies including augmented reality, virtual reality, 3d printing and user supplied mobile devices (collectively referred to as mixed reality) are often being touted as likely to become more a part of the classroom and learning environment. In the discipline areas of STEAM education, experts are expected to be at the forefront of technology and how it might fit into their classroom. This is especially important because increasingly, educators are finding themselves surrounded by new learners that expect to be engaged with participatory, interactive, sensory-rich, experimental activities with greater opportunities for student input and creativity. This paper will explore learner and academic perspectives on mixed reality case studies in 3d spatial design (multimedia and architecture), paramedic science and information technology, through the use of existing data as well as additional one-on-one interviews around the use of mixed reality in the classroom. Results show that mixed reality can provide engagement, critical thinking and problem solving benefits for students in line with this new generation of learners, but also demonstrates that more work needs to be done to refine mixed reality solutions for the classroom