Refractive error, cognitive demand and nearwork-induced transient myopia

Purpose. Whereas many previous studies have identified the association between sustained near work and myopia, few have assessed the influence of concomitant levels of cognitive effort. This study investigates the effect of cognitive effort on near-work induced transient myopia (NITM). Methods. Subjects comprised of six early onset myopes (EOM; mean age 23.7 yrs; mean onset 10.8 yrs), six late-onset myopes (LOM; mean age 23.2 yrs; mean onset 20.0 yrs) and six emmetropes (EMM; mean age 23.8 yrs). Dynamic, monocular, ocular accommodation was measured with the Shin-Nippon SRW-5000 autorefractor. Subjects engaged passively or actively in a 5 minute arithmetic sum checking task presented monocularly on an LCD monitor via a Badal optical system. In all conditions the task was initially located at near (4.50 D) and immediately following the task instantaneously changed to far (0.00 D) for a further 5 minutes. The combinations of active (A) and passive (P) cognition were randomly allocated as P:P; A:P; A:A; P:A. Results. For the initial near task, LOMs were shown to have a significantly less accurate accommodative response than either EOMs or EMMs (p < 0.001). For the far task, post hoc analyses for refraction identified EOMs as demonstrating significant NITM compared to LOMs (p < 0.05), who in turn showed greater NITM than EMMs (p < 0.001). The data show that for EOMs the level of cognitive activity operating during the near and far tasks determines the persistence of NITM; persistence being maximal when active cognition at near is followed by passive cognition at far. Conclusions. Compared with EMMs, EOMs and LOMs are particularly susceptible to NITM such that sustained near vision reduces subsequent accommodative accuracy for far vision. It is speculated that the marked NITM found in EOM may be a consequence of the crystalline lens thinning shown to be a developmental feature of EOM. Whereas the role of small amounts of retinal defocus in myopigenesis remains equivocal, the results show that account needs to be taken of cognitive demand in assessing phenomena such as NITM.

ACARS:adaptive context - aware rate selection for DSRC in vehicular networks

Throughput plays a vital role for data transfer in Vehicular Networks which is useful for both safety and non-safety applications. An algorithm that adapts to mobile environment by using Context information has been proposed in this paper. Since one of the problems of existing rate adaptation algorithm is underutilization of link capacity in Vehicular environments, we have demonstrated that in wireless and mobile environments, vehicles can adapt to high mobility link condition and still perform better due to regular vehicles that will be out of communication range due to range checking and then de-congest the network thereby making the system perform better since fewer vehicles will contend for network resources. In this paper, we have design, implement and analyze ACARS, a more robust algorithm with significant increase in throughput performance and energy efficiency in the mist of high mobility of vehicles.

Ontology-based pathways generation for biomass to bioenergy conversion

Bio energy is a renewable energy and a solution to the depleting fossil fuels. Bio energy such as heat, power and bio fuel is generated by conversion technologies using biomass for example domestic waste, root crops, forest residue and animal slurry. Pyrolysis, anaerobic digestion and combined heat and power engine are some examples of the technologies. Depending on the nature of a biomass, it can be treated with various technologies giving out some products, which can be further treated with other technologies and eventually converted into the final products as bio energy. The pathway followed by the biomass, technologies, intermediate products and bio energy in the conversion process is referred to as bio energy pathway. Identification of appropriate pathways optimizes the conversion process. Although there are various approaches to create or generate the pathways, there is still a need for a semantic approach to generate the pathways, which allow checking the consistency of the knowledge, and to share and extend the knowledge efficiently. This paper presents an ontology-based approach to automatic generation of the pathways for biomass to bio energy conversion, which exploits the definition and hierarchical structure of the biomass and technologies, their relationship and associated properties, and infers appropriate pathways. A case study has been carried out in a real-life scenario, the bio energy project for the North West of Europe (Bioen NW), which showed promising results.

Research on rework strategies for reconfigurable manufacturing system considering mission reliability

Rework strategies that involve different checking points as well as rework times can be applied into reconfigurable manufacturing system (RMS) with certain constraints, and effective rework strategy can significantly improve the mission reliability of manufacturing process. The mission reliability of process is a measurement of production ability of RMS, which serves as an integrated performance indicator of the production process under specified technical constraints, including time, cost and quality. To quantitatively characterize the mission reliability and basic reliability of RMS under different rework strategies, rework model of RMS was established based on the method of Logistic regression. Firstly, the functional relationship between capability and work load of manufacturing process was studied through statistically analyzing a large number of historical data obtained in actual machining processes. Secondly, the output, mission reliability and unit cost in different rework paths were calculated and taken as the decision variables based on different input quantities and the rework model mentioned above. Thirdly, optimal rework strategies for different input quantities were determined by calculating the weighted decision values and analyzing advantages and disadvantages of each rework strategy. At last, case application were demonstrated to prove the efficiency of the proposed method.

Formal methods for the development and verification of autonomic IT systems

This chapter explores ways in which rigorous mathematical techniques, termed formal methods, can be employed to improve the predictability and dependability of autonomic computing. Model checking, formal specification, and quantitative verification are presented in the contexts of conflict detection in autonomic computing policies, and of implementation of goal and utility-function policies in autonomic IT systems, respectively. Each of these techniques is illustrated using a detailed case study, and analysed to establish its merits and limitations. The analysis is then used as a basis for discussing the challenges and opportunities of this endeavour to transition the development of autonomic IT systems from the current practice of using ad-hoc methods and heuristic towards a more principled approach. © 2012, IGI Global.

Design software architecture models using ontology

Software architecture plays an essential role in the high level description of a system design, where the structure and communication are emphasized. Despite its importance in the software engineering process, the lack of formal description and automated verification hinders the development of good software architecture models. In this paper, we present an approach to support the rigorous design and verification of software architecture models using the semantic web technology. We view software architecture models as ontology representations, where their structures and communication constraints are captured by the Web Ontology Language (OWL) and the Semantic Web Rule Language (SWRL). Specific configurations on the design are represented as concrete instances of the ontology, to which their structures and dynamic behaviors must conform. Furthermore, ontology reasoning tools can be applied to perform various automated verification on the design to ensure correctness, such as consistency checking, style recognition, and behavioral inference.