Speed-up fractal image compression with a fuzzy classifier

This paper presents a fractal image compression scheme incorporated with a fuzzy classifier that is optimized by a genetic algorithm. The fractal image compression scheme requires to find matching range blocks to domain blocks from all the possible division of an image into subblocks. With suitable classification of the subblocks by a fuzzy classifier we can reduce the search time for this matching process so as to speedup the encoding process in the scheme. Implementation results show that by introducing three image classes and using fuzzy classifier optimized by a genetic algorithm the encoding process can be speedup by about 40% of an unclassified encoding system.     

Predicting construction firm performance: an empirical assessment of the differential impact between industry‐ and firm‐specific factors

It is obvious that the performance of firms hinges upon the dynamics of both industry‐ and firm‐specific factors. A less obvious, and perhaps a more important, line of inquiry is that to the extent that they have a bearing on firm performance, how much do these two groups of factors respectively predict firm performance? To date, performance differences among construction firms that stem from industry‐ and firm‐specific differential effect has remained largely unexplored. Using a dataset comprising 526 firms across various construction‐related sectors, the sector‐by‐sector firm performance variation that is attributable to the heterogeneity of both industry‐ and firm‐specific characteristics was empirically examined. That statistically significant results of different effect sizes are found indicates that although these factors are often assumed to be intertwined it is possible to study their respective impact on firm performance. Future studies could usefully replicate and extend this study to construction firms in other countries to further investigate what drives firm performance under different national, industry and firm contexts.     

Participating in Health Issue‐Specific Social Networking Sites to Quit Smoking: How Does Online Social Interconnectedness Influence Smoking Cessation Self‐Efficacy?

This study examined members of health issue-specific social networking sites (SNSs) for smoking cessation, hypothesizing that social identification, bridging and bonding social capital, perceived subjective norms, and social support would impact the relationship between participation and smoking cessation self‐efficacy. Results (N = 252) of an online questionnaire revealed that participation significantly influenced each social factor, which in turn resulted in greater smoking cessation self-efficacy. By applying and extending traditional peer influence theories, a structural model predicting 5 underlying mechanisms of social interconnectedness that influence perceived behavioral control for quitting smoking was tested and supported. Implications for future research on health issue-specific SNSs are discussed.     

High-efficiency mid-infrared ZnGeP2 optical parametric oscillator in a multimode-pumped tandem optical parametric oscillator

We demonstrate a high-efficiency ZnGeP(2) optical parametric oscillator (OPO) pumped by another KTP OPO in a multimode-pumped tandem OPO configuration. The maximum optical-to-optical and slope efficiencies were 32% and 42.5%, respectively. Our setup also provides tunable multiband radiation in the 2.03-2.32-mum range and the 2.9-6.2-mum range simultaneously.     

Fractographic study of high-density polyethylene pipe

High-density polyethylene (HDPE) pipe is now being used as an alternative to medium-density polyethylene (MDPE) for gas, water, sewage and waste-water distribution systems. Laboratory tests appear to show that HDPE is more able to suppress rapid crack propagation (RCP), whilst remaining sufficient resistance under the operational circumstances that lead to the type of slow crack growth observed in service failures. There have been many fractographic studies on MDPE pipe materials, actual pipe and fittings, but little on HDPE. A fractographic study of the type of HDPE pipe in current production has been undertaken. For these tests, whole pipe sections were subjected to either static or dynamic internal (water) pressurization fatigue loading. Failure mechanisms are discussed based on the fracture morphologies resulting from these tests. A further argument for good resistance of HDPE pipe to RCP is suggested. © 1998 Chapman & Hall     

Simultaneous detection of burned areas of multiple fires in the tropics using multisensor remote-sensing data

Fires associated with recurrent El Niño events have caused severe damage to tropical peat swamp forests. Accurate quantitative information about the frequency and distribution of the burned areas is imperative to fire management but is lacking in the tropics. This article examines a novel method based on principal component analysis (PCA) of the normalized difference water index (NDWI) from multisensor data for simultaneously detecting areas burned due to multiple El Niño–related fires. The principal components of multitemporal NDWI (NDWI-PCs) were able to capture the areas burned in the 1998 and 2003 El Niño fires in NDWI-PC3 and 2, respectively. The proposed method facilitates the reduction of dimensionality in detecting the burned areas. From 22 image bands, the proposed method was able to accurately detect the burned areas of multiple fires with only three NDWI-PCs. The proposed method also shows superior performance to unsupervised classifications of the principal components of combined image bands, multitemporal NDWI, NDWI differencing and post-classification comparison methods. The results show that the 1998 El Niño fire was devastating especially to intact peat swamp forest. For degraded peat swamp forest, there was an increase in the burned area from 1998 to 2003. The proposed method offers the retrieval of accurate and reliable quantitative information on the frequency and spatial distribution of burned areas of multiple fires in the tropics. This method is also applicable to the detection of changes in general as well as the detection of vegetation changes.     

Cyanate Ester-Based Encapsulation Material for High-Temperature Applications

Cyanate ester resin-based composite materials have been proposed as potential encapsulants for high-temperature applications. The objective of this study is to develop a cyanate ester-based encapsulant, which can also serve as a flip-chip underfill as well as for traditional encapsulation. Two different materials, quartz and alumina fillers, have been studied. The impact of shapes and sizes of the fillers on the overall thermomechanical properties has been investigated. The adhesion strengths of the materials to the ceramic substrate, Kovar lid, and silicon die have also been characterized. The modulus of the resin and the shape of the fillers play a pivotal role in minimizing thermal stress, generated by coefficient of thermal expansion mismatches. Smaller filler particles were found to have better adhesion to the cyanate ester resin. The high-temperature performance of the cyanate ester-based encapsulants was evaluated by thermal aging at 300°C for up to 500 h.     

Health and wellness monitoring through wearable and ambient sensors: exemplars from home-based care of elderly with mild dementia

Monitoring and timely intervention are extremely important in the continuous management of health and wellness among all segments of the population, but particularly among those with mild dementia. In relation to this, we prescribe three design principles for the construction of services and applications. These are ambient intelligence, service continuity, and micro-context. In this paper, we provide three exemplars from our research and development activities that illustrate the use of these design principles in the construction of services and applications. All the applications are drawn from the field of care for mild dementia patients in their living quarters.