Impacts of geographical knowledge, spatial ability and environmental cognition on image searches supported by GIS software

Google Earth search function was used to study the impacts of small-scale spatial ability, large-scale environmental cognition, and geographical knowledge on new technology usage. The participants were 153 junior high students from central Taiwan. Geography grades served as indicators of prior knowledge, mental rotation and abstract reasoning skills as indicators of spatial ability, and sketch maps of school neighborhoods as indicators of environmental cognition (including landmark representation, intersection representation, and frame of reference). Lastly, the authors announced the landmarks searching worksheet and asked the participants to accomplish 16 familiar and unfamiliar landmark searching tasks using Google Earth with keyword search function disabled. The result showed the strongest predictor of landmark searching performance is ‘frame of reference’ in environmental cognition, followed by ‘mental rotation’ of spatial ability, ‘landmark representation’ of environmental cognition, and geographical knowledge. Google Earth landmark searches require complex cognitive processing; therefore, our conclusion is that GIS-supported image search activities give students good practice of active knowledge construction.     

Multi-Scale Adaptive Sampling with Mobile Agents for Mapping of Forest Fires

The use of robotics in distributed monitoring applications requires wireless sensors that are deployed efficiently. A very important aspect of sensor deployment includes positioning them for sampling at locations most likely to yield information about the spatio-temporal field of interest, for instance, the spread of a forest fire. In this paper, we use mobile robots (agents) that estimate the time-varying spread of wildfires using a distributed multi-scale adaptive sampling strategy. The proposed parametric sampling algorithm, “EKF-NN-GAS” is based on neural networks, the extended Kalman filter (EKF), and greedy heuristics. It combines measurements arriving at different times, taken at different scale lengths, such as from ground, airborne, and spaceborne observation platforms. One of the advantages of our algorithm is the ability to incorporate robot localization uncertainty in addition to sensor measurement and field parameter uncertainty into the same EKF model. We employ potential fields, generated naturally from the estimated fire field distribution, in order to generate fire-safe trajectories that could be used to rescue vehicles and personnel. The covariance of the EKF is used as a quantitative information measure for sampling locations most likely to yield optimal information about the sampled field distribution. Neural net training is used infrequently to generate initial low resolution estimates of the fire spread parameters. We present simulation and experimental results for reconstructing complex spatio-temporal forest fire fields “truth models”, approximated by radial basis function (RBF) parameterizations. When compared to a conventional raster scan approach, our algorithm shows a significant reduction in the time necessary to map the fire field.     

Integrating spectral indices with environmental parameters for estimating heavy metal concentrations in rice using a dynamic fuzzy neural-network model

A generalized dynamic fuzzy neural network (GDFNN) was created to estimate heavy metal concentrations in rice by integrating spectral indices and environmental parameters. Hyperspectral data, environmental parameters, and heavy metal content were collected from field experiments with different levels of heavy metal pollution (Cu and Cd). Input variables used in the GDFNN model were derived from 10 variables acquired by gray relational analysis. The assessment models for Cd and Cu concentration employed five and six input variables, respectively. The results showed that the GDFNN for estimating Cu and Cd concentrations in rice performed well at prediction with a compact network structure using the training, validation, and testing sets (for Cu, fuzzy rules=9, R² greater than 0.75, and RMSE less than 2.5; for Cd, fuzzy rules=9, R² greater than 0.75, and RMSE less than 1.0). The final GDFNN model was then compared with a back-propagation (BP) neural network model, adaptive-network-based fuzzy interference systems (ANFIS), and a regression model. The accuracies of GDFNN model prediction were usually slightly better than those of the other three models. This demonstrates that the GDFNN model is more suitable for predicting heavy metal concentrations in rice.     

INTAMAP: The design and implementation of an interoperable automated interpolation web service

INTAMAP is a Web Processing Service for the automatic spatial interpolation of measured point data. Requirements were (i) using open standards for spatial data such as developed in the context of the Open Geospatial Consortium (OGC), (ii) using a suitable environment for statistical modelling and computation, and (iii) producing an integrated, open source solution. The system couples an open-source Web Processing Service (developed by 52°North), accepting data in the form of standardised XML documents (conforming to the OGC Observations and Measurements standard) with a computing back-end realised in the R statistical environment. The probability distribution of interpolation errors is encoded with UncertML, a markup language designed to encode uncertain data. Automatic interpolation needs to be useful for a wide range of applications and the algorithms have been designed to cope with anisotropy, extreme values, and data with known error distributions. Besides a fully automatic mode, the system can be used with different levels of user control over the interpolation process.     

Inside the adaptive enterprise: an information technology capabilities perspective on business process agility

Recent innovations in utility computing, web services, and service-oriented architectures, combined with a growing array of IT skills, have improved firms’ ability to be more agile in responding to change. Using the resource-based view of the firm, prior research suggests that IT resources, in isolation, are unlikely to yield superior performance and so as firms try to boost their agility, the question becomes how to configure IT resources to prepare for, or react to, change. In this paper, we posit that managerial IT capabilities based on IT-business partnerships, strategic planning, and ex-post IT project analysis lead to the development of technical IT capabilities associated with a flexible IT infrastructure which in turn drives agility or a firm’s ability to react to change in its products and markets. Using data from matched surveys of IT and business executives in 241 firms, we find that managerial and technical capabilities affect agility. In further testing, we reveal that in a stable setting, technical IT capabilities are more important to agility than managerial IT capabilities, while in a dynamic setting, the opposite is true. Thus, for firms operating in volatile markets, effective models of managerial IT governance are essential for delivering superior agility or adaptiveness.

MobGeoSen: facilitating personal geosensor data collection and visualization using mobile phones

Mobile sensing and mapping applications are becoming more prevalent because sensing hardware is becoming more portable and more affordable. However, most of the hardware uses small numbers of fixed sensors that report and share multiple sets of environmental data which raises privacy concerns. Instead, these systems can be decentralized and managed by individuals in their public and private spaces. This paper describes a robust system called MobGeoSens which enables individuals to monitor their local environment (e.g. pollution and temperature) and their private spaces (e.g. activities and health) by using mobile phones in their day to day life. The MobGeoSen is a combination of software components that facilitates the phone’s internal sensing devices (e.g. microphone and camera) and external wireless sensors (e.g. data loggers and GPS receivers) for data collection. It also adds a new dimension of spatial localization to the data collection process and provides the user with both textual and spatial cartographic displays. While collecting the data, individuals can interactively add annotations and photos which are automatically added and integrated in the visualization file/log. This makes it easy to visualize the data, photos and annotations on a spatial and temporal visualization tool. In addition, the paper will present ways in which mobile phones can be used as noise sensors using an on-device microphone. Finally, we present our experiences with school children using the above mentioned system to measure their exposure to environmental pollution.

Technology roles and paths of influence in an ecosystem model of technology evolution

We propose a new conceptual model for understanding technology evolution that highlights dynamic and highly interdependent relationships among multiple technologies. We argue that, instead of considering technologies in isolation, technology evolution is best viewed as a dynamic system or ecosystem that includes a variety of interrelated technologies. By considering the interdependent nature of technology evolution, we identify three roles that technologies play within a technology ecosystem. These roles are components, products and applications, and support and infrastructure. Technologies within an ecosystem interact through these roles and impact each others’ evolution. We also classify types of interactions between technology roles, which we term paths of influence. We demonstrate the use of our proposed model through examples of wireless networking (Wi-Fi) technologies and a business mini-case on the digital music industry.

Toxicoproteomics and its application to human health risk assessment

Toxicoproteomics is the use of proteomic technologies to better understand environmental and genetic factors, toxic mechanisms, and modes of action in response to acute exposure to toxicants and in the long-term development of diseases caused or influenced by these exposures. Use of toxicoproteomic technologies to identify key biochemical pathways, mechanisms, and biomarkers of exposure and toxicity will decrease the uncertainties that are associated with human health risk assessments. This review provides an overview of toxicoproteomics from human health risk assessment perspectives. Key toxicoproteomic technologies such as 2-D gel-based proteomic methods and toxicoproteomic approaches are described, and examples of applications of these technologies and methodologies in the risk assessment context are presented. The discussion includes a focus on challenges and future directions.     

国家环境监理信息系统的开发研究

概述了国家环境监理信息系统的设计目标、结构、工作原理、实现功能、技术创新和未来展望。     

Environmental support hypothesis in designing multimedia training for older adults: Is less always more?

This study explores younger and older adults learning of MS Publisher functionalities from a multimedia tutorial. Twenty younger and twenty three older adults assigned to a redundant (experimental) or non-redundant (control) condition were taught how to create a greeting card, while the results of their learning were assessed with immediate and delayed performance measures. While younger learners benefited from a non-redundant condition, older learners exhibited an opposite trend. Redundant condition was beneficial for their performance efficiency on a set of a transfer tasks, and their troubleshooting performance during the delayed session. From a cognitive load perspective, using a redundant text along with an audio narration overloads learner’s working memory by placing more strain on the visual pathway and not providing any additional cognitive advantage. From an environmental support standpoint and decreased processing resources view of cognitive aging, providing additional representational support helps reducing the task demands for older adults and results in better learning. The results have cognitive and practical implications for the design of multimedia learning environments for older adults.