A Structural Solution to Communication Dilemmas in a Virtual Community

In a many-to-many communication setting like a virtual community, individuals may be strongly tempted to free-ride on others' contributions, which would eventually lead to the collapse of the community. To find a structural solution to the "communication dilemma," this study compared the performances of 2 communication structures—one based on the interpersonal networks (network-generalized exchange: N_EX; e.g., blogs) and the other based on a public electronic bulletin board (group-generalized exchange: G_EX). In a 2 × 2 × 2 longitudinal between-subject experiment, it was found that changing G_EX to N_EX could increase the contributions made by individuals. Furthermore, N_EX was found to be an effective structure for N-person communication particularly when a large number of individuals were involved. The findings imply that an individual's cooperative motivation is a function of the incentive structure of a particular form of information exchange, which means that altering the exchange form may be a possible solution to the communication dilemmas in virtual communities.     

Thermochemical stability of Fe- and co-functionalized perovskite-type SrTiO3 oxygen transport membrane materials in syngas conditions

The materials typically used for oxygen transport membranes, Ba_0.5Sr_0.5Co_0.8Fe_0.2O_3?δ (BSCF) and La_0.6Sr_0.4Co_0.2Fe_0.8O₃ (LSCF) tend to decompose due to their low thermochemical stability under reducing atmosphere. Fe- and Co-doped SrTiO₃ (SrTi_1-x-yCo_xFe_yO_3-δ, x + y ≤ 0.35) (STCF) materials showing an oxygen transport comparable to LSCF have great potential for application in ion-transport-devices. In this study, the thermochemical stability of pure perovskite-structured STCF was investigated after annealing in a syngas atmosphere at 600–900 °C. The phase composition of the materials after annealing was characterized by means of X-ray diffraction (XRD). The thermodynamic activities of SrO, FeO, and CoO in the STCF materials were evaluated using Knudsen effusion mass spectrometry (KEMS). Co-doped SrTiO₃ (STC) materials were not stable after annealing in the syngas atmosphere above 5 mol% Co-substitution. Ruddlesden-Popper-like phases and SrCO₃ were detected after annealing at 600 °C. In contrast, Fe substitution (STF) showed good stability after annealing in syngas upto 35 mol% substitution.     

Nanoceria synthesis in molten KOH-NaOH mixture: Characterization and oxygen vacancy formation

Nanoceria was synthesized by treating cerium carbonate hydrate in a molten KOH-NaOH mixture at 200 °C. The nanoceria thus synthesized under a hydrogen atmosphere had a crystal size of 21.6 nm measured by XRD, consistent with the particle size of 23 nm measured by TEM. Raman spectra results indicated that the nanoceria produced under hydrogen had a downshift of 0.9 cm^?1 from the sample synthesized in air. XPS spectra showed that the Ce³⁺ fraction of the nanoceria synthesized in hydrogen was greater than that produced in air. The oxygen vacancies were formed by partial oxidization of the precursor in molten KOH-NaOH mixture. The UV–visible absorption properties of ceria synthesized under hydrogen showed a 34 nm red-shift compared with that synthesized in air. The nanoceria prepared in this work had a better catalytic property for CO oxidization than the commercial nanoceria. Results indicated that the increased Ce³⁺ fraction or oxygen vacancies formed by this partial oxidization process extended the absorption edge of ceria resulting in a narrower band gap, and enhanced the catalytic activity of nanoceria. This method has proven to provide a simple and scalable method for the synthesis of high quality nanoceria.     

Case-based context ontology construction using fuzzy set theory for personalized service in a smart home environment

To provide context-based personalized services utilizing smart appliances in a smart home environment, we propose a framework for PersonAlized Service disCovery Using FuZZY-based CBR and Context Ontology (PASCUZZY). Basically, the PASCUZZY framework is implemented on case-based context ontology. To generate and manage the case instances on the case-based context ontology, we adopt the fuzzy set theory to transpose numerical-type context data sensed from the surrounding environment. The context is transposed to linguistic-type context instances on the context ontology. In addition, to formalize and manage the context and services as multi-attributed data, the context ontology was developed reflecting the structure of cases borrowed from case-based reasoning. Furthermore, we propose adaptation methods to adjust the generic fuzzy membership functions depending on the inhabitants’ context. It is performed by modifying the values of the membership number and/or modifying the numbers of the linguistic terms that are based on the inhabitants’ context to affect the membership numbers. The adapted membership functions return the personalized degree of memberships depending on the specialized context of a specific fuzzy variable. Inevitably, the number of cases on the case-based context ontology will be increased from time to time. We apply Ward’s method not only to reduce the search effort via a hierarchical clustering on the case-based context ontology but also to find the most similar service as a solution to the new context. To verify the superiority of the PASCUZZY framework, we perform two kinds of evaluations. First, we evaluate the effectiveness of the adaptation of the fuzzy membership functions. Second, we verify the effectiveness of the application of a clustering method to the case instances of the case-based context ontology to identify the most similar service. Results of the experiment verified the effectiveness and superiority of the PASCUZZY framework.     

Evaluating the calibration of MTSAT‐1R infrared channels using collocated Terra MODIS measurements

The calibration of four MTSAT‐1R infrared channels was evaluated by comparing MTSAT measurements with Terra/MODIS inferred MTSAT‐equivalent brightness temperatures during August 2005 and August 2006. Theoretical relationships converting MODIS brightness temperatures to MTSAT‐equivalent values were obtained and used for the comparison. Results indicate that MTSAT two split window channels are well calibrated, and no serious systematic errors or biases are found; and the MTSAT water‐vapour channel shows a good linear relationship but with a warm bias up to 2 K. The significant cold bias of MTSAT 3.7 µm channel about ?6.7 K in August 2005 is found to be much removed in August 2006, after correction of the electrical crosstalk between MTSAT‐1R SWIR channel and WV channel starting from March 2006. Since then, calibration performances of MTSAT‐1R split window channels and shortwave IR channel seem to be comparable with MODIS calibration, while the water‐vapour channel shows more uncertainties up to 2 K of bias.     

A study on the student pilot's mental workload due to personality types of both instructor and student

The main purpose of this paper is to provide the ideal flight crew combination for instructor and student pilots in order to enhance the flight training effects based on Myers Briggs Type Indicator (MBTI) theory. In addition to personality, various levels of flight difficulty are considered in order to investigate their potential interaction effect in terms of student pilots' mental workload measured in heart rate, altitude deviation, NASA-TLX (Task Load Index) and subjective degree of personality harmony. Based on an experiment performed in a real flight situation, we found significant effects of personality combinations in terms of all four outcome measures. Both group C types of instructors and students who are concrete, realistic and have mechanical skills turn out to be the ideal flight crew combination. A structural equation model, fitted to analyse causality among the four response variables, implied that as the heart rate increased, the altitude deviation increased. In addition, as the altitude deviation and personality harmony increased, NASA-TLX increased. The results of this study are expected to provide a theoretical basis for manning the flight crew combinations and thereby enhancing the efficiency of flight training.     

Bayesian network analysis for the dynamic prediction of early stage entrepreneurial activity index

Entrepreneurship plays a critical role for the development and well-being of society. Illustration of its dynamic relationship with entrepreneurial attitudes and aspirations can provide a guideline for the cause of such activities. However, a time-lagged causal relationship among these concepts has not yet been established. In this study, we examine a dynamic relationship among early stage entrepreneurial attitudes, activities, and aspirations using Bayesian network (BN) analysis. In addition, we propose an early stage entrepreneurial activity index that can predict the percentage of both nascent entrepreneur and new business owner using the variables related to entrepreneurial attitudes of the previous year. This index, in turn, can be used to predict various aspects of entrepreneurial aspiration of the following year. The proposed index turns out to have very high prediction accuracy and is expected to provide effective policies to boost future entrepreneurial activity and aspiration.     

Prediction of Ozone Formation Based on Neural Network

The atmospheric ozone concentration in Seoul was forecasted using an artificial neural network and spatiotemporal analysis. The artificial neural network was trained by using hourly pollutant and meteorological data that resulted in complex patterns of ozone formation. The finite-volume method was employed in the spatiotemporal analysis in order to take into account the effects of wind. Time horizons in the forecasts were 1–6 h and 16–21 h. The resulting predictions of ozone formation were compared to measured data. From the comparison, it was found that the neural network method gave reliable accuracy within a limited prediction horizon.     

A sales agent for part manufacturers: VMSA

The sales activity of most parts manufacturing companies is based on orders of buyers. The process of promotion, receipt and selection of orders of the parts manufacturers is closely coupled with the load status of the production lines. On deciding whether to accept an order or not, as well as negotiating with buyers, sales persons need information such as load and schedule of production lines, and manufacturability of the order. Manufacturability analysis, process planning, and scheduling are therefore key features in developing an agent of sales activity for the parts manufacturing business. In this paper, an intelligent agent, a virtual manufacturing-based sales agent (VMSA) with multi-agent architecture is proposed to support the sales activity for the parts manufacturers in the Internet environment. A VMSA has an integrated architecture of agent and virtual manufacturing. The prototype of VMSA has been developed for a machine parts manufacturing company that has lathe machines, drilling machines, cutting machines, and milling machines.