Spatial Analytics with Hospitality Big Data: Examining the Impact of Locational Determinants on Customer Satisfaction in the U.S. Hotel Market

Although hotel location has been recognized as one of the important factors affecting hotel selection and guest satisfaction, relatively few studies have examined guest satisfaction with hotel location and its locational determinants at a macro level. This study aims to identify the locational determinants of hotel guest satisfaction through big data spatial analytics via a case study of 5,302 hotels in 151 cities in the U.S. Based on the framework of hotel location satisfaction, we classified all location-related factors into three categories: accessibility to points of interest, transport convenience, and surrounding environment. Our findings indicated that hotel property’s proximity to city area, landmark, park, shopping center, and highway as well as, attraction-driven tourism industry specialization, and hotel industry agglomeration were significant determinants. Furthermore, the impacts of these factors were spatially heterogeneous. These findings can provide geographical insights that are critical for developing a customer service experience and satisfaction model

Removal of 10-nm contaminant particles from Si wafers using CO2 bullet particles

Removal of nanometer-sized contaminant particles (CPs) from substrates is essential in successful fabrication of nanoscale devices. The particle beam technique that uses nanometer-sized bullet particles (BPs) moving at supersonic velocity was improved by operating it at room temperature to achieve higher velocity and size uniformity of BPs and was successfully used to remove CPs as small as 10 nm. CO2 BPs were generated by gas-phase nucleation and growth in a supersonic nozzle; appropriate size and velocity of the BPs were obtained by optimizing the nozzle contours and CO2/He mixture fraction. Cleaning efficiency greater than 95% was attained. BP velocity was the most important parameter affecting removal of CPs in the 10-nm size range. Compared to cryogenic Ar or N2 particles, CO2 BPs were more uniform in size and had higher velocity and, therefore, cleaned CPs more effectively

The relationship between environmental regulations and Korean economy (TFP, outward FDI, trade)

This thesis tries to analyse the relationship between stringency of environmental regulations and Korean economic performance. This research deals with three themes as the following: First examination lies on the effects of Korean domestic environmental restrictions on Total Factor Productivity in terms of industry and firm; second is the influences of relative difference of environmental stringency between Korea and counterpart (importer or host countries) on Korean outward FDI and Korean exports to the nations, and finally, the effects of Korean domestic environmental stringency on Korean trade performance are researched on

Correlated electronic states at domain walls of a Mott-charge-density-wave insulator 1T-TaS2

Domain walls in interacting electronic systems can have distinct localized states, which often govern physical properties and may lead to unprecedented functionalities and novel devices. However, electronic states within domain walls themselves have not been clearly identified and understood for strongly correlated electron systems. Here, we resolve the electronic states localized on domain walls in a Mott-charge-density-wave(CDW) insulator 1T-TaS2 using scanning tunneling spectroscopy. We establish that the domain wall state decomposes into two nonconducting states located at the center of domain walls and edges of domains. Theoretical calculations reveal their atomistic origin as the local reconstruction of domain walls under the strong influence of electron correlation. Our results introduce a concept for the domain wall electronic property, the wall's own internal degrees of freedom, which is potentially related to the controllability of domain wall electronic properties

Automatic Grammar Augmentation for Robust Voice Command Recognition

This paper proposes a novel pipeline for automatic grammar augmentation that provides a significant improvement in the voice command recognition accuracy for systems with small footprint acoustic model (AM). The improvement is achieved by augmenting the user-defined voice command set, also called grammar set, with alternate grammar expressions. For a given grammar set, a set of potential grammar expressions (candidate set) for augmentation is constructed from an AM-specific statistical pronunciation dictionary that captures the consistent patterns and errors in the decoding of AM induced by variations in pronunciation, pitch, tempo, accent, ambiguous spellings, and noise conditions. Using this candidate set, greedy optimization based and cross-entropy-method (CEM) based algorithms are considered to search for an augmented grammar set with improved recognition accuracy utilizing a command-specific dataset. Our experiments show that the proposed pipeline along with algorithms considered in this paper significantly reduce the mis-detection and mis-classification rate without increasing the false-alarm rate. Experiments also demonstrate the consistent superior performance of CEM method over greedy-based algorithms

Organizing Pneumonia by Paragonimiasis and Coexistent Aspergilloma Manifested as a Pulmonary Irregular Nodule

Organizing pneumonia by paragonimiasis and coexistent aspergilloma as a pulmonary nodule is a rare case of lung disease. Its radiographic or CT feature has not been described before in the radiologic literature. We present organizing pneumonia by paragonimiasis and coexistent aspergilloma manifested as a pulmonary irregular nodule on CT

The Effects and Influential Factors of Employee’s Knowledge Integration Capability in the Convergence Environment

Knowledge integration is becoming a primary function of improving organizational capabilities and performance in today’s convergence environment in which the integration of individual knowledge is the source of organizational knowledge creation for new product and service development. This study investigates the influential factors of employee’s knowledge integration capability and its effects. A theoretical research model was developed based on knowledge creation, socio-technical, and information processing perspectives. In particular, the model proposes a positive relationship between the knowledge integration capability of employees and their knowledge creation output. The model also includes organic organizational structure, teamwork quality, expertise, IT support, and knowledge complexity as the influential factors of an employee’s knowledge integration capability. A large-scale survey was conducted for data gathering (a total of 316 samples from 141 organizations) to test the proposed model. The analysis results of the hypotheses test show that expertise and knowledge complexity are the significant influential factors of employee’s knowledge integration capability. In turn, this capability has a positive effect on the knowledge creation output of employees. The results of this study will contribute to the development of initiatives for promoting knowledge integration in the development processes of convergence products and services