Importance-Performance Analysis of Guest Entertainment Technology Amenities in the Lodging Industry

An assessment of how hotel guests view in-room entertainment-technology amenities was conducted to compare the importance of these technologies to how they performed. In-room entertainment technology continues to evolve in the hotel industry. However, given the multitude of entertainment products available in the marketplace today, hoteliers have little understanding of guests’ expectations and of which in-room entertainment-technology amenities will drive guest satisfaction and increase loyalty to the hotel brand. Given that technology is integral to a hotel stay, this study seeks to evaluate the importance and performance of in-room entertainment-technology amenities. Findings indicate that free-to-guest television (FTG TV) and high-speed Internet access were the two most important inroom entertainment-technology amenities when it comes to the selection of a hotel for both leisure and business travelers. The Importance/Satisfaction Matrix presented in the current study showed that many of the in-room entertainment-technology amenities are currently a low priority for guests. Keywords: importance-performance analysis, hotel, in-room entertainment technologies

Field programmable gate array based target detection and gesture recognition

The move from Standard Definition (SD) to High Definition (HD) represents a six times increases in data, which needs to be processed. With expanding resolutions and evolving compression, there is a need for high performance with flexible architectures to allow for quick upgrade ability. The technology advances in image display resolutions, advanced compression techniques, and video intelligence. Software implementation of these systems can attain accuracy with tradeoffs among processing performance (to achieve specified frame rates, working on large image data sets), power and cost constraints. There is a need for new architectures to be in pace with the fast innovations in video and imaging. It contains dedicated hardware implementation of the pixel and frame rate processes on Field Programmable Gate Array (FPGA) to achieve the real-time performance. ^ The following outlines the contributions of the dissertation. (1) We develop a target detection system by applying a novel running average mean threshold (RAMT) approach to globalize the threshold required for background subtraction. This approach adapts the threshold automatically to different environments (indoor and outdoor) and different targets (humans and vehicles). For low power consumption and better performance, we design the complete system on FPGA. (2) We introduce a safe distance factor and develop an algorithm for occlusion occurrence detection during target tracking. A novel mean-threshold is calculated by motion-position analysis. (3) A new strategy for gesture recognition is developed using Combinational Neural Networks (CNN) based on a tree structure. Analysis of the method is done on American Sign Language (ASL) gestures. We introduce novel point of interests approach to reduce the feature vector size and gradient threshold approach for accurate classification. (4) We design a gesture recognition system using a hardware/ software co-simulation neural network for high speed and low memory storage requirements provided by the FPGA. We develop an innovative maximum distant algorithm which uses only 0.39% of the image as the feature vector to train and test the system design. Database set gestures involved in different applications may vary. Therefore, it is highly essential to keep the feature vector as low as possible while maintaining the same accuracy and performance^