Exploring tourist preferences of heritage attractions- Evidence from discrete choice modeling in Taiwan

This study focuses on the tourists’ preference evaluation on service attributes of heritage attractions by stated preference (SP) method and employs logit models to estimate the relative influences of service attributes on site choice behavior of heritage tourists. Also, this study valuates tourists’ willingness to pay for hypothetical managerial developments of the heritage service attributes. The results indicate that provision of outdoor café and restaurant service, operating hours until evening, and entrance fee in heritage attractions exhibit a statistically significant effect on probability of visitation. In addition, the results from welfare effects demonstrate that tourists are willing to pay extra money to utilize more service facilities for heritage attractions

The Synesthesia effects of Online Advertising Stimulus Design on Word-of-Mouth and Purchase Intention: From the Perspective of Consumer Olfactory and Gustatory

Multisensory marketing has been seen as an approach improving advertising effect in the social science, neuroscience, and marketing literature. For examining visual/audio synesthesia, the effect of smelling and tasting an online product, this study first developed design elements of digital video advertising: rational/emotional appeals and fast/slow tempo. Moreover, it strives to investigate empirically the effects of various online advertisement contexts on consumer emotion, attitude, and behavioral intention. We used event-related potentials (ERPs) in a scenario-based laboratory experiments. Data collected from 166 customers provide strong support for the research model. Through EEG and SEM analyses, in rational advertisings, consumers’ olfactory was triggered and both arousal and pleasure of the emotions affected the attitudes; in emotional advertisings, not only olfactory but gustatory were triggered and only pleasure affected the attitudes. By understanding online advertising design and synesthesia, insights from the findings can benefit designers and marketers in implementing more effective marketing strategies

Thermal Design of Three-Dimensional Electronic Assemblies

Currently, three-dimensional electronic assemblies (3D Packages) are a key technology for enabling heterogeneous integration and “more than Moore” functionality. A critical bottleneck to the viability of 3D Packages is their thermal design. Traditionally, heat spreaders are used as a passive method to reduce the peak temperature as well as temperature gradient on the chip. However, heat spreaders by themselves are often insufficient in stacked, multiple-die containing 3D Packages. Towards this end, to more efficiently remove heat, silicon interposers with through silicon vias (TSV) are used. However, careful design of number and location of TSVs is necessary. In addition, the heat spreader design as well as the selection of thermal interface materials needs careful consideration. At the present time, there are no automated tools available to carryout such a thermal design of 3D Packages. The present study is focused on the development of an efficient tool that determines the optimal configuration of heat spreading elements subject to constraints on allowable copper heat spreading area or metal volume. To achieve this goal, a three-dimensional finite element analysis (FEA) code for steady-state heat conduction is coupled with a sequential quadratic programming (SQP) algorithm, and both are implemented within the MATLAB environment. Considerable effort was spent to ensure efficient matrix solution using a sparse matrix solver during FEA. Several example problems are solved and the results are compared against solutions obtained using Simulia iSight in combination with the sophisticated Simulia ABAQUS FEA tool. The developed tool is demonstrated to be nearly two-orders of magnitude faster for the same level of accuracy in the final solution

Improving Patient and Family Experience in Level One Post Anesthesia Care Unit

Historically speaking, post-anesthesia care units (PACU’s) have been closed off to visitation. However, several studies on the patient experience of care that demonstrates that family visitation in PACU not only increases patient and family satisfaction, but also decreases their anxiety. The purpose of this project was to improve family outcomes by implementing family visitation in the PACU, utilizing two new valid survey items in the Consumer Assessment of Healthcare Providers and Systems Outpatient and Ambulatory Surgery survey (CAHPS OAS). This project sought to demonstrate the need to change the focus from health care to optimizing health for patients and their families in the implementation of family visitation in the PACU. The basis for the implementation of this intervention rested on the Family-Centered Care model of practice. Pre-implementation and post-implementation surveys were conducted and collected into two different sets of data. The project result is clear that patient and family satisfaction increased by implementing family visitations in the PACU.D.N.P

A cross-national comparison of parent-consumers' evaluative critieria used in purchasing pre-school children's apparel

The children's apparel industry is a fast-growing industry in the United States. It is important to determine what factors are considered as the most important when parents purchase their pre-school children's clothing. To gain a better understanding of parent-consumers' purchasing behavior of pre-school children's apparel, this study focused on parent-consumers' evaluative criteria used in purchasing pre-school children's apparel both in Taiwan and in the U.S. The purpose of this study was to compare the evaluative criteria used by Taiwan and U.S. parent-consumers in their decisions to purchase children's apparel. The importance of intrinsic criteria directly related to the product itself and some selected extrinsic criteria were examined. The theoretical framework used for the present study was the EKB consumer behavior model; with focus on the alternative evaluation stage of the consumer decision making process. Previous research has examined evaluative criteria used in purchasing women's and men's apparel, but only limited research has investigated evaluative criteria used in purchasing children's apparel. Survey methodology was used to collect data. A self-administered questionnaire was distributed to two non-probability, purposive samples to collect quantitative data. Data were collected through two selected pre-schools at Oregon State University in the U.S. and at Fu Jen Catholic University in Taiwan. The samples consisted of 200 parent-consumers with a child or children, ages 3 to 6. Subjects were given questionnaires through teachers or researcher, resulting in a 84.1% response rate. Collected data were analyzed using two sample t-tests. Significant differences were found between the two groups in the importance of aesthetic and extrinsic criteria but not in the importance of usefulness and performance criteria. Among all 22 criteria, significant differences were found between Taiwan and U.S. respondents in the importance of: fiber content, type of fabric, fabric print, having character/logo, color fastness, price, on sale, brand name, and country of origin. The most important criteria for both groups were comfort and size/fit. By identifying the evaluative criteria used by parent-consumers of pre-school children's apparel in two countries, the results partially supported the EKB consumer behavior model. In addition, the findings about the importance of purchase criteria used by parent-consumers may also benefit children's apparel manufacturers and retailers in revising or improving their competitive ability in global marketing

SASMU: boost the performance of generalized recognition model using synthetic face dataset

Nowadays, deploying a robust face recognition product becomes easy with the development of face recognition techniques for decades. Not only profile image verification but also the state-of-the-art method can handle the in-the-wild image almost perfectly. However, the concern of privacy issues raise rapidly since mainstream research results are powered by tons of web-crawled data, which faces the privacy invasion issue. The community tries to escape this predicament completely by training the face recognition model with synthetic data but faces severe domain gap issues, which still need to access real images and identity labels to fine-tune the model. In this paper, we propose SASMU, a simple, novel, and effective method for face recognition using a synthetic dataset. Our proposed method consists of spatial data augmentation (SA) and spectrum mixup (SMU). We first analyze the existing synthetic datasets for developing a face recognition system. Then, we reveal that heavy data augmentation is helpful for boosting performance when using synthetic data. By analyzing the previous frequency mixup studies, we proposed a novel method for domain generalization. Extensive experimental results have demonstrated the effectiveness of SASMU, achieving state-of-the-art performance on several common benchmarks, such as LFW, AgeDB-30, CA-LFW, CFP-FP, and CP-LFW.Comment: under revie

Streamlined Framework for Agile Forecasting Model Development towards Efficient Inventory Management

This paper proposes a framework for developing forecasting models by streamlining the connections between core components of the developmental process. The proposed framework enables swift and robust integration of new datasets, experimentation on different algorithms, and selection of the best models. We start with the datasets of different issues and apply pre-processing steps to clean and engineer meaningful representations of time-series data. To identify robust training configurations, we introduce a novel mechanism of multiple cross-validation strategies. We apply different evaluation metrics to find the best-suited models for varying applications. One of the referent applications is our participation in the intelligent forecasting competition held by the United States Agency of International Development (USAID). Finally, we leverage the flexibility of the framework by applying different evaluation metrics to assess the performance of the models in inventory management settings