Does PPP hold for Big Mac price or consumer price index? Evidence from panel cointegration

This paper examines the validity of purchasing power parity (PPP) using CPI and Big Mac prices. The benchmark model, i.e., the OLS method, which does not take nonstationarity into account, rejects the hypothesis of PPP regardless of prices used. We next use the panel cointegration method to consider the nonstationary nature of variables. Estimated results for CPI are mixed. The PPP is rejected when the nominal exchange rate is employed as the dependent variable but is not rejected when the price ratio is used as the dependent variable. By contrast, the PPP is overwhelmingly not rejected when the Big Mac price is used. Last, we remove the production bias and re-examine the same issue by using panel cointegration. The PPP is again decisively rejected when CPI price is used but not for Big Mac price. Accordingly, Big Mac price is more supportive to the validity of PPP than CPI price.Big Mac

Using DEA to measure the relative efficiency of the service center and improve operation efficiency through reorganization

[[abstract]]Data envelopment analysis (DEA) has become a practicable approach to evaluate the relative efficiencies of decision-making units in various contexts. This paper conducted a DEA study to measure the relative efficiencies of 17 service centers of the NAN-TOU electricity distribution district of Taiwan Power Company (TPC). In addition, this paper also investigated the alternatives for reorganizing the service centers via efficiency measurement. The results showed that the proposed reorganization alternatives have better efficiency scores. Based on DEA evaluations, we provided specific directions for the inefficient service centers to improve their operation efficiencies, and thus, maintain the competitive advantage of TPC in facing power market liberalization.[[fileno]]2020403010007[[department]]工工

Aversive learning effect on odor coding in rat's piriform cortex

Olfaction, a sense for detecting and discriminating chemical molecules in the environment, is critical for animal survival, reproduction and other adaptive behaviors. The olfactory system is organized in three major stations (a sensor sheet, an initial processing and projection unit, and a central processing unit) that are shared across phyla, and has been functioning for millions of years. Since Buck and Axel identified a multigene family for coding the olfactory receptors, knowledge of the olfactory system has quickly accumulated in the last 20 years. This allows us to investigate fundamental questions in olfaction, including how odor percepts are formed, how olfactory information is used and stored, and how experiences shape olfactory perception in our daily life.Aversive events involving olfactory information are commonly experienced in nature. In the lab, aversive olfactory experiences have been shown to modify odor responses in rodents behaviorally and physiologically. Traditionally, studies regarding olfactory aversive learning were conducted by using odor-shock conditioning. Here, I explored the possibility of using 2-way active avoidance conditioning for awake unit recording in rats. The results confirmed previous findings that the rats can learn to actively avoid both auditory and olfactory cues that are associated with a dangerous event. Interestingly, the rats appeared to have rapid acquisition but poor behavioral retention. After comparing between the two paradigms, I decided to use odor-shock conditioning for chronic unit recording in awake rats.Three different odor-shock conditioning paradigms were used to investigate how aversive learning affects odor processing in the olfactory cortex. We first found that odor-evoked fear responses were training paradigm-dependent and each induced different levels of fear responses and odor generalization. In addition, we observed a decrease in spontaneous firing rate in the olfactory cortical neurons after conditioning and that was associative learning dependent. The results also suggested that generalized fear is associated with an impairment of olfactory cortical discrimination. In conclusion, changes in sensory processing are dependent on the nature of training, and can predict the behavioral outcome of the training

Data Mining to Capture User-Experience: A Case Study in Notebook Product Appearance Design

In the era of rapidly increasing notebook market, consumer electronics manufacturers are facing a highly dynamic and competitive environment. In particular, the product appearance is the first part for user to distinguish the product from the product of other brands. Notebook product should differ in its appearance to engage users and contribute to the user experience (UX). The UX evaluates various product concepts to find the design for user needs; in addition, help the designer to further understand the product appearance preference of different market segment. However, few studies have been done for exploring the relationship between consumer background and the reaction of product appearance. This study aims to propose a data mining framework to capture the user's information and the important relation between product appearance factors. The proposed framework consists of problem definition and structuring, data preparation, rules generation, and results evaluation and interpretation. An empirical study has been done in Taiwan that recruited 168 subjects from different background to experience the appearance performance of 11 different portable computers. The results assist the designers to develop product strategies based on the characteristics of consumers and the product concept that related to the UX, which help to launch the products to the right customers and increase the market shares. The results have shown the practical feasibility of the proposed framework

Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation

While representation learning aims to derive interpretable features for describing visual data, representation disentanglement further results in such features so that particular image attributes can be identified and manipulated. However, one cannot easily address this task without observing ground truth annotation for the training data. To address this problem, we propose a novel deep learning model of Cross-Domain Representation Disentangler (CDRD). By observing fully annotated source-domain data and unlabeled target-domain data of interest, our model bridges the information across data domains and transfers the attribute information accordingly. Thus, cross-domain joint feature disentanglement and adaptation can be jointly performed. In the experiments, we provide qualitative results to verify our disentanglement capability. Moreover, we further confirm that our model can be applied for solving classification tasks of unsupervised domain adaptation, and performs favorably against state-of-the-art image disentanglement and translation methods.Comment: CVPR 2018 Spotligh

LEVERAGING SPORTING EQUIPMENT BALANCE AND WEIGHT DISTRUBUTION INFLUENCE ON PUTTING KINEMATICS –A STUDY ON COUNTER-BALANCED PUTTER DESIGN

In golf, putting is considered one of the most important factors for scoring of professional Tour players (Alexander & Kern, 2005), and accounts for 43% ± 2% per round (Pelz & Frank, 2000). Unlike the long game, short game like putting, is focused on its accuracy and consistency (Hume, Keogh & Reid, 2005). Putting stroke requires accurate and repeatable stroke especially during impact stage, and one of the most recent putter design is to grip down or to have extra weights on the grip end of the club, also known as the counterbalanced putter

Paper-based tuberculosis diagnostic devices with colorimetric gold nanoparticles

A colorimetric sensing strategy employing gold nanoparticles and a paper assay platform has been developed for tuberculosis diagnosis. Unmodified gold nanoparticles and single-stranded detection oligonucleotides are used to achieve rapid diagnosis without complicated and time-consuming thiolated or other surface-modified probe preparation processes. To eliminate the use of sophisticated equipment for data analysis, the color variance for multiple detection results was simultaneously collected and concentrated on cellulose paper with the data readout transmitted for cloud computing via a smartphone. The results show that the 2.6 nM tuberculosis mycobacterium target sequences extracted from patients can easily be detected, and the turnaround time after the human DNA is extracted from clinical samples was approximately 1 h

Pedestrian/Bicyclist Limb Motion Analysis from 110-Car TASI Video Data for Autonomous Emergency Braking Testing Surrogate Development

Many vehicles are currently equipped with active safety systems that can detect vulnerable road users like pedestrians and bicyclists, to mitigate associated conflicts with vehicles. With the advancements in technologies and algorithms, detailed motions of these targets, especially the limb motions, are being considered for improving the efficiency and reliability of object detection. Thus, it becomes important to understand these limb motions to support the design and evaluation of many vehicular safety systems. However in current literature, there is no agreement being reached on whether or not and how often these limbs move, especially at the most critical moments for potential crashes. In this study, a total of 832 pedestrian walking or cyclist biking cases were randomly selected from one large-scale naturalistic driving database containing 480,000 video segments with a total size of 94TB, and then the 832 video clips were analyzed focusing on their limb motions. We modeled the pedestrian/bicyclist limb motions in four layers: (1) the percentages of pedestrians and bicyclists who have limb motions when crossing the road; (2) the averaged action frequency and the corresponding distributions on when there are limb motions; (3) comparisons of the limb motion behavior between crossing and non-crossing cases; and (4) the effects of seasons on the limb motions when the pedestrians/bicyclists are crossing the road. The results of this study can provide empirical foundations supporting surrogate development, benefit analysis, and standardized testing of vehicular pedestrian/bicyclist detection and crash mitigation systems