Estimating fixed-effect panel stochastic frontier models by model transformation

Traditional panel stochastic frontier models do not distinguish between unobserved individual heterogeneity and inefficiency. They thus force all time-invariant individual heterogeneity into the estimated inefficiency. Greene (2005) proposes a true fixed-effect stochastic frontier model which, in theory, may be biased by the incidental parameters problem. The problem usually cannot be dealt with by model transformations owing to the nonlinearity of the stochastic frontier model. In this paper, we propose a class of panel stochastic frontier models which create an exception. We show that first-difference and within-transformation can be analytically performed on this model to remove the fixed individual effects, and thus the estimator is immune to the incidental parameters problem. Consistency of the estimator is obtained by either N→∞ or T→∞, which is an attractive property for empirical researchersStochastic frontier models; Fixed effects; Panel data

The Elderly Access to On-Line Local Government Social Relief Information: Practices in Taiwan

AbstractThere are numerous studies analyzing the quality of governments’ websites produced by academics, but very little analysis has been done regarding specific users, especially senior people. This leads the authors to evaluate the quality of Websites of Taiwan's local governments in facilitating internet access to spread social relief information to their low-to-mid-income families. Following and modifying the model of Perez et al. (2005), the objective of this study is to obtain a series of indicators that represent how access and navigability the websites are. In sum, the friendly index (FI) is highest in the case of the Yunlin county Web page, with a friendly index value of 90 percent. And Tainan city Web page gets a friendly index value of 20 percent

Revisiting the problem of audio-based hit song prediction using convolutional neural networks

Being able to predict whether a song can be a hit has impor- tant applications in the music industry. Although it is true that the popularity of a song can be greatly affected by exter- nal factors such as social and commercial influences, to which degree audio features computed from musical signals (whom we regard as internal factors) can predict song popularity is an interesting research question on its own. Motivated by the recent success of deep learning techniques, we attempt to ex- tend previous work on hit song prediction by jointly learning the audio features and prediction models using deep learning. Specifically, we experiment with a convolutional neural net- work model that takes the primitive mel-spectrogram as the input for feature learning, a more advanced JYnet model that uses an external song dataset for supervised pre-training and auto-tagging, and the combination of these two models. We also consider the inception model to characterize audio infor- mation in different scales. Our experiments suggest that deep structures are indeed more accurate than shallow structures in predicting the popularity of either Chinese or Western Pop songs in Taiwan. We also use the tags predicted by JYnet to gain insights into the result of different models.Comment: To appear in the proceedings of 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP

Comparison of Radical Scavenging Activity, Cytotoxic Effects and Apoptosis Induction in Human Melanoma Cells by Taiwanese Propolis from Different Sources

Propolis is a sticky substance that is collected from plants by honeybees. We previously demonstrated that propolins A, B, C, D, E and F, isolated from Taiwanese propolis (TP), could effectively induce human melanoma cell apoptosis and were strong antioxidant agents. In this study, we evaluated TP for free radical scavenging activity by DPPH (1,2-diphenyl-2-picrylhydrazyl). The phenolic concentrations were quantified by the Folin–Ciocalteu method. The apoptosis trigger activity in human melanoma cells was evaluated. TP contained a higher level of phenolic compounds and showed strong capability to scavenge free radicals. Additionally, TP1g, TP3, TP4 and TP7 exhibited a cytotoxic effect on human melanoma cells, with an IC(50) of ∼2.3, 2.0, 3.3 and 3.3 μg/ml, respectively. Flow cytometric analysis for DNA fragmentation indicated that TP1g, TP2, TP3 and TP7 could induce apoptosis in human melanoma cells and there is a marked loss of cells from the G2/M phase of the cell cycle. To address the mechanism of the apoptosis effect of TP, we evaluated its effects on induction of apoptosis-related proteins in human melanoma cells. The levels of procaspase-3 and PARP [poly(ADP-ribose) polymerase] were markedly decreased. Furthermore, propolins A, B, C, D, E and F in TP were determined using HPLC. The results indicate that TP is a rich source of these compounds. The findings suggest that TP induces apoptosis in human melanoma cells due to its high level of propolins

Supervised Collective Classification for Crowdsourcing

Crowdsourcing utilizes the wisdom of crowds for collective classification via information (e.g., labels of an item) provided by labelers. Current crowdsourcing algorithms are mainly unsupervised methods that are unaware of the quality of crowdsourced data. In this paper, we propose a supervised collective classification algorithm that aims to identify reliable labelers from the training data (e.g., items with known labels). The reliability (i.e., weighting factor) of each labeler is determined via a saddle point algorithm. The results on several crowdsourced data show that supervised methods can achieve better classification accuracy than unsupervised methods, and our proposed method outperforms other algorithms.Comment: to appear in IEEE Global Communications Conference (GLOBECOM) Workshop on Networking and Collaboration Issues for the Internet of Everythin

Environmentally sustainable acoustics in urban residential areas.

The main aim of this thesis is to examine environmentally sustainable acoustics, considering mainly urban residential areas. The study has systematically examined the three essential aspects of environmentally sustainable acoustics, namely, people, buildings and resources. The investigations are focused on three aspects: (l) the effects of urban acoustics on people: a systematic field survey on people's perceptions which considered people's living experiences, sound preferences and social factors; (2) a series of buildings' life cycle assessments which examined the environmental impact from cradle to grave of the building's lifespan and tried to further comprehend acoustic sustainability of residential buildings; (3) various possibilities concerning the use of wind turbines around and above the residential buildings in an attempt to discover how to regenerate renewable wind energy and to avoid serious noise effects. The study has then been expanded from the three aspects, by revealing potential to achieving environmentally sustainable acoustics. Overall, it has been proved that environmentally sustainable acoustics is an essential part of the environmentally sustainability development. The thesis makes a positive contribution to urban residential areas through the illustration of a sustainable acoustics approach to environmentally sustainable development, and demonstrates how these factors should be associated with each other. Acoustics and sustainability is a rather new field this study only reveals some key issues. More systematic and in-depth study in other aspects is still needed