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It is demonstrated that the electric dipole layer due to the overlapping of electron wave functions at the metal/graphene contact results in a negative Fermi-level pinning effect on the region of the GaAs surface with low interface-trap density in the metal/graphene/n-GaAs(001) junction. The graphene interlayer plays the role of a diffusion barrier, preventing the atomic intermixing at the interface and preserving the low interface-trap density region. The negative Fermi-level pinning effect is supported by the decrease of the Schottky barrier with the increase of the metal work function. Our work shows that the graphene interlayer can invert the effective work function of the metal between high and low, making it possible to form both Schottky and Ohmic-like contacts with identical (particularly high work function) metal electrodes on a semiconductor substrate possessing low surface-state density.

It is demonstrated that the heart-rate can be sensed capacitively on a touch screen panel (TSP) together with touch signals. The existing heart-rate sensing systems measure blood pulses by tracing the amount of light reflected from blood vessels during a number of cardiac cycles. This type of sensing system requires a considerable amount of power and space to be implemented in multi-functional mobile devices such as smart phones. It is found that the variation of the effective dielectric constant of finger stemming from the difference of systolic and diastolic blood flows can be measured with laterally interspaced top electrodes of TSP. The spacing between a pair of non-adjacent top electrodes turns out to be wide enough to distinguish heart-rate signals from noises. With the aid of fast Fourier transform, the heart-rate can be extracted reliably, which matches with the one obtained by actually counting heart beats on the wrist.

This study examines the dynamic conditional correlations between the US and Korean financial markets and identifies the determinants of those correlations using the VAR-DCC-MGARCH model. We find that the Global Financial Crisis (GFC) affects both countries. Although the shocks to the Korean market before the GFC are not shared by the US market, those to the US market after the GFC are shared by the Korean market. We also examine the determinants of the dynamic conditional relations between the US and Korean markets using domestic macroeconomic variables and US/Korean financial variables. The results indicate that the US financial variables are more significant than domestic macroeconomic variables and that they have become increasingly important over time.

This study uses an endogenous Markov-switching framework to examine the interrelatedness of the volatility dynamics of the US and Korean markets. Previous literature assumes that the US market impl...

외국인의 주식 및 채권 투자는 1990년대 말부터 증가하기 시작하여, 국내 금융시장에 영향력을 점차 확대해가고 있다. 이에 본 연구는 지난 20여년 간의 외국인 주식 및 채권투자의 추이와 특징을 파악하였다. 아울러 외국인 주식 및 채권 투자의 결정요인을 순매수, 매수, 매도와 같은 거래 형태와 거래 수준에 따라 세분화하여 분석하고 정책적 시사점을 제시하였다. As the linkage between domestic and foreign financial markets grows stronger, concerns have been raised about the inflow and outflow of foreign investment capital as a source of financial instability whenever the financial market becomes unstable. This is because, as the volume of capital inflows and outflows increases and volatility rises in the market, the financial system becomes more vulnerable and financial market price variables and macroeconomic uncertainty are increasing. Considering that opening the capital market is not an option, it becomes essential to examine the determinants of foreign investment to maximize the benefits of foreign capital inflows and outflows for sound growth in the real sector as well as the financial sector. Accordingly, this study attempts to produce evidence-based policy implications by empirically analyzing the determinants of the inflow and outflow of foreign investment funds. (the rest omitted)

Our chapter details a wide variety of approaches used in estimating productivity and efficiency based on methods developed to estimate frontier production using stochastic frontier analysis (SFA) and data envelopment analysis (DEA). The estimators utilize panel, single cross section, and time series data sets. The R programs include such approaches to estimate firm efficiency as the time-invariant fixed effects, correlated random effects, and uncorrelated random effects panel stochastic frontier estimators, time-varying fixed effects, correlated random effects, and uncorrelated random effects estimators, semiparametric efficient panel frontier estimators, factor models for cross-sectional and time-varying efficiency, bootstrapping methods to develop confidence intervals for index number-based productivity estimates and their decompositions, DEA and Free Disposable Hull estimators. The chapter provides the professional researcher, analyst, statistician, and regulator with the most up to date efficiency modeling methods in the easily accessible open source programming language R.

A technology is continuously developed in a rapidly changing global market. A company requires an appropriate R&D strategy for adapting to this environment. That is, the technologies owned by the company needs to be thoroughly analyzed to improve its competitiveness. Alternatively, technology classification using IPC codes is carried out recently in an objective and quantitative way. International Patent Classification, IPC is an internationally specified classification system, so it is helpful to conduct an objective and quantitative patent analysis of technology. In this study, all of the patents owned by company C are investigated and a matrix representing IPC codes of each patent is created. Then, a structured association map of the patents is made through association rules mining based on Confidence. The association map can be used to inspect the current situation of a company about patents. It also allows highly associated technologies to be clustered. Using the association map, this study analyzes the technologies of company C and how it changes with time. The strategy for future technologies is established based on the result.

We utilize the Internet search data from Google Trends to provide short-term forecasts for the inflow of Japanese tourists to South Korea. We construct the Google variable in a systematic way by combining keywords to minimize mean squared or mean absolute forecasting errors. We augment the Google variable to the standard time-series forecasting models and compare their forecasting accuracies. We find that Google-augmented models perform much better than the standard time-series models in terms of short-term forecasting accuracy. In particular, Google models show better out-of-sample forecasting performance than in-sample forecasting.

In this study, we present a highly responsive room-temperature resistive humidity sensor based on a shellac-derived carbon (SDC) active film deposited on sub-micrometer-sized carbon interdigitated electrodes (cIDEs). This monolithic carbon-based sensor demonstrates an excellent linear relationship with humidity and ohmic contact between the active carbon film and carbon electrodes, which results in low noise and low power consumption (∼1 mW). The active SDC film is synthesized by a single-step thermal process, wherein the temperature is found to control the amount of oxygen functional moieties of the SDC film, thereby providing an efficient means to optimize the sensor response time, recovery time, and sensitivity. This SDC–cIDEs-based humidity sensor exhibits an excellent dynamic range (0%–90% RH), a large dynamic response (50%), and high sensitivity (0.54/% RH). In addition, the two-dimensional feature (thickness ∼10 nm) of the SDC film enables a swift absorption/desorption equilibrium, leading to fast response (∼0.14 s) and recovery (∼1.7 s) under a humidity range of 0%–70% RH. Furthermore, the thin SDC-based sensor exhibited excellent selectivity to humidity from various gases, which in combination with its fast response/recovery promises its application for an instant calibration tool for gas sensors.

Using a three-regime Markov-switching framework, with time-varying transition probabilities and exogenous state variables, we find that overseas (US) market factors are more significant than domestic (Korean) factors in explaining VKOSPI dynamics. US financial variables are also more important than domestic variables in modeling time-varying transition probabilities, particularly during crisis periods.

We consider the bootstrap method for the covariates augmented Dickey–Fuller (CADF) unit root test suggested in Hansen (1995) which uses related variables to improve the power of univariate unit root tests. It is shown that there are substantial power gains from including correlated covariates. The limit distribution of the CADF test, however, depends on the nuisance parameter that represents the correlation between the equation error and the covariates. Hence, inference based directly on the CADF test is not possible. To provide a valid inferential basis for the CADF test, we propose to use the parametric bootstrap procedure to obtain critical values, and establish the asymptotic validity of the bootstrap CADF test. Simulations show that the bootstrap CADF test significantly improves the asymptotic and the finite sample size performances of the CADF test, especially when the covariates are highly correlated with the error. Indeed, the bootstrap CADF test offers drastic power gains over the convent...

This study investigates the well-documented phenomenon of phase transition in financial markets using combined information from both return and volume changes within short time intervals. We suggest a new measure for the phase transition behaviour of markets, calculated as a return distribution conditional on local variance in volume imbalance, and show that this measure successfully captures phase transition behaviour under various conditions. We analyse the intraday trade and quote dataset from the KOSPI 200 index futures, which includes detailed information on the original order size and the type of each initiating investor. We find that among these two competing factors, the submitted order size yields more explanatory power on the phenomenon of market phase transition than the investor type.

Commonly used asset pricing models do not successfully account for both time-series and cross-sectional variations of asset returns. In this article, we propose a new method for forming pricing factors that are intended to capture the time-series as well as the cross-sectional variations. The new pricing factors are constructed by utilizing a set of basis assets that are associated with firm characteristics. Compared with popular extant asset pricing models, empirical results show that the new model can parsimoniously and successfully account for both time-series and cross-sectional variations of asset returns and significantly improve model performances in terms of various measures: the Jensen’s α, root mean squared α, time series regression , cross-sectional regression and the HJ-distance measure.

This study examines the endogeneity effects of the US market implied volatility index (VIX) on the dynamics of the Korean implied volatility index (VKOSPI) under an advanced Markov-switching framework. Two types of endogeneity are considered. First, the U.S. variables in the regressors can be correlated with disturbance terms. This allows the direct and indirect effects of global shocks on Korean stock market volatility index to be measured. Second, regime-switching probabilities can be correlated with the disturbance terms. The estimation results show that both types of endogeneity are present in the US variables and more significant during the Global Financial Crisis.

This paper introduces a new estimation method for arbitrary temporal heterogeneity in panel data models. The paper provides a semiparametric method for estimating general patterns of cross-sectional specific time trends. The methods proposed in the paper are related to principal component analysis and estimate the time-varying trend effects using a small number of common functions calculated from the data. An important application for the new estimator is in the estimation of time-varying technical efficiency considered in the stochastic frontier literature. Finite sample performance of the estimators is examined via Monte Carlo simulations. We apply our methods to the analysis of productivity trends in the U.S. banking industry.

Ten-year monitoring and data assessment of a petroleum-hydrocarbon spill site were introduced to measure the effectiveness of natural attention at the site. For one decade, the monitoring of groundwater was conducted and collected data were analyzed to be used for the remediation of groundwater and soil for the future land development. The project site was previously used as gas station and car wash business. Typical groundwater contaminants such as TPH-G, BTEX, and oxygenates (MTBE, DIPE, ETBE, TAME, and TBA) were persistently found at the studied site. The plume and concentrations of monitored contaminants kept changing for the entire monitoring period. For this specific site, natural attenuation was unlikely feasible due to unfavorable environmental conditions. As a remediation strategy, other remediation options must be considered. The combinational method including a clean-up technology and natural attenuation is also recommended.

There have been debates on the effects of Olympics on economy. Previous studies estimated the direct benefits and costs of Olympic Games, and concluded that the net effects were positive or negative depending on specific assumptions used for evaluations. Recent studies turn attentions to indirect benefits. For example, signaling model by Rose and Spiegel (2010) argues that mega events are the signals of liberalization the country sends, and that the hosting of mega events spurs exports. This paper more thoroughly estimates the effects of Summer Olympics on exports and tourism using the Rose and Spiegel¡¯s data set extended up to 2008. Our empirical results show that the Summer Olympics have positively and significantly affected exports and tourists. The patterns are, however, different for exports and tourists. The effects on exports are slow and persist for long periods of time, whereas those on tourists are quick and short-lived. This finding is robust to different specifications. This result implies that, without carefully considering the time horizons of the effects of mega events, impact studies may be prone to over- or under-estimating the benefits of the mega events.

An IV approach, using as instruments non-linear transformations of the lagged levels, is explored to test for unit roots in panels with general dependency and heterogeneity across cross-sectional units. We allow not only for the cross-sectional dependencies of innovations, but also for the presence of co-integration across cross-sectional levels. Unbalanced panels and panels with differing individual short-run dynamics and cross-sectionally related dynamics are also permitted. We also more carefully formulate the unit root hypotheses in panels. In particular, using order statistics, we make it possible to test for and against the presence of unit roots in some of the individual units for a given panel. The individual IV t-ratios, which are the bases of our tests, are asymptotically and normally distributed and cross-sectionally independent. Therefore, the critical values of the order statistics as well as the usual average statistic can be easily obtained from simple elementary probability computations. We show via a set of simulations that our tests work well, whereas other existing tests fail to perform properly. As an illustration, we apply our tests to the panels of real exchange rates, and find no evidence for the purchasing power parity hypothesis, which is in sharp contrast with the previous studies. Copyright , Wiley-Blackwell.

This paper discusses the application of ultraviolet radiation-hydrogen peroxide (UV-HP) process as an advanced oxidation process (AOP) in the treatment of source waters containing natural organic matter (NOM) and contaminated with a synthetic organic chemical (SOC) exemplified by alachlor, an acetanilide pesticide. Alachlor was chosen as the model compound owing to its hydrophobicity and propensity to complex with NOM, besides its classification as an endocrine disrupting chemical (EDC). The study examines the general principles, free-radical chemistry and reaction mechanisms of the UV-HP process from a kinetic modeling standpoint, and provides a systematic approach combining experimental data acquisition with modeling techniques for evaluating the influence of NOM and other free-radical scavengers such as the carbonate species on the contaminant degradation efficiency. The study proposes a kinetic model for predicting and/or simulating the UV-HP decomposition of alachlor in the presence of NOM and other free-radical scavengers under different water quality and operating conditions. The model incorporates additional and descriptive features such as pH decrease during oxidation (due to mineralization of NOM and SOC), and uses UV absorbance at 310 nm (UVA310) as a surrogate parameter for NOM, accounting for changes in NOM structural composition attributable to hydroxyl radical attack and direct photolysis. The experimental data provide model validation and verification for alachlor degradation kinetics for NOM-free and NOM-containing waters. Although the model slightly overestimates the UV-HP process reaction rates for water containing NOM at low pH, it provides insight into the complex free-radical reactions, mechanisms and kinetics for process optimization toward economical and efficient decontamination.

This research investigated the application of H2O2/UV oxidation for source water pretreatment, and membrane cleaning to improve the performance of nanofiltration processes. It further examined the nature and mechanisms of membrane fouling by natural organic matter (NOM), and membrane cleaning using different chemical agents, by employing several surface characterization techniques. These techniques included attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR), X-ray photoelectron spectroscopy (XPS), atomic force microscopy (AFM), and scanning electron microscopy (SEM). The study revealed that significant improvement could be achieved in the efficiency and economics of nanofiltration for removing NOM and synthetic organic chemicals (SOCs) by employing source water pretreatment and membrane cleaning strategies. The H2O2/UV oxidation of source water prior to nanofiltration showed potential for the following: (i) mitigation of flux decline due to membrane fouling, (ii) removal of the pesticide alachlor and hydrogen sulfide, and (iii) improvement in membrane cleanability. Nonetheless, careful control of the preoxidation conditions was exercised to arrive at a reasonable compromise between fouling mitigation and NOM rejection.