The relationships among ideology, policy and economic performance : Mao Tsetung, Liu Shaochi and the economy of China

유신일 University of Nebraska at Lincoln 1991 해외박사

1949-87년 기간의 중국 사회주의 경제사에서 대약진과 문화 대혁명의 극좌 시기와 기타 실용주의 시기 간의 정치사상, 정부 정책, 경제성과 등을 분석하고, 경제 성과를 통계적으로 상호 비교하였습니다. 모택동의 “실천론”, “모순론”, “신민주주의”, “모순에 대한 수정 전략” 등과 유소기의 “모범 공산주의자가 되기 위한 방안”, “당내 투쟁론”, “공산당론”, “제8차 공산당 전당대회의 보고서” 등의 정치사상, 정책 등을 분석하고, 그 사상들이 중국 정치 경제 정책에 어떻게 반영되었는지 대약진(1958-60)과 문화대혁명(1966-76)의 극좌 시기와 실용주의 시기(1949-57, 1961-65, 1977-87) 간의 정부 정책들을 상호 비교하였습니다. 각 시기의 정부 정책이 공급 측면, 즉 사회총생산량, 농업, 중-경공업 생산량, 산업별 고용현황, 산업별 자본투자 현황, 한계 노동 생산량, 한계 자본 생산량, 임금성장율, 노동생산성과 사회총생산량의 성장율 등과, 그리고 수요측면, 즉 저축, 소매 판매량, 평균 소비 성장률과 농촌의 소비 성장률, 소비 추세 변화, 지역 분권화, 대외 무역 등 요소들을 분석하였습니다. 마지막으로 공급, 수요 요소들의 통계 수치들이 각 시기별로 현저한 차이가 있는지 점검하였습니다. 즉,각 수요, 공급 요소들에 대해서, Dummy 변수와, Auto Regression과 OLS 방법 등을 사용하고, Mann Whitney U Test도 병행함으로서, 통계적적으로 그 차이점을 점검하였습니다. 결론은, 사회주의 체제에서“정치경제”의 체제적인 개혁 없이, 경제적인 실용주의 개혁 정책만을 시도할 때, 실용주의 시기와 극좌 시기의 경제성과를 상호 비교한 결과는 통계적으로 그렇게 현저한 차이가 없다는 논지였습니다. 구소련이나 구동구에서도 경험한 바와 같이 체제 변화 없는 실용주의 경제 개혁의 시도는 실패와 함께, 결과적으로 오늘날 사회주의 체제의 붕괴를 야기했다고 생각합니다. 부연하면 중국식 사회주의 시장경제라고는 하지만, 사회주의는 수식어에 불과하며 실제적으로는 (R. Scalapino에 의하면) 박정희 공화당 정부에 비유되는, 즉 실제적인 개혁개방을 시도했던 1992년 이후의 통계 수치를 포함한다면 아마 논문의 결과는 다르게 도출 되었으리라 생각합니다.

Chemosensation in the Common Bed Bug, Cimex Lectularius

Liu, Feng ProQuest Dissertations & Theses Auburn University 2016 해외박사(DDOD)

As an ectoparasite on human beings and other animals, the common bed bug, Cimex lectulatius, has been resurgent worldwide and is of concern by both governments and general public for their biting nuisance and potential risk of disease transmission. The host-seeking or risk-avoiding behavior of bed bugs is mediated by their olfaction system in detecting attractive odorants or chemical repellents. Although the constituents of human emanations and chemical insect repellents have been thoroughly elucidated, we know little about which constituents are sensed and how they are recognized by the bed bug’s olfactory system, such as olfactory receptor neurons (ORNs) or odorant receptors (ORs). In order to reveal the mechanisms involved in the chemoreception of bed bugs, the current study investigated the responses from olfactory receptor neurons and odorant receptor to both human odorants and chemical insect repellents, especially DEET.Different types of olfactory sensilla were found to produce distinctive response profiles to human odorants and chemical insect repellents. Particularly, D types of olfactory sensilla possess the widest spectrum in detecting these odorants; E sensilla respond to very few odorants with low firing frequencies and C sensilla were only found to be sensitive to amines and several heterocyclics. Among all different chemical categories of stimuli, bed bug showed bias in detecting the aldehydes /ketones and alcohols and terpene-derived repellents but not the carboxylic acids and non-terpen-derived repellents. In addition, the dosages of odorants were shown to be an important factor in determining the firing frequency and temporal dynamics of neuronal response in bed bugs.To further decipher the molecular basis of neuronal responses to these odorants, bed bug ORs expressed in the Xenopus oocyte were challenged by odorants from both human being and chemical insect repellents. Each odorant receptor displayed variant tuning curves in response to these odorants and each odorant was encoded by multiple odorant receptors. Aldehydes/ketones, alcohols, heterocyclics and terpenes/terpenoides were more likely to activate bed bug ORs than carboxylic acids, which was consistent with the neuronal response bias. Moreover, dosage and chemical structure of odorants were two critical factors in influencing the responses of ORs.DEET, one of the most successful synthetic insect repellents, showed very significant repulsive effects to the common bed bug. Dual roles of DEET (activating effect and interfering effect) on the olfactory responses of bed bugs were revealed in this study. ORNs housed in two types of olfactory sensilla (Dα and Dβ sensilla) and at least three bed bug ORs (OR20, OR36 and OR37) were identified to be activated directly by DEET. Meanwhile, it was also proven that DEET could block or mask the neuronal responses of bed bugs to certain odorants by interfering with the function of specific odorant receptors in response to certain odorants. Interestingly, those three DEET-sensitive odorant receptors were found to be even more sensitive to the terpenes/terpenoids, which were originally isolated from plants. Behavior bioassays further indicated that these terpenes/terpenoids were much more effective in repelling bed bugs compared to DEET, suggesting that DEET targeted on the bed bug receptors that were naturally sensitive to terpenes/terpenoids. Thus our finding provided a novel mechanism for DEET’s function on insect olfactory systems.Taken together, my study presented a global picture about the chemoreception of the bed bug to both human odorants and chemical insect repellents, which gave insight to mechanisms of odorant recognition in the bed bug peripheral olfactory system. Particularly, we clarified both the activating and interfering effect of DEET in repelling the common bed bug, which should benefit the development of new repellents in bed bug control.

Advanced Statistical Learning Techniques for High-Dimensional Imaging Data

Liu, Leo Yu-feng ProQuest Dissertations & Theses The University of 2018 해외박사(DDOD)

With the rapid development of neuroimaging techniques, scientists are interested in identifying imaging biomarkers that are related to different subtypes or transitional stages of various cancers, neuropsychiatric diseases, and neurodegenerative.

Flexible Graph-based Learning with Applications to Genetic Data Analysis

Liu, Jianyu ProQuest Dissertations & Theses The University of 2019 해외박사(DDOD)

With the abundance of increasingly complex and high dimensional data in many scientific disciplines, graphical models have become an extremely useful statistical tool to explore data structures. In this dissertation, we study graphical models from two perspectives: i) to enhance supervised learning, classification in particular, and ii) graphical model estimation for specific data types. For classification, the optimal classifier is often connected with the feature structure within each class. In the first project, starting from the Gaussian population scenario, we aim to find an approach to utilize the graphical structure information of the features in classification. With respect to graphical models, many existing graphical estimation methods have been proposed based on a homogeneous Gaussian population. Due to the Gaussian assumption, these methods may not be suitable for many typical genetic data. For instance, the gene expression data may come from individuals of multiple populations with possibly distinct graphical structures. Another instance would be the single cell RNA-sequencing data, which are featured by substantial sample dependence and zero-inflation. In the second and the third project, we propose multiple graphical model estimation methods for these scenarios respectively. In particular, two dependent count-data graphical models are introduced for the latter case. Both numerical and theoretical studies are performed to demonstrate the effectiveness of these methods.

Effects of dietary complex probiotics supplementation on performance of weaning pigs and sows

Liu, Wen Chao Graduate School of Dankook University 2017 국내박사

(ABSTRACT) EFFECTS OF DIETARY COMPLEX PROBIOTICS SUPPLEMENTATION ON PERFORMANCE OF WEANING PIGS AND SOWS Department of Bio-Resource Science Graduate School DANKOOK UNIVERSITY WEN CHAO LIU Advisor: Prof. IN HO KIM EXPERIMENT 1: EFFECTS OF COMPLEX PROBIOTICS ON GROWTH PERFORMANCE, NUTRIENT DIGESTIBILITY, BLOOD PROFILES, FECAL MICROFLORA, SCORE AND NOXIOUS GAS EMISSION IN WEANING PIGS Weaning stress leads to pigs are susceptible to gastrointestinal disorders and digestive disturbances, thus resulting in high incidence of diarrhea and depressed growth rate. It has been suggested that probiotics could promote intestinal health and alleviate weaning stress in young pigs. This 42-d feeding trial was conducted to investigate the efficacy of a complex probiotics (Bacillus coagulance 1×1012 cfu/kg, Bacillus lichenformis 5×1011 cfu/kg, Bacillus subtilis 1×1012 cfu/kg, and Clostridium butyricum 1×1011 cfu/kg) in weaning pigs. A total of 125 28-d old weaning pigs [(Landrace × Yorkshire) × Duroc] with an initial average body weight (BW) of 7.26 ± 0.76 kg were randomly allotted into 5 treatments. There were 5 replicate pens per treatment with 5 pigs (3 barrows and 2 gilts) per pen. Dietary treatments included: CON, basal diet; PC1, CON + 0.01% complex probiotics; PC2, CON + 0.03% complex probiotics; PC3, CON + 0.06% complex probiotics; PC4, CON + 0.1% complex probiotics. On d 14, pigs fed the PC4 diet had higher BW gain than pigs fed the CON diet. On d 42, pigs fed multi-strain probiotics supplementation diets had higher BW gain than pigs fed the CON diet. From d 1 to 14, pigs fed the PC2, PC3 and PC4 diets had higher (P<0.05) ADG than pigs fed the CON diet. From d 15 to 42, pigs fed the complex probiotics supplementation diets had higher (P<0.05) average daily gain (ADG) and gain:feed ratio (G:F) than pigs fed the CON diet. The overall period, pigs fed the complex probiotics supplementation diets had higher (P<0.05) ADG and pigs fed the PC2 and PC4 diets had higher (P<0.05) G:F than pigs fed the CON diet. On d 42, pigs fed the PC4 diet had higher (P<0.05) apparent total tract digestibility (ATTD) of dry matter (DM), nitrogen (N) and gross energy (GE), fecal Lactobacillus counts and lower (P<0.05) E. coli counts and NH3 emission than pigs fed the CON diet. Pigs fed complex probiotics supplementation diets had lower (P<0.05) H2S and total mercaptans emissions than pigs fed the CON diet. In conclusion, dietary supplementation with complex probiotics improved growth performance, nutrition digestibility, intestinal microflora balance, and decreased fecal noxious gas emissions in weaning pigs. EXPERIMENT 2: EFFECTS OF COMPLEX PROBIOTICS SUPPLEMENTATION IN DIFFERENT NUTRIENT DENSITY DIETS ON GROWTH PERFORMANCE, NUTRIENT DIGESTIBILITY, BLOOD PROFILES, FECAL MICROFLORA AND NOXIOUS GAS EMISSION IN WEANING PIGS Previous study suggested that probiotics can serve as alternatives to increase performance in weaning pigs and the intake of probiotics can be affected by dietary nutrient density. The objective of this study was to evaluate the effects of complex probiotics (Bacillus coagulance 1×1012 cfu/kg, Bacillus lichenformis 5×1011 cfu/kg, Bacillus subtilis 1×1012 cfu/kg, and Clostridium butyricum 1×1011 cfu/kg) in different nutrient density diets on growth performance, digestibility, blood profiles, fecal microflora, and noxious gas emission in weaning pigs. A total of 140 weaning pigs [(Landrace × Yorkshire) × Duroc] with an average body weight (BW) of 7.05 ± 0.31 kg (28 d of age) were used in this 42-d trial. Pigs were randomly allotted to 1 of 4 treatments in a 2 × 2 factorial arrangement with 2 levels of energy and nutrient density supplemented with probiotics (0 or 0.05%) according to sex and BW (7 replicate pens, 3 gilts and 2 barrows/pen). From d 22 to 42, both high-nutrient-density and probiotics complex supplementation diets increased (P<0.05) the average daily gain (ADG). On d 42, the apparent total tract digestibility (ATTD) of dry matter, nitrogen and gross energy (GE), BUN concentration, NH3 and H2S emission were increased (P<0.05) in pigs fed high-nutrient-density diets. Pigs fed the probiotics complex supplementation diets had higher (P<0.05) ATTD of GE than pigs fed non-supplemented diets. Fecal Lactobacillus counts was increased, whereas E.coli counts, NH3 and H2S emission were decreased (P<0.05) in pigs fed the probiotics complex supplementation diets. Interactive effects (P<0.05) on average daily feed intake (ADFI) were observed from d 22 to 42 and overall, where the probiotics complex improved ADFI more dramatic in low-nutrient-density diets. In conclusion, the use of complex probiotic improved ADG, digestibility of GE, Lactobacilli counts and decreased E. coli counts, fecal NH3 and H2S emission in weaning pigs. Moreover, the beneficial effect of complex probiotics on ADFI is more dramatic with low-nutrient-density diets. EXPERIMENT 3: EFFECTS OF DIETARY COMPLEX PROBIOTICS SUPPLEMENTATION ON REPORDUCTIVE PERFORMANCE AND NOXIOUS GAS EMISSION IN SOWS The impacts of complex probiotics supplementation on reproductive performance and noxious gas emission in sows was evaluated in an experiment with a total of thirty sows (second-parity), from 4 weeks before farrowing to day 21 of lactation. The gestation and lactation diets of sows were supplemented with complex probiotics containing Bacillus subtilis (1.2 × 107 cfu/g) and Lactobacillus acidophilus (1.15 × 106 cfu/g). Treatments included: CON, basal diet, PB0.1, basal diet + 0.1 % probiotics, and PB0.2, basal diet + 0.2 % probiotics. The supplementation of dietary probiotics significantly improved average daily feed intake during the lactation period (quadratic, P=0.0429), sow backfat thickness during the weaning period (linear, P=0.0385), and initial body weight of piglets (linear, P=0.0054) as compared with CON, respectively. Furthermore, the supplementation of dietary probiotics reduced noxious gas emission as compared with CON (linear, P<0.05 for day 5 and day 10), respectively. In conclusion, dietary complex probiotics containing B. subtilis and L. acidophilus improved the reproductive performance of sows, resulted in increased weaning body weight of piglets, and induced an effective and significant reduction in fecal noxious gas emission in lactating sows, as compared with CON.

Mathematical Modeling for Dendritic Cells in the Immune System

Liu, Xiangtao Yale University 2010 해외박사(DDOD)

Dendritic cells (DCs) are specialized antigen presenting cells (APCs) playing key roles in initializing immune responses. Their functions have been thoroughly studied, and many applications to medicine have been derived accordingly. However, the life cycle of DCs, including cell origin, development, death and turnover, is only marginally understood. This thesis is dedicated to using computational methods to study the dynamics of the conventional DC (cDC) populations in mammalian immune systems. Recent experimental findings of dividing DCs in peripheral lymph organs require a mathematical model to illustrate the kinetics of DC homeostasis. To this end, I build a steady-state model consisting of three linear ordinary differential equations (ODEs). Analytical solutions are derived directly from the model. And biological parameters of interest (including input rate, cell cycle length and death rate) are computed using data provided by our collaborator Dr. Kang Liu, which are consistent with other studies. In addition, stability of the model is confirmed by numerical simulations. Furthermore, I extend the steady-state model to deal with stimulated states (equilibrium conditions altered by drugs, infections, or chemicals) by introducing the logistic growth model to cell proliferation with varying population sizes. The population of newly identified cDC precursors (pre-DCs) in spleen is included. In line with K. Liu's growth factor Flt3L-induced experiments, I conduct extensive computations to fine tune the model with regions of parameters. Finally, I derive a systematic model for DC's dynamic life cycle, which unifies both steady- and stimulated-states. In the future, we want to apply our model to predict unforeseen changes, minor or drastic, induced by external stimulations in the DC and pre-DC populations. These computational undertakings may well facilitate immunologists to effectively design their experiments to address key questions on pathogenic mechanisms in DC-related human disorders. The whole modeling approach is applicable to other similar dynamic systems. It can be easily extended to systems of other cell types with knowledge of the developing pathways. Keywords: APCs, cDCs, steady state, logistic growth, systematic model.

Measuring and Quantifying Driver Workload on Limited Access Roads

Liu, Ke ProQuest Dissertations & Theses University of Mich 2019 해외박사(DDOD)

Minimizing driver errors should improve driving safety. Driver errors are more common when workload is high than when it is low. Thus, it is of great importance to study driver workload. Knowing the amount of workload at any given time, take-over time can be determined, adaptive in-vehicle systems can be refined, and distracting in-vehicle secondary tasks can be regulated.In this dissertation, a model quantifying workload as a function of traffic, in which workload is proportional to inverse time headway (THW) and time to collision (TTC), was proposed. Two experiments were conducted to investigate how traffic affected driver workload and evaluate the proposed model. The driving scenarios were categorized into static (i.e., no relative movements among vehicles) and dynamic (i.e., there are relative velocities and lane change actions). Three categories of workload measures (i.e., workload rating, occlusion %, and driving performance statistics) were analyzed and compared. A GOMS model was built based upon a timeline model by using timerequired to represent mental resources demanded and timeavailable to represent mental resources available.In static traffic, the workload rating increased with increased number of vehicles around but was unaffected by participant age. The workload ratings decreased with increasing Distance Headways (DHWs) of each vehicle. From greatest to least, the effects were: DHWLead, DHWLeftLead, DHWLeftFollow, DHWFollow. Any surrounding vehicle that was 14.5 m away from the participant resulted in significant greater workload. Drivers tended to compromise longitudinal speed but still maintain lateral position when workload increased. Although occlusion% was less sensitive to scenarios having no lead vehicles, it can nonetheless be well predicted using the proposed workload model in sensitive scenarios. The resulting equations were occlusion% = 0.35 + 0.05/THWLead + 0.02/THWLeftLead - 0.08Age (Rocclusion2=0.91); rating = 1.74 + 1.74/THWLead + 0.20/THWFollow + 0.79/THWLeftLead + 0.28/THWLeftFollow (Rrating2=0.73). In dynamic traffic, drivers experienced greater workload in the faster lane; higher workload level was associated with greater relative velocity between two lanes. Both rating and occlusion% can be described using the proposed model: Anchored rating = 4.53 + 1.215/THWLeftLeadLead + 0.001/THWLeftFollow + 3.069/THWLeadLead + 0.524/THWLead + 0.240/(TTCLeadxTTCLeadLateral) + 30.487/(TTCLeftLeadxTTCLeftLeadLateral) (Rrating2=0.54); Occlusion% = 0.381 + 0.150/THWLeftLeadLead ˗ 0.117/THWLeadLead + 0.021/THWLead + 2.648/(TTCLeftLeadxTTCLeftLeadLateral) (Rocclusion2=0.58). In addition, it was shown that the GOMS model accounted for the observed differences of workload ratings from the empirical data (R2>0.83).In contrast to most previous studies that focus on average long-term traffic statistics (e.g., vehicles/lane/hour), this dissertation provided equations to predict two measures of workload using real-time traffic. The comparisons among three workload measures provided insights into how to choose the desired workload measures in their future research. In GOMS model, the procedural knowledge of rating workload while driving was developed. They should be transferrable to other workload studies and can serve as the primary tool to justify experimental design.Scientifically, the results of this dissertation offer insights into the mechanism of the way that humans perceive workload and the corresponding driving strategies. From the engineering application and practical value perspective, the proposed workload model would help future driving studies by providing a way to quantify driver workload and support the comparison of studies in different situations.

Exploiting user-generated data for knowledge discovery and recommendation

Liu, Haibin ProQuest Dissertations & Theses The Pennsylvania S 2014 해외박사(DDOD)

The Internet and Web 2.0 have achieved a rapid growth and became ubiquitous in recent years. The advance in information technologies has also enabled users to generate data, implicitly or explicitly, on an unprecedented scale. Consequently, the need to discover and exploit new and useful knowledge from such data has also increased considerably. In this thesis, in this regard, we investigate user-generated data to discover interesting knowledge and enable better recommendation services. First, we tackle the problem of the location type classification using individual Twitter messages. We extend probabilistic text classification models to incorporate temporal features and user history information as probabilistic priors, and show that the proposed models can boost the classification accuracy effectively. Second, we study the problem of quantifying the notion of political legitimacy using collective Twitter messages for specific populaces. We design a framework that aggregates a large number of tweets into the final legitimacy score of a populace by leveraging probabilistic topic modeling and sentiment analysis technique. Our empirical evaluation on eight sample countries using related public tweets demonstrates that our proposed framework shows a strong correlation to results reported in political science literature. We also apply this framework to a traditional news media data set, and compare the results with Twitter data. Several interesting differences are discovered between these two medias for this quantification task of political legitimacy. Third, we study the problem of mining implicit user feedback in recommendation systems. In particular, we tackle the cold-start problem of video recommendation using users' co-view information. We propose a classification framework to incorporate co-view information based on previously seen video pairs, and learn the weights of video attributes for ranking candidate videos to recommend, yielding encouraging recommendation results. Finally, as a way to exploit social network for recommendation, we study the problem of recommending the best team for a given set of roles or skillset considering both individual and team characteristics. To quantitatively capture the team level features, we take various social networks among people into consideration from project history and many other online activities. Moreover, we learn the feature weights from the training dataset based on the correlation between features and project outcomes, and apply a combinatorial optimization algorithm to search the approximate best team. We validate our approach experimentally in a real business scenario and also compare our approach with other state-of-the-art methods using public DBLP dataset. The results demonstrate the effectiveness of our approach.

Essays on Social Network, Consumption and Leadership in Video-Game Community

Liu, Peng ProQuest Dissertations & Theses Indiana University 2019 해외박사(DDOD)

Massively Multiplayer Online Role Playing Games (MMO-RPG), such as World of Warcraft, usually have millions of regular subscribers, which creates a vibrant social network in the virtual world. However, the mechanism of players' purchase behavior is not widely studied in the literature. In the first essay we propose a dynamic structural model to study how dynamic tradeoff between spending time and spending money impact player's purchase decisions. We are trying to answer the following research questions: 1. Do consumers exhibit behavior of trading off time and money in their consumption? 2. Are consumers forward-looking and do they trade off money and time in their consumption inter-temporally? 3. How does consumer's time and money tradeoff behavior affect consumer welfare and firm profits?. In the second essay, we propose a model to study the effects of social factors on consumer's purchase decision in a large online video-game community. We empirically analyze video-game player's purchase of hedonic and utilitarian items. We develop measures of influentialness, friendship tie strength, and observed similarity, while accounting for potential endogeneity of the social influence and price variables. We study whether the effect of observational learning is strengthened or weakened by the above player and friendship characteristics. In the third essay, we study how players pursue leadership in a multiplayer game community, and how such behavior influences their spending decisions. We build a structural model to describe how, motivated by the aspiration to become a leader, players choose "guilds" and make spending decisions in a game. We use counterfactuals to explore how a video game company can make use of such incentive to increase its profit.

An Experimental Study of Water Surface Features in Response to Rain

Liu, Ren University of Maryland, College Park ProQuest Diss 2017 해외박사(DDOD)

Water surface features induced by the impact of raindrops on a deep water pool are studied experimentally in an artificial rain facility. Artificial rain is produced by a rain generator that consists of a rectangular tank with an array of 738 hypodermic needles attached to its bottom and that is mounted at various heights above a deep water pool. In this thesis, three rain intensities and four raindrop impact velocities are used while the diameters of raindrops remain approximately the same. For comparison with some of the results of the rain experiments, a set of single drop impacts on a quiescent water surface were also performed.. In the single drop impact experiments, cinematic shadowgraph methods were used to measure the drop diameter (D) and velocity ( V) just before impact, to observe qualitatively the water surface response and to measure the height of the vertical water jet (stalk) that is typically part of the water surface response. It is found that the stalk height varies with impact Froude number (Fr = V 2/(gD), where g is the acceleration of gravity) in three different ways depending on the Froude number range. In the rain experiments, the drop diameters and velocities are measured with a cinematic shadowgraph technique while the temporal evolution of the surface profile along the center plane of the target water pool is measured with a cinematic Laser Induced Fluorescence (LIF) technique. The history of rain-induced stalk height and the profiles of the rain-induced surface waves are extracted at each instant in time. It is found that the stalk height varies considerably in the rain field and the average stalk heights are less than in cases with single drop impacting a quiescent surface at the same Froude number (Fr). The stalk height distribution correlates with the rain intensities rather than the impact velocity. Occasional bubble entrainment was observed at the lowest raindrop impact velocity (Fr = 500) while bubble entrainment only occurred for Froude numbers greater than 1800 in single drop experiments. Furthermore, surface waves outside of the rain field propagate faster than that inside the rain field. Radar backscattering powers from raindrops, surface waves in front of the rain field and the water surface features inside a rain field are measured. The measurement results show that strong radar return signals are observed from the water surface inside the rain field while the radar return signals from both raindrops and the surface waves in front of the rain field are weak. The experimental results also show that the radar return intensity increases as the rain intensity increases from 85 to 300 mm/hr. In addition, it is found that the attenuation of the radar backscattering from the rain field is likely correlated with a high-water-content layer of secondary droplets generated in the rain field.