Imitation learning with dynamic movement primitives

Scientists have been working on making robots act like human beings for decades. Therefore, how to imitate human motion has became a popular academic topic in recent years. Nevertheless, there are infinite trajectories between two points in three-dimensional space. As a result, imitation learning, which is an algorithm of teaching from demonstrations, is utilized for learning human motion. Dynamic Movement Primitives (DMPs) is a framework for learning trajectories from demonstrations. Likewise, DMPs can also learn orientations given rotational movement's data. Also, the simulation is implemented on Robot Baxter which has seven degrees of freedom (DOF) and the Inverse Kinematic (IK) solver has been pre-programmed in the robot, which means that it is able to control a robot system as long as both translational and rotational data are provided. Taking advantage of DMPs, complex motor movements can achieve task-oriented regeneration without parametric adjustment and consideration of instability. In this work, discrete DMPs is utilized as the framework of the whole system. The sample task is to move the objects into the target area using Robot Baxter which is a robotic arm-hand system. For more effective learning, a weighted learning algorithm called Local Weighted Regression (LWR) is implemented. To achieve the goal, the weights of basis functions are firstly trained from the demonstration using DMPs framework as well as LWR. Then, regard the weights as learning parameters and substitute the weights, desired initial state, desired goal state as well as time-correlated parameters into a DMPs framework. Ultimately, the translational and rotational data for a new task-specific trajectory is generated. The visualized results are simulated and shown in Virtual Robot Experimentation Platform (VREP). For accomplishing the tasks better, independent DMP is used for each translation or rotation axis. With relatively low computational cost, motions with relatively high complexity can also be achieved. Moreover, the task-oriented movements can always be successfully stabilized even though there are some spatial scaling and transformation as well as time scaling. Twelve videos are included in supplementary materials of this thesis. The videos mainly describe the simulation results of Robot Baxter shown on Virtual Robot Experimentation Platform (VREP). The specific information can be found in the appendix

Market Response to Flood Risk: An Empirical Study of Housing Values Using Boundary Discontinuities

This paper presents one of the first studies on flood risk evaluation in the US Northeast - a region where we are likely going to see increasing precipitation variability and associated risk of flood in the coming decades. In the paper, a spatial difference-in-differences framework based on floodplain boundary discontinuities is proposed to control for unobserved heterogeneities. Using parcel-level data from Juniata County and Perry County in Pennsylvania, the paper finds that on average there is a 5-6 percent housing value reduction due to exposure to 1 percent annual chance of flooding within the FEMA (Federal Emergency Management Agency) 100-year flood zone. For Juniata County, it shows that on average there is a $3.28/sqft (in 2015 USD) discount for a full-time SFR (single family residential) property located within the flood zone. For an average housing unit of 1430 sqft living space in the sample, the estimate translates to a$4690 housing value reduction. For Perry County, the corresponding estimates are $4.00/sqft (in 2015 USD) and$6320 for an average housing unit of 1580 sqft. The paper also shows that with similar specifications, a standard hedonic price model underestimates the flood risk impact on housing value by a substantial amount as a result of failing to control for unobserved heterogeneities

An Economic Impact Analysis of Oil and Natural Gas Development in the Permian Basin

This study analyzes the economic impact of oil and natural gas development in the Permian Basin with a focus on the NM part of the Basin. The analysis looks at the impacts on state revenue, local employment and income levels. Several existing economic impact reports from other states have been criticized by the peer-review literature that the impact estimates are very likely overstated due to questionable methodologies. In this analysis, a panel data regression model with county fixed effects and year effects is deployed to identify the impact of oil and natural gas production on employment and per job annual income at the county level. The analysis covers 62 counties (12 counties in NM and 50 counties in TX) for the time period of 1998 – 2016. The main findings of the analysis can be summarized as: 1. Over the last decade, according to different estimates the state revenue generated by the oil and natural gas industries in NM has been consistently exceeding one billion dollars per year. In the meantime, a large amount of intensive direct investment has been capitalized into the southeast NM. 2. In aggregate, per job annual income (in the real term) and the number of jobs have both experienced significant growth in the last two decades of active oil and natural gas development in the region. It is reasonable to speculate that much of the growth can be attributed to the ongoing energy development. 3. It is estimated that on average additional one million BBLs of oil equivalent production brings 54 jobs and about $170 (2015 dollar) extra annual income per job (or a 0.5 4. The intensive oil and natural gas production around the center of the basin (Lea County and Eddy County in NM) have had significant spatial spillover effects to the surrounding counties. Depending on the distance from the given county to the center of the Basin and for additional one million BBLs of oil equivalent production, the employment effect ranges from 35 to 10 jobs and the income effect ranges from$170 to $90 (2015 dollar) extra annual income per job. The paper also provides details on methodology and guidelines on how to interpret estimation results. The estimated economic impact coefficients can be used for prediction purpose with available future production scenarios. The paper includes instructions and suggestions on how the prediction may proceed

An Economic Impact Analysis of Oil and Natural Gas Development in the Permian Basin

This study analyzes the economic impact of oil and natural gas development in the Permian Basin with a focus on the NM part of the Basin. The analysis looks at the impacts on state revenue, local employment and income levels. Several existing economic impact reports from other states have been criticized by the peer-review literature that the impact estimates are very likely overstated due to questionable methodologies. In this analysis, a panel data regression model with county fixed effects and year effects is deployed to identify the impact of oil and natural gas production on employment and per job annual income at the county level. The analysis covers 62 counties (12 counties in NM and 50 counties in TX) for the time period of 1998 – 2016. The main findings of the analysis can be summarized as: 1. Over the last decade, according to different estimates the state revenue generated by the oil and natural gas industries in NM has been consistently exceeding one billion dollars per year. In the meantime, a large amount of intensive direct investment has been capitalized into the southeast NM. 2. In aggregate, per job annual income (in the real term) and the number of jobs have both experienced significant growth in the last two decades of active oil and natural gas development in the region. It is reasonable to speculate that much of the growth can be attributed to the ongoing energy development. 3. It is estimated that on average additional one million BBLs of oil equivalent production brings 54 jobs and about $170 (2015 dollar) extra annual income per job (or a 0.5 4. The intensive oil and natural gas production around the center of the basin (Lea County and Eddy County in NM) have had significant spatial spillover effects to the surrounding counties. Depending on the distance from the given county to the center of the Basin and for additional one million BBLs of oil equivalent production, the employment effect ranges from 35 to 10 jobs and the income effect ranges from$170 to $90 (2015 dollar) extra annual income per job. The paper also provides details on methodology and guidelines on how to interpret estimation results. The estimated economic impact coefficients can be used for prediction purpose with available future production scenarios. The paper includes instructions and suggestions on how the prediction may proceed

Rural Entrepreneurship Development in Southwest China: A Spatiotemporal Analysis

Rural entrepreneurship has been seen by the central government of China as a key means to rural vitalization. However, research focus on the long-term developmental status of rural entrepreneurship at local scale has been limited. According to industry types of differentiation, this research describes rural enterprises registered in the administrative area of Mianyang, southwest China, from 2011 to 2020. The spatial-temporal distribution rule of rural entrepreneurship is explored via a quantitative approach focused on spatial analysis and correlation analysis, as well as the application of geocoding on web data. How contexts such as the natural base, socio-economic condition, and institutional arrangements impact this distribution are empirically explored and discussed. The paper adds spatial-temporal insights into the role of the context of rural entrepreneurship. In particular, the paper highlights that rural entrepreneurship is a process potentially best explored at the regional scale and that physical condition and institutional support play central roles in rural entrepreneurship in southwest China.hina Scholarship CouncilDeutsche Forschungsgemeinschaft (DFG, German Research Foundation)Open Access Publication Fund of Humboldt-Universität zu BerlinPeer Reviewe

Understanding the Challenges Faced by Chinese International Graduate Students in Acquiring Information Literacy: The Impact of Internet Censorship

Previous research identified that Chinese international students face challenges in acquiring information literacy. However, few studies have addressed the influence of Internet censorship. Thus, this study aims to explore the adaptation of Chinese international postgraduate students during the transition from undergraduate study in China to postgraduate study in Canada, with reference to their information literacy skills under the impact of Internet censorship in China. Data collection for this study was comprised of two components: an online survey and individual interviews with four participants. Examined through the mechanism of Internet censorship in China created by Roberts (2018), the findings conclude that Internet censorship affects the Chinese international graduate students’ information literacy acquisition by restricting expression of and access to information. Finally, to enhance the development of students’ information literacy, it is vital that they seek support and advice from the university, and their teachers and peers

Predicting Growth of City\u27s Built-up Land Based on Scenario Planning

In this paper, method of scenario planning is applied to the study of land use planning, putting forward a new approach to analyze future growth of city\u27s built-up land in the context of future uncertainty. By introducing economic and policy factors into land use system, a calculation model of urban built-up land is built based on the correlation between industries and land use. And using Chongqing Municipality from China as an example, we establish 6 different scenarios and simulate future development of city\u27s land use from 2015 to 2020 under each scenario. The results indicate that Chongqing will meet fast urban expansion according to current trend and is in urgent need to improve its land use efficiency which shows strongest effect in controlling city size

A Self-Adjusting Approach to Identify Hotspots

Hotspot identification or detection has been widely used in many fields; however the traditional grid-based approaches may incur some problems when dealing with point database. This article expands on three types of mismatch problems in grid-based approach and suggests a point-based approach may be more suitable. Inspired by the DBSCAN algorithm, a self-adjusting approach is then proposed for hotspot detection which overcomes the weakness of parameter sensitivity shared by most clustering approaches. Finally, the data of commercial points of interest of a city is used for demonstration