Layered Interpretation of Street View Images

We propose a layered street view model to encode both depth and semantic information on street view images for autonomous driving. Recently, stixels, stix-mantics, and tiered scene labeling methods have been proposed to model street view images. We propose a 4-layer street view model, a compact representation over the recently proposed stix-mantics model. Our layers encode semantic classes like ground, pedestrians, vehicles, buildings, and sky in addition to the depths. The only input to our algorithm is a pair of stereo images. We use a deep neural network to extract the appearance features for semantic classes. We use a simple and an efficient inference algorithm to jointly estimate both semantic classes and layered depth values. Our method outperforms other competing approaches in Daimler urban scene segmentation dataset. Our algorithm is massively parallelizable, allowing a GPU implementation with a processing speed about 9 fps.Comment: The paper will be presented in the 2015 Robotics: Science and Systems Conference (RSS

Modeling and Software Synthesis for Multiprocessor Implementation of Wireless Communication Systems

In recent years, the complexity of designing embedded signal processing systems for wireless communications has increased significantly based on the need to support increasing levels of operational flexibility and adaptivity, while also supporting increasing data rates and bandwidths. These trends pose important design and implementation challenges to meet the required demands on communication system performance, real-time operation, energy efficiency, and reconfigurability. Dataflow models of computation provide a useful framework that can be built upon to address these challenges. Dataflow models provide high-level abstractions for specifying, analyzing and implementing a wide range of embedded signal processing applications. They allow designers to specify an application using high-level, platform-independent representations, and synthesize optimized embedded software that is targeted to specific types of hardware resources and design constraints. The growing complexity of wireless communication systems, as motivated above, along with the complexity of system-on-chip platforms for embedded signal processing result in new problems that must be addressed in developing effective dataflow-based design methodologies. First, significant improvements to dataflow-based models and methods are needed to effectively utilize heterogeneous computing platforms and multiple forms of parallelism under stringent constraints on real-time performance and energy consumption. Second, effective modeling and analysis methods for handling dynamic parameters within dataflow graph components are needed for reliable and efficient management of system-level adaptivity and reconfiguration. In this thesis, we address these problems by developing an integrated framework that exploits pipeline, data and task-level parallelism in dataflow models under memory constraints, and proposing novel dataflow modeling concepts and performance optimization techniques for design and implementation of dynamically parameterized communication systems. The main contributions of the thesis are summarized as follows: (1) Software synthesis framework for heterogeneous signal processing platforms. We have developed an integrated dataflow-based design framework called DIF-GPU, which provides a toolset for specification, optimization and software synthesis of embedded software targeted to heterogeneous CPU-GPU platforms. DIF-GPU incorporates novel models and methods in the dataflow interchange format (DIF) that are geared toward design optimization of signal processing systems on heterogeneous architectures composed of multicore CPUs and GPUs. DIF-GPU helps to free developers from low-level, platform-specific fine-tuning, and allows them to focus on higher-level aspects of communication system design. (2) Vectorization in DIF-GPU. In the context of dataflow models for embedded signal processing, vectorization is an important transformation for exploiting data parallelism. We have developed new techniques for integrated dataflow graph vectorization and scheduling on heterogeneous platforms. These techniques are developed in the DIF-GPU framework to provide optimized vectorization and scheduling capabilities for hybrid CPU-GPU platforms under memory constraints. For the targeted class of platforms, these techniques are shown to provide significantly better processing throughput compared to previous methods for a given memory constraint. We demonstrate our integrated vectorization and scheduling techniques by applying them to an Orthogonal Frequency Division Multiplexing (OFDM) receiver system. (3) Modeling parameterized, dynamic dataflow behavior. We introduce a novel modeling method, called parameterized sets of modes (PSMs), that enables efficient representation and analysis of adaptive and dynamically reconfigurable signal processing functionality. PSMs can be viewed as high-level abstractions that model parameterized functionality involving groups of related regimes of operation ("modes") for dynamic dataflow models. We develop formal foundations for PSM-based modeling, and demonstrate the utility of this form of modeling by using it to develop efficient methods for scheduling dynamically parameterized dataflow graphs on different types of relevant platforms

Applying foliar stoichiometric traits of plants to determine fertilization for a mixed pine-oak stand in the Qinling Mountains, China

Background The Chinese Natural Forest Protection program has been conducted nationwide and has achieved resounding success. However, timber importation has increased; therefore, producing more domestic timber is critical to meet the demand for raw materials. Fertilization is one of the most effective silviculture practices used to improve tree and stand growth. However, determining the appropriate type and amount of elements is necessary for effective fertilization of big timber in different forest types and environmental conditions. Stoichiometric theory provides the criteria to assess nutrient limitation in plants and offers important insight into fertilizer requirements of forested ecosystems. Methods Nitrogen (N) and phosphorus (P) concentrations in plants’ leaves, mineral soil, and litter were investigated in a mixed pine-oak stand. Results The big timber rate for Pinus tabuliformis, Pinus armandii and Quercus aliena var. acutesserata is 57.71%, 22.79% and 2.78% of current existing individuals respectively. Foliar N and P concentrations were 9.08 and 0.88 mg g−1, respectively. The N:P in the plants was 10.30. N concentration and N:P in mineral soil decreased from 0–30 cm soil depth. For litter, N and P concentrations were 16.89 and 1.51 mg g−1, respectively, and N:P was 11.51. Concentrations of N and P in mineral soil and litter did not significantly affect plants’leaf concentrations. Similar result was also obtained between litter and mineral soil concentrations. Nitrogen storage in mineral soil was significantly correlated with foliar N:P in the plants. Discussion Foliar N:P of dominant tree species and the plants, and foliar N concentration in Pinus tabuliformis and P. armandii, and foliar P concentration of P. armandii in the mixed pine-oak stand was lower than that in Chinese and other terrestrial plants. Foliar nutrients in the plants were not affected by soil nutrients. According to the criteria of nutrient limitation for plants, growth of dominant tree species was N limited; therefore, 1.49 t ha−1 pure N should be added to forest land to as fertilizer

Biometric and Eddy Covariance Methods for Examining the Carbon Balance of a Larix principis-rupprechtii Forest in the Qinling Mountains, China

The carbon balance of forests is controlled by many component processes of carbon acquisition and carbon loss and depends on the age of vegetation, soils, species composition, and the local climate. Thus, examining the carbon balance of different forests around the world is necessary to understand the global carbon balance. Nevertheless, the available information on the carbon balance of Larix principis-rupprechtii forests in the Qinling Mountains remains considerably limited. We provide the first set of results (2010–2013) from a long-term project measuring forest-atmosphere exchanges of CO2 at the Qinling National Forest Ecosystem Research Station (QNFERS), and compare the net ecosystem exchange (NEE) based on biometric measurements with those observed via the eddy covariance method. We also compare the total ecosystem respiration via scaled-up chamber and eddy covariance measurements. The net primary productivity (NPP) was 817.16 ± 81.48 g·C·m−2·y−1, of which ΔBliving and Dtotal accounted for 77.7%, and 22.3%, respectively. Total ecosystem respiration was 814.47 ± 64.22 g·C·m−2·y−1, and cumulative annual soil respiration, coarse woody debris respiration, stem respiration, and leaf respiration were 715.47 ± 28.48, 15.41 ± 1.72, 35.28 ± 4.78, and 48.31 ± 5.24 g·C·m−2·y−1, respectively, accounting for 87.85%, 1.89%, 4.33%, and 5.93% of the total ecosystem respiration. A comparison between ecosystem respiration from chamber measurements and that from eddy covariance measurements showed a strong linear correlation between the two methods (R2 = 0.93). The NEE of CO2 between forests and the atmosphere measured by eddy covariance was −288.33 ± 25.26 g·C·m−2·y−1, which revealed a carbon sink in the L. principis-rupprechtii forest. This number was 14% higher than the result from the biometric measurements (−336.71 ± 25.15 g·C·m−2·y−1). The study findings provided a cross-validation of the CO2 exchange measured via biometric and eddy covariance, which are beneficial for obtaining the true ecosystem fluxes, and more accurately evaluating carbon budgets

Dynamics of Coarse Woody Debris Characteristics in the Qinling Mountain Forests in China

Coarse woody debris (CWD) is an essential component in defining the structure and function of forest ecosystems. Long-term dynamics of CWD characteristics not only affect the release rates of chemical elements from CWD, but also the species diversity of inhabiting plants, animals, insects, and microorganisms as well as the overall health of ecosystems. However, few quantitative studies have been done on the long-term dynamics of CWD characteristics in forest ecosystems in China. In this study, we conducted nine tree censuses between 1996 and 2016 at the Huoditang Experimental Forest in the Qinling Mountains of China. We quantified forest biomass including CWD and CWD characteristics such as decay states and diameter classes during this period and correlated with stand, site, and climatic variables. The forest biomass was dominated by live tree biomass (88%); followed by CWD mass (6%–10%). Understory biomass contributed only a small portion (1%–4%) of the overall biomass. Significant differences in average annual increment of CWD mass were found among forest stands of different species (p < 0.0001). Forest biomass, stand age, forest type, aspect, slope, stand density, annual average temperature, and precipitation were all significantly correlated with CWD mass (p < 0.05), with forest type exhibiting the strongest correlation (r2 = 0.8256). Over time, the annual mass of different CWD characteristics increased linearly from 1996–2016 across all forest types. Our study revealed that forest biomass, including CWD characteristics, varied by forest type. Stand and site characteristics (forest biomass, forest type, aspect, slope and stand density) along with temperature and precipitation played a major role in the dynamics of CWD in the studied forest ecosystems

Soil pretreatment and fast cell lysis for direct polymerase chain reaction from forest soils for terminal restriction fragment length polymorphism analysis of fungal communities

AbstractHumic substances in soil DNA samples can influence the assessment of microbial diversity and community composition. Using multiple steps during or after cell lysis adds expenses, is time-consuming, and causes DNA loss. A pretreatment of soil samples and a single step DNA extraction may improve experimental results. In order to optimize a protocol for obtaining high purity DNA from soil microbiota, five prewashing agents were compared in terms of their efficiency and effectiveness in removing soil contaminants. Residual contaminants were precipitated by adding 0.6mL of 0.5M CaCl2. Four cell lysis methods were applied to test their compatibility with the pretreatment (prewashing+Ca2+ flocculation) and to ultimately identify the optimal cell lysis method for analyzing fungal communities in forest soils. The results showed that pretreatment with TNP+Triton X-100+skim milk (100mM Tris, 100mM Na4P2O7, 1% polyvinylpyrrolidone, 100mM NaCl, 0.05% Triton X-100, 4% skim milk, pH 10.0) removed most soil humic contaminants. When the pretreatment was combined with Ca2+ flocculation, the purity of all soil DNA samples was further improved. DNA samples obtained by the fast glass bead-beating method (MethodFGB) had the highest purity. The resulting DNA was successfully used, without further purification steps, as a template for polymerase chain reaction targeting fungal internal transcribed spacer regions. The results obtained by terminal restriction fragment length polymorphism analysis indicated that the MethodFGB revealed greater fungal diversity and more distinctive community structure compared with the other methods tested. Our study provides a protocol for fungal cell lysis in soil, which is fast, convenient, and effective for analyzing fungal communities in forest soils