An Integrative Remote Sensing Application of Stacked Autoencoder for Atmospheric Correction and Cyanobacteria Estimation Using Hyperspectral Imagery

Hyperspectral image sensing can be used to effectively detect the distribution of harmful cyanobacteria. To accomplish this, physical- and/or model-based simulations have been conducted to perform an atmospheric correction (AC) and an estimation of pigments, including phycocyanin (PC) and chlorophyll-a (Chl-a), in cyanobacteria. However, such simulations were undesirable in certain cases, due to the difficulty of representing dynamically changing aerosol and water vapor in the atmosphere and the optical complexity of inland water. Thus, this study was focused on the development of a deep neural network model for AC and cyanobacteria estimation, without considering the physical formulation. The stacked autoencoder (SAE) network was adopted for the feature extraction and dimensionality reduction of hyperspectral imagery. The artificial neural network (ANN) and support vector regression (SVR) were sequentially applied to achieve AC and estimate cyanobacteria concentrations (i.e., SAE-ANN and SAE-SVR). Further, the ANN and SVR models without SAE were compared with SAE-ANN and SAE-SVR models for the performance evaluations. In terms of AC performance, both SAE-ANN and SAE-SVR displayed reasonable accuracy with the Nash???Sutcliffe efficiency (NSE) > 0.7. For PC and Chl-a estimation, the SAE-ANN model showed the best performance, by yielding NSE values > 0.79 and > 0.77, respectively. SAE, with fine tuning operators, improved the accuracy of the original ANN and SVR estimations, in terms of both AC and cyanobacteria estimation. This is primarily attributed to the high-level feature extraction of SAE, which can represent the spatial features of cyanobacteria. Therefore, this study demonstrated that the deep neural network has a strong potential to realize an integrative remote sensing application

Analyzing Attacks on Cooperative Adaptive Cruise Control (CACC)

Cooperative Adaptive Cruise Control (CACC) is one of the driving applications of vehicular ad-hoc networks (VANETs) and promises to bring more efficient and faster transportation through cooperative behavior between vehicles. In CACC, vehicles exchange information, which is relied on to partially automate driving; however, this reliance on cooperation requires resilience against attacks and other forms of misbehavior. In this paper, we propose a rigorous attacker model and an evaluation framework for this resilience by quantifying the attack impact, providing the necessary tools to compare controller resilience and attack effectiveness simultaneously. Although there are significant differences between the resilience of the three analyzed controllers, we show that each can be attacked effectively and easily through either jamming or data injection. Our results suggest a combination of misbehavior detection and resilient control algorithms with graceful degradation are necessary ingredients for secure and safe platoons.Comment: 8 pages (author version), 5 Figures, Accepted at 2017 IEEE Vehicular Networking Conference (VNC

Comparison of daily and sub-daily SWAT models for daily streamflow simulation in the Upper Huai River Basin of China

Despite the significant role of precipitation in the hydrological cycle, few studies have been conducted to evaluate the impacts of the temporal resolution of rainfall inputs on the performance of SWAT (soil and water assessment tool) models in large-sized river basins. In this study, both daily and hourly rainfall observations at 28 rainfall stations were used as inputs to SWAT for daily streamflow simulation in the Upper Huai River Basin. Study results have demonstrated that the SWAT model with hourly rainfall inputs performed better than the model with daily rainfall inputs in daily streamflow simulation, primarily due to its better capability of simulating peak flows during the flood season. The sub-daily SWAT model estimated that 58% of streamflow was contributed by baseflow compared to 34 % estimated by the daily model. Using the future daily and three-hour precipitation projections under the RCP (Representative Concentration Pathways) 4.5 scenario as inputs, the sub-daily SWAT model predicted a larger amount of monthly maximum daily flow during the wet years than the daily model. The differences between the daily and sub-daily SWAT model simulation results indicated that temporal rainfall resolution could have much impact on the simulation of hydrological process, streamflow, and consequently pollutant transport by SWAT models. There is an imperative need for more studies to examine the effects of temporal rainfall resolution on the simulation of hydrological and water pollutant transport processes by SWAT in river basins of different environmental conditions

Assessment of different modelling studies on the spatial hydrological processes in an arid alpine catchment

To assess the model description of spatial hydrological processes in the arid alpine catchment, SWAT and MIKE SHE were jointly applied in Yarkant River basin located in northwest China. Not only the simulated daily discharges at the outlet station but also spatiotemporal distributions of runoff, snowmelt and evapotranspiration were analyzed contrastively regarding modules' structure and algorithm. The simulation results suggested both models have their own strengths for particular hydrological processes. For the stream runoff simulation, the significant contributions of lateral interflow flow were only reflected in SWAT with a proportion of 41.4 %, while MIKE SHE simulated a more realistic distribution of base flow from groundwater with a proportion of 21.3 %. In snowmelt calculation, SWAT takes account of more available factors and got better correlations between snowmelt and runoff in temporal distribution, however, MIKE SHE presented clearer spatial distribution of snowpack because of fully distributed structure. In the aspect of water balance, less water was evaporated because of limitation of soil evaporation and less spatially distributed approach in SWAT, on another hand, the spatial distribution of actual evapotranspiration (ETa) in MIKE SHE clearly expressed influence of land use. Whether SWAT or MIKE SHE, without multiple calibrations, the model's limitation might bring in some biased opinions of hydrological processes in a catchment scale. The complementary study of combined results from multiple models could have a better understanding of overall hydrological processes in arid and scarce gauges alpine region

Law, Finance, and Politics: The Case of India

The process of liberalisation of India's economy since 1991 has brought with it considerable development both of its financial markets and the legal institutions which support these. An influential body of recent economic work asserts that a country's 'legal origin'-as a civilian or common law jurisdiction-plays an important part in determining the development of its investor protection regulations, and consequently its financial development. An alternative theory claims that the determinants of investor protection are political, rather than legal. We use the case of India to test these theories. We find little support for the idea that India's legal heritage as a common law country has been influential in speeding the path of regulatory reforms and financial development. There is a complementarity between (i) India's relative success in services and software, (ii) the relative strength of its financial markets for outside equity, as opposed to outside debt, and (iii) the relative success of stock market regulation, as opposed to reforms of creditor rights. We conclude that political explanations have more traction in explaining the case of India than do theories based on 'legal origins'.India, Law and Finance, Investor Protection, Economic structure and financial structure