Search Results (4)

In the e-commerce environment, it is very common for consumers to select goods or services based on online reviews from social platforms. However, the behavior of some unscrupulous merchants who hire a “water army” to brush up on reviews of their products has been continuously exposed, which seriously misleads consumers’ purchasing decisions and undermines consumer trust. Until now, it has been a challenging task to accurately detect the “water army”, who could easily alter their behaviors or writing styles. The focus of this paper is on some collusive clues between members of the same social platform to propose a new graph model to detect the “water army”. First is the extraction of six kinds of user collusive relationships from two aspects: user content and user behavior. Further, the use of three aggregation methods on such collusive relationships generates a user collusive relationship factor (CRF), which is then used as the edge weight value in our graph-based water army detection model. In the combination of the graph grouping method and evaluation rules on candidate subgraphs, the graph model effectively detects multiple collusive groups automatically. The experimental results based on the Mafengwo platform show that the CRF generated from the coefficient of variation (CV) method demonstrates the best performance in detecting collusive groups, which provides some practical reference for the detection of “water armies” in an e-commerce environment. Full article

Fully polarimetric Synthetic Aperture Radar (polSAR) data analysis has wide applications for terrain and ground cover classification. The dynamics of surface and subsurface water events can lead to slope instability resulting in slough slides on earthen levees. Early detection of these anomalies by a remote sensing approach could save time versus direct assessment. We used L-band Synthetic Aperture Radar (SAR) to screen levees for anomalies. SAR technology, due to its high spatial resolution and soil penetration capability, is a good choice for identifying problematic areas on earthen levees. Using the parameters entropy (H), anisotropy (A), alpha (α), and eigenvalues (λ, λ₁, λ₂, and λ₃), we implemented several unsupervised classification algorithms for the identification of anomalies on the levee. The classification techniques applied are H/α, H/A, A/α, Wishart H/α, Wishart H/A/α, and H/α/λ classification algorithms. In this work, the effectiveness of the algorithms was demonstrated using quad-polarimetric L-band SAR imagery from the NASA Jet Propulsion Laboratory’s (JPL’s) Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR). The study area is a section of the lower Mississippi River valley in the Southern USA, where earthen flood control levees are maintained by the US Army Corps of Engineers. Full article

The Juvenile Salmon Acoustic Telemetry System (JSATS) is an active sensing technology developed by the U.S. Army Corps of Engineers, Portland District, for detecting and tracking small fish. It is used primarily for evaluating behavior and survival of juvenile salmonids migrating through the Federal Columbia River Power System to the Pacific Ocean. It provides critical data for salmon protection and development of more “fish-friendly” hydroelectric facilities. The objective of this study was to design and build a Measurement and Calibration System (MCS) for evaluating the JSATS components, because the JSATS requires comprehensive acceptance and performance testing in a controlled environment before it is deployed in the field. The MCS consists of a reference transducer, a water test tank lined with anechoic material, a motion control unit, a reference receiver, a signal conditioner and amplifier unit, a data acquisition board, MATLAB control and analysis interface, and a computer. The fully integrated MCS has been evaluated successfully at various simulated distances and using different encoded signals at frequencies within the bandwidth of the JSATS transmitter. The MCS provides accurate acoustic mapping capability in a controlled environment and automates the process that allows real-time measurements and evaluation of the piezoelectric transducers, sensors, or the acoustic fields. The MCS has been in use since 2009 for acceptance and performance testing of, and further improvements to, the JSATS. Full article

Phytoremediation is a technology that uses vegetation to remediate contaminants from water, soil, and sediments. Unlike traditional remediation techniques such as soil washing or vitrification, phytoremediation offers a technology that is solar-driven, aesthetically pleasing, and cost effective. Recent studies indicate that winter wheat (Triticum aestivum L.) is a potential accumulator for heavy metals such as lead (Pb) and cadmium (Cd) in hydroponic systems. Based on these findings, a laboratory study was conducted with the primary objective of determining the phytoaccumulation capability of this plant species for heavy metals from contaminated dredged materials (DMs) originating from two confined disposal facilities (CDF). The United States Army Corps of Engineers (USACE) manages several hundred million cubic meters of DMs each year, and 5 to 10 % of these DMs require special handling because they are contaminated with hazardous substances that can move from the substrates into food webs causing unacceptable risk outside CDFs. Phytoremediation may offer an alternative to decrease this risk. Chemical analyses by USACE personnel identified 17 metals in various DMs, but in this present study, only zinc (Zn) and Cd were investigated. Pre-germinated seeds of the test plants were planted under laboratory conditions in pots containing the various DMs and reference soil. Four weeks after planting, plants were harvested and separated into roots and shoots for biomass production and tissue metal concentrations analyses. Results showed that T. aestivum plants have the capacity to tolerate and grow in multiple-metal contaminated DMs with the potential of accumulating various amounts of Zn and Cd. Root and shoot biomass of T. aestivum were not significantly affected by the DMs on which the plants were grown suggesting that this plant species can grow just as well on DMs contaminated by various metals as in the reference soil. No significant differences in the Zn tissue concentrations were observed, differences in Cd tissue concentrations were noted. A maximum concentration of 26 mg Cd kg^-1 DW was detected in T. aestivum shoots. Although Cd tissue concentrations of T. aestivum plants in this study were below the Cd plant hyperaccumulation criterion of >100 mg kg^-1 Cd found in other studies, this plant species however may still have beneficial uses for phytoremediation studies. T. aestivum plants may serve as an indicator plant for environmental assessment and management, in which the concentration of heavy metals (e.g. Cd) mirrors the concentration in the substrate without dying due to phytotoxicity at low metal concentrations. Full article