Behavioral Feature and Correlative Detection of Multiple Types of Node in the Internet of Vehicles

Undoubtedly,uncooperative or malicious nodes threaten the safety of Internet of Vehicles(IoV)by destroying routing or data.To this end,some researchers have designed some node detection mechanisms and trust calculating algorithms based on some different feature parameters of IoV such as communication,data,energy,etc.,to detect and evaluate vehicle nodes.However,it is difficult to effectively assess the trust level of a vehicle node only by message forwarding,data consistency,and energy sufficiency.In order to resolve these problems,a novel mechanism and a new trust calculating model is proposed in this paper.First,the four tuple method is adopted,to qualitatively describing various types of nodes of IoV;Second,analyzing the behavioral features and correlation of various nodes based on route forwarding rate,data forwarding rate and physical location;third,designing double layer detection feature parameters with the ability to detect uncooperative nodes and malicious nodes;fourth,establishing a node correlative detection model with a double layer structure by combining the network layer and the perception layer.Accordingly,we conducted simulation experiments to verify the accuracy and time of this detection method under different speed-rate topological conditions of IoV.The results show that comparing with methods which only considers energy or communication parameters,the method proposed in this paper has obvious advantages in the detection of uncooperative and malicious nodes of IoV;especially,with the double detection feature parameters and node correlative detection model combined,detection accuracy is effectively improved,and the calculation time of node detection is largely reduced.

Bioautography and its scope in the field of natural product chemistry

Medicinal plants, vegetables and fruits are the sources of huge number of bioactive lead/scaffolds with therapeutic and nutraceutical importance. Bioautography is a means of target-directed isolation of active molecules on chromatogram. Organic solvents employed in chromatographic separation process can be completely removed before biological detection because these solvents cause inactivation of enzymes and/or death of living organisms. They offer a rapid and easy identification of bioactive lead/scaffolds in complex matrices of plant extracts. Bioautography is a technique to isolate hit（s）/lead（s） by employing a suitable chromatographic process followed by a biological detection system. This review critically describes the methodologies to identify antimicrobial, antioxidant, enzyme inhibitor lead/scaffolds by employing bioautography. A significant number of examples have been incorporated to authenticate the methodologies.

Self-similar segmentation and multifractality of post-stack seismic data

Layering detection is an important step in petroleum engineering.Time series of post-stack seismic data and wire-line log data belong to subsurface layering.They exhibit multifractal properties with complex patterns because of the heterogeneity and different genetic properties in the earth layers.In a multifractal configuration,any piece of a series has a distinct Hurst exponent that reflects its nature and can be used for zone detection.Time series are post-stack seismic traces and wire-line log data near the well-bores.Self-similar Autoregressive Exogenous(SAE)model is a modified method which can place self-similar post-stack seismic and wire-line log segments across layers with the same lithology.The results satisfy the capability of layering identification from seismic data by SAE model.

Interaction of straight chain alcohol vapors with self-assembled MOF film by surface plasmon resonance sensing and imaging

Interaction of straight chain alcohol vapors with MOF-199-functionalized films was studied by SPR. The signals had linear relationships with the concentration of alcohols over a wide range from 0 to 70% （v/v） and were reversible in proportional to the chain length, with R2 all above 0.99.