Recognition of Odor Characteristics Based on BP Neural Network

This paper introduces the basic principle and calculation steps of BP neural network algorithm for classification and prediction of odor characteristic parameters. Using the PEN3 electronic nose collects the volatile components of milk and programming BP neural network algorithm under MATLAB condition. This paper validate the use of BP neural network algorithm on milk quality prediction is effective

Examining Individuals’ Ads Click Intention in the Wechat Moments: A Lens of Elaboration Likelihood Model

Drawing upon elaboration likelihood model (ELM), we compared the dual routesin determining users’ ads click intentions and examined the mediation mechanism of cognitive vs. affective trust on the influence processesin the Wechat Moments. A scenario-based survey was conducted in a university of China, and 183 data was collected. Structural equation modelling analysis was used to test the research model. The empirical results suggestedthat content personalization and social recommendation weresignificant antecedents of ads click intention, and their effects weremediated by cognitive trust and affective trust. Moreover, amulti-group analysis indicatedthat the two influence processes weremoderated by prior product experience. Theoretical and practical implications areillustrated in the final section

IEEE Access Special Section Editorial: Big Data Technology and Applications in Intelligent Transportation

During the last few years, information technology and transportation industries, along with automotive manufacturers and academia, are focusing on leveraging intelligent transportation systems (ITS) to improve services related to driver experience, connected cars, Internet data plans for vehicles, traffic infrastructure, urban transportation systems, traffic collaborative management, road traffic accidents analysis, road traffic flow prediction, public transportation service plan, personal travel route plans, and the development of an effective ecosystem for vehicles, drivers, traffic controllers, city planners, and transportation applications. Moreover, the emerging technologies of the Internet of Things (IoT) and cloud computing have provided unprecedented opportunities for the development and realization of innovative intelligent transportation systems where sensors and mobile devices can gather information and cloud computing, allowing knowledge discovery, information sharing, and supported decision making. However, the development of such data-driven ITS requires the integration, processing, and analysis of plentiful information obtained from millions of vehicles, traffic infrastructures, smartphones, and other collaborative systems like weather stations and road safety and early warning systems. The huge amount of data generated by ITS devices is only of value if utilized in data analytics for decision-making such as accident prevention and detection, controlling road risks, reducing traffic carbon emissions, and other applications which bring big data analytics into the picture

Visibility Video Detection with Dark Channel Prior on Highway

Dark channel prior (DCP) has advantages in image enhancement and image haze removal and is explored to detect highway visibility according to the physical relationship between transmittance and extinction coefficient. However, there are three major error sources in calculating transmittance. The first is that sky regions do not satisfy the assumptions of DCP algorithm. So the optimization algorithms combined with region growing and coefficient correction method are proposed. When extracting atmospheric brightness, different values lead to the second error. Therefore, according to different visibility conditions, a multimode classification method is designed. Image blocky effect causes the third error. Then guided image filtering is introduced to obtain accurate transmittance of each pixel of image. Next, according to the definition meteorological optical visual range and the relationship between transmittance and extinction coefficient of Lambert-Beer’s Law, accurate visibility value can be calculated. A comparative experimental system including visibility detector and video camera was set up to verify the accuracy of these optimization algorithms. Finally, a large number of highway section videos were selected to test the validity of DCP method in different models. The results indicate that these detection visibility methods are feasible and reliable for the smooth operation of highways

An Analysis of Relationship among Income Inequality, Poverty, and Income Mobility, Based on Distribution Functions

Many studies show that the relationship among income inequality, poverty, and income mobility needs to be further discussed. Meanwhile, some researches on Distribution Function offer new perspective and methods to analyze this issue. First, this paper expresses the relationship among the Gini coefficient, poverty ratio, and income mobility of 5 common Distribution Functions through math deduction; this finding cannot be found in relevant literatures. Furthermore, an empirical research result proves that the income distribution of urban residents in the period from 2005 to 2010 fits Log-Logistic Distribution. On the basis of the above analysis and empirical data, the paper explores the relations of income inequality, poverty, and income mobility of urban residents and draws some useful conclusions