Outsourcing Decision Model of Sewage Treatment Based on Emissions Trading

This paper considers the professional treatment manufacturers to participate in emissions trading under the condition of the emissions trading which establish the supply chain between the manufacturers and the providers of professional sewage treatment. By using the strategy analysis method, under the certain conditions this study analyze the difference of the outsourcing decisions on the treatment price fluctuating. This study also conclude that the expected return of the supply chain on the strategy of all manufacturers choose to outsourcing the sewage treatment is less than the expected return on the integration supply chain strategy. Also, this research documents the existence of the supply chain. The conclusions of this paper contribute to the establishment of emissions trading under the conditions of wastewater treatment supply chain and future contributing to the sewage treatment industry with the application.Key words: Emission trading; Outsourcing decision; Sewage treatmen

Formal metrics for quantitative assessment of the quality of expert systems

Investigates several new tools for measuring complexity of expert systems. Most effective was RC (Rule-based complexity) metric, a hybrid metric that takes into account the matching patterns, size and search space af expert systems

Immunomodulatory properties of polysaccharide-protein complex from lycium barbarum L.

Ph.DDOCTOR OF PHILOSOPH

Anchoring countercyclical capital buffer in Basel III

This thesis proposes two top-down approch frameworks to assess the Basel III countercyclical capital buffer. The empirical results demonstrate that sovereign sector distance-to-default and market illiquidity are more suitable indicator for guiding the decision of the buffer during both build-up and release phase than the official indicator, credit-to-GDP ratio. The findings in this thesis are important to help safeguard the globe financial system

A DNS Tunnel Sliding Window Differential Detection Method Based on Normal Distribution Reasonable Range Filtering

A covert attack method often used by APT organizations is the DNS tunnel, which is used to pass information by constructing C2 networks. And they often use the method of frequently changing domain names and server IP addresses to evade monitoring, which makes it extremely difficult to detect them. However, they carry DNS tunnel information traffic in normal DNS communication, which inevitably brings anomalies in some statistical characteristics of DNS traffic, so that it would provide security personnel with the opportunity to find them. Based on the above considerations, this paper studies the statistical discovery methodology of typical DNS tunnel high-frequency query behavior. Firstly, we analyze the distribution of the DNS domain name length and times and finds that the DNS domain name length and times follow the normal distribution law. Secondly, based on this distribution law, we propose a method for detecting and discovering high-frequency DNS query behaviors of non-single domain names based on the statistical rules of domain name length and frequency and we also give three theorems as theoretical support. Thirdly, we design a sliding window difference scheme based on the above method. Experimental results show that our method has a higher detection rate. At the same time, since our method does not need to construct a data set, it has better practicability in detecting unknown DNS tunnels. This also shows that our detection method based on mathematical models can effectively avoid the dilemma for machine learning methods that must have useful training data sets, and has strong practical significance