计算社会科学与科学决策的未来

计算社会科学的发展为复杂决策带来变革的可能。尽管专家知识和判断仍将是决策的重要依据,但基于客观数据和计算的判断将有可能让决策变得更加科学。计算社会科学有两大技术路径:一是以“模仿”(imitate/mimic)为基础的机器学习与人工智能技术;二是以“模拟”(simulate)为基础的行为体建模(Agent-Based Modeling,ABM)技术。而未来的一个重要方向应该是机器学习与ABM技术的结合。根据计算社会科学的这一特点,研究者需要超越“大数据计算”思维,采取“全数据计算”思维,根据需要解决的不同问题确立不同的数据需求组合,而不是让数据量或者来源来决定研究问题。鉴于计算社会科学对决策的积极作用,中国应在“决策计算社会科学”上有所作为。

SECURE DATA SYNCHRONIZATION EXCHANGE SERVICE APPLICATION PROGRAM INTERFACE BASED ON SyncML PROTOCOL

The security-related problem during the data exchange is not considered in the SyncML protocol. To solve this problem, SyncML is enhanced with a secure data synchronization exchange service application program interface （SDSXS-API） to ensure the reliability, the integrity, and the security in the data transmission and exchange. The design and the implementation of SDSXS-API are also given. The proposed APIs can be conveniently used as a uniform exchange interface for any related application programs. And their effectiveness is verified in the prototype mobile database system.

The design and implementation of web mining in web sites security

The backdoor or information leak of Web servers can be detected by using Web Mining techniques on some abnormal Web log and Web application log data. The security of Web servers can be enhanced and the damage of illegal access can be avoided. Firstly, the system for discovering the patterns of information leakages in CGI scripts from Web log data was proposed. Secondly, those patterns for system administrators to modify their codes and enhance their Web site security were provided. The following aspects were described: one is to combine web application log with web log to extract more information,so web data mining could be used to mine web log for discovering the information that firewall and Information Detection System cannot find. Another approach is to propose an operation module of web site to enhance Web site security. In cluster server session, Density -Based Clustering technique is used to reduce resource cost and obtain better efficiency.

Attribute-Based Access Control Scheme with Efficient Revocation in Cloud Computing

Attribute-based encryption(ABE) supports the fine-grained sharing of encrypted data.In some common designs,attributes are managed by an attribute authority that is supposed to be fully trustworthy.This concept implies that the attribute authority can access all encrypted data,which is known as the key escrow problem.In addition,because all access privileges are defined over a single attribute universe and attributes are shared among multiple data users,the revocation of users is inefficient for the existing ABE scheme.In this paper,we propose a novel scheme that solves the key escrow problem and supports efficient user revocation.First,an access controller is introduced into the existing scheme,and then,secret keys are generated corporately by the attribute authority and access controller.Second,an efficient user revocation mechanism is achieved using a version key that supports forward and backward security.The analysis proves that our scheme is secure and efficient in user authorization and revocation.

Robust digital image watermarking against shearing based on Haar orthogonal function system

In this paper, a robust digital watermarking method against shearing based on Haar orthogonal function system was introduced. The proposed method adopted the complete generalized orthogonal properties of Haar ortbogonal function system to achieve the piece-based orthogonal transform on the image. The significant middle frequency coefficients in the transformation matrix are picked up, based on characteristics of the image visual system and the Haar orthogonal transform. The watermark is adoptively weighed to the middle frequency matrix. The method improves the validity of watermarking and shows excellent advantage against shearing attack. Experimental results show that the Haar orthogonal function system based watermark approach can provide an excellent protection under geometric attacks.

A Retrievable Data Perturbation Method Used in Privacy-Preserving in Cloud Computing

With the increasing popularity of cloud computing,privacy has become one of the key problem in cloud security.When data is outsourced to the cloud,for data owners,they need to ensure the security of their privacy;for cloud service providers,they need some information of the data to provide high QoS services;and for authorized users,they need to access to the true value of data.The existing privacy-preserving methods can't meet all the needs of the three parties at the same time.To address this issue,we propose a retrievable data perturbation method and use it in the privacy-preserving in data outsourcing in cloud computing.Our scheme comes in four steps.Firstly,an improved random generator is proposed to generate an accurate "noise".Next,a perturbation algorithm is introduced to add noise to the original data.By doing this,the privacy information is hidden,but the mean and covariance of data which the service providers may need remain unchanged.Then,a retrieval algorithm is proposed to get the original data back from the perturbed data.Finally,we combine the retrievable perturbation with the access control process to ensure only the authorized users can retrieve the original data.The experiments show that our scheme perturbs date correctly,efficiently,and securely.

Donor safety and remnant liver volume in living donor liver transplantation

AIM:To evaluate the relationship between donor safety and remnant liver volume in right lobe living donor liver transplantation(LDLT).METHODS:From July 2001 to January 2009,our liver transplant centers carried out 197 LDLTs.The clinical data from 151 cases of adult right lobe living donors(not including the middle hepatic vein) were analyzed.The conditions of the three groups of donors were well matched in terms of the studied parameters.The donors' preoperative data,intraoperative and postoperative data were calculated for the three groups:Group 1 remnant liver volume(RLV) < 35%,group 2 RLV 36%-40%,and group 3 RLV > 40%.Comparisons included the different remnant liver volumes on postoperative liver function recovery and the impact of systemic conditions.Correlations between remnant liver volume and post-operative complications were also analyzed.RESULTS:The donors' anthroposomatology data,op-eration time,and preoperative donor blood test indicators were calculated for the three groups.No significant differences were observed between the donors' gender,age,height,weight,and operation time.According to the Chengdu standard liver volume formula,the total liver volume of group 1 was 1072.88 ± 131.06 mL,group 2 was 1043.84 ± 97.11 mL,and group 3 was 1065.33 ± 136.02 mL.The three groups showed no statistically significant differences.When the volume of the remnant liver was less than 35% of the total liver volume,the volume of the remnant had a significant effect on the recovery of liver function and intensive care unit time.In addition,the occurrence of complications was closely related to the remnant liver volume.When the volume of the remnant liver was more than 35% of the total liver volume,the remnant volume change had no significant effect on donor recovery.CONCLUSION:To ensure donor safety,the remnant liver volume should be greater than the standard liver volume(35%) in right lobe living donor liver transplantation.

Data Mining and Visualization of Grid-Based City Emergency System

A cluster analyzing algorithm based on grids is introduced in this paper,which is applied to data mining in the city emergency system. In the previous applications, data mining was based on the method of analyzing points and lines, which was not efficient enough in dealing with the geographic information in units of police areas. The proposed algorithm maps an event set stored as a point set to a grid unit set, utilizes the cluster algorithm based on grids to find out all the clusters, and shows the results in the method of visualization. The algorithm performs well when dealing with high dimensional data sets and immense data. It is suitable for the data mining based on geogra-(phic) information system and is supportive to decision-makings in the city emergency system.

Analyzing inspection results of Port State Control by using PCA

The paper applied Principal Components Analysis Method to analyze the PSC inspection results in the area of T-MOU and P-MOU. Set up the assessment of ship detention, the ships＇ main deficiencies of detentions were found out by the standardization of data processing and correlation matrix calculating. Provide the basis for shipping company to master the safety management focus and pass the PSC inspection.

Research on the Office Automation System Development and Practice based on Database Optimization and Security Enhancement Technology

In the paper, we conduct research on the office automation system development and practice based on database optimization and security enhancement technology. Office automation is with the rapid development of computer technology and puts forward a new concept, the abbreviation for OA, refers to the enterprise through the use of advanced science and technology, the allocation of the information resources in a reasonable manner, so as to improve the work efficiency and quality of staff, auxiliary management to make decisions, to obtain more economic benefits and main including images, text, audio, data and other information collection, and processing and storage. Among them, the office automation is based on the staff as the main body, with advanced scientific technology by combining with computer technology and form comprehensive office mode. Our proposed method serves as the novel paradigm for the development of the office automation which is meaningful.