中关村科学城院校企第二次项目对接会举办

2011年11月18日,中关村创新平台举办中关村科学城院校企第二次项目对接会。此次对接会是继10月18日《中关村科学城发展规划》发布后的又一重要举措。旨在进一步推动高校、科研院所、企业、高端人才、     

中关村人才特区举办HR沙龙活动

2012年3月22日，由中关村管委会支持、中关村人力资源经理协会承办的公益活动“2012中关村人才特区HR沙龙”在翠宫饭店举行。参加发布会的有中关村创新平台人才工作组、人才特区部分重点企业及留学生创办企业代表、中关村人力资源协会等。博奥生物人力资源总监陈江、新东方人力资源总监张如国等做了重点发言。中关村管委会人才处处长李志磊对沙龙提出了期望。     

中关村：谋局知识产权竞争新主场

《中关村国家自主创新示范区发展规划纲要（2011—2020）》提出，将中关村建设成国家知识产权制度示范园这将推进首都知识产权战略进一步向纵深发展。     

园区信息

中关村核心区力争2020年总收入达4万亿Z-Park Core Zone Works Hard for Exceeding 4 Trillions Gross Incomes by 20205月29日,中关村国家自主创新示范区核心区建设大会召开,北京市海淀区对外发布了《中关村国家自主创新示范区核心区发展规划纲要（2011-2020年）》、《中关村国家自主创新示范区核心区＂十二五＂发展规划》等五个核心区建设相关规划。根据核心区发展目标,到2020年,核心区力争实现总收入4万亿元,     

寄语艺术中关村

《中关村》办“艺术中关村”，好!于友先（中国出版工作者协会主席、国家新闻出版署原署长、全国政协教科文体委员会副主任）我与《中关村》杂志结缘有六个年头了。令我高兴的是创刊之初拟定的办刊宗旨“新经济、新技术、新文化”，至今仍然富有新意，成为时代的主旋律。这些年来，因为工作之需，     

中关村视线

国务院批复中关村十年规划凸显"创新"、"示范"日前,国务院批复的《中关村国家自主创新示范区发展规划纲要(2011-2020年)》,凸显"创新"和"示范"。批复强调:"中关村国家自主创新示范区要坚持以提高自主创新能力为核心,以深化     

中关村科学城打造“聚焦品牌”

市场条件下，聚焦战略往往成为企业最强有力的竞争武器!同样．产业聚集也能够成为一个区域的竞争优势!2010年9月2日上午，国家首个产业集群基地一中关村科学城首批规划项目正式启动。     

中关村营造创新创业环境的实践与思考

20年来，特别是成为国家自主创新示范区以来，中关村科技园区在营造创新创业环境上，进行了诸多卓有成效的探索。搭建创新平台，这个平台首次实现了中央和地方的资源整合、政策聚焦和工作统筹，实现了制度设计的突破性进展。平台下面设置了八个工作组，有19个国家部委的37名司局长和处长在平台上办公，     

落实《人才规划》是中关村永续发展的核心竞争力

时代呼唤人才,人才造就伟业。在方兴未艾的知识经济时代，人才是我国经济发展的“第一资源”．也是“一个国家的核心竞争力”。日前，党中央、国务院颁布的《人才规划》是我国昂首迈进世界人才强国的行动纲领。中关村的成长历史和实践印证了《人才规划》的科学性、战略性、前瞻性和可操作性。党和国家制定实旌《人才规划》．既是立足国内发展需要采取的重大措施．也是在激烈的国际竞争中赢得主动的战略选择。     

中关村情思(七律四首)

科技园区科技高端硅谷城，前沿学术五洲通。研发一体申专利，孵化千家展大鹏。叶茂梧桐招凤驻，商繁市场引龙腾。中关村里多奇迹，印在京华名片中。科研院所名牌院校聚群英，崇尚科学百世宗。月色荷塘追梦想，湖光塔影入思情。遥天莫叹蟾宫远，今日犹当学术精。只待长空持彩练，神州无处不飞虹！创新平台中关村里筑平台，改革扶持门户开。     

Contributions of Econometrics to Public Policy Analysis in the Information Age

In this paper we model U.S. economic growth over the next 25 years. Despite the anticipated aging of the population, moderate population growth will provide growing supplies of labor well into the 21st century. Improvements in labor quality due to education and experience will also continue for some time, but will eventually disappear. Productivity growth for the U.S. economy will be below long-term historical averages, but labor-using technical change will be a stimulus for growth of labor demand. Year-to-year changes in economic activity will be primarily the consequence of capital accumulation. However, the driving forces of economic growth over the long term will be demography and technology. This is a revised version of the keynote speech that I delivered on 16 January 2009 at the 6th International Conference of Socionetwork Strategies, at Kansai University, Japan.     

Impact of Online Customer Reviews on Sales Outcomes: An Empirical Study Based on Prospect Theory

This study examines the influence of the valence of online customer reviews on sales outcomes based on prospect theory. Numerous studies have revealed the importance of customer reviews in online marketing. However, only few studies have explored the impact of online customer reviews on sales outcomes in the dynamic process. Prior studies in behavioral economics literature have indicated that people differently value gains and losses and that losses have more emotional impact than an equivalent amount of gains. This study verifies whether prospect theory applies to the relation between online customer reviews and sales outcomes. Relevant data were collected from Amazon.co.jp, and three statistical models were employed to investigate the relation between the two factors. Major findings confirm that negative customer reviews considerably impact online sales than positive reviews. Furthermore, the findings indicate that the marginal effects of positive and negative reviews decrease with the increase in their volume. The results of this study will enable marketers to compare the relative sales effects of different types of customer reviews and improve the effectiveness of customer service management.     

Facebook e-Portfolios for Career Education Focused on Japanese Employment Practice: A Case Study

The authors propose the effectiveness of Facebook functions in the promotion of career education. In recent years, career education in Japanese universities has differed slightly from that in other countries. Japanese students are trained to be competitive in the job-hunting process; they need to obtain the technical skills and knowledge necessary to pass a company entrance examination or a university oral interview. This practice is in stark contrast with the intrinsic meaning of vocational/career education, which is the process by which students acquire the abilities and independence required by a certain industry. This meaning is manifested in the purpose of the career education program of Hokkai-Gakuen University’s Faculty of Business Administration. The program’s purpose is to foster independence in its students rather than the acquisition of skills for the job-hunting process. The professional independence of every student is important to their career development after graduating from the university. On the other hand, it is known that e-portfolios generally encourage students to record and assess their activities. To promote the activities that students tackle in the program, we introduced an e-portfolio using Facebook. This study shows the characteristics and achievements of our e-portfolio.     

Prediction Model for Bollywood Movie Success: A Comparative Analysis of Performance of Supervised Machine Learning Algorithms

The main purpose of this paper is to do a comparative analysis of prediction models using various machine learning techniques. The models will be used to predict whether a movie will be a hit or flop before it is actually released. The techniques used for comparisons are decision tree, random forest (RF), support vector machine, logistics regression, adaptive tree boosting, and artificial neural network algorithms. The major predictors used in the models are the ratings of the lead actor, IMDb ranking of a movie, music rank of the movie, and total number of screens planned for the release of a movie. The results of most models indicated a reasonable accuracy, ranging from 80 to 90%. However, models based on two techniques, RF and logistic regression, achieved an accuracy of 92%. From the results, the most important predictors of a movie’s success are music rating, followed by its IMDb rating and total screens used for release.

     

Graph-Based Entropy for Detecting Explanatory Signs of Changes in Market

Graph-based entropy, an index of the diversity of events in their distribution to parts of a co-occurrence graph, is proposed for detecting signs of structural changes in the data that are informative in explaining latent dynamics of consumers’ behavior. For obtaining graph-based entropy, connected sub-graphs are first obtained from the graph of co-occurrences of items in the data. Then, the distribution of items occurring in events in the data to these sub-graphs is reflected on the value of graph-based entropy. For the data on the position of sale, a change in this value is regarded as a sign of the appearance, the separation, the disappearance, or the uniting of consumers’ interests. These phenomena are regarded as the signs of dynamic changes in consumers’ behavior that may be the effects of external events and information. Experiments show that graph-based entropy outperforms baseline methods that can be used for change detection, in explaining substantial changes and their signs in consumers’ preference of items in supermarket stores.     

BLOCKS: Efficient and Stable Online Visualization of Dynamic Network Evolution

It is computationally and cognitively expensive to observe the evolution of community structure on dynamic networks in real-time, not only because the data sets tend to be complex, but also because the visual interfaces are often complicated. We introduce BLOCKS, a simple but efficient framework to abstract and visualize the evolution of community structure on dynamic networks. Instead of indicating detailed changes of nodes and links temporally, BLOCKS regards communities as visual entities and focuses on representing their behaviors and relation changes on a time series. Experiments detected a stable performance of BLOCKS compared with previous methods while detecting the community structure of networks. We also present a case study that shows an effective learning process of network evolution with BLOCKS.     

An Approach to Security for Unstructured Big Data

Security of Big Data is a huge concern. In a broad sense, Big Data contains two types of data: structured and unstructured. Providing security to unstructured data is more difficult than providing security to structured data. In this paper, we have developed an approach to provide adequate security to unstructured data by considering types of data and their sensitivity levels. We have reviewed the different analytics methods of Big Data to build nodes of different types of data. Each type of data has been classified to provide adequate security and enhance the overhead of the security system. To provide security to a data node, and a security suite has been designed by incorporating different security algorithms. Those security algorithms collectively form a security suite which has been interfaced with the data node. Information on data sensitivity has been collected through a survey. We have shown through several experiments on multiple computer systems with varied configurations that data classification with respect to sensitivity levels enhances the performance of the system. The experimental results show how and in what amount the designed security suite reduces overhead and increases security simultaneously.     

The Future of Socionetwork Strategies

In the first stage of creating technological improvements for a democratic society, the leaders of the Society of Socionetwork Strategies have conducted statistical research on the effect of information and communication technology on the global economy. In the second stage, younger professors, based on their Positive Studies, have leapt into a multi-agent simulation of Grid Computing. In the third stage, a terra-bite scale of social data-collecting and the mining of large-scale data in our real world will be next. The next generation of scientists will share knowledge and intellectual inquiry in the fields of statistics, mathematics, and the social sciences with the help of computers connecting such scholars from all over the world.     

Simulation Analysis of a Dynamic Reallocation-based Routing Functionality for SAGE Application

A large amount of scientific data is generated through computation and analysis. Also, today’s scientific research necessitates an aggregation of diverse expertise from experts with different backgrounds. Therefore, visualizing and sharing these data among scientists in an intuitive and easy manner is of more importance in scientific collaborative research than ever. We have focused on SAGE, a middleware that realizes a large-scale remote visualization leveraging network streaming technique as a promising building block technology. However, no advanced network control function for efficient use of the network is equipped with SAGE although SAGE relies on a network streaming techniques. Our previous research integrated a functionality that detected network failures avoided such failure by rerouting network flows of SAGE into the functionality. Nonetheless, a network congestion avoidance functionality to adapt a collection of network flows generated by SAGE to the underlying network has not been developed yet. In this paper we explore the feasibility of a reallocation-based dynamic routing functionality for SAGE, with which all network flows on the network are rearranged. For feasibility research, we perform simulation experiments to observe the behavior of the functionality. The evaluation confirms that our proposed functionality works correctly and brings better throughput for each flow.     

Are Depositors Aware of the Governance of their Banks?1

In the discussion of corporate governance from the standpoint of economists, it is common for economists to pay more attention to the stockholders of a corporation (as stakeholders) than to the creditors. However, the behaviors of depositors as creditors should not be neglected in the management of banking institutions. The purpose of this paper is to analyze statistically the decision factors of depositors in opening an account at a particular bank with respect to corporate governance variables. My result shows that depositors with risk aversion consider banks well managed based on the following: a lower rate of external auditors, a longer time of service by the bank’s president, and the existence of a simultaneous promotion system of the bank’s president and chairperson.