How Infrastructure Construction Reduces Market Segregation in China:Achievements and Problems

Theoretically, infrastructure construction helps remove domestic market segregation and thus create a modern market system. Based on the theory of new economy geography, this paper investigates the relationship between infrastructure construction and market segregation using the Spatial Panel Dubin Model(SPDM) based on China's interprovincial panel data of 1993-2012. As shown by empirical result, the beggar-thyneighbor problem existed persistently within China, infrastructure construction helped remove market segregation and should be enhanced, infrastructure construction had heterogeneous spatial spillover effects across periods, and market segregation behaviors were heterogeneous across regions or localities. China should enhance infrastructure to narrow regional gaps and step up cooperation among investors across regions to reduce the adverse impact of geographical boundary, and create modern service-based local governments, allowing the market to play a decisive role in resource allocation.

A Strategy to Strengthen the US Economy

For decades, the United States＇ competitive position in global manufacturing has steadily declined. Analysts point to increasingly automated manufacturing processes, changing domestic demand factors, outsourcing, and over confidence in service export surplnses. However, Asian and European competitors, undergoing the same pressures, have been able to maintain a healthy percentage of their GDP in manufacturing by growing high techjobs while the United States continues to fall behind, Perhaps the most flmdamental and overlooked contribution to this decline is the lackluster performance of the United States education system. After comparing the performance of US students to that of the other G-8 nations in the critical disciplines of math and science literacy, US students rank last. Furthermore, the most recent PISA test results show US students rank in the bottom half of 30 participating nations in the ability to apply math and science concepts to real world problems. This is particularly troubling when one considers that among the compared nations, the US spends the most on math and science teacher compensation. If the US intends to successfully compete in the global manufacturing arena, significant changes to the education system must be enacted. A new strategy aligning the system with real world demands should begin with a national initiative to increase Pre-K enrollments, a paradigm shift from liberal arts to math, science, problem solving and critical thinking, standardized policies aligning high school graduation requirements with college and work place expectations, and standardized college and career readiness assessment programs. These steps combined with more rigorous secondary education teacher certifications, continued education and involvement with universities and manufacturing f＇mns within the community, should more adeq^tely prepare high school students for further study or to enter the skilled workforce. At the post secondary level, federal and state funding should be targeted to R＆D programs specificly to industrial design, engineering, and alternative energy. Industry investment in such programs should be federally incentivized to foster cooperative relationships between business and academia. Such relationships will ensure faculty spend time focusing on how their discipline relates to manufacturing and instilling the necessary skill sets, knowledge and abilities which graduates will need to compete in the global market. Such a revised system will position the US to create and keep high paying manufacturing positions on its way to sustainable economic growth.

New Approach to the Flexible Planning of Learning Process in High Education System

Expediency of this work is conditioned by the inconsistency between the market requirement of the specialists and the planning process of high educational system. For solving this problem it is important to make consulting or expect system for flexible planning of teaching modules of every specialty. We make an attempt to consider this problem in two aspects： the prediction of market demand for planning taking into consideration of studies duration and scheduling of educational process. The prediction task consists in data acquisition of market requirement for each profession in discrete time interval to predict dynamic evolution of every specialty. The solution of the prediction task will be using to determination of prognostic quantity of students for each specialty. As regards the second aspect, it consists in finding a schedule of the teaching modules, i.e. the distribution of subjects in the semesters, keeping the total limits of credits, to update and adapt syllabus. In this paper, we present a genetic algorithm as a solution method for the modular scheduling problem. Genetic algorithms （GAs） allow a more general approach to the scheduling problem, which is rated using a fitness function. GA can be successfully applied to find optimized sequential schedules.