In Soviet Russia, an agricultural directive could pass 30 management levels on its way from the central gov ernment to the farm. Central planning impeded the adaptation of agricultural practices to the local social ecological contexts and virtually eliminated self-accountability in agriculture. Focusing on contemporary Russia, the paper examines how the state currently influences farmers land management and how this subtle mode of intervention aligns with the local context. Qualitative research in the Western Siberian Grain Belt reveals that the state-designed institutions guide land management in a politically desirable direction. They aim for virtually unlimited agricultural growth and largely misalign with the social-ecological conditions of grain farms.
Keywords: Agriculture ، Land management ، Institutions ، Post-Soviet state ، Russia

The fourth industrial revolution leads the manufacturing companies to develop future and smart factories by merging automation and digitalization to result a more efficient production method. An evolutionary and competitive experimental approach is necessary to foster the innovation and the rapid change of the automation and digitalization. Consequently, software becomes an important component of industrial automation. One of the major challenge in Industry 4.0 is to industrialize the production of software. Software factory, as one industry with a virtual production line to produce software for manufacturing companies, offers a form of flexible employment, called as telecommuting work. Although this form brings many benefits for both employee and employers, some risks associated with telecommuting work exist. Monitoring the employee behavior is one of the employer way to see the accountability of the employee. Hence, understanding the human behavior during the production process would be an important issue for fulfilling overall operational excellence in software factory. Among approaches proposed to discover the human behavior based on the sequence activities, process mining is one of which has received attentions lately. While most recent process mining approaches in the domain of human behavior address process discovery and post-analysis, few of them have paid attentions on pre-analysis. The pre-analysis is one of the ways to produce a reliable and high-quality of event log which purposely impacts on discovering a daily common behavior and disregarding irregular sequential behavior. This study aims to propose a new way of pre-analysis using sequential rule mining. The key contributions of this research first, is to determine the potential local behaviors using sequential rule mining considering time constraint. Second, the local behaviors are used to enhance event log for discovering relevant behavior model. Third, the mined model is verified by performing conformance checking approach to check the conformity between the behavior model and the real logs based on three measurements: f-measure, ABA, and DMF. The resulting local behaviors, called as rules, can be used for guiding stakeholders to pinpoint the relevant behavior for human capital and productivity enhancement.
Keywords: Relevant behavior model ، Log filtering ، Process mining ، Sequential rule mining

The cost of higher education (HE) continues to grow at an unsustainable rate in many country contexts, including in East Asia. With recent and projected HE growth in this region, HE administrators are increasingly faced with how best to provide cost-effective delivery while at the same time addressing how to meet workforce demands of increased quality, accountability, and international standards of excellence. In this article, we examine good and best practices of HE finance models in China, Hong Kong, and Taiwan. A primary objective of this article is to highlight a select number of exemplary models of HE financing that can reduce or at least help level off this unsustainable trend. We conclude with recommendations to assist policy makers, government planners, and HE administrators in their attempts to meet the financial challenges of today and in the future.
keywords: China |Hong Kong |Taiwan |Higher Education |Trends |Finance

Technologies such as Internet of Things allow small devices to offer web-based services in an open and dynamic networking environments on a massive scale. End users or service consumers face a hard decision over which service to choose among the available ones, as security holds a key in the decision making process. In this paper a base linguistic evalua tion set is designed, based on which all the other fuzzy term sets that used for describing security attributes are uniformed and integrated for calculating an overall security value of the services. This work, to the best of our knowledge, is the first practical solution to offer direct comparisons and rankings of network services based on multiple security at tributes such as confidentiality, availability, privacy and accountability. We analysed four major cloud service platforms to illustrate the proposed approach.
Keywords: Web service | Security measurement and evaluation | Quantitative service security | Service level agreement | Linguistic evaluation | Multiple attribute decision making

Technologies such as Internet of Things allow small devices to offer web-based services in an open and dynamic networking environments on a massive scale. End users or service consumers face a hard decision over which service to choose among the available ones, as security holds a key in the decision making process. In this paper a base linguistic evalua tion set is designed, based on which all the other fuzzy term sets that used for describing security attributes are uniformed and integrated for calculating an overall security value of the services. This work, to the best of our knowledge, is the first practical solution to offer direct comparisons and rankings of network services based on multiple security at tributes such as confidentiality, availability, privacy and accountability. We analysed four major cloud service platforms to illustrate the proposed approach.
Keywords: Web service | Security measurement and evaluation | Quantitative service security | Service level agreement | Linguistic evaluation | Multiple attribute decision making