Abstract The direct-drive pump control system has been gradually applied to the industrial control field due to its high control precision, fast response, small throttle loss and compact structure. This paper adopts the fuzzy PID control method to resolve the hydraulic cylinder position servo control of direct-drive pump control system. The system model and fuzzy PID control algorithm was established by... The direct-drive pump control system has been gradually applied to the industrial control field due to its high control precision, fast response, small throttle loss and compact structure. This paper adopts the fuzzy PID control method to resolve the hydraulic cylinder position servo control of direct-drive pump control system. The system model and fuzzy PID control algorithm was established by using AMEsim/Simulink joint simulation platform. The step response and Sine tracking performance of the system with PID and fuzzy PID control algorithms was investigated by simulation. At the same time, the performance of PID and fuzzy PID control was studied on the self-developed electro-hydraulic servo control experiment table. The results show that the adaptive fuzzy PID control can greatly improve the performance of the PID control, and has the characteristics of fast response, short rise time, small time delay and overshoot. Read More Read Less

Abstract With emphasizing the process of innovation, this paper classifies government intervention focused on innovation adoption into three dimensionalities: information support, financial support and personnel support. It also refines technological cognition into two aspects: perceived benefits including functional benefits and social benefits, and perceived costs including financial cost and risk. This paper develops an information technology adoption model of logistic enterprise... With emphasizing the process of innovation, this paper classifies government intervention focused on innovation adoption into three dimensionalities: information support, financial support and personnel support. It also refines technological cognition into two aspects: perceived benefits including functional benefits and social benefits, and perceived costs including financial cost and risk. This paper develops an information technology adoption model of logistic enterprise for the context of government intervention, which based on the technology adoption theories of behavior perspective and follows the corresponding basic principle that government intervention affects adoption intention indirectly via technological cognition. Then, the study takes standard TMS and investigates some logistic enterprises in Zhejiang province to conduct empirical research. With collected 113 valid data, the author tests the model by regression analysis. The results demonstrate that adoption intention is affected by government intervention through technological cognition, and reveals the path in which different kinds of government intervention affect technological cognition. Read More Read Less

Abstract Along with the advance of scientific powers strategic of our country, all types and levels funding limit and quantity of college scientific research project have also increased constantly. It is very important to have complete, accurate and fair evaluations for university scientific research project management performance. Fuzzy analytic hierarchy process (FAHP) as a qualitative, a quantitative and comprehensive evaluation method... Along with the advance of scientific powers strategic of our country, all types and levels funding limit and quantity of college scientific research project have also increased constantly. It is very important to have complete, accurate and fair evaluations for university scientific research project management performance. Fuzzy analytic hierarchy process (FAHP) as a qualitative, a quantitative and comprehensive evaluation method can be able to evaluate the university scientific research project management performance effectively. Read More Read Less

Abstract In the increasingly serious environment of employment of college students, the college student credit evaluation model taking into account of the basic personal situation, on-campus situation and economic situation is employed in this paper for the purpose of improving the quality of college student credit education more efficiently, and in addition, a college student credit prediction mechanism based on the... In the increasingly serious environment of employment of college students, the college student credit evaluation model taking into account of the basic personal situation, on-campus situation and economic situation is employed in this paper for the purpose of improving the quality of college student credit education more efficiently, and in addition, a college student credit prediction mechanism based on the improved RF algorithm is put forward, seen from the test result, the accuracy of college student credit prediction of the algorithm is relatively high, and capable to make student credit education more targeted. Read More Read Less

Abstract Graph-based Fisher Analysis (GbFA) is proposed recently for dimensionality reduction, which has the powerful discriminant ability. However, GbFA is based on the matrix-to-vector way, which not only costs much but also loses spatial relations of pixels in images. Therefore, Tensor Graph-based Linear Discriminant Analysis (TGbLDA) is proposed in the paper. TGbLDA regards samples as data in tensor space and gets... Graph-based Fisher Analysis (GbFA) is proposed recently for dimensionality reduction, which has the powerful discriminant ability. However, GbFA is based on the matrix-to-vector way, which not only costs much but also loses spatial relations of pixels in images. Therefore, Tensor Graph-based Linear Discriminant Analysis (TGbLDA) is proposed in the paper. TGbLDA regards samples as data in tensor space and gets projection matrixes through the iteration way. Besides, TGbLDA inherits merits of GbFA. Experiments on Yale and YaleB face datasets demonstrate the effectiveness of our proposed algorithm. Read More Read Less

Abstract The rule conflict is an important issue for associative classification due to a large set of rules. In this paper, a new approach called Associative Classification with Bayes (AC-Bayes) is proposed. To address rule conflicts, AC-Bayes has two distinguished features: (1) Associative classification is improved. (2) Naïve Bayesian model is applied in process of classification. A small set of high... The rule conflict is an important issue for associative classification due to a large set of rules. In this paper, a new approach called Associative Classification with Bayes (AC-Bayes) is proposed. To address rule conflicts, AC-Bayes has two distinguished features: (1) Associative classification is improved. (2) Naïve Bayesian model is applied in process of classification. A small set of high quality rules is generated by discovering not only frequent but mutual associated itemsets. Therefore, it will reduce the opportunities of rule conflicts. AC-Bayes also selects the best n rules to predict the class value of new instances. When rule conflicts are occurred, we collect those instances covered by these matched rules to form a new training set. Then, it scans new training set to compute the posterior probabilities of each class conditioned on the test instance. The class value that maximizes the posterior probability is assigned to the test instance. The experiments results show that the improved associative classification decreases significantly the number of rules and AC-Bayes has better average classification accuracy in comparison with associative classification and Naïve Bayesian classification. Read More Read Less

Abstract Today, micropayment systems usage is highly topical. For example, applications of mobile micropayment systems are widely used and are well known by the public.The objective of this study was to implement a micropayment system pilot based on an interoperability enabling platform (in this case, Smart-M3) for small businesses with restricted resources, scarce labor force, and a growing number of products... Today, micropayment systems usage is highly topical. For example, applications of mobile micropayment systems are widely used and are well known by the public.The objective of this study was to implement a micropayment system pilot based on an interoperability enabling platform (in this case, Smart-M3) for small businesses with restricted resources, scarce labor force, and a growing number of products and vendors.In these small and medium-sized enterprise (SME) contexts, piloting systems of this kind is usually problematic because of its immediate impact on the core business and monetary transactions that are essential for SMEs. An account-based system was considered an appropriate starting point for the micropayment system pilot. The applicability of the Smart-M3 platform was then validated by the implementation of the system. Lastly, a summative evaluation was carried out by interviewing direct stakeholders, to enrich the observations from the validation. The results of the study show that the implemented system provides small businesses with opportunities to reduce costs and more efficiently use resources, adding new devices and systems, new ways to produce services, andreal-time tracking of the sales process, as well as utilization of the data collected from the system. From the customers point of view, the efficient use of resources may lead to more competitive prices of the products and services. Micropayment system usage can also be seen as a starting point for improved user experience, includingsafety, efficiency, and ease of use. Read More Read Less

Abstract Modern individuals increasingly disclose personal information in today's information-driven society through online platforms. This information is used by the online platform for a particular context and may be reused by other partners or users of the platform in ways that may not have been intended. Current examples include email harvesting for spam, personal photographs used in advertising, or maintaining competitor... Modern individuals increasingly disclose personal information in today's information-driven society through online platforms. This information is used by the online platform for a particular context and may be reused by other partners or users of the platform in ways that may not have been intended. Current examples include email harvesting for spam, personal photographs used in advertising, or maintaining competitor information without explicit purposed consent. With integration and aggregation of information becoming increasingly popular across online platforms through the rise of online collaboration, privacy issues such as unintentional information disclosure become increasingly critical. This is particularly true where individuals representing corporations interact with online platforms using personal accounts to manage both business and private relationships: there is an inherent risk that sensitive information could be inadvertently shared to the wrong audience, with non-trivial consequences. The European research project digital.me developed a user-centric trust metric that powers an intelligent recommendation system to provide privacy advisories to users when they share potentially sensitive information. This metric was tested in an online social networking (OSN) demonstration prototype, the di.me userware, as well as in a customer relationship management (CRM) demonstration prototype, di.me CRM, to determine whether the metric found resonance operators in the rapidly growing CRM market segment. In this context, the trust metric was validated against three mediating conditions for technology acceptance: usability and general acceptance, utility, and privacy concerns. Field trials involving 447 CRM operators showed positive results for all three conditions in both OSN and CRM prototypes. Read More Read Less