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试述区域性行政协议的理论定位及其软法性特征 被引量:19
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作者 熊文钊 郑毅 《广西大学学报(哲学社会科学版)》 2011年第4期66-71,共6页
当前,随着区域经济的不断发展,区域性行政合作不断增加,其表现之一就是大量的区域性行政协议如雨后春笋般涌现。这类行政协议不同于传统认识中的行政合同,具有参与者均为行政主体、各缔约方地位具有对等性等特点。在实际运行过程中,区... 当前,随着区域经济的不断发展,区域性行政合作不断增加,其表现之一就是大量的区域性行政协议如雨后春笋般涌现。这类行政协议不同于传统认识中的行政合同,具有参与者均为行政主体、各缔约方地位具有对等性等特点。在实际运行过程中,区域性行政协议从制度和效力两个方面都体现出浓厚的类软法性,这也为区域性行政协议的实现造成了诸多困难。然而,这只是一种客观的、暂时的、阶段性存在,通过统一立法实现"硬法化"才是区域性行政协议的最终归宿。 展开更多
关键词 区域性行政合作 区域性行政协议 理论定位 特征 评述
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公共图书馆法律责任探究
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作者 张波 《甘肃科技》 2020年第11期73-74,156,共3页
《公共图书馆法》重点规定了公共图书馆的义务和法律责任,如何保障其落到实处,发挥该法对促进公共图书馆事业发展的积极作用,需要我们把握这些义务性规定的特征,分析其违法行为的表现形式,确定其法律责任的构成要件。
关键词 公共图书馆 义务 软法特征 律责任
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试述区域性行政协议的理论定位及其软法性特征
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作者 郑毅 《朝阳法律评论》 2011年第1期95-110,共16页
当前,随着区域经济的不断发展,区域性行政合作不断增加,其表现之一就是大量的区域性行政协议如雨后春笋般涌现。这类行政协议不同于传统认识中的行政合同,具有参与者均为行政主体、各缔约方地位具有对等性等特点。在实际运行过程中,区... 当前,随着区域经济的不断发展,区域性行政合作不断增加,其表现之一就是大量的区域性行政协议如雨后春笋般涌现。这类行政协议不同于传统认识中的行政合同,具有参与者均为行政主体、各缔约方地位具有对等性等特点。在实际运行过程中,区域性行政协议从制度和效力两个方面都体现出浓厚的类软法性,这也为区域性行政协议的实现造成了诸多困难。然而,这只是一种客观的、暂时的、阶段性存在,通过统一立法实现'硬法化'才是区域性行政协议的最终归宿。 展开更多
关键词 区域性行政合作 区域性行政协议 理论定位 特征 评述
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北美自由贸易区模式的创新价值探析 被引量:4
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作者 王春婕 《山东社会科学》 CSSCI 北大核心 2009年第2期83-85,共3页
北美自由贸易区在区域一体化组织模式上具有创新价值,它根据区域一体化组织内成员国的差异性需求,设计了一套兼具软法与硬法特征的组织架构与法律制度。这一模式通过灵活性的制度安排不仅恰当解决了北美自由贸易区内各成员国经济发展水... 北美自由贸易区在区域一体化组织模式上具有创新价值,它根据区域一体化组织内成员国的差异性需求,设计了一套兼具软法与硬法特征的组织架构与法律制度。这一模式通过灵活性的制度安排不仅恰当解决了北美自由贸易区内各成员国经济发展水平不一所带来的诸多问题,而且开创了"南北合作"的新路径,对于"南北合作"类型的区域一体化具有较强的模式借鉴价值。 展开更多
关键词 NAFTA模式 软法特征 特征 创新价值
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NAFTA模式对我国的借鉴价值分析 被引量:1
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作者 王春婕 《商场现代化》 北大核心 2005年第8期132-133,共2页
NAFTA在区域一体化的组织模式上具有创新性,它根据区域一体化组织内成员国的差异性需求,设计了一套兼具软法与硬法特征的组织架构与法律制度.这一模式通过灵活性的制度安排不仅恰当解决了北美自由贸易区内各成员国经济发展水平不一所带... NAFTA在区域一体化的组织模式上具有创新性,它根据区域一体化组织内成员国的差异性需求,设计了一套兼具软法与硬法特征的组织架构与法律制度.这一模式通过灵活性的制度安排不仅恰当解决了北美自由贸易区内各成员国经济发展水平不一所带来的诸多问题,而且开创了"南北合作"的新路径,对于我国参与区域一体化具有较强的模式借鉴价值. 展开更多
关键词 NAFTA模式 软法特征 特征 借鉴价值 NAFTA 价值分析 北美自由贸易区 区域一体化 经济发展水平 “南北合作”
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A Multi-model Approach for Soft Sensor Development Based on Feature Extraction Using Weighted Kernel Fisher Criterion 被引量:7
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作者 吕业 杨慧中 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2014年第2期146-152,共7页
Multi-model approach can significantly improve the prediction performance of soft sensors in the process with multiple operational conditions.However,traditional clustering algorithms may result in overlapping phenome... Multi-model approach can significantly improve the prediction performance of soft sensors in the process with multiple operational conditions.However,traditional clustering algorithms may result in overlapping phenomenon in subclasses,so that edge classes and outliers cannot be effectively dealt with and the modeling result is not satisfactory.In order to solve these problems,a new feature extraction method based on weighted kernel Fisher criterion is presented to improve the clustering accuracy,in which feature mapping is adopted to bring the edge classes and outliers closer to other normal subclasses.Furthermore,the classified data are used to develop a multiple model based on support vector machine.The proposed method is applied to a bisphenol A production process for prediction of the quality index.The simulation results demonstrate its ability in improving the data classification and the prediction performance of the soft sensor. 展开更多
关键词 feature extraction weighted kernel Fisher criterion CLASSIFICATION soft sensor
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Soft measurement for component content based on adaptive model of Pr/Nd color features 被引量:5
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作者 陆荣秀 杨辉 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2015年第12期1981-1986,共6页
For measurement of component content in the extraction and separation process of praseodymium/neodymium(Pr/Nd), a soft measurement method was proposed based on modeling of ion color features, which is suitable for fas... For measurement of component content in the extraction and separation process of praseodymium/neodymium(Pr/Nd), a soft measurement method was proposed based on modeling of ion color features, which is suitable for fast estimation of component content in production field. Feature analysis on images of the solution is conducted,which are captured from Pr/Nd extraction/separation field. H/S components in the HSI color space are selected as model inputs, so as to establish the least squares support vector machine(LSSVM) model for Nd(Pr) content,while the model parameters are determined with the GA algorithm. To improve the adaptability of the model,the adaptive iteration algorithm is used to correct parameters of the LSSVM model, on the basis of model correction strategy and new sample data. Using the field data collected from rare earth extraction production, predictive methods for component content and comparisons are given. The results indicate that the proposed method presents good adaptability and high prediction precision, so it is applicable to the fast detection of element content in the rare earth extraction. 展开更多
关键词 Pr/Nd extraction Color feature Component content Adaptive iterative least squares support vector machine Real-time correction
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A distributed software architecture design framework based on attributed grammar
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作者 贾晓琳 覃征 +1 位作者 何坚 虞凡 《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 SCIE EI CAS CSCD 2005年第6期513-518,共6页
Software architectures shift the focus of developers from lines-of-code to coarser-grained architectural elements and their overall interconnection structure. There are, however, many features of the distributed softw... Software architectures shift the focus of developers from lines-of-code to coarser-grained architectural elements and their overall interconnection structure. There are, however, many features of the distributed software that make the developing methods of distributed software quite different from the traditional ways. Furthermore, the traditional centralized ways with fixed interfaces cannot adapt to the flexible requirements of distributed software. In this paper, the attributed grammar (AG) is extended to refine the characters of distributed software, and a distributed software architecture description language (DSADL) based on attributed grammar is introduced, and then a model of integrated environment for software architecture design is proposed. It can be demonstrated by the practice that DSADL can help the programmers to analyze and design distributed software effectively, so the efficiency of the development can be improved greatly. 展开更多
关键词 Software architecture Attributed grammar Distributed software COMPONENT
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DESIGN METHODOLOGY OF NETWORKED SOFTWARE EVOLUTION GROWTH BASED ON SOFTWARE PATTERNS 被引量:24
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作者 Keqing HE Rong PENG +3 位作者 Jing LIU Fei HE Peng LIANG Bing LI 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2006年第2期157-181,共25页
Recently, some new characteristics of complex networks attract the attentions of scientist, in different fields, and lead to many kinds of emerging research directions. So far, most of the researcl work has been limit... Recently, some new characteristics of complex networks attract the attentions of scientist, in different fields, and lead to many kinds of emerging research directions. So far, most of the researcl work has been limited in discovery of complex network characteristics by structure analysis in large-scale software systems. This paper presents the theoretical basis, design method, algorithms and experiment results of the research. It firstly emphasizes the significance of design method of evolution growth for network topology of Object Oriented (OO) software systems, and argues that the selection and modulation of network models with various topology characteristics will bring un-ignorable effect on the process, of design and implementation of OO software systems. Then we analyze the similar discipline of "negation of negation and compromise" between the evolution of network models with different topology characteristics and the development of software modelling methods. According to the analysis of the growth features of software patterns, we propose an object-oriented software network evolution growth method and its algorithms in succession. In addition, we also propose the parameter systems for OO software system metrics based on complex network theory. Based on these parameter systems, it can analyze the features of various nodes, links and local-world, modulate the network topology and guide the software metrics. All these can be helpful to the detailed design, implementation and performance analysis. Finally, we focus on the application of the evolution algorithms and demonstrate it by a case study. Comparing the results from our early experiments with methodologies in empirical software engineering, we believe that the proposed software engineering design method is a computational software engineering approach based on complex network theory. We argue that this method should be greatly beneficial for the design, implementation, modulation and metrics of functionality, structure and performance in large-scale OO software complex system. 展开更多
关键词 Complex networks evolution growth design method growth characteristics of software patterns networked software OO software network types and modulation of preferential attachment.
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Discovering optimal features using static analysis and a genetic search based method for Android malware detection 被引量:6
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作者 Ahmad FIRDAUS Nor Badrul ANUAR +1 位作者 Ahmad KARIM Mohd Faizal Ab RAZAK 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2018年第6期712-736,共25页
Mobile device manufacturers are rapidly producing miscellaneous Android versions worldwide. Simultaneously, cyber criminals are executing malicious actions, such as tracking user activities, stealing personal data, an... Mobile device manufacturers are rapidly producing miscellaneous Android versions worldwide. Simultaneously, cyber criminals are executing malicious actions, such as tracking user activities, stealing personal data, and committing bank fraud. These criminals gain numerous benefits as too many people use Android for their daily routines, including important communications. With this in mind, security practitioners have conducted static and dynamic analyses to identify malware. This study used static analysis because of its overall code coverage, low resource consumption, and rapid processing. However, static analysis requires a minimum number of features to efficiently classify malware. Therefore, we used genetic search(GS), which is a search based on a genetic algorithm(GA), to select the features among 106 strings. To evaluate the best features determined by GS, we used five machine learning classifiers, namely, Na?ve Bayes(NB), functional trees(FT), J48, random forest(RF), and multilayer perceptron(MLP). Among these classifiers, FT gave the highest accuracy(95%) and true positive rate(TPR)(96.7%) with the use of only six features. 展开更多
关键词 Genetic algorithm Static analysis ANDROID MALWARE Machine learning
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