With the development of Internet of things, cloud computing, mobile Inter- net, the scale of the data shows an alarming growth trend. Agricultural information is an important part of modern agricultural construction, ...With the development of Internet of things, cloud computing, mobile Inter- net, the scale of the data shows an alarming growth trend. Agricultural information is an important part of modern agricultural construction, and the development of a- gricultural industry is becoming more and more deeply with the application of infor- mation technology. This paper reviewed the concept and characteristic of big data, development history of big data at home and abroad, and emphatically expounded the connotation of agricultural big data, development status of agricultural big data at home and abroad, as well as the applications of agricultural big data technology, agriculture big data resources and agricultural big data in various fields.展开更多
Recently a new clustering algorithm called 'affinity propagation' (AP) has been proposed, which efficiently clustered sparsely related data by passing messages between data points. However, we want to cluster ...Recently a new clustering algorithm called 'affinity propagation' (AP) has been proposed, which efficiently clustered sparsely related data by passing messages between data points. However, we want to cluster large scale data where the similarities are not sparse in many cases. This paper presents two variants of AP for grouping large scale data with a dense similarity matrix. The local approach is partition affinity propagation (PAP) and the global method is landmark affinity propagation (LAP). PAP passes messages in the subsets of data first and then merges them as the number of initial step of iterations; it can effectively reduce the number of iterations of clustering. LAP passes messages between the landmark data points first and then clusters non-landmark data points; it is a large global approximation method to speed up clustering. Experiments are conducted on many datasets, such as random data points, manifold subspaces, images of faces and Chinese calligraphy, and the results demonstrate that the two ap-proaches are feasible and practicable.展开更多
In this paper, it described the architecture of a tool called DiagData. This tool aims to use a large amount of data and information in the field of plant disease diagnostic to generate a disease predictive system. In...In this paper, it described the architecture of a tool called DiagData. This tool aims to use a large amount of data and information in the field of plant disease diagnostic to generate a disease predictive system. In this approach, techniques of data mining are used to extract knowledge from existing data. The data is extracted in the form of rules that are used in the development of a predictive intelligent system. Currently, the specification of these rules is built by an expert or data mining. When data mining on a large database is used, the number of generated rules is very complex too. The main goal of this work is minimize the rule generation time. The proposed tool, called DiagData, extracts knowledge automatically or semi-automatically from a database and uses it to build an intelligent system for disease prediction. In this work, the decision tree learning algorithm was used to generate the rules. A toolbox called Fuzzygen was used to generate a prediction system from rules generated by decision tree algorithm. The language used to implement this software was Java. The DiagData has been used in diseases prediction and diagnosis systems and in the validation of economic and environmental indicators in agricultural production systems. The validation process involved measurements and comparisons of the time spent to enter the rules by an expert with the time used to insert the same rules with the proposed tool. Thus, the tool was successfully validated, providing a reduction of time.展开更多
Supported by the development of computer network technology, multi-media technology and database technology, file information digitalization as a new morphology of file emerges. This new kind of file morphology could ...Supported by the development of computer network technology, multi-media technology and database technology, file information digitalization as a new morphology of file emerges. This new kind of file morphology could exercise a long-term saving of file resources and efficiently utilize it. File management is the most important part of university information management. However, as various universities are different in their specific practice, file digital construction is different in construction manner and content.展开更多
The popularity of technology has allowed universities to make changes through their educational system in recent years. Some transitioned from face-to-face instruction to online instruction. The aim of this study is t...The popularity of technology has allowed universities to make changes through their educational system in recent years. Some transitioned from face-to-face instruction to online instruction. The aim of this study is to investigate the perceptions of both the instructors and the students as regards second language acquisition through online education at a rural university. The study was implemented in the context of teaching and learning English as a second language in an online education environment. The course material is based on The Net Languages Learning Platform, which is available at http：//ide.yok.gov.tr/, and the course level is general English pre-elementary. Both quantitative and qualitative methods were used in this study. For quantitative data collection, a questionnaire was employed to understand the reasons for low student attendance on online courses. For qualitative research method, observation was carried out, and interviews are designed as data collection techniques. Purposive selection was used for selection of the participants. The findings revealed that online education needs to be modified. The students are eager to improve their second language competencies; however, they do not want to waste their time on an easy course level.展开更多
The rapid growth of big data technology has become a major trend affecting the pattern of world development.Big data criminal investigation is a new type of criminal detection used extensively in the course of police ...The rapid growth of big data technology has become a major trend affecting the pattern of world development.Big data criminal investigation is a new type of criminal detection used extensively in the course of police practice at home and abroad.Its emergence indicates a trend in criminal justice towards ensuring security at the expense of privacy and exchanging rights for information.Big data criminal investigation highlights the backwardness and dysfunction of the traditional framework of legal norms,evident in doubts about the legal attributes of such investigation and the obvious limitations of techniques for distinguishing data content from metadata.This leaves a vacuum in the regulation of investigative power at the preliminary stage of investigation.Big data criminal investigation itself is a doubleedge sword;in order to forestall the possible abuses it may entail in terms of deep and broad interventions in basic civil rights,big data criminal investigation should be brought under the necessary legal control.We therefore propose adopting a dual regulatory approach comprising investigative and data norms,selectively adopting the traditional normative framework of the principle of legality and the principle of proportionality,and at the same time supplementing it with other legal principles and mechanisms concerning the protection of personal information and data.展开更多
文摘With the development of Internet of things, cloud computing, mobile Inter- net, the scale of the data shows an alarming growth trend. Agricultural information is an important part of modern agricultural construction, and the development of a- gricultural industry is becoming more and more deeply with the application of infor- mation technology. This paper reviewed the concept and characteristic of big data, development history of big data at home and abroad, and emphatically expounded the connotation of agricultural big data, development status of agricultural big data at home and abroad, as well as the applications of agricultural big data technology, agriculture big data resources and agricultural big data in various fields.
基金the National Natural Science Foundation of China (Nos. 60533090 and 60603096)the National Hi-Tech Research and Development Program (863) of China (No. 2006AA010107)+2 种基金the Key Technology R&D Program of China (No. 2006BAH02A13-4)the Program for Changjiang Scholars and Innovative Research Team in University of China (No. IRT0652)the Cultivation Fund of the Key Scientific and Technical Innovation Project of MOE, China (No. 706033)
文摘Recently a new clustering algorithm called 'affinity propagation' (AP) has been proposed, which efficiently clustered sparsely related data by passing messages between data points. However, we want to cluster large scale data where the similarities are not sparse in many cases. This paper presents two variants of AP for grouping large scale data with a dense similarity matrix. The local approach is partition affinity propagation (PAP) and the global method is landmark affinity propagation (LAP). PAP passes messages in the subsets of data first and then merges them as the number of initial step of iterations; it can effectively reduce the number of iterations of clustering. LAP passes messages between the landmark data points first and then clusters non-landmark data points; it is a large global approximation method to speed up clustering. Experiments are conducted on many datasets, such as random data points, manifold subspaces, images of faces and Chinese calligraphy, and the results demonstrate that the two ap-proaches are feasible and practicable.
文摘In this paper, it described the architecture of a tool called DiagData. This tool aims to use a large amount of data and information in the field of plant disease diagnostic to generate a disease predictive system. In this approach, techniques of data mining are used to extract knowledge from existing data. The data is extracted in the form of rules that are used in the development of a predictive intelligent system. Currently, the specification of these rules is built by an expert or data mining. When data mining on a large database is used, the number of generated rules is very complex too. The main goal of this work is minimize the rule generation time. The proposed tool, called DiagData, extracts knowledge automatically or semi-automatically from a database and uses it to build an intelligent system for disease prediction. In this work, the decision tree learning algorithm was used to generate the rules. A toolbox called Fuzzygen was used to generate a prediction system from rules generated by decision tree algorithm. The language used to implement this software was Java. The DiagData has been used in diseases prediction and diagnosis systems and in the validation of economic and environmental indicators in agricultural production systems. The validation process involved measurements and comparisons of the time spent to enter the rules by an expert with the time used to insert the same rules with the proposed tool. Thus, the tool was successfully validated, providing a reduction of time.
文摘Supported by the development of computer network technology, multi-media technology and database technology, file information digitalization as a new morphology of file emerges. This new kind of file morphology could exercise a long-term saving of file resources and efficiently utilize it. File management is the most important part of university information management. However, as various universities are different in their specific practice, file digital construction is different in construction manner and content.
文摘The popularity of technology has allowed universities to make changes through their educational system in recent years. Some transitioned from face-to-face instruction to online instruction. The aim of this study is to investigate the perceptions of both the instructors and the students as regards second language acquisition through online education at a rural university. The study was implemented in the context of teaching and learning English as a second language in an online education environment. The course material is based on The Net Languages Learning Platform, which is available at http：//ide.yok.gov.tr/, and the course level is general English pre-elementary. Both quantitative and qualitative methods were used in this study. For quantitative data collection, a questionnaire was employed to understand the reasons for low student attendance on online courses. For qualitative research method, observation was carried out, and interviews are designed as data collection techniques. Purposive selection was used for selection of the participants. The findings revealed that online education needs to be modified. The students are eager to improve their second language competencies; however, they do not want to waste their time on an easy course level.
文摘The rapid growth of big data technology has become a major trend affecting the pattern of world development.Big data criminal investigation is a new type of criminal detection used extensively in the course of police practice at home and abroad.Its emergence indicates a trend in criminal justice towards ensuring security at the expense of privacy and exchanging rights for information.Big data criminal investigation highlights the backwardness and dysfunction of the traditional framework of legal norms,evident in doubts about the legal attributes of such investigation and the obvious limitations of techniques for distinguishing data content from metadata.This leaves a vacuum in the regulation of investigative power at the preliminary stage of investigation.Big data criminal investigation itself is a doubleedge sword;in order to forestall the possible abuses it may entail in terms of deep and broad interventions in basic civil rights,big data criminal investigation should be brought under the necessary legal control.We therefore propose adopting a dual regulatory approach comprising investigative and data norms,selectively adopting the traditional normative framework of the principle of legality and the principle of proportionality,and at the same time supplementing it with other legal principles and mechanisms concerning the protection of personal information and data.
