With the development of information technology, how to build a resource library that adapt to the development of vocational education, professional characteristics favor standardized resource sharing between vocationa...With the development of information technology, how to build a resource library that adapt to the development of vocational education, professional characteristics favor standardized resource sharing between vocational schools, scientific and open career teaching vocational education teaching reform and information technology become the urgent problem. This article starts from the repository construction characteristics and the actual situation of the College of departure, and actively explores the network database curriculum resource library building programs.展开更多
With the continuous development of computer network technology, its applications in daily life and work have become increasingly widespread, greatly improving efficiency. However, certain security risks remain. To ens...With the continuous development of computer network technology, its applications in daily life and work have become increasingly widespread, greatly improving efficiency. However, certain security risks remain. To ensure the security of computer networks and databases, it is essential to enhance the security of both through optimization of technology. This includes improving management practices, optimizing data processing methods, and establishing comprehensive laws and regulations. This paper analyzes the current security risks in computer networks and databases and proposes corresponding solutions, offering reference points for relevant personnel.展开更多
The typical characteristic of the topology of Bayesian networks (BNs) is the interdependence among different nodes (variables), which makes it impossible to optimize one variable independently of others, and the learn...The typical characteristic of the topology of Bayesian networks (BNs) is the interdependence among different nodes (variables), which makes it impossible to optimize one variable independently of others, and the learning of BNs structures by general genetic algorithms is liable to converge to local extremum. To resolve efficiently this problem, a self-organizing genetic algorithm (SGA) based method for constructing BNs from databases is presented. This method makes use of a self-organizing mechanism to develop a genetic algorithm that extended the crossover operator from one to two, providing mutual competition between them, even adjusting the numbers of parents in recombination (crossover/recomposition) schemes. With the K2 algorithm, this method also optimizes the genetic operators, and utilizes adequately the domain knowledge. As a result, with this method it is able to find a global optimum of the topology of BNs, avoiding premature convergence to local extremum. The experimental results proved to be and the convergence of the SGA was discussed.展开更多
Most knowledgeable people agree that networking and routing technologies have been around about 25 years. Routing is simultaneously the most complicated function of a network and the most important. It is of the same ...Most knowledgeable people agree that networking and routing technologies have been around about 25 years. Routing is simultaneously the most complicated function of a network and the most important. It is of the same kind that more than 70% of computer application fields are MIS applications. So the challenge in building and using a MIS in the network is developing the means to find, access, and communicate large databases or multi databases systems. Because general databases are not time continuous, in fact, they can not be streaming, so we can't obtain reliable and secure quality of service by deleting some unimportant datagrams in the databases transmission. In this article, we will discuss which kind of routing protocol is the best type for large databases or multi databases systems transmission in the networks.展开更多
Sensor networks provide means to link people with real world by processing data in real time collected from real-world and routing the query results to the right people. Application examples include continuous monitor...Sensor networks provide means to link people with real world by processing data in real time collected from real-world and routing the query results to the right people. Application examples include continuous monitoring of environment, building infrastructures and human health. Many researchers view the sensor networks as databases, and the monitoring tasks are performed as subscriptions, queries, and alert. However, this point is not precise. First, databases can only deal with well-formed data types, with well-defined schema for their interpretation, while the raw data collected by the sensor networks, in most cases, do not fit to this requirement. Second, sensor networks have to deal with very dynamic targets, environment and resources, while databases are more static. In order to fill this gap between sensor networks and databases, we propose a novel approach, referred to as 'spatiotemporal data stream segmentation', or 'stream segmentation' for short, to address the dynamic nature and deal with 'raw' data of sensor networks. Stream segmentation is defined using Bayesian Networks in the context of sensor networks, and two application examples are given to demonstrate the usefulness of the approach.展开更多
Rice is one of the most important stable food as well as a monocotyledonous model organism for the plant research community.Here,we present RED（Rice Expression Database;http：//expression.ic4r.org）,an integrated dat...Rice is one of the most important stable food as well as a monocotyledonous model organism for the plant research community.Here,we present RED（Rice Expression Database;http：//expression.ic4r.org）,an integrated database of rice gene expression profiles derived entirely from RNA-Seq data.RED features a comprehensive collection of 284 high-quality RNA-Seq experiments,integrates a large number of gene expression profiles and covers a wide range of rice growth stages as well as various treatments.Based on massive expression profiles,RED provides a list of housekeeping and tissue-specific genes and dynamically constructs co-expression networks for gene（s） of interest.Besides,it provides user-friendly web interfaces for querying,browsing and visualizing expression profiles of concerned genes.Together,as a core resource in BIG Data Center,RED bears great utility for characterizing the function of rice genes and better understanding important biological processes and mechanisms underlying complex agronomic traits in rice.展开更多
The purpose of this study is to analyze and then model, using neural network models, the performance of the Web server in order to improve them. In our experiments, the parameters taken into account are the number of ...The purpose of this study is to analyze and then model, using neural network models, the performance of the Web server in order to improve them. In our experiments, the parameters taken into account are the number of instances of clients simultaneously requesting the same Web page that contains the same SQL queries, the number of tables queried by the SQL, the number of records to be displayed on the requested Web pages, and the type of used database server. This work demonstrates the influences of these parameters on the results of Web server performance analyzes. For the MySQL database server, it has been observed that the mean response time of the Web server tends to become increasingly slow as the number of client connection occurrences as well as the number of records to display increases. For the PostgreSQL database server, the mean response time of the Web server does not change much, although there is an increase in the number of clients and/or size of information to be displayed on Web pages. Although it has been observed that the mean response time of the Web server is generally a little faster for the MySQL database server, it has been noted that this mean response time of the Web server is more stable for PostgreSQL database server.展开更多
Information systems are one of the most rapidly changing and vulnerable systems, where security is a major issue. The number of security-breaking attempts originating inside organizations is increasing steadily. Attac...Information systems are one of the most rapidly changing and vulnerable systems, where security is a major issue. The number of security-breaking attempts originating inside organizations is increasing steadily. Attacks made in this way, usually done by ＂authorized＂ users of the system, cannot be immediately traced. Because the idea of filtering the traffic at the entrance door, by using firewalls and the like, is not completely successful, the use of intrusion detection systems should be considered to increase the defense capacity of an information system. An intrusion detection system （IDS） is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current IDS depends on the system operators in working out the tuning solution and in integrating it into the detection model. Furthermore, an extensive effort is required to tackle the newly evolving attacks and a deep study is necessary to categorize it into the respective classes. To reduce this dependence, an automatically evolving anomaly IDS using neuro-genetic algorithm is presented. The proposed system automatically tunes the detection model on the fly according to the feedback provided by the system operator when false predictions are encountered. The system has been evaluated using the Knowledge Discovery in Databases Conference （KDD 2009） intrusion detection dataset. Genetic paradigm is employed to choose the predominant features, which reveal the occurrence of intrusions. The neuro-genetic IDS （NGIDS） involves calculation of weightage value for each of the categorical attributes so that data of uniform representation can be processed by the neuro-genetic algorithm. In this system unauthorized invasion of a user are identified and newer types of attacks are sensed and classified respectively by the neuro-genetic algorithm. The experimental results obtained in this work show that the system achieves improvement in terms of misclassification cost when compared with conventional IDS. The results of the experiments show that this system can be deployed based on a real network or database environment for effective prediction of both normal attacks and new attacks.展开更多
文摘With the development of information technology, how to build a resource library that adapt to the development of vocational education, professional characteristics favor standardized resource sharing between vocational schools, scientific and open career teaching vocational education teaching reform and information technology become the urgent problem. This article starts from the repository construction characteristics and the actual situation of the College of departure, and actively explores the network database curriculum resource library building programs.
文摘With the continuous development of computer network technology, its applications in daily life and work have become increasingly widespread, greatly improving efficiency. However, certain security risks remain. To ensure the security of computer networks and databases, it is essential to enhance the security of both through optimization of technology. This includes improving management practices, optimizing data processing methods, and establishing comprehensive laws and regulations. This paper analyzes the current security risks in computer networks and databases and proposes corresponding solutions, offering reference points for relevant personnel.
文摘The typical characteristic of the topology of Bayesian networks (BNs) is the interdependence among different nodes (variables), which makes it impossible to optimize one variable independently of others, and the learning of BNs structures by general genetic algorithms is liable to converge to local extremum. To resolve efficiently this problem, a self-organizing genetic algorithm (SGA) based method for constructing BNs from databases is presented. This method makes use of a self-organizing mechanism to develop a genetic algorithm that extended the crossover operator from one to two, providing mutual competition between them, even adjusting the numbers of parents in recombination (crossover/recomposition) schemes. With the K2 algorithm, this method also optimizes the genetic operators, and utilizes adequately the domain knowledge. As a result, with this method it is able to find a global optimum of the topology of BNs, avoiding premature convergence to local extremum. The experimental results proved to be and the convergence of the SGA was discussed.
基金Supported by National Natural Science Foundation of China(6 98730 2 7)
文摘Most knowledgeable people agree that networking and routing technologies have been around about 25 years. Routing is simultaneously the most complicated function of a network and the most important. It is of the same kind that more than 70% of computer application fields are MIS applications. So the challenge in building and using a MIS in the network is developing the means to find, access, and communicate large databases or multi databases systems. Because general databases are not time continuous, in fact, they can not be streaming, so we can't obtain reliable and secure quality of service by deleting some unimportant datagrams in the databases transmission. In this article, we will discuss which kind of routing protocol is the best type for large databases or multi databases systems transmission in the networks.
文摘Sensor networks provide means to link people with real world by processing data in real time collected from real-world and routing the query results to the right people. Application examples include continuous monitoring of environment, building infrastructures and human health. Many researchers view the sensor networks as databases, and the monitoring tasks are performed as subscriptions, queries, and alert. However, this point is not precise. First, databases can only deal with well-formed data types, with well-defined schema for their interpretation, while the raw data collected by the sensor networks, in most cases, do not fit to this requirement. Second, sensor networks have to deal with very dynamic targets, environment and resources, while databases are more static. In order to fill this gap between sensor networks and databases, we propose a novel approach, referred to as 'spatiotemporal data stream segmentation', or 'stream segmentation' for short, to address the dynamic nature and deal with 'raw' data of sensor networks. Stream segmentation is defined using Bayesian Networks in the context of sensor networks, and two application examples are given to demonstrate the usefulness of the approach.
基金supported by grants from Strategic Priority Research Program of the Chinese Academy of Sciences(No. XDA08020102 to Z.Z.and S.H.)International Partnership Program of the Chinese Academy of Sciences(No.153F11KYSB20160008)+3 种基金National Programs for High Technology Research and Development (863 ProgramNo.2015AA020108 to Z.Z.)National Natural Science Foundation of China(No.31100915 to LH.)the 100-Talent Program of Chinese Academy of Sciences(awarded to Z.Z.)
文摘Rice is one of the most important stable food as well as a monocotyledonous model organism for the plant research community.Here,we present RED（Rice Expression Database;http：//expression.ic4r.org）,an integrated database of rice gene expression profiles derived entirely from RNA-Seq data.RED features a comprehensive collection of 284 high-quality RNA-Seq experiments,integrates a large number of gene expression profiles and covers a wide range of rice growth stages as well as various treatments.Based on massive expression profiles,RED provides a list of housekeeping and tissue-specific genes and dynamically constructs co-expression networks for gene（s） of interest.Besides,it provides user-friendly web interfaces for querying,browsing and visualizing expression profiles of concerned genes.Together,as a core resource in BIG Data Center,RED bears great utility for characterizing the function of rice genes and better understanding important biological processes and mechanisms underlying complex agronomic traits in rice.
文摘The purpose of this study is to analyze and then model, using neural network models, the performance of the Web server in order to improve them. In our experiments, the parameters taken into account are the number of instances of clients simultaneously requesting the same Web page that contains the same SQL queries, the number of tables queried by the SQL, the number of records to be displayed on the requested Web pages, and the type of used database server. This work demonstrates the influences of these parameters on the results of Web server performance analyzes. For the MySQL database server, it has been observed that the mean response time of the Web server tends to become increasingly slow as the number of client connection occurrences as well as the number of records to display increases. For the PostgreSQL database server, the mean response time of the Web server does not change much, although there is an increase in the number of clients and/or size of information to be displayed on Web pages. Although it has been observed that the mean response time of the Web server is generally a little faster for the MySQL database server, it has been noted that this mean response time of the Web server is more stable for PostgreSQL database server.
文摘Information systems are one of the most rapidly changing and vulnerable systems, where security is a major issue. The number of security-breaking attempts originating inside organizations is increasing steadily. Attacks made in this way, usually done by ＂authorized＂ users of the system, cannot be immediately traced. Because the idea of filtering the traffic at the entrance door, by using firewalls and the like, is not completely successful, the use of intrusion detection systems should be considered to increase the defense capacity of an information system. An intrusion detection system （IDS） is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current IDS depends on the system operators in working out the tuning solution and in integrating it into the detection model. Furthermore, an extensive effort is required to tackle the newly evolving attacks and a deep study is necessary to categorize it into the respective classes. To reduce this dependence, an automatically evolving anomaly IDS using neuro-genetic algorithm is presented. The proposed system automatically tunes the detection model on the fly according to the feedback provided by the system operator when false predictions are encountered. The system has been evaluated using the Knowledge Discovery in Databases Conference （KDD 2009） intrusion detection dataset. Genetic paradigm is employed to choose the predominant features, which reveal the occurrence of intrusions. The neuro-genetic IDS （NGIDS） involves calculation of weightage value for each of the categorical attributes so that data of uniform representation can be processed by the neuro-genetic algorithm. In this system unauthorized invasion of a user are identified and newer types of attacks are sensed and classified respectively by the neuro-genetic algorithm. The experimental results obtained in this work show that the system achieves improvement in terms of misclassification cost when compared with conventional IDS. The results of the experiments show that this system can be deployed based on a real network or database environment for effective prediction of both normal attacks and new attacks.
