An Information Analysis Decision System

In recent years, we are increasingly coping with macro, complex and large-scale system in whichinformations twist together. It is a worthwhile research to develop general computer-aided meth-od for decision-making on the basis of processing, analysing and deducing from the informationobtained.

Bayesian-based information extraction and aggregation approach for multilevel systems with multi-source data

The ever-increasing complexity of industry facilities has made the reliability analysis and assessment an imperative yet tough work. Motivated by practical engineering requirement, this paper develops a Bayesian-based information extraction and aggregation (BIEA) approach for system level reliability estimation of a complex system. It takes both subjective judgments and objective field outputs into consideration. Novel features of this approach is a unique information content based aggregation process, which allows a flexible application of this framework in separated modules on account for purpose. The coherency of which is guaranteed by the objective information content calculation. This work goes beyond the alternatives that deal with solely attributed data under ideal information circumstance, and investigates a more generic tool for real engineering application. Limitations embedded in traditional statistical modeling methods have been eliminated in a nature manner by information transition and integration. In addition, a double axis driving mechanism (DADM) for erecting the antenna of a satellite is demonstrated as case study for benefit illustration and effectiveness verification. © 2017 Beijing Institute of Aerospace Information.

Separate Analysis of Remote Sensing Information of Structures of Different Geological Periods and Quantitative Study of Corresponding Tectonic Stress Fields

The structural feature shown on a remote sensing image is a synthetic result ofcombination of the deformations produced during the entire geological history of an area.Therefore, the respective tectonic stress field of each of the different stages in the complexdeformation of an area can be reconstructed in three steps: (1) geological structures formed atdifferent times are distinguished in remote sensing image interpretation; (2) structuraldeformation fields at different stages are determined by analyzing relationships betweenmicrostructures (joints and fractures) and the related structures (folds and faults); and (3)tectonic stress fields at different stages are respectively recovered through a study of the featuresof structural deformation fields in different periods. Circular structures and related circlular and radial joints are correlated in space to con-cealed structural rises. The authors propose a new method for establishing a natural model ofthe concealed structural rises and calculating the tectonic stress field by using quantitative dataof the remote sensing information of circular structures and related linear structures.

Capacity Analysis and Information Optimization of WSDM

Wireless statistic division multiplexing (WSDM) is a multiplexing scheme that transmits multiple signals simultaneously in the same frequency band over wireless channels. Based on the Shannon capacity of band-limited waveform AWGN channel with input power constraint, we obtain channel capacity of WSDM. Compared to time division multiplexing (TDM), frequency division multiplexing (FDM), and code division multiplexing (CDM), WSDM is more effective in raising spectrum efficiency. What’s more, we propose information optimization method to separate time-frequency mixed signals. Computer simulations also verify that the proposed method is feasible and performs better than traditional algorithms.

Preliminary Analysis of the Protection of Privacy in the Information Network Age

The development and appli- cation of modern computer information and network technology is a double- edged sword. On the one hand, thanks to the rapid and convenient spread and exchange of computer- ized information and the compressed time and space on the Internet, computerized information plays a positive role in many areas like the economy, culture, education, sci- ence and technology, and politics. On the other hand, it also leads to various online rights infringements： citizens＇ individual information is revealed online; personal comput- ers are hacked; and online shopping lists are copied. Many Internet users worry about these problems to some extent. Especially in recent years, as information technology has devel- oped rapidly, people＇s online privacy rights have faced unprecedented challenges. How to strengthen pro- tection of online individual privacy has become an important challenge to the healthy development of informa- tion networks.

Study on information utility

Information has two aspects. One aspect is the objective one; another aspect is the subjective one. Shannon has discussed the objective aspect of information in information theory. But the subjective aspect of information has not been fully discussed. Someone use “Bayesian approaches” to evaluate the value of information. But in some cases it does not meet the information user＇s need. This paper is focus on the subjective aspect of objectively measurable information and gives formal definitions for information, information utility, and marginal information utility, normalized calculation of information utility. The information discussed in the paper has interdisciplinary nature. This work can be the foundation of many application areas.

The Hidden-Layers Topology Analysis of Deep Learning Models in Survey for Forecasting and Generation of the Wind Power and Photovoltaic Energy

As wind and photovoltaic energy become more prevalent,the optimization of power systems is becoming increasingly crucial.The current state of research in renewable generation and power forecasting technology,such as wind and photovoltaic power(PV),is described in this paper,with a focus on the ensemble sequential LSTMs approach with optimized hidden-layers topology for short-term multivariable wind power forecasting.The methods for forecasting wind power and PV production.The physical model,statistical learningmethod,andmachine learning approaches based on historical data are all evaluated for the forecasting of wind power and PV production.Moreover,the experiments demonstrated that cloud map identification has a significant impact on PV generation.With a focus on the impact of photovoltaic and wind power generation systems on power grid operation and its causes,this paper summarizes the classification of wind power and PV generation systems,as well as the benefits and drawbacks of PV systems and wind power forecasting methods based on various typologies and analysis methods.

A bibliometric analysis of research on nursing models in countries other than China

Objectives＂ To deepen our understanding of the status quo and to identify the hot topics and develop- mental trends of research on nursing models in countries other than China in the most recent decade. Methods： The study subjects were the publications retrieved from the PubMed database using the MeSH terms of ＂Models, Nursing＂. Bibliographic item co-occurrence mining system （BICOMS） software was used for conventional bibliometric analysis of publications during two time periods, 2005-2009 and 2010-2014. The number of published journal articles, journal distribution, authors of publications, country of origin of journals, and language of publications were analyzed to establish a high-frequency keyword profile and co-occurrence matrix. Graphical clustering toolkit （gCLUTO） software was applied for two-way clustering analysis and visualized analysis. Results： A total of 1472 journal articles with a key theme of nursing models were retrieved for final analysis, including 771 published during 2005-2009 and 701 during 2010-2014. The bibliometric analysis revealed that publications other than China concerning nursing models were mostly concentrated in the United States and the United Kingdom and that the number of relevant publications has been continuously decreasing. The two-way clustering analysis showed that there were mainly four types of research themes in the relevant publications in countries other than China during 2005-2009, i.e., nursing education and theoretical research, clinical nursing and psychological care, nursing administration, and models of nursing education, whereas there were five types during 2010-2014, i.e., nursing theories and clinical nursing practice, nursing administration models and assessments of nurses＇ knowledge and skills, community nursing administration models, nursing human resource management, and nursing education models and approaches. Conclusions： Research on nursing models in countries other than China is relatively mature and stable with a broader view, but it has shown a declining trend in recent years. It emphasizes both theory and practice, with research content tending to be structured into four modules, i.e., nursing education, administration, clinical practice, and theoretical research. Community nursing models may become a key research direction in the international research on nursing models in the future.

Risk Analysis of Information System Security Based on Distance of Information-State Transition

The configuration of information system security policy is directly related to the information asset risk, and the configuration required by the classified security protection is able to ensure the optimal and minimum policy in the corresponding security level. Through the random survey on the information assets of multiple departments, this paper proposes the relative deviation distance of security policy configuration as risk measure parameter based on the distance of information-state transition（DIT） theory. By quantitatively analyzing the information asset weight, deviation degree and DIT, we establish the evaluation model for information system. With example analysis, the results prove that this method conducts effective risk evaluation on the information system intuitively and reliably, avoids the threat caused by subjective measurement, and shows performance benefits compared with existing solutions. It is not only theoretically but also practically feasible to realize the scientific analysis of security risk for the information system.

Using information flow analysis to detect implicit information leaks for web service composition

Information leak,which can undermine the compliance of web-service-composition business processes for some policies,is one of the major concerns in web service composition.We present an automated and effective approach for the detection of implicit information leaks in business process execution language(BPEL)based on information flow analysis.We introduce an adequate meta-model for BPEL representation based on a Petri net for transformation and analysis.Building on the concept of Petri net place-based noninterference,the core contribution of this paper is the application of a Petri net reachability graph to estimate Petri net interference and thereby to detect implicit information leaks in web service composition.In addition,a case study illustrates the application of the approach on a concrete workflow in BPEL notation.

A genetic diversity assessment of starch quality traits in rice landraces from the Taihu basin,China

There are nearly 1 000 rice landrace varieties in the Taihu basin, China. To assess the genetic diversity of the rice, 24 intragenic molecular markers（representing 17 starch synthesis-related genes） were investigated in 115 Taihu basin rice landraces and 87 improved cultivars simultaneously. The results show that the average genetic diversity and polymorphism information content values of the landraces were higher than those of improved cultivars. In total, 41 and 39 allele combinations（of the 17 genes） were derived from the landraces and improved cultivars, respectively; only two identical allele combinations were found bet ween the two rice variety sources. Cluster analysis, based on the molecular markers, revealed that the rice varieties could be subdivided into five groups and, within these, the japonica improved rice and japonica landrace rice varieties were in two separate groups. According to the quality reference criteria to classify the rice into grades, some of the landraces were found to perform we ll, in terms of starch quality. For example, according to NY /T595-2002 criteria from the Ministry of Agriculture of China, 25 and 33 landraces reached grade 1, in terms of their apparent amylose content and gel consistency. Th e varieties that had outstanding quality could be used as breeding materials for rice quality breeding programs in the future. Our study is useful for future applications, such as genetic diversity studies, the protection of rice variety and improvment of rice quality in breeding programs.

Sequence Information on Simple Sequence Repeats and Single Nucleotide Polymorphisms through Transcriptome Analysis of Mungbean

Mungbean （Vigna radiata （L.） Wilczek） is a unique species in its ability to fix atmospheric nitrogen, with early maturity, and relatively good drought resistance. We used 454 sequencing technology for transcriptome sequencing. A total of 150 159 and 142 993 reads produced 5 254 and 6 374 large contigs （〉_500 bp） with an average length of 833 and 853 for Sunhwa and Jangan, respectively. Functional annotation to known sequences yielded 41.34% and 41.74% unigenes for Jangan and Sunhwa. A higher number of simple sequence repeat （SSR） motifs was identified in Jangan （1 630） compared with that of Sunhwa （1 334）. A similar SSR distribution pattern was observed in both varieties. A total of 8 249 single nucleotide polymorphisms （SNPs） and indels with 2 098 high-confidence candidates were identified in the two mungbean varieties. The average distance between individual SNPs was -860 bp. Our report demonstrates the utility of transcriptomic data for implementing a functional annotation and development of genetic markers. We also provide large resource sequence data for mungbean improvement programs.

Stability-mutation feature identification of Web search keywords based on keyword concentration change ratio

Purpose: The aim of this paper is to discuss how the keyword concentration change ratio(KCCR) is used while identifying the stability-mutation feature of Web search keywords during information analyses and predictions.Design/methodology/approach: By introducing the stability-mutation feature of keywords and its significance, the paper describes the function of the KCCR in identifying keyword stability-mutation features. By using Ginsberg's influenza keywords, the paper shows how the KCCR can be used to identify the keyword stability-mutation feature effectively.Findings: Keyword concentration ratio has close positive correlation with the change rate of research objects retrieved by users, so from the characteristic of the 'stability-mutation' of keywords, we can understand the relationship between these keywords and certain information. In general, keywords representing for mutation fit for the objects changing in short-term, while those representing for stability are suitable for long-term changing objects. Research limitations: It is difficult to acquire the frequency of keywords, so indexes or parameters which are closely related to the true search volume are chosen for this study.Practical implications: The stability-mutation feature identification of Web search keywords can be applied to predict and analyze the information of unknown public events through observing trends of keyword concentration ratio.Originality/value: The stability-mutation feature of Web search could be quantitatively described by the keyword concentration change ratio(KCCR). Through KCCR, the authors took advantage of Ginsberg's influenza epidemic data accordingly and demonstrated how accurate and effective the method proposed in this paper was while it was used in information analyses and predictions.

Geo-spatial information and technologies in support of EU crisis management

This paper discusses the challenges in operational crisis management and describes the role of information and geo-spatial technologies in meeting those challenges.The paper discusses two main sources of data,Web and very high resolution(VHR)earth observation sensors,in terms of relevance to crisis management and techniques for information extraction and analysis.Although research in information text extraction and analysis is more advanced than in information image extraction and analysis,further research is required in both these fields to take advantage of the increasing complexity but richness of open source and VHR satellite data.The paper also discusses the use of Web,GIS and Digital Earth technologies in facilitating collaborative work,decision-making and information sharing in crisis management.Despite exciting and relevant advances in information sources,information extraction and analysis methods,and collaborative crisis technologies,the main challenge remains to convince stakeholders in operational crisis management that the adoption of these technologies will lead to enhanced and effective crisis management.

Contribution of the MERISE-Type Conceptual Data Model to the Construction of Monitoring and Evaluation Indicators of the Effectiveness of Training in Relation to the Needs of the Labor Market in the Republic of Congo

This study proposes the use of the MERISE conceptual data model to create indicators for monitoring and evaluating the effectiveness of vocational training in the Republic of Congo. The importance of MERISE for structuring and analyzing data is underlined, as it enables the measurement of the adequacy between training and the needs of the labor market. The innovation of the study lies in the adaptation of the MERISE model to the local context, the development of innovative indicators, and the integration of a participatory approach including all relevant stakeholders. Contextual adaptation and local innovation: The study suggests adapting MERISE to the specific context of the Republic of Congo, considering the local particularities of the labor market. Development of innovative indicators and new measurement tools: It proposes creating indicators to assess skills matching and employer satisfaction, which are crucial for evaluating the effectiveness of vocational training. Participatory approach and inclusion of stakeholders: The study emphasizes actively involving training centers, employers, and recruitment agencies in the evaluation process. This participatory approach ensures that the perspectives of all stakeholders are considered, leading to more relevant and practical outcomes. Using the MERISE model allows for: • Rigorous data structuring, organization, and standardization: Clearly defining entities and relationships facilitates data organization and standardization, crucial for effective data analysis. • Facilitation of monitoring, analysis, and relevant indicators: Developing both quantitative and qualitative indicators helps measure the effectiveness of training in relation to the labor market, allowing for a comprehensive evaluation. • Improved communication and common language: By providing a common language for different stakeholders, MERISE enhances communication and collaboration, ensuring that all parties have a shared understanding. The study’s approach and contribution to existing research lie in: • Structured theoretical and practical framework and holistic approach: The study offers a structured framework for data collection and analysis, covering both quantitative and qualitative aspects, thus providing a comprehensive view of the training system. • Reproducible methodology and international comparison: The proposed methodology can be replicated in other contexts, facilitating international comparison and the adoption of best practices. • Extension of knowledge and new perspective: By integrating a participatory approach and developing indicators adapted to local needs, the study extends existing research and offers new perspectives on vocational training evaluation.