Improving the Effectiveness of Image Classification Structural Methods by Compressing the Description According to the Information Content Criterion

The research aims to improve the performance of image recognition methods based on a description in the form of a set of keypoint descriptors.The main focus is on increasing the speed of establishing the relevance of object and etalon descriptions while maintaining the required level of classification efficiency.The class to be recognized is represented by an infinite set of images obtained from the etalon by applying arbitrary geometric transformations.It is proposed to reduce the descriptions for the etalon database by selecting the most significant descriptor components according to the information content criterion.The informativeness of an etalon descriptor is estimated by the difference of the closest distances to its own and other descriptions.The developed method determines the relevance of the full description of the recognized object with the reduced description of the etalons.Several practical models of the classifier with different options for establishing the correspondence between object descriptors and etalons are considered.The results of the experimental modeling of the proposed methods for a database including images of museum jewelry are presented.The test sample is formed as a set of images from the etalon database and out of the database with the application of geometric transformations of scale and rotation in the field of view.The practical problems of determining the threshold for the number of votes,based on which a classification decision is made,have been researched.Modeling has revealed the practical possibility of tenfold reducing descriptions with full preservation of classification accuracy.Reducing the descriptions by twenty times in the experiment leads to slightly decreased accuracy.The speed of the analysis increases in proportion to the degree of reduction.The use of reduction by the informativeness criterion confirmed the possibility of obtaining the most significant subset of features for classification,which guarantees a decent level of accuracy.

An Information Content and Set of Common Superconcepts-Based Algorithm to Estimate Similarity between Concepts of Ontologies

Ontologies have been used for several years in life sciences to formally represent concepts and reason about knowledge bases in domains such as the semantic web, information retrieval and artificial intelligence. The exploration of these domains for the correspondence of semantic content requires calculation of the measure of semantic similarity between concepts. Semantic similarity is a measure on a set of documents, based on the similarity of their meanings, which refers to the similarity between two concepts belonging to one or more ontologies. The similarity between concepts is also a quantitative measure of information, calculated based on the properties of concepts and their relationships. This study proposes a method for finding similarity between concepts in two different ontologies based on feature, information content and structure. More specifically, this means proposing a hybrid method using two existing measures to find the similarity between two concepts from different ontologies based on information content and the set of common superconcepts, which represents the set of common parent concepts. We simulated our method on datasets. The results show that our measure provides similarity values that are better than those reported in the literature.

New Hybrid AD Methodology for Minimizing the Total Amount of Information Content:A Case Study of Rehabilitation Robot Design

Converting customer needs into specific forms and providing consumers with services are crucial in product design.Currently,conversion is no longer difficult due to the development of modern technology,and various measures can be applied for product realization,thus increasing the complexity of analysis and evaluation in the design process.The focus of the design process has thus shifted from problem solving to minimizing the total amount of information content.This paper presents a New Hybrid Axiomatic Design(AD)Methodology based on iteratively matching and merging design parameters that meet the independence axiom and attribute constraints by applying trimming technology,the ideal final results,and technology evolution theory.The proposed method minimizes the total amount of information content and improves the design quality.Finally,a case study of a rehabilitation robot design for hemiplegic patients is presented.The results indicate that the iterative matching and merging of related attributes can minimize the total amount of information content,reduce the cost,and improve design efficiency.Additionally,evolutionary technology prediction can ensure product novelty and improve market competitiveness.The methodology provides an excellent way to design a new(or improved)product.

Information content of index inclusions： Evidence from China

This paper examines whether index inclusion has information content and the downward-sloping demand curve hypothesis in China. We investigate the stock price and volume effects when stocks are included in two major stock indexes, the Shanghai Stock Exchange 30 Index （SH30） and the Shenzhen Component 40 Index （SZ40）. Furthermore, we also study the performance changes after index inclusion. We find significant price and volume increases for the stocks selected by the SH30 when the index was created and announced. Thus, the original inclusion may not be an information-free event. For subsequent index inclusions, we observe significant abnormal returns but not abnormal trade volume around the announcement date. However, the stock returns quickly reversed at the post-announcement period. Moreover, the financial performance of index included firms does not improve. The evidence does not support the price pressure hypothesis in China.

Quality of Provisions for Bad Debts and Earnings Information Contents

We measure the quality of provisions for bad debts, based on both the cross-sectional and time-series basis. Empirical tests show the impacts on earnings information contents, as well as on the incremental information content of cash flows.

The information content of rules and rule sets and its application

The information content of rules is categorized into inner mutual information content and outer impartation information content. Actually, the conventional objective interestingness measures based on information theory are all inner mutual information, which represent the confidence of rules and the mutual information between the antecedent and consequent. Moreover, almost all of these measures lose sight of the outer impartation information, which is conveyed to the user and help the user to make decisions. We put forward the viewpoint that the outer impartation information content of rules and rule sets can be represented by the relations from input universe to output universe. By binary relations, the interaction of rules in a rule set can be easily represented by operators： union and intersection. Based on the entropy of relations, the outer impartation information content of rules and rule sets are well measured. Then, the conditional information content of rules and rule sets, the independence of rules and rule sets and the inconsistent knowledge of rule sets are defined and measured. The properties of these new measures are discussed and some interesting results are proven, such as the information content of a rule set may be bigger than the sum of the information content of rules in the rule set, and the conditional information content of rules may be negative. At last, the applications of these new measures are discussed. The new method for the appraisement of rule mining algorithm, and two rule pruning algorithms, λ-choice and RPClC, are put forward. These new methods and algorithms have predominance in satisfying the need of more efficient decision information.

Identifying M&A targets and the information content of VC/PEs

The information gap in the M&A market hinders acquirers from effectively identifying high-quality targets. We examine whether VC/PEs convey information content in the M&A market and whether acquirers can use such information to identify high-quality targets. We show that VC/PEs have significant information content and can signal high-quality target companies via ‘‘certification". When acquirers lack acquisition experience and targets are located in inferior information environments, VC/PE ‘‘certification" is more significant.The better reputation a VC/PE has, the more information it conveys. Syndicate VC/PEs convey stronger information than independent VC/PEs. We also find that acquirers do not pay higher premiums for high-quality targets. Overall, our results suggest that VC/PEs have value relevance in the M&A market,confirming their ‘‘certification" role. We present means for acquirers to select high-quality targets and investors to build efficient portfolios.

Comparative Analysis of Splice Site Regions by Information Content

We have applied concepts from information theory for a comparative analysis of donor （gt） and acceptor （ag） splice site regions in the genes of five different organisms by calculating their mutual information content （relative entropy） over a selected block of nucleotides. A similar pattern that the information content decreases as the block size increases was observed for both regions in all the organisms studied. This result suggests that the information required for splicing might be contained in the consensus of -6-8 nt at both regions. We assume from our study that even though the nucleotides are showing some degrees of conservation in the flanking regions of the splice sites, certain level of variability is still tolerated, which leads the splicing process to occur normally even if the extent of base pairing is not fully satisfied. We also suggest that this variability can be compensated by recognizing different splice sites with different spliceosomal factors.

Glacial debris flow susceptibility mapping based on combined models in the Parlung Tsangpo Basin,China

Machine learning(ML)-based prediction models for mapping hazard(e.g.,landslide and debris flow)susceptibility have been widely developed in recent research.However,in some specific areas,ML models have limited application because of the uncertainties in identifying negative samples.The Parlung Tsangpo Basin exemplifies a region prone to recurrent glacial debris flows(GDFs)and is characterized by a prominent landform featuring deep gullies.Considering the limitations of the ML model,we developed and compared two combined statistical models(FA-WE and FA-IC)based on factor analysis(FA),weight of evidence(WE),and the information content(IC)method.The final GDF susceptibility maps were generated by selecting 8 most important static factors and considering the influence of precipitation.The results show that the FA-IC model has the best performance.The areas with a very high susceptibility to GDFs are primarily located in the narrow valley section upstream,on both sides of the valley in the middle and downstream of the Parlung Tsangpo River,and in the narrow valley section of each tributary.These areas encompass 86 gullies and are characterized as"narrow and steep".

The Link Between Internet Financial Reporting and Information Asymmetry for American Depository Receipts

We provide evidence on the effect of the presentation format and information content of Internet financial reporting on the market value of American Depository Receipts and on country-specific variables that drive Internet financial reporting. A two-stage Heckman approach was used to determine if Internet financial reporting adds incremental value to firms beyond the decision to cross-list in the United States. The results indicate that investors more highly value firms that provide information in multiple formats. We also find that country-specific variables affect the information content, but not the presentation format of disclosures on corporate websites. The results uncover a disconnection between what the market values （presentation format） and what the firms believe the market values （information content）. This implies that firms are not entirely aware of investors＇ information wants and that they are not utilizing their resources in the manner that will have the most impact on their market value.

政策工具视角下的省级基础教育信息化政策文本分析

目前,虽然教育信息化政策研究已成为学术界关注的热点,但针对其研究多聚焦于国内外教育信息化政策比较、国家教育信息化政策文本分析等层面,对省级教育信息化政策的关注度不够。基于此,文章以9省(自治区、直辖市)公开发布的基础教育信息化政策文本为研究对象,首先在分析政策工具及其应用研究现状的基础上,构建了基于“政策工具—政策时间”的政策文本分析框架;然后通过内容编码,分析了省级基础教育信息化政策文本中政策工具选用的现状和特点;最后从政策工具的系统化设计、供给型和环境型政策工具的内部结构、需求型政策工具的使用方面,提出了基础教育信息化政策改进建议,以期为进一步优化我国省级基础教育信息化政策供给提供参考。

我国农业信息化的内涵、现状及发展对策

论述了农业信息化的涵义和内容.指出了农业信息化在新的农业技术革命中的地位与作用.阐明了我国农业信息化的研究现状,并在此基础上,提出了我国农业信息化的发展对策.参6。

数字化时代高校档案管理信息化建设

文章结合高校档案工作的实践及其特殊性,阐述了数字化时代高校进行档案管理信息化建设的必要性和应遵循的原则,并就高校档案管理信息化建设的具体内容和采取的若干策略进行了系统的论述。

Design and Implementation of Weibo Sentiment Analysis Based on LDA and Dependency Parsing

Information content security is a branch of cyberspace security. How to effectively manage and use Weibo comment information has become a research focus in the field of information content security. Three main tasks involved are emotion sentence identification and classification,emotion tendency classification,and emotion expression extraction. Combining with the latent Dirichlet allocation(LDA) model,a Gibbs sampling implementation for inference of our algorithm is presented,and can be used to categorize emotion tendency automatically with the computer. In accordance with the lower ratio of recall for emotion expression extraction in Weibo,use dependency parsing,divided into two categories with subject and object,summarized six kinds of dependency models from evaluating objects and emotion words,and proposed that a merge algorithm for evaluating objects can be accurately evaluated by participating in a public bakeoff and in the shared tasks among the best methods in the sub-task of emotion expression extraction,indicating the value of our method as not only innovative but practical.

企业管理信息化基本问题探讨

企业管理信息化是增强企业市场竞争力的客观需要。企业在实施管理信息化过程中 ,应明确信息化系统的基本构成内容 ,以最大限度地满足用户需求为目标 ,对设计、采购、制造、库存、销售、财务等业务运作进行系统整合 ,针对企业信息化存在的共性问题加以解决 ,正确处理好信息化实施中的各种关系 ,最终提高企业信息化的运作效率。

Assessment of genetic diversity in Dalbergia sissoo clones through RAPD profiling

We studied the genetic polymorphism among 29 clones of shisham （Dalbergia sissoo Roxb） belonging to different geographic regions using random amplified polymorphic DNA （RAPD） markers. Out of 30 primers used, only 20 primers generated polymorphism in amplified product. In total 232 bands were amplified with 20 primers, of which 192 （82%） were polymorphic with an average of 9.6 bands/primer. The resolving power （Rp） ranged from 2.14 （Primer 5） to 11.93 （Primer 4）. Primer 4 and Primer 3 possessed high Rp value. Polymorphism information content （PIC） ranged from 0.15 （Primer 5） to 0.37 （Primer 4）. Primer 4 amplified total 18 bands in 29 genotypes with PIC value of 0.37 hence; this set of primer was most informative. The similarity coefficient analysis revealed two clusters. The first cluster comprised of only 10 clones and the second major cluster comprised of 19 clones. The genetic similarity among 29 clones ranged from 25.86% （clone 10 and 235） to 100% （clone 19 and 59）, suggesting a wide genetic base in shisham clones.

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.

Integrated Semantic Similarity Model Based on Ontology

To solve the problem of the inadequacy of semantic processing in the intelligent question answering system, an integrated semantic similarity model which calculates the semantic similarity using the geometric distance and information content is presented in this paper. With the help of interrelationship between concepts, the information content of concepts and the strength of the edges in the ontology network, we can calculate the semantic similarity between two concepts and provide information for the further calculation of the semantic similarity between user’s question and answers in knowledge base. The results of the experiments on the prototype have shown that the semantic problem in natural language processing can also be solved with the help of the knowledge and the abundant semantic information in ontology. More than 90% accuracy with less than 50 ms average searching time in the intelligent question answering prototype system based on ontology has been reached. The result is very satisfied. Key words intelligent question answering system - ontology - semantic similarity - geometric distance - information content CLC number TP39 Foundation item: Supported by the important science and technology item of China of “The 10th Five-year Plan” (2001BA101A05-04)Biography: LIU Ya-jun (1953-), female, Associate professor, research direction: software engineering, information processing, data-base application.

教师信息化教学能力的政策内容、演进逻辑及可能走向

制定教师信息化教学能力政策,是政府、行业组织、研究者共同关注的重要问题。基于此,文章首先从政府层面的宏观政策、专业协会的标准、面向教师教育者的标准三个维度,分析了教师信息化教学能力的政策内容。随后,文章阐释了教师信息化教学能力的内在演进逻辑,即从发展整合技术的学科教学知识(Technological Pedagogical Content Knowledge,TPACK)知识到培养计算思维。最后,文章指出教师信息化教学能力将走向跨学科教学。文章还强调,教师信息化教学能力政策的制订需要考虑不同主体的利益、需求和责任,明确各主体的责、权、利,我国教师信息化教学能力的培养着力点及其未来走向可以从中得到一些启示。