Information Management: Knowledge, Emancipation, and Metaphysics in the 21st Century

This text is trying to discuss an approximation to the concept of human emancipation,as part of our well-being,in terms of Education and Knowledge.Without abandoning our metaphysical perception of wholeness,as an extension of the continuity principle which connects our conscious and unconscious world,emancipation is considered as a personal struggle against all oppressions.Some of these are grounded in our inner world.In accordance with the Enlightenment request,reasoning and knowledge can help us to structure new forms of acceptances which are shaping our own emancipatory meaning.Under the impact of social influence and personal interpretation,the perceived knowledge is considered as a mental tool containing an upgraded valid information.Taking under consideration that this validity is not able to overcome the metaphysical origins of human thought,it is suggested that when this mental tool is functioning in a self-transformative,self-constructed,and flexible form,human intelligence is structuring a compatible information management mechanism,which can enable us to formulate our personal acceptances,bridge our empirical and hyper-empirical inner world,and enlighten our request for self-criticism,self-determination,and above all emancipation.

Transformation and influencing factors of scholarly communication based on knowledge transfer: A case study of science and technology literature

Purpose: The process of scientific literature use can be regarded as that of knowledge transfer. With the help of the knowledge transfer theory and data from scientific literature databases, we explored the behavior of scientific researchers during their scholarly communication, and studied the factors that influenced the behavior of researchers under network environment. Design/methodology/approach: Based on the literature databases of CNKI, Elsevier Science Direct and Springer Link, we used the knowledge transfer theory to construct a model for describing the scholarly communication process, which attempts to find out factors that may influence the communication behavior of researchers. With a focus laid on the absorption behavior of researchers during the knowledge acceptance process, we defined the independent variables of the model and proposed hypotheses on the basis of a comprehensive literature study. Afterwards, college students were invited to participate in a questionnaire survey, which was designed to prove our research model and hypotheses.Findings: Our results showed that during the scholarly communication, it is not the professional knowledge, but the ability and willingness for knowledge acceptance, organizations’ importance and internal atmosphere as well as knowledge authority and relevance that have played a positive significant role in the knowledge transfer performance. In addition, our distance indicators showed that knowledge distance and knowledge transfer performance have significant negative correlations. Research limitations: This study is mainly based on a questionnaire survey of college students, which may limit the generalization of our research results. In addition, more resource types need be considered for further studies.Practical implications: Under network environment, scholarly communication performance based on knowledge transfer theory could greatly contribute to the enrichment of the contentof the knowledge transfer theory, and stretch out the range of the field. In addition, our result could help commercial scientific database providers to learn more about the users’ needs, which would not only benefit both scientific communities and content providers, but also promote scholarly communication effectively. Originality/value: Compared with existing researches which mainly emphasized the model construction of scholarly communication, our study focused the knowledge relevance during the scholarly communication and influence factors that impacted on the performance of knowledge acceptance under the network environment, which could provide helpful guides for further studies.

Digital Communication： The Conflicts in the Transmission and Distribution of Information in the Era of Knowledge Economy

This article analyzes the concentration of production and distribution of information, from the analysis of the news in major international news agencies.The biopolitics is more and more interconnected to social, cultural, economical, and political matters, which led us to see in the contemporary scenario the creation of new forms of social organization which will determine how we interact with each other and how we face the world. Additionally, questions emerge about the usage of the means of communication, particularly those related to Technology of Communication and Information （TICs）. The influence of the media over the social-cultural activities tends to create homogenizations of senses, aiming a planetary visibility in a process that can not only disfigure but destroy many symbolic representations and cultural forms. On the other hand, globalization tends to, instead of minimize the differences in the world, ended up creating new conflicts that, through the usage of new technologies of communication, expresses and articulate themselves.

A case study on knowledge communication based on friends-list links in the science blogging community at Sciencenet.cn

Sciencenet.cn is the leading online portal serving the Chinese scientific community. This paper intends to analyze the interdisciplinary and intradisciplinary knowledge communication patterns based on friends-list links in the blog community at Sciencenet.cn by using hyperlink analysis and social network analysis. The major findings are: 1) More bloggers have an academic background in management science and life science; 2) there are some core actors in co-inlink network and co-outlink network, who take the lead in engaging with knowledge exchange activities and produce a great influence on interdisciplinary communication; 3) interactive relationships commonly exist between a blogger and those on his/her friends list, and the most linked-to blogs usually play a key role in generating interactive communication; 4) management science has the highest co-inlink count with life science or information science and it has the highest co-outlink count with life science or mathematical and physical science; 5) management science and life science have the greatest impact on information science and the interdisciplinary knowledge communication will also produce relatively significant influence on the development of information science discipline. It is our hope that this research can serve as a reference source for the future studies of academic virtual communities, and the development of mechanisms for facilitating increased engagement in knowledge exchange activities in academic virtual communities.

Application of graph neural network and feature information enhancement in relation inference of sparse knowledge graph

At present,knowledge embedding methods are widely used in the field of knowledge graph(KG)reasoning,and have been successfully applied to those with large entities and relationships.However,in research and production environments,there are a large number of KGs with a small number of entities and relations,which are called sparse KGs.Limited by the performance of knowledge extraction methods or some other reasons(some common-sense information does not appear in the natural corpus),the relation between entities is often incomplete.To solve this problem,a method of the graph neural network and information enhancement is proposed.The improved method increases the mean reciprocal rank(MRR)and Hit@3 by 1.6%and 1.7%,respectively,when the sparsity of the FB15K-237 dataset is 10%.When the sparsity is 50%,the evaluation indexes MRR and Hit@10 are increased by 0.8%and 1.8%,respectively.

Knowledge, Attitudes, Practices, and Perceptions for Salt/Sodium Reduction in the Gastronomic Sector of Costa Rica

Excess sodium intake is associated with high blood pressure and cardiovascular diseases. This study examined food services in Costa Rica as a major source of sodium. The research included six cafeterias, six fast food establishments, 13 restaurants, and 15 diners using non-probabilistic convenience sampling. Interviews were conducted with workers to assess knowledge, attitudes, and practices regarding salt reduction. The findings were analyzed to determine effective intervention strategies. Participants showed regular knowledge about salt/sodium. While they recognized the link with high blood pressure, understanding of other health problems was limited. Positive attitudes were observed toward healthy cooking and reducing sodium in pre-prepared food, especially in restaurants. Over 70% expressed a desire to reduce salt in food services, with more than 80% indicating a need for staff training, particularly in cafeterias lacking knowledge of low-salt preparations. High-sodium ingredients were prevalent, with saltshakers and sauces readily available. However, some individuals were reluctant to reduce salt/sodium intake, citing concerns about taste, food variety, and customer complaints. Obstacles to reducing salt/sodium levels included limited accessibility and the cost of low-sodium ingredients. The data collection tools and methodologies used in this study can serve as a foundation for future investigations and strategies to reduce salt consumption in food services. The study recommends government support for transforming the gastronomic sector and implementing regulations and knowledge enhancement. Collaboration with the productive sector is crucial for creating healthy environments. This research presents valuable evidence regarding the utilization of salt and sodium in the gastronomic sector, thereby assisting in the decision-making process for public health initiatives and the prevention of non-communicable chronic diseases. It highlights the significance of tackling sodium reduction in food services to encourage the adoption of healthy culinary practices and enhance the overall health of the population.

GoPubMed与Web of Knowledge分析工具Analyze Results的比较研究

GoPubMed是基于本体论的生物医学文献分析工具,它可以对检索到的PubMed文献进行全方位的统计分析,Web of Knowlegde平台的Analyze Results分析功能也可对检索结果进行统计分析。对这2种文献分析工具特点进行对比分析。

Product-design knowledge retrieval based on ontology

In order to improve the utilization ratio of knowledge retrieval, a product-design knowledge retrieval approach based on ontology is proposed. A representation model of product-design knowledge is proposed according to its characteristics. Domain ontology of product-design is estab- lished and the semantic annotation technology is used to connect the design knowledge and ontolo- gy. A new semantic annotation format is developed and semantic information of the design knowl- edge is enriched by making use of ontology. On that basis a retrieval algorithm is designed for semantic retrieval. Finally, this approach is used in a knowledge management system for military-vehi- cle design and its effectiveness and feasibility are validated. Results show that the recall ratio and the precision ratio of knowledge retrieval are improved greatly and users＇ requirements in semantic retrieval are satisfied.

Effects of the information–knowledge–attitude–practice nursing model combined with predictability intervention on patients with cerebrovascular disease

BACKGROUND Cerebrovascular disease(CVD)poses a serious threat to human health and safety.Thus,developing a reasonable exercise program plays an important role in the long-term recovery and prognosis for patients with CVD.Studies have shown that predictive nursing can improve the quality of care and that the information–knowledge–attitude–practice(IKAP)nursing model has a positive impact on patients who suffered a stroke.Few studies have combined these two nursing models to treat CVD.AIM To explore the effect of the IKAP nursing model combined with predictive nursing on the Fugl–Meyer motor function(FMA)score,Barthel index score,and disease knowledge mastery rate in patients with CVD.METHODS A total of 140 patients with CVD treated at our hospital between December 2019 and September 2021 were randomly divided into two groups,with 70 patients in each.The control group received routine nursing,while the observation group received the IKAP nursing model combined with predictive nursing.Both groups were observed for self-care ability,motor function,and disease knowledge mastery rate after one month of nursing.RESULTS There was no clear difference between the Barthel index and FMA scores of the two groups before nursing(P>0.05);however,their scores increased after nursing.This increase was more apparent in the observation group,and the difference was statistically significant(P<0.05).The rates of disease knowledge mastery,timely medication,appropriate exercise,and reasonable diet were significantly higher in the observation group than in the control group(P<0.05).The satisfaction rate in the observation group(97.14%)was significantly higher than that in the control group(81.43%;P<0.05).CONCLUSION The IKAP nursing model,combined with predictive nursing,is more effective than routine nursing in the care of patients with CVD,and it can significantly improve the Barthel index and FMA scores with better knowledge acquisition,as well as produce high satisfaction in patients.Moreover,they can be widely used in the clinical setting.

转变研究模式 推动知识创新——新一代学术信息资源整合体系ISI Web of Knowledge评介

介绍了ISI Web of Knowledge基于知识管理的学术信息资源整合的特点和各项功能,指出其通过学术信息大规模聚合、统一平台处理、分析评价功能以及由超链接构成的体系化的知识,实现了学术信息流管理的四大愿景:开创个体研究者与人类知识总合的崭新关系,集成科研信息活动的全过程(检索、分析、管理、发现),营造集资源、工具与技术为一体的新型合作研究环境,将传统数据库系统转化为创新平台,实现了由"支撑"科研向"引领"科研的跨越。

Implicit Knowledge, Explicit Knowledge and Interaction in the College English Teaching

In each act or process of knowledge, all components can be classified into two kinds: tacit (implicit) components and focal (explicit) components. This article, first of all introduces the terms of implicit knowledge, explicit knowledge and their distinctions in the process of English language learning and then provides interactive instruction design to improve learners' communicative competence.

Collaborative Tools and Techniques of Knowledge Sharing: A Literature Review

Nowadays, the world is frequently referred to as the “information world”. Companies rely on knowledge to differentiate themselves and get a competitive advantage. As a result, businesses pay close attention to knowledge management and devote a significant amount of time and resources to ensuring that knowledge is appropriately owned and exploited. Individual knowledge transfer is also a factor. The paper examines knowledge transfer and sharing, with the goal of determining the most effective internal communication tool for information transfer. The research findings should aid company management in organizing internal communication in a way that allows them to carry out their knowledge management plan.

A discussion of the emotive element of knowledge service practice:An empirical study at the Chinese Academy of Sciences

With the arrival of the information age, research activities focused on the practice and approaches of knowledge services are on a marked increase as evidenced in the publications of social sciences. According to a social network analysis on knowledge service related literature, it reveals that information and knowledge workers often fail to take such an important element as the functional role of an emotive engagement into consideration in their study of knowledge services. It has increasingly become an issue of high profile with the rapid development of digital libraries and their web-based knowledge services in China and anywhere else in the world. In order to have a clearer understanding about issues involved in knowledge servicing so as to maximize the effectiveness and efficiency of digital libraries in their knowledge service performance, the author has conducted surveys for seven times on the online information seeking behavior of graduate students at the Chinese Academy of Sciences with such research methods as questionnaires, interviews and natural observations during September 2006-June 2009. The research result has showed the emotive element has an important role in the user's information seeking behavior and in knowledge services practice. Therefore, knowledge services rendered may be more effective by adding the emotiveness-oriented communication element into such practice. This paper recommends that such an emotiveness-oriented communication approach should be carefully studied and factored into libraries' knowledge services practice.

Dynamic Spectrum Access Based on Prior Knowledge Enabled Reinforcement Learning with Double Actions in Complex Electromagnetic Environment

The spectrum access problem of cognitive users in the fast-changing dynamic interference spectrum environment is addressed in this paper.The prior knowledge for the dynamic spectrum access is modeled and a reliability quantification scheme is presented to guide the use of the prior knowledge in the learning process.Furthermore,a spectrum access scheme based on the prior knowledge enabled RL(PKRL)is designed,which effectively improved the learning efficiency and provided a solution for users to better adapt to the fast-changing and high-density electromagnetic environment.Compared with the existing methods,the proposed algorithm can adjust the access channel online according to historical information and improve the efficiency of the algorithm to obtain the optimal access policy.Simulation results show that,the convergence speed of the learning is improved by about 66%with the invariant average throughput.

Extracting and Measuring Uncertain Biomedical Knowledge from Scientific Statements

Purpose:Given the information overload of scientific literature,there is an increasing need for computable biomedical knowledge buried in free text.This study aimed to develop a novel approach to extracting and measuring uncertain biomedical knowledge from scientific statements.Design/methodology/approach:Taking cardiovascular research publications in China as a sample,we extracted subject-predicate-object triples(SPO triples)as knowledge units and unknown/hedging/conflicting uncertainties as the knowledge context.We introduced information entropy(IE)as potential metric to quantify the uncertainty of epistemic status of scientific knowledge represented at subject-object pairs(SO pairs)levels.Findings:The results indicated an extraordinary growth of cardiovascular publications in China while only a modest growth of the novel SPO triples.After evaluating the uncertainty of biomedical knowledge with IE,we identified the Top 10 SO pairs with highest IE,which implied the epistemic status pluralism.Visual presentation of the SO pairs overlaid with uncertainty provided a comprehensive overview of clusters of biomedical knowledge and contending topics in cardiovascular research.Research limitations:The current methods didn’t distinguish the specificity and probabilities of uncertainty cue words.The number of sentences surrounding a given triple may also influence the value of IE.Practical implications:Our approach identified major uncertain knowledge areas such as diagnostic biomarkers,genetic polymorphism and co-existing risk factors related to cardiovascular diseases in China.These areas are suggested to be prioritized;new hypotheses need to be verified,while disputes,conflicts,and contradictions need to be settled.Originality/value:We provided a novel approach by combining natural language processing and computational linguistics with informetric methods to extract and measure uncertain knowledge from scientific statements.

Knowledge and Skills for Management of Sexually Transmitted Infections by Rural Medical Practitioners in Bangladesh

Sexually transmitted infection (STI) management is considered rudimentary among rural medical practitioners (RMPs) in Bangladesh. We sought to understand the level of knowledge and skills in STI management and to assess the impact of a two-day training orientation among RMPs in Tangail district. Data were collected through a baseline survey of 225 practicing RMPs in the study area and a three-month follow-up survey of 99 RMPs who participated in a two-day STI/HIV orientation training. The level of formal training among RMPs ranged from none (22.7%), to paramedical training (14.7%) and local medical assistant training (62.6%). The baseline survey revealed a low level of STI/HIV knowledge and misconceptions about the transmission of STI/HIV among RMPs. RMPs mostly prescribed first line antibiotics for treatment of common reproductive tract infections (RTIs) including STIs, but they rarely prescribed the correct dosages according to the national RTI/STI management guidelines. Only 3% of RMPs were able to correctly answer all four HIV transmission (unprotected sexual intercourse, blood transfusion, needle sharing and mother to child transmission) questions at baseline, while 94.9% of RMPs answered all four correctly at three months following the training (p = 0.001). Only 10% of RMPs reported suggesting the recommended drug (azithromycin) and only 2% mentioned about the recommended dosage (2 gm single dose) for the treatment of urethritis/cervicitis;compared to 49.5% suggested azithromycin at follow-up with 39.4% mentioned the recommended 2 gm single dose (p = 0.001). Our study found low level of knowledge and poor practices related RTI/STI management among RMPs. Short orientation training and education intervention shown promise to increase knowledge and management skills for RTIs/STIs.

Knowledge Fusion and Synchronization over Ubiquitous Ontology Mapping

With the rapid development and popularization of web services, the available information types and structure are becoming more and more complex and challenging. Actually web services involve the need for dynamic integration and transparent knowledge integration, in light of the urgent information changing track. Under this situation, the traditional search engine and information integration cannot finish this challenge, thereby bringing the opportunity for knowledge fusion and synchronization. This paper proposes a multi-matching strategy ontology mapping method for web information, i.e., ubiquitous ontology mapping method (U-Mapping), which can be viewed as a base collection of information on multiple ontologies made to appear anytime and everywhere. This approach is usually built independently by different information providers, avoiding the grammatical and semantic conflict. Finally, the ontology case information can be utilized under the consolidation of the U-Mapping, concerning language technology and machine learning methods.

Ontology Based Ocean Knowledge Representation for Semantic Information Retrieval

The drastic growth of coastal observation sensors results in copious data that provide weather information.The intricacies in sensor-generated big data are heterogeneity and interpretation,driving high-end Information Retrieval(IR)systems.The Semantic Web(SW)can solve this issue by integrating data into a single platform for information exchange and knowledge retrieval.This paper focuses on exploiting the SWbase systemto provide interoperability through ontologies by combining the data concepts with ontology classes.This paper presents a 4-phase weather data model:data processing,ontology creation,SW processing,and query engine.The developed Oceanographic Weather Ontology helps to enhance data analysis,discovery,IR,and decision making.In addition to that,it also evaluates the developed ontology with other state-of-the-art ontologies.The proposed ontology’s quality has improved by 39.28%in terms of completeness,and structural complexity has decreased by 45.29%,11%and 37.7%in Precision and Accuracy.Indian Meteorological Satellite INSAT-3D’s ocean data is a typical example of testing the proposed model.The experimental result shows the effectiveness of the proposed data model and its advantages in machine understanding and IR.

Knowledge-based bridge detection from SAR images

Automatic bridge detection is an important application of SAR images. Differed from the classical CFAR method, a new knowledge-based bridge detection approach is proposed. The method not only uses the backscattering intensity difference between targets and background but also applies the contextual information and spatial relationship between objects. According to bridges＇ special characteristics and scattering properties in SAR images, the new knowledge-based method includes three processes： river segmentation, potential bridge areas detection and bridge discrimination. The application to AIRSAR data shows that the new method is not sensitive to rivers＇ shape. Moreover, this method can detect bridges successfully when river segmentation is not very exact and is more robust than the radius projection method.

Tunable structure priors for Bayesian rule learning for knowledge integrated biomarker discovery

AIM To develop a framework to incorporate background domain knowledge into classification rule learning for knowledge discovery in biomedicine.METHODS Bayesian rule learning(BRL) is a rule-based classifier that uses a greedy best-first search over a space of Bayesian belief-networks(BN) to find the optimal BN to explain the input dataset, and then infers classification rules from this BN. BRL uses a Bayesian score to evaluate the quality of BNs. In this paper, we extended the Bayesian score to include informative structure priors, which encodes our prior domain knowledge about the dataset. We call this extension of BRL as BRL_p. The structure prior has a λ hyperparameter that allows the user to tune the degree of incorporation of the prior knowledge in the model learning process. We studied the effect of λ on model learning using a simulated dataset and a real-world lung cancer prognostic biomarker dataset, by measuring the degree of incorporation of our specified prior knowledge. We also monitored its effect on the model predictive performance. Finally, we compared BRL_p to other stateof-the-art classifiers commonly used in biomedicine.RESULTS We evaluated the degree of incorporation of prior knowledge into BRL_p, with simulated data by measuring the Graph Edit Distance between the true datagenerating model and the model learned by BRL_p. We specified the true model using informative structurepriors. We observed that by increasing the value of λ we were able to increase the influence of the specified structure priors on model learning. A large value of λ of BRL_p caused it to return the true model. This also led to a gain in predictive performance measured by area under the receiver operator characteristic curve(AUC). We then obtained a publicly available real-world lung cancer prognostic biomarker dataset and specified a known biomarker from literature [the epidermal growth factor receptor(EGFR) gene]. We again observed that larger values of λ led to an increased incorporation of EGFR into the final BRL_p model. This relevant background knowledge also led to a gain in AUC.CONCLUSION BRL_p enables tunable structure priors to be incorporated during Bayesian classification rule learning that integrates data and knowledge as demonstrated using lung cancer biomarker data.