Search

The search for patentability is a critical element in the patent process, and failure to find a certain relevant patent may result in costly legal consequences. This paper aims to review the studies that have been conducted in result to improve the significance efficacy of patent information retrieval, which is focused on creating techniques and methods for retrieving patent documents in response to a specific user query. The prior-art search is a crucial step in the patent retrieval process, the choice of pertinent search terms is essential to the task’s success. In this review, we develop prior-art queries derived from query patents using query expansion to pseudo relevance feedback in result of increase the retrievability of patents. The review of this literature lists numerous studies that have been done to enhance current information retrieval methods or use conventional methods at different phases of the patent retrieval task in order to achieve better results in the task. This research focuses solely on the literature on patent text and image retrieval. Given the different methods and frameworks available, as well as their limitations, there is a lot of room for further research in the field of patent retrieval techniques. [ABSTRACT FROM AUTHOR]

The study focuses on the transformation of the alimentary models of the imaginative Other. Based on the statistics of the Russian Internet queries, the authors identified a number of markers, determining the main alimentary models of the Other. They carried out a comparative analysis of the obtained in 2018-2019 (pre-Сovid-19) models with similar Post-Covid models for 2021-2022. The researchers' hypothesis is that the queries can reveal the attitude of the modern Russians to the Other, determine the criteria by which the images are formed and the factors, affecting their transformation. The study showed that interest in the Other’s food is unstable. The number of queries constantly fluctuates. Both external factors (geopolitical, etc.) and contact with the objects of foreign mass culture can influence the growth of interests. At the same time, all markers (and stereotypes) can be conditionally divided into two groups: stable (fixed for several years), and situational, determined by external factors. The long-term analysis allowed the authors to trace the increased relevance of a number of cannibalistic markers in the image of the Other, the main reason for which, according to the researchers, was the pandemic, and the subsequent decline of interest in them in 2022. We should also mention the growing interest in video content (mukbang) In our view, this interest may be indicative of the observer's desire to transcend cultural boundaries and interact more closely with the Other. It is also particularly curious that this interest is directed toward the most alert models of the Other.

Search engine queries are the starting point for studies in different fields, such as health or political science. These studies usually aim to make statements about social phenomena. However, the queries used in the studies are often created rather unsystematically and do not correspond to actual user behavior. Therefore, the evidential value of the studies must be questioned. We address this problem by developing an approach (query sampler) to sample queries from commercial search engines, using keyword research tools designed to support search engine marketing. This allows us to generate large numbers of queries related to a given topic and derive information on how often each keyword is searched for, that is, the query volume. We empirically test our approach with queries from two published studies, and the results show that the number of queries and total search volume could be considerably expanded. Our approach has a wide range of applications for studies that seek to draw conclusions about social phenomena using search engine queries. The approach can be applied flexibly to different topics and is relatively straightforward to implement, as we provide the code for querying Google Ads API. Limitations are that the approach needs to be tested with a broader range of topics and thoroughly checked for problems with topic drift and the role of close variants provided by keyword research tools.

Introduction: The institutional ethics committees (IECs) raise queries following protocol reviews. The quality of these queries would be a useful metric to assess how well the IEC executes its fundamental role of protecting participants. Methods: Queries received after the initial review and replies sent by a single research department were evaluated. A content analysis was done to identify the domains and categories of queries. We categorized these queries as administrative, ethics related, and scientific. The impact of each query in improving the science or safeguarding the rights and safety of research participants (ethics) was evaluated by two authors of this manuscript: one affiliated and the other nonaffiliated to the institute. Kappa statistics were used to evaluate for agreement between the two. Results: A total of 13 studies (investigator-initiated studies [IISs]: 7 and pharmaceutical industry-sponsored studies [PSSs]: 6) formed the final sample size for analysis. The total number of queries was 364 (IIS: 106 and PSS: 258; P < 0.001). With regard to the categories, we found n = 42 (11.54%) to be irrelevant at that stage of the review process; n = 51 (14.01%) were about information already available which the IEC had missed; n = 67 (18.41%) queries where the IEC needed paraphrasing; n = 50 (13.74%) were entirely relevant with the need for further clarification; and n = 154 (42.31%) had been missed by the investigator during the initial submission. The overall agreement between the affiliated and unaffiliated investigators was just 12.9% (P < 0.001). Conclusions: We found that approximately 25% of the queries raised by the IEC were redundant. It is our opinion that this redundancy could have been channeled into greater focus on scientific and ethical aspects of the protocol. Ongoing dialog between investigators and ethics committees may help address this. Perspectives between the affiliated and the unaffiliated investigators with regard to the relevance of queries were grossly different. [ABSTRACT FROM AUTHOR]

Much geospatial information is stored in relational databases. Relational databases provide a reliable method for managing large amounts of data while offering a combination of system performance and ease of implementation. Users interacting with these systems perform queries to them with the primary objective of retrieving information. These queries are nothing more than natural language questions about the world and how people relate to it. This article discusses the main topics related to Geographic Information Systems and their most popular tools worldwide. Relevant aspects about Database Management Systems are also explained and a comparison between Relational and NoSQL is established. In addition, the main types of queries are discussed, as well as the language in which they are made and some examples of them are shown. [ABSTRACT FROM AUTHOR]

Background: People living with dementia or other cognitive decline and their caregivers (PLWD) increasingly rely on the web to find information about their condition and available resources and services. The recent advancements in large language models (LLMs), such as ChatGPT, provide a new alternative to the more traditional web search engines, such as Google. Objective: This study compared the quality of the results of ChatGPT and Google for a collection of PLWD-related queries. Methods: A set of 30 informational and 30 service delivery (transactional) PLWD-related queries were selected and submitted to both Google and ChatGPT. Three domain experts assessed the results for their currency of information, reliability of the source, objectivity, relevance to the query, and similarity of their response. The readability of the results was also analyzed. Interrater reliability coefficients were calculated for all outcomes. Results: Google had superior currency and higher reliability. ChatGPT results were evaluated as more objective. ChatGPT had a significantly higher response relevance, while Google often drew upon sources that were referral services for dementia care or service providers themselves. The readability was low for both platforms, especially for ChatGPT (mean grade level 12.17, SD 1.94) compared to Google (mean grade level 9.86, SD 3.47). The similarity between the content of ChatGPT and Google responses was rated as high for 13 (21.7%) responses, medium for 16 (26.7%) responses, and low for 31 (51.6%) responses. Conclusions: Both Google and ChatGPT have strengths and weaknesses. ChatGPT rarely includes the source of a result. Google more often provides a date for and a known reliable source of the response compared to ChatGPT, whereas ChatGPT supplies more relevant responses to queries. The results of ChatGPT may be out of date and often do not specify a validity time stamp. Google sometimes returns results based on commercial entities. The readability scores for both indicate that responses are often not appropriate for persons with low health literacy skills. In the future, the addition of both the source and the date of health-related information and availability in other languages may increase the value of these platforms for both nonmedical and medical professionals. [ABSTRACT FROM AUTHOR]

Neuroscientists can leverage technological advances to image neural tissue across a range of different scales, potentially forming the basis for the next generation of brain atlases and circuit reconstructions at submicron resolution, using Electron Microscopy and X-ray Microtomography modalities. However, there is variability in data collection, annotation, and storage approaches, which limits effective comparative and secondary analysis. There has been great progress in standardizing interfaces for large-scale spatial image data, but more work is needed to standardize annotations, especially metadata associated with neuroanatomical entities. Standardization will enable validation, sharing, and replication, greatly amplifying investment throughout the connectomics community. We share key design considerations and a usecase developed for metadata for a recent large-scale dataset. [ABSTRACT FROM AUTHOR]

Neuroscientists can leverage technological advances to image neural tissue across a range of different scales, potentially forming the basis for the next generation of brain atlases and circuit reconstructions at submicron resolution, using Electron Microscopy and X-ray Microtomography modalities. However, there is variability in data collection, annotation, and storage approaches, which limits effective comparative and secondary analysis. There has been great progress in standardizing interfaces for large-scale spatial image data, but more work is needed to standardize annotations, especially metadata associated with neuroanatomical entities. Standardization will enable validation, sharing, and replication, greatly amplifying investment throughout the connectomics community. We share key design considerations and a usecase developed for metadata for a recent large-scale dataset.

This article describes an approach to the collection and preprocessing of data received from mobile phones for the purpose of their further processing by data mining methods, in particular using neural networks. This is a comprehensive work that was carried out using graph theory methods; parallel computing, set theory, databases, fuzzy logic methods and neural networks, mobile application design methods. The most important results of this work, which are presented in this article, are developed methods for accelerating data processing in relational and NoSQL databases, the architecture of a system for monitoring the status of patients with Parkinson's disease using mobile technologies; modules for a mobile phone for collecting patient status data; and modules based on neural networks for classifying the status of patients with Parkinson's disease. [ABSTRACT FROM AUTHOR]

A cluster of pneumonia cases of unknown aetiology was reported from Wuhan, Hubei province of China on 31st December, 2019. The World Health Organisation (WHO) declared the outbreak a Public Health Emergency of International Concern (PHEIC) on 30th January, 2020. Thereafter, it has spread through China and reached the level of a pandemic expanding to 210 countries with 77.9M confirmed cases and 1.71M deaths as per Corona virus Disease (COVID-19) situation report issued by WHO based on data received upto 23rd December, 2020. A number of questions remain unanswered regarding pathogen-associated variables for amplification dynamics, host environment and agent interaction. This short communication makes an effort to compile the information gathered from published articles of renowned journals and newsletters to explore the epidemiological characteristics of COVID-19. Hereby in this article, authors have tried to assemble the epidemiological lacunae created by the novel characteristics of the SARS-CoV-2 (Severe Acute Respiratory Syndrome-Corona Virus-2) which presently pose a rather puzzling transmission dynamics of COVID-19 that still remain unanswered.

Skyline queries are important in many application domains. In this paper, we propose a novel structure Skyline Diagram, which given a set of points, partitions the plane into a set of regions, referred to as skyline polyominos. All query points in the same skyline polyomino have the same skyline query results. Similar to $k$ k th-order Voronoi diagram commonly used to facilitate $k$ k nearest neighbor ($k$ k NN) queries, skyline diagram can be used to facilitate skyline queries and many other applications. However, it may be computationally expensive to build the skyline diagram. By exploiting some interesting properties of skyline, we present several efficient algorithms for building the diagram with respect to three kinds of skyline queries, quadrant, global, and dynamic skylines. In addition, we propose an approximate skyline diagram which can significantly reduce the space cost. Experimental results on both real and synthetic datasets show that our algorithms are efficient and scalable. [ABSTRACT FROM AUTHOR]

Data about rabbit meat production are provided from the web site of Food and Agriculture Organization of the United Nations. The mentioned information for the studied three Balkan countries (Bulgaria, Romania and Greece) has been extracted and organized in a created relational database. Different parameter queries have been used for visualization of certain subsets from the indicated database. Subsequently, they have been processed and evaluated. The article presents comparative analysis of the rabbit meat production in these Balkan countries for the period 1984-2018. Hierarchical cluster analysis has also been applied to the considered data. The grouping of the investigated indicator is discussed. The obtained results showed that the rabbit meat production in Romania increased significantly for 1984-1990. The same process was observed in Bulgaria and Greece during 1987-1997 and 1988-1993, respectively. The values of this indicator for Greece and Bulgaria are quite higher in comparison with those ones in Romania for 2006-2018. A decreasing tendency in the rabbit meat production in the listed three countries was established for the last five years of the time interval. [ABSTRACT FROM AUTHOR]

This work was supported in part by the National Natural Science Fund of China under Grant 61233011, Grant 61374006, Grant 61473086, Grant 61463008, Grant 61703100, Grant 61773118, and Grant 61773117, in part by the Major Program of National Natural Science Foundation of China under Grant 11190015, in part by the Natural Science Foundation of Jiangsu under Grant BK20131300 and Grant BK20170692, in part by the Innovation Fund of Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education, Nanjing University of Science and Technology, under Grant JYB201601, in part by the Innovation Fund of Key Laboratory of Measurement and Control of Complex Systems of Engineering, Southeast University, under Grant MCCSE2017B01, and in part by the Fundamental Research Funds for the Central Universities under Grant 2242016k30009.

A framework for private and secure communication and interaction between agents interacting in transportation services is developed. An agent, i.e. a user, can ask questions or submit queries regarding whether the other agents, i.e. drivers, use the desired road at specific times of the day in an encrypted fashion. The authors developed the framework using semi-homomorphic encryption (namely, the Paillier's encryption method) to enable the algebraic manipulation of plain data without the need for decryption using appropriate computations over the encrypted data. Strong privacy and security guarantees are proved for the agents. Subsequently, the semi-homomorphic encryption method is utilised to develop privacy-aware ride-sharing and routing algorithms without the need for disclosing the origin and destination of the user.

A rational management of defluoridation works must include surveillance of defluoride filters, estimation of individual operation periods, and on-time recharge of saturated filters. This is done best in a database, where all necessary information is included, i.e., about the client, the site, the raw water, the water analyses, the filter, its recharges, and, most importantly, its first expected date of exhaustion and recharge. Automatically, the database would produce up-to-date lists of installed filters that would need recharge and further merge E-mails to clients indicating to them the length of time their filters have been operating, offering them new recharges on time, and stating to them the prices and conditions. Our experience shows that the database and the E-mail reminders made the maintenance and the surveillance of the filters more efficient and this has contributed to a higher sustainability of defluoridation works. The principles and setup of the Defluoridation Technology Project database are explained further. It is concluded that defluoridation works can only be sustainable if managed efficiently through a database system. [ABSTRACT FROM AUTHOR]

Slow uptake of biosimilars in some regions is often attributed to a lack of knowledge combined with concerns about safety and efficacy. To alleviate physician and patient apprehensions, regulatory reviews from four major regulatory authorities (RAs) (European Medicines Agency, US Food and Drug Administration, Health Canada, and Japan Pharmaceuticals and Medical Devices Authority) across a portfolio of eight biosimilars were analyzed to provide insight into RA review focus and approach. RA queries were evaluated in an unbiased and systematic manner by major classification (Chemistry, Manufacturing and Controls [CMC], nonclinical, clinical or regulatory) and then via detailed sub-classification. There was a consistent, predominant focus on CMC from all RAs. The review focus based on sub-classification of clinical and regulatory queries was influenced by molecular complexity, with significant differences between categories (monoclonal antibody or protein) in the distribution of query topics; specifically, bioanalytical (p = 0.023), comparative safety and efficacy (p = 0.023), and statutory (including the justification of extrapolation) (p = 0.00033). Each biosimilar had a distinct distribution of clinical query topics, tailored to product-specific data. This analysis elucidated areas of heightened RA interest, and validated their application of regulatory science in the evaluation of biosimilar safety and efficacy.

Background: The complexity of drug therapies has increased the need to evaluate the drug information scientifically. In this regard, the aim of drug information centers (DICs) is to promote rational use of drugs in a health-care setting. DI pharmacists play a vital role in providing the necessary and reliable information on drugs to promote the concept of rational drug use, eventually leading to a better patient outcome. The objective of the present study was to assess the drug-related queries received by the DIC at the King Saud Medical City (KSMC) from health-care professionals working in a large tertiary care setting. Methods: A retrospective analysis was conducted from February 2016 to January 2017. Data were collected using the DI request form, available in both printed and electronic formats for use by the health-care professionals. Descriptive statistics were used to calculate frequencies and percentages. Data analysis was performed using the Statistical Package of the Social Sciences software, version 16.0. Results: The current study received a total of 139 queries that were answered by the DIC pharmacists over a period of 1 year. The majority of queries were asked by pharmacists (61.2%), followed by physicians (23.7%) and nurses (10.10%). About half of the queries were related to the dosage and administration of the drugs. Lexicomp® acted as the common resource of information. Conclusion: DIC has been instrumental in the dissemination of drug-related information to health-care professionals since its inception in February 2016, resulting in the provision of quality health care to the patients. However, based on yearly queries, there still exists a need to increase the awareness of health-care professionals about the DIC at KSMC, which will urge them to take drug consultation from DIC pharmacists and promote patient safety.

A cluster of pneumonia cases of unknown aetiology was reported from Wuhan, Hubei province of China on 31st December, 2019. The World Health Organisation (WHO) declared the outbreak a Public Health Emergency of International Concern (PHEIC) on 30th January, 2020. Thereafter, it has spread through China and reached the level of a pandemic expanding to 210 countries with 77.9M confirmed cases and 1.71M deaths as per Corona virus Disease (COVID-19) situation report issued by WHO based on data received upto 23rd December, 2020. A number of questions remain unanswered regarding pathogen-associated variables for amplification dynamics, host environment and agent interaction. This short communication makes an effort to compile the information gathered from published articles of renowned journals and newsletters to explore the epidemiological characteristics of COVID-19. Hereby in this article, authors have tried to assemble the epidemiological lacunae created by the novel characteristics of the SARS-CoV-2 (Severe Acute Respiratory Syndrome-Corona Virus-2) which presently pose a rather puzzling transmission dynamics of COVID-19 that still remain unanswered. [ABSTRACT FROM AUTHOR]

Search Engine retrieves significant and essential information from the web based on query terms given by the user. Due to the lack of background knowledge about the information required, shorter length queries posed by the user, the ambiguity of query keywords and dynamic growth of the web, irrelevant and redundant results are also retrieved by the search engine. Query recommendations is an important technique which analyze the real search intent of the user and suggests the alternative queries to be used by the user in future to satisfies their information need. The proposed method recommends and ranks the alternative queries and evaluates the ranking order of the recommendations with the help of the ranking measures Normalized Discounted Cumulative Gain (NDCG) and Coefficient of Variance (CV). These measures identify the relationship between the ranking techniques. The proposed strategies are experimentally evaluated using a real time search engine query log.

The article presents a discussion of the optimisation methods involving the modification of query syntax on the example of the use of indexes that served for the application of the methods in practice, and the presentation and analysis of the test results and their comparison. All the queries were made in a Microsoft SQL Server Management Studio 2014 environment, using the AdventureWorksDW2012 test database provided by Microsoft. The object of the research were SELECT queries, which consequently returned the desired set of output data.

Background: The complexity of drug therapies has increased the need to evaluate the drug information scientifically. In this regard, the aim of drug information centers (DICs) is to promote rational use of drugs in a health-care setting. DI pharmacists play a vital role in providing the necessary and reliable information on drugs to promote the concept of rational drug use, eventually leading to a better patient outcome. The objective of the present study was to assess the drug-related queries received by the DIC at the King Saud Medical City (KSMC) from health-care professionals working in a large tertiary care setting. Methods: A retrospective analysis was conducted from February 2016 to January 2017. Data were collected using the DI request form, available in both printed and electronic formats for use by the health-care professionals. Descriptive statistics were used to calculate frequencies and percentages. Data analysis was performed using the Statistical Package of the Social Sciences software, version 16.0. Results: The current study received a total of 139 queries that were answered by the DIC pharmacists over a period of 1 year. The majority of queries were asked by pharmacists (61.2%), followed by physicians (23.7%) and nurses (10.10%). About half of the queries were related to the dosage and administration of the drugs. Lexicomp® acted as the common resource of information. Conclusion: DIC has been instrumental in the dissemination of drug-related information to health-care professionals since its inception in February 2016, resulting in the provision of quality health care to the patients. However, based on yearly queries, there still exists a need to increase the awareness of health-care professionals about the DIC at KSMC, which will urge them to take drug consultation from DIC pharmacists and promote patient safety. [ABSTRACT FROM AUTHOR]

In this article an approach to get statistical data about ultrasound examinations, carried out in the framework of SonaRes, the decision support system for ultrasound diagnostics, is described. A list and description of respective queries for data base of patients' examinations sessions is provided to get the information interesting for ultrasonographers and the system developers.

Objective: To evaluate the various drug information queriesreceived, and to access the drug information services providedby the pharmacy practice department.Method: Drug information queries received during wardrounds, direct communication, telephone or internet etc. weredocumented in the drug information request anddocumentation forms prepared by the department over theperiod of January 2010 to June 2010. Various parameters likestatus of enquirer, their specialty, mode of receipt of query,purpose of query, type of query etc. were consider forevaluation.Results: Out of 208 queries received, major 56 (26.9%) frommale medical ward. Maximum [82 (39.4 %)] queries were fromthe physicians. 73 (35.0 %) of the queries were about therecent advances and the updating of the information, It wasfound that mostly the mode of request was during wardrounds 85 (40.9%). Most of the queries [126 (60.6%)] wereanswered by written or printout format. Majority of thequeries [195 (93.8 %)] were answered directly to theenquirers through direct access. Most of the queries wereanswered through books in the department [86 (41.3 %)].Conclusion: Results of the external auditing revealed thatrequestors were generally satisfied with the service provided.The drug information services provided by clinical pharmacistsat the hospital were found to be useful and beneficial to thehealthcare professionals and patients.

This paper examines the ways of different types inquiries to Wolfram|Alpha, in particular, the possibility of natural language queries. The characteristic of mobile access to Wolfram|Alpha are highlighted. The data representation format was considered to visual representations, images, HTML, Mathematica Cell, text view, plain text, MathML, Mathematica input, Mathematica output, audio presentation, special types of Wolfram|Alpha output. The paper aim is the analysis and synthesis of capabilities for requests to Wolfram|Alpha in many ways and opportunities to provide characteristics of mobile access to Wolfram|Alpha. The subject of the study is Wolfram|Alpha as cloud-based service of mathematics learning. In preparing the paper material used case studies and experimental research presentation capabilities of different types of requests to Wolfram|Alpha. Conclusion: Wolfram|Alpha work is based on natural language processing (currently only English), a large library of algorithms and NKS-approach to answering queries. Wolfram|Alpha does not issue a list of links based on query results, and calculates the answer based on their own knowledge base. Service is able to convert data between different measurement units, counting systems, etc.

To determine if expanded queries can be used to identify specific reportable diseases/conditions not detected by using automated syndrome categories, we developed new categories to use with the Electronic Surveillance System for the Early Notification of Community Based Epidemics. Results suggest innovative queries can enhance clinicians’ compliance with reportable disease requirements.

From sensor networks to transportation infrastructure to social networks, we are awash in data. Many of these real-world networks tend to be large ('big data') and dynamic, evolving over time. Their evolution can be modeled as a series of graphs. Traditional systems that store and analyze one graph at a time cannot effectively handle the complexity and subtlety inherent in dynamic graphs. Modern analytics require systems capable of storing and processing series of graphs. We present such a system. G* compresses dynamic graph data based on commonalities among the graphs in the series for deduplicated storage on multiple servers. In addition to the obvious space-saving advantage, large-scale graph processing tends to be I/O bound, so faster reads from and writes to stable storage enable faster results. Unlike traditional database and graph processing systems, G* executes complex queries on large graphs using distributed operators to process graph data in parallel. It speeds up queries on multiple graphs by processing graph commonalities only once and sharing the results across relevant graphs. This architecture not only provides scalability, but since G* is not limited to processing only what is available in RAM, its analysis capabilities are far greater than other systems which are limited to what they can hold in memory. This paper presents G*'s design and implementation principles along with evaluation results that document its unique benefits over traditional graph processing systems. [ABSTRACT FROM AUTHOR]

Search Engine retrieves significant and essential information from the web based on query terms given by the user. Due to the lack of background knowledge about the information required, shorter length queries posed by the user, the ambiguity of query keywords and dynamic growth of the web, irrelevant and redundant results are also retrieved by the search engine. Query recommendations is an important technique which analyze the real search intent of the user and suggests the alternative queries to be used by the user in future to satisfies their information need. The proposed method recommends and ranks the alternative queries and evaluates the ranking order of the recommendations with the help of the ranking measures Normalized Discounted Cumulative Gain (NDCG) and Coefficient of Variance (CV). These measures identify the relationship between the ranking techniques. The proposed strategies are experimentally evaluated using a real time search engine query log. [ABSTRACT FROM AUTHOR]

In this paper, we deal with the integration of multiple sources of information such as Earth observation (EO) synthetic aperture radar (SAR) images and their metadata, semantic descriptors of the image content, as well as other publicly available geospatial data sources expressed as linked open data for posing complex queries in order to support geospatial data analytics. Our approach lays the foundations for the development of richer tools and applications that focus on EO image analytics using ontologies and linked open data. We introduce a system architecture where a common satellite image product is transformed from its initial format into to actionable intelligence information, which includes image descriptors, metadata, image tiles, and semantic labels resulting in an EO-data model. We also create a SAR image ontology based on our EO-data model and a two-level taxonomy classification scheme of the image content. We demonstrate our approach by linking high-resolution TerraSAR-X images with information from CORINE Land Cover (CLC), Urban Atlas (UA), GeoNames, and OpenStreetMap (OSM), which are represented in the standard triple model of the resource description frameworks (RDFs). [ABSTRACT FROM PUBLISHER]

Abstract The data warehouse is supposed to provide storage, functionality and responsiveness to queries beyond the capabilities of today’s transaction databases. Also Data warehouse is built to improve the data access performance of databases. Resumen Los almacenes de datos se supone que proporcionan almacenamiento, funcionalidad y capacidad de repuesta a las consultas y análisis más eficiente que las bases de datos transaccionales. También el almacén de datos se construiye para mejorar el rendimiento de acceso a los datos.

Background and objective Usage of data from electronic health records (EHRs) in clinical research is increasing, but there is little empirical knowledge of the data needed to support multiple types of research these sources support. This study seeks to characterize the types and patterns of data usage from EHRs for clinical research. Materials and methods We analyzed the data requirements of over 100 retrospective studies by mapping the selection criteria and study variables to data elements of two standard data dictionaries, one from the healthcare domain and the other from the clinical research domain. We also contacted study authors to validate our results. Results The majority of variables mapped to one or to both of the two dictionaries. Studies used an average of 4.46 (range 1–12) data element types in the selection criteria and 6.44 (range 1–15) in the study variables. The most frequently used items (e.g., procedure, condition, medication) are often available in coded form in EHRs. Study criteria were frequently complex, with 49 of 104 studies involving relationships between data elements and 22 of the studies using aggregate operations for data variables. Author responses supported these findings. Discussion and conclusion The high proportion of mapped data elements demonstrates the significant potential for clinical data warehousing to facilitate clinical research. Unmapped data elements illustrate the difficulty in developing a complete data dictionary. [ABSTRACT FROM AUTHOR]

The fuzzy object-oriented databases have been proposed to meet the need of dealing with fuzzy as well as complex objects. In this paper, we present a formal fuzzy object-oriented database model. Based on the semantic measure of fuzzy data, we first identify two kinds of fuzzy object redundancies, which are inclusion redundancy and equivalence redundancy, and then define three kinds of merging operation for redundancy removal. On the basis, we define some fuzzy algebraic operations for fuzzy classes and fuzzy objects. Finally, in the paper, we discuss fuzzy querying strategies and give the form of SQL-like fuzzy querying for the fuzzy object-oriented databases. [ABSTRACT FROM AUTHOR]