Query Technology Research Articles

A Fuzzy Query Method Oriented to Knowledge Graph

With the widespread application of Knowledge Graphs, Knowledge Graph query technology has received widespread attention. The daily use of natural language usually contains fuzzy terms. The use of fuzzy terms in queries is more in line with natural language habits. Therefore, fuzzy questions have been widely discussed and applied in relational data models, and their use in NoSQL data models has also begun to be affected in recent years. RDF (Resource Description Framework) is a representative model of the knowledge graph, and SPARQL is the standard query language of RDF. To realize the fuzzy query of the knowledge graph, this paper introduces the unclear expansion syntax of aggregate function based on summarizing and analyzing the existing SPARQL fuzzy expansion. Supplements the qualitative preference analysis method then proposes and SPARQL1. 1 Corresponding fuzzy SPARQL1.1 (f-SPARQL1.1) simultaneously provides strategies and techniques for rewriting ambiguous queries into classic SPARQL queries. In addition, this article also provides a visual interface for defining the membership functions of fuzzy terms and provides three interactive methods for setting fuzzy membership functions. Compared with the previous fuzzy query methods for RDF models, the method proposed in this paper has more vital fuzzy query ability and more flexible universality. The experimental results show the usability of the method proposed in this paper.

HBase-based spatial-temporal index model for trajectory data

The development of global positioning technology and the popularization of smart mobile terminals has led to a trend of rapid growth in the data volume and coverage of trajectory data. This type of data has the characteristics of fast update speed, high dimensional characteristics, and a large amount of information that can be mined. Many technology companies will use trajectory data to provide location-based services, such as vehicle scheduling and road condition estimation. However, the storage and query efficiency of massive trajectory data have increasingly become bottlenecks in these applications, especially for large-scale spatiotemporal query scenarios. This paper solves this problem by designing a trajectory data index model based on GeoSOT-ST spatiotemporal coding. Based on this model, the HBase-based trajectory data storage scheme and spatiotemporal range query technology are studied, and MapReduce is used as the calculation engine to complete the query attribute condition filtering in parallel. Comparative experiments prove that the index model proposed in this paper can achieve efficient trajectory data query management.

A Security Multi-Dimensional Range Query Protocol Based on Left 0-1 Encoding in Two-Tiered Wireless Sensor Networks

In this research on range query technology for two-tiered wireless sensor networks, the existing researches still need improvement in privacy security and communication cost of the sensor node. In this paper, a security multi-dimensional range query protocol is proposed. The left 0-1 encoding mechanism (a new and optimized encoding mechanism), HMAC algorithm, and BASE64 encoding are employed to optimize the calculation of comparison factor. The encryption index chain is constructed by using AES algorithm to replace the long encryption constraint chain, so as to lower the energy consumption of computation and communication. The base station can verify the authenticity and integrity of query results on the basis of continuity of storage time and encryption index chain. The experiment has been conducted in the real systems. The protocol is compared and analyzed with the latest proposed Communication-Efficient Secure Range Queries (CSRQ). The results have shown that the proposed protocol can gain a better performance in terms of four aspects, i.e., the length of sensing data, the number of data collected in each cycle, the number of data dimensions and the number of sensor nodes in each unit. Meanwhile, compared with CSRQ, the communication cost of the proposed protocol is reduced by at least 10%.

Copyright Transaction Mode and Copyright Protection Risk Analysis of Green Industry from the Perspective of Information Environment

At present, the requirements of the current environment and background require us to have higher requirements for the data mode of copyright transaction. According to the previous way to conduct copyright transactions, it will cause a lot of unnecessary trouble, and according to the establishment of the copyright transaction database, we analyse the data types and patterns of copyright transactions and related copyright transaction protection measures and risk prevention. According to the copyright transaction database, we adopt BS network model, CIF copyright transaction data set model, CI data set model, data interactive query technology, and block matching technology to deal with the copyright transaction data model and copyright transaction risk prevention under the background of Informa ionization as follows: (1) we use BS network model, CIF copyright transaction data set model, and CI data set model to analyse and detect the copyright transaction data before transaction, which better reflects the network model effect of self‐enhancing operation rate of copyright transaction data and effectively avoids overfitting problem. (2) By using interactive data query technology, the data presented in the preparation work before the transaction is more detailed, the samples are normalized, and the collected transaction data are tested for accuracy, which can eliminate potential dangers. (3) The method of similarity feature reconstruction of copyright transaction data set completes the extraction of association matching features of copyright transaction data system, which provides strong support for us to prevent risks and effectively match data in copyright transaction.

An Internet of Things based scalable framework for disaster data management

In recent years, undesirable disasters attacked the cities frequently, leaving heavy casualties and serious economic losses. Meanwhile, disaster detection based on the Internet of Things(IoT) has become a hot spot that benefited from the established development of smart city construction. And the IoT is visibly sensitive to the management and monitoring of disasters, but massive amounts of monitoring data have brought huge challenges to data storage and data analysis. This article develops a new and much more general framework for disaster emergency management under the IoT environment. The framework is a bottom-up integration of highly scalable Raw Data Storages(RD-Stores) technology, hybrid indexing and queries technology, and machine learning technology for emergency disasters. Experimental results show that hybrid index and query technology have better performance under the condition of supporting multi-modal retrieval, and providing a better solution to offer real-time retrieval for the massive sensor sampling data in the IoT. In addition, further works to evaluate the top-level sub-application system in this framework were performed based on the GPS trajectory data of 35,000 Beijing taxis and the volumetric ground truth data of 7,500 images. The results show that the framework has desirable scalability and higher utility.

Cybersecurity Leaders: Knowledge Driving Human Capital Development

Abstract Cybersecurity leaders must be able to use critical reading and thinking skills, exercise judgment when policies are not distinct and precise, and have the knowledge, skills, and abilities to tailor technical and planning data to diverse customers’ levels of understanding. Ninety-three percent of cybersecurity leaders do not report directly to the chief operating officer. While status differences influence interactions amid groups, attackers are smarter. With the aim of protecting organizations and reducing risk, knowledge about security must increase. Understanding voids are costly and increased breach chances are imminent. Burning questions exist. What are needed technological learnings for cybersecurity leaders to become smarter and remain ahead of attackers? How might these technologies hasten the understanding of the ‘what,’ ‘how,’ and ‘why’ reasons and key drivers for organizational behaviors. This article offers comparative analyses for cybersecurity leaders to engage in the questioning of practices, scrutinize entrenched assumptions about technology, customary practices, and query technology’s outputs by pursuing to comprehend all assumptions that could influence operations. Because understanding continues to rely upon progressively multifaceted epistemic technologies, outcomes of the research suggest that the salience of status distinctions is of central significance to the development of ongoing and proactive technological learning and up scaling solutions.

Application of processing technology based on skyline query in computer network

With the rapid development of network data communication technology, the complexity of the network environment makes the data in the data stream have uncertain characteristics, and a large number of data streams are generated in many fields. Therefore, it is necessary to find an efficient and accurate processing method to process a large amount of data in a computer network. This paper takes the skyline probability calculation and the actual efficiency of the unknown object index structure in the skyline query processing technology on the uncertain data stream as the research object. Based on the skyline query technology, we study an efficient skyline query processing method on the unknown network traffic based on the model SUMG. The method includes two algorithms: dynamic modeling algorithm DMG and skyline query algorithm GST. The DMG algorithm samples the data in the sliding window of the uncertain data stream and establishes a model to convert the data stream into the parameter stream in the uncertain object probability density function, the GST algorithm establishes the R-tree index structure, which is in order to reduce the amount of calculation, it uses the parameter flow of the model. In both methods, the set of local skyline results is first obtained at the distributed node, and the skyline query is performed again on the union of the local skyline results to obtain the global skyline result set. The experimental results show that compared with the skyline query method BNL for unknown network traffic without an index structure, the SUMG method can not only effectively model the link-type unknown object to assist the skyline query, but also effectively prune the uncertain data object and improve the skyline. The distributed skyline query method can cope with the skyline query task on the distributed data stream.

Design of a Stereo Monitoring System Based on Wireless Sensor Networks

Recently, Wireless sensor network is regarded as a new information acquisition platform, its relevant technologies have been widely used as the basis of the Internet of Things. In order to realize the campus information construction, a campus stereo monitoring system based on wireless sensor network is designed in this paper. Such technologies as the intelligent information processing technology of wireless sensor network, the remote WIFI wireless data communication technology, the cloud services technology and the management query technology for monitoring points based on the internet display platform are adopted in this system synthetically, realize on line real time monitoring and location, which can not only reduce the human cost, but also has important significance in maintaining campus safety and campus management.

Quality Of Education System As A Determinant Of Socio-Economic Development: Assessment Of Technological Level Of Readyness

The article is devoted to finding ways to assess the quality of educational activities at the university through analogies between tangible (technical) and intangible systems. The approach to determining the level of technological readiness for implementation (TRL) was used as a tool to assess the level of development of the quality of education system. The abstract-logical method and the method of induction-deduction were used in the analysis of the causal relationship between the quality of education and the assessment of the technological level of development readiness. Bibliometric analysis was performed using SciVal and VOSviewer tools based on data from the scientific-metric databases Scopus and Web of Science. Based on bibliometric analysis, it was found that currently the TRL approach has not been used to describe the dynamic system of education quality, as it is not adapted to intangible systems. A link was also established between the search query technology readiness level and socio-economic indicators of technology implementation in industry. The description of each level of technological readiness of development on the example of the system quality of education with consistent progress in the development of quality assurance system and a brief description of each level of the studied intangible system. An example of determining the technological level of development readiness using the NYSERDA calculator is given. The results of the work can be useful for universities that build an effective internal system of quality assurance in education as an algorithm for consistent transition between levels of readiness and the relevant indicators of a particular technological level.

Secure K-Nearest neighbor queries in two-tiered mobile wireless sensor networks

Tiered Mobile Wireless Sensor Network(TMWSN) is a new paradigm introduced by mobile edge computing. Now it has received wide attention because of its high scalability, robustness, deployment flexibility, and it has a wide range of application scenarios. In TMWSNs, the storage nodes are the key nodes of the network and are more easily captured and utilized by attackers. Once the storage nodes are captured by the attackers, the data stored on them will be exposed. Moreover, the query process and results will not be trusted any more. This paper mainly studies the secure KNN query technology in TMWSNs, and we propose a secure KNN query algorithm named the Basic Algorithm For Secure KNN Query(BAFSKQ) first, which can protect privacy and verify the integrity of query results. However, this algorithm has a large communication overhead in most cases. In order to solve this problem, we propose an improved algorithm named the Secure KNN Query Algorithm Based on MR-Tree(SEKQAM). The MR-Trees are used to find the K-nearest locations and help to generate a verification set to process the verification of query results. It can be proved that our algorithms can effectively guarantee the privacy of the data stored on the storage nodes and the integrity of the query results. Our experimental results also show that after introducing the MR-Trees in KNN queries on TMWSNs, the communication overhead has an effective reduction compared to BAFSKQ.

Research on Group Reverse Farthest Neighbour Query Algorithm

In recent years, the demand for location-based services is growing. From resource tracking to personal life assistance, spatial data query technology plays an important role, especially the application of reverse nearest neighbor query technology in decision support, resource allocation optimization, data mining. By contrast, the reverse farthest neighbor query has become a more and more hot topic in the research of spatial database theory in recent years. The purpose of the reverse farthest neighbor query is to obtain the final result sets with the given point as its farthest neighbor, which is specially used to solve the problem of weak influence set in space. This paper gives a query optimization algorithm based on the least covering circle. The algorithm firstly introduces the minimal covering circle algorithm. Secondly, the p-ray pruning algorithm is used to filter the candidate set in the second level, and the candidate set is modified by the reverse far-neighborhood range query algorithm to obtain the final result set, which solves the problem in Euclidean effectively. Through specific comparative experimental analysis, c-grfn algorithm has good query performance not only in random distributed environment, but also in Gaussian distribution. It usually has 20% advantages of time in distributed space. As the data set increases, the time advantage becomes more obvious

A novel tool for patient data management in the ICU—Ensuring timely and accurate vital data exchange among ICU team members

ObjectiveThe coronavirus pandemic has highlighted the need to simplify data collection for critically-ill patients, particularly for physicians relocated to the ICU setting. Herein we present a simple, reproducible, and highly-customizable manual-entry tool to track ICU patients using new HIPAA-compliant Google Big Query technology for parsing large datasets. This innovative flow chart is useful and could be modified to serve the particular needs of different sub-specialists, particularly those that either rely heavily on hand-written notes or experience poor electronic medical record (EMR) penetration. MethodsThe tool was developed using a combination of three Google Enterprise features: Google Forms for data input, Google Sheets for data output, and Google Big Query for data parsing. Code was written in SQL. Sheets functions were used to transpose and filter parsed data. White and black box tests were performed to examine functionality. ResultsOur tool was successfully able to collect and output fictional patient data across all 57 data points specified by the intensivists and surgeons of Cardiovascular Department of Mt. Sinai Morningside Hospital. ConclusionThe functional tests performed demonstrate use of the tool. Though originally conceived to simplify patient data collection for newly relocated physicians to the ICU, our tool also overcomes financial and technological barriers previously described in low-income countries that could dramatically improve patient care and provide data to power future studies in these regions. With the original code provided, implementers may adapt our tool to best meet the requirements of their clinical setting and protocols during this very challenging time.

Power Query: The formation of professional competencies of a business analyst

The article is a description of the Power Query technology training methodology implemented within the framework of the Federal State Educational Standard for Higher Education 3++ taking into account professional standards in the direction of the bachelor’s program “Business Informatics”. The authors propose a set of laboratory works in the form of situational tasks and cases that allow to create professional competencies and labor functions of a future specialist (business analyst) as part of the development of the ETL process for processing data using Power Query technology. The use of situational tasks and cases allows to effectively implement the development of a set of professional competencies, which are elements of generalized labor functions, without tying the material in question specifically to any discipline. As part of the implementation of situational tasks and cases described in the article, bachelors not only learn to use the basic elements of Power Query technology, but also gain the skills and abilities associated with the application of the studied technology in performing standard professional tasks stipulated by a professional standard. The format for describing the methodology is presented in the form of the traditional “Key-by-Key” technology, widely used in obtaining professional IT competencies.

Research and Implementation of Geography Information Query System Based on Improved B-Order Algorithm

With the rise of cloud computing research, more and more application systems begin to migrate to the cloud platform. However, the difference between cloud platform and traditional single or multiple sever model bring certain challenges to the system development. In this thesis, a Geography information query system based on HBase was studied and implemented relied on National Geography Public Welfare Project. The query system can make users to retrieve the information of sea wind and satellite images by the graphical interface. In the implement process of Geography information query system, this thesis studied and optimized the query technology. Firstly, in the query process of NearGoos data, B-order was used to divide the two-dimensional space and combine the sort features of rowkey in the table of HBase to optimize the spatial query. By improving the B-order algorithm, this algorithm made the query efficiency increase two orders of magnitude than before.

A Voronoi-Based Group Reverse k Farthest Neighbor Query Method in the Obstacle Space

With the rapid development of intelligent transportation and geographic information system, spatial data query technology has attracted the attention of many scholars. Among them, the reverse farthest neighbor query from the data point to find the target point as its farthest adjacent data points, used to obtain target set of weak influence. Its research results have been widely applied to facility location, earthquake relief, marketing and other major areas. Thus, the research of reverse furthest neighbor query technology is of great significance. However, the existing methods only deal with a single query point, and do not consider how to obtain the optimal farthest neighbor position of group reverse when the number of query points changes from one to a group. In addition, considering it is difficult to avoid some geographical location restrictions in the real situation, the existing studies are limited to road network or Euclidean space simplely, without taking the existence of obstacles into consideration. To this end, this paper proposed the V-OGRkFN(Voronoi-Obstacle Group Reverse $k$ Farthest Neighbor) algorithm. Firstly, the algorithm gets the minimum cover circle of query points which are considered into a whole. Secondly, we use the framework based on the filtering and refining process of query by pruning strategy based on Voronoi diagram's properties. Then we get the candidate set using the theorem of transformation between $k$ nearest neighbors and $k$ farthest neighbors. Finally, the refining algorithm is given to get the final results. V-OGRkFN algorithm shows great performance of reverse $k$ farthest neighbor query through the specific comparative experimental analysis.

Research and Implementation of Geography Information Query System Based on HBase

With the rise of cloud computing research, the advantages of cloud computing and storage resources are discovered continuously: distributed computing, massive, dynamic and so on. Consequently, more and more application systems begin to migrate to the cloud platform. However, the difference between cloud platform and traditional single or multiple sever model bring certain challenges to the system development. In this thesis, a Geography information query system based on HBase was studied and implemented rellied on National Geography Public Welfare Project. The query system can make users to retrieve the information of sea wind and satellite images by the graphical interface. Through the effective application of query technology, the system can efficiently extract the concerned Geography data information for the fishery production and Geography disaster prevention. This thesis firstly displayed the Geography information query system with the running examples, and secondly tested and analized the HBase query optimization technology to vertify its great expandability and usability. Finally, the performance test of Geography information query system indicated that the system had high scalability and high reliability in the cloud environment.

Research on application of multimedia image processing technology based on wavelet transform

With the development of information technology, multimedia has become a common information storage technology. The original information query technology has been difficult to adapt to the development of this new technology, so in order to be able to retrieve useful information in a large amount of multimedia information which has become a hot topic in the development of search technology, this paper takes the image in the multimedia information storage technology as the research object, uses the wavelet transform to divide the picture into the advantages of the low-frequency and high-frequency characteristics, and establishes the multimedia processing technology model based on the wavelet transform. The simulation results of face, vehicle, building, and landscape images show that different wavelet basis functions and different layers of images are decomposed, and the retrieval results and retrieval speed of images are different, When taking four layers of wavelet decomposition, the cubic b-spline wavelet as the wavelet basis function makes the classification result optimal, and the accuracy rate is 89.08%.

On the RFID Information Query Technology Based on IPV9

Abstract Since coding format of RF label is inconsistent with the protocol format of the information server’s network, a design scheme of network architecture is proposed to achieve the connectivity between the decimal network based on IPV9 and the Internet network based on IPV4/IPV6. And also, two ways of information’s Query and connectivity based on D-ONS and direct routing between the decimal network is devised by using the expert modules. The experiment results shows that both the two ways can provide efficient service of RFID Information Query.

Research and Implementation of Geography Information Query System Based on Hbase

With the rise of cloud computing research, the advantages of cloud computing and storage resources are discovered continuously: distributed computing, massive, dynamic and so on. Consequently, more and more application systems begin to migrate to the cloud platform. However, the difference between cloud platform and traditional single or multiple sever model bring certain challenges to the system development. In this thesis, a Geography information query system based on HBase was studied and implemented rellied on National Geography Public Welfare Project. The query system can make users to retrieve the information of sea wind and satellite images by the graphical interface. Through the effective application of query technology, the system can efficiently extract the concerned Geography data information for the fishery production and Geography disaster prevention. This thesis firstly displayed the Geography information query system with the running examples, and secondly tested and analyzed the HBase query optimization technology to verify its great expandability and usability. Finally, the performance test of Geography information query system indicated that the system had high scalability and high reliability in the cloud environment.

A survey of real-time approximate nearest neighbor query over streaming data for fog computing

Real-time approximate nearest neighbor (ANN) query over streaming data in fog computing environment is the fundamental problem of real-time analysis of big data. As the fog computing paradigm needs to provide real-time and low latency services, and traditional streaming data ANN query technology cannot be directly applied. Exploring the basic theory, querying framework and technology of real-time ANN query over streaming data for fog computing becomes one of the current research hotspots. This paper summarizes the related ANN query technology based on random hash, learning-to-hash and synopses, analyzes the problems and challenges of real-time ANN query in resource-limited fog computing environment, and finally discusses in detail the basic theory and method of the query, the dimension reduction and encoding method based on learning-to-hash, the generating synopses method for ANN query over streaming data from Internet of Thing, and the future related research directions of ANN query framework and others. Additionally, we propose a Dynamic Adaptive Quantization (DAQ) method for learning-to-hash. Experiments show that DAQ outperformed other quantization methods.