Information Query Research Articles

A Multilingual Unified Character Encoding Scheme Based on a Normative Character Set

The scheme is a unified character coding set of Sibe, Manchu, Mongolian and Todo languages, and the letters in the set are arranged in Latin alphabetical order. Compared with the system based on the nominal character encoding, this set does no need free variation selectors in Sibe and Manchu, and greatly reduce the use of the selectors in other languages. Thus, it is more in line with the general user's habits, and improve the information query, search, and transmission.

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.

Food Safety Traceability System Based on Blockchain and EPCIS

In recent years, food safety issues have drawn growing concerns from society. In order to efficiently detect and prevent food safety problems and trace the accountability, building a reliable traceability system is indispensable. It is especially essential to accurately record, share, and trace the specific data within the whole food supply chain, including the process of production, processing, warehousing, transportation, and retail. The traditional traceability systems have issues, such as data invisibility, tampering, and sensitive information disclosure. The blockchain is a promising technology for the food safety traceability system because of the characteristics, such as the irreversible time vector, smart contract, and consensus algorithm. This paper proposes a food safety traceability system based on the blockchain and the EPC Information Services and develops a prototype system. The management architecture of on-chain & off-chain data is proposed as well, through which the traceability system can alleviate the data explosion issue of the blockchain for the Internet of Things. Furthermore, the enterprise-level smart contract is designed to prevent data tampering and sensitive information disclosure during information interaction among participants. The prototype system was implemented based on the Ethereum. According to the test results, the average time of information query response is around 2 ms, while the amount of on-chain data and query counts are 1 GB and 1000 times/s, respectively.

Enabling Smart Anonymity Scheme for Security Collaborative Enhancement in Location-Based Services

Security enhancement is and always will be a prime concern for the deployment of point-of-interest (POI) recommendation services in mobile sensing environment. Recent tamper-proof technical protection such as strong encryption has undoubtedly become a major safeguard against threats to privacy in location-based services. Although the disclosure of location information could increase recommendation accuracy, the publication of trajectory data to untrusted entities could reveal sensitive details, e.g., daily routes, destinations, and favorite restaurants. In this paper, we propose a smart scheme named BUSA to approach the above problem by reconciling the tension between privacy protection and recommendation accuracy in location-based recommendation services. This scheme uses anonymizer agents positioned between the service-requesting users and location service providers; these agents operate by dividing the query information and using k -anonymity to enhance privacy protection. The scheme also utilizes clustering techniques to group users into clusters by learning their trajectory data and selects the spatial center cells as a cluster core and a benchmark for calculating recommendations via trust computing. An anonymizer coordination strategy is proposed to replace a low-performing anonymizer with one that provides stronger privacy protection for a recommendation service. The BUSA scheme adopts k-anonymity and clustering to protect privacy, and the calculated recommendation will be suitable for the cluster core that represents the entirety of users' location preferences. The security analysis reveals that the BUSA scheme can effectively protect privacy against fraudulent query requestors and the simulation results also indicate that it provides stronger privacy protection than its counterparts from the perspective of recommendation hit rate and the extent of disclosure.

Students’ Information Needs and Digital Technologies in Academic Libraries

Thesis/objective – The topic of this article is the influence of digital technologies on the functioning of academic libraries in the context of their users’ needs. Users’ information behaviors have changed significantly through the influence of these technologies, what can be identified in particular in students’ behaviors. Do far-reaching changes in the way in which users, in case of this article - students, interact with information cause transformations in the functioning and mission of academic libraries? On the basis of literature containing the results of researches conducted around the world an attempt was made to present the way academic libraries react to these changes and how they modify their services and resources. Research method – The first step in responding to the actual needs of users is to conduct research in this area. For this reason, the subject of the analysis in this article were publications presenting research on the users’ (students) needs in the context of using academic libraries. The next stage was to identify the texts in which the use of digital technology was discussed. The analyzed literature was selected from leading journals indexed in the Science Citation Index Expanded (SCI-EXPANDED), the Social Sciences Citation Index (SSCI), and the Arts & Humanities Citation Index (A & HCI), and included articles which were published within the last 5 years (2013-2018) – a period in which digital technologies in most academic libraries in the world were most widely used, making changes caused by them possible to be diagnosed, and which corresponds to the information query. The results of the query contained 328 articles, 80 of them have been analyzed in detail, because they were deemed to contain the results of research on the functioning of academic libraries in the context of the needs and expectations of the students. Results/conclusions – On the basis of the analysis it can be concluded that the widespread use of digital technologies has changed functioning of academic libraries to a large extent, but these changes are not revolutionary. The way of implementing library tasks has changed, but the tasks themselves as well as the mission of an academic library have remained similar. One of the most important postulates for the future is the necessity of far-reaching personalization of the services being offered. The conducted analysis is based on the research presented in the literature, the next planned stage is verification of these conclusions in empirical research.

Reliable Label-Efficient Learning for Biomedical Image Recognition.

The use of deep neural networks for biomedical image analysis requires a sufficient number of labeled datasets. To acquire accurate labels as the gold standard, multiple observers with specific expertise are required for both annotation and proofreading. This process can be time-consuming and labor-intensive, making high-quality, and large-annotated biomedical datasets difficult. To address this problem, we propose a deep active learning framework that enables the active selection of both informative queries and reliable experts. To measure the uncertainty of the unlabeled data, a dropout-based strategy is integrated with a similarity criterion for both data selection and random error elimination. To select the reliable labelers, we adopt an expertise estimator to learn the expertise levels of labelers via offline-testing and online consistency evaluation. The proposed method is applied to classification tasks on two types of medical images including confocal endomicroscopy images and gastrointestinal endoscopic images. The annotations are acquired from multiple labelers with diverse levels of expertise. The experiments demonstrate the efficiency and promising performance of the proposed method compared to a set of baseline methods.

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.

Query Recommendation Using Hybrid Query Relevance

With the explosion of web information, search engines have become main tools in information retrieval. However, most queries submitted in web search are ambiguous and multifaceted. Understanding the queries and mining query intention is critical for search engines. In this paper, we present a novel query recommendation algorithm by combining query information and URL information which can get wide and accurate query relevance. The calculation of query relevance is based on query information by query co-concurrence and query embedding vector. Adding the ranking to query-URL pairs can calculate the strength between query and URL more precisely. Empirical experiments are performed based on AOL log. The results demonstrate the effectiveness of our proposed query recommendation algorithm, which achieves superior performance compared to other algorithms.

The Development and application of 3-D visual display platform for safety monitoring information of hydropower project

In the long-term project operation and safety management, the safety monitoring is used to monitor the project safety change and to identify and avoid project risk. As the eyes, ears and technical means of administration department, it can ensure the safety and can improve the efficiency of the project. How to display the monitoring information and results intuitively has been a constant pursuit of monitoring technicians. This paper introduces a kind of the monitoring data display platform based on the virtual reality technology and the interactive simulation technology. The platform will have a unified expression of the hydropower project applying the TST-VR virtual reality tools and 3-D modelling technology. It will set up the integrated visible virtual environment and realize the 3-D scene roaming, monitoring information query and other interactive control. The platform integrates the existing data resources of information system and displays all the information in an intuitive way, which is convenient for managers to query and manage, and can also meet the macro-control of superior management departments.

Context-Aware Query Selection for Active Learning in Event Recognition.

Activity recognition is a challenging problem with many practical applications. In addition to the visual features, recent approaches have benefited from the use of context, e.g., inter-relationships among the activities and objects. However, these approaches require data to be labeled, entirely available beforehand, and not designed to be updated continuously, which make them unsuitable for surveillance applications. In contrast, we propose a continuous-learning framework for context-aware activity recognition from unlabeled video, which has two distinct advantages over existing methods. First, it employs a novel active-learning technique that not only exploits the informativeness of the individual activities but also utilizes their contextual information during query selection; this leads to significant reduction in expensive manual annotation effort. Second, the learned models can be adapted online as more data is available. We formulate a conditional random field model that encodes the context and devise an information-theoretic approach that utilizes entropy and mutual information of the nodes to compute the set of most informative queries, which are labeled by a human. These labels are combined with graphical inference techniques for incremental updates. We provide a theoretical formulation of the active learning framework with an analytic solution. Experiments on six challenging datasets demonstrate that our framework achieves superior performance with significantly less manual labeling.

Public key encryption with conjunctive keyword search secure against keyword guessing attack from lattices

AbstractPublic key encryption With keyword search (PEKS) enables a cloud server (CS) to get the search trapdoor to identify ciphertext containing the target keyword without decrypting the ciphertext or knowing the target keyword. With the advent of mobile cloud computing, PEKS has ushered in an era of new development opportunities and new challenges. In mobile cloud computing environment, the PEKS schemes demand strict bounded timing response and security. However, traditional PEKS schemes rely on heavy bilinear pairing computations, which causes a delay from the CS to the mobile terminal. Moreover, as computing power increases, PEKS is more vulnerable to suffer from an inherent insecurity known as inside keyword guessing attack, which leaks user data query information. To achieve a secure and efficient searchable encryption scheme in the mobile cloud computing environment, we put forward a lattice‐based searchable encryption scheme that supports conjunctive keyword search. Our scheme achieves higher computational efficiency and is resistant against quantum attacks compared with traditional PEKS schemes. To further enhance security and make our scheme secure against keyword guessing attack, we hide the decryption parameters by outsourcing part of the decryption process to a semitrusted third party called unusual keyword server, so that the CS cannot guess the exact keyword by performing consistency verification.

Design and Implementation of Wind Resources Web Platform

In the context of China’s rapid industrialization and rapid growth of energy demand, wind power development has become an inevitable choice for China’s sustainable development. Therefore, it is of great practical significance to study the development status of wind power in China. This paper demonstrates a web platform designed by Dreamweaver CS5 software and HTML5. It clearly and intuitively shows the situation of the development and utilization of wind power in China by four main parts: wind power status, wind power distribution, wind power prediction and wind power application, the development and implementation of this platform can provide convenience for wind power information query and research in China.

Cognitively Motivated Query Abstraction Model Based on Associative Root-Pattern Networks

Abstract This paper attempts to investigate some aspects related to problems involved in textual inter-cognitive communication in the context of search queries. Furthermore, it aims at stressing on the root-pattern and morpho-phonetic dimension of a word meaning within a query, and its effects on understanding and predicting the intended information conveyed by some search patterns in a human language. As humans are inclined to use very few words possibly pervaded with vague and uncertain interpretational potential for requesting information, misinterpreting conveyed information in a query term might critically influence an inter-cognitive communication, particularly in case of Arabic- and Semitic-based computer systems. Furthermore, as phonetic patterns are involved in the mental word perception, an abstract morpho-phonetic query model is proposed based on the non-linearity of the morpho-phonetic characteristic of Arabic word cognition. This model suggests forming the intended query information by constructing morpho-phonetic query patterns relying on the most associative root-pattern subnetworks. An important advantage of this model resides in introducing the concept of query abstract morpho-phonetic vectors expressing query vector space. Furthermore, this approach suggests employing the fuzzy subsethood theorem as an assessment reflecting model accuracy and the closeness to human associative word-networks. Finally, it opens the discussion to consider indexing based on a higher level of abstraction, such as utilising patterns as cognitive search variables. Furthermore, as this model is capable of predicting most human associative query key terms, integrating these within certain human-machine interaction would improve inter-cognitive communications.

GLOBE BASED 3D GIS SOLUTIONS FOR VIRTUAL HERITAGE

Abstract. During the last years, many solutions have been proposed for 3D Virtual Heritage representations. Recently, also new technologies for online gaming evolved, based on javascript libraries (WebGL), used to create and publish virtual interactive environments. They are based on recent Web browser’s functionalities, surpassing some limitations of VRML technologies. On the side of geospatial information, technology has evolved from desktop GIS to 2D WebGIS and globe applications. The use of globe applications is, today, very diffused due to its immediate and at the same time impressive representation of the earth surface and territories. These technologies have been, also, applied to Virtual Heritage 3D reconstructions, to improve the fruition of Cultural Heritage (CH), with the achievement of interesting results. The topic of this paper is the experimentation on the fusion between globe based and gaming technologies (in our case WebGL) that allow achieving a more user-centric and powerful solution useful for publishing 3D geospatial information of CH on Web. This choice allows obtaining GIS oriented 3D models, typical of globe applications, and, at the same time, a more immersive exploration of CH and its surrounding environment. In particular, it also gives complementary text and multimedia information on the history, architectural features of each cultural good, based on querying of semantic information. The test field of the research is the construction of the 3D GIS virtual globe model of the Manfredonic Castle of Mussomeli (Sicily-Italy), developed for PON-NEPTIS EU Project, to compare open-source technologies and commercial proprietary applications.

BC Data ScoutTM: A New Tool To Investigate Datasets For Health Research

IntroductionBC’s Ministry of Health (MOH) maintains many administrative databases with rich information and analytical potential. Researchers are keen to use these data for both discovery and applied research. Historically, limited views of data availability and populations therein have supported study feasibility. Therefore, we developed BC Data ScoutTM, a cohort browser.
 Objectives and ApproachWe developed a cohort browser service to provide information to researchers planning a study using MOH data. The objective was to create a tool that is simple to use, provides quick results and is free to users to encourage its use. A better understanding of the data available can improve study quality and expand the user-base by giving researchers access to information not previously available during the planning stages. The tool will be evaluated by examining the number of requests received and a user satisfaction survey. Plans are in place to expand into additional data sources and extend query sophistication.
 ResultsThe BC Data ScoutTM online tool provides cohort information in the form of highly aggregated, approximate results to researchers planning a study. It was developed by the MOH, the BC SUPPORT Unit and Population Data BC (PopData) and was launched in February 2018. The service is delivered by PopData. BC Data ScoutTM offers province-wide information for query, is accessible to a wide group of eligible researchers, and has data availability from the year 2000 onwards. Four types of MOH data are available for query: hospital data; physician data; pharmaceutical data; and demographics. In addition to determining study feasibility, the aggregate reports also help to further refine a full data access request and provide enough information to complete and strengthen a funding application.
 Conclusion/ImplicationsBC Data ScoutTM will be beneficial for researchers planning to request data. This preliminary information may increase the chances of meaningful research studies to obtain funding, and the production of relevant, high-quality research results. BC will be among the first jurisdictions across Canada to offer this type of feasibility service.

Research on Data Collection System of smart meters Based on RFID Communication Technology

In order to meet the intelligent trend of electric energy meters, to solve the bad management problem of smart meters. First, the RFID chip integrated into the smart meter circuit board so that RFID read-write device and smart meter can achieve mutual communication through the wireless communication, and on this basis by combining UHF RFID communication technology, WIFI/3G/4G, cloud platform and other technologies, an smart meter data collection system based on RFID communication technology has been developed, which is used in smart meter information query, warehouse management, on-site reading smart meter and data transmission. The system Significantly reducing the time to track and find and has Realized the smart meter information real-time query and warehouse accurate inventory, improve the efficiency of the smart meter management by taking advantage of RFID Technology without contact, passive, and can be instantaneous long-distance bulk reading smart meter data information. In addition, the use of hand-held RFID read-write device for on-site smart meter reading, making the meter reading process more efficient, intelligent and convenient, which effectively solve the problem of the common electronic energy meter function single, Meter reading method lags behind and so on.

Design and Research of Mobile Phone Library Management System in Private University based on ASP.NET

Mobile phone library is also called “mobile library”. It is a new way of library information service that people can query and access library information resources by using mobile devices, such as mobile phones, without limitation of time and space. ASP.NET Core open source, cross platform technology is a new breakthrough and innovation of ASP.NET, especially worthy of our study. This paper studies the characteristics and needs of private university libraries. According to its characteristics and needs, the function and design of mobile library management system are deeply studied, so as to apply ASP.NET technology to design and develop private university library management system and it can provide high-quality document information service for teaching and scientific research, and meet the information needs of teachers and students.

Ontology-based Tamil–English cross-lingual information retrieval system

Cross-lingual information retrieval (CLIR) systems facilitate users to query for information in one language and retrieve relevant documents in another language. In general, CLIR systems translate query in source language to target language and retrieve documents in target language based on the keywords present in the translated query. However, the presence of ambiguity in source and translated queries reduces the performance of the system. Ontology can be used to address this problem. The current approaches to ontology-based CLIR systems use manually constructed multilingual ontology, which is expensive. However, many methods exist to automatically construct ontology for any domain in English but not in other languages like Tamil. We propose a methodology for Tamil–English CLIR system by translating the Tamil query to English and retrieve pages in English to address these issues. Our approach uses a word sense disambiguation module to resolve the ambiguity in Tamil query. An automatically constructed ontology in English is used to address the ambiguity of English query. We have developed a morphological analyser for Tamil language, Tamil–English bilingual dictionary and named entity database to translate a Tamil query to English. The translated query is reformulated using ontology and the reformulated queries are given to a search engine to retrieve English documents from the Internet. We have evaluated our methodology for agriculture domain and the evaluation results show that our approach outperforms other approaches in terms of precision.

The Integration Processing Method of the Ground Fissures Geospatial Data

The disaster of ground fissures is a kind of extremely destructive and regional geological disaster. The characteristics of the ground fissures spatial data is multi-source, heterogeneous and big data. This paper put forward the key integration method of the ground fissures spatial data. It can not only improve the accuracy, timeliness and scientificity of multi-source and heterogeneous ground fissures information query and acquisition, but also can better share and overall management of the ground fissures data.

Efficient and Privacy-Preserving Proximity Detection Schemes for Social Applications

With the pervasiveness of location-aware mobile terminals and the popularity of social applications, location-based social networking service (LBSNS) has brought great convenience to people's life. Meanwhile, proximity detection, which makes LBSNS more flexible, has aroused widespread concern. However, the prosperity of LBSNS still faces many severe challenges on account of users' location privacy and data security. In this paper, we propose two efficient and privacy-preserving proximity detection schemes, named arbitrary geometric range query for polygons (AGRQ-P) and arbitrary geometric range query for circles (AGRQ-C), for location-based social applications. With proposed schemes, a user can choose any area on the map, and query whether her/his friends are within the region without divulging the query information to both social application servers and other users, meanwhile, the accurate locations of her/his friends are also confidential for the servers and the query user. Specifically, with algorithms based on ciphertext of geometric range query, users' query and location information is blurred into ciphertext in client, thus no one but the user knows her/his own sensitive information. Detailed security analysis shows that various security threats can be defended. In addition, the proposed schemes are implemented in an IM APP with a real LBS dataset, and extensive simulation results over smart phones further demonstrate that AGRQ-P and AGRQ-C are highly efficient and can be implemented effectively.