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There can be many inherent issues in the process of managing cloud infrastructure and the platform of the cloud. The platform of the cloud manages cloud software and legality issues in making contracts. The platform also handles the process of managing cloud software services and legal contract-based segmentation. In this paper, we tackle these issues directly with some feasible solutions. For these constraints, the Averaged One-Dependence Estimators (AODE) classifier and the SELECT Applicable Only to Parallel Server (SELECT-APSL ASA) method are proposed to separate the data related to the place. ASA is made up of the AODE and SELECT Applicable Only to Parallel Server. The AODE classifier is used to separate the data from smart city data based on the hybrid data obfuscation technique. The data from the hybrid data obfuscation technique manages 50% of the raw data, and 50% of hospital data is masked using the proposed transmission. The analysis of energy consumption before the cryptosystem shows the total packet delivered by about 71.66% compared with existing algorithms. The analysis of energy consumption after cryptosystem assumption shows 47.34% consumption, compared to existing state-of-the-art algorithms. The average energy consumption before data obfuscation decreased by 2.47%, and the average energy consumption after data obfuscation was reduced by 9.90%. The analysis of the makespan time before data obfuscation decreased by 33.71%. Compared to existing state-of-the-art algorithms, the study of makespan time after data obfuscation decreased by 1.3%. These impressive results show the strength of our methodology.

One of the most important tasks of any platform for big data processing is storing the data received. Different systems have different requirements for the storage formats of big data, which raises the problem of choosing the optimal data storage format to solve the current problem. This paper describes the five most popular formats for storing big data, presents an experimental evaluation of these formats and a methodology for choosing the format. The following data storage formats will be considered: avro, CSV, JSON, ORC, parquet. At the first stage, a comparative analysis of the main characteristics of the studied formats was carried out; at the second stage, an experimental evaluation of these formats was prepared and carried out. For the experiment, an experimental stand was deployed with tools for processing big data installed on it. The aim of the experiment was to find out characteristics of data storage formats, such as the volume and processing speed for different operations using the Apache Spark framework. In addition, within the study, an algorithm for choosing the optimal format from the presented alternatives was developed using tropical optimization methods. The result of the study is presented in the form of a technique for obtaining a vector of ratings of data storage formats for the Apache Hadoop system, based on an experimental assessment using Apache Spark.

Development of mobile applications is a very popular trend of today’s informational technologies. Moreover, mapping applications are one of the most popular among all. However, development of mobile applications has some issues while implementing application for multiple mobile platforms and while making it work offline. According to our development experience, it was decided to show main methods of mobile application development, describe advantages and disadvantages of each with respect to mapping functions and application complexity. Special attention was paid to hybrid mobile development technology in order to check out the widespread information about it’s high development speed in compare to “native” and to make sure that it allows to realize easy transferring of existing web application to mobile platform.

PurposeLarge collections of patent documents disclosing novel, non-obvious technologies are publicly available and beneficial to academia and industries. To maximally exploit its potential, searching these patent documents has increasingly become an important topic. Although much research has processed a large size of collections, a few studies have attempted to integrate both patent classifications and specifications for analyzing user queries. Consequently, the queries are often insufficiently analyzed for improving the accuracy of search results. This paper aims to address such limitation by exploiting semantic relationships between patent contents and their classification.Design/methodology/approachThe contributions are fourfold. First, the authors enhance similarity measurement between two short sentences and make it 20 per cent more accurate. Second, the Graph-embedded Tree ontology is enriched by integrating both patent documents and classification scheme. Third, the ontology does not rely on rule-based method or text matching; instead, an heuristic meaning comparison to extract semantic relationships between concepts is applied. Finally, the patent search approach uses the ontology effectively with the results sorted based on their most common order.FindingsThe experiment on searching for 600 patent documents in the field of Logistics brings better 15 per cent in terms of F-Measure when compared with traditional approaches.Research limitations/implicationsThe research, however, still requires improvement in which the terms and phrases extracted by Noun and Noun phrases making less sense in some aspect and thus might not result in high accuracy. The large collection of extracted relationships could be further optimized for its conciseness. In addition, parallel processing such as Map-Reduce could be further used to improve the search processing performance.Practical implicationsThe experimental results could be used for scientists and technologists to search for novel, non-obvious technologies in the patents.Social implicationsHigh quality of patent search results will reduce the patent infringement.Originality/valueThe proposed ontology is semantically enriched by integrating both patent documents and their classification. This ontology facilitates the analysis of the user queries for enhancing the accuracy of the patent search results.

PurposeThis article aims to explore how to incorporate similarity joins into XML database management systems (XDBMSs). The authors aim to provide seamless and efficient integration of similarity joins on tree-structured data into an XDBMS architecture.Design/methodology/approachThe authors exploit XDBMS-specific features to efficiently generate XML tree representations for similarity matching. In particular, the authors push down a large part of the structural similarity evaluation close to the storage layer.FindingsEmpirical experiments were conducted to measure and compare accuracy, performance and scalability of the tree similarity join using different similarity functions and on the top of different storage models. The results show that the authors’ proposal delivers performance and scalability without hurting the accuracy.Originality/valueSimilarity join is a fundamental operation for data integration. Unfortunately, none of the XDBMS architectures proposed so far provides an efficient support for this operation. Evaluating similarity joins on XML is challenging, because it requires similarity matching on the text and structure. In this work, the authors integrate similarity joins into an XDBMS. To the best of the authors’ knowledge, this work is the first to leverage the storage scheme of an XDBMS to support XML similarity join processing.

Purpose – The purpose of this paper is to extract appropriate terms to summarize the current results in terms of the contents of textual facets. Faceted search on XML data helps users find necessary information from XML data by giving attribute–content pairs (called facet-value pair) about the current search results. However, if most of the contents of a facet have longer texts in average (such facets are called textual facets), it is not easy to overview the current results. Design/methodology/approach – The proposed approach is based upon subsumption relationships of terms among the contents of a facet. The subsumption relationship can be extracted using co-occurrences of terms among a number of documents (in this paper, a content of a facet is considered as a document). Subsumption relationships compose hierarchies, and the authors utilize the hierarchies to extract facet-values from textual facets. In the faceted search context, users have ambiguous search demands, they expect broader terms. Thus, we extract high-level terms in the hierarchies as facet-values. Findings – The main findings of this paper are the extracted terms improve users’ search experiences, especially in cases when the search demands are ambiguous. Originality/value – An originality of this paper is the way to utilize the textual contents of XML data for improving users’ search experiences on faceted search. The other originality is how to design the tasks to evaluate exploratory search like faceted search.

Purpose – The purpose of this paper is to propose and evaluate XKQSS, a query structuring method that relegates the task of generating structured queries from a user to a search engine while retaining the simple keyword search query interface. A more effective way for searching XML database is to use structured queries. However, using query languages to express queries prove to be difficult for most users since this requires learning a query language and knowledge of the underlying data schema. On the other hand, the success of Web search engines has made many users to be familiar with keyword search and, therefore, they prefer to use a keyword search query interface to search XML data. Design/methodology/approach – Existing query structuring approaches require users to provide structural hints in their input keyword queries even though their interface is keyword base. Other problems with existing systems include their inability to put keyword query ambiguities into consideration during query structuring and how to select the best generated structure query that best represents a given keyword query. To address these problems, this study allows users to submit a schema independent keyword query, use named entity recognition (NER) to categorize query keywords to resolve query ambiguities and compute semantic information for a node from its data content. Algorithms were proposed that find user search intentions and convert the intentions into a set of ranked structured queries. Findings – Experiments with Sigmod and IMDB datasets were conducted to evaluate the effectiveness of the method. The experimental result shows that the XKQSS is about 20 per cent more effective than XReal in terms of return nodes identification, a state-of-art systems for XML retrieval. Originality/value – Existing systems do not take keyword query ambiguities into account. XKSS consists of two guidelines based on NER that help to resolve these ambiguities before converting the submitted query. It also include a ranking function computes a score for each generated query by using both semantic information and data statistic, as opposed to data statistic only approach used by the existing approaches.

Purpose - This paper considers schemaless XML data stored in a column-oriented storage, particularly in C-store. Axes of the XPath language are studied and a design and analysis of algorithms for processing the XPath fragment XP{*, //, /} are described in detail. The paper aims to discuss these issues. Design/methodology/approach - A two-level model of C-store based on XML-enabled relational databases is supposed. The axes of XPath language in this environment have been studied by Cástková and Pokorný. The associated algorithms have been used for the implementation of the XPath fragment XP{*, //, /}. Findings - The main advantage of this approach is algorithms implementing axes evaluations that are mostly of logarithmic complexity in n, where n is the number of nodes of XML tree associated with an XML document. A low-level memory system enables the estimation of the number of two abstract operations providing an interface to an external memory. The algorithms developed are mostly of logarithmic complexity in n, where n is the number of nodes of XML tree associated with an XML document. Originality/value - The paper extends the approach of querying XML data stored in a column-oriented storage to the XPath fragment using only child and descendant axes and estimates the complexity of evaluating its queries.

Data bases or relational data base management systems (RDBMS) offer advantages over the common saving as data files for the storage of qualitative data in secondary analysis archives and larger research projects. But the use of databases in qualitative data analysis (QDA) until now has not been popular because of the feature of QDA programs which permit only the assignment of documents stored as data files. To facilitate a more efficient use of professional DBMS in QDA we developed the conception of an interface to QDA programs. The present prototype QUESSY.ti is an interface between some of the most popular and powerful RDBMS (MS SQL, Oracle, MySQL, MS Access) on the one side, and ATLAS.ti on the other. QUESSY.ti lets the user post a detailed SQL query to the RDBMS and retrieves the results. In an elaborate mapping stage, database field names (attributes) can then be directly \"translated\" into the \"language\" of QDA software. A third stage allows for direct import of the retrieved data into the QDA program (currently, ATLAS.ti). This article, after introducing the use of databases in qualitative data storing, describes the workings of QUESSY.ti, relays the findings of an international poll of ATLAS.ti users, and finally discusses potential fields of application. URN: urn:nbn:de:0114-fqs0501350

This chapter contains sections titled: Introduction Preparation of High‐B s Soft Magnetic Film Using Electrodeposition Techniques Preparation of High‐Magneticflux‐Density CONiFeB Film by Electroless Deposition Preparation of Magnetic Seed Layer of Pd Nanocluster by Displacement Plating Chemical Synthesis of FePt Nanoparticles for High‐Density Magnetic Recording Media Summary References