JavaScript Object Notation Research Articles

Incorporating big data into treatment plan evaluation: Development of statistical DVH metrics and visualization dashboards

PurposeTo develop statistical dose-volume histogram (DVH)–based metrics and a visualization method to quantify the comparison of treatment plans with historical experience and among different institutions. Methods and materialsThe descriptive statistical summary (ie, median, first and third quartiles, and 95% confidence intervals) of volume-normalized DVH curve sets of past experiences was visualized through the creation of statistical DVH plots. Detailed distribution parameters were calculated and stored in JavaScript Object Notation files to facilitate management, including transfer and potential multi-institutional comparisons. In the treatment plan evaluation, structure DVH curves were scored against computed statistical DVHs and weighted experience scores (WESs). Individual, clinically used, DVH-based metrics were integrated into a generalized evaluation metric (GEM) as a priority-weighted sum of normalized incomplete gamma functions. Historical treatment plans for 351 patients with head and neck cancer, 104 with prostate cancer who were treated with conventional fractionation, and 94 with liver cancer who were treated with stereotactic body radiation therapy were analyzed to demonstrate the usage of statistical DVH, WES, and GEM in a plan evaluation. A shareable dashboard plugin was created to display statistical DVHs and integrate GEM and WES scores into a clinical plan evaluation within the treatment planning system. Benchmarking with normal tissue complication probability scores was carried out to compare the behavior of GEM and WES scores. ResultsDVH curves from historical treatment plans were characterized and presented, with difficult-to-spare structures (ie, frequently compromised organs at risk) identified. Quantitative evaluations by GEM and/or WES compared favorably with the normal tissue complication probability Lyman-Kutcher-Burman model, transforming a set of discrete threshold-priority limits into a continuous model reflecting physician objectives and historical experience. ConclusionsStatistical DVH offers an easy-to-read, detailed, and comprehensive way to visualize the quantitative comparison with historical experiences and among institutions. WES and GEM metrics offer a flexible means of incorporating discrete threshold-prioritizations and historic context into a set of standardized scoring metrics. Together, they provide a practical approach for incorporating big data into clinical practice for treatment plan evaluations.

Emergency Medical Service for Patients with Cardiovascular Disease Based on Internet of Things

Internet of Things (IoT) is an evolving technology in which smart objects actively collaborate among themselves and with other physical and virtual objects available in the web, in order to perform high level tasks for the benefit of end users. Patients with Cardiovascular diseases (CVDs) require continuous real-time monitoring of their vital signs to provide remote healthcare assistance. In this paper cloud enabled architecture based on IoT for monitoring the vital signs of the patient is proposed which helps in providing the early treatment. This will not only prevent the premature deaths of the patient with CVD but also improve the further management. The IBM Bluemix cloud is used to connect doctors and patients through various body sensors. This system fetches data from body of the patient through sensors in Java Script Object Notation (JSON) format, which enables to run low powered hardware and provides mechanisms to monitor, process, visualize, store the vital sign in real time and send notifications about patient’s conditions to the healthcare providers

A fast and efficient python library for interfacing with the Biological Magnetic Resonance Data Bank

BackgroundThe Biological Magnetic Resonance Data Bank (BMRB) is a public repository of Nuclear Magnetic Resonance (NMR) spectroscopic data of biological macromolecules. It is an important resource for many researchers using NMR to study structural, biophysical, and biochemical properties of biological macromolecules. It is primarily maintained and accessed in a flat file ASCII format known as NMR-STAR. While the format is human readable, the size of most BMRB entries makes computer readability and explicit representation a practical requirement for almost any rigorous systematic analysis.ResultsTo aid in the use of this public resource, we have developed a package called nmrstarlib in the popular open-source programming language Python. The nmrstarlib’s implementation is very efficient, both in design and execution. The library has facilities for reading and writing both NMR-STAR version 2.1 and 3.1 formatted files, parsing them into usable Python dictionary- and list-based data structures, making access and manipulation of the experimental data very natural within Python programs (i.e. “saveframe” and “loop” records represented as individual Python dictionary data structures). Another major advantage of this design is that data stored in original NMR-STAR can be easily converted into its equivalent JavaScript Object Notation (JSON) format, a lightweight data interchange format, facilitating data access and manipulation using Python and any other programming language that implements a JSON parser/generator (i.e., all popular programming languages). We have also developed tools to visualize assigned chemical shift values and to convert between NMR-STAR and JSONized NMR-STAR formatted files. Full API Reference Documentation, User Guide and Tutorial with code examples are also available.We have tested this new library on all current BMRB entries: 100% of all entries are parsed without any errors for both NMR-STAR version 2.1 and version 3.1 formatted files. We also compared our software to three currently available Python libraries for parsing NMR-STAR formatted files: PyStarLib, NMRPyStar, and PyNMRSTAR.ConclusionsThe nmrstarlib package is a simple, fast, and efficient library for accessing data from the BMRB. The library provides an intuitive dictionary-based interface with which Python programs can read, edit, and write NMR-STAR formatted files and their equivalent JSONized NMR-STAR files. The nmrstarlib package can be used as a library for accessing and manipulating data stored in NMR-STAR files and as a command-line tool to convert from NMR-STAR file format into its equivalent JSON file format and vice versa, and to visualize chemical shift values. Furthermore, the nmrstarlib implementation provides a guide for effectively JSONizing other older scientific formats, improving the FAIRness of data in these formats.

JavaScript Object Notation (JSON) data serialization for IFC schema in web-based BIM data exchange

Abstract In the building industry, building data such as objects and processes are described in Industry Foundation Classes (IFC) data model schema to support a neutral data exchange format for BIM tools interoperability. While IFC specification has been encoded in ifcXML format by buildingSMART to support XML-based data transmission, there is a lack of studies on the implementation of IFC specification using JavaScript Object Notation (JSON) serialization. JSON is a key-value style lightweight data exchange format that has higher parsing efficiency than XML and due to the inadequacies of XML, JSON has been widely used in Web applications, specifically in Asynchronous JavaScript and XML (AJAX) Web services. This paper highlights the need for JSON implementation of IFC specification and introduces ifcJSON Schema and its data content. The main objective of this study is to outline how IFC specification can be represented in JSON format. Therefore, the study explains the implementation of the IFC standard as a JSON schema to guide the creation of JSON documents. The ifcJSON documents can be used for web-based data transfer as an alternative to XML documents. Since current IFC specification release is IFC4 Add1, the implementation of ifcJSON4 schema is specified and guidelines for generating and validating ifcJSON documents are described. Additionally, this paper implements ifcJSON4 schema in a use case within the precast concrete domain by indicating the data content for a precast building element with its corresponding geometry representation, product placement, and owner history data. The analysis of results indicates that ifcJSON4 schema developed in this paper is a valid JSON schema that can guide the creation of valid ifcJSON documents to be used for web-based data transfer and to improve interoperability of Cloud-based BIM applications.

JSON Implementation to Minimize the Use of the Number of Columns of a Table in a PostgreSQL Database

On the development of the database currently has become a very important thing, each will plan something, consider any thing we will need and use existing data in a database, The development of the database currently has become a very important thing, when we want to plan something and consider everything, we will need and use existing data in a database, PostgreSQL is one Object Relational Database Management Systems (DBMS) open source with a lot of features that are not less sophisticated to commercial databases. On daily use, it sometimes occurs a case that requires a dynamic column, therefore we should make the new columns to meet those needs. However, if each row of the table column requires different column and potentially need another ones, then it is going to be useless. On the research of utilizing the technology of JavaScript Object Notation (JSON),Json_encode PHP programming language can simplify the use of the column so that a new column is no longer needed when we want to create a new column on the table, we only need a new column that stores an array that has been converted into a JSON string forms the result of json_encode that represents the column name and the content of the columns of a table.

One-Page Multimedia Interactive Map

The relevance of local knowledge in cultural heritage is by now acknowledged. It helps to determine many community-based projects by identifying the material to be digitally maintained in multimedia collections provided by communities of volunteers, rather than for-profit businesses or government entities. Considering that the search and browsing of texts, images, video, and 3D models related to places is more essential than using a simple text-based search, an interactive multimedia map was implemented in this study. The map, which is loaded on a single HyperText Markup Language (HTML) page using AJAX (Asynchronous JavaScript and XML), with a client-side control mechanism utilising jQuery components that are both freely available and ad-hoc developed, is updated according to user interaction. To simplify the publication of geo-referenced information, the application stores all the data in a Geographic JavaScript Object Notation (GeoJSON) file rather than in a database. The multimedia contents—associated with the selected Points of Interest (PoIs)—can be selected through text search and list browsing as well as by viewing their previews one by one in a sequence all together in a scrolling window (respectively: “Table”, “Folder”, and “Tile” functions). PoIs—visualised on the map with multi-shape markers using a set of unambiguous colours—can be filtered through their categories and types, accessibility status and timeline, thus improving the system usability. The map functions are illustrated using data collected in a Comenius project. Notes on the application software and architecture are also presented in this paper.

Ontology driven meta-modelling of clinical documents

In recent days, distinct healthcare information systems use and exchange electronic clinical documents enormously. Further, modern technologies, such as connected home monitoring devices, incorporate contextual awareness into clinical documents. Besides this, today's healthcare domain is driven by emergence of new roles played by related stakeholders. Consequently, there is a need in healthcare information systems to achieve common semantic interpretation of clinical documents so that, 1) those can be exchanged among healthcare information systems meaningfully; 2) personalised document view in a specific context can be achieved effectively. To address these issues in this paper, an ontology driven meta-model for clinical documents is proposed. The proposed conceptualisation is implemented in an ontology editorial tool Protégé and illustrated using a case study based on e-prescription. Further, the specification is transformed towards JSON (Java Script Object Notation Schema) schema for demonstration of its practical utility.

Ontology driven meta-modelling of clinical documents

In recent days, distinct healthcare information systems use and exchange electronic clinical documents enormously. Further, modern technologies, such as connected home monitoring devices, incorporate contextual awareness into clinical documents. Besides this, today's healthcare domain is driven by emergence of new roles played by related stakeholders. Consequently, there is a need in healthcare information systems to achieve common semantic interpretation of clinical documents so that, 1) those can be exchanged among healthcare information systems meaningfully; 2) personalised document view in a specific context can be achieved effectively. To address these issues in this paper, an ontology driven meta-model for clinical documents is proposed. The proposed conceptualisation is implemented in an ontology editorial tool Protege and illustrated using a case study based on e-prescription. Further, the specification is transformed towards JSON (Java Script Object Notation Schema) schema for demonstration of its practical utility.

Creating Integrating Participatory Mapping Through a Web Application to Enable Public Involvement in City Planning: The Portneuf River Vision Study

This paper presents a conceptual framework for developing an online public participation geographic information system (PPGIS) to support community engagement in collaborative planning with stakeholders. Its basic characteristics include a lightweight, open internet standard data format GeoJSON (JavaScript Object Notation for geographical features), asynchronous communication between web browser and server, and open source server scripts using PHP and Python. This readily adaptable framework provides viewers with real-time processing and display of geo-comments, and preliminary descriptive statistics of participating social groups based on location and commentary themes. Visualizations are in the form pie charts and word clouds, which are understandable for a wide variety of non-expert GIS and/or urban planning users. This framework can also handle concurrent and multiple user requests. The advantage of this PPGIS web-based mapping application is that any web server can implement the workflow, and its real-time feedback feature supports the monitoring of social groups’ participation.

Utilizing Nested Normal Form to Design Redundancy Free JSON Schemas

JSON (JavaScript Object Notation) is a lightweight data-interchange format for the Internet. JSON is built on two structures: (1) a collection of name/value pairs and (2) an ordered list of values (http://www.json.org/). Because of this simple approach, JSON is easy to use and it has the potential to be the data interchange format of choice for the Internet. Similar to XML, JSON schemas allow nested structures to model hierarchical data. As data interchange over the Internet increases exponentially due to cloud computing or otherwise, redundancy free JSON data are an attractive form of communication because they improve the quality of data communication through eliminating update anomaly. Nested Normal Form, a normal form for hierarchical data, is a precise characterization of redundancy. A nested table, or a hierarchical schema, is in Nested Normal Form if and only if it is free of redundancy caused by multivalued and functional dependencies. Using Nested Normal Form as a guide, this paper introduces a JSON schema design methodology that begins with UML use case diagrams, communication diagrams and class diagrams that model a system under study. Based on the use cases’ execution frequencies and the data passed between involved parties in the communication diagrams, the proposed methodology selects classes from the class diagrams to be the roots of JSON scheme trees and repeatedly adds classes from the class diagram to the scheme trees as long as the schemas satisfy Nested Normal Form. This process continues until all of the classes in the class diagram have been added to some JSON scheme trees.

Computational Chemistry Data Management Platform Based on the Semantic Web

This paper presents a formal data publishing platform for computational chemistry using semantic web technologies. This platform encapsulates computational chemistry data from a variety of packages in an Extensible Markup Language (XML) file called CSX (Common Standard for eXchange). On the basis of a Gainesville Core (GC) ontology for computational chemistry, a CSX XML file is converted into the JavaScript Object Notation for Linked Data (JSON-LD) format using an XML Stylesheet Language Transformation (XSLT) file. Ultimately the JSON-LD file is converted to subject-predicate-object triples in a Turtle (TTL) file and published on the web portal. By leveraging semantic web technologies, we are able to place computational chemistry data onto web portals as a component of a Giant Global Graph (GGG) such that computer agents, as well as individual chemists, can access the data.

Definition of REST web services with JSON schema

SummaryThe Web has evolved from being a collection of documents to a collection of interconnected services that interoperate throughout the Internet. Web services are a natural consequence of this evolution. The web services model was initially centered around the eXtensible Markup Language (XML). Such services can be described by Web Services Description Language documents that are formally defined through the XML Schema Definition language. However, in recent years the popularity of XML‐based web services has declined, as more developers favor JavaScript Object Notation (JSON)‐based alternatives. Although the use of the latter language is spreading, no official standard to formally describe JSON documents exists. The aim of this article is to demonstrate how JSON Schema, and particularly the JSON Hyper Schema extension, is suitable to describe JSON‐based web services that follow the REST architectural pattern. Copyright © 2016 John Wiley & Sons, Ltd.

PENCARIAN INFORMASI DATA PESAWAT MENGGUNAKAN NOMOR REGISTRASI PESAWAT DENGAN MEMANFAATKAN DATABASE DAN JSON

Currently, not much o f public didn’t know about the information of data aircraft, the manufacture and type is sample. The aircraft also has registration number which not same between one aircraft with another aircraft. Information retrival of data aircraft can used registrationnumber with developed in an applicationwith take advantage of database and JSON (JavaScript Object Notation). JSON is a data exchange system that ’s easily translated in to the language o f computer or human. Data exchange these give mean make the distribution application base o f webservices. Web services is a system that provide service the another system to share resource. Procces o f made an application with base of web services must suitable with SOA (Service Oriented Architecture), where SOA is a model representation to up model shape which hasdistribution. For Implementation SOA, it can use the language of programming PHP (Hypertext Preprocessor). Tested on six aircraft, indicated o f airport and airline data can to point out that use of database and JSON can be run well. Decided o f internet network is an obtacle to present data.

SciData: a data model and ontology for semantic representation of scientific data.

With the move toward global, Internet enabled science there is an inherent need to capture, store, aggregate and search scientific data across a large corpus of heterogeneous data silos. As a result, standards development is needed to create an infrastructure capable of representing the diverse nature of scientific data. This paper describes a fundamental data model for scientific data that can be applied to data currently stored in any format, and an associated ontology that affords semantic representation of the structure of scientific data (and its metadata), upon which discipline specific semantics can be applied. Application of this data model to experimental and computational chemistry data are presented, implemented using JavaScript Object Notation for Linked Data. Full examples are available at the project website (Chalk in SciData: a scientific data model. http://stuchalk.github.io/scidata/, 2016).

Efficiency of JSON approach for Data Extraction and Query Retrieval

<p>Students’ Information System (SIS) in Universiti Sultan Zainal Abidin (UniSZA) handles thousands of records on the information of students, subject registration, etc. Efficiency of storage and query retrieval of these records is the matter of database management especially involving with huge data. However, the execution time for storing and retrieving these data are still considerably inefficient due to several factors. In this contribution, two database approaches namely Extensible Markup Language (XML) and JavaScript Object Notation (JSON) were investigated to evaluate their suitability for handling thousands records in SIS. The results showed JSON is the best choice for storage and query speed. These are essential to cope with the characteristics of students’ data. Whilst, XML and JSON technologies are relatively new to date in comparison to the relational database. Indeed, JSON technology demonstrates greater potential to become a key database technology for handling huge data due to an increase of data annually.</p>

Information system for image classification based on frequency curve proximity

With the size digital collections are currently reaching, retrieving the best match of a document from large collections by comparing hundreds of tags is a task that involves considerable algorithm complexity, even more so if the number of tags in the collection is not fixed. For these cases, similarity search appears to be the best retrieval method, but there is a lack of techniques suited for these conditions. This work presents a combination of machine learning algorithms put together to find the most similar object of a given one in a set of pre-processed objects based only on their metadata tags. The algorithm represents objects as character frequency curves and is capable of finding relationships between objects without an apparent association. It can also be parallelized using MapReduce strategies to perform the search. This method can be applied to a wide variety of documents with metadata tags. The case-study used in this work to demonstrate the similarity search technique is that of a collection of image objects in JavaScript Object Notation (JSON) containing metadata tags.

DATABASE HEALTH MONITORING (DHM) SEBAGAI ALAT MONITORING KESEHATAN DATABASE

DSS (Decision Support Systems) has the notion that a computer-based system that presents and process information that allows decisions to be more productive, dynamic and innovative [1]. In this study, a concept with the name DHM (Database Health Monitoring). DHM concept is a form of development of the DSS is a concept of how to analyze the health of a database in which the level of health in the database is measured by the number of empty fields. To calculate the number of empty fields required sql queries which query results are then processed into a protocol JSON (JavaScript Object Notation) is a concise format computer data exchange [6]. In JSON protocol is what ultimately made a dashboard. The results are displayed in the form of dashboards to facilitate leadership read the information received. In addition, the leadership does not need direct access to the database to get information.

Implementation of a non intrusive software component to monitor web applications in a public entity

La importancia de medir el tiempo de respuesta de las aplicaciones Web es transcendental para la toma de decisiones y/o correctivos por parte de los funcionarios públicos involucrados en los departamentos de tecnologías y sistemas de información. Esta investigación provee el marco conceptual del desarrollo de un componente J2EE (Java 2 Enterprise Edition) no intrusivo mediante filtros -Web de Servlets e Interceptors de Spring Framework. Así mismo, emplea el protocolo de comunicaciones TCP/IP para el envío de tramas en el formato JSON (JavaScript Object Notation) y su posterior recepción por un componente stand-alone para el registro en una base de datos. Finalmente, se realiza una prueba de hipótesis entre las tecnologías Log4j y Socket Simple, logrando determinar un tiempo de registro promedio de la tramas aproximado a 0.05 segundos, así como señalar que no existen evidencias estadísticas suficientes para afirmar que una sea más óptima y/o rápida que la otra.

An Online Atlas for Exploring Spatio-Temporal Patterns of Cancer Mortality (1972-2011) and Incidence (1995-2008) in Taiwan.

Public health mapping and Geographical Information Systems (GIS) are already being used to locate the geographical spread of diseases. This study describes the construction of an easy-to-use online atlas of cancer mortality (1972–2011) and incidence (1995–2008) in Taiwan.Two sets of color maps were made based on “age-adjusted mortality by rate” and “age-adjusted mortality by rank.” AJAX (Asynchronous JavaScript and XML), JSON (JavaScript Object Notation), and SVG (Scaling Vector Graphic) were used to create the online atlas. Spatio-temporal patterns of cancer mortality and incidence in Taiwan over the period from 1972 to 2011 and from 1995 to 2008.The constructed online atlas contains information on cancer mortality and incidence (http://taiwancancermap.csmu-liawyp.tw/). The common GIS functions include zoom and pan and identity tools. Users can easily customize the maps to explore the spatio-temporal trends of cancer mortality and incidence using different devices (such as personal computers, mobile phone, or pad). This study suggests an easy- to-use, low-cost, and independent platform for exploring cancer incidence and mortality. It is expected to serve as a reference tool for cancer prevention and risk assessment.This online atlas is a cheap and fast tool that integrates various cancer maps. Therefore, it can serve as a powerful tool that allows users to examine and compare spatio-temporal patterns of various maps. Furthermore, it is an-easy-to use tool for updating data and assessing risk factors of cancer in Taiwan.

JSONDiscoverer: Visualizing the schema lurking behind JSON documents

The so-called API economy is pushing more and more companies to provide open Web APIs to access their data, typically using the JavaScript Object Notation (JSON) as interchange data format. While JSON has been designed to be easy to read and parse, their structure is implicit. This poses a serious problem when consuming and integrating Web APIs from different sources since it forces us to manually analyze each individual API in detail. This paper presents JSONDiscoverer, a tool that alleviates this problem by discovering (and visualizing) the implicit schema of JSON documents as well as possible composition links among JSON-based Web APIs.Tool website: http://som-research.uoc.edu/tools/jsonDiscoverer