The healthcare industry is one of the most significant sources of Big data. It is not feasible to manually interpret and understand the huge amounts of data generated by hospitals accurately. This creates the need for...
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ISBN:
(纸本)9781665400268
The healthcare industry is one of the most significant sources of Big data. It is not feasible to manually interpret and understand the huge amounts of data generated by hospitals accurately. This creates the need for a data analytics and visualization tool. visualizations are intuitive and help interpret the data easily. It would help the hospital to get insights from the data and to provide better service to the society. The aim of this project was to develop a data analysis and visualization tool for a hospital. This was implemented as a web application. The web application is developed using Django, which is a Python-based free and open-source web framework. For the visualizations embedded in the application, the Python library Altair was used. The application supports the upload of files that are the source for the visualizations and provides interactive visualizations based on the analysis performed. The visualizations can be exported as images using the application. Generating visualizations of choice becomes easier using navigation by menu bars in the application rather than writing complicated queries to the database. The tool ultimately attempts to help the hospital optimize time and resources effectively. Prediction using Long Short Term Memory (LSTM) for pharmacy orders and number of orders per patient will further help the hospital predict trends, patterns and outliers. Analysis tools will help analysing past, current and predict future pharmacy and diagnostics in a hospital which ultimately lead to better quality, efficient smart healthcare.
As the Internet of Things (IoT) grows rapidly, huge amounts of wireless sensor networks emerged monitoring a wide range of infrastructure, in various domains such as healthcare, energy, transportation, smart city, bui...
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ISBN:
(纸本)9781450388337
As the Internet of Things (IoT) grows rapidly, huge amounts of wireless sensor networks emerged monitoring a wide range of infrastructure, in various domains such as healthcare, energy, transportation, smart city, building automation, agriculture, and industry producing continuously streamlines of data. Big data technologies play a significant role within IoT processes, as visual analytics tools, generating valuable knowledge in real-time in order to support critical decision making. This paper provides a comprehensive survey of visualization methods, tools, and techniques for the IoT. We position data visualization inside the visual analytics process by reviewing the visual analytics pipeline. We provide a study of various chart types available for data visualization and analyze rules for employing each one of them, taking into account the special conditions of the particular use case. We further examine some of the most promising visualization tools. Since each IoT domain is isolated in terms of Big data approaches, we investigate visualization issues in each domain. Additionally, we review visualization methods oriented to anomaly detection. Finally, we provide an overview of the major challenges in IoT visualizations.
Purpose: This paper aims to introduce the use of data visualization tool, the Viewshare, in library environment. Design/methodology/approach: Viewshare has been successfully adopted in various institutions for depicti...
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As mobile visualization is increasingly used and new mobile device form factors and hardware capabilities continuously emerge, it is timely to reflect on what has been discovered to date and to look into the future. T...
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ISBN:
(纸本)9781450356213
As mobile visualization is increasingly used and new mobile device form factors and hardware capabilities continuously emerge, it is timely to reflect on what has been discovered to date and to look into the future. This workshop will bring together researchers, designers, and practitioners from relevant application and research fields, including visualization, personal informatics, and data journalism. We will work on identifying a research agenda for mobile data visualization as well as to collect and propagate practical guidance for mobile visualization design. Our overarching goal is to bring us closer to making an effective use of ubiquitous mobile devices as data visualization platforms.
Today, complex logistics operations include different levels of communication and interactions. This paper explores the requirements of these operations and conceptualizes important key performance indicators, stakeho...
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ISBN:
(纸本)9789897583063
Today, complex logistics operations include different levels of communication and interactions. This paper explores the requirements of these operations and conceptualizes important key performance indicators, stakeholders, and different data visualizations to support the stakeholders in order to understand interactions between entities easier and faster. Three different levels were identified-supply chain, automated warehouse, and intelligent agent-to define the complex logistics operations. For each level, important stakeholders and performance indicators were determined. A case study was designed and described to exemplify the role of cyber-physical systems in complex logistics operations. Moreover, different data visualizations were developed as part of a dashboard to illustrate key performance indicators of different levels for the purpose of supporting stakeholders. This exploratory study concludes by identifying important data necessity for each performance indicator, suggesting ways to collect these data, and exemplifying how data visualization approach can be used through a dashboard design.
In contrast to the previous studies that have conducted visual analyses of refugee documentaries, the aim of this study is to provide new insight into how the refugee crisis in Indochina has been portrayed in the Japa...
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This article investigates population journalism, a fin-de-siecle periodical genre that combined data visualization with narrative analysis of vital statistics about human populations. Through the visualization of popu...
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This article investigates population journalism, a fin-de-siecle periodical genre that combined data visualization with narrative analysis of vital statistics about human populations. Through the visualization of population data, population journalism combined Victorian popular culture and population politics, or what Michel Foucault terms 'biopolitics'. Following an overview of biopolitics, vital statistics, and data visualization in the long nineteenth century, the article focuses on population journalism in Pearson's Magazine to examine how this genre combined the verbal rhetoric of statistical narrative with the visual, spatial, and material aesthetics of data visualization to represent the British nation as a managed population body. Pearson's used two types of images for its population journalism: abstract data visualizations reproduced by line-block engraving and photorealistic data visualizations reproduced by halftone engraving. Through their respective aesthetics, the abstract and photorealistic population visualizations imbricated modern image reproduction technology and modern statistical methods, encouraging readers to conflate population politics with popular culture. While the abstract visualizations rationalized the individual body as an abstract population unit, the photorealistic visualizations remediated the individual body as a component of multimodal, mass print spectacle. This case study demonstrates that historical and contemporary population data visualization, as a set of practices for quantifying human life, enacts a biopolitics of normalization. My analysis also shows that fully understanding this politics requires attention to the roles played by the medium and aesthetic affordances of a particular data visualization, the media literacy of its users, and the ideological genealogy of the data visualization practices that produced it.
This research draws inspiration from the desire to help sustain and boost the production of abaca in Catanduanes being the topmost abaca producing province in the Philippines through an information campaign in a websi...
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ISBN:
(纸本)9781450365093
This research draws inspiration from the desire to help sustain and boost the production of abaca in Catanduanes being the topmost abaca producing province in the Philippines through an information campaign in a website with the application of data visualization tools and techniques. Result of this research will draw attention about the usefulness and benefits that could be derived through the production of abaca in uplifting the socioeconomic status and standard of living of farmers. Likewise, this research would also support the rural development program of the government on embracing climate-resilient ecological farming practices to adjust to climate change. Sustainability of the abaca production in the province means ensuring vibrancy of economy especially for the abaca farmers. Demographic data about abaca production were obtained from the abaca concerned government offices in Catanduanes. Documentary analysis, Interview, Website development and evaluation were the methodologies employed in this investigation. Likewise, a survey questionnaire was utilized to gather data about the usability of the website from the persons from government agencies that are concerned on abaca and website development. Three (3) criteria were used to evaluate the usability of the website - usefulness, ease of use and satisfaction. Frequency count and weighted mean were the statistics used in analyzing the responses and the respondents have generally evaluated the developed website as "Strongly Agree".
In modem electronics one of the most important target is to make reliability tests shorter and more effective. To solve that problem, the novel fast data acquisition system was developed. It uses fast FPGA modules, a ...
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ISBN:
(纸本)9781424428137
In modem electronics one of the most important target is to make reliability tests shorter and more effective. To solve that problem, the novel fast data acquisition system was developed. It uses fast FPGA modules, a microcontroller for fast-response feedback and FPGA control as well as transmission of the data to PC over Ethernet protocol. Single test lasts for many days and produces large amount of data. It is necessary to acquire, store and visualize data in efficient way. There is no commercial product, which can handle multiple channel data acquisition and visualization over Ethernet protocol in real-time and provide very short response times. To improve quality of detection algorithms, there is a possibility to set-up custom triggers directly from visualization module. Software is written using only standard Win32 API, and is fully and compatible with all Windows (R) based PC (it is independent from specific OS version). Using this solution together with our propriety classes, it was possible to achieve very high efficiency and flexibility. The main advantage of using an Ethernet protocol in control system is a possibility of flexible, fast and reliable data transfer between multiple devices (measuring unit, control unit, storage unit) on existing network infrastructure (IEEE 802.1). [GRAPHICS] Although the Ethernet does not guarantee reliable data delivery, we improved its reliability simply sending multiple copies of each packet. Because usually we use only few percent of the network throughput (using 100Mbit/s links) sending spare data packets doesn't increase network load significantly.
Although the use of tables, graphs, and figures to summarize information has long existed, the advent of the big data era and improved computing power has brought renewed attention to the field of data visualization. ...
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Although the use of tables, graphs, and figures to summarize information has long existed, the advent of the big data era and improved computing power has brought renewed attention to the field of data visualization. As such, it is crucial that introductory statistics courses train students to become critical authors and consumers of data visualizations. To that end, we have developed a semester-long, instructor-supported, group project that exposes students to this growing field. We have found this project to be an exciting and effective way to teach students the power of statistics and, more importantly, the critical role context plays when interpreting statistics. Among the many benefits of this project are hands-on learning, improved mathematical reasoning, and better collaboration and communication skills. In this article, we describe the project structure, project assessment, and techniques for facilitating effective group work.
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