scholarly journals SilkViser: A Visual Explorer of Blockchain-based Cryptocurrency Transaction Data

2020 ◽  
Author(s):  
Ying Zhao
Keyword(s):  
User Study ◽  
Data Exploration ◽  
Transaction Data ◽  
Free Data ◽  
Novice Users ◽  
Copper Coin

<p>Many blockchain-based cryptocurrencies provide users with online blockchain explorers for viewing online transaction data. However, traditional blockchain explorers mostly present transaction information in textual and tabular forms. Such forms make understanding cryptocurrency transaction mechanisms difficult for novice users (NUsers). They are also insufficiently informative for experienced users (EUsers) to recognize advanced transaction information. This study introduces a new online cryptocurrency transaction data viewing tool called SilkViser. Guided by detailed scenario and requirement analyses, we create a series of appreciating visualization designs, such as paper ledger-inspired block and blockchain visualizations and ancient copper coin-inspired transaction visualizations, to help users understand cryptocurrency transaction mechanisms and recognize advanced transaction information. We also provide a set of lightweight interactions to facilitate easy and free data exploration. Moreover, a controlled user study is conducted to quantitatively evaluate the usability and effectiveness of SilkViser. Results indicate that SilkViser can satisfy the requirements of NUsers and EUsers. Our visualization designs can compensate for the inexperience of NUsers in data viewing and attract potential users to participate in cryptocurrency transactions.</p>

scholarly journals SilkViser: A Visual Explorer of Blockchain-based Cryptocurrency Transaction Data

2020 ◽  
Author(s):  
Ying Zhao
Keyword(s):  
User Study ◽  
Data Exploration ◽  
Transaction Data ◽  
Free Data ◽  
Novice Users ◽  
Copper Coin

<p>Many blockchain-based cryptocurrencies provide users with online blockchain explorers for viewing online transaction data. However, traditional blockchain explorers mostly present transaction information in textual and tabular forms. Such forms make understanding cryptocurrency transaction mechanisms difficult for novice users (NUsers). They are also insufficiently informative for experienced users (EUsers) to recognize advanced transaction information. This study introduces a new online cryptocurrency transaction data viewing tool called SilkViser. Guided by detailed scenario and requirement analyses, we create a series of appreciating visualization designs, such as paper ledger-inspired block and blockchain visualizations and ancient copper coin-inspired transaction visualizations, to help users understand cryptocurrency transaction mechanisms and recognize advanced transaction information. We also provide a set of lightweight interactions to facilitate easy and free data exploration. Moreover, a controlled user study is conducted to quantitatively evaluate the usability and effectiveness of SilkViser. Results indicate that SilkViser can satisfy the requirements of NUsers and EUsers. Our visualization designs can compensate for the inexperience of NUsers in data viewing and attract potential users to participate in cryptocurrency transactions.</p>

Conceptual Three-Dimensional Modeling Using Intuitive Gesture-Based Midair Three-Dimensional Sketching Technique

2018 ◽  
Vol 18 (4) ◽  
Author(s):  
Jinmiao Huang ◽  
Rahul Rai
Keyword(s):  
User Study ◽  
Low Cost ◽  
Three Dimensional ◽  
3D Models ◽  
Interaction Technique ◽  
Three Dimensional Modeling ◽  
Study Results ◽  
Novice Users ◽  
Technical Solutions ◽  
3D Shapes

We introduce an intuitive gesture-based interaction technique for creating and manipulating simple three-dimensional (3D) shapes. Specifically, the developed interface utilizes low-cost depth camera to capture user's hand gesture as the input, maps different gestures to system commands and generates 3D models from midair 3D sketches (as opposed to traditional two-dimensional (2D) sketches). Our primary contribution is in the development of an intuitive gesture-based interface that enables novice users to rapidly construct conceptual 3D models. Our development extends current works by proposing both design and technical solutions to the challenges of the gestural modeling interface for conceptual 3D shapes. The preliminary user study results suggest that the developed framework is intuitive to use and able to create a variety of 3D conceptual models.

scholarly journals MudGet: Reproduction of the desired lighting environment using a smart-LED

2017 ◽  
Vol 4 (3) ◽  
pp. 231-237 ◽  
Author(s):  
Yong Hwi Kim ◽  
Yong Yi Lee ◽  
Bilal Ahmed ◽  
Moon Gu Son ◽  
Junho Choi ◽  
...  
Keyword(s):  
Interior Design ◽  
Digital Image ◽  
Clustering Algorithm ◽  
User Study ◽  
Lighting Design ◽  
Novice Users ◽  
Lighting Environment ◽  
Color Clustering ◽  
Lighting Systems ◽  
Intuitive Interface

Abstract With the emergence of smart LEDs, lighting based interior design is becoming popular. However, most of the smart LED-based lighting systems rely on expert-human intervention to create a desired atmosphere. For convenience, commercial lighting systems offer a number of options but their usability is fairly restricted. Therefore, an intuitive interface is required for novice users to generate the desired lighting environment. In this paper, we have developed a software, named MudGet, which automatically extracts the light mood from a digital image and controls the LED lamps to reproduce a desired lighting effect according to the extracted light mood. In our method, the light mood is regarded as a set of the representative colors of the digital image. The representative colors are extracted by utilizing K-means clustering algorithm. The dimming parameters are set for which each of the LED lamps create the lighting environment with the mood extracted by the software. To evaluate the feasibility of mood reproduction qualitatively, the degree of similarity between the light mood in the digital image and the reproduced result using LEDs is evaluated by a user study under a miniaturized experimental set. We observe that users can easily produce a desired atmosphere through the proposed MudGet software. Highlights An image based lighting design interface is proposed. The interface controls customized LED module wirelessly. Desired lighting effect is generated from the color clustering centers of image.

scholarly journals Pattern-Driven Navigation in 2D Multiscale Visualizations with Scalable Insets

2018 ◽  
Author(s):  
Fritz Lekschas ◽  
Michael Behrisch ◽  
Benjamin Bach ◽  
Peter Kerpedjiev ◽  
Nils Gehlenborg ◽  
...  
Keyword(s):  
Visual Search ◽  
User Study ◽  
Frequency Estimation ◽  
Visual Representations ◽  
Data Exploration ◽  
Navigational Cues ◽  
Large Numbers ◽  
Speed Up ◽  
Pattern Comparison ◽  
The Cost

AbstractWe present Scalable Insets, a technique for interactively exploring and navigating large numbers of annotated patterns in multiscale visualizations such as gigapixel images, matrices, or maps. Exploration of many but sparsely-distributed patterns in multiscale visualizations is challenging as visual representations change across zoom levels, context and navigational cues get lost upon zooming, and navigation is time consuming. Our technique visualizes annotated patterns too small to be identifiable at certain zoom levels using insets, i.e., magnified thumbnail views of the annotated patterns. Insets support users in searching, comparing, and contextualizing patterns while reducing the amount of navigation needed. They are dynamically placed either within the viewport or along the boundary of the viewport to offer a compromise between locality and context preservation. Annotated patterns are interactively clustered by location and type. They are visually represented as an aggregated inset to provide scalable exploration within a single viewport. In a controlled user study with 18 participants, we found that Scalable Insets can speed up visual search and improve the accuracy of pattern comparison at the cost of slower frequency estimation compared to a baseline technique. A second study with 6 experts in the field of genomics showed that Scalable Insets is easy to learn and provides first insights into how Scalable Insets can be applied in an open-ended data exploration scenario.

scholarly journals A comparative user study of visualization techniques for cluster analysis of multidimensional data sets

2020 ◽  
Vol 19 (4) ◽  
pp. 318-338 ◽  
Author(s):  
Elio Ventocilla ◽  
Maria Riveiro
Keyword(s):  
User Study ◽  
Quality Measures ◽  
Multidimensional Data ◽  
Data Sets ◽  
Data Set ◽  
Novice Users ◽  
Data Points ◽  
Perceived Usability ◽  
Multidimensional Data Sets ◽  
Cluster Quality

This article presents an empirical user study that compares eight multidimensional projection techniques for supporting the estimation of the number of clusters, [Formula: see text], embedded in six multidimensional data sets. The selection of the techniques was based on their intended design, or use, for visually encoding data structures, that is, neighborhood relations between data points or groups of data points in a data set. Concretely, we study: the difference between the estimates of [Formula: see text] as given by participants when using different multidimensional projections; the accuracy of user estimations with respect to the number of labels in the data sets; the perceived usability of each multidimensional projection; whether user estimates disagree with [Formula: see text] values given by a set of cluster quality measures; and whether there is a difference between experienced and novice users in terms of estimates and perceived usability. The results show that: dendrograms (from Ward’s hierarchical clustering) are likely to lead to estimates of [Formula: see text] that are different from those given with other multidimensional projections, while Star Coordinates and Radial Visualizations are likely to lead to similar estimates; t-Stochastic Neighbor Embedding is likely to lead to estimates which are closer to the number of labels in a data set; cluster quality measures are likely to produce estimates which are different from those given by users using Ward and t-Stochastic Neighbor Embedding; U-Matrices and reachability plots will likely have a low perceived usability; and there is no statistically significant difference between the answers of experienced and novice users. Moreover, as data dimensionality increases, cluster quality measures are likely to produce estimates which are different from those perceived by users using any of the assessed multidimensional projections. It is also apparent that the inherent complexity of a data set, as well as the capability of each visual technique to disclose such complexity, has an influence on the perceived usability.

scholarly journals DataSite: Proactive visual data exploration with computation of insight-based recommendations

2018 ◽  
Vol 18 (2) ◽  
pp. 251-267 ◽  
Author(s):  
Zhe Cui ◽  
Sriram Karthik Badam ◽  
M Adil Yalçin ◽  
Niklas Elmqvist
Keyword(s):  
Data Analysis ◽  
Visual Analytics ◽  
Domain Knowledge ◽  
Recommendation System ◽  
User Study ◽  
Data Exploration ◽  
Server Side ◽  
Knowledge Requirements ◽  
High Knowledge ◽  
Visual Data Exploration

Effective data analysis ideally requires the analyst to have high expertise as well as high knowledge of the data. Even with such familiarity, manually pursuing all potential hypotheses and exploring all possible views is impractical. We present DataSite, a proactive visual analytics system where the burden of selecting and executing appropriate computations is shared by an automatic server-side computation engine. Salient features identified by these automatic background processes are surfaced as notifications in a feed timeline. DataSite effectively turns data analysis into a conversation between analyst and computer, thereby reducing the cognitive load and domain knowledge requirements. We validate the system with a user study comparing it to a recent visualization recommendation system, yielding significant improvement, particularly for complex analyses that existing analytics systems do not support well.

scholarly journals Evaluating Immersive Approaches to Multidimensional Information Visualization

2019 ◽  
Author(s):  
Jorge A. Wagner Filho ◽  
Carla M. D. S. Freitas ◽  
Luciana Nedel
Keyword(s):  
Information Visualization ◽  
User Study ◽  
Direct Interaction ◽  
Data Exploration ◽  
Multidimensional Data ◽  
Frequent User ◽  
Multidimensional Information ◽  
Immersive Environment ◽  
Time Overhead ◽  
User Comfort

This dissertation investigates the use of Virtual Reality for the exploration of multidimensional data represented as 3D scatterplots. After an initial user study indicated that an immersive environment required less effort to find information and less navigation, but resulted in inefficient times and frequent user discomfort, we proposed and evaluated an alternative data exploration approach based on the use of physical movements, direct interaction with data at arms reach and a virtual reproduction of the analysts work desk. Through a second study, we demonstrate that this setup, named VirtualDesk, presents excellent results regarding user comfort, and performs equally or better in all tasks, while adding minimal or no time overhead and amplifying data exploration.

scholarly journals Cloudy with a chance of peptides: accessibility, scalability and reproducibility with cloud-hosted environments

2020 ◽  
Author(s):  
Benjamin Neely
Keyword(s):  
High Performance ◽  
Mass Spectrometry Data ◽  
Remote Work ◽  
Label Free ◽  
Research Groups ◽  
Data Set ◽  
Transformative Potential ◽  
Free Data ◽  
Novice Users ◽  
Computational Resources

Cloud-hosted environments offer known benefits when computational needs outstrip affordable local workstations, enabling high-performance compute without a physical cluster. What has been less apparent, especially to novice users, is the transformative potential for cloud-hosted environments to bridge the digital divide that exists between poorly funded and well-resourced laboratories, and to empower modern research groups with remote personnel and trainees. Using cloud-based proteomic bioinformatic pipelines is not predicated on analyzing thousands of files, but instead can be used to improve accessibility during remote work, extreme weather or working with under-resourced remote trainees. The general benefits of cloud-hosted environments also allow for scalability and encourage reproducibility. Since one possible hurdle to adoption is awareness, this paper is written with the non-expert in mind. The benefits and possibilities of using a cloud-hosted environment are emphasized by describing how to setup an example workflow to analyze a previously published label-free data-dependent acquisition mass spectrometry data set of mammalian urine. Cost and time of analysis are compared using different computational tiers, and important practical considerations are described. Overall, cloud-hosted environments offer the potential to solve large computational problems, but more importantly can enable and accelerate research in smaller research groups with inadequate infrastructure and suboptimal local computational resources.

Using an Avatar, RFID & speech recognition for hands-free data collection

2008 ◽  
Author(s):  
Kristie Nemeth ◽  
Nicole Arbuckle ◽  
Andrea Snead ◽  
Drew Bowers ◽  
Christopher Burneka ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Data Collection ◽  
Free Data

Pemanfaatan Metode K-Means Dalam Penentuan Persediaan Barang

2018 ◽  
Vol 6 (1) ◽  
pp. 41-48
Author(s):  
Santoso Setiawan
Keyword(s):  
Data Mining ◽  
Stock Management ◽  
Transaction Data ◽  
Business People ◽  
Cluster Data ◽  
Data Clusters ◽  
Inventory Strategy ◽  
Transactional Data

Abstract   Inaccurate stock management will lead to high and uneconomical storage costs, as there may be a void or surplus of certain products. This will certainly be very dangerous for all business people. The K-Means method is one of the techniques that can be used to assist in designing an effective inventory strategy by utilizing the sales transaction data that is already available in the company. The K-Means algorithm will group the products sold into several large transactional data clusters, so it is expected to help entrepreneurs in designing stock inventory strategies.   Keywords: inventory, k-means, product transaction data, rapidminer, data mining   Abstrak   Manajemen stok yang tidak akurat akan menyebabkan biaya penyimpanan yang tinggi dan tidak ekonomis, karena kemungkinan terjadinya kekosongan atau kelebihan produk tertentu. Hal ini sangat berbahaya bagi para pelaku bisnis. Metode K-Means adalah salah satu teknik yang dapat digunakan untuk membantu dalam merancang strategi persediaan yang efektif dengan memanfaatkan data transaksi penjualan yang telah tersedia di perusahaan. Algoritma K-Means akan mengelompokkan produk yang dijual ke beberapa cluster data transaksi yang umumnya besar, sehingga diharapkan dapat membantu pengusaha dalam merancang strategi persediaan stok.   Kata kunci: data transaksi produk, k-means, persediaan, rapidminer, data mining.

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