The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
We are interested in forecasting a large collection of FMCG demand time series. As the demand of FMCG exists in a hierarchy (from manufacturers to distributors to retailers), the bottom level of the hierarchy may contain thousands or even millions of time series. Producing aggregate consistent forecasts while utilizing the unique features from each time series thus become a technical challenge. To...
Recent advances in microscopy imaging and genomics have created an explosion of patient data in the pathology domain. Whole-slide images (WSIs) of tissues can now capture disease processes as they unfold in high resolution, recording the visual cues that have been the basis of pathologic diagnosis for over a century. Each WSI contains billions of pixels and up to a million or more microanatomic objects...
Generating the maximum number of visual patterns by uncovering the entire space of possible visual designs remains a challenge within the construction process of information visualization. Users interact with different mindsets consisting of design, data analysis, application development, and hardware resource usage. Therefore, they desire a flexible and productive interface that keeps them clued...
Capturing human movement has become available in detail due to the advancement of motion sensor technology integrated by micro-machine and also due to the one of optical recording by high speed and high resolution image sensors. Therefore, we can easily record the human activity as the body movement BigData and analyze it to quest skill to become an expert of a target body movement. Especially, in...
Transaction and high availability are both important to applications. While data partition, distribution and replication are the three key mechanisms to guarantee high availability, a coordination to reach consensuses on replica state transitions, transaction operation orders and commit decisions is required for transaction processing. This coordination impairs transaction processing performance....
Readmissions to a hospital after procedures are costly and considered to be an indication of poor quality. As Per the Affordable Care Act of 2010, hospitals may be reimbursed at a reduced rate for patients readmitted to a hospital within 30 days of discharge. In this project, we used statistical and machine-learning methods to analyze the Nationwide Inpatient Sample dataset provided by HCUP (Healthcare...
Data of all sizes, generated by simulation and observation (i.e., instruments and satellites) activities, should be collected, stored, and organized, along with associated tools and research results, so that they are easily discoverable and accessible. Most observational data capture conditions at an exact point in time and are thus not reproducible, therefore it is imperative that initial data be...
It is a challenge to visualize high dimensional data such as project data to yield new and interesting types of insights. To address this, we augment the traditional PERT network diagram with additional nodes that represent resources, and with arcs from the resource nodes to the activities that use those resources. Subsequently, we apply various graph layout algorithms that can reveal the hidden patterns...
In this study we analyzed a series of LiDAR point clouds acquired over Taijiang district (part of Fujian province, China). The objective was to detect and extract water surface area from individual LiDAR point cloud, in a parallel means. To this end, interactive visualization of fine-grained data, global cluster algorithms, and statistical investigation were applied. We first rasterized point clouds...
With rapidly growing computing power, ultra high-resolution Earth science simulations with a long period of time are feasible. However, it is still very challenging to distribute and analyze a huge amount of simulation results, which could be over 100TB. One key reason is that typical Earth science data are represented in NetCDF, which is not supported by the popular and powerful Hadoop Distribute...
Big Data constitutes an opportunity for companies to empower their analysis. However, at the moment there is no standard way for approaching Big Data projects. This, coupled with the complex nature of Big Data, is the cause that many Big Data projects fail or rarely obtain the expected return of investment. In this paper, we present a methodology to tackle Big Data projects in a systematic way, avoiding...
Visualizing many events over long time periods poses a unique set of challenges. We show how two-dimensional plots displaying the timings between events can reveal both outliers and hidden structure. Adopted from the field of chaotic systems, these "time maps" allow users to identify features that can take place on timescales ranging from milliseconds to months, all within a single image...
Dimensionality Reduction (DR) is a crucial tool to facilitate high-dimensional data analysis. As the volume and the variety of features used to describe a phenomenon keeps increasing, DR has become not only desirable but paramount. However, DR can result in unreliable depictions of data. The uncertainties involved in DR may stem from the selection of methods, parameter configurations, and the constraints...
The availability of massive volumes of trajectory data has made it convenient for the study of different types of movement behaviors. Among them, bi-directional movement behaviors exist ubiquitously in our daily life, from urban traffic to animal migration, and from sports to wars. To analyze bi-directional movement behaviors, people need to compare movements in two directions simultaneously for detecting...
The rapid converging of big data and IoT (Internet of Things) technologies provides more opportunities in the area of road traffic applications. In this paper, we discuss a timeline visualization tool which enables us to better understand of traffic behaviors from road traffic big data.
We consider constrained label placement problem considering touch interface such as smartphone or tablet. For scientific dataset search, the search results are shown on the global map based on spatial information. There spatial region are often unevenly distributed and most of them are overlapped each other. To select non-overlapped regions from overlapped regions can be considered as a combinational...
Dynamically mining textual information streams to gain real-time situational awareness is especially challenging with social media systems where throughput and velocity properties push the limits of a static analytical approach. In this paper, we describe an interactive visual analytics system, called Matisse, that aids with the discovery and investigation of trends in streaming text. Matisse addresses...
In this paper, we propose strategies and objectives for immersive data visualization with applications in materials science using the Oculus Rift virtual reality headset. We provide background on currently available analysis tools for neutron scattering data and other large-scale materials science projects. In the context of the current challenges facing scientists, we discuss immersive virtual reality...
Automatically extracting events from large, unstructured/semi-structured textual data requires a mechanism for identifying the event, abstracting it from the text, validating the event's occurrence against some known values, and sharing the event with users effectively. Inherent in the challenge of Big Data is that it often exceeds a scale at which humans can effectively operate. In this paper, we...
The success of the Hadoop MapReduce programming model has greatly propelled research in big data analytics. In recent years, there is a growing interest in the High Performance Computing (HPC) community to use Hadoop-based tools for processing scientific data. This interest is due to the facts that data movement becomes prohibitively expensive, highperformance data analytic becomes an important part...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.