Dear colleagues,

new journal: “Visual Informatics”
( https://www.journals.elsevier.com/visual-informatics/ )
,which is a peer-reviewed, online journal with open access to the academic community and mainly concerned with the theory and algorithms on perception based visual information modeling, synthesis and processing .

The contents of its high cited articles are attached below for you reference:

1、Towards better analysis of machine learning models: A visual analytics perspective

Shixia Liu, Xiting Wang, Mengchen Liu, Jun Zhu Tsinghua University, Beijing, China

Abstract：Interactive model analysis, the process of understanding, diagnosing, and refining a machine learning model with the help of interactive visualization, is very important for users to efficiently solve real-world artificial intelligence and data mining problems. Dramatic advances in big data analytics have led to a wide variety of interactive model analysis tasks. In this paper, we present a comprehensive analysis and interpretation of this rapidly developing area. Specifically, we classify the relevant work into three categories: understanding, diagnosis, and refinement. Each category is exemplified by recent influential work. Possible future research opportunities are also explored and discussed.
key words: Interactive model analysis, Interactive visualization, Machine learning, Understanding, Diagnosis, Refinement
DOI:10.1016/j.visinf.2017.01.006
2、Recent advances in transient imaging: A computer graphics and vision perspective

Adrian Jarabo, Belen Masia, Julio Marco, Diego Gutierrez Universidad de Zaragoza - I3A, Zaragoza 50018, Spain

Abstract:Transient imaging has recently made a huge impact in the computer graphics and computer vision fields. By capturing, reconstructing, or simulating light transport at extreme temporal resolutions, researchers have proposed novel techniques to show movies of light in motion, see around corners, detect objects in highly-scattering media, or infer material properties from a distance, to name a few. The key idea is to leverage the wealth of information in the temporal domain at the pico or nanosecond resolution, information usually lost during the capture-time temporal integration. This paper presents recent advances in this field of transient imaging from a graphics and vision perspective, including capture techniques, analysis, applications and simulation.
Key words: Transient imaging Ultrafast imaging Time-of-flight
DOI:10.1016/j.visinf.2017.01.008

3、2.Support-free interior carving for 3D printing

Yue Xie, Xiang Chen

Abstract:Recent interior carving methods for functional design necessitate a cumbersome cut-and-glue process in fabrication. We propose a method to generate interior voids which not only satisfy the functional purposes but are also support-free during the 3D printing process. We introduce a support-free unit structure for voxelization and derive the wall thicknesses parametrization for continuous optimization. We also design a discrete dithering algorithm to ensure the printability of ghost voxels. The interior voids are iteratively carved by alternating the optimization and dithering. We apply our method to optimize the static and rotational stability, and print various results to evaluate the efficacy.
Key words: Interior carving ; Support-free ; Voxels dithering ; Shape optimization ; 3D printing
DOI:10.1016/j.visinf.2017.01.002

4、4.Visual exploration of movement and event data with interactive time masks,

Abstract:Natalia Andrienko Gennady Andrienko, Elena Camossi, Christophe Claramunt, Jose Manuel Cordero Garcia, Georg Fuchs, Melita Hadzagic, Anne-Laure Jousselme, Cyril Ray, David Scarlatti, George Vouros
We introduce the concept of time mask, which is a type of temporal filter suitable for selection of multiple disjoint time intervals in which some query conditions fulfil. Such a filter can be applied to timereferenced objects, such as events and trajectories, for selecting those objects or segments of trajectories that fit in one of the selected time intervals. The selected subsets of objects or segments are dynamically summarized in various ways, and the summaries are represented visually on maps and/or other displays to enable exploration. The time mask filtering can be especially helpful in analysis of disparate data (e.g., event records, positions of moving objects, and time series of measurements), which may come from different sources. To detect relationships between such data, the analyst may set query conditions on the basis of one dataset and investigate the subsets of objects and values in the other datasets that co-occurred in time with these conditions. We describe the desired features of an interactive tool for time mask filtering and present a possible implementation of such a tool. By example of analysing two real world data collections related to aviation and maritime traffic, we show the way of using time masks in combination with other types of filters and demonstrate the utility of the time mask filtering.
Key words： Data visualization Interactive visualization Interaction technique
DOI：10.1016/j.visinf.2017.01.004

Visual Informatics is launched by State Key Lab of CAD&CG, Zhejiang University in cooperation with Elsevier. We look forward to your kind attention and contribution to this new journal!

With best regards!
Editorial Office of Visual Informatics