3D Visualization Model and Sample Implementation of 0-1 Function on Variant Logic

2013 ◽  
Vol 718-720 ◽  
pp. 480-483
Author(s):  
Huan Wang ◽  
Jie Ao Zhu ◽  
Xue Liu ◽  
Jeffrey Zheng
Keyword(s):  
Data Visualization ◽  
3D Visualization ◽  
Random Sequence ◽  
Relevant Logic ◽  
Complex Data ◽  
Paper Sample ◽  
Logic Function ◽  
Visual Model ◽  
Logic Functions ◽  
Visual Results

Random sequences generated by different logic functions play an important role in cryptography. The structure and the special properties of the logic function has been one of the most active areas of research. In order to study the random sequence and its related logic functions, many models have been established, and different advanced tools are applied to make complex data visualization. In this paper, sample logic functions are transferred into variant logic expressions to form a set of measurements. Using selected measurements, a 3D visual model is proposed. Selected 3D visual results are shown their intrinsic 3D spatial characteristics of relevant logic functions respectively.

scholarly journals Fostering Computational Thinking Through Data Visualization and Design on Secondary School Students

2021 ◽  
Vol 27 (3) ◽  
pp. 285-302
Author(s):  
Güldem Alev Özkök
Keyword(s):  
Secondary School ◽  
Data Visualization ◽  
Secondary School Students ◽  
Algorithm Design ◽  
Real Life ◽  
Computational Thinking ◽  
Design Solution ◽  
Problem Analysis ◽  
Complex Data ◽  
School Students

This research aims to model the process of data visualization (DV) and design to facilitate computational thinking (CT) of secondary-level students. As an interdisciplinary method for visualizing complex data, creating data visualizations requires learners to analyze data from knowledge of pure and applied science. This study investigates creating DV to facilitate CT as an interdisciplinary method which combines mathematics and information technology. The study was carried out using synthesised design-based research (DBR) method by conducting two cycles comprised of five phases: problem analysis within real-life context, design solution, develop solution, evaluate in practice and reflection. CT dimensions (decomposition, pattern recognition, abstraction, and algorithm design) were tested by using the Computational Thinking through Data Visualization Rubric and reflection form acquired during implementation. The sample consisted of secondary school students in the data visualization creation process with 27 in the first cycle and 31 in the second cycle. This research proposes a model to facilitate development of CT by DV with the analysis of complex data, creating an effective method by enabling analytics and visualizing data. The proposed DV development process facilitating CT has the potential to inform research on interdisciplinary learning environments.

3D data visualization: The advantages of volume graphics and big data to support geologic interpretation

2015 ◽  
Vol 3 (3) ◽  
pp. SX29-SX39 ◽  
Author(s):  
Carl Byers ◽  
Andrew Woo
Keyword(s):  
Big Data ◽  
Case Studies ◽  
Data Visualization ◽  
3D Visualization ◽  
Data Types ◽  
Volume Graphics ◽  
3D Data ◽  
Geologic Interpretation ◽  
Diverse Data

The ability to integrate diverse data types from multiple live and simulated sources, manipulate them dynamically, and deploy them in integrated, visual formats and in mobile settings provides significant advantages. We have reviewed some of the benefits of volume graphics and the use of big data in the context of 3D visualization case studies, in which inherent features, such as representation efficiencies, dynamic modifications, cross sectioning, and others, could improve interpretation processes and workflows.

DESIGN AND APPLICATION OF AN INTERACTIVE WHEELCHAIR TRAINING SYSTEM

2008 ◽  
Vol 20 (06) ◽  
pp. 377-385 ◽  
Author(s):  
Chern-Sheng Lin ◽  
Chia-Chang Chang ◽  
Wei-Lung Chen
Keyword(s):  
Control Function ◽  
Training System ◽  
Digital Logic ◽  
3D Simulation ◽  
Initial Time ◽  
Logic Function ◽  
Wheelchair Users ◽  
Rehabilitation Training ◽  
Direction Control ◽  
Logic Functions

In this paper we constructed an interactive wheelchair rehabilitation training platform. The roller wheel on the platform is driven mainly by turning the wheelchair, and then the relative position of wheelchair on the screen can be adjusted based on the rotation speed of left and right wheels on the platform. Comparing the digital logic function when two wheels rotate at the same time and judging the variance in digital logic, the steering direction of wheels can be known and be controlled forward or backward. Additionally, the standard digital logic function could be individually judged when left wheel rotates and vice versa, so as to control the steering. Through judging three digital logic functions, the initial time of left wheel, next signal selecting time of left wheel, initial time of right wheel, and next signal selecting time of right wheel could be obtained, then the system can achieve the required direction control function through the judgment formula. The direction control function is indicated by standard digital logic function, so that the user can operate smoothly in the interactive situation software and make an interaction with the computer 3D simulation scene, the patient would have rehabilitation training through various 3D simulation real exteriors. This study not only provides basic trainings but also records the service behavior of wheelchair users, so that the rehabilitation consultant would have reference for the future diagnosis.

scholarly journals Combining 2D and 3D Visualization with Visual Analytics in the Environmental Domain

Information ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 7
Author(s):  
Milena Vuckovic ◽  
Johanna Schmidt ◽  
Thomas Ortner ◽  
Daniel Cornel
Keyword(s):  
Data Visualization ◽  
Visual Analytics ◽  
Simulation Analysis ◽  
3D Visualization ◽  
Heavy Rain ◽  
Daily Practice ◽  
Environmental Domain ◽  
2D Data ◽  
Visualization Techniques ◽  
2D And 3D

The application potential of Visual Analytics (VA), with its supporting interactive 2D and 3D visualization techniques, in the environmental domain is unparalleled. Such advanced systems may enable an in-depth interactive exploration of multifaceted geospatial and temporal changes in very large and complex datasets. This is facilitated by a unique synergy of modules for simulation, analysis, and visualization, offering instantaneous visual feedback of transformative changes in the underlying data. However, even if the resulting knowledge holds great potential for supporting decision-making in the environmental domain, the consideration of such techniques still have to find their way to daily practice. To advance these developments, we demonstrate four case studies that portray different opportunities in data visualization and VA in the context of climate research and natural disaster management. Firstly, we focus on 2D data visualization and explorative analysis for climate change detection and urban microclimate development through a comprehensive time series analysis. Secondly, we focus on the combination of 2D and 3D representations and investigations for flood and storm water management through comprehensive flood and heavy rain simulations. These examples are by no means exhaustive, but serve to demonstrate how a VA framework may apply to practical research.

scholarly journals Study of T-norms and Quantum Logic Functions on BL-algebra and Their Relationships to the Classical Probability Structures

2020 ◽  
pp. 591-599
Author(s):  
Ahmed AL-Adilee ◽  
Habeeb Kareem Abdullah ◽  
Hawraa A. AL-Challabi
Keyword(s):  
Quantum Logic ◽  
Probability Space ◽  
Binary Operation ◽  
The Other ◽  
Symmetric Difference ◽  
Logic Function ◽  
Classical Probability ◽  
Binary Operations ◽  
Basic Probability ◽  
Logic Functions

This paper is concerned with the study of the T-norms and the quantum logic functions on BL-algebra, respectively, along with their association with the classical probability space. The proposed constructions depend on demonstrating each type of the T-norms with respect to the basic probability of binary operation. On the other hand, we showed each quantum logic function with respect to some binary operations in probability space, such as intersection, union, and symmetric difference. Finally, we demonstrated the main results that explain the relationships among the T-norms and quantum logic functions. In order to show those relations and their related properties, different examples were built.

scholarly journals Foundations for Applications of Gibbs Derivatives in Logic Design and VLSI

VLSI Design ◽  
2002 ◽  
Vol 14 (1) ◽  
pp. 65-81 ◽  
Author(s):  
Radomir S. Stanković ◽  
Milena Stanković ◽  
Reiner Creutzburg
Keyword(s):  
New Technologies ◽  
Differential Operators ◽  
Rate Of Change ◽  
Logic Design ◽  
Logic Function ◽  
Spectral Techniques ◽  
Cad Systems ◽  
Vlsi Cad ◽  
Efficient Calculation ◽  
Logic Functions

New technologies and increased requirements for performances of digital systems require new mathematical theories and tools as a basis for future VLSI CAD systems. New or alternative mathematical approaches and concepts must be suitable to solve some concrete problems in VLSI and efficient algorithms for their efficient application should be provided. This paper is an attempt in this direction and relates with the recently renewed interest in arithmetic expressions for switching functions, instead representations in Boolean structures, and spectral techniques and differential operators in switching theory and applications. Logic derivatives are efficiently used in solving different tasks in logic design, as for example, fault detection, functional decomposition, detection of symmetries and co-symmetries of logic functions, etc. Their application is based on the property that by differential operators, we can measure the rate of change of a logic function. However, by logic derivatives, we can hardly distinguish the direction of the change of the function, since they are defined in finite algebraic structures. Gibbs derivatives are a class of differential operators on groups, which applied to logic functions, permit to overcome this disadvantage of logic derivatives. Therefore, they may be useful in logic design in the same areas where the logic derivatives have been already using. For such applications, it is important to provide fast algorithms for calculation of Gibbs derivatives on finite groups efficiently in terms of space and time. In this paper, we discuss the methods for efficient calculation of Gibbs derivatives. These methods should represent a basis for further applications of these and related operators in VLSI CAD systems.

scholarly journals Synthetic metabolic computation in a bioluminescence-sensing system

2019 ◽  
Vol 47 (19) ◽  
pp. 10464-10474 ◽  
Author(s):  
Natalia Barger ◽  
Phyana Litovco ◽  
Ximing Li ◽  
Mouna Habib ◽  
Ramez Daniel
Keyword(s):  
Protein Interactions ◽  
Detection Threshold ◽  
Living Cells ◽  
Genetic Circuit ◽  
Biological Research ◽  
Protein Protein Interactions ◽  
Genetic Circuits ◽  
Logic Function ◽  
Single Input ◽  
Logic Functions

Abstract Bioluminescence is visible light produced and emitted by living cells using various biological systems (e.g. luxCDABE cassette). Today, this phenomenon is widely exploited in biological research, biotechnology and medical applications as a quantitative technique for the detection of biological signals. However, this technique has mostly been used to detect a single input only. In this work, we re-engineered the complex genetic structure of luxCDABE cassette to build a biological unit that can detect multi-inputs, process the cellular information and report the computation results. We first split the luxCDABE operon into several parts to create a genetic circuit that can compute a soft minimum in living cells. Then, we used the new design to implement an AND logic function with better performance as compared to AND logic functions based on protein-protein interactions. Furthermore, by controlling the reverse reaction of the luxCDABE cassette independently from the forward reaction, we built a comparator with a programmable detection threshold. Finally, we applied the redesigned cassette to build an incoherent feedforward loop that reduced the unwanted crosstalk between stress-responsive promoters (recA, katG). This work demonstrates the construction of genetic circuits that combine regulations of gene expression with metabolic pathways, for sensing and computing in living cells.

scholarly journals Evolution of SOMs’ Structure and Learning Algorithm: From Visualization of High-Dimensional Data to Clustering of Complex Data

Algorithms ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 109 ◽  
Author(s):  
Marian B. Gorzałczany ◽  
Filip Rudziński
Keyword(s):  
Data Visualization ◽  
Data Clustering ◽  
Learning Algorithm ◽  
High Dimensional Data ◽  
High Dimensional ◽  
Data Sets ◽  
Complex Data ◽  
Self Organizing Maps ◽  
Grid Networks ◽  
Self Organizing

In this paper, we briefly present several modifications and generalizations of the concept of self-organizing neural networks—usually referred to as self-organizing maps (SOMs)—to illustrate their advantages in applications that range from high-dimensional data visualization to complex data clustering. Starting from conventional SOMs, Growing SOMs (GSOMs), Growing Grid Networks (GGNs), Incremental Grid Growing (IGG) approach, Growing Neural Gas (GNG) method as well as our two original solutions, i.e., Generalized SOMs with 1-Dimensional Neighborhood (GeSOMs with 1DN also referred to as Dynamic SOMs (DSOMs)) and Generalized SOMs with Tree-Like Structures (GeSOMs with T-LSs) are discussed. They are characterized in terms of (i) the modification mechanisms used, (ii) the range of network modifications introduced, (iii) the structure regularity, and (iv) the data-visualization/data-clustering effectiveness. The performance of particular solutions is illustrated and compared by means of selected data sets. We also show that the proposed original solutions, i.e., GeSOMs with 1DN (DSOMs) and GeSOMS with T-LSs outperform alternative approaches in various complex clustering tasks by providing up to 20 % increase in the clustering accuracy. The contribution of this work is threefold. First, algorithm-oriented original computer-implementations of particular SOM’s generalizations are developed. Second, their detailed simulation results are presented and discussed. Third, the advantages of our earlier-mentioned original solutions are demonstrated.

scholarly journals Stereo3D: using stereo images to enrich 3D visualization

2020 ◽  
Vol 36 (14) ◽  
pp. 4189-4190
Author(s):  
Yang Liu ◽  
Vinod Kumar Singh ◽  
Deyou Zheng
Keyword(s):  
3D Visualization ◽  
Complex Structure ◽  
R Package ◽  
Supplementary Information ◽  
High Dimensional ◽  
Complex Data ◽  
Stereo Images ◽  
3D Space ◽  
Visualization Software ◽  
Critical Process

Abstract Summary Visualization in 3D space is a standard but critical process for examining the complex structure of high-dimensional data. Stereoscopic imaging technology can be adopted to enhance 3D representation of many complex data, especially those consisting of points and lines. We illustrate the simple steps that are involved and strongly recommend others to implement it in designing visualization software. To facilitate its application, we created a new software that can convert a regular 3D scatterplot or network figure to a pair of stereo images. Availability and implementation Stereo3D is freely available as an open source R package released under an MIT license at https://github.com/bioinfoDZ/Stereo3D. Others can integrate the codes and implement the method in academic software. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

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