scholarly journals A Computational Framework for Iceberg and Ship Discrimination: Case Study on Kaggle Competition

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 82320-82327 ◽  
Author(s):  
Xulei Yang ◽  
Jie Ding
Keyword(s):  
Computational Framework

Revisiting Tourism Destination Image: A Holistic Measurement Framework Using Big Data

2021 ◽  
pp. 004728752110247
Author(s):  
Vinh Bui ◽  
Ali Reza Alaei ◽  
Huy Quan Vu ◽  
Gang Li ◽  
Rob Law
Keyword(s):  
Large Scale ◽  
Structural Model ◽  
Destination Image ◽  
Tourism Destination ◽  
Computational Framework ◽  
Four Dimensions ◽  
Tourism Management ◽  
Measurement Framework ◽  
Compare And Contrast

Understanding and being able to measure, analyze, compare, and contrast the image of a tourism destination, also known as tourism destination image (TDI), is critical in tourism management and destination marketing. Although various methodologies have been developed, a consistent, reliable, and scalable method for measuring TDI is still unavailable. This study aims to address the challenge by proposing a framework for a holistic measure of TDI in four dimensions, including popularity, sentiment, time, and location. A structural model for TDI measurement that covers various aspects of a tourism destination is developed. TDI is then measured by a comprehensive computational framework that can analyze complex textual and visual data on a large scale. A case study using more than 30,000 images, and 10,000 comments in relation to three tourism destinations in Australia demonstrates the effectiveness of the proposed framework.

Linear free energy relationships for transition metal chemistry: case study of CH activation with copper–oxygen complexes

2020 ◽  
Vol 22 (14) ◽  
pp. 7155-7159 ◽  
Author(s):  
Zhenzhuo Lan ◽  
Shaama Mallikarjun Sharada
Keyword(s):  
Free Energy ◽  
Transition Metal ◽  
Transition Metal Complexes ◽  
Linear Free Energy Relationships ◽  
Computational Framework ◽  
Ch Activation ◽  
Linear Free Energy ◽  
Energy Relationships ◽  
Oxygen Complexes

We propose a computational framework for developing Taft-like linear free energy relationships to characterize steric effects on the catalytic activity of transition metal complexes.

scholarly journals DynaMorph: learning morphodynamic states of human cells with live imaging and sc-RNAseq

2020 ◽  
Author(s):  
Zhenqin Wu ◽  
Bryant B. Chhun ◽  
Galina Schmunk ◽  
Chang N. Kim ◽  
Li-Hao Yeh ◽  
...  
Keyword(s):  
Human Cells ◽  
Cellular Systems ◽  
Label Free ◽  
Computational Framework ◽  
Human Microglia ◽  
Functional States ◽  
Automated Discovery ◽  
Genetic Labeling ◽  
The Brain

Morphological states of human cells are widely imaged and analyzed to diagnose diseases and to discover biological mechanisms. Morphodynamics of cells capture their functions more fully than their morphology. Discovery of morphodynamic states of human cells is challenging, because genetic labeling or manual annotation may not be feasible. We propose a computational framework, DynaMorph, that combines quantitative label-free imaging and deep learning for automated discovery of morphodynamic states. As a case study, we apply DynaMorph to study the morphodynamic states of live primary human microglia, which are mobile immune cells of the brain that exhibit complex functional states. DynaMorph identifies two distinct morphodynamic states of microglia under perturbation by cytokines and glioblastoma supernatant. We find that microglia actively transition between the two states. Moreover, single-cell RNA-sequencing of the perturbed microglia shows that the morphodynamic states correspond to distinct transcriptomic clusters of the cells, revealing how perturbations alter gene expression and phenotype. DynaMorph can broadly enable automated discovery of functional states of cellular systems.

Dynamic Non-Interference Constraints in Goal-Directed Geometry

1995 ◽  
Author(s):  
Stewart Coulter ◽  
Bert Bras ◽  
David Rosen
Keyword(s):  
Computer Aided Design ◽  
Preliminary Design ◽  
Design Tools ◽  
Multi Objective Optimization ◽  
Computational Framework ◽  
Linkage Design ◽  
Engineering Models ◽  
Aided Design ◽  
Dynamic Interference

Abstract Improvements in computer-aided design tools can significantly increase designer productivity. The ability to explore a variety of possible designs quickly and effectively is essential for a designer. In a previous paper, Goal Directed Geometry (GDG) was introduced as a computational framework for preliminary design, aiding the formulation of engineering models with geometric considerations, and the solution of these models with a multi-objective optimization package. The geometric considerations were limited to static noninterference constraints, introducing a metric and method for prevention of geometric interference between two subassemblies. In this paper, this metric and method are expanded to include the prevention of interference between moving subassemblies, or dynamic interference. Based on a series of repetitive static checks, this metric is intended to be accurate and simple for the designer to use. A case study is presented showing the GDG implementation for a linkage design problem, demonstrating the use of this metric. This parametric GDG model is then solved using an existing optimization program called DSIDES.

scholarly journals Energy Flow in Multibody Limb Models: A Case Study in Frogs

2019 ◽  
Vol 59 (6) ◽  
pp. 1559-1572 ◽  
Author(s):  
Christopher T Richards
Keyword(s):  
Energy Flow ◽  
Center Of Mass ◽  
Coupling Mechanism ◽  
Dynamic Coupling ◽  
Coordinated Motion ◽  
Computational Framework ◽  
Inertia Properties ◽  
Jump Trajectory ◽  
Multi Body

Abstract A frog jump is both simple and difficult to comprehend. The center-of-mass (COM) follows a two-dimensional (2D) path; it accelerates diagonally upward, then traces a predictable arc in flight. Despite this simplicity, the leg segments trace intricate trajectories to drive the COM both upwards and forwards. Because the frog sits crouched with sprawled legs, segments must pivot, tilt, and twist; they solve a long-recognized problem of converting non-linear 3D motion of the leg segments to linear 2D motion of the COM. I use mathematical approaches borrowed from robotics to address: How do frogs manipulate the flow of kinetic energy through their body to influence jump trajectory? I address (1) transfer of motion through kinematic transmission and (2) transfer of motion through dynamic coupling of segment mass-inertia properties. Using a multi-body simulation, I explore how segment acceleration induces rotations at neighboring segments (even without accounting for bi-articular muscles). During jumps, this inertial coupling mechanism is likely crucial for modulating the direction of travel. The frog case study highlights a useful computational framework for studying how limb joints produce coordinated motion.

From handicraft prototypes to limited serial productions: Exploiting knowledge artifacts to support the industrial design of high quality products

2010 ◽  
Vol 24 (1) ◽  
pp. 17-34 ◽  
Author(s):  
S. Bandini ◽  
F. Sartori
Keyword(s):  
Experiential Knowledge ◽  
The Internet ◽  
Electric Guitar ◽  
Specific Knowledge ◽  
High Quality ◽  
Computational Framework ◽  
Knowledge Based ◽  
Design And Manufacturing ◽  
Electric Guitars

AbstractThis paper presents a conceptual and computational framework to support experts in the design and manufacturing of high quality products. The framework is based on the development of specific knowledge artifacts characterized by tools for the management of functional, procedural, and experiential knowledge. As a case study, the GUITAR HERO project is presented. The project aims at building a knowledge-based system to support experts of a handicraft enterprise involved in the design and manufacturing of electric guitars characterized by an aluminum body. The domain of the project is extremely innovative, because electric guitars are typically manufactured with different kinds of wood rather than metals or other materials. To this aim, an ontological representation of the electric guitar has been implemented exploiting NavEditOW, a computational framework for the codification, navigation, and querying of ontologies over the Internet, based on the OWL language.

FCDECOMP: Decomposition of metabolic networks based on flux coupling relations

2014 ◽  
Vol 12 (05) ◽  
pp. 1450028 ◽  
Author(s):  
Abolfazl Rezvan ◽  
Sayed-Amir Marashi ◽  
Changiz Eslahchi
Keyword(s):  
Metabolic Networks ◽  
System Level ◽  
Computational Framework ◽  
Flux Coupling ◽  
Metabolic Functions ◽  
Original Genome ◽  
A Cell ◽  
Scale Network ◽  
Genome Scale

A metabolic network model provides a computational framework to study the metabolism of a cell at the system level. Due to their large sizes and complexity, rational decomposition of these networks into subsystems is a strategy to obtain better insight into the metabolic functions. Additionally, decomposing metabolic networks paves the way to use computational methods that will be otherwise very slow when run on the original genome-scale network. In the present study, we propose FCDECOMP decomposition method based on flux coupling relations (FCRs) between pairs of reaction fluxes. This approach utilizes a genetic algorithm (GA) to obtain subsystems that can be analyzed in isolation, i.e. without considering the reactions of the original network in the analysis. Therefore, we propose that our method is useful for discovering biologically meaningful modules in metabolic networks. As a case study, we show that when this method is applied to the metabolic networks of barley seeds and yeast, the modules are in good agreement with the biological compartments of these networks.

scholarly journals Computational framework for the selection of energy solutions in indigenous communities in Colombia: Kanalitojo case study

2021 ◽  
Vol 8 (1) ◽  
pp. 1926406
Author(s):  
Ramón Fernando Colmenares-Quintero ◽  
Luis Fernando Latorre-Noguera ◽  
Natalia Rojas ◽  
Karl Kolmsee ◽  
Kim E. Stansfield ◽  
...  
Keyword(s):  
Indigenous Communities ◽  
Computational Framework ◽  
Selection Of

Computational Design of Scheduling Strategies for Multi-Robot Cooperative 3D Printing

2019 ◽  
Author(s):  
Laxmi Poudel ◽  
Wenchao Zhou ◽  
Zhenghui Sha
Keyword(s):  
3D Printing ◽  
Computational Design ◽  
Geometric Constraints ◽  
Computational Framework ◽  
Novel Approach ◽  
Dependency Tree ◽  
Scheduling Strategies ◽  
Evaluation Metric ◽  
Printing Time

Abstract Cooperative 3D printing (C3DP) is a novel approach to additive manufacturing, where multiple printhead-carrying mobile robots work together cooperatively to print a desired part. The core of C3DP is the chunk-based printing strategy in which the desired part is first split into smaller chunks, and then the chunks are assigned to individual printing robots. These robots will work on the chunks simultaneously and in a scheduled sequence until the entire part is complete. Though promising, C3DP lacks proper framework that enables automatic chunking and scheduling given the available number of robots. In this study, we develop a computational framework that can automatically generate print schedule for specified number of chunks. The framework contains 1) a random generator that creates random print schedule using adjacency matrix which represents directed dependency tree (DDT) structure of chunks; 2) a set of geometric constraints against which the randomly generated schedules will be checked for validation; and 3) a printing time evaluation metric for comparing the performance of all valid schedules. With the developed framework, we present a case study by printing a large rectangular plate which has dimensions beyond what traditional desktop printers can print. The study showcases that our computation framework can successfully generate a variety of scheduling strategies for collision-free C3DP without any human interventions.

scholarly journals Analysis of Potential Shift to Low-Carbon Urban Travel Modes: A Computational Framework Based on High-Resolution Smartphone Data

2020 ◽  
Vol 12 (15) ◽  
pp. 5901
Author(s):  
Mehrdad Bagheri ◽  
Miloš N. Mladenović ◽  
Iisakki Kosonen ◽  
Jukka K. Nurminen
Keyword(s):  
Data Collection ◽  
Travel Time ◽  
Active Travel ◽  
Travel Times ◽  
Low Carbon ◽  
Computational Framework ◽  
Physically Active ◽  
Study Results ◽  
Longitudinal Data Collection

Given the necessity to understand the modal shift potentials at the level of individual travel times, emissions, and physically active travel distances, there is a need for accurately computing such potentials from disaggregated data collection. Despite significant development in data collection technology, especially by utilizing smartphones, there are limited efforts in developing useful computational frameworks for this purpose. First, development of a computational framework requires longitudinal data collection of revealed travel behavior of individuals. Second, such a computational framework should enable scalable analysis of time-relevant low-carbon travel alternatives in the target region. To this end, this research presents an open-source computational framework, developed to explore the potential for shifting from private car to lower-carbon travel alternatives. In comparison to previous development, our computational framework estimates and illustrates the changes in travel time in relation to the potential reductions in emission and increases in physically active travel, as well as daily weather conditions. The potential usefulness of the framework was evaluated using long-term travel data of around a hundred travelers within the Helsinki Metropolitan Region, Finland. The case study outcomes also suggest that in several cases traveling by public transport or bike would not increase travel time compared to the observed car travel. Based on the case study results, we discuss potentially acceptable travel times for mode shift, and usefulness of the computational framework for decisions regarding transition to sustainable urban mobility systems. Finally, we discuss limitations and lessons learned for data collection and further development of similar computational frameworks.

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