scholarly journals Christmas tree case study: computed tomography as a tool for mastering complex real world objects with applications in computer graphics

2003 ◽  
Author(s):  
A. Kanitsar ◽  
T. Theussl ◽  
L. Mroz ◽  
M. Sramek ◽  
A.V. Bartroli ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Computer Graphics ◽  
Real World ◽  
Christmas Tree

Qualitative Case Study Research Design

2015 ◽  
Vol 25 (1) ◽  
pp. 39-45 ◽  
Author(s):  
Jennifer Tetnowski
Keyword(s):  
Research Design ◽  
Real World ◽  
Qualitative Case Study ◽  
Case Study Research ◽  
Study Research

Qualitative case study research can be a valuable tool for answering complex, real-world questions. This method is often misunderstood or neglected due to a lack of understanding by researchers and reviewers. This tutorial defines the characteristics of qualitative case study research and its application to a broader understanding of stuttering that cannot be defined through other methodologies. This article will describe ways that data can be collected and analyzed.

Value of cone beam computed tomography to evaluate complication of intracranial haemorrhage in endovascular treatment (evt): a case report

2019 ◽  
Vol 1 (1) ◽  
pp. 16-18 ◽  
Author(s):  
Norafida Bahari ◽  
Nik Azuan Nik Ismail ◽  
Jegan Thanabalan ◽  
Ahmad Sobri Muda
Keyword(s):  
Computed Tomography ◽  
Arteriovenous Malformation ◽  
Endovascular Treatment ◽  
Cone Beam Computed Tomography ◽  
Diagnostic Value ◽  
Cone Beam ◽  
Brain Arteriovenous Malformation ◽  
Embolic Materials

In this article, we evaluate the effectiveness of Cone Beam Computed Tomography, through a case study, in assessing the complication of intracranial bleeding during an endovascular treatment of brain arteriovenous malformation when compared to Multislice-Detector Computed Tomography performed immediately after the procedure. The image quality of Cone Beam Computed Tomography has enough diagnostic value in differentiating between haemorrhage, embolic materials and the arteriovenous malformation nidus to facilitate physicians to decide for further management of the patient.

Value of cone beam computed tomography to evaluate complication of intracranial haemorrhage in endovascular treatment (evt): a case report.

2019 ◽  
pp. 16-18
Author(s):  
Norafida Bahari ◽  
NikAzuan Nik Ismail ◽  
Jegan Thanabalan ◽  
Ahmad Sobri Muda
Keyword(s):  
Computed Tomography ◽  
Arteriovenous Malformation ◽  
Endovascular Treatment ◽  
Cone Beam Computed Tomography ◽  
Diagnostic Value ◽  
Cone Beam ◽  
Brain Arteriovenous Malformation ◽  
Embolic Materials

In this article, we evaluate the effectiveness of Cone Beam Computed Tomography, through a case study, in assessing the complication of intracranial bleeding during an endovascular treatment of brain arteriovenous malformation when compared to Multislice-Detector Computed Tomography performed immediately after the procedure. The image quality of Cone Beam Computed Tomography has enough diagnostic value in differentiating between haemorrhage, embolic materials and the arteriovenous malformation nidus to facilitate physicians to decide for further management of the patient.

scholarly journals Reservoir Sediment Management Using Artificial Neural Networks: A Case Study of the Lower Section of the Alpine Saalach River

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 818
Author(s):  
Markus Reisenbüchler ◽  
Minh Duc Bui ◽  
Peter Rutschmann
Keyword(s):  
Real World ◽  
Close Correlation ◽  
Critical Issue ◽  
Management Tool ◽  
Lower Section ◽  
Reservoir Sediment ◽  
Efficiency And Effectiveness ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

Reservoir sedimentation is a critical issue worldwide, resulting in reduced storage volumes and, thus, reservoir efficiency. Moreover, sedimentation can also increase the flood risk at related facilities. In some cases, drawdown flushing of the reservoir is an appropriate management tool. However, there are various options as to how and when to perform such flushing, which should be optimized in order to maximize its efficiency and effectiveness. This paper proposes an innovative concept, based on an artificial neural network (ANN), to predict the volume of sediment flushed from the reservoir given distinct input parameters. The results obtained from a real-world study area indicate that there is a close correlation between the inputs—including peak discharge and duration of flushing—and the output (i.e., the volume of sediment). The developed ANN can readily be applied at the real-world study site, as a decision-support system for hydropower operators.

scholarly journals Applying the PECSL: using case studies to demonstrate the Pedagogy of Experience Complexity for Smart Learning

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Pen Lister
Keyword(s):  
Real World ◽  
Mobile Apps ◽  
Urban Environments ◽  
Learning Activities ◽  
Learning Activity ◽  
Opportunities To Learn ◽  
Practical Application ◽  
Design And Development ◽  
Smart Learning

AbstractThis paper discusses the uses and applications of the Pedagogy of Experience Complexity for Smart Learning (PECSL), a four-tier model of considerations for the design and development of smart learning activities. Using existing mobile apps and relevant activities as illustrative examples, the PECSL is applied to indicate concepts and mechanisms by which useful pedagogical considerations can work alongside user-centred design principles for the design and development of smart learning in urban hyper-localities. Practical application of the model is discussed using real world examples of activities as a basis to demonstrate the potential for manifold opportunities to learn, and plan for experience complexity in a smart learning activity. Case study approaches reflect on aspects of the PECSL in how it might be a useful and pragmatic guide to some of the issues faced when designing digital citizen learning activities in complex urban environments.

scholarly journals Method for Viewing Real-World Scenes while Recording Video

2021 ◽  
Vol 11 (10) ◽  
pp. 4617
Author(s):  
Daehee Park ◽  
Cheoljun Lee
Keyword(s):  
Real World ◽  
Video Recording ◽  
Emotional Responses ◽  
Target Object ◽  
Error Rates ◽  
User Needs ◽  
High Quality ◽  
Gradient Algorithms ◽  
Squared Error

Because smartphones support various functions, they are carried by users everywhere. Whenever a user believes that a moment is interesting, important, or meaningful to them, they can record a video to preserve such memories. The main problem with video recording an important moment is the fact that the user needs to look at the scene through the mobile phone screen rather than seeing the actual real-world event. This occurs owing to uncertainty the user might feel when recording the video. For example, the user might not be sure if the recording is of high-quality and might worry about missing the target object. To overcome this, we developed a new camera application that utilizes two main algorithms, the minimum output sum of squared error and the histograms of oriented gradient algorithms, to track the target object and recognize the direction of the user’s head. We assumed that the functions of the new camera application can solve the user’s anxiety while recording a video. To test the effectiveness of the proposed application, we conducted a case study and measured the emotional responses of users and the error rates based on a comparison with the use of a regular camera application. The results indicate that the new camera application induces greater feelings of pleasure, excitement, and independence than a regular camera application. Furthermore, it effectively reduces the error rates during video recording.

scholarly journals Simplification and Detection of Outlying Trajectories from Batch and Streaming Data Recorded in Harsh Environments

2019 ◽  
Vol 8 (6) ◽  
pp. 272 ◽  
Author(s):  
Iq Reviessay Pulshashi ◽  
Hyerim Bae ◽  
Hyunsuk Choi ◽  
Seunghwan Mun ◽  
Riska Asriana Sutrisnowati
Keyword(s):  
South Korea ◽  
Real World ◽  
Experimental Evaluation ◽  
Streaming Data ◽  
Harsh Environments ◽  
Noise Filtering ◽  
New Approach ◽  
Detection Algorithms ◽  
Outlying Point

Analysis of trajectory such as detection of an outlying trajectory can produce inaccurate results due to the existence of noise, an outlying point-locations that can change statistical properties of the trajectory. Some trajectories with noise are repairable by noise filtering or by trajectory-simplification. We herein propose the application of a trajectory-simplification approach in both batch and streaming environments, followed by benchmarking of various outlier-detection algorithms for detection of outlying trajectories from among simplified trajectories. Experimental evaluation in a case study using real-world trajectories from a shipyard in South Korea shows the benefit of the new approach.

scholarly journals Automated computed tomography quantification of fibrosis predicts prognosis in combined pulmonary fibrosis and emphysema in a real-world setting: a single-centre, retrospective study

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Masahiro Nemoto ◽  
Yuichiro Nei ◽  
Brian Bartholmai ◽  
Kazuki Yoshida ◽  
Hiroki Matsui ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Retrospective Study ◽  
Pulmonary Fibrosis ◽  
Acute Exacerbation ◽  
Real World ◽  
Medical Center ◽  
Pulmonary Function Tests ◽  
Quantitative Computed Tomography ◽  
Single Centre ◽  
Real World Setting

Abstract Background Combined pulmonary fibrosis and emphysema (CPFE) is a heterogeneous clinico-radiological syndrome without a consensus definition. There are limited data on the relation between the amount of parenchymal fibrosis and prognosis. In this study, we assessed the prognostic implications of the extent of fibrosis assessed by an automated quantitative computed tomography (CT) technique and the radiological and functional change over time in patients with a broad spectrum of fibrotic interstitial lung diseases (ILDs) encountered in a real-world setting. Methods We conducted a single-centre, retrospective study of 228 consecutive patients with CPFE, encountered from 2007 to 2015 at Kameda Medical Center, Chiba, Japan. We investigated the prognostic value of automated CT fibrosis quantification and the subsequent course of CPFE. Results Among 228 patients with CPFE, 89 had fibrosis affecting < 5% of their lungs, 54 had 5 to < 10% fibrosis, and 85 had ≥ 10% fibrosis at the time of diagnosis. Lower volume of fibrosis correlated with lower rates of mortality and acute exacerbation (p < 0.001). In particular, among those with < 5% fibrosis, only 4.5% died and none experienced acute exacerbation during follow-up, whereas 57.6% and 29.4% of those with ≥ 10% fibrosis experienced death and acute exacerbation, respectively. Although, the ≥ 10% fibrosis group had the poorest overall survival as well as the highest incidence of acute exacerbation, the incidence of decline in pulmonary function tests, change per year in total lung volume, and progression of fibrosis on chest CT was highest in the 5 to < 10% fibrosis group. The Cox proportional hazard model for CPFE progression (defined by composite criteria of death, acute exacerbation, and decline in forced vital capacity or diffusing capacity) showed fibrosis proportion was a risk factor independent of age, sex, smoking pack-years, the Charlson Comorbidity Index, lung cancer, connective tissue disease, and idiopathic pulmonary fibrosis. Conclusions Less severe (< 5%) fibrosis at baseline was associated with disease stability and better prognosis compared to more severe fibrosis in CPFE occurring with fibrotic ILDs. Further studies including a validation cohort will be needed. Trial Registration Retrospectively registered.

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