scholarly journals Overcoming navigational challenges: A novel approach to the study and assessment of topographical orientation

2021 ◽  
Author(s):  
Alessia Bonavita ◽  
Alice Teghil ◽  
Maria Chiara Pesola ◽  
Cecilia Guariglia ◽  
Fabrizia D’Antonio ◽  
...  
Keyword(s):  
Virtual Environments ◽  
Internal Consistency ◽  
The Other ◽  
Ecological Environment ◽  
Route Knowledge ◽  
Survey Knowledge ◽  
Novel Approach ◽  
Topographical Orientation ◽  
Vestibular Information ◽  
High Internal Consistency

AbstractSeveral studies investigating environmental navigation require participants to navigate in virtual environments, in which the proprioceptive and vestibular components present during real environmental navigation are lost. Here, we aimed to provide a novel computerized ecological navigational battery, investigating whether the absence of proprioceptive and vestibular inputs yields a representation of the navigational space comparable to that acquired ecologically. In Study 1, 38 participants underwent two sets of tasks, one performed in a laboratory-based setting (LBS) and the other in an ecological environment (EE), with both including evaluation of route, landmark, and survey knowledge and a landmark ordering task. All tasks, except the route task, significantly correlated between EE and LBS. In LBS, performance in the landmark ordering task was predicted by that in the survey task, but not by those in the route and landmark tasks. Results of Study 1 were replicated in Study 2, in which 44 participants completed a modified and shorter online version of LBS tests. Reliability of the online LBS tests was also tested and showed a moderate-to-high internal consistency. Overall, results show that the conditions in which tasks are performed affect the acquisition of route knowledge, likely due to the lack of proprioceptive and vestibular information in LBS. However, LBS tasks presented here provide a standard battery of tests that can overcome the replicability problems encountered by ecological navigation tests, while taking into consideration all the complexities of navigational processes in terms of the use of landmark, route, and survey strategies.

The Effects of the Interface on Navigation in Virtual Environments

1998 ◽  
Vol 42 (21) ◽  
pp. 1496-1500 ◽  
Author(s):  
Barry Peterson ◽  
Maxwell Wells ◽  
Thomas A. Furness ◽  
Earl Hunt
Keyword(s):  
Virtual Environments ◽  
The Body ◽  
The Other ◽  
Motion Controller ◽  
Route Learning ◽  
Survey Knowledge ◽  
Mental Map ◽  
Alternative Routes

Thirty participants explored two virtual mazes. Half of the participants used a hand-controller (joystick); the other half used the Virtual Motion Controller (VMC), a body-controller interface. Maneuvering performance, as measured by the precision with which subjects followed a marked route, was slightly better with the joystick. Route learning, as measured by the subjects' ability to replicate the route, was the same for both devices. Survey knowledge, or the ability to form a mental map of the space and to use it to find alternative routes was significantly better with the VMC. This enhancement in performance was conditional on maze difficulty. The more difficult the maze the greater was the performance benefit of using the VMC. The experiment provided evidence that an interface that uses the body may enhance certain components of navigation in virtual environments.

The Stigma of Suicide Scale

Crisis ◽  
2013 ◽  
Vol 34 (1) ◽  
pp. 13-21 ◽  
Author(s):  
Philip J. Batterham ◽  
Alison L. Calear ◽  
Helen Christensen
Keyword(s):  
Construct Validity ◽  
Psychometric Properties ◽  
Factor Structure ◽  
Internal Consistency ◽  
Concurrent Validity ◽  
Online Survey ◽  
National University ◽  
Stigmatizing Attitudes ◽  
High Internal Consistency ◽  
At Home

Background: There are presently no validated scales to adequately measure the stigma of suicide in the community. The Stigma of Suicide Scale (SOSS) is a new scale containing 58 descriptors of a “typical” person who completes suicide. Aims: To validate the SOSS as a tool for assessing stigma toward suicide, to examine the scale’s factor structure, and to assess correlates of stigmatizing attitudes. Method: In March 2010, 676 staff and students at the Australian National University completed the scale in an online survey. The construct validity of the SOSS was assessed by comparing its factors with factors extracted from the Suicide Opinion Questionnaire (SOQ). Results: Three factors were identified: stigma, isolation/depression, and glorification/normalization. Each factor had high internal consistency and strong concurrent validity with the Suicide Opinion Questionnaire. More than 25% of respondents agreed that people who suicided were “weak,” “reckless,” or “selfish.” Respondents who were female, who had a psychology degree, or who spoke only English at home were less stigmatizing. A 16-item version of the scale also demonstrated robust psychometric properties. Conclusions: The SOSS is the first attitudes scale designed to directly measure the stigma of suicide in the community. Results suggest that psychoeducation may successfully reduce stigma.

Internal Structure of the Spanish Adaptation of the Eating Disorder Inventory-3

2012 ◽  
Vol 28 (1) ◽  
pp. 25-31 ◽  
Author(s):  
Paula Elosua ◽  
Alicia López-Jáuregui
Keyword(s):  
Eating Disorders ◽  
Eating Disorder ◽  
Internal Structure ◽  
Internal Consistency ◽  
Clinical Sample ◽  
Temporal Stability ◽  
Second Order ◽  
Order Structure ◽  
Eating Disorder Inventory ◽  
High Internal Consistency

In this study the Eating Disorder Inventory-3 was adapted to Spanish and analyzed the internal psychometric properties of the test in a clinical sample of females with eating disorders. The results showed a high internal consistency of the scores as well as high temporal stability. The factor structure of the scale composites was analyzed using confirmatory factor analysis. The results supported the existence of a second-order structure beyond the psychological composites. The second-order factor showed high correlation with the factor related to eating disorders. Overall, the Spanish version of the EDI-3 showed good psychometric qualities in terms of internal consistency, temporal stability and internal structure.

An Intuitionistic Fuzzy Based Novel Approach to CPU Scheduler

2020 ◽  
Vol 16 (4) ◽  
pp. 316-328
Author(s):  
Supriya Raheja
Keyword(s):  
Fuzzy Inference ◽  
The Other ◽  
Simulation Environment ◽  
Inference System ◽  
Intuitionistic Fuzzy ◽  
Novel Approach ◽  
Continuous Feedback ◽  
Simulation Results ◽  
Effectiveness And Efficiency ◽  
Unique Capability

Background: The extension of CPU schedulers with fuzzy has been ascertained better because of its unique capability of handling imprecise information. Though, other generalized forms of fuzzy can be used which can further extend the performance of the scheduler. Objectives: This paper introduces a novel approach to design an intuitionistic fuzzy inference system for CPU scheduler. Methods: The proposed inference system is implemented with a priority scheduler. The proposed scheduler has the ability to dynamically handle the impreciseness of both priority and estimated execution time. It also makes the system adaptive based on the continuous feedback. The proposed scheduler is also capable enough to schedule the tasks according to dynamically generated priority. To demonstrate the performance of proposed scheduler, a simulation environment has been implemented and the performance of proposed scheduler is compared with the other three baseline schedulers (conventional priority scheduler, fuzzy based priority scheduler and vague based priority scheduler). Results: Proposed scheduler is also compared with the shortest job first CPU scheduler as it is known to be an optimized solution for the schedulers. Conclusion: Simulation results prove the effectiveness and efficiency of intuitionistic fuzzy based priority scheduler. Moreover, it provides optimised results as its results are comparable to the results of shortest job first.

Reliability and Validity of the Parent form of the Social Competence Scale in Chinese Preschoolers

2012 ◽  
Vol 111 (1) ◽  
pp. 266-268 ◽  
Author(s):  
Xiao Zhang ◽  
Xue Ke ◽  
Xiaoyan Wang
Keyword(s):  
Preschool Children ◽  
Social Competence ◽  
Internal Consistency ◽  
Student Teacher ◽  
Reliability And Validity ◽  
Single Dimension ◽  
Student Teacher Relationship ◽  
The Social ◽  
Competence Scale ◽  
High Internal Consistency

The Parent Form of the Social Competence Scale (SCS–PF) was translated into Chinese and validated in a sample of Chinese preschool children ( N = 443). Results confirmed a single dimension and high internal consistency in the SCS–PF. Mothers' ratings on the SCS–PF correlated moderately with teachers' ratings on the Teacher Form of the Social Competence Scale and weakly with teachers' ratings on the Student–Teacher Relationship Scale.

scholarly journals Citizenship matters: Translating and adapting the Citizenship Measure to Norwegian

2021 ◽  
pp. 145507252110186
Author(s):  
Linda Nesse ◽  
Marianne Thorsen Gonzalez ◽  
Michael Rowe ◽  
Ruth Kjærsti Raanaas
Keyword(s):  
Internal Consistency ◽  
Convergent Validity ◽  
Mental Health Problems ◽  
Supported Housing ◽  
Measurement Properties ◽  
Convenience Sample ◽  
Marginalised Groups ◽  
Two Factors ◽  
Back Translation ◽  
High Internal Consistency

Citizenship is considered intertwined with recovery, and may be a useful perspective for advancing quality of life among marginalised groups. Yet, matters of citizenship among persons with co-occurring substance use and mental health problems both in research and practice. Aims: In order to measure citizenship among persons with co-occurring problems in a Norwegian study, a measure of citizenship was translated from English to Norwegian. The aims of the study were to 1) translate and adapt the Citizenship Measure, developed by Rowe and colleagues at the Yale Program for Recovery and Community Health, to Norwegian, and 2) to assess the internal consistency and convergent validity of the Norwegian translated measure. Methods: The translation process was carried out using forward and back translation procedures. To examine measurement properties, a convenience sample of 104 residents with co-occurring problems living in supported housing completed the measure. Results: Two factors were identified, related to rights, and to relational citizenship. The Norwegian translation of the Citizenship Measure showed has high internal consistency and adequate convergent validity. Conclusions: We argue that the measure can be useful in assessing perceived citizenship, and in initiating efforts to support citizenship among persons with co-occurring problems.

Mining discriminative patches for script identification in natural scene images

2021 ◽  
Vol 40 (1) ◽  
pp. 551-563
Author(s):  
Liqiong Lu ◽  
Dong Wu ◽  
Ziwei Tang ◽  
Yaohua Yi ◽  
Faliang Huang
Keyword(s):  
Neural Networks ◽  
Experimental Results ◽  
The Other ◽  
Natural Scene ◽  
Fixed Size ◽  
Script Identification ◽  
Aspect Ratios ◽  
Novel Approach ◽  
Public Datasets ◽  
Natural Scene Images

This paper focuses on script identification in natural scene images. Traditional CNNs (Convolution Neural Networks) cannot solve this problem perfectly for two reasons: one is the arbitrary aspect ratios of scene images which bring much difficulty to traditional CNNs with a fixed size image as the input. And the other is that some scripts with minor differences are easily confused because they share a subset of characters with the same shapes. We propose a novel approach combing Score CNN, Attention CNN and patches. Attention CNN is utilized to determine whether a patch is a discriminative patch and calculate the contribution weight of the discriminative patch to script identification of the whole image. Score CNN uses a discriminative patch as input and predict the score of each script type. Firstly patches with the same size are extracted from the scene images. Secondly these patches are used as inputs to Score CNN and Attention CNN to train two patch-level classifiers. Finally, the results of multiple discriminative patches extracted from the same image via the above two classifiers are fused to obtain the script type of this image. Using patches with the same size as inputs to CNN can avoid the problems caused by arbitrary aspect ratios of scene images. The trained classifiers can mine discriminative patches to accurately identify some confusing scripts. The experimental results show the good performance of our approach on four public datasets.

scholarly journals Density Guarantee on Finding Multiple Subgraphs and Subtensors

2021 ◽  
Vol 15 (5) ◽  
pp. 1-32
Author(s):  
Quang-huy Duong ◽  
Heri Ramampiaro ◽  
Kjetil Nørvåg ◽  
Thu-lan Dam
Keyword(s):  
Lower Bound ◽  
State Of The Art ◽  
The State ◽  
The Other ◽  
Exact Methods ◽  
Practical Solution ◽  
Novel Approach ◽  
Wide Range ◽  
Real World Datasets ◽  
Tensor Data

Dense subregion (subgraph & subtensor) detection is a well-studied area, with a wide range of applications, and numerous efficient approaches and algorithms have been proposed. Approximation approaches are commonly used for detecting dense subregions due to the complexity of the exact methods. Existing algorithms are generally efficient for dense subtensor and subgraph detection, and can perform well in many applications. However, most of the existing works utilize the state-or-the-art greedy 2-approximation algorithm to capably provide solutions with a loose theoretical density guarantee. The main drawback of most of these algorithms is that they can estimate only one subtensor, or subgraph, at a time, with a low guarantee on its density. While some methods can, on the other hand, estimate multiple subtensors, they can give a guarantee on the density with respect to the input tensor for the first estimated subsensor only. We address these drawbacks by providing both theoretical and practical solution for estimating multiple dense subtensors in tensor data and giving a higher lower bound of the density. In particular, we guarantee and prove a higher bound of the lower-bound density of the estimated subgraph and subtensors. We also propose a novel approach to show that there are multiple dense subtensors with a guarantee on its density that is greater than the lower bound used in the state-of-the-art algorithms. We evaluate our approach with extensive experiments on several real-world datasets, which demonstrates its efficiency and feasibility.

scholarly journals A Novel Approach to Oil Layer Recognition Model Using Whale Optimization Algorithm and Semi-Supervised SVM

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 757
Author(s):  
Yongke Pan ◽  
Kewen Xia ◽  
Li Wang ◽  
Ziping He
Keyword(s):  
Optimization Algorithm ◽  
Oil And Gas ◽  
The Other ◽  
Whale Optimization Algorithm ◽  
Classification Model ◽  
Support Vector ◽  
Recognition Model ◽  
Novel Approach ◽  
Whale Optimization ◽  
Oil And Gas Reservoir

The dataset distribution of actual logging is asymmetric, as most logging data are unlabeled. With the traditional classification model, it is hard to predict the oil and gas reservoir accurately. Therefore, a novel approach to the oil layer recognition model using the improved whale swarm algorithm (WOA) and semi-supervised support vector machine (S3VM) is proposed in this paper. At first, in order to overcome the shortcomings of the Whale Optimization Algorithm applied in the parameter-optimization of the S3VM model, such as falling into a local optimization and low convergence precision, an improved WOA was proposed according to the adaptive cloud strategy and the catfish effect. Then, the improved WOA was used to optimize the kernel parameters of S3VM for oil layer recognition. In this paper, the improved WOA is used to test 15 benchmark functions of CEC2005 compared with five other algorithms. The IWOA–S3VM model is used to classify the five kinds of UCI datasets compared with the other two algorithms. Finally, the IWOA–S3VM model is used for oil layer recognition. The result shows that (1) the improved WOA has better convergence speed and optimization ability than the other five algorithms, and (2) the IWOA–S3VM model has better recognition precision when the dataset contains a labeled and unlabeled dataset in oil layer recognition.

The Italian version of the Unité Rhumatologique des Affections de la Main (URAM) for Dupuytren’s disease: The URAM-I(10)

Hand Therapy ◽  
2021 ◽  
pp. 175899832110345
Author(s):  
E Lanfranchi ◽  
T Fairplay ◽  
P Arcuri ◽  
M Lando ◽  
F Marinelli ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Internal Consistency ◽  
Cultural Adaptation ◽  
Dupuytren’S Disease ◽  
Divergent Validity ◽  
Dupuytren's Disease ◽  
Retest Reliability ◽  
Sf 36 ◽  
High Internal Consistency ◽  
Test Retest Reliability

Introduction Several general hand functional assessment tools for Dupuytren’s disease have been reported, but none of the patient-reported-outcome measures specific to Dupuytren’s disease-associated disabilities are available in the Italian language. The purpose of this study was to culturally adapt the Unité Rhumatologique des Affections de la Main (URAM) into Italian (URAM-I) and determine its measurement properties. Methods Cross-cultural adaptation was performed according to the current guidelines. Construct validity (convergent and divergent validity) was measured by comparing the URAM-I with the Pain-Rated Wrist/Hand Evaluation (PRWHE-I), Short-Form 36 (SF-36-I) scale and finger range of motion, respectively. Factor analysis was used to investigate the URAM-I’s internal structure. Reliability was assessed by internal consistency (Cronbach’s alpha) and test-retest reliability by Intra-Class Correlation Coefficient (ICC). Results This study included 96 patients (males = 85%, age = 66.8 ± 9.3). Due to the cultural adaptation, we divided the original item #1 into two separate items, thus generating the URAM-I(10). Convergent validity analysis showed a strong positive (r = 0.67), significant (p < 0.01) Pearson’s correlation with the PRWHE-I. Divergent validity analysis showed a weak, negative (r < 0.3) and not significant correlation with the SF-36-I subscales, except for the physical pain subscale (r = −0.21, p < 0.05). Factor analysis revealed a 2-factor, 4-item solution that explained 76% of the total variance. The URAM-I(10) demonstrated high internal consistency (α = 0.94) and high test-retest reliability (ICC = 0.97). Conclusion The URAM-I(10) demonstrates moderate construct validity, high internal consistency and test-retest reliability, and showed a 2-factor internal structure. Its evaluative use can be suggested for the Italian Dupuytren’s population.

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