122 research outputs found
3D Graph Visualization with the Oculus Rift
No full textVisualization of large graphs in 3D has been hampered by the expense and inconvenience of a virtual reality equipment. The Oculus Rift is an affordable head-mounted VR system that is becoming popular in gaming and education markets. The Gluskap software package for creating and editing graphs in 3D has been extended to include support for the Oculus Rift for stereographic 3D viewing, and navigation
A EMOTION-FOCUSSED TREATMENT FOR DECREASING CONJUGAL STRESS- A RANDOMIZED REPRESENTATIVE SINGLE-SITE CONTROLLED STUDY
No full textObjective:
Marital life is closely related to physical, social, and mental well-being. The aim of this study was to determine the reduction in chronic marital life stress among exposed subjects through the emotion re-focus approach.
Methods:
The individuals meeting our inclusion criteria were screened with the help of Stockholm Marital Stress Scale. The cognitive assessment was also made with the help of an Abbreviated Mental Test. The subjects were assigned a random number in a double-blind and independent manner, and half of them were provided eight therapeutic sessions lasting 90 minutes for eight weeks. The remaining ones were provided identical service after the entire data collection. All analyses were carried-out in 99.0% confidence interval, 0.01% type-I error and 1.0% type-II error.
Results:
A total of 138 subjects with marital life stress were allocated to both testing and control group. Both groups did not differ in social, statistical, and clinical variables. The between-group mean stress score did not differ statistically at baseline (p=0.1), but did differ at the culmination (p<0.001). For control group, the mean stress score changed from 2.8, 99%CI 2.7-2.9 to 2.7, 99%CI 2.6-2.8, p=0.1 between pre-post assessment. For testing group, the mean stress score changed from 2.9, 99%CI 2.8-3.0 to 2.4, 99%CI 2.3-2.5, p<0.001 (diff=17.2%, ES=1.40, R2=0.32) between pre-post assessment. The within-group improvement in stress score among subjects from their own baseline was 0-3.8% among control group and 1.9-30.6% in testing group. The sample power was 99.1%.
Conclusions:
Within our strengths and limitations, we may conclude that emotion re-focus may help to overcome chronic conjugal life distress with 0.1% false positive error.
Full text fully formatted PDF text version and Speech Abstract©:
academia and Egnyte and [email protected] information: The Intergovernmental Research and Policy Journal (IRPJ) is a unique interdisciplinary peer-reviewed and open access Journal. It operates under the authority of the only global and treaty-based intergovernmental university in the world (EUCLID), with other intergovernmental organizations in mind. Currently, there are more than 17,000 universities globally, but less than 15 are multilateral institutions, EUCLID, as IRPJ's sponsor, is the only global and multi-disciplinary UN-registered treaty-based institution.
IRPJ authors can be assured that their research will be widely visible on account of the trusted Internet visibility of its ".int" domain which virtually guarantees first page results on matching keywords (.int domains are only assigned by IANA to vetted treaty-based organizations and are recognized as trusted authorities by search engines). In addition to its ".int" domain, IRPJ is published under an approved ISSN for intergovernmental organizations ("international publisher") status (also used by United Nations, World Bank, European Space Agency, etc.).
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Submit manuscript: [email protected]
EICs: Prof. Charalee GRAYDON, JD; Prof. Devender BHALLA, HD
Dataset of the study "Exploring the Notion of Risk in Reviewer Recommendation"
No full textThis repository contains the necessary data for replicating the necessary information to replicate the study of "Exploring the Notion of Risk in Reviewer Recommendation." This code extends the RelationalGit package (https://github.com/CESEL/RelationalGit) from the study of E. Mirsaeedi and P. C. Rigby [1] and adds some functionality that is needed to incorporate the concept of the fix-inducing likelihood of a project.
In addition to our dataset, this repository also have the supporting materials for our study. The supporting materials are in the "ICSME_online_materials_ICSME.pdf" and contains the following items:
Table 1 contains the detail of the dataset and some related statistics for each of the studied projects.
Table 2 have risk measures that were used in our defect prediction model. We use Commit Guru Tool to extracts the data from the GitHub repositories and then use this data to train our defect prediction model.
Figure 1 illustrates the distribution of predicted defect probability of different projects. This distribution shows how defect probability of different periods are similar to the adjacent periods.
References:
[1] E. Mirsaeedi and P. C. Rigby, ‘Mitigating turnover with code review recommendation: Balancing expertise, workload, and knowledge distribution’, στο Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering, 2020
Reliability Estimation under Scarcity of Data: A Comparison of Three Approaches
No full textDuring the last decades, the optimization of the maintenance plan in process plants has lured the attention of many researchers due to its vital role in assuring the safety of operations. Within the process of scheduling maintenance activities, one of the most significant challenges is estimating the reliability of the involved systems, especially in case of data scarcity. Overestimating the average time between two consecutive failures of an individual component could compromise safety, while an underestimate leads to an increase of operational costs. Thus, a reliable tool able to determine the parameters of failure modelling with high accuracy when few data are available would be welcome. For this purpose, this paper aims at comparing the implementation of three practical estimation frameworks in case of sparse data to point out the most efficient approach. Hierarchical Bayesian modelling (HBM), maximum likelihood estimation (MLE), and least square estimation (LSE) are applied on data generated by a simulated stochastic process of a natural gas regulating and metering station (NGRMS), which was adopted as a case of study. The results identify the Bayesian methodology as the most accurate for predicting the failure rate of the considered devices, especially for the equipment characterized by less data available. The outcomes of this research will assist maintenance engineers and asset managers in choosing the optimal approach to conduct reliability analysis either when sufficient data or limited data are observed.Ship Design, Production and Operation
Web-based drawing software for graphs in 3D and two layout algorithms
No full textA new web-based software system for visualization and manipulation of graphs in 3D,
named We3Graph is presented with a focus on accessibility, customizability for applications
of graph drawing, usability and extendibility. The software system allows multiple
users to work on the same graph at the same time and is accessible through web browsers.
The software can be extended using plugins written in any programming language and
custom render engines written in the Javascript language. Also two new algorithms are
proposed to answer the following question, previously raised in [53]:
Given a graph G with n vertices, V = fv1;v2; : : : ;vng, and given a set of n
distinct points P = fp1; p2; : : : ; png each with integer coordinates in three dimensions,
can G be drawn crossing-free on P with vi at pi and with a number
of bends polynomial in n and in a volume polynomial in n and the dimension
of P
‘Environmental Impact Assessment’ in Drylands: Late Knowledge Penetration or a Deliberate Ignorance for Megaprojects?
No full textDespite the paramount role of drylands in supporting people’s livelihoods and rendering ecosystem services, legislation on Environmental Impact Assessment has been introduced belatedly after several decades. By exemplifying Iran, the author proposes two main reasons for such a delayed action. First, drylands are misleadingly considered as barren lands where biodiversity is relatively low. In one classification, deserts are even categorized along with rocks. Second, the author emphasizes that drylands have been subjected to unprecedented changes due to the expansion of infrastructure and urbanization that started in the 1970s. These growing pressures have been beyond the ecological resilience of drylands and have not been monitored, assessed, and modified correctly. Further scrutiny regarding EIA undertakings in drylands and the way they can be improved is now needed
Machine learning and deep learning for safety applications : Investigating the intellectual structure and the temporal evolution
No full textPublisher Copyright: © 2023 The Author(s)Over the last decades, safety requirements have become of primary concern. In the context of safety, several strategies could be pursued in many engineering fields. Moreover, many techniques have been proposed to deal with safety, risk, and reliability matters, such as Machine Learning (ML) and Deep Learning (DL). ML and DL are characterised by a high variety of algorithms, adaptable for different purposes. This generated wide and fragmented literature on ML and DL for safety purposes, moreover, literature review and bibliometric studies of the past years mainly focus on a single research area or application field. Thus, this paper aims to provide a holistic understanding of the research on this topic through a Systematic Bibliometric Analysis (SBA), along with proposing a viable option to conduct SBAs. The focus is on investigating the main research areas, application fields, relevant authors and studies, and temporal evolution. It emerged that rotating equipment, structural health monitoring, batteries, aeroengines, and turbines are popular fields. Moreover, the results depicted an increase in popularity of DL, along with new approaches such as deep reinforcement learning through the past four years. The proposed workflow for SBA has the potential to benefit researchers from multiple disciplines, beyond safety science.Peer reviewe
An Ultrasonically-Powered System for 1.06mm<sup>3</sup> Implantable Optogenetics and Drug Delivery Dust
No full textThis brief presents an ultrasonically powered micro-system for deep tissue optogenetic stimulation. The developed system is composed of a Base for Powering and Controlling (BPC) and an implantable Dust for optogenetics and drug delivery. The Dust consists of a piezoelectric crystal, a rectifier chip, and a micro-scale custom-designed light-emitting-diode (μ LED) integrated, miniaturized, and envisioned to be used for freely moving animal studies. The proposed Dust operates in frequencies up to 5 MHz, power levels in the 0-10 mW range, achieves start-up within 1.8~μ s at 2.9 MHz operating frequency at 14.4 mW/mm2 ultrasound power density, and 98.1% chip efficiency at 2 mW input power. With the BPC implemented and attached to ( 500~μ m )3 PZT4 crystals, set to 60 V at 2.8 MHz operating frequency at 3 mm distance in demineralized water, the dust delivered up to 6 mW to its load (μ LED for optogenetics), which translates to 0.11% total system efficiency.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Bio-Electronic
Ultrasonically Powered and Controlled Microsystem for Dual-Wavelength Optogenetics with a Multi-Load Regulation Scheme
No full textThis letter presents an ultrasonically powered dual-wavelength optogenetic device that targets simultaneous excitation and inhibition of neural activities, or in a broader sense, optical stimulation in two distinct wavelengths for targeting different populations of neurons. This can be applied to a variety of neurological disorders. The device features a load regulator circuit that shares the available power budget between two LEDs in a power-efficient and controlled way suppressing the need for adaptive matching and overvoltage protection circuits. Furthermore, the regulator circuit is capable of detecting power burst availability on the device and generating a control signal, accordingly. For 5.25 -mW acoustic power at the device's surface, the rectified voltage, and the total current load of the system are regulated to 2.79 V and 600A , respectively. The maximum chip and device efficiencies of 92.5% and 31.8% are measured, respectively. The total die area in 180- nm CMOS technology nose and the estimated system volume are 0.16/2 and 0.572/3 , respectively.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Bio-Electronic
Managing Knowledge-based Projects
No full textIn knowledge-based projects, many risks can be resulted due to lack of knowledge applied in the project. To avoid these risks, project based companies need to implement a convenient mechanism to develop knowledge management strategies. In this article, this mechanism is addressed as a KM strategic planning model, which is inherently a process model. This model helps to build a bridge between PMBOK processes and knowledge management strategy development. The foundation of this bridge is made on two pillars. First, the spiral of knowledge introduced by Nonaka [1] and, second, PMBOK processes. To develop the KM strategic planning model, the author is used his experiences acquired in applying knowledge management in managing projects in a consulting company
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