Effects of Temporal Uncertainty on Performance of a Probability-Monitoring Task

1969 ◽  
Author(s):  
Glynn D. Coates ◽  
Earl A. Alluisi
Keyword(s):  
Temporal Uncertainty ◽  
Monitoring Task

Binary Spectrum Feature for Improved Classifier Performance

2020 ◽  
Author(s):  
Nalika Ulapane ◽  
Karthick Thiyagarajan ◽  
sarath kodagoda
Keyword(s):  
Machine Learning ◽  
Classification Performance ◽  
Feature Reduction ◽  
Sensor Data ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Svm Classifier ◽  
Monitoring Task ◽  
Classifier Performance ◽  
Spectrum Feature

<div>Classification has become a vital task in modern machine learning and Artificial Intelligence applications, including smart sensing. Numerous machine learning techniques are available to perform classification. Similarly, numerous practices, such as feature selection (i.e., selection of a subset of descriptor variables that optimally describe the output), are available to improve classifier performance. In this paper, we consider the case of a given supervised learning classification task that has to be performed making use of continuous-valued features. It is assumed that an optimal subset of features has already been selected. Therefore, no further feature reduction, or feature addition, is to be carried out. Then, we attempt to improve the classification performance by passing the given feature set through a transformation that produces a new feature set which we have named the “Binary Spectrum”. Via a case study example done on some Pulsed Eddy Current sensor data captured from an infrastructure monitoring task, we demonstrate how the classification accuracy of a Support Vector Machine (SVM) classifier increases through the use of this Binary Spectrum feature, indicating the feature transformation’s potential for broader usage.</div><div><br></div>

Effects of Visual Location of Information on The Performance of Monitoring Task Searhing in Digital Interactive Interface

2020 ◽  
Vol 64 (1) ◽  
pp. 473-479
Author(s):  
Xiaoli Wu ◽  
Qizhi Li
Keyword(s):  
Layout Design ◽  
Experimental Results ◽  
Target Information ◽  
Target Task ◽  
Monitoring Task ◽  
Interactive Interface ◽  
Task Order

The visual location of the information influences the searching efficiency of the monitoring task. In this paper, from the division of human eye’s visual regions, the task searching experiments of visual location in digital interactive interface are conducted. The experimental results show that, for target information blocks in the foveal and the parafoveal regions, the operators can finish the task searching efficiently and rapidly. However, when the target task is away from present fixation range’s parafoveal region, it will easily lead to sequence searching that will cost extra unnecessary task searching time, or even lead to failure of task searching. Therefore, the information layout design of digital interactive interface should be set successively in effective visual locations, i.e., the foveal and the parafoveal regions according to task order. This will satisfy the visual location rule and will efficiently improve the performance of task searching.

scholarly journals Monitoring advances including consent: learning from COVID-19 trials and other trials running in UKCRC registered clinical trials units during the pandemic

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Sharon B. Love ◽  
Emma Armstrong ◽  
Carrie Bayliss ◽  
Melanie Boulter ◽  
Lisa Fox ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Remote Monitoring ◽  
Research Collaboration ◽  
Monitoring Task ◽  
Critical Data ◽  
Site Monitoring ◽  
Clinical Trials Unit ◽  
Third Person ◽  
Trial Monitoring ◽  
The Uk

AbstractThe COVID-19 pandemic has affected how clinical trials are managed, both within existing portfolios and for the rapidly developed COVID-19 trials. Sponsors or delegated organisations responsible for monitoring trials have needed to consider and implement alternative ways of working due to the national infection risk necessitating restricted movement of staff and public, reduced clinical staff resource as research staff moved to clinical areas, and amended working arrangements for sponsor and sponsor delegates as staff moved to working from home.Organisations have often worked in isolation to fast track mitigations required for the conduct of clinical trials during the pandemic; this paper describes many of the learnings from a group of monitoring leads based in United Kingdom Clinical Research Collaboration (UKCRC) Clinical Trials Unit (CTUs) within the UK.The UKCRC Monitoring Task and Finish Group, comprising monitoring leads from 9 CTUs, met repeatedly to identify how COVID-19 had affected clinical trial monitoring. Informed consent is included as a specific issue within this paper, as review of completed consent documentation is often required within trial monitoring plans (TMPs). Monitoring is defined as involving on-site monitoring, central monitoring or/and remote monitoring.Monitoring, required to protect the safety of the patients and the integrity of the trial and ensure the protocol is followed, is often best done by a combination of central, remote and on-site monitoring. However, if on-site monitoring is not possible, workable solutions can be found using only central or central and remote monitoring. eConsent, consent by a third person, or via remote means is plausible. Minimising datasets to the critical data reduces workload for sites and CTU staff. Home working caused by COVID-19 has made electronic trial master files (TMFs) more inviting. Allowing sites to book and attend protocol training at a time convenient to them has been successful and worth pursuing for trials with many sites in the future.The arrival of COVID-19 in the UK has forced consideration of and changes to how clinical trials are conducted in relation to monitoring. Some developed practices will be useful in other pandemics and others should be incorporated into regular use.

scholarly journals Dynamic Control of Response Criterion in Premotor Cortex during Perceptual Detection under Temporal Uncertainty

Neuron ◽  
2015 ◽  
Vol 86 (4) ◽  
pp. 1067-1077 ◽  
Author(s):  
Federico Carnevale ◽  
Victor de Lafuente ◽  
Ranulfo Romo ◽  
Omri Barak ◽  
Néstor Parga
Keyword(s):  
Premotor Cortex ◽  
Dynamic Control ◽  
Response Criterion ◽  
Temporal Uncertainty

Sentence processing in language-impaired children under conditions of filtering and time compression

1995 ◽  
Vol 16 (2) ◽  
pp. 137-154 ◽  
Author(s):  
Rachel E. Stark ◽  
James W. Montgomery
Keyword(s):  
Sentence Processing ◽  
High Frequency ◽  
Response Times ◽  
Language Impaired ◽  
Monitoring Task ◽  
Time Compression ◽  
Lower Accuracy ◽  
On Line ◽  
Impaired Children ◽  
Monitoring Performance

ABSTRACTNineteen language-impaired (LI) and 20 language-normal (LN) children participated in an on-line word-monitoring task. Words were presented in lists and in sentences readily comprehended by younger children. The sentences were unaltered, tow-pass filtered, and time- compressed. Both groups had shorter mean response times (MRTs), but lower accuracy, for words in sentences than words in lists. The LI children had significantly longer MRTs under sentence conditions and lower accuracy overall than the LN children. Filtering had an adverse effect upon accuracy and MRT for both subject groups. Time compression did not, suggesting that the reduction in high-frequency information and the rate of presentation exert different effects. Subject differences in attention, as well as in linguistic competence and motor control, may have influenced word-monitoring performance.

CSMC

2021 ◽  
Vol 5 (4) ◽  
pp. 1-22
Author(s):  
Hai Wang ◽  
Baoshen Guo ◽  
Shuai Wang ◽  
Tian He ◽  
Desheng Zhang
Keyword(s):  
Large Scale ◽  
Mobile Network ◽  
Signal Propagation ◽  
Spectrum Management ◽  
External Information ◽  
Temporal Uncertainty ◽  
Large Area ◽  
Fine Grained ◽  
Map Construction ◽  
Spatio Temporal

The rise concern about mobile communication performance has driven the growing demand for the construction of mobile network signal maps which are widely utilized in network monitoring, spectrum management, and indoor/outdoor localization. Existing studies such as time-consuming and labor-intensive site surveys are difficult to maintain an update-to-date finegrained signal map within a large area. The mobile crowdsensing (MCS) paradigm is a promising approach for building signal maps because collecting large-scale MCS data is low-cost and with little extra-efforts. However, the dynamic environment and the mobility of the crowd cause spatio-temporal uncertainty and sparsity of MCS. In this work, we leverage MCS as an opportunity to conduct the city-wide mobile network signal map construction. We propose a fine-grained city-wide Cellular Signal Map Construction (CSMC) framework to address two challenges including (i) the problem of missing and unreliable MCS data; (ii) spatio-temporal uncertainty of signal propagation. In particular, CSMC captures spatio-temporal characteristics of signals from both inter- and intra- cellular base stations and conducts missing signal recovery with Bayesian tensor decomposition to build large-area fine-grained signal maps. Furthermore, CSMC develops a context-aware multi-view fusion network to make full use of external information and enhance signal map construction accuracy. To evaluate the performance of CSMC, we conduct extensive experiments and ablation studies on a large-scale dataset with over 200GB MCS signal records collected from Shanghai. Experimental results demonstrate that our model outperforms state-of-the-art baselines in the accuracy of signal estimation and user localization.

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