Showing papers on "Reliability (statistics) published in 2018"

Applying LDA Topic Modeling in Communication Research: Toward a Valid and Reliable Methodology

Abstract: Latent Dirichlet allocation (LDA) topic models are increasingly being used in communication research. Yet, questions regarding reliability and validity of the approach have received little attentio...

Optimum Placement of UAV as Relays

Abstract: Unmanned aerial vehicles (UAVs) as aerial base stations or relays are becoming increasingly important in communications. In this letter, the optimum placement of a relaying UAV for maximum reliability is studied. The total power loss, the overall outage, and the overall bit error rate are derived as reliability measures. The optimum altitude is investigated for both static and mobile UAVs. Numerical results show that different reliability measures have slightly different optimum altitudes and that decode-and-forward is better than amplify-and-forward.

On the state-of-the-art of particle methods for coastal and ocean engineering

Abstract: The article aims at providing an up-to-date review on several latest advancements related to particle methods with applications in coastal and ocean engineering. The latest advancements corresponding to accuracy, stability, conservation properties, multiphase multi-physics multi-scale simulations, fluid-structure interactions, exclusive coastal/ocean engineering applications and computational efficiency are reviewed. The future perspectives for further enhancement of applicability and reliability of particle methods for coastal/ocean engineering applications are also highlighted.

Discriminative Correlation Filter Tracker with Channel and Spatial Reliability

Abstract: Short-term tracking is an open and challenging problem for which discriminative correlation filters (DCF) have shown excellent performance. We introduce the channel and spatial reliability concepts to DCF tracking and provide a learning algorithm for its efficient and seamless integration in the filter update and the tracking process. The spatial reliability map adjusts the filter support to the part of the object suitable for tracking. This both allows to enlarge the search region and improves tracking of non-rectangular objects. Reliability scores reflect channel-wise quality of the learned filters and are used as feature weighting coefficients in localization. Experimentally, with only two simple standard feature sets, HoGs and colornames, the novel CSR-DCF method--DCF with channel and spatial reliability--achieves state-of-the-art results on VOT 2016, VOT 2015 and OTB100. The CSR-DCF runs close to real-time on a CPU.

Uji Validitas dan Reliabilitas Instrumen Penelitian Kuantitatif

Abstract: The research instrument is a tool used to collect data or measure objects of a research variable To obtain the correct data for the conclusion that is in accordance with the actual situation, then required a valid instrument and consistent and appropriate in providing data of research result Instrument reliability tests to include test-retest, equivalent, and internal consistency Internal consistency tests have several testing techniques depending on the type of instrument Testing techniques included split half test, KR 20, KR 21, and Alfa Cronbach The value of the validity and reliability of an instrument is influenced by the measured subject, the instrument user, and the instrument itself Sehinggga, validity and reliability must always be tested before the instrument is used

Correlation Tracking via Joint Discrimination and Reliability Learning

Abstract: For visual tracking, an ideal filter learned by the correlation filter (CF) method should take both discrimination and reliability information. However, existing attempts usually focus on the former one while pay less attention to reliability learning. This may make the learned filter be dominated by the unexpected salient regions on the feature map, thereby resulting in model degradation. To address this issue, we propose a novel CF-based optimization problem to jointly model the discrimination and reliability information. First, we treat the filter as the element-wise product of a base filter and a reliability term. The base filter is aimed to learn the discrimination information between the target and backgrounds, and the reliability term encourages the final filter to focus on more reliable regions. Second, we introduce a local response consistency regular term to emphasize equal contributions of different regions and avoid the tracker being dominated by unreliable regions. The proposed optimization problem can be solved using the alternating direction method and speeded up in the Fourier domain. We conduct extensive experiments on the OTB-2013, OTB-2015 and VOT-2016 datasets to evaluate the proposed tracker. Experimental results show that our tracker performs favorably against other state-of-the-art trackers.

Accuracy, intra- and inter-unit reliability, and comparison between GPS and UWB-based position-tracking systems used for time-motion analyses in soccer.

Abstract: There is interest in the accuracy and inter-unit reliability of position-tracking systems to monitor players. Research into this technology, although relatively recent, has grown exponentially in t...

Probabilistic fatigue life prediction and reliability assessment of a high pressure turbine disc considering load variations

Abstract: In the present work, a probabilistic framework for fatigue life prediction and reliability assessment of an engine high pressure turbine disc is proposed to incorporate the effects of load variatio...

Reliability and Validity of Ambulatory Cognitive Assessments

Abstract: Mobile technologies are increasingly used to measure cognitive function outside of traditional clinic and laboratory settings. Although ambulatory assessments of cognitive function conducted in people's natural environments offer potential advantages over traditional assessment approaches, the psychometrics of cognitive assessment procedures have been understudied. We evaluated the reliability and construct validity of ambulatory assessments of working memory and perceptual speed administered via smartphones as part of an ecological momentary assessment protocol in a diverse adult sample ( N = 219). Results indicated excellent between-person reliability (≥0.97) for average scores, and evidence of reliable within-person variability across measurement occasions (0.41-0.53). The ambulatory tasks also exhibited construct validity, as evidence by their loadings on working memory and perceptual speed factors defined by the in-lab assessments. Our findings demonstrate that averaging across brief cognitive assessments made in uncontrolled naturalistic settings provide measurements that are comparable in reliability to assessments made in controlled laboratory environments.

A Survey on Computer Vision for Assistive Medical Diagnosis From Faces

Abstract: Automatic medical diagnosis is an emerging center of interest in computer vision as it provides unobtrusive objective information on a patient's condition. The face, as a mirror of health status, can reveal symptomatic indications of specific diseases. Thus, the detection of facial abnormalities or atypical features is at upmost importance when it comes to medical diagnostics. This survey aims to give an overview of the recent developments in medical diagnostics from facial images based on computer vision methods. Various approaches have been considered to assess facial symptoms and to eventually provide further help to the practitioners. However, the developed tools are still seldom used in clinical practice, since their reliability is still a concern due to the lack of clinical validation of the methodologies and their inadequate applicability. Nonetheless, efforts are being made to provide robust solutions suitable for healthcare environments, by dealing with practical issues such as real-time assessment or patients positioning. This survey provides an updated collection of the most relevant and innovative solutions in facial images analysis. The findings show that with the help of computer vision methods, over 30 medical conditions can be preliminarily diagnosed from the automatic detection of some of their symptoms. Furthermore, future perspectives, such as the need for interdisciplinary collaboration and collecting publicly available databases, are highlighted.

Development of Energy Storage Systems for Power Network Reliability: A Review

Abstract: Electricity plays a crucial role in the well-being of humans and is a determining factor of the economic development of a country. Electricity issues have encouraged researchers to focus on improving power availability and quality along with reliability. This pursuit has increasingly raised the intention to integrate renewable energy (RE) into power systems to curb the problem of energy deficiency. However, intermittency in the sources of RE supply coupled with fluctuating changes in demand with respect to time has induced high risk in maintaining system reliability in terms of providing adequate supply to consumers. Whilst an energy storage system (ESS) is not another source of electricity, it is proven to be effective and viable in solving the aforementioned issues. Thus, this paper comprehensively reviews the development of ESS technologies and discusses the benefits and real-life applications of these technologies. The concept of reliability in power systems is also explored to provide an improved understanding of this study. Lastly, notable studies that have addressed the reliability impact of ESSs on power systems are discussed. This review paper therefore is expected to provide a critical analysis of ESS developments, as well as recognize their research gaps in terms of reliability studies in modern RE-integrated power networks.

Role of Outage Management Strategy in Reliability Performance of Multi-Microgrid Distribution Systems

Abstract: This paper develops a general framework for reliability assessment of multi-microgrid (MMG) distribution systems. It also investigates reliability impacts of coordinated outage management strategies in a MMG distribution network. According to the proposed reliability evaluation framework, which is based on sequential Monte Carlo simulation method, distribution system is divided into smaller sections/microgrids based on protection system configuration and operating measures are efficiently simulated considering different operation modes. In order to demonstrate the role of outage management strategy in reliability performance of MMG distribution systems, at first, the required features of an outage management strategy are identified. Then, suitable centralized and hierarchical schemes are introduced for operation of such systems during outage events. The proposed schemes, which are based on model predictive control approach, minimize total load curtailments in the system. Moreover, they are flexible and can effectively deal with multiple contingencies as well as uncertainties of outage duration. The developed reliability assessment framework is applied to a test system and performance of the presented outage management schemes are explored through extensive case studies. Obtained results suggest that implementation of an appropriate coordinated scheme is crucial to reliable operation of MMG distribution systems.

Machine Learning approach for Predictive Maintenance in Industry 4.0

Abstract: Condition monitoring together with predictive maintenance of electric motors and other equipment used by the industry avoids severe economic losses resulting from unexpected motor failures and greatly improves the system reliability. This paper describes a Machine Learning architecture for Predictive Maintenance, based on Random Forest approach. The system was tested on a real industry example, by developing the data collection and data system analysis, applying the Machine Learning approach and comparing it to the simulation tool analysis. Data has been collected by various sensors, machine PLCs and communication protocols and made available to Data Analysis Tool on the Azure Cloud architecture. Preliminary results show a proper behavior of the approach on predicting different machine states with high accuracy.

The Cyber-Physical Systems Revolution

Abstract: Cyber-physical systems constitute a disruptive technology across many industries, with a strong impact on economies and social processes. Their applications in many domains, from manufacturing to agriculture and from critical infrastructure to assistive living, brings challenges in technology, business, law and ethics.

Enhancing the validity of a Quality of Life measure for autistic people

Abstract: Accurate measurement of quality of life (QoL) is important for evaluation of autism services and trials of interventions. We undertook psychometric validation of the World Health Organisation measure-WHOQoL-BREF, examined construct validity of the WHO Disabilities module and developed nine additional autism-specific items (ASQoL) from extensive consultation with the autism community. The sample of 309 autistic people was recruited from the Adult Autism Spectrum Cohort-UK. The WHOQoL-BREF had good psychometric properties, including criterion, convergent, divergent and discriminant validity. The WHO Disabilities module showed adequate construct validity and reliability. The ASQoL items form a unitary factor of QoL, with one global item. Future studies can use the WHO measures alongside the ASQoL items to measure QoL of autistic people.

Test-Retest Reliability and Interpretation of Common Concussion Assessment Tools: Findings From the NCAA-DoD CARE Consortium

Abstract: Concussion diagnosis is typically made through clinical examination and supported by performance on clinical assessment tools. Performance on commonly implemented and emerging assessment tools is known to vary between administrations, in the absence of concussion. To evaluate the test-retest reliability of commonly implemented and emerging concussion assessment tools across a large nationally representative sample of student-athletes. Participants (n = 4874) from the Concussion Assessment, Research, and Education Consortium completed annual baseline assessments on two or three occasions. Each assessment included measures of self-reported concussion symptoms, motor control, brief and extended neurocognitive function, reaction time, oculomotor/oculovestibular function, and quality of life. Consistency between years 1 and 2 and 1 and 3 were estimated using intraclass correlation coefficients or Kappa and effect sizes (Cohen’s d). Clinical interpretation guidelines were also generated using confidence intervals to account for non-normally distributed data. Reliability for the self-reported concussion symptoms, motor control, and brief and extended neurocognitive assessments from year 1 to 2 ranged from 0.30 to 0.72 while effect sizes ranged from 0.01 to 0.28 (i.e., small). The reliability for these same measures ranged from 0.34 to 0.66 for the year 1–3 interval with effect sizes ranging from 0.05 to 0.42 (i.e., small to less than medium). The year 1–2 reliability for the reaction time, oculomotor/oculovestibular function, and quality-of-life measures ranged from 0.28 to 0.74 with effect sizes from 0.01 to 0.38 (i.e., small to less than medium effects). This investigation noted less than optimal reliability for most common and emerging concussion assessment tools. Despite this finding, their use is still necessitated by the absence of a gold standard diagnostic measure, with the ultimate goal of developing more refined and sound tools for clinical use. Clinical interpretation guidelines are provided for the clinician to apply with a degree of certainty in application.

A review of reliability-based methods for risk analysis and their application in the offshore wind industry

Abstract: Offshore and marine renewable energy applications are governed by a number of uncertainties relevant to the design process and operational management of assets. Risk and reliability analysis methods can allow for systematic assessment of these uncertainties, supporting decisions integrating associated consequences in case of unexpected events. This paper focuses on the review and classification of such methods applied specifically within the offshore wind industry. The quite broad differentiation between qualitative and quantitative methods, as well as some which could belong to both groups depending on the way in which they are used, is further differentiated, based on the most commonly applied theories. Besides the traditional qualitative failure mode, tree, diagrammatic, and hazard analyses, more sophisticated and novel techniques, such as correlation failure mode analysis, threat matrix, or dynamic fault tree analysis, are coming to the fore. Similarly, the well-practised quantitative approaches of an analytical nature, such as the concept of limit states and first or second order reliability methods, and of a stochastic nature, such as Monte Carlo simulation, response surface, or importance sampling methods, are still common practice. Further, Bayesian approaches, reliability-based design optimisation tools, multivariate analyses, fuzzy set theory, and data pooling strategies are finding more and more use within the reliability assessment of offshore and marine renewable energy assets.

Seismic Reliability of Code-Conforming Italian Buildings

Abstract: This paper presents and discusses some research results related to the seismic failure risk of standard, residential and industrial, buildings designed for damage, and life-safety according to the ...

Internal, External, and Ecological Validity in Research Design, Conduct, and Evaluation:

Abstract: Reliability and validity describe desirable psychometric characteristics of research instruments The concept of validity is also applied to research studies and their findings Internal validity examines whether the study design, conduct, and analysis answer the research questions without bias External validity examines whether the study findings can be generalized to other contexts Ecological validity examines, specifically, whether the study findings can be generalized to real-life settings; thus ecological validity is a subtype of external validity These concepts are explained using examples so that readers may understand why the consideration of internal, external, and ecological validity is important for designing and conducting studies, and for understanding the merits of published research

Semi-Markov Processes: Applications in System Reliability and Maintenance

Abstract: Semi-Markov Processes: Applications in System Reliability and Maintenance is a modern view of discrete state space and continuous time semi-Markov processes and their applications in reliability and maintenance. The book explains how to construct semi-Markov models and discusses the different reliability parameters and characteristics that can be obtained from those models. The book is a useful resource for mathematicians, engineering practitioners, and PhD and MSc students who want to understand the basic concepts and results of semi-Markov process theory. * Clearly defines the properties and theorems from discrete state Semi-Markov Process (SMP) theory.* Describes the method behind constructing Semi-Markov (SM) models and SM decision models in the field of reliability and maintenance.* Provides numerous individual versions of SM models, including the most recent and their impact on system reliability and maintenance.

Sensor dynamic reliability evaluation based on evidence theory and intuitionistic fuzzy sets

Abstract: This paper presents a new method for sensor dynamic reliability evaluation based on evidence theory and intuitionistic fuzzy sets when the prior knowledge is unknown. The dynamic reliability of sensors is evaluated based on supporting degree between basic probability assignments (BPAs) provided by sensors. First, the concept of asymmetric supporting degree is proposed. By transforming BPAs to intuitionistic fuzzy sets, supporting degree between BPAs is calculated based on intuitionistic fuzzy operations and similarity measure. Then the relationship between dynamic reliability and supporting degree is analyzed. The process of dynamic reliability evaluation is proposed. Finally, the proposed dynamic reliability evaluation is applied to evidence combination. A new evidence combination rule is proposed based on evidence discounting operation and Dempster’s rule. Comparative analysis on the performance of the proposed reliability evaluation method and evidence combination rule is carried out based on numerical examples. The proposed method for data fusion is also applied in target recognition to show its feasibility and validity.