9 results on '"probabilistic model"'
Search Results
2. Probabilistic Models for Competence Assessment in Education.
- Author
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López de Aberasturi Gómez, Alejandra, Sabater-Mir, Jordi, and Sierra, Carles
- Subjects
ASSESSMENT of education ,STANDARD deviations ,BAYESIAN field theory ,MULTIAGENT systems - Abstract
Probabilistic models of competence assessment join the benefits of automation with human judgment. We start this paper by replicating two preexisting probabilistic models of peer assessment ( P G 1 -bias and PAAS). Despite the use that both make of probability theory, the approach of these models is radically different. While P G 1 -bias is purely Bayesian, PAAS models the evaluation process in a classroom as a multiagent system, where each actor relies on the judgment of others as long as their opinions coincide. To reconcile the benefits of Bayesian inference with the concept of trust posed in PAAS, we propose a third peer evaluation model that considers the correlations between any pair of peers who have evaluated someone in common: P G -bivariate. The rest of the paper is devoted to a comparison with synthetic data from these three models. We show that P G 1 -bias produces predictions with lower root mean squared error (RMSE) than P G -bivariate. However, both models display similar behaviors when assessing how to choose the next assignment to be graded by a peer, with an " R M S E decreasing policy" reporting better results than a random policy. Fair comparisons among the three models show that P G 1 -bias makes the lowest error in situations of scarce ground truths. Nevertheless, once nearly 20 % of the teacher's assessments are introduced, PAAS sometimes exceeds the quality of P G 1 -bias' predictions by following an entropy minimization heuristic. P G -bivariate, our new proposal to reconcile PAAS' trust-based approach with P G 1 -bias' theoretical background, obtains a similar percentage of error values to those of the original models. Future work includes applying the models to real experimental data and exploring new heuristics to determine which teacher's grade should be obtained next to minimize the overall error. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
3. Probabilistic Moment Capacity Models of Reinforced Concrete Slab Members for Underground Box Culverts.
- Author
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Kim, Sang-Hyo, Boldoo, Tuguldur, Kim, Dae-Yoon, Chu, Inyeop, and Woo, Sang-Kyun
- Subjects
MONTE Carlo method ,CONCRETE slabs ,CULVERTS ,FLEXURAL strength ,MATERIALS testing ,ULTIMATE strength ,BUILDING sites - Abstract
This study was performed to evaluate the probabilistic characteristics of the flexural strength of reinforced concrete (RC) flexural members adopted for underground box culverts. These probabilistic models were developed to be adopted for the development of limit state load combination formats for underground RC box culverts. The probabilistic models of uncertainties inherent in the basic design variables were developed to evaluate flexural strength using field material test data as well as field survey data collected from various domestic construction sites of underground box culverts in Korea. The basic design variables include concrete strength, steel rebar strength, and section dimensions, such as slab thickness and rebar locations. Some design variables are assumed to have inherent construction error characteristics, which may be different from those inherent in the RC members for buildings and bridges. The bias models on flexural strength were evaluated based on the experimental results of four-point flexural tests on one-way RC slabs, which were fabricated following the general practice adopted in the local underground box culvert construction process. Based on the probabilistic models of basic design variables, as well as the bias models of flexural strength, Monte Carlo simulations were performed to examine the probabilistic characteristics of both ultimate flexural strength and yield moment strength of RC slab members. Some sensitivity analyses were performed to confirm the soundness of various probability models and the assumptions adopted in the development procedure. The proposed procedure may be applied to develop probabilistic resistance models for structural members, in which the construction error characteristics are assumed to be different from other practices. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
4. Modeling of Vessel Traffic Flow for Waterway Design–Port of Świnoujście Case Study.
- Author
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Nowy, Agnieszka, Łazuga, Kinga, Gucma, Lucjan, Androjna, Andrej, Perkovič, Marko, and Srše, Jure
- Subjects
TRAFFIC flow ,AUTOMATIC identification ,SYSTEM identification ,STANDARD deviations ,WATERWAYS ,NAVIGATION ,RISK assessment - Abstract
The paper presents an analysis of ship traffic using the port of Świnoujście and the problems associated with modelling vessel traffic flows. Navigation patterns were studied using the Automatic Identification System (AIS); an analysis of vessel traffic was performed with statistical methods using historical data; and the paper presents probabilistic models of the spatial distribution of vessel traffic and its parameters. The factors that influence the spatial distribution were considered to be the types of vessels, dimensions, and distances to hazards. The results show a correlation between the standard deviation of the traffic flow, the vessel sizes, and the distance to the hazard. These can be used in practice to determine the safety of navigation and the design of non-existing waterways and to create a general model of vessel traffic flow. The creation of the practical applications is intended to improve navigation efficiency, safety, and risk analysis in any particular area. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
5. A Probabilistic-Based Deep Learning Model for Skin Lesion Segmentation.
- Author
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Adegun, Adekanmi Adeyinka, Viriri, Serestina, and Yousaf, Muhammad Haroon
- Subjects
DEEP learning ,SKIN imaging ,SKIN disease diagnosis ,SIGNAL convolution ,RANDOM fields ,SKIN cancer - Abstract
The analysis and detection of skin cancer diseases from skin lesion have always been tedious when done manually. The complex nature of skin lesion images is one of the key reasons for this. The skin lesion images contain noise and artifacts such as hairs, oil and bubbles, blood vessels, and skin lines. They also have variegated colors, low contrast, and irregular borders. Various computational approaches have been designed in the past for aiding in the detection and diagnosis of skin cancer diseases using skin lesion images. The existing techniques have been limited due to the interference of the aforementioned features of skin lesion. Recently, machine learning techniques, in particular the deep learning techniques have been used for the detection of skin cancer. However, they are still limited to the fuzzy and irregular borders of skin lesion images coupled with the low contrast that exists between the diseased lesion and healthy tissues. In this paper, we utilized a probabilistic model for the enhancement of a fully convolutional network-based deep learning system to analyze and segment skin lesion images. The probabilistic model employs an efficient mean-field approximate probabilistic inference approach with a fully connected conditional random field that utilizes a Gaussian kernel. The probabilistic model further performs a refinement of skin lesion borders. The whole framework is tested and evaluated on publicly available skin lesion image datasets of ISBI 2017 and PH2. The system achieved a better performance, having an accuracy of 98%. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
6. Proposal of a Probabilistic Model on Rotating Bending Fatigue Property of a Bearing Steel in a Very High Cycle Regime.
- Author
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Sakai, Tatsuo, Nakagawa, Akiyoshi, Nakamura, Yuki, Oguma, Noriyasu, and Rossetto, Massimo
- Subjects
HIGH cycle fatigue ,BEARING steel ,HIGH strength steel ,FAILURE mode & effects analysis ,STRESS concentration ,STATISTICAL models - Abstract
In S-N diagrams for high strength steels, the duplex S-N curves for surface-initiated failure and interior inclusion-initiated failure were usually confirmed in the very high cycle regime. This trend is more distinct in the loading type of rotating bending, due to the stress distribution across the section. In the case of interior failure mode, the fish-eye is usually observed on the fracture surface and an inclusion is also observed at the center of the fish-eye. In the present work, the authors attempted to construct a probabilistic model on the statistical fatigue property in the interior failure mode, based on the distribution characteristics of the location and the size of the interior inclusion at the crack initiation site. Thus, the P-S-N characteristics of the bearing steel (SUJ2) in the very high cycle regime were successfully explained. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
7. A Probabilistic Hyperspectral Imagery Restoration Method.
- Author
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Wei, Wei, Nie, Jiatao, and Tian, Chunna
- Subjects
LOW-rank matrices ,RANDOM noise theory ,GAUSSIAN distribution ,IMAGE denoising ,PIXELS ,NOISE - Abstract
Hyperspectral image (HSI) restoration is an important task of hyperspectral imagery processing, which aims to improve the performance of the subsequent HSI interpretation and applications. Considering HSI is always influenced by multiple factors—such as Gaussian noise, stripes, dead pixels, etc.—we propose an HSI-oriented probabilistic low-rank restoration method to address this problem. Specifically, we treat the expected clean HSI as a low-rank matrix. We assume the distribution of complex noise obeys a mixture of Gaussian distributions. Then, the HSI restoration problem is casted into solving the clean HSI from its counterpart with complex noise. In addition, considering the rank number need to be assigned manually for existing low-rank based HSI restoration method, we propose to automatically determine the rank number of the low-rank matrix by taking advantage of hyperspectral unmixing. Experimental results demonstrate HSI image can be well restored with the proposed method. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
8. Effects of Crack and Climate Change on Service Life of Concrete Subjected to Carbonation.
- Author
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Wang, Xiao-Yong
- Subjects
CARBONATION (Chemistry) ,STEEL bars ,CORROSION & anti-corrosives - Abstract
Carbonation is among the primary reasons for the initiation of the corrosion of steel rebar in reinforced concrete (RC) structures. Due to structural loading effects and environmental actions, inevitable cracks have frequently occurred in concrete structures since the early ages. Additionally, climate change, which entails increases in CO
2 concentration and environmental temperature, will also accelerate the carbonation of concrete. This article presents an analytical way of predicting the service life of cracked concrete structures considering influences of carbonation and climate change. First, using a hydration model, the quantity of carbonatable materials and concrete porosity were calculated. Carbonation depth was evaluated considering properties of concrete materials and environmental conditions. Second, the influence of cracks on CO2 diffusivity was examined. Carbonation depth for cracked concrete was evaluated using equivalent CO2 diffusivity. The effects of climate change, for example, growing CO2 concentration and environmental temperature, were considered using different schemes of carbonation models. Third, different climate change scenarios (such as Representative Concentration Pathways (RCP) 2.6, RCP 4.5, RCP 8.5 and upper 90% confidence interval of RCP 8.5) and time slices (such as 2000 and 2050) were used for case studies. By utilizing the Monte Carlo method, the influences of various climate change scenarios on the service life loss of concrete structures were highlighted. [ABSTRACT FROM AUTHOR]- Published
- 2018
- Full Text
- View/download PDF
9. An Appropriate Wind Model for Wind Integrated Power Systems Reliability Evaluation Considering Wind Speed Correlations.
- Author
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Karki, Rajesh, Dhungana, Dinesh, and Billinton, Roy
- Subjects
EMISSIONS (Air pollution) ,ECOLOGICAL impact ,RENEWABLE energy sources ,WIND power ,RELIABILITY in engineering ,WIND power plants - Abstract
Adverse environmental impacts of carbon emissions are causing increasing concerns to the general public throughout the world. Electric energy generation from conventional energy sources is considered to be a major contributor to these harmful emissions. High emphasis is therefore being given to green alternatives of energy, such as wind and solar. Wind energy is being perceived as a promising alternative. This source of energy technology and its applications have undergone significant research and development over the past decade. As a result, many modern power systems include a significant portion of power generation from wind energy sources. The impact of wind generation on the overall system performance increases substantially as wind penetration in power systems continues to increase to relatively high levels. It becomes increasingly important to accurately model the wind behavior, the interaction with other wind sources and conventional sources, and incorporate the characteristics of the energy demand in order to carry out a realistic evaluation of system reliability. Power systems with high wind penetrations are often connected to multiple wind farms at different geographic locations. Wind speed correlations between the different wind farms largely affect the total wind power generation characteristics of such systems, and therefore should be an important parameter in the wind modeling process. This paper evaluates the effect of the correlation between multiple wind farms on the adequacy indices of wind-integrated systems. The paper also proposes a simple and appropriate probabilistic analytical model that incorporates wind correlations, and can be used for adequacy evaluation of multiple wind-integrated systems. [ABSTRACT FROM AUTHOR]
- Published
- 2013
- Full Text
- View/download PDF
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