scholarly journals Planning with Partner Uncertainty Modeling for Efficient Information Revealing in Teamwork

2020 ◽  
Author(s):  
Shih-Yun Lo ◽  
Elaine Schaertl Short ◽  
Andrea L. Thomaz
Keyword(s):  
Uncertainty Modeling ◽  
Efficient Information

Hybrid Deep Neural Model for Duplicate Question Detection in Transliterated Bi-lingual Data

2019 ◽  
Vol 12 ◽  
Author(s):  
Seema Rani ◽  
Avadhesh Kumar ◽  
Naresh Kumar
Keyword(s):  
Question Answering ◽  
Neural Model ◽  
Manhattan Distance ◽  
Semantic Matching ◽  
English Only ◽  
Detection Model ◽  
Proposed Model ◽  
Reported Study ◽  
Social Media Platforms ◽  
Efficient Information

Background: Duplicate content often corrupts the filtering mechanism in online question answering. Moreover, as users are usually more comfortable conversing in their native language questions, transliteration adds to the challenges in detecting duplicate questions. This compromises with the response time and increases the answer overload. Thus, it has now become crucial to build clever, intelligent and semantic filters which semantically match linguistically disparate questions. Objective: Most of the research on duplicate question detection has been done on mono-lingual, majorly English Q&A platforms. The aim is to build a model which extends the cognitive capabilities of machines to interpret, comprehend and learn features for semantic matching in transliterated bi-lingual Hinglish (Hindi + English) data acquired from different Q&A platforms. Method: In the proposed DQDHinglish (Duplicate Question Detection) Model, firstly language transformation (transliteration & translation) is done to convert the bi-lingual transliterated question into a mono-lingual English only text. Next a hybrid of Siamese neural network containing two identical Long-term-Short-memory (LSTM) models and Multi-layer perceptron network is proposed to detect semantically similar question pairs. Manhattan distance function is used as the similarity measure. Result: A dataset was prepared by scrapping 100 question pairs from various social media platforms, such as Quora and TripAdvisor. The performance of the proposed model on the basis of accuracy and F-score. The proposed DQDHinglish achieves a validation accuracy of 82.40%. Conclusion: A deep neural model was introduced to find semantic match between English question and a Hinglish (Hindi + English) question such that similar intent questions can be combined to enable fast and efficient information processing and delivery. A dataset was created and the proposed model was evaluated on the basis of performance accuracy. To the best of our knowledge, this work is the first reported study on transliterated Hinglish semantic question matching.

scholarly journals Method of Estimating Uncertainty as a Way to Evaluate Continuity Quality of Power Supply in Hospital Devices

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 486
Author(s):  
Marek Stawowy ◽  
Adam Rosiński ◽  
Jacek Paś ◽  
Tomasz Klimczak
Keyword(s):  
Power Systems ◽  
Power Supply ◽  
Uncertainty Modeling ◽  
Supply System ◽  
Additional Advantage ◽  
Quality Models ◽  
Reliability Indicators ◽  
Electrical Devices

The article presents issues related to the determination of the continuity quality of power supply (CQoPS) for hospital electrical devices. The model describing CQoPS takes into account power redundancy. The uncertainty modeling method based on the certainty factor (CF) of the hypothesis was used to establish the single-valued CQoPS factor. CQoPS modeling takes into account multidimensional quality models and physical stages of power. The quality models take into account seven dimensions that make up CQoPS (availability, appropriate amount, power supply reliability, power quality, assurance, responsiveness, security). The model of power stages includes five of these stages (power generation, delivery to recipient, distribution by recipient, delivery to device, power-consuming device). To date, when designing hospital power systems, the applied reliability indicators revealed limitations because they do not consider all the possible factors influencing the power continuity. Estimating the supply continuity quality with the use of the uncertainty modeling proposed in this article allows for taking into account all possible factors (not just reliability factors) that may affect supply continuity. The presented modeling offers an additional advantage, namely, it allows an expanded evaluation of the hospital supply system and a description using only one indicator. This fact renders the evaluation of the supply system possible for unqualified staff. At the end of the article, some examples of calculations and simulations are presented, thus showing that the applied methods give the expected results.

scholarly journals A Survey on Microgrid Energy Management Considering Flexible Energy Sources

Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2156 ◽  
Author(s):  
Hossein Shayeghi ◽  
Elnaz Shahryari ◽  
Mohammad Moradzadeh ◽  
Pierluigi Siano
Keyword(s):  
Energy Management ◽  
Renewable Energy Sources ◽  
Uncertainty Modeling ◽  
Optimization Techniques ◽  
Point Of View ◽  
Energy Sources ◽  
Market Prices ◽  
Distributed Generations ◽  
Peak Loads ◽  
Microgrid Energy Management

Aggregation of distributed generations (DGs) along with energy storage systems (ESSs) and controllable loads near power consumers has led to the concept of microgrids. However, the uncertain nature of renewable energy sources such as wind and photovoltaic generations, market prices and loads has led to difficulties in ensuring power quality and in balancing generation and consumption. To tackle these problems, microgrids should be managed by an energy management system (EMS) that facilitates the minimization of operational costs, emissions and peak loads while satisfying the microgrid technical constraints. Over the past years, microgrids’ EMS have been studied from different perspectives and have recently attracted considerable attention of researchers. To this end, in this paper a classification and a survey of EMSs has been carried out from a new point of view. EMSs have been classified into four categories based on the kind of the reserve system being used, including non-renewable, ESS, demand-side management (DSM) and hybrid systems. Moreover, using recent literature, EMSs have been reviewed in terms of uncertainty modeling techniques, objective functions (OFs) and constraints, optimization techniques, and simulation and experimental results presented in the literature.

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