A novel approach to the state regulator problem with inaccessible states

1972 ◽  
Vol 17 (2) ◽  
pp. 254-255
Author(s):  
J. Walden ◽  
W. McDaniel
Keyword(s):  
The State ◽  
Regulator Problem ◽  
Novel Approach ◽  
State Regulator

Effectiveness of Government Regulation of the Banking Sector: Assessment and Rating of Banks

2020 ◽  
pp. 85-95
Author(s):  
Halyna O. Kryshtal
Keyword(s):  
Government Regulation ◽  
Banking Sector ◽  
Credit Rating ◽  
Analytical Data ◽  
The State ◽  
Economic Sector ◽  
Rating Agencies ◽  
Depth Study ◽  
State Regulator ◽  
Almost All

The article deals with the causes of the negative situation in the banking sector, as the state of the bank depends on the analysis of almost all aspects of banking activity for some time. It is determined that during the banking sector audits, the state regulator uses analytical data on the banking sector's operations with its monetary obligations, compliance with maturities and maturities of assets that operate and terms and amounts of liabilities, namely, dealing with banking sector liquidity. As their financial reliability is important in the banking sector, therefore, bank clients are a socio-economic sector, needing an objective and independent assessment, as reliability directly affects the socio-economic development of the country. The banking sector was analyzed in 2016-2019 and it was found that during this period violations of laws and regulations issued by the state regulator were made in the banking sector. A number of penalties, written warnings and administrative penalties were applied by the state regulator. The method of determining the rating of banks in respect of which penalties were applied by the state regulator is proposed. The rating allows investors and potential clients to understand the situation in the banking market and helps banks identify their weaknesses and correct their work. The application of the proposed economic and mathematical model in the rating of participants in the banking sector can have a positive effect on: improving the quality of management in the banking sector and transparency in the activities of each individual bank; standardization of technologies of rating of the banking sector under the prism of the applied sanctions by the state regulator. Therefore, there is a need for an in-depth study of the techniques used by credit rating agencies in the banking sector and the identification of the main problems in establishing the rating of the banking sector. Key words: banking sector, state regulator, economic sector, efficiency, rating, rating, social sector.

scholarly journals Density Guarantee on Finding Multiple Subgraphs and Subtensors

2021 ◽  
Vol 15 (5) ◽  
pp. 1-32
Author(s):  
Quang-huy Duong ◽  
Heri Ramampiaro ◽  
Kjetil Nørvåg ◽  
Thu-lan Dam
Keyword(s):  
Lower Bound ◽  
State Of The Art ◽  
The State ◽  
The Other ◽  
Exact Methods ◽  
Practical Solution ◽  
Novel Approach ◽  
Wide Range ◽  
Real World Datasets ◽  
Tensor Data

Dense subregion (subgraph & subtensor) detection is a well-studied area, with a wide range of applications, and numerous efficient approaches and algorithms have been proposed. Approximation approaches are commonly used for detecting dense subregions due to the complexity of the exact methods. Existing algorithms are generally efficient for dense subtensor and subgraph detection, and can perform well in many applications. However, most of the existing works utilize the state-or-the-art greedy 2-approximation algorithm to capably provide solutions with a loose theoretical density guarantee. The main drawback of most of these algorithms is that they can estimate only one subtensor, or subgraph, at a time, with a low guarantee on its density. While some methods can, on the other hand, estimate multiple subtensors, they can give a guarantee on the density with respect to the input tensor for the first estimated subsensor only. We address these drawbacks by providing both theoretical and practical solution for estimating multiple dense subtensors in tensor data and giving a higher lower bound of the density. In particular, we guarantee and prove a higher bound of the lower-bound density of the estimated subgraph and subtensors. We also propose a novel approach to show that there are multiple dense subtensors with a guarantee on its density that is greater than the lower bound used in the state-of-the-art algorithms. We evaluate our approach with extensive experiments on several real-world datasets, which demonstrates its efficiency and feasibility.

scholarly journals Identification of Micro-calcification in Mammogram for Breast Cancer Analysis using SVM Classifier

2018 ◽  
Vol 7 (2.16) ◽  
pp. 29
Author(s):  
Gaurav Makwana ◽  
Lalita Gupta
Keyword(s):  
Breast Cancer ◽  
Clustering Algorithm ◽  
Automatic Segmentation ◽  
Breast Cancer Diagnosis ◽  
The State ◽  
Svm Classifier ◽  
Common Disease ◽  
Test Technique ◽  
Novel Approach ◽  
Breast Calcification

Breast cancer is most common disease in women of all ages. To identify & confirm the state of tumor in breast cancer diagnosis, patients are undergo biopsy number of times to identify malignancy. Early detection of cancer can save the patient. In this paper a novel approach for automatic segmentation & classification of breast calcification is proposed. The diagnostic test technique for detection of breast condition is very costly & requires human expertise whereas proposed method can help in automatically identifying the disease by comparing the data with the standard database. In proposed method a database has been created to define various stage of breast calcification & testing images are pre-processed to resize, enhance & filtered to remove background noise. Clustering is performed by using k-means clustering algorithm. GLCM is used to extract out statistical feature like area, mean, variance, standard deviation, homogeneity, skewness etc. to classify the state of tumor. SVM classifier is used for the classification using extracted feature. 

scholarly journals Multi-hop Reading Comprehension across Documents with Path-based Graph Convolutional Network

2020 ◽  
Author(s):  
Zeyun Tang ◽  
Yongliang Shen ◽  
Xinyin Ma ◽  
Wei Xu ◽  
Jiale Yu ◽  
...  
Keyword(s):  
Reading Comprehension ◽  
Human Performance ◽  
The State ◽  
Ensemble Model ◽  
Human Reasoning ◽  
Convolutional Network ◽  
Gating Mechanism ◽  
Novel Approach ◽  
Multiple Documents ◽  
State Of Art

Multi-hop reading comprehension across multiple documents attracts much attentions recently. In this paper, we propose a novel approach to tackle this multi-hop reading comprehension problem. Inspired by the human reasoning processing, we introduce a path-based graph with reasoning paths which extracted from supporting documents. The path-based graph can combine both the idea of the graph-based and path-based approaches, so it is better for multi-hop reasoning. Meanwhile, we propose Gated-GCN to accumulate evidences on the path-based graph, which contains a new question-aware gating mechanism to regulate the usefulness of information propagating across documents and add question information during reasoning. We evaluate our approach on WikiHop dataset, and our approach achieves the the-state-of-art accuracy against previous published approaches. Especially, our ensemble model surpasses the human performance by 4.2%.

scholarly journals Learning to Transfer Relational Representations through Analogy

2019 ◽  
Vol 33 ◽  
pp. 10015-10016
Author(s):  
Gaetano Rossiello ◽  
Alfio Gliozzo ◽  
Michael Glass
Keyword(s):  
State Of The Art ◽  
Relation Extraction ◽  
Knowledge Bases ◽  
The State ◽  
Large Set ◽  
Relational Information ◽  
Siamese Network ◽  
Distant Supervision ◽  
Novel Approach ◽  
Art Methods

We propose a novel approach to learn representations of relations expressed by their textual mentions. In our assumption, if two pairs of entities belong to the same relation, then those two pairs are analogous. We collect a large set of analogous pairs by matching triples in knowledge bases with web-scale corpora through distant supervision. This dataset is adopted to train a hierarchical siamese network in order to learn entity-entity embeddings which encode relational information through the different linguistic paraphrasing expressing the same relation. The model can be used to generate pre-trained embeddings which provide a valuable signal when integrated into an existing neural-based model by outperforming the state-of-the-art methods on a relation extraction task.

A Novel Approach for Buckling Analysis of Pretwisted Spatially Curved Beams by State Equations

2016 ◽  
Vol 16 (05) ◽  
pp. 1550011 ◽  
Author(s):  
S. R. Kuo ◽  
Judy P. Yang ◽  
Y. B. Yang
Keyword(s):  
Rigid Body ◽  
Buckling Analysis ◽  
The State ◽  
Curved Beams ◽  
State Equations ◽  
State Matrix ◽  
Current Configuration ◽  
Matrix Operations ◽  
Novel Approach ◽  
Force Equilibrium

Based on force equilibrium and rigid body considerations, a novel approach is proposed for deriving the state equations and then the buckling equations of pretwisted spatially curved beams. Based on statical consideration of an infinitesimal element from the last calculated configuration [Formula: see text] to the current configuration [Formula: see text], a set of condition equations for the state matrix is derived. Next, by enforcing the rigid body rule for the beam, another set of condition equations for the state matrix is derived. From these two sets of equations, the state matrix of the beam is derived that leads directly to the buckling differential equations. The merit of the proposed approach is that it only requires simple differential and matrix operations. No hidden errors are possible because no higher-order terms need to be treated. In addition, a direct link is established between the straight and curved beam theories. Finally, examples are provided to demonstrate the application of the theory to the buckling analysis of various curved beams, including the helical ones.

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