scholarly journals Estimativa da produção de sedimentos utilizando a curva-chave de sedimentos

2021 ◽  
Vol 43 ◽  
pp. e17
Author(s):  
Danrlei Menezes ◽  
Francisco Fernando Noronha Marcuzzo ◽  
Marcia Conceição Rodrigues Pedrollo
Keyword(s):  
Sediment Transport ◽  
Sediment Yield ◽  
Data Set ◽  
Data Comparison ◽  
Erosion Processes ◽  
Single Section ◽  
Relative Standard ◽  
Excel Solver ◽  
The One ◽  
Comparison Of The Results

Quantification of sediment yield is important in determining the impacts of erosion processes on the watersheds. One way to determine their values is through the construction of the sediment-transport curve. The objective of this work is to calculate the sediment yield and to analyze the time variation in a hydrosedimentological monitoring station by designing and adjusting the sediment-transport curve, testing the deviations for curve fitting with a single section and divided into two sections. The 87380000 station is located in the municipality of Campo Bom (RS), operated by CPRM. The sediment-transport curve was built in a single section and divided into two sections. In addition, the Excel solver was used to set the curve to the data. Comparison of the relative standard deviation calculated for each curve allowed a comparison of the results. The sediment-transport curve. that best represented the data set was the one constructed with the split in two sections adjusted by the solver.

LAVSED-II—A model for predicting suspended load in northern streams

1986 ◽  
Vol 13 (2) ◽  
pp. 162-170 ◽  
Author(s):  
P. Y. Julien ◽  
M. Frenette
Keyword(s):  
Sediment Transport ◽  
Soil Erosion ◽  
Sediment Yield ◽  
Meteorological Data ◽  
Suspended Load ◽  
Climatic Parameters ◽  
Physical Processes ◽  
Empirical Relationships ◽  
Erosion Processes ◽  
St Lawrence River

The model LAVSED-II (LAVal SEDimentological model number II) has been developed to evaluate the suspended load in northern streams that results from rainfall and snowmelt erosion on upslope areas. The most important parameters are (1) the physical characteristics involved in soil erosion processes and (2) the climatic parameters on a month-to-month basis. Two fundamental relationships are obtained from the governing physical processes and empirical relationships describing snowmelt and sediment transport. The model has been applied to four large watersheds, tributaries of the St. Lawrence River. The computed sediment yield compares very well with the measured suspended load (mostly wash load) in the rivers. The magnitude of the peak during spring is particularly well predicted. The computed sediment yield is shown to be very sensitive to meteorological data. In the case of ungaged watersheds, the model can be applied to estimate the sediment yield.

scholarly journals Modeling of solid sediment transport in mountain rivers

2020 ◽  
Vol 175 ◽  
pp. 12002 ◽  
Author(s):  
Issam Boukhanef ◽  
Anna Khadzhidi ◽  
Lyudmila Kravchenko ◽  
Zeroual Ayoub ◽  
Kastali Abdennour
Keyword(s):  
Sediment Transport ◽  
Fine Particles ◽  
Agricultural Soils ◽  
Suspended Sediments ◽  
High Water ◽  
The Other ◽  
Concentration Data ◽  
Solid Transport ◽  
One Year ◽  
The One

In Algeria, the problems of erosion and sediment transport are critical, since they have the most dramatic consequences of the degradation of agricultural soils on the one hand and the siltation of the dam on the other .The sediment transport in the Algerian basins is very important especially during the periods of floods, It is in this sense that this study, which consists of estimating the sediment transport in suspension and determining the models of relation linking the liquid discharge and the sediment discharge in order to estimate the solid transport in the absence of suspended sediments concentration data at the Sidi Akkacha station at the outlet of the basin of Oued Allala which is subject to a high water erosion, it degrades from one year to the other under the effect of this phenomenon especially during the floods which drain high amounts of fine particles exceeding in general, the concentration of 150 g/l, the results obtained from the application of the models are very encouraging since the correlation between liquid and solid discharge exceeds 80 %.

Intuitionistic fuzzy two-factor variance analysis of movie ticket sales

2021 ◽  
pp. 1-11
Author(s):  
Velichka Traneva ◽  
Stoyan Tranev
Keyword(s):  
Comparative Analysis ◽  
Real Data ◽  
Intuitionistic Fuzzy Sets ◽  
Real Numbers ◽  
Data Set ◽  
Important Method ◽  
Ticket Sales ◽  
Intuitionistic Fuzzy ◽  
The One ◽  
First Time

Analysis of variance (ANOVA) is an important method in data analysis, which was developed by Fisher. There are situations when there is impreciseness in data In order to analyze such data, the aim of this paper is to introduce for the first time an intuitionistic fuzzy two-factor ANOVA (2-D IFANOVA) without replication as an extension of the classical ANOVA and the one-way IFANOVA for a case where the data are intuitionistic fuzzy rather than real numbers. The proposed approach employs the apparatus of intuitionistic fuzzy sets (IFSs) and index matrices (IMs). The paper also analyzes a unique set of data on daily ticket sales for a year in a multiplex of Cinema City Bulgaria, part of Cineworld PLC Group, applying the two-factor ANOVA and the proposed 2-D IFANOVA to study the influence of “ season ” and “ ticket price ” factors. A comparative analysis of the results, obtained after the application of ANOVA and 2-D IFANOVA over the real data set, is also presented.

scholarly journals Extreme geomagnetic activities: a statistical study

2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Ryuho Kataoka
Keyword(s):  
Magnetic Storms ◽  
Magnetic Observatory ◽  
Statistical Distributions ◽  
Limited Data ◽  
Data Set ◽  
Sudden Commencements ◽  
The One ◽  
Log Normal ◽  
Geomagnetic Activities ◽  
Log Normal Distribution

Abstract Statistical distributions are investigated for magnetic storms, sudden commencements (SCs), and substorms to identify the possible amplitude of the one in 100-year and 1000-year events from a limited data set of less than 100 years. The lists of magnetic storms and SCs are provided from Kakioka Magnetic Observatory, while the lists of substorms are obtained from SuperMAG. It is found that majorities of events essentially follow the log-normal distribution, as expected from the random output from a complex system. However, it is uncertain that large-amplitude events follow the same log-normal distributions, and rather follow the power-law distributions. Based on the statistical distributions, the probable amplitudes of the 100-year (1000-year) events can be estimated for magnetic storms, SCs, and substorms as approximately 750 nT (1100 nT), 230 nT (450 nT), and 5000 nT (6200 nT), respectively. The possible origin to cause the statistical distributions is also discussed, consulting the other space weather phenomena such as solar flares, coronal mass ejections, and solar energetic particles.

scholarly journals Farm Gate Prices for Non-Varietal Wine in Argentina: A Multilevel Comparison of the Prices Paid by Cooperatives and Investor-Oriented Firms

2017 ◽  
Vol 16 (1) ◽  
Author(s):  
Agustina Malvido Perez Carletti ◽  
Markus Hanisch ◽  
Jens Rommel ◽  
Murray Fulton
Keyword(s):  
Multilevel Regression ◽  
Data Set ◽  
Unique Data ◽  
Market Shares ◽  
Price Effects ◽  
Theoretical Predictions ◽  
The One ◽  
The Cost ◽  
Price Differences ◽  
Multilevel Regression Model

AbstractIn this paper, we use a unique data set of the prices paid to farmers in Argentina for grapes to examine the prices paid by non-varietal wine processing cooperatives and investor-oriented firms (IOFs). Motivated by contrasting theoretical predictions of cooperative price effects generated by the yardstick of competition and property rights theories, we apply a multilevel regression model to identify price differences at the transaction level and the departmental level. On average, farmers selling to cooperatives receive a 3.4 % lower price than farmers selling to IOFs. However, we find cooperatives pay approximately 2.4 % more in departments where cooperatives have larger market shares. We suggest that the inability of cooperatives to pay a price equal to or greater than the one paid by IOFs can be explained by the market structure for non-varietal wine in Argentina. Specifically, there is evidence that cooperative members differ from other farmers in terms of size, assets and the cost of accessing the market. We conclude that the analysis of cooperative pricing cannot solely focus on the price differential between cooperatives and IOFs, but instead must consider other factors that are important to the members.

scholarly journals Improving MUSLE performance for sediment yield prediction at micro-watershed level using seasonal classified data

2018 ◽  
Vol 13 (3) ◽  
pp. 505-512
Author(s):  
Hamzeh Noor ◽  
Mohammad Rostami Khalaj
Keyword(s):  
Sediment Yield ◽  
Traditional Approach ◽  
Estimation Error ◽  
Superior Performance ◽  
North East ◽  
Erosion Processes ◽  
The North ◽  
East Of Iran ◽  
Different Seasons

Abstract Separating erosion data and assessing season-based models are of great importance considering the variation in soil erosion processes in different seasons, especially in semi-arid regions. However, evaluation of an erosion model using seasonal classification of data and at a micro-watershed level have rarely been considered. Therefore, the present study was conducted to evaluate the modified universal soil loss equation (MUSLE): 1) with the seasonal classification of data and 2) with the traditional approach (no classification of data), in the Sanganeh research micro-watershed. This watershed has an area of 1.2 ha and is located in the north east of Iran. The results showed that the original MUSLE overestimated the sediment yield in the study watershed. Also, after calibration of MUSLE, the seasonal classification of data (with a relative estimation error (RE) of 34%) showed its superior performance compared with the traditional calibration approach (with a RE of 62%). In this regard, the obtained REs of 33, 40, and 31% respectively for spring, autumn, and winter are within or close to the acceptable range.

How Price Dispersion Changes When Upgrades Are Introduced: Theory and Empirical Evidence from the Airline Industry

2019 ◽  
Vol 65 (8) ◽  
pp. 3835-3852 ◽  
Author(s):  
Yao Cui ◽  
A. Yeşim Orhun ◽  
Izak Duenyas
Keyword(s):  
Operations Management ◽  
Airline Industry ◽  
Price Dispersion ◽  
Consumer Welfare ◽  
Data Set ◽  
Differentiation Strategy ◽  
Valuation Effect ◽  
Price Distribution ◽  
The One ◽  
The Impact

This paper studies the effect of introducing a new vertical differentiation strategy, paying for an upgrade to a premium product after purchasing the base product, on the price dispersion of the base product arising from existing price discrimination strategies. In particular, we examine how a major U.S. airline’s price dispersion in the coach cabin changes after introducing the option to upgrade to a new type of premium economy seating within the coach cabin. We first provide a theoretical analysis that highlights two competing pressures that the new premium economy seating upgrades created on coach class prices. On the one hand, the airline benefits from lowering its prices because by allowing more customers to purchase in the first place, it increases the probability of selling upgrades (admission effect). On the other hand, for some customers, the value of flying with the airline increases because of the upgrade availability, therefore the airline may find it optimal to increase its prices (valuation effect). In the second part of the paper, we conduct an empirical investigation of the impact of upgrade introduction on coach class prices, based on a proprietary transaction-level data set from a major U.S. airline company. The empirical analysis tests the main predictions of our theoretical model and examines further nuances. The results show that the introduction of the premium economy seating upgrades is associated with an increase in the price dispersion and revenues in the coach class, the admission effect is stronger than the valuation effect on the low end of the price distribution, and the opposite is true on the high end of the price distribution. Finally, we discuss implications of our results for firm revenues and consumer welfare. This paper was accepted by Serguei Netessine, operations management.

scholarly journals There Is No Logical Negation Here, But There Are Alternatives: Modeling Conversational Negation with Distributional Semantics

2016 ◽  
Vol 42 (4) ◽  
pp. 637-660 ◽  
Author(s):  
Germán Kruszewski ◽  
Denis Paperno ◽  
Raffaella Bernardi ◽  
Marco Baroni
Keyword(s):  
Large Data ◽  
Semantic Space ◽  
The Other ◽  
Similarity Function ◽  
Distributional Semantics ◽  
Application Domain ◽  
Data Set ◽  
Logical Negation ◽  
The One ◽  
The Right

Logical negation is a challenge for distributional semantics, because predicates and their negations tend to occur in very similar contexts, and consequently their distributional vectors are very similar. Indeed, it is not even clear what properties a “negated” distributional vector should possess. However, when linguistic negation is considered in its actual discourse usage, it often performs a role that is quite different from straightforward logical negation. If someone states, in the middle of a conversation, that “This is not a dog,” the negation strongly suggests a restricted set of alternative predicates that might hold true of the object being talked about. In particular, other canids and middle-sized mammals are plausible alternatives, birds are less likely, skyscrapers and other large buildings virtually impossible. Conversational negation acts like a graded similarity function, of the sort that distributional semantics might be good at capturing. In this article, we introduce a large data set of alternative plausibility ratings for conversationally negated nominal predicates, and we show that simple similarity in distributional semantic space provides an excellent fit to subject data. On the one hand, this fills a gap in the literature on conversational negation, proposing distributional semantics as the right tool to make explicit predictions about potential alternatives of negated predicates. On the other hand, the results suggest that negation, when addressed from a broader pragmatic perspective, far from being a nuisance, is an ideal application domain for distributional semantic methods.

scholarly journals Key Parts of Transmission Line Detection Using Improved YOLO v3

2021 ◽  
Vol 18 (6) ◽  
Author(s):  
Tu Renwei ◽  
Zhu Zhongjie ◽  
Bai Yongqiang ◽  
Gao Ming ◽  
Ge Zhifeng
Keyword(s):  
Transmission Line ◽  
Detection Accuracy ◽  
Data Sets ◽  
Feature Maps ◽  
Data Set ◽  
Detection Model ◽  
The Neural Network ◽  
Low Efficiency ◽  
The One ◽  
Detection Speed

Unmanned Aerial Vehicle (UAV) inspection has become one of main methods for current transmission line inspection, but there are still some shortcomings such as slow detection speed, low efficiency, and inability for low light environment. To address these issues, this paper proposes a deep learning detection model based on You Only Look Once (YOLO) v3. On the one hand, the neural network structure is simplified, that is the three feature maps of YOLO v3 are pruned into two to meet specific detection requirements. Meanwhile, the K-means++ clustering method is used to calculate the anchor value of the data set to improve the detection accuracy. On the other hand, 1000 sets of power tower and insulator data sets are collected, which are inverted and scaled to expand the data set, and are fully optimized by adding different illumination and viewing angles. The experimental results show that this model using improved YOLO v3 can effectively improve the detection accuracy by 6.0%, flops by 8.4%, and the detection speed by about 6.0%.

scholarly journals A Dense Long Short-Term Memory Model for Enhancing the Imagery-Based Brain-Computer Interface

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xiaofei Zhang ◽  
Tao Wang ◽  
Qi Xiong ◽  
Yina Guo
Keyword(s):  
Short Term Memory ◽  
Recognition Algorithm ◽  
Training Process ◽  
Short Term ◽  
Data Set ◽  
Static State ◽  
Term Memory ◽  
Long Short Term Memory ◽  
Model Training ◽  
The One

Imagery-based brain-computer interfaces (BCIs) aim to decode different neural activities into control signals by identifying and classifying various natural commands from electroencephalogram (EEG) patterns and then control corresponding equipment. However, several traditional BCI recognition algorithms have the “one person, one model” issue, where the convergence of the recognition model’s training process is complicated. In this study, a new BCI model with a Dense long short-term memory (Dense-LSTM) algorithm is proposed, which combines the event-related desynchronization (ERD) and the event-related synchronization (ERS) of the imagery-based BCI; model training and testing were conducted with its own data set. Furthermore, a new experimental platform was built to decode the neural activity of different subjects in a static state. Experimental evaluation of the proposed recognition algorithm presents an accuracy of 91.56%, which resolves the “one person one model” issue along with the difficulty of convergence in the training process.

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