scholarly journals Task Price Prediction Based on Clustering and DNN in Crowdsensing

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Bing Jia ◽  
Xi Luo ◽  
Tao Feng ◽  
Yan Jia
Keyword(s):  
Prediction Models ◽  
Prediction Method ◽  
Pricing Mechanism ◽  
Price Prediction ◽  
Taxonomic Description ◽  
Pricing Rules ◽  
Constraint Relation ◽  
Data Source ◽  
The Common ◽  
Common Problems

With the popularization of mobile devices and the development of wireless networks, crowdsensing is devoted to providing universal Internet of Things services. A reasonable task pricing mechanism can not only motivate more users to participate in the sensing task but also help the benign development of crowdsensing platform, so it has gradually become a research hotspot in the field of crowdsensing. Aiming at the common problems of insufficient analysis of task pricing rules and large deviations of pricing prediction models, a task price prediction method based on clustering and DNN is proposed. Using the real historical trade price set as the data source, natural grouping and taxonomic description of task price are realized by exploring sensing task pricing law with complex constraint relation using two-step clustering analysis. On the basis of the above, the price interval prediction model based on DNN is implemented. The experimental results show that the predicting accuracy of the pricing mechanism is higher than 82.7%.

Applying Possessive pronoun in Writing Sentences: Exploring Students’ Ability and Problems in a Mixed Method Study

2019 ◽  
Vol 1 (3) ◽  
pp. 79-83
Author(s):  
Eka Utami Putri ◽  
Syahdan Syahdan
Keyword(s):  
Mixed Method ◽  
Simple Random Sampling ◽  
Average Score ◽  
Mixed Method Study ◽  
Z Score ◽  
Possessive Pronoun ◽  
Efl Students ◽  
The Common ◽  
Common Problems ◽  
Essay Test

The purpose of this research was to find out the students' ability in applying Possessive pronoun in writing sentences and the problems encounter it.  This mixed method study employs an explanatory design to reveals it. 53 students out of 105 students from1st semester EFL students from one reputable University in Pekanbaru, Indonesia, were invited to this study. These 53 students were selected using simple random sampling and enrolled for an essay test and interview to see the students' ability and explaining the problems. The data analysis using SPSS showed that the average score of students was 52.98. Meanwhile for the median is 48, the mode is 20. The score of Standard Deviation is 27.93, Variance is 780.25, and Range is 84.  Z-Score was found 41.5%, which is means higher than average and 58.5% while, students' ability was indicated below the average. It showed that the students were low ability in applying possessive pronoun in writing sentences. The study also found the common problems, i.e., (1) students still mixed up between possessive pronoun and possessive adjectives. (2) students used the wrong pattern in using a possessive pronoun. (3) students did not understand clearly about a possessive pronoun, (4) experiencing difficulties in learning possessive pronoun. 

A Historical Data based Ensemble System for Efficient Stock Price Prediction

2019 ◽  
Vol 12 ◽  
Author(s):  
Vijay Kumar Dwivedi ◽  
Manoj Madhava Gore
Keyword(s):  
Stock Price ◽  
Prediction Models ◽  
Historical Data ◽  
Stock Exchange ◽  
Primary Objective ◽  
Lasso Regression ◽  
Stock Price Prediction ◽  
Price Prediction ◽  
Consistent Manner ◽  
Selection Operator

Background: Stock price prediction is a challenging task. The social, economic, political, and various other factors cause frequent abrupt changes in the stock price. This article proposes a historical data-based ensemble system to predict the closing stock price with higher accuracy and consistency over the existing stock price prediction systems. Objective: The primary objective of this article is to predict the closing price of a stock for the next trading in more accurate and consistent manner over the existing methods employed for the stock price prediction. Method: The proposed system combines various machine learning-based prediction models employing least absolute shrinkage and selection operator (LASSO) regression regularization technique to enhance the accuracy of stock price prediction system as compared to any one of the base prediction models. Results: The analysis of results for all the eleven stocks (listed under Information Technology sector on the Bombay Stock Exchange, India) reveals that the proposed system performs best (on all defined metrics of the proposed system) for training datasets and test datasets comprising of all the stocks considered in the proposed system. Conclusion: The proposed ensemble model consistently predicts stock price with a high degree of accuracy over the existing methods used for the prediction.

scholarly journals Study of Price Determinants of Sharing Economy-Based Accommodation Services: Evidence from Airbnb.com

2020 ◽  
Vol 16 (4) ◽  
pp. 584-601
Author(s):  
Chunwei Chang ◽  
Shengli Li
Keyword(s):  
Prediction Models ◽  
Interaction Effects ◽  
Sharing Economy ◽  
Tourist Attractions ◽  
Price Prediction ◽  
Price Determinants

This research aims to identify price determinants for sharing economy-based accommodation services and to further use the identified price determinants to predict accommodation prices. A dataset drawn from Airbnb.com, was collected for analysis. We identify price determinants from five categories. The top five price determinants are identified as room type, city, distance to tourist attractions, number of pictures posted, and number of amenities provided. More importantly, we find that interaction effects between variables can also significantly influence price. Finally, a series of price prediction models are built based on the identified price determinants.

scholarly journals Re-entry prediction of objects with low-eccentricity orbits based on mean ballistic coefficients

2020 ◽  
Vol 29 (1) ◽  
pp. 210-219
Author(s):  
Zhang Wei ◽  
Cui Wen ◽  
Wang Xiuhong ◽  
Wei Dong ◽  
Liu Xing
Keyword(s):  
Orbit Determination ◽  
Prediction Method ◽  
Atmospheric Drag ◽  
Average Effect ◽  
Step Size ◽  
Orbit Propagation ◽  
Ballistic Coefficient ◽  
Orbital Revolution ◽  
Data Source ◽  
The Mean

AbstractDuring re-entry objects with low-eccentricity orbits traverse a large portion of the dense atmospheric region almost every orbital revolution. Their perigee decays slowly, but the apogee decays rapidly. Because ballistic coefficients change with altitude, re-entry predictions of objects in low-eccentricity orbits are more difficult than objects in nearly circular orbits. Problems in orbit determination, such as large residuals and non-convergence, arise for this class of objects, especially in the case of sparse observations. In addition, it might be difficult to select suitable initial ballistic coefficient for re-entry prediction. We present a new re-entry prediction method based on mean ballistic coefficients for objects with low-eccentricity orbits. The mean ballistic coefficient reflects the average effect of atmospheric drag during one orbital revolution, and the coefficient is estimated using a semi-numerical method with a step size of one period. The method is tested using Iridium-52 which uses sparse observations as the data source, and ten other objects with low-eccentricity orbits which use TLEs as the data source. We also discuss the performance of the mean ballistic coefficient when used in the evolution of drag characteristics and orbit propagation. The results show that the mean ballistic coefficient is ideal for re-entry prediction and orbit propagation of objects with low-eccentricity orbits.

scholarly journals Common issues in the hetero-epitaxial seeding on SiC substrates in the sublimation growth of AlN crystals

2021 ◽  
Vol 127 (8) ◽  
Author(s):  
R. Radhakrishnan Sumathi
Keyword(s):  
Power Electronic ◽  
Etch Pit ◽  
Micro Hole ◽  
Wet Chemical ◽  
The Common ◽  
Common Problems ◽  
Hole Defects ◽  
Sublimation Growth ◽  
Impurity Elements ◽  
Very High

AbstractAluminium nitride (AlN) is a futuristic material for efficient next-generation high-power electronic and optoelectronic applications. Sublimation growth of AlN single crystals with hetero-epitaxial approach using silicon carbide substrates is one of the two prominent approaches emerged, since the pioneering crystal growth work from 1970s. Many groups working on this hetero-epitaxial seeding have abandoned AlN growth altogether due to lot of persistently encountered problems. In this article, we focus on most of the common problems encountered in this process such as macro- and micro-hole defects, cracks, 3D-nucleation, high dislocation density, and incorporation of unintentional impurity elements due to chemical decomposition of the substrate at very high temperatures. Possible ways to successfully solve some of these issues have been discussed. Other few remaining challenges, namely low-angle grain boundaries and deep UV optical absorption, are also presented in the later part of this work. Particular attention has been devoted in this work on the coloration of the crystals with respect to chemical composition. Wet chemical etching gives etch pit density (EPD) values in the order of 105 cm-2 for yellow-coloured samples, while greenish coloration deteriorates the structural properties with EPD values of at least one order more.

Variations of Cystic Duct and Its Clinical Significance

2021 ◽  
Vol 9 (4) ◽  
pp. 8120-8126
Author(s):  
K. Sangameswaran ◽  
Keyword(s):  
Bile Duct ◽  
Cystic Duct ◽  
Gallstone Disease ◽  
Cystic Artery ◽  
Normal Anatomy ◽  
Biliary Anatomy ◽  
Medical College ◽  
Gallbladder Surgery ◽  
The Common ◽  
Common Problems

Background: Cystic duct drains the bile from the gallbladder into the common bile duct. Gallstone disease is one of the most common problems affecting the digestive tract and may lead to many complications. To avoid the complications in these patients the gallbladder is removed surgically (Cholecystectomy). Ligation of cystic duct and cystic artery is a prerequisite procedure when cholecystectomy is done. Understanding about the normal anatomy & the possible variations in biliary ductal system is important for the surgeons for doing cholecystectomy surgery successfully. Errors during gallbladder surgery commonly result from failure to appreciate the common variations in the anatomy of the biliary system. Aim of the study: To find out the incidence of variations in the length, course, and termination of cystic duct in cadavers. Materials and Methods: Present study was done in 50 adult cadavers in the Department of Anatomy, Government Tiruvannamalai medical college, Tamilnadu. Meticulous dissection was done in the hepatobiliary system of these cadavers. Observations: During the study variations in the length of cystic duct, course and different modes of insertion of cystic duct were observed. Conclusion: Knowledge of variations in the length of cystic duct and knowing about different modes of course & insertion of cystic duct is necessary for surgeons while conducting cholecystectomy. The risk of iatrogenic injury is especially high in cases where the biliary anatomy is misidentified prior to surgery. KEY WORDS: Cystic duct, Gallbladder, Cholecystectomy.

The Management of Rescued Shipwreck Survivors

1980 ◽  
Vol 66 (2) ◽  
pp. 107-113
Author(s):  
F. St. C. Golden
Keyword(s):  
Medical Officer ◽  
The Common ◽  
Common Problems

AbstractA ship’s medical officer may be called upon at any time to attend to casualties from a shipwreck. This paper outlines some of the common problems which may be encountered in such a situation and gives advice on a possible course of procedure.

scholarly journals An Analysis of the Questionnaire Investigation on Tourists’ Behavior

2017 ◽  
Vol 6 (4) ◽  
pp. 16
Author(s):  
Akane Okubo ◽  
Kazuhiro Takeyasu
Keyword(s):  
Local Government ◽  
Hypothesis Testing ◽  
Regional Cooperation ◽  
Economic Aspects ◽  
Local Society ◽  
Tourist Behavior ◽  
Regional Collaboration ◽  
The Common ◽  
Common Problems ◽  
And Migration

Tourists from abroad are increasing rapidly in Japan. Particular aims of local government are to overcome the common problems of an aging population and declining birthrate through tourism-generated income and to stimulate the local society through regional exchange and migration. In order to analyze economic aspects of tourism, accurate and up-to-date statistics and information regarding tourism are needed. Specifically, this study presents opportunities for inter-regional cooperation in marketing, in light of studies of tourist behavior at events featuring seasonal flowers and held in Kawazu town, which is located on the Izu Peninsula in Shizuoka Prefecture. In this paper, a questionnaire investigation is executed in order to clarify tourists’ behavior, and to seek the possibility of developing regional collaboration among local government, tourism related industry and visitors. Hypothesis testing was executed based on that. Some interesting and instructive results were obtained.

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