Volume 10 | Issue 6 |

 Abstract

This Paper provides an overview of estimation of change points. The paper discusses the statistical inference problem about a change point model: (1) to determine if any change point should exist in the sequence; and (2) estimate the number and position(s) of change point(s), and other qualities of interest which are related to the change (for example, the magnitude of the jump of the mean). Bayesian methods are proposed to study the estimates of change points in the sequence of Burr Type III Distribution under Squared error Loss function(SELF). A simulation study is done by R-programming.

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 Keywords

Change Point Estimation, Burr Type III Distribution. Bayesian method, Natural Conjugate Inverted Gamma Prior, Squared Error Loss Function

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In the context of computer vision, object tracking is a crucial challenge. Image noise, variations in backdrop illumination, dynamic object motion, and partial and complete occlusion of objects all add to the complexity of object tracking. i.e. video of poor quality. Despite the impressive outcomes of deep learning, there has been less emphasis on low-resolution object recognition as compared to high-resolution images. We proposed a framework for reducing model size state-of-the-art single stage detector i.e. YOLOv4 with pruning and Kalman filtering for tracking the low quality video. The framework addresses compression in the following stages: Sparsity Induction, Filter Choice, and Filter Pruning. The detector model for detecting object is sparsified in the Sparsity by using a better global threshold. In the Filter Selection & Pruning stage, we choose and remove filters based on sparsity metrics of filter weights in two subsequent convolutional layers. As a result, the model is smaller than the majority of compact designs available now on the market. We test our framework's performance with a MSCOCO datasets. The model with compressing algorithm with having Kalman filter to produce good quality image representation on the low-quality input image or video feed analysis proposed for the condition. The models size examines for the inferences and the analytical framework for the better represent for the detection stages and evaluation results.

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Single Shot Detector, Filter Pruning, Sparsity, Kalman filter, YOLOv4

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Advance in cybercrime have prompted cybercrime, security issues, intruders and criminals. Virtual Entertainment discussions have acquired a great deal of fame as it is the best and proficient method for imparting and offer data. In excess of a billion clients are associated with online entertainment and an absence of mindfulness about protection and security concerns is prompting an expansion in cybercrime. Digital Crime Investigation is quite possibly the most extensive Data Mining programs and can be utilized to anticipate and identify crime. This advantages the local area and advances a superior life. In this exploration paper, we dissect cybercrime via virtual entertainment utilizing a Data Mining calculation for example Ensemple technique. We thought about calculations in light of the F esteem relating to the precision with the exactness measure utilizing WEKA. Likewise, we have proposed a profoundly practical model and it will actually want to assist us with further developing execution to distinguish the danger and catch the client another way consequently

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Social Media, Cyber Crime Cyber Threats, Ensemple Method

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The main aim of the project is to build a Arduino Uno based safety device for covid-19 safety rules to reduce the disease spread. We focus on most common indoor measurement system to allow the people. This project makes a use of DHT11 temperature sensor to detect the body temperature and camera, open CV to detect the mask whether the person is wearing a mask or not. We introduce an affordable COVID-19 indoor safety system.

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 Keywords

Aurdino Uno , DHT11 Temperature Sensor , LCD Display , Servo Motor , LED/Buzzer , Computer System , Camera , ESP32, Wifi Module

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Here in this writing I am going to discuss, what is virtue and how Moral luck influencing our virtuous life? Luck is everywhere in our life, from the very beginning to till our death we cannot escape from this. To live a good and happy life we need to be virtuous. Men are by birth possesses some special kind of ability and character which somehow can be a great advantage to live a virtuous life, and some times it may be a disadvantage for some people. So here my main focus is to show that, if there any relationship between Luck and Virtuous life. That means as the title saying I going to investigate deeply to perceive if virtue is possible on the basis of Moral Luck? And if so, then how can be it possible?

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Moral Luck, Virtue, Relationship of virtue and Luck.

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 Abstract

Background: The calf muscle complex is an important part of locomotor performance and weight loading. It has been found that due to straining the calf muscles, there is an increased risk of calf muscle injury and related foot symptoms. Since calf muscle plays a key role in the biomechanics of foot, tightness in the calf muscle can unevenly distribute the force of body weight load. Static stretching improves ROM, reduces stiffness and reduces the risk of injury from acute strain. Eccentric contraction is the movement of active muscles during contraction under load. Eccentric training has the effect of increasing flexibility for the lower body, helping to increase muscle length. Aim: To Study the comparative Effect of Static stretching and Eccentric Training on the Flexibility of Calf Muscle in Healthy Individuals. Method. 62 participants were selected based on the selection criteria. Participants were briefed about the nature of the study and the intervention. Their informed written consent was taken Prior and after the treatment the outcome measures, Knee to wall test were measured. Participants were randomly divided into two groups with n=31 in each group. Group A received static stretching while group B received Eccentric training. The treatment was given for 6 consecutive days. Results: According to the finding, Eccentric training (Group B) showed significant difference in post mean value as compared to static stretching (group A). there is a significant statistical reliable difference between the pre & post treatment values with p-value is less than the 5% significance level (i.e., 0.001 < 0.05) in the study and therefore it justifies the improvements in health outcome post intervention. Conclusion: This study concluded that use of Eccentric training is more effective than Static stretching to reduce the calf muscle tightness in healthy individuals.

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Knee to wall test, Static stretching, Eccentric training, Calf muscle tightness.

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 Abstract

Electricity is an essential requirement for humans. It is generally used for domestic, industrial and agricultural purposes. Now a days power theft has become a major problem specifically in India. This causes a considerable loss to electricity boards, so this can be prevented by using Smart Energy Meter (SEM). Theft cases are signaled to local authorities through SMS sent by GSM. The present system of energy billing in India is prone to error and also time and labor consuming. This pre-paid meter converts conventional meter reading methods and enables remote access of existing energy meters from energy suppliers. They can also monitor meter readings on a regular basis without having to visit each home by a person.

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Arduino UNO, GSM module, Relay, Theft detection, Prepaid meter

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Aim To find out impact of video assisted teaching on psychosomatic problems related to problematic internet use among adolescents in selected senior secondary schools. Methodology Methodology: The sample size taken for the study was 480 with selected senior secondary school by non randomized convenient sampling technique. Sample was divided in to two groups; one is experimental and second is control group. The experimental group was treated by video assisted teaching whereas control group was not treated by any intervention. A standard semi structured questionnaire and a rating scale was used to assess the psychosomatic problems related to problematic internet use among adolescents. Data were analyzed with the help of SPSS 16.0 software. Results: In experimental group the mean pre-test problematic internet use score is 55.200 and mean post-test problematic internet use score is 43.366. The estimated paired't value was (1.199), which is significant at p<0.05. This reduction is statistically significant. The mean pre-test Depression related to problematic internet use score is 22.116 and mean post-test Depression related to problematic internet use score is 14.933. The estimated paired't value was (19.505), which is significant at p<0.05. The mean pre-test Anxiety related to problematic internet use score is 20.633and mean post-test Anxiety related to problematic internet use score is 10.766. The estimated paired't value was (18.509), which is significant at p<0.05. The mean pre-test Stress related to problematic internet use score is 20.550 and mean post-test Stress related to problematic internet use score is 15.766. The estimated paired't value was (14.284), which is significant at p<0.05. The mean pre-test Somatic problems related to problematic internet use score is 10.000 and mean post-test Somatic problems related to problematic internet use score is 7.733. The estimated paired't value was (12.632), which is significant at p<0.05 in experimental group. In control group the mean pre-test problematic internet use score is 52.425and mean post-test problematic internet use score is 55.383. The estimated paired't value was (1.882), which is not significant at p<0.05. But we can see that in experimental group the reduction is of 11.834 points which is higher than the reduction score (-2.958) of control group . The mean pre-test Depression related to problematic internet use score is 21.716 and mean post-test Depression related to problematic internet use score is 21.100. The estimated paired't value was (4.428), which is significant at p<0.05. The mean pre-test Anxiety related to problematic internet use score is 20.350 and mean post-test Anxiety related to problematic internet use score is 19.400. The estimated paired't value was (4.558), which is significant at p<0.05. The mean pre-test Stress related to problematic internet use score is 20.566and mean post-test Stress related to problematic internet use score is 20.166. The estimated paired't value was (4.478), which is significant at p<0.05. The mean pre-test Somatic problems related to problematic internet use score is 10.066 and mean post-test Somatic problems related to problematic internet use score is 9.683. The estimated paired't value was (4.834), which is significant at p<0.05 in control group. Conclusion: It is concluded that adolescents with psychosomatic problems related to problematic internet use show better improvement in their level of psychosomatic problems related to problematic internet use after administration of video assisted teaching compare to non administration of any intervention.

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 Keywords

Impact, video assisted teaching. Psychosomatic problems, problematic internet use etc.

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Creative Commons Attribution 4.0 and The Open Definition

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TEACHER PARENT RELATION MAPNI KA NIRMAN EVM MANKIKARAN

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Data technology has additionally converted the manner college students engage with instructors and compare their overall performance. Teachers can use statistics to investigate the comments they get from college students and use it to enhance their own Teaching. Data technology may be used to create predictive fashions that could expect pupil dropout rates. Primarily based totally on their overall performance and tell the teachers to take the important precautions. For schools, IBM Analytics has developed a project to evaluate students' performance depending on their performance. Universities are using data to avoid retention to supplement the performance of their students. The University of Florida, for example, uses IBM Cognos Analytics to monitor student progress and make appropriate projections. MOOCs and online education platforms also use data science to track recipients, automate assignment scoring, and improve courses based on student feedback.

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Data technology, Statistics, IBM Analytics, data science, MOOCs, automate assignment scoring.

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Creative Commons Attribution 4.0 and The Open Definition