Using SVM with Financial Statement Analysis for Prediction of Stocks

At present, there are many technical analyses for prediction in stock market. However, the technical indices are fluctuated with the quantity of stock exchanges. The financial indices are more reliable, nonvolatile and valid compared with the technical indices. In this paper, we propose an original and universal method by using SVM with financial statement analysis for prediction of stocks. We applied the SVM to construct the prediction model and select Gaussian radial basis function (RBF) as the kernel function. The experimental results show our method not only improve the accuracy rate, but also meet the different stockholders’ expectations

Consumer Behavior based on APP use for Food and Beverage Consumption

McDonalds is one of the brands that release the APP on the Smartphone, the APP is called McDonalds McDelivery APP. It suitable for the way of today’s society way of life, where people are busy and don’t want to line and queue in store to buy foods and beverages for too long. People have a freedom to choose and to order through their Smartphone. The mobile APP offers the advantages, it is easy to operate, easy to use, and doesn’t spend a lot of money. In order to understand the consumers behaviour of using APP, this study conduct the descriptive statistical analysis, variance analysis and regression analysis to detect technology acceptance model for perceived usefulness, ease of use, behaviour intention and actual of use. This study conduct the questionnaire through online google forms and obtained 109 valid questionnaires for analysis. We finds that there was no significant effect on degree of the users, and frequencies of using internet. Perceived usefulness and ease of use of behavioural intentions, behavioural intentions and actual of use had significantly difference

Integrating Real-Time Weather Forecasts Data Using OpenWeatherMap and Twitter

Weather forecasts are made by collecting as much data as possible about the current state of the atmosphere (particularly the temperature, humidity, and wind) and using an understanding of atmospheric processes (through meteorology) to determine how the atmosphere evolves in the future. There are several reasons why weather forecasts are important. It forewarns the people about future weather conditions so that people can plan their activities accordingly. It warns people about the impending severe weather conditions and other weather hazards such as thunderstorms, hurricanes, and heavy rainfalls. Thus far, accurate weather predictions have been able to save the lives of many. At its core, Twitter is a real-time public broadcast channel. These characteristics make Twitter a natural platform for public safety communication and early-warning systems.  Furthermore, Twitter became an essential source for up-to-date meteorological data and agency announcements. OpenWeatherMap processes all data in a way that it attempts to provide accurate online weather forecast data and weather maps, such as those for clouds and preciptations Besides, we will use Phyton programming language to get real-time weather data from OpenWeatherMap and post the information to our social media Twitter. Finally, OAuth and Tweepy are a very powerful library that enables the Python code to communicate with Twitter. Tweets about the weather could prove useful to anybody wanting to use it. &nbsp

An Image Retrieval System Based on the Color Complexity of Images

The fuzzy color histogram (FCH) spreads each pixel's total membership value to all histogram bins based on their color similarity. The FCH is insensitive to quantization errors. However, the FCH can state only the global properties of an image rather than the local properties. For example, it cannot depict the color complexity of an image. To characterize the color complexity of an image, this paper presents two image features -- the color variances among adjacent segments (CVAAS) and the color variances of the pixels within an identical segment (CVPWIS). Both features can explain not only the color complexity but also the principal pixel colors of an image. Experimental results show that the CVAAS and CVPWIS based image retrieval systems can provide a high accuracy rate for finding out the database images that satisfy the users' requirement. Moreover, both systems can also resist the scale variances of images as well as the shift and rotation variances of segments in images

Stochastic Optimization: Theory and Applications

As an important branch of applied mathematics, optimization theory, especially stochastic optimization, becomes an important tool for solving multiobjective decision-making problems in random process recently. Many kinds of industrial, biological, engineering, and economic problems can be viewed as stochastic systems, for example, area of communication, gene, signal processing, geography, civil engineering, aerospace, banking, and so forth. Stochastic optimization is suitable to solve the decision-making problems in these stochastic systems

Various generative adversarial networks model for synthetic prohibitory sign image generation

A synthetic image is a critical issue for computer vision. Traffic sign images synthesized from standard models are commonly used to build computer recognition algorithms for acquiring more knowledge on various and low-cost research issues. Convolutional Neural Network (CNN) achieves excellent detection and recognition of traffic signs with sufficient annotated training data. The consistency of the entire vision system is dependent on neural networks. However, locating traffic sign datasets from most countries in the world is complicated. This work uses various generative adversarial networks (GAN) models to construct intricate images, such as Least Squares Generative Adversarial Networks (LSGAN), Deep Convolutional Generative Adversarial Networks (DCGAN), and Wasserstein Generative Adversarial Networks (WGAN). This paper also discusses, in particular, the quality of the images produced by various GANs with different parameters. For processing, we use a picture with a specific number and scale. The Structural Similarity Index (SSIM) and Mean Squared Error (MSE) will be used to measure image consistency. Between the generated image and the corresponding real image, the SSIM values will be compared. As a result, the images display a strong similarity to the real image when using more training images. LSGAN outperformed other GAN models in the experiment with maximum SSIM values achieved using 200 images as inputs, 2000 epochs, and size 32 × 32

SHORT COMMUNICATION: COVID-19 Pandemic and Attitude of Citizens in Bandung City Indonesia (Case Study in Cibiru Subdistrict)

In the beginning, the pandemic panicked the people of Cibiru. Over time, the case fell in line with the increasing number of patients recovering. In addition, different views between elements of government make people surrender and believe in the power of nature's creator. Under these conditions, the researchers were interested in learning more. The study was conducted using a descriptive analysis of a number of parties regarding economic and social activities. The results show that there are three important components: First, trust builds the creator and reduces to the government component, communication that a number of parties do not work consistently when responding to COVID-19, and enforcement of unclear rules. In a nutshell. The citizens, grouped into two groups, agree that a pandemic is dangerous and urge them to follow values in the form of existing rules. Also,The pandemic communication competes in a short time and therefore cannot be carried out interactively.The government’s assertiveness of forcing residents to be at home becomes difficult as compensation can be granted for lost opportunities to seek family income Lastly, due to the preparation of the strategy that precedes the arrival of a pandemic, it cannot be face wisely

Social Vulnerability and How It Matters: A Bibliometric Analysis

Interdisciplinary and cross-cultural studies of the impacts of environment and social vulnerability must be undertaken to address the problem of social vulnerability in the foreseeable future. Scientist or social scientists should first continuously strive towards approaches can integrate municipal technological expertise, experiences, knowledge, perceptions, and expectations into emergency circumstances, so that people can be sharper on issues and offer responses with their matters. In this paper. We performing the Bibliometric Analysis to review published papers on the keyword 'Social Vulnerability'. There are 29,468 papers published in the last 52 years from 1969 to November 2020. Disaster research by implementing the Internet of Things (IoT), data mining, machine learning is still needed