After doing research in IoT related areas, we start our experiment by fulfilling the following functions. We use two TI sensor tags to configure the WSN. The two Raspberry Pi are used as the router and gateway respectively. Signals can be obtained from the two tags, and transferred to router by Bluetooth connection, then forward to gateway with AD-Hoc network. At last, the topics will be transferred to the broker onto the cloud. Signals will be published from gateway to the broker. At the same time, signals can be shown on the dashboard.
0. Aim of this…
After introducing the basic knowledge and cutting-edge technology for IoT, we propose our design idea about developing Internet of Things system over the AWS Cloud, and show our experiment result. Then we analyse some important technologies and show our code at the Conclusion part. Generally speaking, we fulfil the process from publish to subscribe by defining rules and applying security and identification technologies. Lastly, dashboard is being used to display.
A research proposal practice based on
We use GARCH-MIDAS model to estimate the Bitcoin volatility. Financial factors, macro-economic measurement as well as Bitcoin specific variables are considered to be the potential drivers of Bitcoin volatility. Most of the previous studies emphasize the dependency on other assets for the short-term, while this study uses GARCH-MIDAS model which can divide up the volatility components into short-term and long-term. If the highly relevant measurements from financial area and macro-economic field are extracted, the research on Bitcoin volatility can be dependent on the more mature assets, such as products in stock and option market or commodities such as gold and copper. …
A research proposal practice based on H. Jang and L. Jaewook’s paper.
Since its invention, Bitcoin has gained amazing popularity and much attention in various research fields, including computer science, economics and cryptography. With the emergence of the Blockchain technology, the innovative ledger technology underpinning Bitcoin. This study employs Bayesian neural networks (BNN) to model and predict the short-term Bitcoin prices. Some most relevant factors like Blockchain information, macroeconomic factors and foreign exchange rates are selected as input features to improve the forecasting accuracy of proposed model. A comparative analysis is also planned to evaluate the prediction performance between BNN and other two linear and non-linear benchmark methods. …
Support Vector Machines(SVM) and Artificial Neural Networks(ANN) are among the most popular methods applied in various kind of pattern recognition. It is never an easy task for a machine to recognize letters, numbers, figures like humans being. Character recognition has become a challenging and fascinating topic in the field of image processing and machine learning. In this paper, we propose to recognize handwritten character by feedforward neural network and SVM classifier. Letter recognition dataset is used for training the SVM and ANN. Both methods are divided into training and testing phase. A comparative analysis and evaluation between two classifiers is presented with SVM and ANN. …
Table of Contents
2.1 Preferred Learning Method: Support Vector Machine
2.1.1 Using hyperplane classification
2.1.2 Find the maximum margin
2.1.3 Kernel function for nonlinear space
2.2 Datasets Required for the Project
2.3 Brief Justification on SVMs
Machine learning is thefield of computer science of using statistical techniques to enables the computers to act and make data-driven decisions, and progressively learn and improve over time without being explicitly programmed . …
Volatility forecasting has become one of the most influential tasks in the real financial world. Over the last decades of time, this successfully attracted the attention of professionals. We searched materials in major databases, and we can find thousands of academic papers and published books which focus on studying different volatility models on volatility forecasting . There is a large repercussion for the volatility of the financial market. For example, the disaster of 911 occurred in US in 2001 had caused great frustration on financial world among different areas in the world and had a non-evitable negative effect on world’s economy . It can be taken as an obvious evidence that there is a strong link between public confidence and uncertainty of the financial world. …
1. Based on the road code, assisted with shared experience on the web, simulated and reviewed by the coach, practiced and innated by repeated training, adjusted and refined your body like a machine.
Remember, road code learning is always the most important.
2. Prepare for the worst and visualize it.
Considering your backup plan.
If you have more practice and imagion the most complicated scnarioes, you can feel more relax and confident during the test.
If you passed, you may think:”Wow, it’s quite easy this time. I am a lucky man.”
If you failed, then complement the new scnario in your check list. …
Data Warehouse (DW) is a system which is used to report and analyze data, and it is considered as the core part of business intelligence (Golfarelli, Rizzi, & Cella). DW stores both the current and historical data in one single place where to create analytical reports for responding people throughout the enterprise (Inmon & W. H, 2005). This report introduces a DW system for a bicycle company, specializing in sales person’s evaluation system. We utilized the high-performance star schema with multi-layer ETL design. Partition and indexing are also developed in order to improve the query and extraction performance. To ensure data quality, we analyzed the correlations among different tables and created rigorous DQA rules. Full and increment loading is fulfilled in this system and data loading will automatically executed every day. There is also a reporting portal for the users to check the queries what they are concerned. …
The framework design of Enterprise Data Warehouse (EDW) system is one of the most important and complex tasks in building a robust and scalable data warehouse system at enterprise level. Benefit from the constantly decline in prices of memory, in-memory computing has become an applicable solution for many EDW systems. This paper first introduced the basic concepts of in-memory computing based on SAP High-Performance Analytic Appliance (HANA), a new platform based on in-memory databases (IMDB). Then the paper discussed the new generation of SAP data warehouse solution-SAP Business Warehouse (BW) on HANA and focused on the framework changes from Layered Scalable Architecture (LSA) to Layered Scalable Architecture based on SAP HANA (LSA++). Further, a field study of the evolution of EDW framework in L company was conducted and a case study of L company’s mixed EDW modelling scenario was analyzed in detail. …