Friday, November 22, 2019

Five things at home that wreak havoc on the wifi signal

Check out the five things you have inside your home that you didn't know are affecting the wifi signal.


There are often times when the wifi signal at home is quite weak and many do not know the reason why this is happening. In fact, many of us are forced to use our mobile data or lose patience by surfing with great difficulty and slow pace. Usually most of the problem comes from our internet provider or router settings. However, there are other factors that play a role in influencing the wifi signal.

1. Metal surfaces and furniture

Metal is a conductor, which virtually means it absorbs electricity. As your WiFi emits electromagnetic waves, any metal surface or object in your home will prevent the waves from spreading. If you want your Internet connection to work smoothly, you need to place the router away from the metal.

2. Brick or stone wall

There are some types of walls that can block the wifi signal Among the most common materials that block the connection are marble, cement, plaster and brick. That's why in two-storey houses, too, usually one floor doesn't have such good internet access. To fix it, place the router outdoors and away from the walls.

3. Mirrors

The material that allows us to see our reflection also reflects the signal released by the router. This object acts as a shield, making the Internet connection low.

4. Refrigerators and washing machines

As a general rule, electrical appliances that have tubes running in the water do not "do very well" with WiFi. Water can retain some of the energy from wireless waves, which negatively affects the quality of the internet connection.

5. Christmas lights

The colorful Christmas lights can also contribute to the poor quality of the Internet at home. The lamps have a chip means that generates a magnetic field that interacts with the router's electrical waves. In December, try to keep the router away from your Christmas tree.

Πέμπτη, 3 Οκτωβρίου 2019

Wi-Fi technology Closes in 20 Years: The Key Points

In an increasingly interconnected world, for many, the "coming" of WiFi technology was seen as a historic turning point in this story. Specifically, last Monday, September 30, was the 20th anniversary of the emergence of this technology during which people from all over the world have managed to reach out to their loved ones, work and so on. So, in a related document released by Cisco, a networking company, the key points of this 20-year WiFi journey are outlined.   Choosing the name  Reference to ALOHAnet could not be omitted from WiFi history. In 1971, the University of Hawaii built a network system that laid the foundations for the future development of wireless connectivity as we know it today. Today, we are all more or less dependent on it, but do we really know what its story is? When it comes to WiFi in essence, it is about IEEE 802.11, which is a standard protocol used to communicate with local wireless networks. Therefore, WiFi is the commercial "point" of this protocol, which was first introduced in 1997 and has a speed of about 2 Mbps.

For the future, in 2022, WiFi will become the main source of Internet access. Also in the same year, the average connection speed will reach 54.2 Mbps, as opposed to 24.4 in 2017.   1999: The WiFi debut in the market 1999 is the first year that WiFi made its debut on the market, thanks to the launch of 802.11b. Compared to its previous version, WiFi has now improved in speed and usability. The first devices that took advantage of this technology, such as laptops, were also released that year.    2004: WiFi is available on flights  The gradual deployment of this technology has persuaded many companies to use it for the benefit of their passengers since 2004. That year, wireless made its first appearance on the flight, allowing customers to use their personal computers to check in. e-mails them and do their jobs in general.

1999: The WiFi debut in the market 1999 is the first year that WiFi made its debut on the market, thanks to the launch of 802.11b. Compared to its previous version, WiFi has now improved in speed and usability. The first devices that took advantage of this technology, such as laptops, were also released that year.   

2004: WiFi is available on flights  The gradual deployment of this technology has persuaded many companies to use it for the benefit of their passengers since 2004. That year, wireless made its first appearance on the flight, allowing customers to use their personal computers to check in. e-mails them and do their jobs in general.

2009: The arrival of Wi-Fi 4 Four years later, specifically in 2009, the technology is moving to a new stage, namely WiFi 4, which promises users an even faster speed thanks to Mimo technology. The latter allows for even faster data transfer with Mbps reaching 450.   

2011-2012: millions of hotspots around the world  Between 2011 and 2012, WiFi is now well into the day-to-day lives of users. Now, there are millions of hotspots around the world, with about a quarter of families having this connection.   

2013: The arrival of 1 Gbps In 2013, the 802.11ac standard was introduced for the first time, enabling users to navigate at speeds of 1 Gbps. Indeed, according to a 2015 survey by IDC, wireless is the second thing that people could not live without. For the story, food tops the list with 30%.

2018: 13 billion devices are connected worldwide In 2018, the financial value of WiFi reached $ 2,000 billion. This increase is evident in terms of access to this technology. In fact, it is estimated that on average one person has two devices that allow him to access the Internet.   

2019: The appearance of WiFi 6 2019 will go down in history as the year of the introduction of WiFi 6, a technology based on the 5G network, reaching up to 5 Gbps. However, for this technology to be available on all devices available on the market, we will have to wait until 2020 for all devices to be compatible.   

2022: The average connection speed is increased even more As for the future, in 2022, according to a Cisco study, WiFi will become the main source of Internet access. 59% of people will actually use the wireless connection to navigate the web. Also the same year. the average connection speed will reach 54.2 Mbps, compared to 24.4 in 2017.   

Is WiFi Health Hazardous?  Are WiFi Networks Really Dangerous to Health? Although numerous investigations have been carried out in recent years, public debate on this issue is still open. In particular, in 2011, the IARC, the International Organization for Research on Cancer, labeled these networks as 2B, which may mean carcinogens. However, today there is no research to prove that there is a cause-and-effect relationship between the use of devices, such as smartphones and computers connected to WiFi, and the creation of tumors.

Thursday, October 3, 2019

What are the core skills of Data Scientist?


  Being able to accurately describe the problem from the vague concept and propose a framework for understanding the problem

For a newcomer just getting started, maybe many of the problems you have encountered are clear. For example, in the next year, which country has the most potential for user growth; tablet users spend the most time in what place. However, as your skills deepen, you will become more and more exposed to more ambiguous problems, and sometimes even feel that the problem itself is too virtual to start. For example, can we start to promote this new product? How to measure whether we have achieved success?At this time, the first point is to be able to break the problem into several specific small problems. For the question "Can we start to promote this new product?", we may want to know: Does the product quality itself meet the preset standards? What is the most important use characteristic of the user in the early stage of the product? Is it a feature that can be promoted? If we promote the product and get the X user, how many users will be left in a few months?

 The ability to answer questions from different angles and have trade-offs

Perhaps no one method is 100% correct or can give 100% of the answers to the questions, but a good data analyst can give data of different dimensions, sum up the stories and give the most likely answers.Continuing with the previous example, what are the most important features of the user in the early stage of the product? Is it a feature that can be promoted?In addition to looking at the user's usage data for this product, you may want to look at the user's usage data in other competing products. Maybe you want to look at some market data to determine the market size and market demand. Maybe you want to look at the user itself. Attributes (age, education, gender, place of residence or main social circle), maybe also want to see the changes after the user uses the product...There are so many things you can see, and it's easy to get lost in an endless curve. But what are the most important ones?

 Believe in intuition, but not blindly believe; before data analysis, dare to make their own guesses, but objectively accept the various possibilities presented by the data, and rationally 
choose the most likely outcome

I have encountered a lot of data analysis that I deliberately pieced together to tell a story. In this case, I am always angry. If you have determined that Product A will be better than Product B, why do you have to do everything possible to prove this with data? The goal of data analysis is to let you rationally compare A and B to help you make the right choices, rather than letting you affirm your guess and persuading others to follow you. The latter is just one result of data analysis
In the era of big data, what occupations are more popular? The answer can be found in this year's list of school salary recruits – algorithmic engineers, artificial intelligence researchers, data analysis and other positions. In fact, there is a certain intersection between these positions, that is, a large amount of data needs to be processed, especially as a data scientist. The main work is on processing data and analyzing data, and some work overlaps with algorithm engineers and artificial intelligence researchers. Its advantage is that it is more sensitive to data. So what are the skills that should be available as a data scientist? This article will give a glimpse of what.

      Academic
   data scientists generally have a high degree of education - 88% of data scientists are at least master's degree, 46% of data scientists are doctorates, which indicates that wanting to become a data scientist requires a very good educational background (knowledge understanding ). Common majors are computer science, social sciences, physical sciences, and statistics. The most common areas of research are mathematics and statistics (32%), followed by computer science (19%) and engineering applications (16%). The expertise you've learned while pursuing these degrees will provide you with the skills you need to process and analyze big data.        Can you sit back and relax after you have earned your degree? The answer is no, now is the era of lifelong learning. In fact, most data scientists continue to use online training to learn how to use special skills such as Hadoop or big data queries after they have a master's or doctoral degree.

 R programming language

 For data scientists, the R language is usually the preferred programming language. The R language is specifically designed for data science needs, and the R language can be used to solve any problems encountered in data science. In fact, 43% of data scientists are using the R language to solve statistical problems.        But there is a hindrance when learning R language, that is, if you have mastered another programming language, it is very painful to learn. Despite this, there are many R language learning resources on the Internet, such as Simplilearn's data science training and R programming language . Technical Skills: Computer Science

Python Programming

The Python language has been very popular lately. With the development of artificial intelligence and deep learning, Python has surpassed the Java language to become the most commonly used language in programming. Python is also a common coding language in data science. According to the survey, 40% of respondents use Python as their main programming language.       Because of the versatility of Python, it can be used for all steps involved in the data science process. For example, Python can use data in a variety of formats and can easily import SQL tables into your code. In addition, it allows you to create data sets.