Blockchain’s claim to fame is Bitcoin. While it may be its most well-known application, the interest over the technology continues to expand as countries like Switzerland and Hong Kong are getting on board.

Beyond Bitcoin

Blockchain offers a multitude of applications across industries, and its immutable and decentralized nature that make it virtually robust poses great advantage in handling a significant amount of data during nationwide elections. In fact, the Swiss tax haven of Zug is currently working on using blockchain to log votes. The Zug municipality is not just keen to become a blockchain capital; it is also among the first administrations to express interest to usher in blockchain-based voting.

The municipality completed its first trial, which involved people voting via their smartphones and the town’s new electronic ID system. The trial was completed last June 25.

“The premiere was a success,” Fortune quoted Zug communications chief Dieter Müller told the Swiss News Agency. There were not as many participants but those who took part found the entire process easy. Technical analysis of how the trial went will come next as this is the most common issue with electronic voting. The Holy Grail for electronic voting will be a system to allow auditing but will still preserve the anonymity of individuals. Some believe that blockchain might just be the right answer.

Hong Kong wants to be international blockchain hub

Hong Kong’s Securities and Futures Commission (SFC) said in their annual report that they intend to watch cryptocurrencies and Initial Coin Offerings (ICO) closely. The watchdog also noted that the new technology brings in risks so they plan to intervene if necessary. While the SFC has taken steps to create more defined policies against ICOs and local cryptos – warning people about the possible risks – Hong Kong has also continued on nurturing financial, cross-border initiatives based on blockchain. In fact, the region has been steadily gaining reputation as an international blockchain hub.

As an autonomous territory of China, Hong Kong operates with a separate political system that also extends to its local economy. This means the city does not approach crypto in the same way that China does. Several crypto-related businesses moved to the region after the Chinese crackdown. It was around the same time in September 2017 that Hong Kong expressed support for blockchain. It has a relatively friendlier position towards the technology when compared to China.

The hard drives are prone to breakage, and the data stored in them could be lost. Some common reasons that cause data loss are as follows:

The hard drive component can be faulty and can break, which will lead to data loss. This mechanical failure can lead to damage to the component, and the data can not be accessed.
There could be scenarios like the hard disk board might blow due to the fluctuating power supply to the units.
Some logical errors may also lead to the loss of data. The reasons can be like the programming code of the hard drive got corrupted.
They can have bad sectors. This causes the data to be inaccessible and assumed as data is deleted.
Sometimes we accidentally delete the files containing essential files and documents.
A reinstallation or formatting can also lead to the loss of important files.
The data can be recovered from the hard drives in the majority of the situations. But, the process of recovering the data should be right. Otherwise, the data cannot be retrieved.
Recovering the data by self:

You can recover the data by yourself or take the help of the professionals’ services, but conditions apply. You don’t have to go to a service center if only some files are deleted. Only if there is any problem with your hard drive, then the professionals should be consulted. Otherwise, deletion of files and documents can be recovered by any software available online.

Recovery of Deleted Files in Windows 10 Recycle Bin:

You can restore the files deleted by simply following the procedure given below:

Step 1. Click on the ‘Recycle Bin.’

Step 2. Browse and locate the file that you are looking for.

Step 3. Right-click on the file. Click on the option ‘Restore.’

These steps will retrieve the files that were previously deleted. You can access these from the same location that they were saved on.

Recovery of Deleted Files Using The Software:

If the files that have been deleted are not available in the recycling bin, you can use a lot of software in the market. Any paid or free software can be used to restore the data. This software restores the files that were deleted permanently from the laptop or PC.

Recovering the data with the help of the company:

If there is a failure of the hard drive, then you should consult the company.

Any fault like a problem in the structure and construction, failure of the units that supply the power to the hard drive, fault in the firmware, drives that have bad sectors, etc., should be taken directly to the company. You shouldn’t try to retrieve the data on your own. Taking the help of the available software also increases the risk of further deterioration of the files. Consult companies like Data Clinic Ltd. for recovery of the data lost.

For example, assume your hard drive has encountered some mechanical failure. Its heads are not working properly. Because of this, it fails the self-test, which is crucial before starting the PC. As a result, it keeps resetting itself. Then, a firm that provides data recovery quality should be taken into consideration. Data Clinic Ltd. recovers the deleted data from hard drives, Android phones, iPhones, NAS disks, and RAID 5.

What is Machine Learning?

Machine learning is a branch of artificial intelligence that involves a computer and its calculations. In machine learning, the computer system is given raw data, and the computer makes calculations based on it. The difference between traditional systems of computers and machine learning is that with traditional systems, a developer has not incorporated high-level codes that would make distinctions between things. Therefore, it cannot make perfect or refined calculations. But in a machine learning model, it is a highly refined system incorporated with high-level data to make extreme calculations to the level that matches human intelligence, so it is capable of making extraordinary predictions. It can be divided broadly into two specific categories: supervised and unsupervised. There is also another category of artificial intelligence called semi-supervised.

Supervised ML

With this type, a computer is taught what to do and how to do it with the help of examples. Here, a computer is given a large amount of labeled and structured data. One drawback of this system is that a computer demands a high amount of data to become an expert in a particular task. The data that serves as the input goes into the system through the various algorithms. Once the procedure of exposing the computer systems to this data and mastering a particular task is complete, you can give new data for a new and refined response. The different types of algorithms used in this kind of machine learning include logistic regression, K-nearest neighbors, polynomial regression, naive bayes, random forest, etc.

Unsupervised ML

With this type, the data used as input is not labeled or structured. This means that no one has looked at the data before. This also means that the input can never be guided to the algorithm. The data is only fed to the machine learning system and used to train the model. It tries to find a particular pattern and give a response that is desired. The only difference is that the work is done by a machine and not by a human being. Some of the algorithms used in this unsupervised machine learning are singular value decomposition, hierarchical clustering, partial least squares, principal component analysis, fuzzy means, etc.

Reinforcement Learning

Reinforcement ML is very similar to traditional systems. Here, the machine uses the algorithm to find data through a method called trial and error. After that, the system itself decides which method will bear most effective with the most efficient results. There are mainly three components included in machine learning: the agent, the environment, and the actions. The agent is the one that is the learner or decision-maker. The environment is the atmosphere that the agent interacts with, and the actions are considered the work that an agent does. This occurs when the agent chooses the most effective method and proceeds based on that.

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