5G

Artificial neural network (ANN) is a group of neuron nodes, interconnected with each other. Every circular node works as an artificial neuron that exchanges information with each other, similar to the functional principles of biological neural networks. The whole system is termed ANN. The main advantage of artificial neural network implementation lies in the ability to perform complex mathematical modelling for emulation. This helps scientists to predict different processes and trends based on the visualisation of these models. ANN is a simple system of processors (artificial neuron), in which neurons connect and interact reciprocally with each other. Each neuron periodically receives signals and sends them to others. By connecting to a reasonably large network of similar neurons, these single processors can perform quite complex actions. From the point of view of machine learning, neural networks are special cases of discriminant analysis, pattern recognition and grouping methods. From the mathematical point of view, the learning of neural networks is a multiparameter problem of nonlinear optimization. From the development of computation and programming, neural networks are a way to solve efficient parallel problems. From a cybernetic perspective, neural networks are used for problems of adaptive control and robotic algorithms. From the point of view of artificial intelligence, neural networks are the basis of the philosophy of connectionism and the main direction of the structural methods of using computer algorithms to establish the possibility of natural intelligence. Neural networks are not just programmed, but are also well trained. The possibility of ‘learning’ is one of the main advantages of ANN over traditional algorithms. Stages of problem solving Data collection for training; Selection of network topology; Preparation and normalization of data; Experimental selection of training parameters; Experimental selection of network characteristics; Actually learning; Checking the adequacy of training; Adjustment of parameters, final training; Verbalization of the network for further use. Technically, ‘learning’ is to find the coefficient connection  between neurons. During this process, the neural network is able to detect complex dependencies between data input and output and perform generalization. This means that if training succeeds, the network can return the correct results based on data not provided in training samples and incomplete and / or "noisy" and partially distorted data. So, with the help of the ANN we can predict the most probable event. For the business environment, such operations are vital in the financial, medical, construction and any decision-making field.

Networking hardware is a set of devices necessary for the operation of a computer network, for example: a router, a switch, a hub, a patch panel, etc.   Active networking hardware is equipment containing electronic circuits receiving power from an electrical network or other sources and performing the functions of amplification, signal transformation, and others.  This means such equipment is able to process the signal by special algorithms. In the networks there is a package data transfer, each data package also contains technical information about its source, purpose, the integrity of information, etc, allowing to deliver the package to its destination. Active networking hardware includes the following types of devices: Network adapter - a card that is installed in the computer and provides its connection to the LAN; Repeater - a device, usually with two ports, designed to repeat the signal in order to increase the length of the network segment; Hub (active hub, multiport repeater) - a device with 4-32 ports, used to connect users to the network; Bridge - a device with 2 ports, usually used to combine several LAN (local area network) workgroups, allows you to filter network traffic by analyzing network (MAC) addresses; Switch - a device with several (4-32) ports, used to combine several LAN working groups (otherwise called multiport bridge); Router (router) - used to combine several  LAN workgroups, allows you to filter network traffic by analyzing network (IP) addresses; Retranslator - to create an advanced wireless network with a larger coverage area and is an alternative to a wired network. By default, the device operates in the signal amplification mode and acts as a relay station that catches the signal from the base network router or access point and transfers it to previously unavailable sites. Media converter - a device, usually with two ports, used to convert the data transfer medium (coaxial-twisted pair, twisted-pair optical fibre); A network transceiver is a device, usually with two ports, commonly used to convert the data format. A transceiver can be mentioned as a Medium Access Unit (MAU) in Ethernet network terminology. Additionally to this set of devices, to become a part of the network, a computer must have a network interface card (NIC). Mentioned above networking hardware can be called a set of computer networking devices or network equipment.  

Net Promoter Score (NPS) is an index that identifies customer loyalty to a product or company and is used to assess readiness for re-purchases. How It Works Measuring the NPS loyalty index involves several steps: Consumers are asked to answer the question “What is the probability that you would recommend a company/product/brand to your friends/acquaintances/colleagues?” On a 10-point scale, where 0 corresponds to the answer “I will not recommend it in any way”, and 10 - “ I will surely recommend. " Based on the estimates obtained, all consumers are divided into 3 groups: 9-10 points - product/brand promoters, 7-8 points - passives, 0-6 points - detractors. Calculation of the NPS index itself. NPS =% supporters -% critics As a result, the the user’s loyalty score calculated on the scale from -100 to 100. If all the customers are willing to recommend the product, the score will be about 90-100, if they are not willing to recommend it - the NPS will drop to -90-100 points.   NPS trade mark was registered for the marketing tool, which automates the calculation of the above mentioned data. History Frederick Reichheld is considered the founder of the method, who first announced the method in the article “One Number You Need to Grow”, published in the Harvard Business Review in December 2003. In 2006, he released a book entitled “The Ultimate Question: Driving Good Profits and True Growth”. He continued his arguments on the loyalty, profitability and growth of the company. In 2001, Reichheld conducted research in more than 400 American companies, where the main task was to measure the influence of customer loyalty (measured by NPS) on its growth rate. The main result was the conclusion that the average NPS by market in the industry was 16%, but for companies such as eBay and Amazon NPS it was 75%. Reichheld does not say that communication is present everywhere: it is absent altogether in monopolistic markets. However, industries such as passenger air travel, insurance and car rental have become a prime example of interconnection. This is obvious, since these companies are service providers, where customer satisfaction and loyalty depend on the level of customer service. As a result, many companies have become adherents of this technology, including Apple, American Express,  eBay, Amazon, Allianz, P & G, Intuit,, Philips, etc. For certain industries, especially software, it has been proven that Detractors often stay with the company while Passives leave.  This seems to be a relatively high barrier to trade. Faced with criticism of the promoter's score, proponents of the network promoter's approach stated that the proposed statistical analysis only proved that the "recommendation" problem was similar to other indicators in predictive capacity, but failed to solve the real problem and this is the core of the argument presented by Reichheld. Proponents of the method also argue that third-party data analysis is not as good as analyzing the company in its own set of customers, and the actual benefits of the method (simple communication concepts, short survey, customer follow-up features ) exceed any statistical disadvantage of the approach. They also allow inquiries using any other issues to be used in the net promotion system, as long as it meets the criteria to securely classify customers as promoters, passives and detractors.

is an open source general purpose PHP framework. The Laravel creators themselves called it “framework for artisans”, hinting that the platform gives programmers complete creative freedom without putting any obstacles in the development process. MVC Code Structure The Laravel framework code structure corresponds to the MVC design pattern, i.e. programmers can select views, models, and controllers. MVC has proven to be a time-tested solution to the challenge of creating effective app structure. This development pattern allows making the code more readable, and the creation process comfortable by demarcating the work of backend and frontend developers. Artisan Artisan is a Laravel console, in the commands arsenal. There is work with controllers and models, migrations, authorization and other basic framework components. Migrations A sort of version control for the database table structure. Each migration file contains either a table structure or changes in its structure. The process of building new database entities in the Laravel framework happens when you create a migration and launch it with the help of special artisan console commands. Blade Blade is its own template engine with a set of its own directives. Its working principle is similar to most of its fellows - Smarty, Twig, etc. Twitter Bootstrap and jQuery out of the box After installing the Laravel framework, the developer has at his disposal the app.css and app.js files, which are the BootStrap and  jQuery of the latest versions that were assembled and minimized at the time of the Laravel release. Eloquent ORM ORM is a programming technology built to make it easier for developers to work with the database by providing API methods for standard operations (fetching, adding, updating, deleting, etc.). Various ways of Working with Sessions Session objects are stored on the server, therefore, they can be easily and conveniently manipulated by the server programming languages, as well as assigning them to various storages. Laravel developers took the advantage of this feature, having introduced into the framework the ability to choose how to store session objects using different technologies. cookie; file storage on the server - standard session objects; memcached; saving data in the database; redis; temporary php array With Laravel, as well as any other framework, programmers can make completely different types of sites, starting with landing pages and ending with social networks. This is their fundamental difference from CMS, which, for the most part, are highly specialized.