Composer is a dependency manager for PHP applications. It allows you to install, update, and manage third-party libraries for your Laravel project. Laravel uses Composer to manage its own dependencies, as well as the dependencies of any packages you install.

To install Composer on Windows, you can follow these steps:

1. Go to https://getcomposer.org/download/ in your web browser.

2. Download the Composer-Setup.exe file by clicking on the “Windows Installer” option.

3. Once the file is downloaded, double-click on it to run the installer.

4. The installer will guide you through the setup process. You can leave the default settings as they are or customize them as per your preference.

5. When you reach the “Installation Options” screen, make sure the “Add Composer to PATH” option is checked. This will allow you to use Composer from any directory in the Command Prompt.

6. Continue with the installation by following the remaining on-screen instructions.

7. After the installation finishes, open a new Command Prompt window (or restart it if it was already open).

8. To verify if Composer is installed properly, type “composer” in the Command Prompt and press Enter. It should display the Composer version and a list of available commands.

That’s it! Composer is now installed on your Windows system, and you can start using it for managing your PHP dependencies.

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PHP is Open Source server-side programming / Scripting language that is especially suited for web development and can be embedded into HTML.

PHP stands for Hypertext Preprocessor but it’s original name, Personal Home Page. It was created by Ramsum Lerdorf in 1994.

PHP runs on various platforms Windows, Linux, Unix, Mac OS X, etc.

PHP is compatible with almost all servers Apache, IIS, etc.

At Present in 2017 Php 7.2.0 is latest version of PHP

PHP File Extension .php

What we can do with PHP

• Generate Dynamic Page
• Handle button clicks, radio button
• Create Database Application
• Client/server Application
• Student Registration
• Online Course
• Online Shopping cart
• Chat Rooms

Example

How PHP Works

Development Environment

• Operating System – Windows, Linux, Mac etc.
• Web Server – XAMP, WAMP, MAMP etc.
  • §XAMP – Apache + MariaDB + PHP + Perl

• Editor/IDE – NotePad, NotePad ++, NetBeans, Brackets, Eclipse etc.
• Web Browser – Chrome, Firefox etc.

Basic Structure of PHP

Basic Structure of PHP

Variable

Variables are containers which is used to store information.

Type of Variables: –

• Local Variable
• Global Variable
• Static Variable

Variable Declaration

In PHP, variable names begin with $ sign, followed by a name.

Ex: –

• $roll
• $price
• $name

Rules

• Variable starts with $ sign.
• Variable name only starts with a letter, an underscore ( _ ).
• Variable name cannot start with a number.
• It is case sensitive which implies that the variable num in lowercase is different from variable NUM in uppercase.
• Do not use Predefined constant name e.g. PHP_VERSION , PHP_OS etc.
• Do not use reserved keywords. e.g. else, if etc.

Variable Initialization

PHP can store all type of data in variables. Before using a variable in PHP, assign a value to it so PHP will create that variable and store data in it. That means we have to assign data to a variable before attempting to read a variable’s value.

Ex: –

• $roll = 256;
• $price = 25.50;
• $name = “Geeky Shows”;

Note – If a variable is created without a value, it is automatically assigned a value of NULL.

Internal Data Types

In other language, you need to specify the exact data format of each variable, but PHP handles that for you.

• Integer – It can hold whole number. Ex: 12, 0, -34 etc.
• Float/Double – It can hold floating point number. Ex: 25.2654, 2.12 etc.
• String – It can hold text or group of characters. Ex: – “Geeky Shows” etc.
• Boolean – It can hold true/false value.
• Array – It can hold multiple values in one single variable.
• Object – It can hold programming objects.
• Resource – It is special variable that hold references to resources external to PHP.
• NULL – It can hold only one value – NULL .

The post PHP Tutorial For Beginners Step By Step With Example Session-1 appeared first on Artificial Intelligence.

The Python Integrated Development Environment Ide Software report provides a detailed analysis of the major factors influencing the market growth, including the drivers, restraints, lucrative opportunities, technology advancements, industry-specific challenges, recent developments, and competitive analysis, CAGR, market share, revenue, gross margin, value, volume, industry size, share, growth, segmentation, main trends, standardization, deployment models, strategies, future roadmaps, and Annual forecast for the year 2027 and other key market figures that give an accurate picture of the growth of the Python Integrated Development Environment Ide Software market. 

The report includes an elaborate executive summary, along with a snapshot of the growth behavior of various segments included in the scope of the study. Furthermore, the report sheds light on the changing competitive dynamics in the global Python Integrated Development Environment Ide Software market. These indices serve as valuable tools for existing market players as well as for entities interested in entering the global Python Integrated Development Environment Ide Software market.

The historical and forecast information provided in the report span between 2020 and 2027. To provide a stronger and stable business outlook, the regional outlook has been presented by inspecting several industries across different global regions.

**This market research report was prepared after considering the COVID-19 impacts**

Analytical Insights Included from the Python Integrated Development Environment Ide Software Market Report:

• Estimated earnings rise of the marketplace throughout the forecast period.
• Factors expected to aid the rise of the Python Integrated Development Environment Ide Software marketplace.
• The growth potential of this market in a variety of regions.
• Consumption, pricing arrangement, and adoption routine of this market.
• Company profiles of top players in the market.

The report includes Competitor’s Landscape:

➊ Major trends and growth projections by region and country
➋ Key winning strategies followed by the competitors
➌ Who are the key competitors in this industry?
➍ What shall be the potential of this industry over the forecast tenure?
➎ What are the factors propelling the demand for the Python Integrated Development Environment Ide Software Industry?
➏ What are the opportunities that shall aid in the significant proliferation of the market growth?
➐ What are the regional and country-wise regulations that shall either hamper or boost the demand for Python Integrated Development Environment Ide Software Industry?
➑ How has the covid-19 impacted the growth of the market?
➒ Has the supply chain disruption caused changes in the entire value chain?

enefits of buying the report:

The report is compiled using a vigorous and thorough research methodology. Stratagem Market Insights is also known for its data accuracy and granular market reports.

• A complete picture of the competitive scenario of the Python Integrated Development Environment Ide Software market is depicted by this report.
• The report consists of a vast amount of data about the recent product and technological developments in the markets.
• The extensive spectrum of analysis regarding the impact of these advancements on the future of market growth.
• SMI is keeping a track of the market since 2015 and has blended the necessary historical data and analysis in the research report. Therefore, any additional data requirement can be easily fulfilled.
• The insights in the report are easy to understand and include a graphical representation of the numbers in the form of histograms, bar graphs, pie charts, etc.
• Components such as market drivers, restraints, challenges, and opportunities for the Python Integrated Development Environment Ide Software market are explained in detail.
• It also provides a complete assessment of the expected behavior about the future market and changing market scenario.
• Making an informed business decision is a tough job; this report offers several strategic business methodologies to support you in making those decisions.

Important Features that are under offering & key highlights of the report:

1) Does the study cover COVID-19 Impact Analysis and its effect on Growth %?

Yes, the overall industry has seen quite a big impact due to slowdown and shutdown. The study covers a separate qualitative chapter on COVID-19 Impact analysis. Additionally, it also provides before and after the scenario of COVID-19 on sales growth & market size estimation to better analyze the exact scenario of the industry.

2) How companies are selected or profiled in the report?

A list of some players that are profiled in the report includes,  PyCharm, Eclipse, AWS Cloud9, The Jupyter Notebook, Kite, Codenvy, Selenium IDE, Wing Python IDE, ActiveState, Aptana Studio, Ninja IDE, Kdevelop, Koding, Eclipse IoT, UEStudio, Codeanywhere.

Usually, we follow NAICS Industry standards and validate company profile with product mapping to filter relevant Industry players, furthermore the list is sorted to come up with a sample size of at least 50 to 100 companies having greater topline value to get their segment revenue for market estimation.

3) Can we add or profiled a new company as per our needs?

Yes, we can add or profile a new company as per client need in the report, provided it is available in our coverage list as mentioned in answer to Question 1 and after feasibility run, final confirmation will be provided by the research team checking the constraints related to the difficulty of survey. 

4) Can a specific country of interest be added? What all regional segmentation covered?

Yes, Country-level splits can be modified in the study as per objectives. Currently, the research report gives special attention and focus on the following regions:

⇨ Asia-Pacific (Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia)
⇨ Europe (Turkey, Germany, Russia UK, Italy, France, etc.)
⇨ North America (the United States, Mexico, and Canada.)
⇨ South America (Brazil etc.)
⇨ The Middle East and Africa (GCC Countries and Egypt.)

“The report also covers the trade scenario, Porter’s Analysis, PESTLE analysis, value chain analysis, company market share, segmental analysis”

The post Python Integrated Development Environment Ide Software Market Projected to Discern Stable Expansion During 2020-2027 | Key Players: PyCharm, Eclipse, AWS Cloud9, The Jupyter Notebook appeared first on Artificial Intelligence.

Due to the public outcry and tax cuts, companies are going green with AI to prevent irreversible harm to the planet.

We are the first generation to witness the effects of climate change unfold, and the last with the ability to prevent those effects from intensifying and irreversibly harming our planet.

According to the US Environmental Protection Agency, global carbon emissions from fossil fuels rose significantly since 1900. CO2 emissions have increased by about 90% since 1970, with emissions from fossil fuel combustion and industrial processes contributing about 78% of the total greenhouse gas emissions increase from 1970 to 2011.

These insights are not new to operators of industrial plants and factories. China is followed by the US and the EU as the largest emitters of CO2. They collectively account for over 50% of global emissions.

Most industrial facilities are well aware of their carbon footprint. Due to public demand for environmental sustainability and higher taxes on emissions, they have every intention to implement decarbonization measures. For the most part, however, their efforts have fallen short, leaving a gap between their ambitions and the reality of their carbon reduction activities.

According to the Boston Consulting Group, the standard three-step approach to implementing decarbonization measures starts with assessing the carbon footprint and comparing it against the carbon footprint of industry peers, as well as national/international standards. The next step is to develop realistic short- and long-term decarbonization targets based on a thorough cost-benefit analysis. The final step is to define the specific measures that will provide environmental and economic benefits.

Most industrial plants and factories already have the necessary capabilities to go green, both in terms of production and logistics. Depending on the industry, the necessary change may be a switch in energy sources, such as solar and wind in place of coal and fossil fuels. In most cases, however, the change calls for an upgrade in processes and technologies for increased efficiency. Some companies, such as the Israel-based EcoPlant, are working to tackle that challenge before it’s too late.

EcoPlant, which has offices in Israel and the US, developed a SaaS (Software as a Service) solution that connects to air compressors’ controllers and property sensors to monitor and continuously optimize entire systems. Their predictive AI algorithms conduct ongoing energy surveys and dynamically control each compressor and the whole system.

The end result? Significantly reduced energy waste, increased reliability, and optimized maintenance. Such a solution enables continuous savings of hundreds of thousands of dollars annually. EcoPlant’s proprietary algorithms can also be applied in settings such as hospitals and commercial buildings, as well as critical infrastructure equipment, such as pumps and chillers, essentially making it a one-size-fits-all solution.

The harmful effects that stem from energy waste and CO2 emissions undoubtedly trace back to human decisions and errors. Undoing those negative effects, especially in the modern post-pandemic world, requires the collaborative efforts of human intelligence with machine intelligence. Numerous facilities hailing from industries with the largest carbon footprints, such as technology, automotive and process industries, are already getting on board with AI solutions such as EcoPlant, to meet popular and regulatory demands.
According to the Paris Climate Agreement, which is an ambitious global action plan to fight climate change and its negative impact, emissions from production and logistics would need to drop approximately 45% by 2030 to be on a path to meet the 1.5°C target for limiting the global temperature increase. To meet this goal, it is imperative for industrial plants and factories to ramp up their efforts to go green by turning to AI.

The post Artificial Intelligence can reliably help industrial plants go green appeared first on Artificial Intelligence.

The Center for Noise and Vibration Control at KAIST announced that their coughing detection camera recognizes where coughing happens, visualizing the locations. The resulting cough recognition camera can track and record information about the person who coughed, their location, and the number of coughs on a real-time basis.

Professor Yong-Hwa Park from the Department of Mechanical Engineering developed a deep learning-based cough recognition model to classify a coughing sound in real time. The coughing event classification model is combined with a sound camera that visualizes their locations in public places. The research team said they achieved a best test accuracy of 87.4 %.

Professor Park said that it will be useful medical equipment during epidemics in public places such as schools, offices, and restaurants, and to constantly monitor patients’ conditions in a hospital room.

Fever and coughing are the most relevant respiratory disease symptoms, among which fever can be recognized remotely using thermal cameras. This new technology is expected to be very helpful for detecting epidemic transmissions in a non-contact way. The cough event classification model is combined with a sound camera that visualizes the cough event and indicates the location in the video image.

To develop a cough recognition model, a supervised learning was conducted with a convolutional neural network (CNN). The model performs binary classification with an input of a one-second sound profile feature, generating output to be either a cough event or something else.

In the training and evaluation, various datasets were collected from Audioset, DEMAND, ETSI, and TIMIT. Coughing and others sounds were extracted from Audioset, and the rest of the datasets were used as background noises for data augmentation so that this model could be generalized for various background noises in public places.

The dataset was augmented by mixing coughing sounds and other sounds from Audioset and background noises with the ratio of 0.15 to 0.75, then the overall volume was adjusted to 0.25 to 1.0 times to generalize the model for various distances.

The training and evaluation datasets were constructed by dividing the augmented dataset by 9:1, and the test dataset was recorded separately in a real office environment.

In the optimization procedure of the network model, training was conducted with various combinations of five acoustic features including spectrogram, Mel-scaled spectrogram and Mel-frequency cepstrum coefficients with seven optimizers. The performance of each combination was compared with the test dataset. The best test accuracy of 87.4% was achieved with Mel-scaled Spectrogram as the acoustic feature and ASGD as the optimizer.

The trained cough recognition model was combined with a sound camera. The sound camera is composed of a microphone array and a camera module. A beamforming process is applied to a collected set of acoustic data to find out the direction of incoming sound source. The integrated cough recognition model determines whether the sound is cough or not. If it is, the location of cough is visualized as a contour image with a ‘cough’ label at the location of the coughing sound source in a video image.

A pilot test of the cough recognition camera in an office environment shows that it successfully distinguishes cough events and other events even in a noisy environment. In addition, it can track the location of the person who coughed and count the number of coughs in real time. The performance will be improved further with additional training data obtained from other real environments such as hospitals and classrooms.

Professor Park said, “In a pandemic situation like we are experiencing with COVID-19, a cough detection camera can contribute to the prevention and early detection of epidemics in public places. Especially when applied to a hospital room, the patient’s condition can be tracked 24 hours a day and support more accurate diagnoses while reducing the effort of the medical staff.”

This study was conducted in collaboration with SM Instruments Inc.

/Public Release. The material in this public release comes from the originating organization and may be of a point-in-time nature, edited for clarity, style and length. View in full here.

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KIRTLAND AIR FORCE BASE ― The Air Force Research Laboratory will begin maneuvers today, Oct. 20, as the first-ever inspection mission to support real-time on-orbit spacecraft anomaly resolution operations. 

This effort will be a rendezvous between the experimental Mycroft satellite and a second experimental AFRL satellite called the Small Satellite Space Surveillance System, or S5. The S5, launched Feb. 22, 2019, is a small satellite designed to test affordable SmallSat space situational awareness constellation technologies. 

AFRL has experienced communication challenges with the S5 satellite and has had no communication with S5 since March 2019. Operators confirm that the spacecraft is alive and maintaining solar power by tracking the sun, but without communications S5 cannot perform its experiments. Mycroft is an AFRL-developed SmallSat launched with the EAGLE satellite April 14, 2018.

Mycroft separated from EAGLE and drifted about 35 kilometers away before transiting carefully back to within a few kilometers of EAGLE. It has performed space situational awareness, or SSA, and satellite inspection experiments over the past 18 months. The Mycroft experiment is aimed at improving autonomous rendezvous and proximity operations, or RPO, SSA, satellite inspection and characterization, and autonomous navigation technologies. 

Mycroft satellite operators will initiate a series of maneuvers to rendezvous with S5 near 6 degrees East longitude at Geosynchronous Orbit to support anomaly resolution efforts. EAGLE will also maneuver into the vicinity of the RPO to observe the inspection from a safe distance. Mycroft will inspect the S5 satellite and provide operators with verification of the fully-deployed solar array and of the sun pointing orientation. Mycroft will then examine the exterior of the S5 spacecraft to search for damaged components such as the solar array and antennas. 

The Mycroft-S5 RPO will occur in stages over a period of several weeks, demonstrating the utility of inspection and characterization capabilities in a real-world satellite recovery. AFRL is planning to transition operations to Air Force Space Command later this year.

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