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Freebie Friday: TMS FNC Maps helper functions

We are back with another freebie friday! TMS FNC Maps comes with a lot of great functionality as well as a (lesser visible) unit bundling helper functions to empower your developments. The unit is called (FMX.)TMSFNCMapsCommonTypes.pas. The prefix FMX., can be replaced with VCL., WEBLib. or LCL depending on the framework. Below are a couple of helper functions explained to help you in write your code more efficiently or add more complex functionality to your application. Plus Codes Plus Codes are like street addresses for people or places that don’t have one. Instead of addresses with street names and numbers, Plus Codes are based on latitude and longitude, and displayed as numbers and letters. With a Plus Code, people can receive deliveries, access emergency and social services, or just help other people find them. source: https://maps.google.com/pluscodes/ TMS FNC Maps supports Plus Codes encoding & decoding with the TTMSFNCMapsPlusCode class. To get started, and convert an existing coordinate to a Plus Code, use the following code: procedure TForm1.EncodeCoordinate; var p: string; begin p := TTMSFNCMapsPlusCode.Encode(CreateCoordinate(40.689188, -74.044562)); //p = ’87G7MXQ4+M5′ end; To decode a Plus Code to a coordinate bounds, which defines the area corresponding to the code, the Decode function can be used: procedure TForm1.DecodePlusCode; var c: TTMSFNCMapsBoundsRec; begin c := TTMSFNCMapsPlusCode.Decode(’87G7MXQ4+M5′);  end;  Measuring distance between 2 coordinates Another great utility function is to measure the distance (in meters) between 2 coordinates. The distance measured is based on the average earth radius (6371000 meters). The sample below demonstrates how to measure the distance between 2 coordinates, but also how to create bounds, create a circle, calculate a new coordinate based on the bearing and many more. procedure TForm1.AddCircle; var   b: TTMSFNCMapsBoundsRec;   d, br: Double;   c: TTMSFNCMapsCoordinateRec;   I: Integer; begin   b := CreateBounds(40.76437, -73.94928, 40.76799, -73.98235);   d := MeasureDistance(b.NorthEast, b.SouthWest);   c := CalculateCoordinate(b.NorthEast, CalculateBearing(b.NorthEast, b.SouthWest), d);   TMSFNCMaps1.BeginUpdate;   with TMSFNCMaps1.AddCircle(b.NorthEast, Round(MeasureDistance(b.NorthEast, b.SouthWest) / 2)) do   begin     FillColor := gcRed;     FillOpacity := 0.5;     StrokeWidth := 10;     StrokeColor := gcPink;   end;   TMSFNCMaps1.EndUpdate; end;

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How to Create a Responsive JavaScript Admin Dashboard Easily with Ext JS

A well-built admin dashboard can significantly increase the productivity of your business. With Sencha Ext JS, you can create responsive admin dashboards easily, allowing your company to discover valuable insights into your data at a glance. The benefits are clear, with a better understanding of your data, you can make more timely and informed business decisions. In this post, you will find all the details you need to get started on your admin dashboard. What is Sencha Ext JS? Sencha Ext JS is a very powerful JavaScript library. It excels in allowing you to quickly create feature-rich web applications. To help you do this, it includes over 140 UI components, including the D3 adapter, grids, and panels. More importantly, Sencha Ext JS supports cross-platform functionality so you can use it to build web apps for any modern device, like desktop PCs, laptops, and smartphones. How to Build a Responsive Admin Dashboard with Sencha Because it supports the MVC architecture, creating admin dashboards is pretty easy with Sencha Ext JS.  Let’s explore the possibilities, starting with this example: To build the dashboard shown above, you have to follow these steps: Create the Model 1. Create a new directory, called the model. Go inside the folder. Then create the email directory. Inside the new folder, create an Email.js file and add these codes: Ext.define(‘Admin.model.email.Email’, { extend: ‘Admin.model.Base’,   fields: [ { type: ‘int’, name: ‘id’ }, { name: ‘read’ }, { type: ‘string’, name: ‘title’ }, { name: ‘user_id’ }, { type: ‘string’, name: ‘contents’ }, { type: ‘string’, name: ‘from’ }, { name: ‘has_attachments’ }, { name: ‘attachments’ }, { name: ‘received_on’, type: ‘date’ }, { name: ‘favorite’ } ] }); Here, you are adding various fields, including id, title, and content. 2. Next, create a Friend.js file and add this code: Ext.define(‘Admin.model.email.Friend’, { extend: ‘Admin.model.Base’,   fields: [ { type: ‘int’, name: ‘id’ }, { type: ‘string’, name: ‘name’ }, { type: ‘string’, name: ‘thumbnail’ }, { type: ‘boolean’, name: ‘online’ } ] }); 3. When you are done, go back to the model folder and create the faq directory. Inside the new folder, create your Category.js file and add the following: Ext.define(‘Admin.model.faq.Category’, { extend: ‘Admin.model.Base’,   fields: [ { type: ‘string’, name: ‘name’ } ],   hasMany: { name: ‘questions’, model: ‘faq.Question’ } }); 4. Create Question.js file and add these codes: Ext.define(‘Admin.model.faq.Question’, { extend: ‘Admin.model.Base’,   fields: [ { type: ‘string’, name: ‘name’ } ] }); 5. After that, go back to the model folder. Then create the search directory. Inside the new folder, create your Attachment.js file and add this code: Ext.define(‘Admin.model.search.Attachment’, { extend: ‘Admin.model.Base’,   fields: [ { type: ‘int’, name: ‘id’ }, { type: ‘string’, name: ‘url’ }, { type: ‘string’, name: ‘title’ } ] }); 6. Ok, now create your Result.js file and add this code: Ext.define(‘Admin.model.search.Result’, { extend: ‘Admin.model.Base’,   fields: [ { type: ‘int’, name: ‘id’ }, { type: ‘string’, name: ‘title’ }, { type: ‘string’, name: ‘thumbnail’ }, { type: ‘string’, name: ‘url’ }, { type: ‘string’, name: ‘content’ } ],   hasMany: { name: ‘attachments’, model: ‘search.Attachment’ } }); 7. We are almost there. Create your User.js file and add these lines: Ext.define(‘Admin.model.search.User’, { extend: ‘Admin.model.Base’,   fields: [ { type: ‘int’, name: ‘identifier’ }, { type: ‘string’, name: ‘fullname’ […]

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6 Ways To Rapidly Collect Massive Datasets in your Apps

What is web scraping? Web Scraping is a technique where a computer program extracts data from human-readable output coming from websites. The web scraping software may directly access the World Wide Web using the Hypertext Transfer Protocol or a web browser. While Web Scraping can be done manually by a software user, the term typically refers to automated processes implemented using a program, bot, or web crawler. It is a form of copying in which specific data is gathered and copied from the web, typically into a central local database, spreadsheet, API, or any format that is more useful for the user, for later retrieval or analysis. First, the app needs to interpret a web page as data Web pages are built using text-based mark-up languages; like HTML and XHTML, and frequently contain rich and useful data in text form. Quite obviously, most web pages are designed for human end-users and not really for ease of automated use. As a result, this can make it a challenging task to build specialized tools and software to facilitate the scraping of any web pages. Delphi plus Python is a powerful combination for web scraping In this tutorial, we’ll build Windows Apps with extensive Web Scraping capabilities by integrating Python’s Web Scraping libraries with Embarcadero’s Delphi, using Python4Delphi (P4D). P4D empowers Python users with Delphi’s award-winning VCL functionalities for Windows which enables us to build native Windows apps 5x faster. This integration enables us to create a modern GUI with Windows 10 looks and responsive controls for our Python Web Scraping applications. Python4Delphi also comes with an extensive range of demos, use cases, and tutorials. We’re going to cover the following… How to use Requests, BeautifulSoup, Instaloader, Snscrape, Tweepy, and Feedparser Python libraries to perform Web Scraping tasks All of them would be integrated with Python4Delphi to create Windows Apps with Web Scraping capabilities. Prerequisites Before we begin to work, download and install the latest Python for your platform. Follow the Python4Delphi installation instructions mentioned here. Alternatively, you can check out the easy instructions found in the Getting Started With Python4Delphi video by Jim McKeeth. Time to get started! First, open and run our Python GUI using project Demo1 from Python4Delphi with RAD Studio. Then insert the script into the lower Memo, click the Execute button, and get the result in the upper Memo. You can find the Demo1 source on GitHub. The behind the scene details of how Delphi manages to run your Python code in this amazing Python GUI can be found at this link. Open Demo01.dproj. How do I Scrape Website’s Data using Python Requests? “Requests” is a simple, yet elegant HTTP library. Requests allow you to execute standard HTTP requests extremely easily. Using this library, you can pass parameters to requests, add headers, receive and process responses, execute authenticated requests. Requests are ready for the demands of building robust and reliable HTTP–speaking applications, for the needs of today. Keep-Alive & Connection Pooling International Domains and URLs Sessions with Cookie Persistence Browser-style TLS/SSL Verification Basic & Digest Authentication Familiar dict–like Cookies Automatic Content Decompression and Decoding Multi-part File Uploads SOCKS Proxy Support Connection Timeouts Streaming Downloads Automatic honoring of .netrc Chunked HTTP Requests After installing Python4Delphi properly, you can get Requests using pip or easy install to your command prompt: […]

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Detecting Objects on images using Google Cloud Vision API

Lets take a look at this image below. Let’s try to think about 2 or 3 objects we can see and focus on what calls our attention the most. If we write them down , lets see if Google can guess it right. Google’s cloud-based vision API – making sense of what we see and much more Google Cloud’s Vision API offers powerful pre-trained machine learning models that you can easily use on your desktop and mobile applications through REST or RPC API methods calls. Lets say you want your application to detect objects, locations, activities, animal species, and products. Or maybe you want not only to detect faces but also their emotion expressed on the faces. Or perhaps you have the need to read printed or handwritten text. All of this and much more is possible to be done for free (up to first 1000 units/month per feature) or at very affordable prices and it’s scalable too with no upfront commitments. Object localization The option for “Object Localization” is part of the Vision API that we can use to detect and extract information about multiple objects in an image. For each object detected the following elements are returned: A textual description – what is it, in plain human language? A confidence score – how certain is the API of what it has detected? And normalized vertices [0,1] for the bounding polygon around the object. Where are the objects on the image? Using RAD Studio Delphi to control the Google Cloud Vision API We can use RAD Studio and Delphi to easily setup its REST client library to take advantage of Google Cloud’s Vision API to empower our desktop and mobile applications and if the request is successful, the server returns a 200 OK HTTP status code and the response in JSON format. Our RAD Studio and Delphi applications will be able to either call the API and perform the detection on a local image file by sending the contents of the image file as a base64 encoded string in the body of the request or rather use an image file located in Google Cloud Storage or on the Web without the need to send the contents of the image file in the body of your request. How do I set up the Google Cloud Vision Object Localization API? Make sure you refer to Google Cloud Vision API documentation in the Object Localization section (https://cloud.google.com/vision/docs/object-localizer), but in general terms this is what you need to do on Google’s side: Visit https://cloud.google.com/vision and login with your Gmail account Create or select a Google Cloud Platform (GCP) project Enable the Vision API for that project Enable the Billing for that project Create a API Key credential How do I call Google Vision API Object Localization endpoint? Now all we need to do is to call the API URL via a HTTP POST method passing the request JSON body with type OBJECT_LOCALIZATION and source as the link to the image we want to analyze. One can do that using REST Client libraries available on several programming languages and a quick start guide is available on Google’s documentation (https://cloud.google.com/vision/docs/quickstart-client-libraries). Actually, at the bottom page of the Google Cloud Vision documentation Guide (https://cloud.google.com/vision/docs/object-localizer) there is an option “Try This API” which allows you to post […]

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Upscale Images Via Machine Learning With Javascript Super Resolution API

  Images are everywhere. Whether on the internet, our phones, or even in our day-to-day lives, most people amass huge volumes of data in the form of digital images of varying quality. Any library of digital images, personal or public, is likely to contain low-quality or blurry images. Unfortunately, however, these can problematic to view or, or worse, to analyze. In particularly bad cases, you need to zoom to better see or analyze parts of an image, but even then the image may lack the detail or resolution to do this effectively.  For this reason, having an automated and intelligent tool that can upscale and create high-quality, high-resolution images is remarkably useful. Enter DeepAI’s Super Resolution API. It uses machine learning (ML) and AI techniques to upscale images into higher resolutions without compromising their quality or losing their content. DeepAI’s Super Resolution AI can generate an upscaled version of an image within seconds. If this sounds useful, let’s take a look at how you can quickly build a Sencha Ext JS app that upscales any image you input by calling the DeepAI Super Resolution API. Once we are done, your final app will look like this: What is the DeepAI Super Resolution API? To understand the DeepAI Super Resolution API, once you have your prerequisites installed type the following at the command prompt: curl -F ‘image=https://upload.wikimedia.org/wikipedia/commons/thumb/c/c4/Tulipa_orphanidea_060506.jpg/260px-Tulipa_orphanidea_060506.jpg’ -H ‘api-key:quickstart-QUdJIGlzIGNvbWluZy4uLi4K’ https://api.deepai.org/api/torch-srgan This command accepts the URL of an input image and submits an API key to generate a new version of the image with a higher resolution and better quality. If you get it right, the response from the API looks like this: {   “id”: “025c64f7-a610-4ee5-aa33-b215d703c595”,   “output_url”: “https://api.deepai.org/job-view-file/025c64f7-a610-4ee5-aa33-b215d703c595/outputs/output.jpg”} As you can see, it returns a response that is a JSON object with the URL of the upscaled image. Better yet, not only is the input image enlarged 4 times, it has also has improved in quality. One thing you need to be aware of though, is that with DeepAI APIs, you only get a quick start API key with a set number of queries. Once your trial expires, you have to get your own API key. How can I upscaling images using AI in Javascript? If you think this is useful, here are 4 easy steps that you can follow to build your own application in a matter of minutes. Step 1: Create an Ext JS Minimal Desktop Application To develop an app to upscale any image you input, first create a blank minimal desktop application in EXT JS. If you are new to Sencha’s Ext JS framework, you can follow this tutorial to create a minimal desktop application from the command prompt. I have chosen to create all my files in a folder called super-res and I call the app superRes. Step 2: Include the DeepAI Package To include the DeepAI package, open the index.html file located in the main directory and add the following line anywhere in the header of the HTML: Step 3: Create the Main View In the main view, we have the following: A text field for the URL of the input image An area to display the input image A button labelled ‘Upscale Image’ A text field to display the URL of the output upscaled image An area to display the output image To get started, […]

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Biggest Cloud Breaches of 2020

Published May 20, 2021 WRITTEN BY ED TITTEL. Ed Tittel is a long-time IT industry writer and consultant who specializes in matters of networking, security, and Web technologies. For a copy of his resume, a list of publications, his personal blog, and more, please visit www.edtittel.com or follow @EdTittel 2020 was a year to remember, and that many would like to forget, for a variety of reasons ranging from the largest global pandemic since the Spanish Flu of 1918, to political turmoil in the USA over a fractious Presidential race, to economic and employment dips of epic proportions. And indeed, 2020 also came with a number of record-setting security breaches, nearly all of which involved the cloud in some form or fashion. In fact, there are numerous top 10 security breach collections among which to choose. One in particular is worth reciting, and then reflecting on the cloud’s presence in that itemized list. PCR is a leading information source for IT resellers and distributors in the United Kingdom. It reports its top 10 based on the number of records breached in the incidents selected. They cite the Risk Based Security Report to observes that nearly 3K breaches were reported just for Q1 2020, and the number records exposed at 36 billion (for the whole year of 2019, “only” 15 billion records were exposed). Here’s their top 10 list with some annotations and reflections, in ascending order by number of records breached: 10. Unknown source (201M): In January, 2020, security researchers found a database containing over 200M sensitive personal records online. The compromised host was on the Google Cloud Platform, so though the source or owner of the data remains unidentified, there’s no disputed that this collection of US personal and demographic data has a definite cloud connection. After Google was alerted to the matter, it took the server down over a month later. 9. Microsoft (250M): In January, 2020, MS itself reported a data breach on servers storing customer support analytics in its Azure Cloud. The records involved included email and IP addresses, plus support case details, stored on 5 ElasticSearch services, inadvertently disclosed owing to misconfigured security rules. 8. Wattpad (268M): In June, 2020, records belonging to this Canadian website and app for writers used to publish user-generated stories and text were exposed (later reports raise the count to 271M records). Malicious actors compromised the company’s SQL database which contained account information, email and IP addresses, and other personal data. Reports on this breach do not mention a specific cloud connection, but the site’s current DNS information appears to show it is hosted by Amazon Web Services (a definite cloud connection). 7. Broadvoice (350M): A US provider of Voice over IP (VoIP) services to business, October, 2020, reports confirm exposure of 350 million customer records from this company. Data disclosed includes names, phone numbers, and call transcripts, including calls to medical and financial services providers. Owing to a configuration error, security researchers were able to access ten of the company’s databases without providing access credentials. Broadvoice changed the configuration and notified relevant legal authorities. It’s not clear that these databases were cloud-based, though it’s hard to imagine a VoIP company NOT doing business in the cloud. 6. Estée Lauder (440M): In January, 2020, the company had an unprotected, unencrypted […]

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Automate Aircraft Workflow With Delphi And A Mobile Phone

If you’re like me flying is probably a slightly mystical experience. You’re not entirely sure how the plane defies gravity and the job of a pilot seems to involve a bewildering array of switches, dials and incredibly expensive sunglasses. There’s a lot more going on, of course, beyond the cockpit and safety briefings. Modern flights, even in smaller aircraft, involve much more tedious ephemera like equipment reservations, invoices, fees and the relentless recording of flight data. Making the process of flying less trying Belgian developers Micriconsult have poured their talent into a dedicated Android app specially for members of The Noordzee Vliegclub. Using RAD Studio Delphi and the Firemonkey FMX framework they have helped ease and automate some of the tasks of the flying business with some thoughtful and intelligent workflow analysis to create a really useful tool which pilots can simply carry around in their pocket – especially useful for smaller light-commercial and pleasure craft where space is at a premium. Noordzee Vliegclub Website What does the Noordzee Vliegclub app do? The app allows a member from the Noordzee Vliegclub to reserve a plane, to enter the flight data to help fulfil legal obligations as well as keep tabs on the myriad expenses of the modern world of flight. According to the developer, “It also keeps track of all flights and all costs involved, presented as monthly invoices. At any time a member can update its database data. This app allows a member from the Noordzee Vliegclub to reserve a plane and enter the flight data. At any time a member can update its database data. A flight instructor can define a plane as a training plane (preventing members to use it for regular flights), authorize a pilot member to fly on a specific plane type and keep track on the flying hours of each student. Users who are not a member of the Noordzee Vliegclub cannot use this app.” Google Play Noordzee Vliegclub Screenshot Gallery You could really make a difference – use your talent with RAD Studio today and be a high-flyer!

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What’s new in TMS FNC UI Pack 3.4

There are a lot of great new features available in our FNC components and this blog will highlight the new additions to the TMS FNC UI Pack. If you want to check the improvements on TMS FNC Maps, click here. For the list of fixes and improvements, you can check the version history, but two new components were added to the product as well. TTMSFNCPassLock TTMSFNCPassLock is an updated version of the FMX passlock in the TMS FMX UI Pack.This component gives you the ability to add password protection to your application. It’s not only possible to further customize the buttons and pattern, but also the ability to not show the length of your password. Next to that you have the similar workings of the numpad and pattern layout and the learn mode to set a new password. TTMSFNCControlPicker The TTMSFNCControlPicker helps you to create a dropdown variant of your control. This can be done with the ITMSFNCControlPicker interface and is implemented by default in the TTMSFNCTreeView, TTMSFNCTableView, TTMSFNCListBox and TTMSFNCListEditor. It is possible to implement the interface in your own control, for more information regarding the necessary procedures and functions to implement, please check the documentation.Some additional events are available, to mimic the basic mechanics of the interface without implementing it and to make the control even more customizable. This is an example of the base implementation to retrieve the content that should be shown in the dropdown edit. It shows the number of times the button was clicked. First create a new extended button class: type TButtonEx = class(TButton, ITMSFNCControlPickerBase) private FCount: Integer; function PickerGetContent: String; protected procedure Click; override; public constructor Create(AOwner: TComponent); override; end; { ButtonEx } procedure TButtonEx.Click; begin inherited; Inc(FCount); if Assigned(Parent) and (Parent is TTMSFNCCustomSelector) and Assigned(Parent.Owner) and (Parent.Owner is TTMSFNCControlPicker)then begin //Update ControlPicker if assigned as control (Parent.Owner as TTMSFNCControlPicker).UpdateDropDown; end; end; constructor TButtonEx.Create(AOwner: TComponent); begin inherited; FCount := 0; Text := ‘Click this’; end; function TButtonEx.PickerGetContent: String; begin Result := IntToStr(FCount) + ‘ Clicks’; end; The only thing left to do is creating the button and assiging it to a TTMSFNCControlPicker: procedure TForm1.FormCreate(Sender: TObject); begin b := TButtonEx.Create(Self); b.Parent := self; TMSFNCControlPicker.Control := b; end;

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Announcing support for FMXLinux!

Intro A couple of weeks ago we announced beta support for FMXLinux and today we announce stable support. The beta period is finished and we now fully support FMXLinux in the latest version of all of our FNC products. Download the latest update today to get started! Below is a list of FNC products that have been tested in FMXLinux. With FMXLinux, we add a new platform to the wide variety of already supported platforms in FNC. TMS FNC Components can be used simultaneously on these frameworks TMS FNC Components can be used simultaneously on these operating systems/browsers TMS FNC Controls can be used simultaneously on these IDEs Getting Started The components have been tested and deployed on a Linux environment (Ubuntu 20.04) after properly setting up FMXLinux and other dependencies required for various parts of FNC. Support for FMXLinux is limited to RAD Studio 10.4 Sydney and the path to the source files has to be manually configured in the library path (the automated installer currently does not pick up FMXLinux). Please follow the instructions below to add FMXLinux support to RAD Studio. Please note that adding the SDK is an essential part of the configuration process and it is important to add the SDK to RAD Studio when all the necessary libraries are added to your Linux environment. After following the above instructions, please execute the following commands sudo apt install joe wget p7zip-full curl openssh-server build-essential zlib1g-dev libcurl4-gnutls-dev libncurses5 sudo apt-get install zlib1g-dev sudo apt install libgl1-mesa-glx libglu1-mesa libgtk-3-common libgstreamer1.0-0 libgstreamer-plugins-base1.0-0 sudo apt install libwebkit2gtk-4.0-dev Add each path that contains FNC source files of the products you have installed to the Linux 64 bit library path. Start a new multi-device FMX project and select the Linux 64 bit profile. When the PAServer is running correctly, you can connect to Linux environment and start deploying your application.  Video The above instructions along with a showcase of some FNC components are demonstrated in the video below. Stay tuned! With FMXLinux support we add yet another major and exciting feature to the already huge amount of features and components FNC has to offer. Yesterday we also announced exciting new features and improvements in TMS FNC Maps 1.5 and TMS FNC UI Pack 3.4. Read the linked blog posts to find out more. Stay tuned for more FNC improvements and features coming up in the near future!.

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What’s new in TMS FNC Maps 1.5

We are back with another substantial update for TMS FNC Maps. 4 new components are introduced in TMS FNC Maps v1.5: TTMSFNCStaticMap, TTMSFNCMapsImage, TTMSFNCTollCost and TTMSFNCTimeZone. 1. Static Maps & Map Image The new TTMSFNCStaticMap component lets you request a static map image for a specific location. The static image can be customized by setting the map type (roads, satellite …), zoom level and an optional marker at the center point. The resulting image can be displayed by using the TTMSFNCMapsImage component. The following mapping services are supported: Azure, Bing, Google, Here, MapBox, TomTom Only a single line of code is needed to request and display a static map image: TMSFNCMapsImage1.URL := TMSFNCStaticMap1.GetStaticMap(CenterCoordinate,  TMSFNCMapsImage1.Width, TMSFNCMapsImage1.Height, ZoomLevel, ShowMarkerBoolean, MapType);     2. Toll Cost calculation Using the TTMSFNCTollCost component the toll route costs between an origin and destination location can be calculated. Toll cost information is returned for each toll segment along the route together with turn by turn directions. The following mapping services are supported: Here, PTV xServer The toll cost calculation can be requested with just one line of code: TMSFNCTollCost1.GetTollCost(OriginCoordinate, DestinationCoordinate); 3. TimeZone information The TTMSFNCTimeZone component can be used to request time zone information for a specified location. The following mapping services are supported: Azure, Bing, Google, Here Again a minimum of code is needed to request and display time zone information: procedure TForm1.TMSFNCMaps1MapClick(Sender: TObject;  AEventData: TTMSFNCMapsEventData);begin  TMSFNCTimeZone1.GetTimeZone(AEventData.Coordinate.toRec)end;procedure TForm1.TMSFNCTimeZone1GetTimeZone(Sender: TObject;  const ARequest: TTMSFNCTimeZoneRequest;  const ARequestResult: TTMSFNCCloudBaseRequestResult);var  it: TTMSFNCTimeZoneItem;begin  it := ARequest.Items[0];  memo.Lines.Clear;  memo.Lines.Add(‘TimeZone: ‘ + it.TimeZone);  meTimeZone.Lines.Add(it.Description);  meTimeZone.Lines.Add(‘Offset: ‘ + it.Offset);  meTimeZone.Lines.Add(‘DST: ‘ + it.DSTOffset);end; 4. Minor improvements Apart from all the new components, some improvements are also included with this update. One of the noteworthy improvements is the possibility to retrieve the index of the waypoints in the optimized order for TTMSFNCDirections. The following mapping services are supported: Azure, Google Maps, TomTom That’s it for this TMS FNC Maps v1.5 update. I hope you’ll enjoy all these exciting new features!

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