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Many Linux users have a set of applications – browser, file manager, image viewer – that they’re loyal to. In most cases, these applications correspond to the default setup of a Linux distribution. If you’re a KDE user, you’ve probably heard of Konqueror. It’s a powerful application that has been a part of KDE for years, but it’s often unfairly neglected in favor of newer apps. Did you know you can use Konqueror not only as a file manager, but also as a web browser, PDF viewer and document editor?

If this sounds interesting, you can install Konqueror from the repositories of Ubuntu, Debian, Arch and other distributions, or from the source. Note that you’ll have to install many packages as Konqueror’s dependencies if you don’t already have KDE on your system. I recommend you also install a package called “konq-plugins” which contains browser extensions.

Using Konqueror as a Web Browser

The UserAgent Changer extension can modify Konqueror’s identification – it can “pretend” to be a different browser. The “Web Browsing” section in the Configure Konqueror dialog lets you enable Do Not Track headers as a part of browser identification. The only essential thing that Konqueror lacks is private browsing, but other features make up for it.

Split View is one such feature. Accessed via the Window menu or with keyboard shortcuts (Ctrl+Shift+L to split vertically, Ctrl+Shift+T horizontally), Split View divides the active tab into as many small frames as you want. You can open new links in separate frames to preview multiple websites at the same time.

File Management and Beyond

Speaking of file opening, Konqueror can handle several filetypes – you can use it to open PDF files, edit text documents, preview and even convert between basic image formats (JPG, PNG, TIFF, GIF, BMP). It can also display Linux info and man pages in a nice, readable format; just type man:/[name] into the address bar.

Konqueror’s versatility is made possible by KParts, a KDE component framework that’s used to manage file types or embed applications into one another. Technically, any KDE application that supports KParts can be embedded into Konqueror, meaning that Konqueror can “take over” its functionality. This is how Konqueror works as a file manager – it embeds Dolphin and offers all its features. Users switching from Dolphin will surely appreciate this.

Konqueror’s power derives from the convenience and seamless integration of features that would otherwise require opening several applications. True, you need to have Okular, Dolphin and other apps installed if you want to use Konqueror as anything other than a browser, so some people might consider this embedding as “cheating” or even “useless.” On the other hand, it’s extremely practical when working with multiple files since you can view them all in one window or quickly switch between tabs. Konqueror can act as a container for other apps and eliminate clutter from your workflow, and you can always go back to using it as a lighweight web browser.

Ivana Isadora Devcic

Ivana Isadora is a freelance writer, translator and copyeditor fluent in English, Croatian and Swedish. She’s a Linux user & KDE fan interested in startups, productivity and personal branding. Find out how to connect with Ivana here.

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Owc Thunderbolt 3 Dock Review: Unleash The Power Of 14 Ports

Imagine if your MacBook could have 14 ports? And you can use them all simultaneously for charging, external display, audio input/output, data transfer, and more. Seems like a dream, right? Well, with OWC Thunderbolt 3 Dock, you get that!

But does this sleek OWC dock work as smoothly as it claims? Let’s find out as I test it and share my in-depth, hands-on review with you guys.

OWC Thunderbolt 3 Dock: An overview

The Thunderbolt 3 Dock sets out to inject more convenience, speed, power, and functionality into your workflow with just a single cable.

That’s right, just a single cable to connect and seamlessly access displays, other peripherals, mobile devices, and more to a Thunderbolt 3-equipped Mac or Windows laptop.

The rectangular brick-like dock boats 14 ports strewn across the front and back.

PortsNo.USB 3.1 Gen 11 – front, 4 – backUSB 3.1 Gen 2 (Type C)1 – frontAnalog Audio In/Out1 – frontmicroSD slot1 – frontSD Card1 – frontGigabit Ethernet1 – backThunderbolt 3 Ports2 – backMini DisplayPort1 – backOptical Audio Out1 – backTotal14

OWC Thunderbolt 3 Dock: Power you need OWC Thunderbolt 3 Dock: Speed and use

While the power quotient is impressive, a dock should also bring in great speed. And the specs of the Thunderbolt 3 Dock did not disappoint me at all.

10Gb/s: Two rear-facing USB-C ports

8Gb/s: Front-facing USB-C port

5Gb/s: Five rear-facing USB-A ports

1000Mb/s connection: Rear-facing Gigabit Ethernet

So, whether you want to charge your phone, transfer data from an external SSD, connect a printer or other peripherals, you’ll get optimal speed from the Thunderbolt 3 Dock.

OWC Thunderbolt 3 Dock: Design

To be honest, I am pretty conflicted about the design of the Thunderbolt 3 Dock. I love that it employs optimal port configuration to ensure a comfortable and clutter-free experience for most users.

For instance, you’ll probably need to insert and eject SD cards or headphones repetitively; so, the audio and media card ports are placed in the front for quick and hassle-free usage.

But on the other hand, the aluminum body frame is quite chunky and will demand some real estate on your desk. And the piano gloss finish on the top is a fingerprint and dirt magnet.

Moreover, it doesn’t work without the charger, a bulkier and heavier addition to the equation. All things considered, the dock is not a portable accessory.

However, I must say that the weight and four rubber feet on the bottom make it slip-proof. So, there is some light at the end of the tunnel.

The missing component

Most external displays today come with either an HDMI port or DisplayPort. Although I love the inclusion of a Mini DisplayPort and the perks it offers, an HDMI port is missing.

That means you’ll have to purchase additional adapters or converters.

Is the OWC Thunderbolt 3 Dock worth docking? Our Verdict

In terms of usage, OWC Thunderbolt 3 Dock worked like a charm. Everything from power to speed was as promised. However, the size and weight of the dock are surely off-putting.

I feel the glass top could have an LED display, or the indicator light could be on top or at the front instead of the bottom. There is some scope for improvement in the design department.

Who is it for?

After using the Thunderbolt 3 Dock for a while, I felt that it is designed for iMac or Mac Pro users. Those who have proper workstation setups and have a bunch of peripherals attached all the time.

Everything from the weight to speed works in their favor here. And it could be a worthy investment for professionals like music producers, video editors, graphic designers, or gamers.

Colors: Silver and Space Gray

Warranty:  2-year limited warranty

Buy it from OWC

Video: OWC Thunderbolt 3 Dock review

Author Profile


A self-professed Geek who loves to explore all things Apple. I thoroughly enjoy discovering new hacks, troubleshooting issues, and finding and reviewing the best products and apps currently available. My expertise also includes curating opinionated and honest editorials. If not this, you might find me surfing the web or listening to audiobooks.

Sdg Group: Leading Into The Next Normal Through The Power Of Data & Analytics

SDG Group is a Global Data & Analytics Consulting Firm, offering in-depth expertise that empowers its clients’ strategies to become data-driven enterprises and bridges the gap between data and business decisions.

With a global presence, the company’s mission is to transform data into better business decisions, making the results of its projects a core and sustainable differentiator for its clients. SDG Group believes in “Data As A Transformational Asset” (“D.A.T.A.”), meaning data is used as the basis for new ways of performing various functions 

and  operating

 as a business.  

The company has a technology-agnostic approach, which allows the firm to innovate its value proposition with the latest and best technologies to provide the ultimate data and analytics solutions in the market. 

Mitigating the Impact of the COVID-19 Crisis 

When the COVID-19 pandemic impacted the world, SDG Group looked for opportunities to use its data and analytics expertise to help. They collaborated with global healthcare experts and used the latest technologies to develop, 


, a revolutionary AI-assisted remote diagnosis app, recognized by

The World Health Organization (WHO)

 for being one of the most innovative digital health solutions worldwide. The app detects vital signs remotely to help healthcare professionals safely visit patients and enables the digital health taskforce to manage and monitor patients and customers through a Patient Management Dashboard. 

SDG Group also collaborated with the 

Red Cross

 on its

Red Cross RESPONDS Plan.

 The initiative takes action to address COVID-19 in all affected areas of society; emergencies, health, social inclusion, education, employment, and the environment. SDG Group deployed an Open Data Platform that made data centralized and current, and the actions of the Red Cross transparent to the public and key stakeholders.

Helping Clients Overcome New Challenges

In addition to assisting in healthcare and nonprofit organizations, SDG Group manages the pandemic’s impact on its clients. The company helps them create new strategies and solutions to thrive in the “next normal.”  

A primary focus is moving data and analytics into the Cloud. SDG Group believes the Cloud is critical for reacting quickly to disruptions because it provides an agile, secure, scalable, and reliable way to extract data. The Cloud also enables its clients to focus more on getting value from data, instead of only spending time managing and maintaining infrastructure.

Another concentration related to the Cloud is Data Sharing. SDG Group believes that having a single data vision where there are no information silos is the most optimal way to address business challenges. The company facilitates Data Sharing within its clients and, in parallel, ensures they have reliable data and speak the same data language through effective Data Management and Data Governance practices.

Also, a Digital Analytics Strategy is more critical than ever now that digital channels are the only means for connecting with people and finding new business opportunities. SDG Group helps its clients discover new ways to reach their customers. With a customer-centric vision, the company developed

SDG Eagle Digital Analytics

, a solution that provides a comprehensive view of data from all channels.

The economy and recession are also 




 War Room Solution

 to provide its clients with visibility into cash flow to evaluate every possible scenario. The solution helps its clients better manage liquidity and pursue new growth opportunities. 

Lastly, SDG Group uses disruptive technologies such as AI, Machine Learning, and Advanced Analytics as catalysts for innovation that will enable its clients to excel in a post-pandemic world. 

Innovating the Data Value Chain to Accelerate Business Insights 

SDG Group innovates the entire Data Value Chain 

in order to

 turn data into transformative insights. For this reason, the company’s services offerings support the full lifecycle of data: Strategy & Transformation, Analytics Infrastructure, Data Management, Business Analytics, Advanced Analytics, Performance Management, and Business Insights. 


 a well-known principle at SDG Group to avoid “copying and pasting”.  That means a solution that worked for one client may not work for another and the company should always bring an innovation to every project. This core belief results in unique, next-level solutions for every SDG client.

The company’s business model is also innovative. 


 a mix of management consulting, industry knowledge, and data & analytics expertise. They have a unique, team-based 

approach to staff projects and provide clients with local teams connected across the globe 

in order to

 scale for some of the world’s largest companies and complex projects.

SDG Group builds strategic technology alliances with industry leaders who add value to their services and solutions and play an important role in achieving their vision of D.A.T.A.  Partners include AWS, Microsoft, SAP, Snowflake, 


, IBM, Informatica, Talend, 





, Dataiku, Qlik, Tableau, 


, Board, 



, Cloudera, and more.

Position as Global Market Leaders 

Since its founding in 1994, SDG Group’s mission is to transform data into better business decisions and its projects to result in a core and sustainable differentiator for its clients. They aim to be the market leaders in Data & Analytics.

SDG Group aligns its strategy with its values and seeks to create an environment led by meritocracy and powered by teamwork. This maximizes efficiency because it ensures that all employees work towards common goals and use the same methodologies. 

Client success is the priority in all projects.  SDG builds relationships with clients based on the value they provide, measured by the adoption of the solutions they build rather than the revenue they generate. This unique relationship with clients is how the company creates success, adds 


 and builds an enduring and trusted partnership.  

The company has been successful with its mission because it manages the company by its values. This success has led to growth and new business locations in Italy, Spain, France, Portugal, the United Kingdom, Germany, Belgium, Egypt, Algeria, United Arab Emirates, Colombia, and the United States. 

Their success has also led to recognition and awards. Over the last decade, SDG Group has been named a key consulting firm in the Gartner Market Scope for Europe, and a Global Representative Vendor in Gartner’s Market Guide for Data & Analytics Service Providers, which includes only 37 companies worldwide. 

Leaders in local markets also endorse the company. Some of these recognitions are from Analytics Insight in the United States, BARC in Germany, 


 in Iberia and Latin America, and Industrial Process News in the United Kingdom. 

In parallel, SDG is awarded regularly by its technology partners, such as SAP, 


, Board, Snowflake, and Qlik, for execution, quality, and excellence in its implementations. 



 Future Possibilities

SDG Group is a firm that envisions new possibilities with data. They believe they can lead in a new world that many people cannot conceive yet. This vision into the future helps SDG Group’s clients excel in the long-term. 

Each year, they name the industry trends that will have the biggest impact. In 2023, the most significant will come from the lasting effects of COVID-19 and the ten

2023 Data & Analytics Trends

 below. SDG Group categorizes the trends into three categories. 

Given Trends:

 Trends that are a must and require action now. 

Trends on the Rise:

 Trends that will have a significant impact. 

Slow-Shift Trends:

 Trends that are starting to surface. Companies will need to adjust their strategies accordingly to face the future business landscape successfully.

Visionary Leadership 

Alejandro Martinez is a Partner of SDG Group and the CEO of the United States and Canada. He joined the company in 2009 and has made notable contributions to SDG Group and the Data & Analytics industry, which include: 

Creating an agile organization that can manage clients’ demands with proximity and velocity while simultaneously managing the company’s challenges and goals.

Supporting global and regional clients in building and executing large-scale, global development programs in different areas, implementing new strategies to analyze data and make the most of it.

Participating as a Member of the Board of Directors in startups that SDG Group supports. 

Contributing to SDG Group’s technology alliances in their Partner Advisory Councils and direct engagements with their R&D departments to influence the market execution and the technology roadmap.

Challenging the status quo by creating and leading new units and teams to enhance its value proposition for its clients and reach market positioning.

Prospecting the business and partners in the Benelux region

Starting Up and working with the team to consolidate SDG Group USA and bring a new wave of innovation 

Participating as a Strategy Management Lecturer and Speaker in industry events

Study – Webmasters And Online Marketers Are Missing Out On The Power Of

Launched by Google, Microsoft, Yahoo! and recently adopted by Yandex, is an initiative to standardize a set of tools to help webmasters incorporate structured data within their sites.

Structured data is a way of formatting online information using a specific language or markup placed within the source code of web pages so search engines can easily understand it. It’s used by the leading search engines to identify and understand web content, so they can enhance the results displayed for specific search queries, for example by integrating additional text, images or links known as rich snippets.

We studied tens of thousands keyword results and half a million domains to analyze how often domains or URLs using markup schema are displayed in Google’s US search results. We looked at whether a schema integration may have a positive effect on a domain’s rankings. Despite the potential marketing boost, our new research at Searchmetrics shows that few sites are actually making use of schema markup.

Nearly 40% of Keywords on Google Include Schema Snippets

Of the Google search results for tens of thousands of keywords we studied, 36.6% included at least one snippet with information derived from chúng tôi (see chart below).

Of course, some sites use other tools to markup structured data. Large sites such as chúng tôi and chúng tôi seem to have agreed their own methods with Google in this area. So, if you include results which incorporate at least one integration which is‘like’, then the number goes up to 65.6%. This shows the potential power of using structured data and

Find more information about the various types of snippets and integrations that can be supported by

If you had to guess which chúng tôi integrations are shown most frequently on Google, you’d probably say something like “Reviews” because they are applicable to such a wide variety of domains – for example, anyone that offers products or services.

But as you can see from the chart , “movie” integrations came out on top (27%). This included integrations from popular movie sites such as IMDb, for example.

The second most frequent integration at 21% was “offers” which is commonly used when online retail and eCommerce sites appear in search results – a very important integration to drive traffic and conversions for transactional searches.

Pages Using chúng tôi Markups Rank Higher in Google?

We wanted to test the hypothesis that the integration of chúng tôi data in Google might be rewarded with a better ranking. So we analyzed the top 50 search results for our keyword set, taking into account sites both with and without schema integrations.

We found the average ranking of domains without schema integrations (99.7%) is 25.

Sites with schema integrations in 2014 ranked on average four positions better than those without.

It must be noted that this is not necessarily a causal relationship. It may not be the case that pages are actually preferred by Google just because they provide schema integrations. An alternative explanation for the higher rankings could be that webmasters who use chúng tôi integrations are one step ahead of the competition due to other factors that affect their rankings in a positive way.

Very Few Domains Integrate Schema

Despite the potential benefits, currently only a small fraction of domains use the integration of chúng tôi markups. In fact, based on our keyword sets, the percentage was only 0.3%. In general, we found that larger sites are more likely to use schema markup.


So, while Schema offers online marketers the potential to increase traffic to their sites by helping them providing useful information to search engines which could result in enhanced search listings, few sites are making use of it. This could be due to a gap in technical knowledge or just a time lag.

About Our Study:

In search results for tens of thousands of keywords we analyzed each of the first 50 search results looking for integrations that result from using chúng tôi and/or other structured data.

We analyzed over half a million domains to determine whether chúng tôi data can be found.

The survey was conducted in March 2014 for Google USA.

Power Of Latent Diffusion Models: Revolutionizing Image Creation

This article was published as a part of the Data Science Blogathon.


One approach to achieving this goal is through the use of latent diffusion models, which are a type of machine learning model that is capable of generating detailed images from text descriptions. These models work by learning to map the latent space of an image generator network to the space of text descriptions, allowing them to generate images that are highly detailed and realistic.

In this article, we will explore the concept of latent diffusion models in more detail and discuss how they can be leveraged for creative image generation. We will also discuss some of the challenges and limitations of this approach and consider the potential applications and impact of this technology.

Source: Keras

Unveiling the Mysteries of Latent Diffusion

Latent diffusion models are machine learning models designed to learn the underlying structure of a dataset by mapping it to a lower-dimensional latent space. This latent space represents the data in which the relationships between different data points are more easily understood and analyzed.

In the context of image generation, latent diffusion models are used to map the latent space of an image generator network to the space of text descriptions. This allows the model to generate images from text descriptions by sampling from the latent space and then using the image generator network to transform the samples into images.

Na the Challenges of Latent Diffusion

Despite the promise o usion models for creative image generation, there are a number of challenges and limitations to this approach.

The need for large amounts of high-quality training data: The model needs to learn the mapping between the latent space of the image generator network and the space of text descriptions, which requires a lot of data to do accurately.

Difficulty in generating highly detailed and realistic images: Latent diffusion models may still have some limitations in terms of the level of realism they are able to achieve because the image generator network may not be able to fully capture all of the subtle variations and nuances in the data, leading to some loss of realism in the generated images.

Difficulty in controlling the diversity of generated images: Latent diffusion models use a random process to sample the points in the latent space, which may lead to generating similar images or not being able to generate certain types of images.

Difficulty in controlling specific attributes of generated images: It is challenging to control the specific attributes of the generated images, such as the pose, lighting, and background of an object.

Limited ability to handle multi-modal data: Current models are not able to handle multi-modal data well, meaning it is difficult for the model to generate images that are a combination of different attributes or concepts.

Latent Diffusion in Action

There are a number of existing models that use latent diffusion for image generation.

Stable Diffusion Generative Adversarial Network (SD-GAN):

Developed by researchers at Stanford University

Uses stable diffusion to generate highly detailed and realistic images from text descriptions

Produces impressive results in a number of experimental studies

Latent Space Models (LSM) approach:

Developed by researchers at MIT

Works by mapping the latent space of an image generator network to the space of text descriptions

Allows it to generate highly detailed and realistic images from text descriptions

Has been used to generate a wide range of images, including faces, animals, and objects

Produces impressive results in a number of experimental studies

Other models that use latent diffusion for image generation:

Latent Adversarial Diffusion Network (LADN)

Latent Attribute Model (LAM)

These models have been used to generate a wide range of images and have demonstrated promising results in a number of experimental studies

The Future is Here: How Latent Diffusion is Transforming Industries?

Despite these challenges and limitations, latent diffusion models have the potential to revolutionize the way we create and share visual content. These models could significantly accelerate and enhance the creative process by enabling us to generate detailed and realistic images simply by describing them in words.

Latent diffusion models have a lot of potential applications beyond the image generation examples mentioned above. Some other potential applications that may be better than the existing applications include:

Video Generation: Latent diffusion models could be used to generate videos from text descriptions, allowing for the creation of realistic and highly detailed videos.

3D Model Generation: Latent diffusion models could be used to generate 3D models from text descriptions, allowing for the creation of highly detailed and realistic 3D models for use in video games, animation, and other applications.

Speech Generation: Latent diffusion models could be used to generate speech from text descriptions, creating realistic and natural-sounding speech.

Music Generation: Latent diffusion models could be used to generate music from text descriptions, allowing for the creation of highly detailed and realistic music.

Text-to-image Translation: Latent diffusion Models could be used to generate images from text descriptions with more control of the attributes of the image, resulting in more realistic and diverse outputs.

Multi-modal Generation: Latent diffusion models could be used to generate multi-modal outputs such as text-to-image-to-video, allowing for more diverse and realistic outputs.

Overall, these potential applications of latent diffusion models may be better than existing applications because they allow for more control and diversity in the generated outputs and may also be more useful in practical applications.

Wrapping Up

Overall, the use of latent diffusion models for creative image generation has the potential to greatly enhance and accelerate the creative process and is an exciting area of research and development in the field of artificial intelligence.

Latent diffusion models offer a promising approach to generating detailed and realistic images from text descriptions.

These models work by learning to map the latent space of an image generator network to the space of text descriptions, allowing them to generate images that are highly representative of the data.

However, this approach has challenges and limitations, including the need for large amounts of high-quality training data and the difficulty of generating fully realistic images.

I hope, you find this short article useful. Thank you for reading!

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Runners Map Lets You Easily Share And Discover Running Routes

Tracking and mapping your runs to a T is something most of us runners do, mainly because it provides valuable insights into your training progress. At the same time, there is something to be said about archiving runs for posterity and having the ability to review and show off older running tracks. The likes of Nike+ or Runtastic – i.e. the big players in the game – have recognised the immense potential of route tracking years ago and beefed up their apps accordingly.

A key caveat with those behemoth apps is the coerced reliance on them: in order to map and share your routes, any major app will insist you use their interface during the actual run as well. D’oh! you might think, and to some, this is not a massive sacrifice. To others however it’s a trade-off decision they grudgingly make.

Personally, I have grown fond of the simplicity of Apple’s Workout app on my Apple Watch and am content with its GPS tracking – but find myself wishing for a feature to share routes with fellow sports.

Runners Maps sets out to abstract the battle of the running platforms by separating the two key features major apps typically conflate: the running companion itself and the subsequent mapping and sharing.

In simpler terms, Runners Maps gives you the freedom to use whichever app you love the most during your workout, then grabs the data and feeds it into its own, bipartisan map. The third-party app deftly leverages iOS 11’s newly granted access to its HealthKit data, which enables the collection on neutral grounds. Runners Maps makes a point proclaiming that no sensitive data is being accessed or uploaded during the process.

The post-run running app

Now that we have warmed up, time to get to the nitty gritty. What – and perhaps more crucially who – is this thing good for?

While the idea to learn of the most popular running locations in a place otherwise unbeknown to you is not without precedence, Runners Map’s bloat-free, and above all unaffiliated approach certainly is. Filters to apply to the map are still few and far between, but the most important one – running distance – can be toggled on to define lower and upper distance limits. Another upside with Runners Map is that the app can be used retroactively and you do not need the presence of mind to hit a button before you start your jog.

Who should consider giving this app a crack? At this point in time, I can think of two and a half good use cases for it. Everyone enjoys a good scratch map and if you love to leave a visible mark on locations you have conquered in your trainers, this is an easy way of doing it. Next, there’s the altruistic motive to let fellow runners in on your favorite tracks. If you know some mean routes and want to help others discover them, uploading them through Runners Map is a breeze.

Reason two and a half should naturally be number three, however owing to the app’s young age its database of run entries still comes up a little too short to sincerely plug it as such to you. Especially in the US, you’re basically looking at a clean slate with a few exception depending on your location. This is bound to change quickly – and already has in Europe – when the app picks up steam, but for now there remains a lot of route data collection to be done for all US runners out there.

If you want to give Runners Map a shake, download it on the App Store for free.

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