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License information was derived automatically
Attributes of sites in Hamilton City which collect anonymised data from a sample of vehicles. Note: A Link is the section of the road between two sites
Column_InfoSite_Id, int : Unique identiferNumber, int : Asset number. Note: If the site is at a signalised intersection, Number will match 'Site_Number' in the table 'Traffic Signal Site Location'Is_Enabled, varchar : Site is currently enabledDisabled_Date, datetime : If currently disabled, the date at which the site was disabledSite_Name, varchar : Description of the site locationLatitude, numeric : North-south geographic coordinatesLongitude, numeric : East-west geographic coordinates
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Disclaimer
Hamilton City Council does not make any representation or give any warranty as to the accuracy or exhaustiveness of the data released for public download. Levels, locations and dimensions of works depicted in the data may not be accurate due to circumstances not notified to Council. A physical check should be made on all levels, locations and dimensions before starting design or works.
Hamilton City Council shall not be liable for any loss, damage, cost or expense (whether direct or indirect) arising from reliance upon or use of any data provided, or Council's failure to provide this data.
While you are free to crop, export and re-purpose the data, we ask that you attribute the Hamilton City Council and clearly state that your work is a derivative and not the authoritative data source. Please include the following statement when distributing any work derived from this data:
‘This work is derived entirely or in part from Hamilton City Council data; the provided information may be updated at any time, and may at times be out of date, inaccurate, and/or incomplete.'
Be ready for a cookieless internet while capturing anonymous website traffic data!
By installing the resolve pixel onto your website, business owners can start to put a name to the activity seen in analytics sources (i.e. GA4). With capture/resolve, you can identify up to 40% or more of your website traffic. Reach customers BEFORE they are ready to reveal themselves to you and customize messaging toward the right product or service.
This product will include Anonymous IP Data and Web Traffic Data for B2B2C.
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Mobile accounts for approximately half of web traffic worldwide. In the last quarter of 2024, mobile devices (excluding tablets) generated 62.54 percent of global website traffic. Mobiles and smartphones consistently hoovered around the 50 percent mark since the beginning of 2017, before surpassing it in 2020. Mobile traffic Due to low infrastructure and financial restraints, many emerging digital markets skipped the desktop internet phase entirely and moved straight onto mobile internet via smartphone and tablet devices. India is a prime example of a market with a significant mobile-first online population. Other countries with a significant share of mobile internet traffic include Nigeria, Ghana and Kenya. In most African markets, mobile accounts for more than half of the web traffic. By contrast, mobile only makes up around 45.49 percent of online traffic in the United States. Mobile usage The most popular mobile internet activities worldwide include watching movies or videos online, e-mail usage and accessing social media. Apps are a very popular way to watch video on the go and the most-downloaded entertainment apps in the Apple App Store are Netflix, Tencent Video and Amazon Prime Video.
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License information was derived automatically
Code:
Packet_Features_Generator.py & Features.py
To run this code:
pkt_features.py [-h] -i TXTFILE [-x X] [-y Y] [-z Z] [-ml] [-s S] -j
-h, --help show this help message and exit -i TXTFILE input text file -x X Add first X number of total packets as features. -y Y Add first Y number of negative packets as features. -z Z Add first Z number of positive packets as features. -ml Output to text file all websites in the format of websiteNumber1,feature1,feature2,... -s S Generate samples using size s. -j
Purpose:
Turns a text file containing lists of incomeing and outgoing network packet sizes into separate website objects with associative features.
Uses Features.py to calcualte the features.
startMachineLearning.sh & machineLearning.py
To run this code:
bash startMachineLearning.sh
This code then runs machineLearning.py in a tmux session with the nessisary file paths and flags
Options (to be edited within this file):
--evaluate-only to test 5 fold cross validation accuracy
--test-scaling-normalization to test 6 different combinations of scalers and normalizers
Note: once the best combination is determined, it should be added to the data_preprocessing function in machineLearning.py for future use
--grid-search to test the best grid search hyperparameters - note: the possible hyperparameters must be added to train_model under 'if not evaluateOnly:' - once best hyperparameters are determined, add them to train_model under 'if evaluateOnly:'
Purpose:
Using the .ml file generated by Packet_Features_Generator.py & Features.py, this program trains a RandomForest Classifier on the provided data and provides results using cross validation. These results include the best scaling and normailzation options for each data set as well as the best grid search hyperparameters based on the provided ranges.
Data
Encrypted network traffic was collected on an isolated computer visiting different Wikipedia and New York Times articles, different Google search queres (collected in the form of their autocomplete results and their results page), and different actions taken on a Virtual Reality head set.
Data for this experiment was stored and analyzed in the form of a txt file for each experiment which contains:
First number is a classification number to denote what website, query, or vr action is taking place.
The remaining numbers in each line denote:
The size of a packet,
and the direction it is traveling.
negative numbers denote incoming packets
positive numbers denote outgoing packets
Figure 4 Data
This data uses specific lines from the Virtual Reality.txt file.
The action 'LongText Search' refers to a user searching for "Saint Basils Cathedral" with text in the Wander app.
The action 'ShortText Search' refers to a user searching for "Mexico" with text in the Wander app.
The .xlsx and .csv file are identical
Each file includes (from right to left):
The origional packet data,
each line of data organized from smallest to largest packet size in order to calculate the mean and standard deviation of each packet capture,
and the final Cumulative Distrubution Function (CDF) caluclation that generated the Figure 4 Graph.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This is a dataset of Tor cell file extracted from browsing simulation using Tor Browser. The simulations cover both desktop and mobile webpages. The data collection process was using WFP-Collector tool (https://github.com/irsyadpage/WFP-Collector). All the neccessary configuration to perform the simulation as detailed in the tool repository.The webpage URL is selected by using the first 100 website based on: https://dataforseo.com/free-seo-stats/top-1000-websites.Each webpage URL is visited 90 times for each deskop and mobile browsing mode.
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The global website traffic analysis tool market is experiencing robust growth, driven by the increasing reliance on digital marketing and the need for businesses of all sizes to understand their online audience. The market, estimated at $15 billion in 2025, is projected to grow at a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors. The rising adoption of cloud-based solutions provides scalability and cost-effectiveness for businesses, particularly SMEs seeking affordable analytics. Moreover, the evolution of sophisticated analytics features, including advanced user behavior tracking and predictive analytics, enhances the value proposition for both SMEs and large enterprises. The market is segmented by application (SMEs and large enterprises) and by type (cloud-based and web-based), with cloud-based solutions dominating due to their accessibility and flexibility. Competitive pressures among numerous vendors, including established players like Google Analytics, Semrush, and Ahrefs, as well as emerging niche players, drive innovation and affordability, benefiting users. Geographic distribution shows strong growth across North America and Europe, with Asia-Pacific emerging as a high-growth region. However, factors such as data privacy concerns and the increasing complexity of website analytics can act as potential restraints. Despite these challenges, the continued expansion of e-commerce and digital marketing strategies across various industries will solidify the demand for robust website traffic analysis tools. The market is expected to witness further consolidation through mergers and acquisitions, with leading players investing heavily in research and development to enhance their offerings. The increasing need for real-time data analysis and integration with other marketing automation platforms will further shape market evolution. The emergence of AI-powered analytics, providing predictive insights and automated reporting, is transforming the industry and will continue to drive market expansion in the coming years. This makes this market an attractive landscape for investors and technology providers looking for strong future growth.
Between July and September 2022, BYJU's emerged as the top Ed Tech platform for K12 and test preparation In India. It recorded approximately *** million website visits. Following closely behind was Toppr.com, with around *** million visits during the same period.
In November 2021, mobile devices accounted for nearly ** percent of the web traffic to Google.com in Kenya. The website had the highest number of total visits in the country. Among the leading websites, most of them had a higher share of traffic from mobile. Youtube.com was an exception, with only ********* of its traffic originating from mobile devices.
In November 2024, Google.com was the most popular website worldwide with 136 billion average monthly visits. The online platform has held the top spot as the most popular website since June 2010, when it pulled ahead of Yahoo into first place. Second-ranked YouTube generated more than 72.8 billion monthly visits in the measured period. The internet leaders: search, social, and e-commerce Social networks, search engines, and e-commerce websites shape the online experience as we know it. While Google leads the global online search market by far, YouTube and Facebook have become the world’s most popular websites for user generated content, solidifying Alphabet’s and Meta’s leadership over the online landscape. Meanwhile, websites such as Amazon and eBay generate millions in profits from the sale and distribution of goods, making the e-market sector an integral part of the global retail scene. What is next for online content? Powering social media and websites like Reddit and Wikipedia, user-generated content keeps moving the internet’s engines. However, the rise of generative artificial intelligence will bring significant changes to how online content is produced and handled. ChatGPT is already transforming how online search is performed, and news of Google's 2024 deal for licensing Reddit content to train large language models (LLMs) signal that the internet is likely to go through a new revolution. While AI's impact on the online market might bring both opportunities and challenges, effective content management will remain crucial for profitability on the web.
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License information was derived automatically
## Overview
Only Test Site Korean Traffic Light 2 is a dataset for object detection tasks - it contains Green Red Left PZAm annotations for 2,038 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
## Overview
Traffic Checker is a dataset for object detection tasks - it contains Street Objects And Person annotations for 574 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
In 2022, notion.so held the leading position as the most popular startup website in the United States and Europe based on global traffic. The workspace platform, which launched in 2013, saw over ***** million monthly website visits on average in the examined year. The U.S.-based visual tool Miro.com came in second, generating almost ** million average monthly visits from users worldwide. Additionally, the website of the startup accelerator Y Combinator ranked third with approximately ** million monthly visits.
CIRA-CIC-DoHBrw-2020-and-DoH-Tunnel-Traffic-HKD.zip: If you use the dataset, please be sure to cite the following papers because the dataset has data from the CIRA-CIC-DoHBrw-2020 [1] and DoH-Tunnel-Traffic-HKD [2] datasets. Mohammadreza MontazeriShatoori, Logan Davidson, Gurdip Kaur, and Arash Habibi Lashkari, "Detection of DoH Tunnels using Time-series Classification of Encrypted Traffic," The 5th IEEE Cyber Science and Technology Congress, Calgary, Canada, August 2020. https://ieeexplore.ieee.org/document/9251211 Rikima Mitsuhashi, Yong Jin, Katsuyoshi Iida, Takahiro Shinagawa, and Yoshiaki Takai, "Malicious DNS Tunnel Tool Recognition using Persistent DoH Traffic Analysis," in IEEE Transactions on Network and Service Management, 2022. https://ieeexplore.ieee.org/document/9924534
In March 2024, search platform Google.com generated approximately 85.5 billion visits, down from 87 billion platform visits in October 2023. Google is a global search platform and one of the biggest online companies worldwide.
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edX Statistics: In this digital era, online learning has developed into a powerful tool for education and career enhancement. Among many platforms in this regard, edX is a key provider of Massive Open Online Courses (MOOCs). Founded by Harvard University and MIT, edX grew in 2012 and has continued to do so by offering thousands of courses in various fields. In 2024, edX has achieved new milestones in terms of its users, revenue, partnerships, and courses.
This article shall look at the latest edX statistics concerning its influence on learners and the future of education.
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The WordPress Site Management Software market size is projected to experience robust growth in the coming years, with a forecasted CAGR of 8.6% from 2024 to 2032. In 2023, the market was valued at approximately USD 2.8 billion, and it is expected to reach an impressive USD 5.8 billion by 2032. This significant growth can be attributed to various factors including the rising demand for efficient website management solutions, the proliferation of online businesses, and the increasing adoption of digital platforms for content management and e-commerce purposes.
A critical growth factor fueling the WordPress Site Management Software market is the surging popularity of WordPress as a content management system (CMS). WordPress powers over 40% of websites globally, making it an indispensable tool for bloggers, e-commerce platforms, and enterprises looking to enhance their online presence. The easy-to-use interface, vast library of plugins and themes, and a strong community of developers contribute to WordPress's dominance in the CMS space. As businesses increasingly recognize the importance of maintaining dynamic and user-friendly websites, the demand for comprehensive management software that optimizes WordPress functionalities continues to rise.
Another key driver of market growth is the continuous evolution of digital marketing strategies and the need for personalized user experiences. Businesses are investing in WordPress site management software to harness data analytics, SEO optimization, and content customization tools that enhance visitor engagement and conversion rates. The shift towards a more digital-centric business environment, accelerated by the COVID-19 pandemic, has made it crucial for enterprises to adopt solutions that streamline content creation, web performance monitoring, and security management. As a result, the demand for sophisticated management software that can handle these tasks efficiently is on the rise.
The growing trend of remote work and the need for remote collaboration tools also contribute to the expanding WordPress Site Management Software market. With teams dispersed across various locations, enterprises require robust software solutions that enable seamless website updates, content management, and workflow automation. Cloud-based deployment options have gained traction as they offer flexibility, scalability, and accessibility, aligning perfectly with the needs of a remote workforce. This trend is expected to continue, further driving the adoption of WordPress site management solutions globally.
In the realm of digital solutions, Link Management Software has emerged as a pivotal tool for businesses aiming to optimize their online presence. This software facilitates the organization, tracking, and management of hyperlinks across various digital platforms, ensuring that businesses maintain a coherent and efficient web strategy. By automating the process of link monitoring and reporting, Link Management Software helps enterprises prevent broken links, improve SEO performance, and enhance user experience. As digital landscapes become increasingly complex, the integration of such software into WordPress site management solutions becomes essential, offering a streamlined approach to maintaining website integrity and boosting online visibility.
Regionally, North America holds a significant share of the WordPress Site Management Software market, driven by the presence of major technology companies and a high concentration of digital content creators and e-commerce businesses. The region's advanced infrastructure and early adoption of innovative technologies contribute to this dominance. However, the Asia Pacific region is anticipated to experience the fastest growth during the forecast period, with a projected CAGR of 9.2%. The increasing digitization of businesses, rising internet penetration, and the growth of the e-commerce sector in emerging economies like China and India are key factors propelling market expansion in this region. Europe and Latin America are also witnessing steady growth due to the increasing importance of digital platforms in business strategies.
The WordPress site management software market is segmented by components into plugins, themes, and services. Plugins represent a critical aspect of this market, offering extended functionalities to WordPress websites. The popularity of plugins stems from their ability to enhance
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General data recollected for the studio " Analysis of the Quantitative Impact of Social Networks on Web Traffic of Cybermedia in the 27 Countries of the European Union".
Four research questions are posed: what percentage of the total web traffic generated by cybermedia in the European Union comes from social networks? Is said percentage higher or lower than that provided through direct traffic and through the use of search engines via SEO positioning? Which social networks have a greater impact? And is there any degree of relationship between the specific weight of social networks in the web traffic of a cybermedia and circumstances such as the average duration of the user's visit, the number of page views or the bounce rate understood in its formal aspect of not performing any kind of interaction on the visited page beyond reading its content?
To answer these questions, we have first proceeded to a selection of the cybermedia with the highest web traffic of the 27 countries that are currently part of the European Union after the United Kingdom left on December 31, 2020. In each nation we have selected five media using a combination of the global web traffic metrics provided by the tools Alexa (https://www.alexa.com/), which ceased to be operational on May 1, 2022, and SimilarWeb (https:// www.similarweb.com/). We have not used local metrics by country since the results obtained with these first two tools were sufficiently significant and our objective is not to establish a ranking of cybermedia by nation but to examine the relevance of social networks in their web traffic.
In all cases, cybermedia whose property corresponds to a journalistic company have been selected, ruling out those belonging to telecommunications portals or service providers; in some cases they correspond to classic information companies (both newspapers and televisions) while in others they refer to digital natives, without this circumstance affecting the nature of the research proposed.
Below we have proceeded to examine the web traffic data of said cybermedia. The period corresponding to the months of October, November and December 2021 and January, February and March 2022 has been selected. We believe that this six-month stretch allows possible one-time variations to be overcome for a month, reinforcing the precision of the data obtained.
To secure this data, we have used the SimilarWeb tool, currently the most precise tool that exists when examining the web traffic of a portal, although it is limited to that coming from desktops and laptops, without taking into account those that come from mobile devices, currently impossible to determine with existing measurement tools on the market.
It includes:
Web traffic general data: average visit duration, pages per visit and bounce rate Web traffic origin by country Percentage of traffic generated from social media over total web traffic Distribution of web traffic generated from social networks Comparison of web traffic generated from social netwoks with direct and search procedures
In January 2025 mobile devices excluding tablets accounted for over ** percent of web page views worldwide. Meanwhile, over ** percent of webpage views in Africa were generated via mobile. In contrast, just over half of web traffic in North America still took place via desktop connections with mobile only accounting for **** percent of total web traffic. While regional infrastructure remains an important factor in broadband vs. mobile coverage, most of the world has had their eyes on the recent 5G rollout across the globe, spearheaded by tech-leaders China and the United States. The number of mobile 5G subscriptions worldwide is forecast to reach more than ***** billion by 2028. Social media: room for growth in Africa and southern Asia Overall, more than ** percent of the world’s mobile internet subscribers are also active on social media. A fast-growing market, with newcomers such as TikTok taking the world by storm, marketers have been cashing in on social media’s reach. Overall, social media penetration is highest in Europe and America while in Africa and southern Asia, there is still room for growth. As of 2021, Facebook and Google-owned YouTube are the most popular social media platforms worldwide. Facebook and Instagram are most effective With nearly ***** billion users, it is no wonder that Facebook remains the social media avenue of choice for the majority of marketers across the world. Instagram, meanwhile, was the second most popular outlet. Both platforms are low-cost and support short-form content, known for its universal consumer appeal and answering to the most important benefits of using these kind of platforms for business and advertising purposes.
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The website speed test market has witnessed significant growth, reaching a market size of XXX million in 2025. This growth is primarily attributed to the increasing demand for faster and more reliable internet speeds, driven by the widespread adoption of streaming video, online gaming, and cloud-based applications. The CAGR of the market is projected to remain strong over the forecast period from 2023 to 2033, reaching a value of XXX million by 2033. Key market trends include the growing adoption of 5G networks and the increasing popularity of fiber optic internet, both of which offer significantly faster speeds compared to traditional copper-based connections. In terms of segmentation, the market for website speed test can be divided into two main types: cable internet and fiber optic internet. Cable internet is currently the most widely used type of broadband internet connection, but fiber optic internet is rapidly gaining popularity due to its superior speed and reliability. Other types of broadband internet connections include fixed wireless internet, satellite internet, and DSL internet. The market can also be segmented based on its application, with individuals and businesses being the two primary user groups. Businesses typically require faster and more reliable internet speeds than individuals, and are therefore more likely to invest in higher-end solutions such as fiber optic internet. Major companies in the website speed test market include Fusion Connect, Bandwidth Place, Ookla, Netflix, and Measurement Lab, among others.
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The global website analytics tool market is experiencing robust growth, driven by the increasing need for businesses of all sizes to understand their online audience and optimize their digital strategies. The market, valued at approximately $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This substantial growth is fueled by several key factors. The rising adoption of cloud-based solutions offers scalability, cost-effectiveness, and accessibility for businesses, regardless of their technical expertise. Furthermore, the expanding use of mobile devices and the proliferation of data are creating a surge in demand for sophisticated analytics tools capable of providing real-time insights into user behavior, campaign performance, and website effectiveness. The market is segmented by deployment (cloud-based and on-premises) and user type (SMEs and large enterprises), with the cloud-based segment dominating due to its inherent advantages. Competitive pressures are intensifying, with established players like Google Analytics and Adobe Analytics facing competition from agile startups offering innovative features and pricing models. While data privacy concerns and the complexity of implementing and interpreting analytics data pose challenges, the overall market trajectory remains overwhelmingly positive, underpinned by continued digital transformation across industries and a growing awareness of the importance of data-driven decision-making. The regional distribution of the market reflects the global landscape of digital adoption, with North America and Europe currently holding significant market shares. However, the Asia-Pacific region is expected to witness the fastest growth in the coming years, driven by rapid economic development and increasing internet penetration. This presents substantial opportunities for both established players and new entrants in the market. The future will likely see further integration of website analytics with other marketing technologies, the rise of AI-powered analytics capabilities offering predictive insights, and a greater emphasis on data security and compliance. This dynamic environment necessitates continuous innovation and adaptation for businesses operating within the website analytics tool market.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Attributes of sites in Hamilton City which collect anonymised data from a sample of vehicles. Note: A Link is the section of the road between two sites
Column_InfoSite_Id, int : Unique identiferNumber, int : Asset number. Note: If the site is at a signalised intersection, Number will match 'Site_Number' in the table 'Traffic Signal Site Location'Is_Enabled, varchar : Site is currently enabledDisabled_Date, datetime : If currently disabled, the date at which the site was disabledSite_Name, varchar : Description of the site locationLatitude, numeric : North-south geographic coordinatesLongitude, numeric : East-west geographic coordinates
Relationship
Disclaimer
Hamilton City Council does not make any representation or give any warranty as to the accuracy or exhaustiveness of the data released for public download. Levels, locations and dimensions of works depicted in the data may not be accurate due to circumstances not notified to Council. A physical check should be made on all levels, locations and dimensions before starting design or works.
Hamilton City Council shall not be liable for any loss, damage, cost or expense (whether direct or indirect) arising from reliance upon or use of any data provided, or Council's failure to provide this data.
While you are free to crop, export and re-purpose the data, we ask that you attribute the Hamilton City Council and clearly state that your work is a derivative and not the authoritative data source. Please include the following statement when distributing any work derived from this data:
‘This work is derived entirely or in part from Hamilton City Council data; the provided information may be updated at any time, and may at times be out of date, inaccurate, and/or incomplete.'