Mobile subscriptions are defined as the number of active SIM cards. It includes both voice and data services, installed in telephones, modem, usb keys or other devices.

Original source

Electronic communications market indicators collected by Commission services, through National Regulatory Authorities, for the Communications Committee (COCOM) - January and July reports.:

http://ec.europa.eu/digital-agenda/about-fast-and-ultra-fast-internet-access

Parent dataset

This dataset is part of of another dataset:

http://digital-agenda-data.eu/datasets/digital_agenda_scoreboard_key_indicators

In Italy, prepaid SIM cards increased from accounting for **** percent of all mobile data SIM cards in 2016 to **** percent in 2023. Consequently, post-paid subscriptions decreased from **** percent of mobile SIM contracts in 2016 to **** percent as of December 2023.

SIM Cards Market Outlook

In 2023, the global SIM cards market size was valued at approximately USD 3.5 billion, and it is projected to reach USD 5.8 billion by 2032, growing at a CAGR of 5.3% during the forecast period. The SIM cards market is experiencing substantial growth driven by the continuous demand for mobile connectivity, advancements in mobile network technology, and the increasing penetration of smartphones and other connected devices.

The rapid adoption of smartphones worldwide is a major growth factor for the SIM cards market. With the proliferation of affordable smartphones, especially in emerging markets, the demand for SIM cards has been steadily increasing. Moreover, the shift towards 5G technology is further propelling this growth. As telecommunications providers upgrade their infrastructure to support 5G networks, the need for advanced SIM cards that can handle higher data speeds and enhanced connectivity features is becoming crucial. Additionally, the growing trend of multiple SIM card usage among consumers, who prefer to switch between different service providers for better coverage and competitive pricing, is contributing to the market expansion.

Another significant growth factor is the rising demand for machine-to-machine (M2M) communication and the Internet of Things (IoT). Embedded SIM cards (eSIMs), which are soldered directly onto a device's circuit board, are becoming increasingly popular in IoT applications due to their smaller size and greater versatility. These eSIMs enable seamless connectivity for wearable devices, automotive applications, and smart home devices, among others. The expanding IoT ecosystem, which encompasses a wide range of applications from smart cities to industrial automation, is creating new opportunities for the SIM cards market.

Additionally, the increased focus on security and authentication is driving the adoption of advanced SIM card technologies. SIM cards play a crucial role in securing mobile communications by providing robust authentication and encryption mechanisms. With the rising concerns about data breaches and cyber threats, there is a growing emphasis on enhancing the security features of SIM cards. This has led to the development of new technologies such as SIM-based authentication for secure access to online services and mobile payments.

Regionally, the Asia Pacific region dominates the SIM cards market, owing to the large population base, high smartphone penetration, and significant investments in telecommunications infrastructure. Countries like China, India, and Japan are major contributors to the market growth in this region. North America and Europe also hold substantial market shares due to the presence of advanced telecom networks and high consumer demand for connected devices. The Middle East & Africa and Latin America regions are witnessing steady growth, driven by the increasing adoption of mobile technologies and the expansion of telecom networks.

Type Analysis

The SIM cards market by type includes Standard SIM, Micro SIM, Nano SIM, and Embedded SIM (eSIM). Standard SIM cards, being the first generation of SIM cards, are still in use but are gradually being phased out in favor of more compact versions. The transition from Standard SIM to Micro and Nano SIM cards has been driven by the need to save space within mobile devices, allowing manufacturers to design slimmer and more feature-rich devices. Micro SIM cards, which were introduced to address the space constraints of mobile devices, became widely adopted in the early 2010s. However, they too are being replaced by smaller Nano SIM cards, which have become the industry standard for most modern smartphones and tablets.

Nano SIM cards offer the same functionality as their predecessors but in a significantly smaller form factor, which is essential for the latest generation of mobile devices that prioritize sleek designs and increased battery capacity. The adoption of Nano SIM cards is expected to continue growing as new smartphones and other connected devices are launched. Additionally, the ongoing trend of miniaturization in consumer electronics further propels the demand for these compact SIM cards. These advancements cater to the industry's push towards enhanced user experiences through design and hardware optimization.

Embedded SIM cards (eSIMs) represent a significant technological advancement in the SIM card industry. Unlike traditional removable SIM cards, eSIMs are embedded directly into the device's hardware, offering several advantages such as improved security, bette

Dataset Card for TRANSIC Data

This dataset card is accompanied with the CoRL 2024 paper titled TRANSIC: Sim-to-Real Policy Transfer by Learning from Online Correction. It includes generated simulation data and real-robot human correction data for sim-to-real transfer of robotic arm manipulation policies.

  Dataset Details





  Dataset Description

This dataset includes two parts, 1) simulation data used in student policy distillation and 2) real-robot data used in… See the full description on the dataset page: https://huggingface.co/datasets/transic-robot/data.

High-quality oxygen isotope analysis of composition-variable minerals (e.g., ubiquitous carbonates) using secondary ion mass spectrometry (SIMS) is extremely challenging. The classical off-line procedure, which requires additional electron probe microanalyzer (EPMA) chemical compositions for calibrating instrumental mass fractionation (IMF), is inherently inaccurate and analytically inefficient. In this study, the first accurate and paired SIMS analysis of δ18O and Fe# [molar Fe/(Mg + Fe)] in dolomite is reported. Based on five newly developed dolomite O-isotopic standards with an Fe# range of 0.01–0.35 obtained by SIMS, a novel accurate and rapid online matrix effect calibration method for dolomite O-isotope analysis was developed using concurrent SIMS 18O–16O–56Fe16O–24Mg16O measurements without additional chemical electron probe microanalysis. A logistic equation was proposed as the best-fit curve to represent the δ18O matrix effect based on the 56Fe16O/24Mg16O ratios. For CTD-4 carbonatitic dolomite with variable Fe# but homogeneous oxygen isotopes, the off-line method exhibited highly variable apparent δ18O values in the range of 5.74–10.11‰. The online method yielded a homogeneous δ18O value of 7.94 ± 0.34‰ (2SD, n = 40), which is comparable with that of bulk analysis (7.94 ± 0.20‰; 2SD). Comprehensive analyses validated the online method as the best strategy for performing accurate δ18O analysis of samples with highly heterogeneous compositions. Based on its accuracy, simplicity, and economic feasibility, this method has potential applications in the analysis of composition-complex dolomites, detrital dolomites, and other precious terrestrial and extraterrestrial materials.

Arbor library version 0.2, tagged as v0.2. Arbor is a library for implementing performance portable network simulations of multi-compartment neuron models.An installation guide and library documentation are available online at Read the Docs. Submit a ticket if you have any questions or want help. Some key features include: Optimized back ends for CUDA, KNL, AVX2, ARM NEON intrinsics. Asynchronous spike exchange that overlaps compute and communication. Efficient sampling of voltage and current on all back ends. Efficient implementation of all features on GPU. Reporting of memory and energy consumption (when available on platform). An API for addition of new cell types, e.g. LIF and Poisson spike generators. Change Log Changes since v0.1: A new Hines matrix solver back end for the GPU that parallelises over cell branches, not cells, to increase the amount of parallelism. See #631. Support for describing and simulating electrical gap junctions. See #661 #686. An additional library libarborenv is now installed with useful helper functionality for managing the environment (e.g. detecting the number of available CPU cores). See #679. Detection and allocation of GPUs to MPI ranks on systems with more than one GPU per node in libarborenv. See #659 and #654. The miniapp example was removed and replaced with a simple single cell model that shows how to use morphologies. See #703 and #710.Support for ARM NEON intrinsics. See #698. Basic Python support. Full Python support is slated for v0.3. See #668. Contributors Nora Abi Akar John Biddiscombe Benjamin Cumming Felix Huber Marko Kabic Vasileios Karakasis Wouter Klijn Anne Küsters Alexander Peyser Stuart Yates

Prepaid Communication Market size was valued at USD 1200 Billion in 2024 and is projected to reach USD 1819 Billion by 2032, growing at a CAGR of 5.4% from 2026 to 2032.The market drivers for the prepaid communication market can be influenced by various factors. These may include:Demand for Budget Control: Use of prepaid plans continues to be driven by demand for cost management, particularly across regions where disposable income remains low or fluctuates frequently.Mobile Penetration in Developing Areas: Prepaid subscriptions tend to be preferred as mobile phone access is expanded in rural and underserved communities without credit requirements.

Aplikasi SIM APBS Online Dinas Pendidikan Kota Semarang

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Reliance Jio was the leading company with a wireless telecom subscriber base of over 465 million across India as of December 2024. The south Asian country was the second-largest telecom market worldwide. The number of mobile subscribers in India amounted to around 1.15 billion in the same year. The country also achieved a 100 percent digitalization of the cable television network in 2019. Reliance JioReliance Jio is the subsidiary of Jio Platforms, the digital services segment of the Reliance Industries. The company only operates a 5G and LTE network and does not offer 2G or 3G services. Launched in December 2015 as Jio soft, it became publicly available in September 2016. The company is the largest mobile operator in India, and the third-largest network operator in the world. At the end of financial year 2024, the operating revenue of Reliance Jio was around 1.3 trillion Indian rupees. Telecom sector outlookThe telecom equipment sector revenue was estimated to be 3.36 trillion Indian rupees in 2024. The number of internet subscribers has grown more than five times in the last decade. It was estimated, by 2029, the internet users in the country will surpass 1.2 billion.

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