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Topic Review
Requirements of Compression in Key-Value Stores
A key–value store is a de facto standard database for unstructured big data. Key–value stores, such as Google’s LevelDB and Meta’s RocksDB, have emerged as a popular solution for managing unstructured data due to their ability to handle diverse data types with a simple key–value abstraction. Simultaneously, a multitude of data management tools have actively adopted compression techniques, such as Snappy and Zstd, to effectively reduce data volume.
  • 582
  • 27 Oct 2023
Topic Review
MIMO Wireless Signals
This entry presents a comprehensive, contemporary review of the latest subsystems, architectures and integrated technologies of MIMO wireless signals backhauling using optical fibre or fibre access networks, such as passive optical networks (PONs).
  • 581
  • 09 Feb 2021
Topic Review
Remote Keyless Using Pre-Trained Deep Neural Network
Keyless systems have replaced the old-fashioned methods of inserting physical keys into keyholes to unlock the door, which are inconvenient and easily exploited by threat actors. Keyless systems use the technology of radio frequency (RF) as an interface to transmit signals from the key fob to the vehicle.
  • 581
  • 10 Nov 2022
Topic Review
Computational Biology in Drug Design
Traditional drug design requires a great amount of research time and developmental expense. Booming computational approaches, including computational biology, computer-aided drug design, and artificial intelligence, have the potential to expedite the efficiency of drug discovery by minimizing the time and financial cost. In recent years, computational approaches are being widely used to improve the efficacy and effectiveness of drug discovery and pipeline, leading to the approval of plenty of new drugs for marketing. The present review emphasizes on the applications of these indispensable computational approaches in aiding target identification, lead discovery, and lead optimization. Some challenges of using these approaches for drug design are also discussed. Moreover, researchers propose a methodology for integrating various computational techniques into new drug discovery and design.
  • 581
  • 28 Nov 2022
Topic Review
Power Supply for Wearables with Task Offloading Capabilities
Task-offloading approaches can be efficiently combined with energy harvesting to address the issue of insufficient battery capacity and limited computation resources in IoMT devices and consequently increase the operating time of wearable devices. This is referred to as joint energy harvesting and task offloading. Using this technology, users can extract energy, convert it into useful energy, store it in the appropriate energy-storage device, and use that energy to perform the corresponding local computing and offloading tasks.
  • 580
  • 18 Feb 2022
Topic Review
Wearable Travel Aids for Blind/Partially Sighted People
The ability to travel (independently) is very important for participation in education, work, leisure activities, and all other aspects of modern life. Blind and partially sighted people experience a number of barriers to travel, including inaccessible information and environments, and consequently require support from technology or other people to overcome them. 
  • 580
  • 11 Aug 2022
Topic Review
Power Soccer (Browser-based Game)
Power Soccer, also known as Power Challenge and PS, was a massively multiplayer online browser-based sports game, developed by the Swedish developer Power Challenge, the same company that develops ManagerZone (but PS focuses in the sports gameplay instead of management simulation). This game was a browser-based soccer simulator in which users could create a team and play against other users from all around the globe. Additional benefits were offered to those that purchased the Club Membership. Following a decline in interest from users in the game, it was announced that on May 16, 2016 Power Soccer would come to an end, encouraging users to join their sister game ManagerZone. The announcement was made months before the closure date, which led to many posts in the forums where some users even wanted to donate to keep the game afloat but to no avail, and in the early hours of May 16, 2016, the game closed.
  • 580
  • 27 Sep 2022
Topic Review
Perl Compatible Regular Expressions
Perl Compatible Regular Expressions (PCRE) is a library written in C, which implements a regular expression engine, inspired by the capabilities of the Perl programming language. Philip Hazel started writing PCRE in summer 1997. PCRE's syntax is much more powerful and flexible than either of the POSIX regular expression flavors (BRE, ERE) and than that of many other regular-expression libraries. While PCRE originally aimed at feature-equivalence with Perl, the two implementations are not fully equivalent. During the PCRE 7.x and Perl 5.9.x phase, the two projects have coordinated development, with features being ported between them in both directions. In 2015 a fork of PCRE was released with a revised programming interface (API). The original software, now called PCRE1 (the 1.xx–8.xx series), has had bugs mended, but no further development. (As of 2020), it is considered obsolete, and the current 8.45 release is likely to be the last. The new PCRE2 code (the 10.xx series) has had a number of extensions and coding improvements and is where development takes place. A number of prominent open-source programs, such as the Apache and Nginx HTTP servers, and the PHP and R scripting languages, incorporate the PCRE library; proprietary software can do likewise, as the library is BSD-licensed. As of Perl 5.10, PCRE is also available as a replacement for Perl's default regular-expression engine through the "re::engine::PCRE" module. The library can be built on Unix, Windows, and several other environments. PCRE2 is distributed with a POSIX C wrapper, several test programs, and the utility program "pcre2grep" built in tandem with the library.
  • 580
  • 14 Nov 2022
Topic Review
Machine Learning for Hydropower Generation
Hydropower is the most prevalent source of renewable energy production worldwide. As the global demand for robust and ecologically sustainable energy production increases, developing and enhancing the current energy production processes is essential. In the past decade, machine learning has contributed significantly to various fields, and hydropower is no exception. All three horizons of hydropower models could benefit from machine learning: short-term, medium-term, and long-term. Dynamic programming is used in the majority of hydropower scheduling models.
  • 580
  • 27 Jun 2023
Topic Review
Data-Driven Learning Methods for Network Intrusion Detection Systems
An effective anomaly-based intelligent IDS (AN-Intel-IDS) must detect both known and unknown attacks. Hence, there is a need to train AN-Intel-IDS using dynamically generated, real-time data in an adversarial setting. Furthermore, the lack of real-time data produces potentially biased models that are less effective in predicting unknown attacks. Therefore, training AN-Intel-IDS using imbalanced and adversarial learning is instrumental to their efficacy and high performance. Unfortunately, the public datasets available to train AN-Intel-IDS are ineluctably static, unrealistic, and prone to obsolescence. Furthermore, the lack of real-time data produces potentially biased models that are less effective in predicting unknown attacks. Therefore, training AN-Intel-IDS using imbalanced and adversarial learning is instrumental to their efficacy and high performance. 
  • 579
  • 28 Feb 2022
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