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Topic Review
Cycle Process of High-Temperature Heat Pump
The high-temperature heat pump, as a low-carbonization technology, has broad application prospects in replacing boiler heating, reducing carbon dioxide emissions, and improving the energy utilization efficiency.
  • 338
  • 25 Sep 2023
Topic Review
DAISY Digital Talking Book
DAISY (Digital Accessible Information SYstem) is a technical standard for digital audiobooks, periodicals and computerized text. DAISY is designed to be a complete audio substitute for print material and is specifically designed for use by people with "print disabilities", including blindness, impaired vision, and dyslexia. Based on the MP3 and XML formats, the DAISY format has advanced features in addition to those of a traditional audio book. Users can search, place bookmarks, precisely navigate line by line, and regulate the speaking speed without distortion. DAISY also provides aurally accessible tables, references and additional information. As a result, DAISY allows visually impaired listeners to navigate something as complex as an encyclopedia or textbook, otherwise impossible using conventional audio recordings. DAISY multimedia can be a book, magazine, newspaper, journal, computerized text or a synchronized presentation of text and audio. It provides up to six embedded "navigation levels" for content, including embedded objects such as images, graphics, and MathML. In the DAISY standard, navigation is enabled within a sequential and hierarchical structure consisting of (marked-up) text synchronized with audio. DAISY 2 was based on XHTML and SMIL. DAISY 3 is a newer technology, also based on XML, and is standardized as ANSI/NISO Z39.86-2005. The DAISY Consortium was founded in 1996 and consists of international organizations committed to developing equitable access to information for people who have a print disability. The consortium was selected by the National Information Standards Organization (NISO) as the official maintenance agency for the DAISY/NISO Standard.
  • 873
  • 09 Nov 2022
Topic Review
Data-Driven Decision-Making
Decision-making for manufacturing and maintenance operations is benefiting from the advanced sensor infrastructure of Industry 4.0, enabling the use of algorithms that analyze data, predict emerging situations, and recommend mitigating actions. 
  • 645
  • 22 Apr 2021
Topic Review
Data-Driven Modeling in Drilling in Well Operations
Swab and surge pressure fluctuations are decisive during drilling for oil. The axial movement of the pipe in the wellbore causes pressure fluctuations in wellbore fluid; these pressure fluctuations can be either positive or negative, corresponding to the direction of the movement of the pipe. For example, if the drill string is lowering down in the borehole, the drop is positive (surge pressure), and if the drill string is pulling out of the hole, the drop is negative (swab pressure). The intensity of these pressure fluctuations depends on the speed of the lowering down (tripping in) or withdrawing the pipe out (tripping out). High tripping speed corresponds to higher pressure fluctuations and can lead to fracturing the well formation. Low tripping speed leads to a slow operation, causing non-productive time, thus increasing the overall well budget. 
  • 654
  • 22 Apr 2022
Topic Review
Data-Driven Production Logistics
A data-driven approach in production logistics is adopted as a response to challenges such as low visibility and system rigidity. within data-driven production logistics, data is the backbone of the system and all the components are bound together with data. Any decision is made based on data rather than intuition or even experience. All production logistics related activities are supported by data, which is constantly collected from data sources such as machines, human resources, sensors, actuators, etc. A data-driven approach facilitates transition towards a smart, autonomous production logistics system.
  • 1.1K
  • 28 Apr 2021
Topic Review
Deep Learning Based Demand Forecasting in Smart Grids
Smart grids are able to forecast customers’ consumption patterns, i.e., their energy demand, and consequently electricity can be transmitted after taking into account the expected demand. To face demand forecasting challenges, where the data generated by smart grids is huge, modern data-driven techniques need to be used. In this scenario, Deep Learning models are a good alternative to learn patterns from customer data and then forecast demand for different forecasting horizons. Among the commonly used Artificial Neural Networks, Long Short-Term Memory networks—based on Recurrent Neural Networks—are playing a prominent role.
  • 400
  • 04 May 2023
Topic Review
Deep Learning Stranded Neural Network Model
Maintenance processes are of high importance for industrial plants. They have to be performed regularly and uninterruptedly. To assist maintenance personnel, industrial sensors monitored by distributed control systems observe and collect several machinery parameters in the cloud. Then, machine learning algorithms try to match patterns and classify abnormal behaviors.
  • 189
  • 19 Oct 2023
Topic Review
Development and Implementation of Inverse Design Method
The increasingly stringent requirements in terms of flexibility and efficiency for hydraulic turbines pose new challenges for designers. The inverse three-dimensional design strategy has recently demonstrated its effectiveness in improving the hydraulic machines performance hence representing a valid alternative to the traditional design method.
  • 215
  • 13 Jul 2023
Topic Review
Different Portland Cement Types in South Africa
Cement has long been recognized as an energy- and emission-intensive construction material. Cement production has recently experienced significant growth despite its high energy consumption, resource usage, and carbon emissions.
  • 513
  • 28 Jul 2023
Topic Review
Digital Circular Business Models
The concept of circular economy (CE) is receiving increasing attention worldwide as a way to overcome the issues of the current production and consumption model. It requires companies to rethink their supply chains and business models (BM). The CE is a regenerative economic system that necessitates a paradigm shift to replace the end of life (EoL) concept with reducing, alternatively reusing, recycling, and recovering materials throughout the supply chain, with the aim of promoting value maintenance and sustainable development, creating environmental quality, economic development, and social equity, to the benefit of current and future generations.
  • 368
  • 29 Nov 2023
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