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Topic Review
Radar Depth and Velocity Estimation
Radar can measure range and Doppler velocity, but both of them cannot be directly used for downstream tasks. The range measurements are sparse and therefore difficult to associate with their visual correspondences. The Doppler velocity is measured in the radial axis and, therefore, cannot be directly used for tracking.
  • 1.1K
  • 08 Jun 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
Control-Based 4D Printing
Building on the recent progress of four-dimensional (4D) printing to produce dynamic structures, this study aimed to bring this technology to the next level by introducing control-based 4D printing to develop adaptive 4D-printed systems with highly versatile multi-disciplinary applications, including medicine, in the form of assisted soft robots, smart textiles as wearable electronics and other industries such as agriculture and microfluidics. This study introduced and analyzed adaptive 4D-printed systems with an advanced manufacturing approach for developing stimuli-responsive constructs that organically adapted to environmental dynamic situations and uncertainties as nature does. The adaptive 4D-printed systems incorporated synergic integration of three-dimensional (3D)-printed sensors into 4D-printing and control units, which could be assembled and programmed to transform their shapes based on the assigned tasks and environmental stimuli. This paper demonstrates the adaptivity of these systems via a combination of proprioceptive sensory feedback, modeling and controllers, as well as the challenges and future opportunities they present.
  • 1.1K
  • 28 Oct 2020
Topic Review
Abstract Syntax Notation One
Abstract Syntax Notation One (ASN.1) is a standard interface description language for defining data structures that can be serialized and deserialized in a cross-platform way. It is broadly used in telecommunications and computer networking, and especially in cryptography. Protocol developers define data structures in ASN.1 modules, which are generally a section of a broader standards document written in the ASN.1 language. The advantage is that the ASN.1 description of the data encoding is independent of a particular computer or programming language (other than ASN.1.) Because ASN.1 is both human-readable and machine-readable, an ASN.1 compiler can compile modules into libraries of code, CODECs, that decode or encode the data structures. Some ASN.1 compilers can produce code to encode or decode several encodings, e.g. packed, BER or XML. ASN.1 is a joint standard of the International Telecommunication Union Telecommunication Standardization Sector (ITU-T) and ISO/IEC, originally defined in 1984 as part of CCITT X.409:1984. In 1988, ASN.1 moved to its own standard, X.208, due to wide applicability. The substantially revised 1995 version is covered by the X.680 series. The latest revision of the X.680 series of recommendations is the 5.0 Edition, published in 2015.
  • 1.1K
  • 04 Nov 2022
Topic Review
Multi-Omics Model for Cancer Genetics
In the coming age of omics technologies, next gen sequencing, proteomics, metabolomics, and other high throughput techniques will become the usual tools in biomedical cancer research. However, their integrative approach is not trivial due to the broad diversity of data types, dynamic ranges and sources of experimental and analytical errors characteristic of each omics.
  • 1.1K
  • 02 Jun 2021
Topic Review
Camp Lazlo
Camp Lazlo (stylized as CAMP LAZLO!) is an American animated television series created by Joe Murray for Cartoon Network. It was produced by Cartoon Network Studios. The show revolves around Lazlo, a spider monkey who attends a Boy Scout-like summer camp with a cast of anthropomorphic animal characters. The series has a style of humor similar to the Nickelodeon series Rocko's Modern Life (which Murray also created and is most known for) SpongeBob SquarePants and The Powerpuff Girls. The series premiered on Cartoon Network on July 8, 2005 at 8:00 p.m. ET/PT with five seasons, 61 episodes, and an hour-long television special. During its run, the series won three Emmy Awards and three Pulcinella Awards, and was also nominated for another Emmy and an Annie Award.
  • 1.1K
  • 07 Nov 2022
Topic Review
Structure of Power QKD Network
Considering the complexity of the power grid environment and the diversity of power communication transmission losses, this paper proposes a quantum key distribution (QKD) network structure suitable for power business scenarios. Through the simulation of the power communication transmission environment, the performance indicators of quantum channels and data interaction channels in the power QKD system are tested and evaluated from six aspects, such as distance loss, galloping loss, splice loss, data traffic, encryption algorithm, and system stability. In the actual environment, this paper combines the production business to build a QKD network suitable for power scenarios, and conducts performance analysis. The experimental results show that the power QKD technology can meet the operation index requirements of power business, as well as provide a reference for the large-scale application of the technology.
  • 1.1K
  • 12 Apr 2021
Topic Review
Artificial Intelligent in Education
The application of Artificial Intelligence or AI in education has been the subject of academic research. The field examines learning wherever it occurs, in traditional classrooms or at workplaces so to support formal education and lifelong learning. It combines interdisciplinary AI and learning sciences (such as education, psychology, neuroscience, linguistics, sociology and anthropology) in order to facilitate the development of effective adaptive learning environments and various flexible, inclusive tools. Nowadays, there are several new challenges in the field of education technology in the era of smart phones, tablets, cloud computing, Big Data, etc., whose current research questions focus on concepts such as ICT-enabled personalized learning, mobile learning, educational games, collaborative learning on social media, MOOCs, augmented reality application in education and so on. Therefore, to meet these new challenges in education, several fields of research using AI have emerged over time to improve teaching and learning using digital technologies.
  • 1.1K
  • 03 Mar 2022
Topic Review
Firo (Cryptocurrency)
Firo, formerly known as Zcoin, is a cryptocurrency aimed at using cryptography to provide better privacy for its users compared to other cryptocurrencies such as Bitcoin.
  • 1.1K
  • 28 Nov 2022
Topic Review
Sports Analytics
Sports analytics are a collection of relevant, historical, statistics that can provide a competitive advantage to a team or individual. Through the collection and analyzation of these data, sports analytics inform players, coaches and other staff in order to facilitate decision making both during and prior to sporting events. The term "sports analytics" was popularized in mainstream sports culture following the release of the 2011 film, Moneyball, in which Oakland Athletics General Manager Billy Beane (played by Brad Pitt) relies heavily on the use of analytics to build a competitive team on a minimal budget. There are two key aspects of sports analytics — on-field and off-field analytics. On-field analytics deals with improving the on-field performance of teams and players, including questions such as "which player on the Red Sox contributed most to the team's offense?" or "who is the best wing player in the NBA?", etc. Off-field analytics deals with the business side of sports. Off-field analytics focuses on helping a sport organization or body surface patterns and insights through data that would help increase ticket and merchandise sales, improve fan engagement, etc. Off-field analytics essentially uses data to help rightsholders take decisions that would lead to higher growth and increased profitability. As technology has advanced over the last number of years data collection has become more in-depth and can be conducted with relative ease. Advancements in data collection have allowed for sports analytics to grow as well, leading to the development of advanced statistics and machine learning, as well as sport specific technologies that allow for things like game simulations to be conducted by teams prior to play, improve fan acquisition and marketing strategies, and even understand the impact of sponsorship on each team as well as its fans. Another significant impact sports analytics have had on professional sports is in relation to sport gambling. In depth sports analytics have taken sports gambling to new levels, whether it be fantasy sports leagues or nightly wagers, bettors now have more information at their disposal to help aid decision making. A number of companies and webpages have been developed to help provide fans with up to the minute information for their betting needs.
  • 1.1K
  • 14 Nov 2022
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