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Topic Review
Multi-Method Diagnosis of CT Images
Intracranial hemorrhaging is considered a type of disease that affects the brain and is very dangerous, with high-mortality cases if there is no rapid diagnosis and prompt treatment. CT images are one of the most important methods of diagnosing intracranial hemorrhages. CT images contain huge amounts of information, requiring a lot of experience and taking a long time for proper analysis and diagnosis. Thus, artificial intelligence techniques provide an automatic mechanism for evaluating CT images to make a diagnosis with high accuracy and help radiologists make their diagnostic decisions.
  • 442
  • 30 Aug 2022
Topic Review
DNIX
DNIX (original spelling: D-Nix) is a discontinued Unix-like real-time operating system from the Swedish company Dataindustrier AB (DIAB). A version named ABCenix was developed for the ABC 1600 computer from Luxor. Daisy Systems also had a system named Daisy DNIX on some of their computer-aided design (CAD) workstations. It was unrelated to DIAB's product.
  • 442
  • 01 Nov 2022
Topic Review
Weakly Supervised Object Detection for Remote Sensing Images
To account for the lack of fine-grained annotations, such as object bounding boxes, several object detection methods have been developed that leverage only coarse-grain annotations (especially image-level labels indicating only the presence or absence of an object). This approach is called inexact Weak Supervision and introduces a new branch of Object Detection called Weakly Supervised Object Detection. Given an image, Remote Sensing Fully Supervised Object Detection (RSFSOD) aims to locate and classify objects based on Bounding Boxes annotations. Differently from RSFSOD, Remote Sensing Weakly Supervised Object Detection aims to precisely locate and classify object instances in Remote Sensing Images using only image-level labels or other types of coarse-grained labels (e.g., points or scribbles) as ground truth. 
  • 442
  • 24 Nov 2022
Topic Review
Exploration of Generative Artificial Intelligence
Generative Artificial Intelligence (GAI) has brought revolutionary changes to the world, enabling businesses to create new experiences by combining virtual and physical worlds. As the use of GAI grows along with the Metaverse, it is explored by academics, researchers, and industry communities for its endless possibilities.
  • 442
  • 23 Mar 2023
Topic Review
Reliable Storage of Cloud Data
The prime objective of the cloud data storage process is to make the service, irrespective of being infinitely extensible, a more reliable storage and low-cost model that also encourages different data storage types. Owing to the storage process, it must satisfy the cloud users’ prerequisites. Nevertheless, storing massive amounts of data becomes critical as this affects the data quality or integrity. Hence, this poses various challenges for existing methodologies. An efficient, reliable cloud storage model is proposed using a hybrid heuristic approach to overcome the challenges. The prime intention of the proposed system is to store the data effectively in the cloud environment by resolving two constraints, which are general and specific (structural). The cloud data were initially gathered and used to analyze the storage performance. Since the data were extensive, different datasets and storage devices were considered. Every piece of data as specified by its corresponding features, whereas the devices were characterized by the hardware or software components. Subsequently, the objective function was formulated using the network’s structural and general constraints. The structural constraints were determined by the interactions between the devices and data instances in the cloud. Then, the general constraints regarding the data allocation rules and device capacity were defined. To mitigate the constraints, the components were optimized using the Hybrid Pelican–Billiards Optimization Algorithm (HP-BOA) to store the cloud data. Finally, the performance was validated, and the results were analyzed and compared against existing approaches. Thus, the proposed model exhibited the desired results for storing cloud data appropriately. 
  • 442
  • 15 May 2023
Topic Review
Machine-Learning Forensics
A world-wide trend has been observed that there is widespread adoption across all fields to embrace smart environments and automation. Smart environments include a wide variety of Internet-of-Things (IoT) devices, so many challenges face conventional digital forensic investigation (DFI) in such environments. These challenges include data heterogeneity, data distribution, and massive amounts of data, which exceed digital forensic (DF) investigators’ human capabilities to deal with all of these challenges within a short period of time.
  • 442
  • 21 Sep 2023
Topic Review
Digital Media Technology Applied in Self-Guided Learning
This research adopts Keller’s ARCS motivation theory as a method to create a teaching experiment by integrating augmented reality (AR) into teaching in order to enhance learning interest and learning effectiveness in a digital media design course. The purpose of this research is to examine the application of AR in quarantine during the COVID-19 pandemic, whereby students can enhance their learning interest, learning satisfaction, and learning performance. Augmented reality acts as a tool for this research, wherein it is applied with the course of a 3D model-based interface and built-in learning contexts for the “digital media design” of the learning topics.The contribution of this research is proving that AR teaching materials are suitable for normal learning programs during the COVID-19 pandemic. At present, it appears as though online learning and self-study at home will become the norm for the students all over the world. Digital media design was the research field, and the coding program and the project development as professional domain knowledge of the Unity platform were found suitable for AR teaching materials for online learning solutions. However, the limitations of the research are that for successful AR teaching experiences, teachers must devote substantial additional time to work on AR-based textbooks,in contrast to other teaching models, which represents a major impediment for educators.
  • 441
  • 05 Jan 2022
Topic Review
Here Be Dragons
Here Be Dragons (formerly known as Vrse.works) is a medium-agnostic creative studio co-founded by Patrick Milling-Smith, Chris Milk and Brian Carmody.
  • 441
  • 08 Oct 2022
Topic Review
Glossary of Military Modeling and Simulation
The US DoD Modeling and Simulation Glossary (formally known as DoD 5000.59-M), was originally created in 1998. (As of October 2010) the glossary was being updated, without changing its main objective of providing a uniform language for use by the M&S community. This article contains a list of terms and acronyms, based on the original DoD 5000.59-M and information related to the update.
  • 441
  • 22 Nov 2022
Topic Review
Feit–Thompson Theorem
In mathematics, the Feit–Thompson theorem, or odd order theorem, states that every finite group of odd order is solvable. It was proved by Walter Feit and John Griggs Thompson (1962, 1963).
  • 441
  • 22 Nov 2022
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