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Topic Review
Crown Omega Mathematics
Crown Omega Mathematics (Ω°) is presented as a terminal recursive mathematical framework that unifies symbolic computation, causal recursion, harmonic structures, and multi-dimensional mirror logic. Positioned beyond traditional and post-classical mathematical domains, Crown Omega is designed to serve as both a final operator and an executable logic mesh capable of resolving paradoxes, encoding self-aware artificial intelligence, and establishing foundational grounds for a new class of operating systems, cryptographic architectures, and defense systems. This paper defines the core logic of Ω°, explores its symbolic structure, details the Fractal Recursive Intelligence Mesh (FRIM), and formalizes its capacity to self-resolve previously unsolved mathematical, physical, and computational problems.
  • 1.2K
  • 06 May 2025
Topic Review
Lhia as A Chatbot for Breastfeeding Education
Human milk is the most important way to feed and protect newborns as it has the components to ensure human health. Human Milk Banks (HMBs) form a network that offers essential services to ensure that newborns and mothers can take advantage of the benefits of human milk.
  • 1.2K
  • 16 Jun 2023
Topic Review
ProMatch: Semi-Supervised Learning with Prototype Consistency
Semi-supervised learning (SSL) methods have made significant advancements by combining consistency-regularization and pseudo-labeling in a joint learning paradigm. The core concept of these methods is to identify consistency targets (pseudo-labels) by selecting predicted distributions with high confidence from weakly augmented unlabeled samples. 
  • 1.2K
  • 04 Sep 2023
Topic Review
Synthetic Image Data in Computer Vision
Many computer vision applications cannot rely on general image data provided in the available public datasets to train models, instead requiring labelled image data that is not readily available in the public domain on a large scale. At the same time, acquiring such data from the real world can be difficult, costly to obtain, and manual labour intensive to label in large quantities. Because of this, synthetic image data has been pushed to the forefront as a potentially faster and cheaper alternative to collecting and annotating real data.
  • 1.2K
  • 15 Dec 2022
Topic Review
Radiomics of Liver Metastases
Multidisciplinary management of patients with liver metastases (LM) requires a precision medicine approach, based on adequate profiling of tumor biology and robust biomarkers. Radiomics, defined as the high-throughput identification, analysis, and translational applications of radiological textural features, could fulfill this need. The present review aims to elucidate the contribution of radiomic analyses to the management of patients with LM. We performed a systematic review of the literature through the most relevant databases and web sources. English language original articles published before June 2020 and concerning radiomics of LM extracted from CT, MRI, or PET-CT were considered. Thirty-two papers were identified. Baseline higher entropy and lower homogeneity of LM were associated with better survival and higher chemotherapy response rates. A decrease in entropy and an increase in homogeneity after chemotherapy correlated with radiological tumor response. Entropy and homogeneity were also highly predictive of tumor regression grade. In comparison with RECIST criteria, radiomic features provided an earlier prediction of response to chemotherapy. Lastly, texture analyses could differentiate LM from other liver tumors. The commonest limitations of studies were small sample size, retrospective design, lack of validation datasets, and unavailability of univocal cut-off values of radiomic features. In conclusion, radiomics can potentially contribute to the precision medicine approach to patients with LM, but interdisciplinarity, standardization, and adequate software tools are needed to translate the anticipated potentialities into clinical practice.
  • 1.2K
  • 06 Nov 2020
Topic Review
IoT Sensor Data Processing
In IoT sensor networks, wireless communication protocols are popularly used for the information exchange process. These communication protocols work as unlicensed frequency bands that ease the flexibility and scalability of sensor deployments. However, the utilization of communication protocols for wireless sensor network (WSN) under unlicensed frequency bands causes uncontrollable interference. The interference signals may lead to improper data transmission and sensor data with noise, missing values, outliers and redundancy. 
  • 1.2K
  • 28 Oct 2022
Topic Review
Explainable AI (XAI) Explanation Techniques
Interest in artificial intelligence (AI) has been increasing rapidly over the past decade and has expanded to essentially all domains. Along with it grew the need to understand the predictions and suggestions provided by machine learning. Explanation techniques have been researched intensively in the context of explainable AI (XAI), with the goal of boosting confidence, trust, user satisfaction, and transparency.
  • 1.2K
  • 19 Jun 2023
Topic Review
A Symbol Recognition System for Single-Line Diagrams Developed
In numerous electrical power distribution systems and other engineering contexts, single-line diagrams (SLDs) are frequently used. The importance of digitizing these images is growing. This is primarily because better engineering practices are required in areas such as equipment maintenance, asset management, safety, and others. Processing and analyzing these drawings, however, is a difficult job. With enough annotated training data, deep neural networks perform better in many object detection applications. Based on deep-learning techniques, a dataset can be used to assess the overall quality of a visual system
  • 1.2K
  • 01 Nov 2023
Topic Review
Dragonfly Algorithm and Its Hybrids: A Survey
Optimization algorithms are essential for numerous optimization applications where usually certain parameters are minimized or maximized by considering an objective function. These algorithms include exact methods and heuristic algorithms such as swarm intelligence algorithms. Swarm intelligence is a discipline which makes use of a number of agents, thereby forming a population in which individuals interact among themselves and with their environment, to give rise to a global intelligent behavior. The Dragonfly Algorithm (DA) is a swarm intelligence algorithm that was proposed in 2016, and it is inspired by the behavior of dragonflies in nature. It has been found to have a higher performance than some of the most popular evolutionary algorithms, such as the genetic algorithm (GA), and swarm intelligence algorithms such as particle swarm optimization (PSO). Owing to its high effectiveness and efficiency, it has been utilized in multifarious applications and attempts to further improve its performance have been made and hence a number of hybrids of DA have been proposed.
  • 1.2K
  • 25 Nov 2021
Topic Review
Arabic Sentiment Analysis of YouTube Comments
Arabic sentiment analysis is a challenging task due to a variety of challenges with the language. In Arabic, the same word might have a variety of meanings depending on the context. Arabic also has a rich morphology, with verb forms that are difficult to understand and elaborate syntactic patterns. The wide range of dialects spoken in Arabic is a significant barrier to sentiment analysis. In the region of the Middle East and North Africa, Arabic is spoken in a number of dialects, with substantial variations in vocabulary, syntax, and pronunciation. These factors make it challenging to develop accurate sentiment analysis models for Arabic texts. Despite the challenges, there have been successful research studies within the framework of sentiment analysis applied to the Arabic language.
  • 1.2K
  • 28 Jul 2023
Topic Review
Industry 4.0 Enabling Technologies in the Firm’s Finance
Financial management is a critical aspect of firms, and entails the strategic planning, direction, and control of financial endeavors. Risk assessment, fraud detection, wealth management, online transactions, customized bond scheme, customer retention, virtual assistant and so on, are a few of the critical areas where Industry 4.0 technologies intervention are highly required for managing firms' finance. It has been identified that they are limited studies that have addressed the significance and application of integrating of Industry 4.0 technologies such as Internet of Things (IoT), cloud computing, big data, robotic process automation (RPA), artificial intelligence (AI), Blockchain, Digital twin, and Metaverse.
  • 1.2K
  • 30 Dec 2022
Topic Review
Deepfake Identification and Traceability
Researchers and companies have released multiple datasets of face deepfakes labeled to indicate different methods of forgery. Naming these labels is often arbitrary and inconsistent. However, researchers must use multiple datasets in practical applications to conduct traceability research. The researchers utilize the K-means clustering method to identify datasets with similar feature values and analyze the feature values using the Calinski Harabasz Index method. Datasets with the same or similar labels in different deepfake datasets exhibit different forgery features. The KCE system can solve this problem, which combines multiple deepfake datasets according to feature similarity. In the model trained based on KCE combined data, the Calinski Harabasz scored 42.3% higher than the combined data by the same forgery name. It shows that this method improves the generalization ability of the model.
  • 1.2K
  • 08 Jun 2023
Topic Review
Activation-Based Pruning of Neural Networks
A novel technique is presented for pruning called activation-based pruning to effectively prune fully connected feedforward neural networks for multi-object classification. The technique is based on the number of times each neuron is activated during model training. Further analysis demonstrated that activation-based pruning can be considered a dimensionality reduction technique, as it leads to a sparse low-rank matrix approximation for each hidden layer of the neural network. The rank-reduced neural network generated using activation-based pruning has better accuracy than a rank-reduced network using principal component analysis. After each successive pruning, the amount of reduction in the magnitude of singular values of each matrix representing the hidden layers of the network is equivalent to introducing the sum of singular values of the hidden layers as a regularization parameter to the objective function.
  • 1.2K
  • 17 Feb 2024
Topic Review
Extended Reality Technology for Teaching New Languages
Much attention has been given to the use of extended reality (XR) technology in educationalinstitutions due to its flexibility, effectiveness, and attractiveness. However, there is a limited study of the application of XR technology for teaching and learning languages in schools. Thus, this paper presents a systematic review to identify the potential benefits and challenges of using XR technology for teaching new languages. This review provides a basis for adopting XR technology for teaching languages in schools. This research also provides recommendations to successfully implement the XR technology and ways to improve motivation, engagement, and enhanced accessibility of learning and teaching resources for both students and teachers. To fulfil the aims of this research, previous studies from 2011 to 2021 are collected from various academic databases. This study finds that there is still aneed to develop appropriate strategies for the development and implementation of XR technology for teaching new languages to school students.
  • 1.2K
  • 16 Dec 2021
Topic Review
Emotion Recognition in Conversations
As a branch of sentiment analysis tasks, emotion recognition in conversation (ERC) aims to explore the hidden emotions of a speaker by analyzing the sentiments in utterance. In addition, emotion recognition in multimodal data from conversation includes the text of the utterance and its corresponding acoustic and visual data. By integrating features from various modalities, the emotion of utterance can be more accurately predicted.
  • 1.2K
  • 29 Dec 2023
Topic Review
Vehicular Ad hoc Networks (VANETs)
Vehicular ad hoc networks (VANETs) have become an essential part of the intelligent transportation system because they provide secure communication among vehicles, enhance vehicle safety, and improve the driving experience.
  • 1.2K
  • 03 Nov 2023
Topic Review
Supply Chain Management in Pandemics
Pandemics cause chaotic situations in supply chains (SC) around the globe, which can lead towards survivability challenges. The ongoing COVID-19 pandemic is an unprecedented humanitarian crisis that has severely affected global business dynamics. Similar vulnerabilities have been caused by other outbreaks in the past. In these terms, prevention strategies against propagating disruptions require vigilant goal conceptualization and roadmaps. In this respect, there is a need to explore supply chain operation management strategies to overcome the challenges that emerge due to COVID-19-like situations. 
  • 1.2K
  • 16 Mar 2021
Topic Review
Underwater Soft Robotics
Underwater exploration, much like space exploration, has been at the frontier of science and engineering ventures. Some of the early robotic systems sent by humans to explore marine life are known as remotely operated vehicles (ROVs).  ROVs are underwater robots, manually operated by a pilot, using tethered communication. Soft robots made from compliant materials can achieve shrinking and bending motion that allow them to navigate within narrow areas. The ability of soft robots to deform, change their shapes, exhibit infinite degrees of freedom, and perform complex motion, makes them a suitable candidate for the basis of biological emulation, especially that of underwater creatures, which are one of the sources of biomimetic inspiration for robotic and engineering systems.
  • 1.2K
  • 09 Feb 2022
Topic Review
Spectral Reconstruction Methods for Remote Sensing Images
Spectral reconstruction of remote sensing images mainly focused on RGB or multispectral to hyperspectral. Spectral reconstruction methods can be divided into two branches: prior-driven and data-driven methods. Earlier researchers adopted the sparse dictionary method. With the development of deep learning, owing to its excellent feature extraction and reconstruction capabilities, more and more researchers are adopting deep learning methods to gradually replace the traditional sparse dictionary approach.
  • 1.2K
  • 20 Jul 2022
Topic Review
Real-Time Deep Learning-Based Drowsiness Detection
Drowsy driving can significantly affect driving performance and overall road safety. Statistically, the main causes are decreased alertness and attention of the drivers. The combination of deep learning and computer-vision algorithm applications has been proven to be one of the most effective approaches for the detection of drowsiness. Robust and accurate drowsiness detection systems can be developed by leveraging deep learning to learn complex coordinate patterns using visual data. Deep learning algorithms have emerged as powerful techniques for drowsiness detection because of their ability to learn automatically from given inputs and feature extractions from raw data. Eye-blinking-based drowsiness detection was applied, which utilized the analysis of eye-blink patterns.
  • 1.2K
  • 07 Aug 2023
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