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Topic Review
Measure of Presortedness
In computer science, a measure of presortedness of a sequence represents how much work is required to sort the sequence. If the sequence is pre-sorted, sorting the sequence entirely require little work, hence it is expected to have a small measure of presortedness. In particular, the measure of a sorted sequence is 0. Some sorting algorithms are more efficient on pre-sorted list, as they can use this pre-work into account to avoid duplicate work. The measure of presortedness allows to formalize the notion that an algorithm is optimal for a certain measure.
  • 953
  • 07 Nov 2022
Topic Review
Machine Learning Methods for Stock Market Prediction
Stock market prediction models are developed with different goals. The primary focus of stock market prediction has been on forecasting the price of a share for a specific future period. The price of a share is a numerical value, and its variation over time is often treated as a time series in various studies. 
  • 953
  • 21 Jul 2023
Topic Review
Integrated IoT-Fog-Cloud Systems
Integrated IoT-fog-cloud system (iIFC) offers the opportunity to create suitable platforms to develop and operate important smart city applications. These applications can utilize services provided by IoT devices, fog nodes, and cloud services.
  • 952
  • 07 Dec 2021
Topic Review
Automatic Diagnosis of Glaucoma from Retinal Images
Glaucoma is characterized by increased intraocular pressure and damage to the optic nerve, which may result in irreversible blindness. The drastic effects of this disease can be avoided if it is detected at an early stage. However, the condition is frequently detected at an advanced stage in the elderly population. Therefore, early-stage detection may save patients from irreversible vision loss. The manual assessment of glaucoma by ophthalmologists includes various skill-oriented, costly, and time-consuming methods. Several techniques are in experimental stages to detect early-stage glaucoma, but a definite diagnostic technique remains elusive. The detection technique involves the identification of patterns from the retinal images that are often overlooked by clinicians. The proposed approach uses the gray channels of fundus images and applies the data augmentation technique to create a large dataset of versatile fundus images to train the convolutional neural network model. Using the ResNet-50 architecture, the proposed approach achieved excellent results for detecting glaucoma on the G1020, RIM-ONE, ORIGA, and DRISHTI-GS datasets. Researchers obtained a detection accuracy of 98.48%, a sensitivity of 99.30%, a specificity of 96.52%, an AUC of 97%, and an F1-score of 98% by using the proposed model on the G1020 dataset. The proposed model may help clinicians to diagnose early-stage glaucoma with very high accuracy for timely interventions.
  • 952
  • 25 May 2023
Topic Review
Path Planning for Agricultural Ground Robots
Ground robots have been developed for a variety of agricultural applications, with autonomous and safe navigation being one of the most difficult hurdles in this development. When a mobile platform moves autonomously, it must perform a variety of tasks, including localization, route planning, motion control, and mapping, which is a critical stage in autonomous operations. 
  • 951
  • 26 Sep 2023
Topic Review
Recommender System for the Tourism Domain
Tourism is a widespread activity and a huge industry, in their travels, tourists have to select among numerous alternatives of landmarks, places and in general points of interest (POIs) they can visit. This can be challenging for travellers that have no prior experience of or “inside knowledge” regarding their destination, and even more so for short-term visits. As a result, a booming industry of travel-related recommender systems (RSs) has been developed, in order to provide users with recommendations most relevant to their interests. Recommender systems are considered to be personalized and non-personalized. Personalized recommender systems extrapolate user’s preferences to create efficient recommendations based on the users’ past interaction with the system. On the contrary, non-personalized recommenders suggest items that are most relevant and popular among all users.
  • 950
  • 23 Oct 2023
Topic Review
Vision-Based Pose Estimation of Non-Cooperative Target
In the realm of non-cooperative space security and on-orbit service, a significant challenge is accurately determining the pose of abandoned satellites using imaging sensors. Traditional methods for estimating the position of the target encounter problems with stray light interference in space, leading to inaccurate results.
  • 950
  • 18 Dec 2023
Topic Review
Irritable Bowel Syndrome and Artificial Intelligence
Irritable bowel syndrome (IBS) has a global prevalence of around 4.1% and is associated with a low quality of life and increased healthcare costs. Current guidelines recommend that IBS is diagnosed using the symptom-based Rome IV criteria. Despite this, when patients seek medical attention, they are usually over-investigated. This issue might be resolved by novel technologies in medicine, such as the use of Artificial Intelligence (AI). 
  • 948
  • 07 Nov 2023
Topic Review
Categorical Exploratory Data Analysis
Categorical exploratory data analysis (CEDA) is demonstrated to provide new resolutions for two topics: multiclass classification (MCC) with one single categorical response variable and response manifold analytics (RMA) with multiple response variables. 
  • 947
  • 08 Jul 2021
Topic Review
Intelligent Question Answering System
Intelligent question answering system is an innovative information service system which integrates natural language processing, information retrieval, semantic analysis and artificial intelligence. The system mainly consists of three core parts, which are question analysis, information retrieval and answer extraction. Through these three parts, the system can provide users with accurate, fast and convenient answering services.
  • 946
  • 20 Aug 2024
Topic Review
Green Space Quality Analysis Using Machine Learning Approaches
Green space is any green infrastructure consisting of vegetation. Green space is linked with improving mental and physical health, providing opportunities for social interactions and physical activities, and aiding the environment. The quality of green space refers to the condition of the green space.
  • 944
  • 22 May 2023
Topic Review
Deep Learning Methods in Plant Taxonomy
Plant taxonomy is the scientific study of the classification and naming of various plant species. It is a branch of biology that aims to categorize and organize the diverse variety of plant life on earth. Traditionally, plant taxonomy has been performed using morphological and anatomical characteristics, such as leaf shape, flower structure, and seed and fruit characters. Artificial intelligence (AI), machine learning, and especially deep learning can also play an instrumental role in plant taxonomy by automating the process of categorizing plant species based on the available features.
  • 943
  • 26 Jul 2023
Topic Review
Neuromorphic Sentiment Analysis Using Spiking Neural Networks
Spiking neural networks, often employed to bridge the gap between machine learning and neuroscience fields, are considered a promising solution for resource-constrained applications. Since deploying spiking neural networks on traditional von-Newman architectures requires significant processing time and high power, typically, neuromorphic hardware is created to execute spiking neural networks. The objective of neuromorphic devices is to mimic the distinctive functionalities of the human brain in terms of energy efficiency, computational power, and robust learning. 
  • 942
  • 20 Sep 2023
Topic Review
IoT for Smart Cities
Smart city is a collective term for technologies and concepts that are directed toward making cities efficient, technologically more advanced, greener and more socially inclusive. These concepts include technical, economic and social innovations. This term has been tossed around by various actors in politics, business, administration and urban planning since the 2000s to establish tech-based changes and innovations in urban areas. The idea of the smart city is used in conjunction with the utilization of digital technologies and at the same time represents a reaction to the economic, social and political challenges that post-industrial societies are confronted with at the start of the new millennium. The key focus is on dealing with challenges faced by urban society, such as environmental pollution, demographic change, population growth, healthcare, the financial crisis or scarcity of resources. In a broader sense, the term also includes non-technical innovations that make urban life more sustainable. So far, the idea of using IoT-based sensor networks for healthcare applications is a promising one with the potential of minimizing inefficiencies in the existing infrastructure. A machine learning approach is key to successful implementation of the IoT-powered wireless sensor networks for this purpose since there is large amount of data to be handled intelligently. 
  • 941
  • 15 Sep 2021
Topic Review
6-DoF Object Pose Estimation
Accurately estimating the six-degree-of-freedom (6-DoF) of objects is a critical task in various applications, including robotics, autonomous driving, and virtual reality. For instance, the precise estimation of spatial coordinates and rotational orientation of an object is essential for robotic tasks such as manipulation, navigation, and assembly.
  • 941
  • 13 Oct 2023
Topic Review
Enhanced Perception for Autonomous Driving Using Semantic-Geometric Fusion
Environment perception remains one of the key tasks in autonomous driving for which solutions have yet to reach maturity. Multi-modal approaches benefit from the complementary physical properties specific to each sensor technology used, boosting overall performance. The presented 360∘ enhanced perception component is based on low-level fusion between geometry provided by the LiDAR-based 3D point clouds and semantic scene information obtained from multiple RGB cameras, of multiple types. This multi-modal, multi-sensor scheme enables better range coverage, improved detection and classification quality with increased robustness. Semantic, instance and panoptic segmentations of 2D data are computed using efficient deep-learning-based algorithms, while 3D point clouds are segmented using a fast, traditional voxel-based solution. 
  • 940
  • 01 Aug 2022
Topic Review
Artificial Intelligence-Driven Digital Technologies on SDG
Artificial Intelligence-Driven (AI-Driven) digital technologies (DT) are intrinsically connected to interact, perceive, and understand people, businesses, economies, and lives in general. The term Artificial Intelligence (AI) can be understood as a general combination and integration of applications with other “DTs” to create machines capable of thinking like humans. AI-Driven DT economic and societal impacts increase on a continuous basis and more recently they are assuming an important role in the Sustainable Development Goals (SDG) Agenda 2030, and their implementations are a considerable decision for developed and developing countries. In turn, Brazil and Portugal have been elected in this research to display their view on AI-driven DT on SDG achievements, contradicting their perspectives in this field.
  • 939
  • 28 Mar 2022
Topic Review
Computational Intelligence in Stock Portfolio Management
Stock portfolio management consists of defining how some investment resources should be allocated to a set of stocks. It is an important component in the functioning of modern societies throughout the world. However, it faces important theoretical and practical challenges. ANNs have high accuracy, fast prediction speed and clear superiority in predictions related to financial markets.
  • 938
  • 16 May 2022
Topic Review
Graph Neural Networks for Parkinson’s Disease
Graph neural networks (GNNs) have been increasingly employed in the field of Parkinson’s disease (PD) research. The use of GNNs provides a promising approach to address the complex relationship between various clinical and non-clinical factors that contribute to the progression of PD. 
  • 933
  • 13 Nov 2023
Topic Review
Knowledge Distillation for ADHD
Attention Deficit Hyperactivity Disorder (ADHD) is a brain disorder with characteristics such as lack of concentration, excessive fidgeting, outbursts of emotions, lack of patience, difficulty in organizing tasks, increased forgetfulness, and interrupting conversation, and it is affecting millions of people worldwide. 
  • 931
  • 14 Sep 2021
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