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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. 
  • 974
  • 26 Sep 2023
Topic Review
The Synergistic Relationship between AI and the Economy
Artificial intelligence (AI) is transforming various aspects of the economy, including manufacturing, healthcare, finance, and transportation. AI-powered systems are augmenting human decision-making, reducing operational costs, enhancing productivity, and creating new business models. However, the integration of AI into the economy also poses several challenges, such as job displacement, economic inequality, and ethical concerns. This research explores the complex relationship between AI and the economy, highlighting the opportunities and challenges that arise from their synergy.
  • 973
  • 18 May 2023
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.
  • 973
  • 13 Oct 2023
Topic Review
Electroencephalogram-Based Emotion Classification
Rapid advancements in the medical field have drawn much attention to automatic emotion classification from EEG data. People’s emotional states are crucial factors in how they behave and interact physiologically. The diagnosis of patients’ mental disorders is one potential medical use. When feeling well, people work and communicate more effectively. Negative emotions can be detrimental to both physical and mental health. Many earlier studies that investigated the use of the electroencephalogram (EEG) for emotion classification have focused on collecting data from the whole brain because of the rapidly developing science of machine learning.
  • 972
  • 09 Jan 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). 
  • 972
  • 07 Nov 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. 
  • 971
  • 01 Aug 2022
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.
  • 971
  • 23 Oct 2023
Topic Review
Conflict Prediction in Sub-Saharan Africa
This entry offers policymakers and researchers pragmatic and sustainable approaches to identify and mitigate conflict threats by looking beyond p-values and plausible instruments. We argue that predicting conflict successfully depends on the choice of algorithms, which, if chosen accurately, can reduce economic and social instabilities caused by post-conflict reconstruction. After collating data with variables linked to conflict, we used a grid level dataset of 5928 observations spanning 48 countries across sub-Saharan Africa to predict civil conflict. The goals of the study were to assess the performance of supervised classification machine learning (ML) algorithms in comparison with logistic model, assess the implication of selecting a specific performance metric on policy initiatives, and evaluate the value of interpretability of the selected model. After comparing class imbalance resampling methods, the synthetic minority over-sampling technique (SMOTE) was employed to improve out-of-sample prediction for the trained model. The results indicate that if our selected performance metric is recall, gradient tree boosting is the best algorithm; however, if precision or F1 score is the selected metric, then the multilayer perceptron algorithm produces the best model. 
  • 970
  • 09 Jul 2021
Topic Review
Hesitant Fuzzy Graph Neural Network-Based Prototypical Network
Few-shot text classification aims to recognize new classes with only a few labeled text instances. Previous studies mainly utilized text semantic features to model the instance-level relation among partial samples. However, the single relation information makes it difficult for many models to address complicated natural language tasks. A novel hesitant fuzzy graph neural network (HFGNN) model that explores the multi-attribute relations between samples is proposed. HFGNN is combined with the Prototypical Network (HFGNN-Proto) to achieve few-shot text classification.
  • 967
  • 20 Dec 2022
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. 
  • 966
  • 08 Jul 2021
Topic Review
Data-Driven Methods in Power Grids
Applications of data-driven methods in power grids are motivated by the need to predict and mitigate intermittency in a (future) grid that is expected to lean heavily on renewables.
  • 965
  • 22 Jun 2022
Topic Review
ChatGPT in Teaching Practice
The emergence of new tools, especially those based on AI, raises concerns that technology may replace the teacher in the classroom. ChatGPT can support and automate the activities of educators, but their role as mentors who provide guidance and more profound assessment of learner abilities and role models cannot be entirely replaced by technology. ChatGPT, a generative artificial intelligence (GAI) representative, can create quizzes and assignments that are automatically checked and graded, generate feedback, and provide personalized learning content depending on the learners’ results.
  • 963
  • 06 Nov 2023
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.
  • 961
  • 28 Mar 2022
Topic Review
Cardiac Failure Forecasting
Accurate prediction of heart failure can help prevent life-threatening situations. Several factors contribute to the risk of heart failure, including underlying heart diseases such as coronary artery disease or heart attack, diabetes, hypertension, obesity, certain medications, and lifestyle habits such as smoking and excessive alcohol intake. Machine learning approaches to predict and detect heart disease hold significant potential for clinical utility but face several challenges in their development and implementation.
  • 961
  • 15 Aug 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.
  • 960
  • 07 Dec 2021
Topic Review
Deep Learning Methods for Retinal Disease Diagnosis
The advancement of digital medical imaging has brought about a significant change in ophthalmology as it has introduced effective technologies that help in the detection of such diseases. By improving early detection through image analysis and identifying minuscule anomalies, Artificial Intelligence (AI) has considerably coped with retinal diseases. Different Machine Learning (ML) and Convolutional Neural Networks (CNNs) are efficient at analyzing images and are particularly incredible at recognizing complex patterns in medical images.
  • 960
  • 21 Oct 2023
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.
  • 959
  • 22 May 2023
Topic Review
Equilibrium Optimizer Algorithm
The equilibrium optimizer (EO) is a recently developed physics-based optimization technique for complex optimization problems.
  • 959
  • 04 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. 
  • 957
  • 15 Sep 2021
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.
  • 957
  • 16 May 2022
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