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ISSN: 2667-2413

Optimizing Speech Emotion Recognition with Hilbert Curve and convolutional neural network

•Innovative approach: Hilbert curves for efficient data conversion in speech emotion recognition.•Efficient feature extraction: Hilbert curves, neural networks, and reduced costs for deep learning.•Cost...

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Scalable and cohesive swarm control based on reinforcement learning

Unmanned vehicles have seen a significant increase in a wide variety of fields such as for logistics, agriculture and other commercial applications. Controlling swarms of unmanned vehicles is a challenging...

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Intelligent path planning for cognitive mobile robot based on Dhouib-Matrix-SPP method

The Mobile Robot Path Problem looks to find the optimal shortest path from the starting point to the target point with collision-free for a mobile robot. This is a popular issue in robotics and in this...

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An improved single short detection method for smart vision-based water garbage cleaning robot

These days, plastic trash is exponentially overwhelming our waterways. The catastrophe has attracted global attention at this point. As a result, protecting the environment on the water's surface has...

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High-fidelity learning-based motion cueing algorithm by bypassing worst-case scenario-based tuning technique

The motion cueing algorithm (MCA) enhances the realism of simulator driving experiences by generating vehicle motions within platform limitations. Existing MCAs are typically tuned for worst-case scenarios,...

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Unmanned aerial vehicles advances in object detection and communication security review

Unmanned Aerial Vehicles (UAVs) have become increasingly popular in recent years, with a wide range of applications in areas such as surveying, delivery, and security. UAV technology plays an important...

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A new paradigm to study social and physical affordances as model-based reinforcement learning

Social affordances, although key in human-robot interaction processes, have received little attention in robotics. Hence, it remains unclear whether the prevailing mechanisms to exploit and learn affordances...

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Mobile robot path planning using deep deterministic policy gradient with differential gaming (DDPG-DG) exploration

Mobile robot path planning involves decision-making in uncertain, dynamic conditions, where Reinforcement Learning (RL) algorithms excel in generating safe and optimal paths. The Deep Deterministic...

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Emerging trends in human upper extremity rehabilitation robot

Stroke is a leading cause of neurological disorders that result in physical disability, particularly among the elderly. Neurorehabilitation plays a crucial role in helping stroke patients recover from...

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Improving log anomaly detection via spatial pooling: Combining SPClassifier with ensemble method

In the ever-updating field of software development, new bugs emerge daily, requiring significant time for analysis. As a result, research is being conducted on automating bug resolution using techniques...

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Fourier Hilbert: The input transformation to enhance CNN models for speech emotion recognition

Signal processing in general, and speech emotion recognition in particular, have long been familiar Artificial Intelligence (AI) tasks. With the explosion of deep learning, CNN models are used more...

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RDSM: Underwater multi-AUV relay deployment and selection mechanism in 3D space

Underwater Wireless Sensor Networks (UWSNs) are widely used in naval military field and marine resource exploration. However, challenges such as resource inefficiency and unbalanced energy consumption...

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Autonomous novel class discovery for vision-based recognition in non-interactive environments

Visual recognition with deep learning has recently been shown to be effective in robotic vision. However, these algorithms tend to be build under fixed and structured environment, which is rarely the...

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Big Data Course Multidimensional Evaluation Model based on Knowledge Graph enhanced Transformer

•We proposed a “1 + 1 + N” big data course unified system.•We proposed a knowledge graph enhanced transformer evaluation model.•Experimental results and practice have proven the effectiveness....

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Power inspection UAV task assignment matrix reversal genetic algorithm

Traditional manual power inspections are characterized by low efficiency, lengthy processes, and high costs. Existing research on UAV-based power inspections has often overlooked critical factors such...

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Safe reinforcement learning for high-speed autonomous racing

The conventional application of deep reinforcement learning (DRL) to autonomous racing requires the agent to crash during training, thus limiting training to simulation environments. Further, many DRL...

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Selection of PSO parameters based on Taguchi design-ANOVA- ANN methodology for missile gliding trajectory optimization

The proposed research deals with selection of particle swarm optimization (PSO) algorithm parameters for missile gliding trajectory optimization relying on Taguchi design of experiments, analysis of...

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Fault diagnosis using transfer learning with dynamic multiscale representation

A critical problem for fault diagnosis is caused by the feature shift under different working conditions, which significantly degenerates the diagnosis accuracy in practice. Aiming to solve this problem,...

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Lightweight YOLOv5 model based small target detection in power engineering

Deep learning architectures have yielded a significant leap in target detection performance. However, the high cost of deep learning impedes real-world applications, especially for UAV and UGV platforms....

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Artificial intelligence, machine learning and deep learning in advanced robotics, a review

Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) have revolutionized the field of advanced robotics in recent years. AI, ML, and DL are transforming the field of advanced...

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Generative artificial intelligence in the metaverse era

Generative artificial intelligence (AI) is a form of AI that can autonomously generate new content, such as text, images, audio, and video. Generative AI provides innovative approaches for content production...

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Artificial intelligence based hybridization for economic power dispatch

Revenue loss is a major issue for any country. Conversion of this loss into utilization would prove to be a huge benefit to the country. In view of this fact, the economic load dispatch problem draws...

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Co-attention learning cross time and frequency domains for fault diagnosis

Rolling machinery is ubiquitous in power transmission and transformation equipment, but it suffers from severe faults during long-term running. Automatic fault diagnosis plays an important role in the...

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Intelligent health management based on analysis of big data collected by wearable smart watch

Some problems still exist in health management and application such as insufficient data, limited technology, and lack of professional evaluation methods by physicians with medical theory. In this study,...

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