Moving towards autonomy, unmanned vehicles rely heavily on state-of-the-art collision avoidance systems (CAS). A lot of work is being done to make the CAS as safe and reliable possible, necessitating a comparative study recent in this important area. The paper provides comprehensive review strategies used for vehicles, with main emphasis aerial (UAV). It an in-depth survey different techniques that are categorically explained along analysis considered approaches w.r.t. scenarios technical...

The development of a navigation system is one the major challenges in building fully autonomous platform. Full autonomy requires dependable capability not only perfect situation with clear GPS signals but also situations, where unreliable. Therefore, self-contained odometry systems have attracted much attention recently. This paper provides general and comprehensive overview state art field self-contained, i.e., denied systems, identifies out-coming that demand further research future....

One of the most challenging problems facing network operators today is attacks identification due to extensive number vulnerabilities in computer systems and creativity attackers. To address this problem, we present a deep learning approach for intrusion detection systems. Our uses Deep Auto-Encoder (DAE) as one well-known models. The proposed DAE model trained greedy layer-wise fashion order avoid overfitting local optima. experimental results on KDD-CUP'99 dataset show that our provides...

In machine learning one often assumes the data are independent when evaluating model performance. However, this rarely holds in practise. Geographic information sets an example where points have stronger dependencies among each other closer they geographically. This phenomenon known as spatial autocorrelation (SAC) causes standard cross validation (CV) methods to produce optimistically biased prediction performance estimates for models, which can result increased costs and accidents...

One of the most challenging problems facing network operators today is attacks identification due to extensive number vulnerabilities in computer systems and creativity attackers. To address this problem, we present a deep learning approach for intrusion detection systems. Our uses Deep Auto-Encoder (DAE) as one well-known models. The proposed DAE model trained greedy layer-wise fashion order avoid overfitting local optima. experimental results on KDD-CUP'99 dataset show that our provides...

Background The molecular mechanisms mediating postnatal loss of cardiac regeneration in mammals are not fully understood. We aimed to provide an integrated resource mRNA , protein, and metabolite changes the neonatal heart for identification metabolism‐related associated with regeneration. Methods Results Mouse ventricular tissue samples taken on day 1 (P01), P04, P09, P23 were analyzed RNA sequencing global proteomics metabolomics. Gene ontology analysis, KEGG pathway fuzzy c‐means...

This paper proposes a novel and simple local neural classifier for the recognition of mental tasks from on-line spontaneous EEG signals. The proposed recognizes three Correct is around 70%. modest rate largely compensated by two properties, namely low percentage wrong decisions (below 5%) rapid responses (every 1/2 s). Interestingly, achieves this performance with few units, normally just one per task. Also, since subject his/her personal interface learn simultaneously each other, subjects...

Electroencephalograph (EEG)-based brain-computer interfaces (BCI's) require on-line detection of mental states from spontaneous EEG signals, In this framework, surface Laplacian (SL) transformation signals has proved to improve the recognition scores imagined motor activity. The results authors obtained in first year an European project named adaptive brain (ABI) suggest that: (1) activity can be by using signal space projection (SSP) method as a classifier and (2) particular type electrodes...

An ecological niche modelling (ENM) approach was developed to model the suitable habitat for 0-group European hake, Merluccius merluccius L., 1758, in Mediterranean Sea. The ENM built combining knowledge on biological traits of hake recruits (e.g. growth, settlement, mobility and feeding strategy) with patterns selected variables (chlorophyll-a fronts concentration, bottom depth, sea current temperature) highlight favourable nursery habitats. results show that nurseries require stable...

Background Low-density lipoprotein (LDL) particles, the major carriers of cholesterol in human circulation, have a key role physiology and development atherosclerosis. The most prominent structural components LDL are core-forming cholesteryl esters (CE) particle-encircling single copy huge, non-exchangeable protein, apolipoprotein B-100 (apoB-100). shape native particles conformation apoB-100 on remain incompletely characterized at physiological body temperature (37°C). Methodology/Principal...

In recent years, Artificial Intelligence (AI) has been widely deployed in a variety of business sectors and industries, yielding numbers revolutionary applications services that are primarily driven by high-performance computation storage facilities the cloud. On other hand, embedding intelligence into edge devices is highly demanded emerging such as autonomous systems, human-machine interactions, Internet Things (IoT). these applications, it advantageous to process data near or at source...

Object detection is a fundamental computer vision task for many real-world applications. In the maritime environment, this challenging due to varying light, view distances, weather conditions, and sea waves. addition, light reflection, camera motion illumination changes may cause false detections. To address challenge, we present three fusion architectures fuse two imaging modalities: visible infrared. These can provide complementary information from modalities in different levels:...

Autonomous systems are becoming inherently ubiquitous with the advancements of computing and communication solutions enabling low-latency offloading real-time collaboration distributed devices. Decentralized technologies blockchain ledger (DLTs) playing a key role. At same time, advances in deep learning (DL) have significantly raised degree autonomy level intelligence robotic autonomous systems. While these technological revolutions were taking place, raising concerns terms data security...

Abnormal behavior detection is currently receiving much attention because of the availability marine equipment and data allowing maritime agents to track vessels. One most popular tools for developing an efficient anomaly system Automatic Identification System (AIS). The aim this paper explore performance existing well-known clustering methods detecting two dangerous abnormal behaviors based on AIS. include K-means, Density-Based Spatial Clustering Applications with Noise (DBSCAN), Affinity...

We characterized features of magnetoencephalographic (MEG) and electroencephalographic (EEG) signals generated in the sensorimotor cortex three tetraplegics attempting index finger movements. Single MEG EEG trials were classified offline into two classes using different classifiers, a batch trained classifier dynamic classifier. Classification accuracies obtained with better, at 75%, 89%, 91% subjects, when 0.5-3.0-Hz frequency band. did not differ.

Abstract Forest harvesting operations with heavy machinery can lead to significant soil rutting. Risks of rutting depend on the bearing capacity which has considerable spatial and temporal variability. Trafficability prediction is required in selection suitable operation sites for a given time window conditions, on-site route optimization during operation. Integrative tools are necessary plan carry out forest minimal negative ecological economic impacts. This study demonstrates...

Two important aspects in dealing with autonomous navigation of a swarm drones are collision avoidance mechanism and formation control strategy; possible competition between these two modes operation may have negative implications for success efficiency the mission. This issue is exacerbated case distributed leader-follower based swarms since nodes concurrently decide act through individual observation neighbouring nodes' states actions. To dynamically handle this duality control, plan action...

Unprecedented agility and dexterous manipulation have been demonstrated with controllers based on deep reinforcement learning (RL), a significant impact legged humanoid robots. Modern tooling simulation platforms, such as NVIDIA Isaac Sim, enabling advances. This article focuses demonstrating the applications of in local planning obstacle avoidance one most fundamental ways which mobile robot interacts its environments. Although there is extensive research proprioception-based RL policies,...

Abstract Human pose estimation has gained significant attention in recent years for its potential to revolutionize athletic performance analysis, enhance understanding of player interactions, and optimize training regimes. Deep learning models, particularly Convolutional Neural Networks (CNNs), have outperformed traditional methods tasks. This study addresses a gap sports analytics by applying two popular CNN-based frameworks, YOLO DeepLabCut, analyze hurdles athletes. Videos single female...

Maximizing product use is a central goal of many businesses, which makes retention and monetization two analytics metrics in games. Player may refer to various duration variables quantifying use: total playtime or session are popular research targets, active well-suited for subscription Such often has the increasing player conversely decreasing churn. Survival analysis framework powerful tools well suited type data. This paper contributes new methods game on how can be measured using...

Abstract This work focuses on the development of an effective collision avoidance algorithm that detects and avoids obstacles autonomously in vicinity a potential by using single ultrasonic sensor controlling movement vehicle. The objectives are to minimise deviation from vehicle’s original path also utilising one cheapest sensors available for very lost cost systems. For instance, scenario where main ranging malfunctions, backup low is required safe navigation vehicle while keeping minimum....