177 Results Found

In this paper, we propose a multi-position cluster-based weighted position estimation method that minimizes the influence of multipath (MP)/non-line-of-sight (NLOS) signals using a global navigation satellite system (GNSS) receiver. The proposed meth...

This research proposes an algorithm that improves the position accuracy of indoor pedestrian dead reckoning, by compensating the position error with a magnetic field map-matching technique, using multiple magnetic sensors and an outlier mitigation te...

Aiming at the problem of mutual interference between millimeter-wave frequency-modulation continuous-wave (FMCW) radars, an interference mitigation method based on outlier detection and variational mode decomposition (VMD) is proposed in this paper....

The classification of the wireless propagation channel between Line-of-Sight (LOS) or Non-Line-of-Sight (NLOS) is useful in the operation of wireless communication systems. The research community has increasingly investigated the application of machi...

In multicriteria decision-making (MCDM), methods such as TOPSIS are essential for evaluating and comparing alternatives across multiple criteria. However, traditional normalization techniques often struggle with datasets containing outliers, large va...

Accurate and low-complexity phase estimation is crucial for optimal data recovery in coherent optical receivers, especially for applications in emerging scenarios such as low-margin optical networks, green networks, probabilistic-shaping modulation,...

The multipath effect is a critical factor that prevents the Global Navigation Satellite System (GNSS) from achieving millimeter-level positioning accuracy. A multipath hemispherical map (MHM) is a popular approach to achieving real-time multipath err...

The seismic data inversion from observations contaminated by spurious measures (outliers) remains a significant challenge for the industrial and scientific communities. This difficulty is due to slow processing work to mitigate the influence of the o...

It is well known that the microbiome data are ridden with outliers and have heavy distribution tails, but the impact of outliers and heavy-tailedness has yet to be examined systematically. This paper investigates the impact of outliers and heavy-tail...

Compound-Gaussian distributions with inverse Gaussian textures, referred to as the IGCG distributions, are often used to model moderate/high-resolution sea clutter in amplitude. In moderate/high-resolution maritime radars, parameter estimation of the...

In the presence of multicollinearity, the ordinary least squares (OLS) estimators, aside from BLUE (best linear unbiased estimator), lose efficiency and fail to achieve minimum variance. In addition, these estimators are highly sensitive to outliers...

Denoising is always an important step in seismic processing, in order to produce high-quality data for subsequent imaging and inversion. Different types of noise can be suppressed using targeted denoising methods. For outlier noise with singular ampl...

Outlier detection refers to the problem of the identification and, where appropriate, the elimination of anomalous observations from data. Such anomalous observations can emerge due to a variety of reasons, including human or mechanical errors, fraud...

There have been numerous studies attempting to overcome the limitations of current autonomous driving technologies. However, there is no doubt that it is challenging to promise integrity of safety regarding urban driving scenarios and dynamic driving...

The indoor localization method based on the Received Signal Strength (RSS) fingerprint is widely used for its high positioning accuracy and low cost. However, the propagation behavior of radio signals in an indoor environment is complicated and alway...

Precise and dependable wind speed forecasting (WSF) enables operators of wind turbines to make informed decisions and maximize the use of available wind energy. This study proposes a hybrid WSF model based on outlier correction, heuristic algorithms,...

In this work, we deal with a robust fitting of a wrapped normal model to multivariate circular data. Robust estimation is supposed to mitigate the adverse effects of outliers on inference. Furthermore, the use of a proper robust method leads to the d...

Fairness in peer review is of vital importance in academic activities. Current peer review systems focus on matching suitable experts with proposals but often ignore the existence of outliers. Previous research has shown that outlier scores in review...

Accurate diagnosis of acute appendicitis from abdominal ultrasound is a challenging task, since traditional sonographic diagnostic criteria for appendicitis, such as diameter, compressibility, and wall thickness, rely on complete identification or vi...

With the rapid growth of sensor technology and computer vision, efficient deep learning models are essential for real-time image feature extraction in resource-constrained environments. However, most existing quantized deep neural networks (DNNs) are...

Entropy quantification algorithms are becoming a prominent tool for the physiological monitoring of individuals through the effective measurement of irregularity in biological signals. However, to ensure their effective adaptation in monitoring appli...

This paper presents a novel unsupervised learning framework for estimating scene depth and camera pose from video sequences, fundamental to many high-level tasks such as 3D reconstruction, visual navigation, and augmented reality. Although existing u...

Retired batteries are approaching the recycling peak, and their secondary utilization can prevent resource waste and environmental pollution from battery retirement. Evaluating the state of health (SOH) of retired batteries is crucial for secondary u...

The implementation of accurate positioning methods in both line-of-sight (LOS) and non-line-of-sight (NLOS) environments has been emphasized for seamless 6G application services. In LOS environments with unobstructed paths between the transmitter and...

Coprime array with $M+N$ sensors can achieve an increased degrees-of-freedom (DOF) of $\mathcal{O}\left(MN\right)$ for direction-of-arrival (DOA) estimation. Utilizing the compressive sensing (CS)-based DOA estimation methods, the increased DOF offe...

The utilization of multibeam sonar systems has significantly facilitated the acquisition of underwater bathymetric data. However, efficiently processing vast amounts of multibeam point cloud data remains a challenge, particularly in terms of rejectin...

Agricultural Internet of Things (Agri-IoT) systems need strong anomaly detection to monitor crops effectively. However, current approaches lack accuracy and efficiency. To mitigate this problem, we proposed an advanced hierarchical ensemble framework...

The ISP (Internet Service Provider) industry relies heavily on internet traffic forecasting (ITF) for long-term business strategy planning and proactive network management. Effective ITF frameworks are necessary to manage these networks and prevent n...

Estimating outstanding claims reserves in the non-life insurance business is often impaired by outlier-contaminated datasets. Widely used methods to eliminate outliers in non-life development triangles are either limiting the number of outliers by ro...

The network of distributed microphone arrays is usually established in an ad hoc manner; hence, network parameters such as the mutual positioning and rotation of the arrays, positions of sources, and synchronization of their recording onset times are...

A growing number of cases of the spread and establishment of non-native species outside their previously known ranges has been reported in recent years. Here we report new distributional records of Lepturges (Lepturges) limpidus Bates, 1872 (Cerambyc...

In smart meters, loose contact at screw terminals can lead to prolonged overheating and arcing, posing significant fire hazards. To mitigate these risks through early fault detection, this study proposes a data-driven framework integrating the Local...

Partial domain adaptation (PDA) is a framework for mitigating the covariate shift problem when target labels are contained in source labels. For this task, adversarial neural network (ANN) methods proposed in the literature have been proven to be fle...

Three-dimensional (3D) analysis of borehole data is very important for effective mineral exploration. It can be used not only to understand the geological structure of the underground, but to estimate the amount of the resource. In the mining industr...

Total kidney volume measured on MRI is an important biomarker for assessing the progression of autosomal dominant polycystic kidney disease and response to treatment. However, we have noticed that there can be substantial differences in the kidney vo...

Multitemporal imagery is by and large geometrically and radiometrically accurate, but the residual noise arising from removal clouds and other atmospheric and electronic effects can produce outliers that must be mitigated to properly exploit the remo...

In underwater environments, the presence of multipath effects can cause measurement outliers in acoustic sensors, leading to reduced estimation accuracy for integrated navigation. To address this issue, this paper proposes a sliding window variationa...

In brain mapping, structural templates derived from population-specific MRI scans are essential for normalizing individual brains into a common space. This normalization facilitates accurate group comparisons and statistical analyses. Although templa...

Operational safety and fuel efficiency are critical, yet often conflicting, objectives in modern civil get engine designs. Optimal efficiency operating conditions are typically close to unsafe regions, such as compressor stalls, which can cause sever...

Noncontact, high-fidelity data acquisition has enabled terrestrial laser scanning (TLS) to be widely adopted for bridge geometry measurement and condition monitoring. In TLS applications, point cloud registration directly affects data quality and the...

Vehicle gearboxes are subject to strong noise interference during operation, and the noise in the signal affects the accuracy of fault identification. Signal denoising and fault diagnosis processes are often conducted independently, overlooking their...

Fire models predict fire behavior and effects. However, there is a need to know how confident users can be in forecasts. This work developed a probabilistic methodology based on ensemble simulations that incorporated uncertainty in weather, fuel load...

Satellite-based navigation is prevalent in both commercial applications and critical infrastructures, providing precise position and time referencing. As a consequence, interference to such systems can have repercussions on a plethora of fields. Addi...

Robust estimation aims to provide accurate and reliable parameter estimations, particularly when data are affected by noise or outliers. Traditional methods like random sample consensus (RANSAC) struggle with handling outliers because they treat all...

Unmanned aerial vehicles (UAVs) are increasingly used indoors for inspection, security, and emergency tasks. Achieving accurate and robust localization under Global Navigation Satellite System (GNSS) unavailability and obstacle occlusions is therefor...

Ochroma pyramidale (Cav. ex. Lam.) Urb. (balsa-tree) is a commercially important tree species that ranges from Mexico to northern Brazil. Due to its low weight and mechanical endurance, the wood is particularly well-suited for wind turbine blades, sp...

Low carbon energy transitions are important to mitigate climate change, reduce air pollution, and reduce fossil fuel resource depletion. The Nordic countries (Denmark, Finland, Iceland, Norway, Sweden) are seen as leaders in low carbon energy transit...

In this paper, we present a novel multi-target feature selection algorithm that incorporates adaptive graph learning and target correlations. Specifically, our proposed approach introduces the low-rank constraint on the regression matrix, allowing us...

Achieving higher accuracy and robustness stands as the central objective in the navigation field. In complex urban environments, the integrity of GNSS faces huge challenges and the performance of integrated navigation systems can be significantly aff...

Climate clocks are currently ticking down to a point in time when it will be impossible to arrest the rate of CO₂ emissions within the bounds of the parameters set by the Paris Climate Agreement. The tourism academy has been at the forefront of effor...