This paper investigates system identification algorithms for modal identification of frame structures, such as a suspension bridge and an overhead transmission line-crossing frame, using ambient vibration measurements. The modal identification proced...
In order to improve the separation control effect of an oscillating jet, the external flow field of the actuators and the wing wake are obtained via hot-wire measurements to optimize the actuator and achieve wing separation flow control. The optimiza...
Vital defect information present in the magnetic field data of oil and gas pipelines can be perceived by developing such non-parametric algorithms that can extract modal features and performs structural assessment directly from the recorded signal da...
Sparse component analysis (SCA) has been widely used for blind source separation(BSS) for many years. Recently, SCA has been applied to operational modal analysis (OMA), which is also known as output-only modal identification. This paper considers th...
Operational modal analysis is based on data collected using a network of sensors installed on a monitored structure to measure its response to the external stimuli. As the instrumentation can be costly, sensors are placed at a limited number of locat...
The adoption of wireless sensor networks has brought a significant breakthrough in structural health monitoring, providing an effective alternative to the challenges associated with traditional cable-based sensors. In recent years, a growing interest...
Accurate estimation of Interrupted Sampling Repeater Jamming (ISRJ) sampling duration is essential for effective radar anti-jamming. However, in complex electromagnetic environments, the simultaneous presence of suppressive and deceptive jamming, cou...
Lamb waves have multimodal and dispersion effects, which reduces their performance in damage localization with respect to resolution. To detect damage with fewest sensors and high resolution, a method, using only two piezoelectric transducers and bas...
The passive estimation of harmonic sound source depth is of great significance for underwater target localization and identification. Passive source depth estimation using a single hydrophone with an unknown seabed geoacoustic property is a crucial c...
Metal structural plates are extensively used in various engineering structures due to their high strength, high-temperature resistance, toughness, and plasticity. However, they are susceptible to damage from external loads and impacts over time. The...
Numerous studies have demonstrated that animal brains accurately infer whether multisensory stimuli are from a common source or separate sources. Previous work proposed that the multisensory neurons in the dorsal medial superior temporal area (MST-d)...
This paper sets out to investigate the modal uses of the lexeme hɒ3 ‘good’ in the Jidong Shaoxing variety of Wu and to reconstruct its grammaticalization pathway. Modal meanings of hɒ3 include circumstantial possibility, deontic...
This study aims to propose and validate the state space mode decomposition technique for precise mode separation of non-classical damping systems and closely distributed modal systems. To assess the reliability and applicability of this technique, a...
Separating induction motor noise sources can provide an important reference basis for induction motor condition detection, noise reduction treatment, and fault diagnosis. Induction motors have different types of noise sources that partially overlap,...
RGB-D saliency object detection (SOD) primarily segments the most salient objects from a given scene by fusing RGB images and depth maps. Due to the inherent noise in the original depth map, fusion failures may occur, leading to performance bottlenec...
Deep water shallow natural gas hydrate (NGH) is a kind of clean energy and has entered the commercial exploitation stage. However, it produces a lot of seabed sediment in the process of large-scale mining, which not only easily causes undersea natura...
This study characterized the damage characteristics of carbon fiber composite pressure vessels by the modal acoustic emission (MAE) method. The study showed how to use the extracted damage modal features and established MAE parameters to determine th...
Modern high-bypass turbofan engines often operate near their structural natural frequencies, posing significant challenges for vibration isolation in aircraft engine mount systems. This study presents a comprehensive modal optimization framework to e...
Target detection in remote sensing images has garnered significant attention due to its wide range of applications. Many traditional methods primarily rely on unimodal data, which often struggle to address the complexities of remote sensing environme...
Parameter tuning based adapter methods have achieved notable success in vision-language models (VLMs). However, they face challenges in scenarios with insufficient training samples or limited resources. While leveraging image modality caching and ret...
Cross-modality person re-identification faces challenges such as illumination discrepancies, local occlusions, and inconsistent modality structures, leading to misalignment and sensitivity issues. We propose GLCN, a framework that addresses these pro...
Operational modal analysis (OMA) is required for the maintenance of large-scale civil structures. This paper developed a novel methodology of non-contact-based blind identification of the modal frequency of a vibrating structure from its video measur...
Successful performance of a task relies on selectively attending to the target, while ignoring distractions. Studies on perceptual load theory (PLT), conducted involving independent tasks with visual and auditory modalities, have shown that if a task...
This paper introduces Graph-Propagated Multi-Scale Hashing with Contrastive Learning (GPMCL), a novel unsupervised cross-modal hashing framework designed to address the semantic deficiency in large-scale unlabeled multimodal data. GPMCL first constru...
This dataset was acquired during collaboration and competition tasks performed by sixteen subject pairs (N = 32) of one female and one male under different (face-to-face and online) modalities. The collaborative task corresponds to cooperating to put...
Proactive inhibition is divided into two components: action postponing (AP), which refers to slowing the onset of response, and action restraint (AR), which refers to preventing the response. To date, several studies have reported alterations in proa...
Person re-identification is the task of recognizing a subject across different non-overlapping cameras across different views and times. Most state-of-the-art datasets and proposed solutions tend to address the problem of short-term re-identification...
The timely discovery of low-frequency oscillations in power systems and accurate identification of their modal parameters is critical in numerous applications. Therefore, we investigated the feasibility of using multi-channel signals and established...
To improve the spatial processing performance in the low frequency and long range shallow water communication system, a multi-mode joint equalization scheme is proposed, which combines modal depth function estimation, mode filtering, and multi-input...
Semantic segmentation of multi-modal remote sensing images is an important branch of remote sensing image interpretation. Multi-modal data has been proven to provide rich complementary information to deal with complex scenes. In recent years, semanti...
Due to the fast retrieval speed and low storage cost, cross-modal hashing has become the primary method for cross-modal retrieval. Since the emergence of deep cross-modal hashing methods, cross-modal retrieval significantly improved. However, the exi...
Medical images of brain tumors are critical for characterizing the pathology of tumors and early diagnosis. There are multiple modalities for medical images of brain tumors. Fusing the unique features of each modality of the magnetic resonance imagin...
The cross-modal retrieval task can return different modal nearest neighbors, such as image or text. However, inconsistent distribution and diverse representation make it hard to directly measure the similarity relationship between different modal sam...
A symmetric graphene plasmon waveguide (SGPWG) is proposed here to achieve excellent subwavelength waveguiding performance of mid-infrared waves. The modal properties of the fundamental graphene plasmon mode are investigated by use of the finite elem...
Enabling the effective representation of an object’s position and depth in augmented reality (AR) is crucial not just for realism, but also to enable augmented reality’s wider utilization in real world applications. Domains such as archit...
Most well-known supervised dimensionality reduction algorithms suffer from the curse of dimensionality while handling high-dimensional sparse data due to ill-conditioned second-order statistics matrices. They also do not deal with multi-modal data pr...
Apparently, Subjunctive tenses express temporal location, and, in some constructions, the past subjunctive can also express modal values. A long-standing debate exists over whether—even in the latter case—verbal tenses are temporal operat...
Audio guidance is a common means of helping visually impaired individuals to navigate, thereby increasing their independence. However, the differences between different guidance modalities for locating objects in 3D space have yet to be investigated....
The characteristics of oscillation modes, such as interarea, regional, and subsynchronous modes, can vary during a power system fault, which can cause switching and control actions in the power system. Transient data of the modal response due to such...
In recent years, the single-modal spam filtering systems have had a high detection rate for image spamming or text spamming. To avoid detection based on the single-modal spam filtering systems, spammers inject junk information into the multi-modality...
This paper proposes a methodology to process and interpret the complex signals acquired from the health monitoring of civil structures via scale-space empirical wavelet transform (EWT). The FREEVIB method, a widely used instantaneous modal parameters...
As traditional automobiles develop towards new energy vehicles, the noise, vibration and harshness (NVH) performance of automobiles is facing new challenges. Without the cover of the traditional engine noise and inlet and exhaust noise, the high-spee...
Actual industrial processes often exhibit multimodal characteristics, and their data exhibit complex features, such as being dynamic, nonlinear, multimodal, and strongly coupled. Although many modeling approaches for process fault monitoring have bee...
Thermal Power Plants (TPPs), as widely used industrial facilities for electricity generation, represent a key task in remote sensing image interpretation. However, detecting TPPs remains a challenging task due to their complex and irregular compositi...
As the scale of distribution networks expand, existing defect identification methods face numerous challenges, including limitations in single-modal feature identification, insufficient cross-modal information fusion, and the lack of a multi-stage fe...
Remote sensing cross-modal text-image retrieval (RSCTIR) has recently attracted extensive attention due to its advantages of fast extraction of remote sensing image information and flexible human–computer interaction. Traditional RSCTIR methods...
In the field of modern computer vision, pedestrian detection technology holds significant importance in applications such as intelligent surveillance, autonomous driving, and robot navigation. However, single-modal images struggle to achieve high-pre...
Gravitational wave (GW) signals are often affected by noise interference in the detection system; in order to attenuate the impact of detector noise and enhance the waveform characteristics of the signal, this paper proposes a space-based GW signal d...
To bridge the modality gap between camera images and LiDAR point clouds in autonomous driving systems—a critical challenge exacerbated by current fusion methods’ inability to effectively integrate cross-modal features—we propose the...
In multi-modal emotion aware frameworks, it is essential to estimate the emotional features then fuse them to different degrees. This basically follows either a feature-level or decision-level strategy. In all likelihood, while features from several...
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