Background/Objectives: Population aging is rapidly increasing, and the importance of preventive medicine has been stressed. Health checkups, diet, and exercise are of paramount importance. This study aimed to evaluate the effectiveness of a personali...
We developed a shoe sole sensor system with four high-capacity, compact triaxial force sensors using a nitrogen added chromium strain-sensitive thin film mounted on the sole of a shoe. Walking experiments were performed, including straight walking an...
This study aimed to investigate the timing of foot-off and initial contact at the end of the first walking training session with a Wearable Power-Assist Locomotor (WPAL) in novice healthy users. Eight healthy volunteers with no walking experience wit...
For the prevention of falling in the elderly, gait training has been proposed using tasks such as the multi-target stepping task (MTST), in which participants step on assigned colored targets. This study presents a gait measurement system using a las...
In this paper, we propose Sound Source Localization (SSL) using deep learning for Human–Robot Interaction (HRI) under intelligent robot environments. The proposed SSL method consists of three steps. The first step preprocesses the sound source...
In this paper, we address the task of zero-shot cross-lingual news sentiment classification. Given the annotated dataset of positive, neutral, and negative news in Slovene, the aim is to develop a news classification system that assigns the sentiment...
It has been suggested that neuroplasticity-promoting neuromodulation can restore sensory-motor pathways after spinal cord injury (SCI), reactivating the dormant locomotor neuronal circuitry. We introduce a neuro-rehabilitative approach that leverages...
Long-span railway bridges crossing active faults are more vulnerable owing to the joint combination of pulse ground motions and surface dislocation. To study the dynamic effects resulting from the coupling of long-span railway suspension bridges cros...
This study analyzes forecasts of Bitcoin price using the autoregressive integrated moving average (ARIMA) and neural network autoregression (NNAR) models. Employing the static forecast approach, we forecast next-day Bitcoin price both with and withou...
A number of previous works have shown that information about a subject is encoded in sparse kinematic information, such as the one revealed by so-called point light walkers. With the work at hand, we extend these results to classifications of soft bi...
To enhance the performance of surface electromyography (sEMG)-based gesture recognition, we propose a novel network-agnostic two-stage training scheme, called sEMGPoseMIM, that produces trial-invariant representations to be aligned with corresponding...
For a humanoid robot, it is difficult to predict a motion trajectory through end-to-end imitation learning when performing complex operations and multi-step processes, leading to jittering in the robot arm. To alleviate this problem and reduce the co...
The increasing need for scalable and efficient crop monitoring systems in industrial plant factories calls for image-based deep learning models that are both accurate and robust to domain variability. This study investigates the feasibility of CNN-ba...
The Fourier transform infrared microspectroscopy (FTIRm) system of the Australian Synchrotron has a unique optical configuration with a peculiar beam profile consisting of two parallel lines. The beam is tightly focused using a 36× Schwarzschil...
To address the semantic mismatch between limited textual descriptions in image captioning training datasets and the multi-semantic nature of images, as well as the underutilized external commonsense knowledge, this article proposes a novel image capt...
A comprehensive analysis of cross-country skiing races is a pivotal step in establishing effective training objectives and tactical strategies. This study aimed to develop a method of classifying sub-techniques and analyzing skiing characteristics du...
We present a method to train a deep-network-based feature descriptor to calculate discriminative local descriptions from renders and corresponding real images with similar geometry. We are interested in using such descriptors for automatic industrial...
Most cross-domain intelligent diagnosis approaches presume that the health states in training datasets are consistent with those in testing. However, it is usually difficult and expensive to collect samples under all failure states during the trainin...
In carbazole-substituted phthalocyanine complexes 2,3,9,10,16,17,23,24-octakis-(3,6-dibromo-9Hcarbazol) phthalocyaninato zinc(II) (Pc 2) and 2,3,9,10,16,17,23,24-Octakis-(9H-carbazol-9-yl) phthalocyaninato zinc(II) (Pc 4) and their conjugated complex...
Point cloud registration is a crucial preprocessing step for point cloud data analysis and applications. Nowadays, many deep-learning-based methods have been proposed to improve the registration quality. These methods always use the sum of two cross-...
Since building Neural Machine Translation (NMT) systems requires a large parallel corpus, various data augmentation techniques have been adopted, especially for low-resource languages. In order to achieve the best performance through data augmentatio...
Despite the abundance of research on coral reef change detection, few studies have been conducted to assess the spatial generalization principles of a live coral cover classifier trained using remote sensing data from multiple locations. The aim of t...
Good data feature representation and high precision classifiers are the key steps for pattern recognition. However, when the data distributions between testing samples and training samples do not match, the traditional feature extraction methods and...
Electronic nose (e-nose) is a new technology applied for the identification of volatile organic compounds (VOC) in breath air. Measuring VOC in exhaled breath can adequately identify airway inflammation, especially in asthma. Its noninvasive characte...
Recently, the dangers associated with face generation technology have been attracting much attention in image processing and forensic science. The current face anti-spoofing methods based on Generative Adversarial Networks (GANs) suffer from defects...
Worldwide, a large number of cases of harmful mushroom exposure and consumption result in hallucinations, sickness, and death. One contributing factor is that certain poisonous mushrooms closely resemble their edible counterparts, making it difficult...
Recently, digital pathology is an essential application for clinical practice and medical research. Due to the lack of large annotated datasets, the deep transfer learning technique is often used to classify histopathology images. A softmax classifie...
High-fidelity structural analysis using numerical techniques, such as finite element method (FEM), has become an essential step in design of laminated composite structures. Despite its high accuracy, the computational intensiveness of FEM is its seri...
Walking is the original form of transportation, and pedestrians have always made up a significant share of transportation system users. In contrast to motorized traffic, which has to move on precisely defined lanes and follow strict rules, pedestrian...
In this work, a cross-validation procedure is used to identify an appropriate Autoregressive Integrated Moving Average model and an appropriate state space model for a time series. A minimum size for the training set is specified. The procedure is ba...
The accurate prediction of train acceleration is an essential requirement for Automatic Train Operation (ATO) in urban railways. While traditional single-point mass models fail to capture the distributed dynamics of coupled vehicles, multi-point mode...
16 November 2023
Background: It is well-established that cross-sectional measurements of poor body composition are associated with impaired physical function and that power training effectively enhances total lean mass and physical function in older adults. However,...
Since various phenomena produce infrasound, including both man-made and natural sources, the ever-growing dataflow demands automatic processes via machine learning for signal classification. In this study, we demonstrate a single array approach at th...
Image captioning plays a crucial role in aligning visual content with natural language, serving as a key step toward effective cross-modal understanding. Transformer has become the dominant language model in image captioning. Existing Transformer-bas...
This work presents a lightweight and practical methodology for detecting inter-turn short-circuit faults in squirrel-cage induction motors under different mechanical load conditions. The proposed approach utilizes a one-dimensional convolutional neur...
The temporal dominance of sensations (TDS) method captures assessors’ real-time sensory experiences during food tasting, while the temporal liking (TL) method evaluates dynamic changes in food preferences or perceived deliciousness. These senso...
Knowledge of protein-protein interactions and their binding sites is indispensable for in-depth understanding of the networks in living cells. With the avalanche of protein sequences generated in the postgenomic age, it is critical to develop computa...
Edible mushrooms have been recognized as a highly nutritional food for a long time, thanks to their specific flavor and texture, as well as their therapeutic effects. This study proposes a new, simple approach based on FT-IR analysis, followed by sta...
Ship detection in remote sensing images plays an important role in maritime surveillance. Recently, convolution neural network (CNN)-based methods have achieved state-of-the-art performance in ship detection. Even so, there are still two problems tha...
Retention time prediction, facilitated by advances in machine learning, has become a useful tool in untargeted LC-MS applications. State-of-the-art approaches include graph neural networks and 1D-convolutional neural networks that are trained on the...
Step counting devices were previously shown to be efficient in a variety of applications such as athletic training or patient’s care programs. Various sensor placements and algorithms were previously experimented, with a best mean absolute perc...
An algorithm providing information on the key geometric features of an aorta extracted from multi-slice computed tomography images is proposed. Using the numerical method, the aorta’s geometric characteristics, such as vessel cross-sectional ar...
The precise identification of splice sites is essential for unraveling the structure and function of genes, constituting a pivotal step in the gene annotation process. In this study, we developed a novel deep learning model, DRANetSplicer, that integ...
To minimize dependency on the availability of data labels, some WiFi-CSI based-gesture recognition solutions utilize an unsupervised representation learning phase prior to fine-tuning downstream task classifiers. In this case, however, the overall pe...
Mathematical modeling and data-driven methodologies are frequently required to optimize industrial processes in the context of Cyber-Physical Systems (CPS). This paper introduces the PipeGraph software library, an open-source python toolbox for easin...
Background/Objectives: Physical inactivity and sedentary lifestyles remain leading behavioral risk factors for chronic disease across generations. Mothers with young children face unique barriers to exercise, including time constraints, fatigue, and...
The aim of this study was to investigate if the order of submaximal lactate threshold and maximal oxygen uptake testing would influence test outcomes. Twelve well-trained male cross-country skiers (mean age 19.6 years) performed two test sessions wit...
Segmenting vessels in brain images is a critical step for many medical interventions and diagnoses of illnesses. Recent advances in artificial intelligence provide better models, achieving a human-like level of expertise in many tasks. In this paper,...
The cross-sectional dimensions of structural elements in a structure are design elements that need to be carefully designed and are related to the stiffness of the structure. Various optimization processes are applied to determine the optimum cross-s...
Clinical support systems are affected by the issue of high variance in terms of chronic disorder prognosis. This uncertainty is one of the principal causes for the demise of large populations around the world suffering from some fatal diseases such a...
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