Search Results (24,532)

This paper presents the development of a vital sign monitoring system designed specifically for professional athletes, with a focus on runners. The system aims to enhance athletic performance and mitigate health risks associated with intense training regimens. It comprises a wearable glove that monitors key physiological parameters such as heart rate, blood oxygen saturation (SpO2), body temperature, and gyroscope data used to calculate linear speed, among other relevant metrics. Additionally, environmental variables, including ambient temperature, are tracked. To ensure accuracy, the system incorporates an onboard filtering algorithm to minimize false positives, allowing for timely intervention during instances of physiological abnormalities. The study demonstrates the system’s potential to optimize performance and protect athlete well-being by facilitating real-time adjustments to training intensity and duration. The experimental results show that the system adheres to the classical “220-age” formula for calculating maximum heart rate, responds promptly to predefined thresholds, and outperforms a moving average filter in noise reduction, with the Gaussian filter delivering superior performance. Full article

Background: Both lung lobe segmentation and lung fissure segmentation are useful in the clinical diagnosis and evaluation of lung disease. It is often of clinical interest to quantify each lobe separately because many diseases are associated with specific lobes. Fissure segmentation is important for a significant proportion of lung lobe segmentation methods, as well as for assessing fissure completeness, since there is an increasing requirement for the quantification of fissure integrity. Methods: We propose a method for the fully automatic segmentation of pulmonary fissures on lung computed tomography (CT) based on U-Net and PAN models using a Derivative of Stick (DoS) filter for data preprocessing. Model ensembling is also used to improve prediction accuracy. Results: Our method achieved an F1 score of 0.916 for right-lung fissures and 0.933 for left-lung fissures, which are significantly higher than the standalone DoS results (0.724 and 0.666, respectively). We also performed lung lobe segmentation using fissure segmentation. The lobe segmentation algorithm shows results close to those of state-of-the-art methods, with an average Dice score of 0.989. Conclusions: The proposed method segments pulmonary fissures efficiently and have low memory requirements, which makes it suitable for further research in this field involving rapid experimentation. Full article

An approach to approximate the 2D Gaussian filter for all possible kernel sizes based on the binary optimization technique is introduced. The approximate filter coefficients are designed as negative powers of two, allowing hardware implementation with remarkable savings in the chip area. The proposed approximate filters were evaluated and compared with competing methods using both similarity analysis and edge detection applications. The proposed method and the competing works for masks of size 3×3, 5×5, and 7×7 were implemented in a Xilinx Artix-7 FPGA. The proposed method showed up to a 60.0% reduction in DSP usage and a 75.0% increase in the maximum operating frequency when compared with state-of-art methods for the 7×7 kernel size case and a 48.8% reduction in the dynamic power normalized by the maximum operating frequency. Full article

The growth of high-quality in vitro potato plants (Solanum stenotomum subsp. stenotomum, Solanum stenotomum subsp. goniocalyx, and Solanum tuberosum subsp. andigena) is affected by multiple biological, operational, and environmental factors. Research on in vitro culture is frequently focused on the species, explant, composition of the culture medium, and incubation conditions, but only limited information is available on the effect of the gas exchange rate and volume of in vitro culture vessels under variable planting densities. In the present study, these factors were evaluated with a set of seven diverse potato landraces. The results were compared to the plants’ responses in routinely used in vitro culture vessels, i.e., 13 × 100 mm and 25 × 150 mm test tubes, and GA7^® magenta vessels. In vitro potato plants grown in plastic vessels equipped with a HEPA filter delivering a high gas exchange rate developed thicker stems (0.95 mm), a higher total average leaf area (2.51 cm²), increased chlorophyll content in leaves (32.2 ppm), and lower moisture content in their tissues (90.1%) compared to filter systems with lower gas exchange rates. A high planting density of 10 × 10 plants per vessel (360 and 870 mL) negatively affected the average stem width and root length but increased the plant height (3.4 cm). High fluctuations of ion-uptake of NO₃⁻, Ca⁺⁺, K⁺, and Na⁺ were observed between genotypes, with some accessions having a 4.6-times higher Ca⁺⁺-ion concentration in their tissues (190–234 ppm). The in vitro plants developed more robust stems, longer roots, and larger leaves within in vitro culture vessels equipped with a HEPA filter (high gas exchange rate) compared to the control vessels, in contrast to the chlorophyll content in leaves, which was higher in plants grown in narrow test tubes. Depending on the purpose of the subculture of in vitro plants, their growth and development can be molded using different gas exchange rates, planting densities, and vessel volumes. Full article

A Lamb wave is a guided wave that propagates within plate-like structures, with its vibration mode resulting from the coupling of a longitudinal wave and a shear vertical wave, which can be applied in sensors, filters, and frequency control devices. The working principle of Lamb wave sensors relies on the excitation and propagation of this guided wave within piezoelectric material. Lamb wave sensors exhibit significant advantages in various sensing applications due to their unique wave characteristics and design flexibility. Compared to traditional surface acoustic wave (SAW) and bulk acoustic wave (BAW) sensors, Lamb wave sensors can not only achieve higher frequencies and quality factors in smaller dimensions but also exhibit superior integration and multifunctionality. In this paper, we briefly introduce Lamb wave sensors, summarizing methods for enhancing their sensitivity through optimizing electrode configurations and adjusting piezoelectric thin plate structures. Furthermore, this paper systematically explores the development of Lamb wave sensors in various sensing applications and provides new insights into their future development. Full article

This research focused on the helicopter turboshaft engine dynamic model, identifying task solving in unsteady and transient modes (engine starting and acceleration) based on sensor data. It is known that about 85% of helicopter turboshaft engines operate in steady-state modes, while only around 15% operate in unsteady and transient modes. Therefore, developing dynamic multi-mode models that account for engine behavior during these modes is a critical scientific and practical task. The dynamic model for starting and acceleration modes has been further developed using on-board parameters recorded by sensors (gas-generator rotor r.p.m., free turbine rotor speed, gas temperature in front of the compressor turbine, fuel consumption) to achieve a 99.88% accuracy in identifying the dynamics of these parameters. An improved Elman recurrent neural network with dynamic stack memory was introduced, enhancing the robustness and increasing the performance by 2.7 times compared to traditional Elman networks. A theorem was proposed and proven, demonstrating that the total execution time for N Push and Pop operations in the dynamic stack memory does not exceed a certain value O(N). The training algorithm for the Elman network was improved using time delay considerations and Butterworth filter preprocessing, reducing the loss function from 2.5 to 0.12% over 120 epochs. The gradient diagram showed a decrease over time, indicating the model’s approach to the minimum loss function, with optimal settings ensuring the stable training. Full article

Bluetooth devices have been widely used for pedestrian positioning and navigation in complex indoor scenes. Bluetooth beacons are scattered throughout the entire indoor walkable area containing stairwells, and pedestrian positioning can be obtained by the received Bluetooth packets. However, the positioning performance is sharply deteriorated by the multipath effects originating from indoor clutter and walls. In this work, an ultra-wideband (UWB)-assisted Bluetooth acquisition of signal strength value method is proposed for the construction of a Bluetooth fingerprint library, and a multi-frame fusion particle filtering approach is proposed for indoor pedestrian localization for online matching. First, a polynomial regression model is developed to fit the relationship between signal strength and location. Then, particle filtering is utilized to continuously update the hypothetical location and combine the data from multiple frames before and after to attenuate the interference generated by the multipath. Finally, the position corresponding to the maximum likelihood probability of the multi-frame signal is used to obtain a more accurate position estimation with an average error as low as 70 cm. Full article

Drones are being used for agriculture monitoring in many different crops. Nevertheless, the use of drones for green areas’ evaluation is limited, and information is scattered. In this survey, we focus on the collection and evaluation of existing experiences of using drones for turfgrass monitoring. Despite a large number of initial search results, after filtering the information, very few papers have been found that report the use of drones in green areas. Several aspects of drone use, the monitored areas, and the additional ground-based devices for information monitoring are compared and evaluated. The data obtained are first analysed in a general way and then divided into three groups of papers according to their application: irrigation, fertilisation, and others. The main results of this paper indicate that despite the diversity of drones on the market, most of the researchers are using the same drone. Two options for using cameras in order to obtain infrared information were identified. Moreover, differences in the way that drones are used for monitoring turfgrass depending on the aspect of the area being monitored have been identified. Finally, we have indicated the current gaps in order to provide a comprehensive view of the existing situation and elucidate future trends of drone use in turfgrass management. Full article

Low ventilation rates used to conserve energy in pig nurseries in winter can worsen air quality, harming piglet health. A recirculating air cleaner consisting of a dust filter and ultraviolet C (UVC) lamps was evaluated in a pig nursery. It had a recirculation rate of 6.4 air changes per hour, residence time of 0.43 s, and UVC volumetric dose of 150 J·m⁻³. Reduced ventilation led to high particulate matter (PM) concentrations in the nursery. During the first 9 d, the air cleaner increased floor temperature in its vicinity by 1.9 °C vs. a more distant location. The air cleaner had average removal efficiencies of 29 and 27% for PM_2.5 (PM with aerodynamic equivalent diameter or AED < 2.5 µm) and PM₁₀ (PM with AED < 10 µm), respectively. It reduced PM_2.5 and PM₁₀ concentrations by 38 and 39%, respectively, in its vicinity vs. a more distant location. The air cleaner was mostly inconsistent in inactivating heterotrophic bacteria, but it eliminated fungi. It trapped 56% of the ammonia but did not trap nitrous oxide, methane, or carbon dioxide. The air cleaner demonstrated the potential for reducing butanoic, propanoic, and pentanoic acids. Design improvements using modeling and further testing are required. Full article

Visual servoing technology is well developed and applied in many automated manufacturing tasks, especially in tools’ pose alignment. To access a full global view of tools, most applications adopt an eye-to-hand configuration or an eye-to-hand/eye-in-hand cooperation configuration in an automated manufacturing environment. Most research papers mainly put efforts into developing control and observation architectures in various scenarios, but few have discussed the importance of the camera’s location in the eye-to-hand configuration. In a manufacturing environment, the quality of camera estimations may vary significantly from one observation location to another, as the combined effects of environmental conditions result in different noise levels of a single image shot in different locations. In this paper, we propose an algorithm for the camera’s moving policy so that it explores the camera workspace and searches for the optimal location where the image’s noise level is minimized. Also, this algorithm ensures the camera ends up at a suboptimal (if the optimal one is unreachable) location among the locations already searched with the limited energy available for moving the camera. Unlike a simple brute-force approach, the algorithm enables the camera to explore space more efficiently by adapting the search policy by learning the environment. With the aid of an image-averaging technique, this algorithm, in the use of a solo camera, achieves observation accuracy in eye-to-hand configurations to a desirable extent without filtering out high-frequency information in the original image. An automated manufacturing application was simulated, and the results show the success of this algorithm’s improvement in observation precision with limited energy. Full article

With the increasing awareness of environmental protection, the rotary hearth furnace system has emerged as a key technology that facilitates a win-win situation for both environmental protection and enterprise economic benefits. This is attributed to its high flexibility in raw material utilization, capability of directly supplying blast furnaces, low energy consumption, and high zinc removal rate. However, the complexity of the raw material proportioning process coupled with the rotary hearth furnace system’s reliance on human labor results in a time-consuming and inefficient process. This paper innovatively introduces an intelligent formula method for proportioning raw materials based on online clustering algorithms and develops an intelligent batching system for rotary hearth furnaces. Firstly, the ingredients of raw materials undergo data preprocessing, which involves using the local outlier factor (LOF) method to detect any abnormal values, using Kalman filtering to smooth the data, and performing one-hot encoding to represent the different kinds of raw materials. Afterwards, the affinity propagation (AP) clustering method is used to evaluate past data on the ingredients of raw materials and their ratios. This analysis aims to extract information based on human experience with ratios and create a library of machine learning formulas. The incremental AP clustering algorithm is utilized to learn new ratio data and continuously update the machine learning formula library. To ensure that the formula meets the actual production performance requirements of the rotary hearth furnace, the machine learning formula is fine-tuned based on expert experience. The integration of machine learning and expert experience demonstrates good flexibility and satisfactory performance in the practical application of intelligent formulas for rotary hearth furnaces. An intelligent batching system is developed and executed at a steel plant in China. It shows an excellent user interface and significantly enhances batching efficiency and product quality. Full article

In many languages, a subject/non-subject Ā-extraction asymmetry can be observed: While non-subject extraction is unproblematic, long extraction of the subject requires repair strategies. This phenomenon is known as the that-trace effect. Two broad types of approaches to this effect have been proposed in the literature: (a) structural accounts that prohibit subject extraction in the syntax; (b) surface-oriented PF accounts according to which nothing blocks long subject movement in the syntax, but a surface filter prohibits the output string where a trace follows the complementizer. In this paper, we argue for a syntactic cause of the effect in Igbo (Benue-Congo, Nigeria). The empirical evidence centers around the distribution of resumptive pronouns in the language. We show that Igbo has all the ingredients required for a PF approach to the that-trace effect (viz., long Ā-movement and trace spell-out); nevertheless, it does not apply them to enable long subject extraction but rather resorts to prolepsis (among other strategies). Further evidence against a PF account comes from the impossibility of short subject extraction. Finally, we provide evidence from subextraction from subjects for an antilocality component underlying the subject extraction restriction in Igbo. Full article

This study addresses the dynamic object detection problem for Unmanned Surface Vehicles (USVs) in marine environments, which is complicated by boat tilting and camera illumination sensitivity. A novel pipeline named “Seal” is proposed to enhance detection accuracy and reliability. The approach begins with an innovative preprocessing stage that integrates data from the Inertial Measurement Unit (IMU) with LiDAR sensors to correct tilt-induced distortions in LiDAR point cloud data and reduce ripple effects around objects. The adjusted data are grouped using clustering algorithms and bounding boxes for precise object localization. Additionally, a specialized Kalman filter tailored for maritime environments mitigates object discontinuities between successive frames and addresses data sparsity caused by boat tilting. The methodology was evaluated using the VRX simulator, with experiments conducted on the Volga River using real USVs. The preprocessing effectiveness was assessed using the Root Mean Square Error (RMSE) and tracking accuracy was evaluated through detection rate metrics. The results demonstrate a 25% to 30% improvement in detection accuracy and show that the pipeline can aid industry even with sparse object representation across different frames. This study highlights the potential of integrating sensor fusion with specialized tracking for accurate dynamic object detection in maritime settings, establishing a new benchmark for USV navigation systems’ accuracy and reliability. Full article

Visual–Inertial SLAM (VI-SLAM) has a wide range of applications spanning robotics, autonomous driving, AR, and VR due to its low-cost and high-precision characteristics. VI-SLAM is divided into localization and mapping tasks. However, researchers focus more on the localization task while the robustness of the mapping task is often ignored. To address this, we propose a map-point convergence strategy which explicitly estimates the position, the uncertainty, and the stability of the map point (SoM). As a result, the proposed method can effectively improve the quality of the whole map while ensuring state-of-the-art localization accuracy. The convergence strategy mainly consists of a perpendicular-based triangulation and 3D Gaussian–uniform mixture filter, and we name it PGMF, perpendicular-based 3D Gaussian–uniform mixture filter. The algorithm is extensively tested on open-source datasets, which shows the RVM (Ratio of Valid Map points) of our algorithm exhibits an average increase of 0.1471 compared to VINS-mono, with a variance reduction of 68.8%. Full article

Soft soil sites can amplify the peak acceleration by a factor of 1.5 to 3.5 and exhibit the filtering effect on seismic waves. This effect results in the attenuation of high frequencies, amplification of low frequencies, and extension of the predominant period of ground motion. Consequently, soft soil sites have a more pronounced impact on isolation buildings constructed on them. The seismic isolation structure design typically involves assuming rigid foundation for calculations. However, the soil properties can significantly impact the dynamic response of the structure, affecting factors such as input ground motion, changes in vibration characteristics, radiation energy dissipation, and material damping energy dissipation. Therefore, neglecting these influences and relying solely on the rigid foundation assumption for calculations can lead to significant errors in the final seismic response analysis of the structure. Currently, there are numerous LNG storage tanks, museums, and other isolation buildings constructed on soft soil sites. Therefore, research on seismic isolation measures for soft soil sites holds significant practical importance. In light of this, this paper, firstly, provides a systematic summary of seismic isolation strategies and engineering applications for soft soil sites. Secondly, it further discusses advancements in research on the dynamic interactions of soil–isolated structures, covering analytical methods, numerical investigations, and experimental studies on soft soil sites. Lastly, the paper concludes with insights on current research progress and prospects for further studies. Full article