Drop Mechanism Research Articles

Attention-guided mask learning for self-supervised 3D action recognition

Most existing 3D action recognition works rely on the supervised learning paradigm, yet the limited availability of annotated data limits the full potential of encoding networks. As a result, effective self-supervised pre-training strategies have been actively researched. In this paper, we target to explore a self-supervised learning approach for 3D action recognition, and propose the Attention-guided Mask Learning (AML) scheme. Specifically, the dropping mechanism is introduced into contrastive learning to develop Attention-guided Mask (AM) module as well as mask learning strategy, respectively. The AM module leverages the spatial and temporal attention to guide the corresponding features masking, so as to produce the masked contrastive object. The mask learning strategy enables the model to discriminate different actions even with important features masked, which makes action representation learning more discriminative. What’s more, to alleviate the strict positive constraint that would hinder representation learning, the positive-enhanced learning strategy is leveraged in the second-stage training. Extensive experiments on NTU-60, NTU-120, and PKU-MMD datasets show that the proposed AML scheme improves the performance in self-supervised 3D action recognition, achieving state-of-the-art results.

Analysis of the Flow Structure inside an Oscillating Sessile Drops in a Shear Flow Using Double-Helix 3D Particle Tracking Velocimetry and Adaptive Optics

The motion and particularly the detachment mechanism of sessile drops in an air-shear-flow is highly relevant for many technical applications. For instance, water drops in fuel cells can block the oxygen transport and thus lower the overall efficiency. Hence, a deeper understanding of the drop detachment mechanism could facilitate efficiency optimisations. Nonetheless, until now only simplified models exist for predicting the critical velocity that do not take into account the mutual interaction of the air and the liquid via the non-rigid interface. One reason for this is the lack of knowledge of the flow inside the oscillating drop. In this contribution, we present the first three-dimensional flow measurements in oscillating sessile drops in shear flow. Time-averaged flow measurements were conducted for different Reynolds numbers. Furthermore, the phase-averaged flow field was measured. The measurements were conducted with a novel 3D-PTV method, which offers scanless three-dimensional flow measurements with a single optical access for a measurement volume that covers about 90 % of the drop volume. Moreover, we present a novel technique for conducting flow measurements through fluctuating gas-liquid interfaces based on adaptive optics. We demonstrate that this technique enables the correction of a systematic error corresponding to the magnitude of the first drop eigenfrequency, which seems to play an important role in the detachment mechanism of drops. The results give new insights about the fluid mechanics of sessile drops and thus may help in the optimisation of drop removal in e. g. fuel cells.

AI Enabled Drone for Automatic Detection of Human Movements in Disaster Situation

The concept of an innovative drone system designed to revolutionize search and rescue operations in disaster scenarios. This system aims to harness the power of artificial intelligence (AI) for automatic human detection, alongside advanced technologies such as cameras, processors, and payload mechanisms. By integrating these components, the drone system will autonomously survey disaster areas, identifying individuals in need of assistance with precision and speed. Upon detection, the system will generate alarms to alert rescue teams promptly. Furthermore, the drone will be equipped with efficient payload dropping mechanisms, enabling it to deliver essential supplies to remote or inaccessible locations within the disaster zone. Through the seamless integration of AI and advanced technologies, this drone system represents a significant advancement in disaster response capabilities, with the potential to save lives and mitigate the impact of disasters on affected communities.

Advancement in Vegetable Transplanting: Mechanization, Challenges and Opportunities By IJISRT

The transplanting operation is required higher labour intensity and lower efficiency for the operation by hand in vegetable production. It is largely done by hand in India and vegetable transplanting is a time-consuming field operation when performed manually. This makes it necessary to adapt the mechanization for vegetable transplantation to save money and time and increase the productivity to fulfil the food requirement of a huge population. Due to the growing demand for vegetables all year round, the use of vegetable transplanters has become widespread in agricultural production. Hand transplanting of vegetable seedlings is always been a time consuming and laborious activity which often leads to muscular fatigue. The work is drudgeries and laborious as the operation is done in a bending and squatting posture. The semi-automatic vegetable transplanters are heavy to operate due to limitations on manual feeding rates of seedlings which vary with respect to work duration and skill of the operator. Automation in the field of vegetable transplanters has provided opportunities for savings in labour and time required for transplanting operation. The beginning and current advances in transplanting technologies suggest ample scope of working on automated seedling pickup and drop mechanisms using robotics. This study highlights the discuss vegetable transplanter and advances in transplanting technologies used in the field.

Reactive Power Demand Estimation and Dynamic Reactive Power Optimal Allocation for HVDC Receiving Network

The transient voltage stability of the receiver system is severely challenged by the AC-DC interaction and the short electrical distance between individual DC drop points of the receiver network. Firstly, the dynamic reactive power of DC receiver system is analyzed in this paper. The analysis of the dynamic reactive power in the DC receiver system is presented in this paper. In addition, the evaluation method for the reactive power necessary to sustain the voltage of the converter bus AC system is proposed, taking into consideration the voltage drop mechanism when a DC block occurs. Finally, a mechanism for the reactive power dynamic optimization of the AC-DC receiving power network is proposed based on the sensitivity of the transient voltage track index. The optimal access node is determined by quantitatively evaluating the bus transient voltage increase of the inverter station when each node is connected to the dynamic compensation device of reactive power, and the simulation calculation is carried out by the actual power network to validate the performance of the methodology.

DESIGN AND STRUCTURAL ANALYSIS OF THE CHARACTERISTICS OF A FIRE UNMANNED AERIAL VEHICLE

Wildfires are generally Class A fires that are very difficult to control due to difficult terrain and uncontrolled fire behavior. The purpose of this article is to propose the idea of using unmanned aerial vehicles such as a quadcopter to extinguish a forest fire. It is necessary to develop an unmanned aerial vehicle that can operate functionally at such elevated temperatures. These unmanned aerial vehicles, using a payload drop mechanism, can carry and drop fire extinguishing balls over the fire to extinguish it. Structural analysis is carried out to check the dynamic characteristics of these vehicles. Thermal insulation provided for sufficient thermal protection of electronics and circuits.

Research on The Source Parameters and Scaling Relations of Earthquakes in Weihe Basin and Its Adjacent Area

By using the data recorded in Shaanxi seismic network, seismic source parameters were determined through spectrum analyzing basing on Brune’s source model for 125 small to moderate earthquakes (1.1 ≤ ML ≤ 4.8) from 1997 to 2016 in Weihe basin and its adjacent area. Seismic radiated energies were also obtained through integral of observed velocity spectra. The relations between stress drop, scaled energy E s / M 0 and Zúñiga parameter ε with seismic moment are analyzed. The results show that the earthquakes are with low stress drop in this area, the mean value is 0.16 MPa. More than 90% of the events in the region observed the ε value is less than 1. The low stress drop and low ε value indicate that earthquakes in this area can be explained by fractional stress drop mechanism or low effective stress model. These may be the result of mature fault activity, however, it cannot be ruled out effect of underground fluid. The scaled energy of earthquakes (1.3 ≤ MW ≤ 3.6) in this area is less than that of larger earthquakes (3.6 ≤ MW ≤ 6.0) in other areas. The earthquakes in this area are fairly small, so the heat energy generated in the rupture process is small, which is not enough to produce melting along the fault plane. With large dynamic friction force, it is not easy to produce rapid brittle rupture, resulting in low scalsed energy.

Information support for the creation of a special purpose quadrocopter dropping mechanism

This article described the concept of a dropping mechanism for a special purpose quadcopter using graphical design methods. Also described is the information support for the creation of a dropping mechanism for special purpose quadcopters with wide modification possibilities, ease of maintenance of the dropping mechanism, and most importantly - with a low cost in the execution of the mechanism. The article described the developed and implemented dropping mechanism for special-purpose quadcopters with a wide range of modernization possibilities and fairly easy operational characteristics, namely: the dropping mechanism is designed to deliver cargo with a payload of up to 8 kg. During the implementation of the project, information support for the creation of a dropping mechanism for special-purpose quadcopters was described, in particular: a graphical calculation of the strength of the dropping mechanism under the conditions of payloads of different weights was performed and it was found that with a payload of up to 8 kg, the structure of the dropping mechanism can withstand the required load. A 3D model of the dropping mechanism was made, which combines ease of maintenance and wide possibilities for modernization. After the analysis of existing mechanisms, the basic form factor of the mechanism and its purpose were determined. Focusing on the calculations and construction of the developed dropping mechanism, an experimental model of the dropping mechanism was made using 3D printing.

Enhancing Autonomous Drones With Self- Designed Payload Dropping Mechanism

This research paper provides a comprehensive exploration of an autonomous drone experiment integrating the Pixhawk 2.4.8 flight controller. The study offers a detailed analysis of a drone system characterized by a 200-gram payload capacity and a maximum flight duration of 13 minutes. The CAD model, meticulously designed using Dassault's SolidWorks Design Tool, incorporates carbon fiber propellers to optimize both durability and flexibility. One noteworthy contribution of this research is the introduction of a self-designed payload deployment mechanism, further extending the drone's capabilities. Additionally, specialized landing equipment is developed to enhance takeoff and landing stability, thereby elevating overall system performance. The study emphasizes the drone's precise control and navigation capabilities, made possible by its robust processing capacity and integrated sensors. Leveraging the computational prowess of the Raspberry Pi 4B, this project efficiently manages complex algorithms crucial for autonomous operations, all while maintaining cost-effectiveness. The Raspberry Pi's high-resolution capabilities and seamless integration prove to be the optimal choice for accurate object detection, environmental recognition, autonomous navigation, and successful payload deployment missions. This research contributes valuable insights into the integration of advanced technologies in autonomous drone systems, with a particular focus on enhancing their capabilities through self-designed payload deployment mechanisms.

ResFuseYOLOv4_Tiny: Enhancing detection accuracy for lightweight networks in infrared small object detection tasks

When deploying infrared target detection systems at the edge, one often encounters constraints on computational and storage resources. In such scenarios, lightweight networks prove to be a viable detection solution. Compared to large-scale deep networks, lightweight networks, after discarding redundant structures, often do not achieve satisfactory detection accuracy, especially in the context of small object detection tasks. This paper proposes ResFuseYOLOv4_Tiny, an improved lightweight network specifically designed for the effective detection of infrared small objects, particularly in resource-constrained scenarios. We extend the YOLOv4_Tiny neck network to enable efficient feature extraction. By integrating Res_head with residual structures and fusion-based feature reuse, our framework substantially enhances the capability to detect small objects by expanding the receptive field and effectively merging features from various receptive fields. Additionally, we introduce a drop and adaptive parameter-based attention mechanism called DCA, leveraging the inclusion of drop layers to effectively reduce information redundancy. Moreover, we replace the conventional CIoU loss function with our customized MSIoU, incorporating parameter m to adaptively adjust the loss weights in response to the influence of small target sizes. Experimental results conducted on synthetic and real infrared small object datasets respectively reveal a significant 14.47% and 11.28% improvement in detection accuracy. The proposed ResFuseYOLOv4_Tiny framework presents a viable solution for lightweight networks when both detection speed and accuracy are concurrently considered.

Satisfying strict deadlines for cellular Internet of Things through hybrid multiple access

AbstractLatency‐constrained aspects of cellular Internet of Things (IoT) applications rely on Ultra‐Reliable and Low Latency Communications (URLLC), which highlight research on satisfying strict deadlines. In this study, we address the problem of latency‐constrained communications with strict deadlines under average power constraint using Hybrid Multiple Access (MA), which consists of both Orthogonal MA (OMA) and power domain Non‐Orthogonal MA (NOMA) as transmission scheme options. We aim to maximize the timely throughput, which represents the average number of successfully transmitted packets before deadline expiration, where expired packets are dropped from the buffer. We use Lyapunov stochastic optimization methods to develop a dynamic power assignment algorithm for minimizing the packet drop rate while satisfying time average power constraints. Moreover, we propose a flexible packet dropping mechanism called Early Packet Dropping (EPD) to detect likely to become expired packets and drop them immediately. Numerical results show that Hybrid MA improves the timely throughput compared to conventional OMA by up to and on average by more than . With EPD, these timely throughput gains improve to and , respectively.

Development of Binder-Free Pigment Inks for Direct Inkjet Printing on Cotton Fabric without Pretreatment.

Inkjet printing technology is widely used in the textile digital printing application today though the current technology still requires pretreatment and postwashing procedures before and after printing. Additional chemical treatment generates a large amount of wastewater and complicates the process. Among the many potential approaches for reducing chemical waste, pigments with self-dispersing capability were prepared and formulated into binder-free inkjet inks that require no pretreatment or after-washing process when printing cotton fabrics. The new self-dispersing pigment inks were tested and evaluated on cotton fabrics. The distribution of particles was between 122.2 and 188.5 nm, and inks have excellent storage capability. Printed fabrics' light fastness and acid/alkali resistance are about grade 5, and printed cotton's washing and rubbing fastness are above grade 3. The mechanism and performance of ink drops were investigated by LF-NMR and ink-drop observation methods. This work provides a possible solution for reducing wastewater in the textile industry.

Inter-Stage Pressure Drop of Multi-Stage Brush Seal With Differentiated Structure

Abstract Uneven pressure drops among stages of multistage brush seal (MBS) leads to early failure of single-stage seal units, which directly affects service life of the seal used in aeroengines, gas turbines, and steam turbines. In this paper, influence factors of interstage pressure drop were studied to analyze formation mechanism of the uneven pressure drops. Moreover, an MBS with differentiated structure was presented, and its interstage pressure drops were further investigated. The results showed that the MBS with several same single-stage seal units had uneven pressure drops among stages under high inlet/outlet pressure ratios. In view of remarkably increasing velocity and decreasing pressure in downstream region of bristle pack near rotor surface during flow of airflow, adjustments of structural parameters (i.e., increasing height of backing plate to rotor surface Hb, increasing seal clearance Hg, and decreasing axial width of bristle pack B) could improve the uneven pressure drops among different stages due to increasing outlet air flow area of the stage. The closer pressure drop proportions of different stages to ideal average value indicated increase of Hb had a more effective effect to balance the pressure drops among different stages compared to increase of Hg and decrease of B. An MBS with differentiated structure, in which both Hb and Hg of all the single-stage seal units were increased progressively and B was decreased step by step, showed a good performance to obtain even interstage pressure drops.

A Method for Diagnosing the Performance of the Dropping Mechanism in the High-Precision Absolute Gravimeter

The absolute gravimeters used in gravity measurements have wide applications across disciplines. The precision of a classical free-fall absolute gravimeter is limited by the performance of its dropping mechanism. The mismatch between the linear bearings and guideways can give rise to vibrations in measurement and lead to errors in the gravity results. To detect this problem, this research develops a diagnostic approach based on the current analysis of the motor that drives the dropping mechanism. Several dropping chambers are tested under gravity measurement within 12 hours to calculate the uncertainty of the mean and be tagged as qualified or unqualified. The status of the dropping mechanism is assessed by applying four parameters of the current data in the time and frequency domains during steady motion and feature coefficients of transient current under wavelet packet decomposition (WPD). The proper ranges of the parameters are identified through comparative experiments. Empirical evidence confirms the feasibility of the parameters and coefficients used to determine whether a gravimeter dropping mechanism meets the requirement of precision around 1 micro Gal. In addition, the analysis based on continuous wavelet transform (CWT) proves its potential to locate the faults in the unqualified dropping mechanism. The proposed diagnostic approach can be applied within 20 times of motor current acquisition, which makes it practicable and helpful in improving and achieving high-precision gravity measurement.

Collector-assisted efficient coal/gangue recognition based on liquid intervention in longwall top coal caving

ABSTRACT Efficient coal/gangue recognition is vital to improve the top coal recovery in thick seam mining with the longwall top coal caving method. Gangue is a gray-black rock mixed into the top coal flow during the drawing process. Liquid intervention is a new approach to distinguish coal and gangue based on their temperature difference through infrared thermal imaging. This study employs three common flotation collectors, kerosene, hydrocarbon oil, and activated slime collectors, with different concentrations for efficient coal/gangue recognition based on liquid intervention compared with that based on traditional liquid (clean water). The results show that all three collectors have a stronger ability to improve the temperature variation value of coal/gangue and expand the temperature difference between coal and gangue. In general, kerosene exhibits the best effect, and the activated slime and hydrocarbon oil collectors have a better effect when the concentration is low. The analyses of temperature dropping mechanisms verify that the recognition efficiency significantly improves with different collector-assisted interventions, while different collectors need different concentrations to achieve the best improving effect. This research provides a foundation to find an economical and efficient intervening liquid with a better recognition efficiency.

A constitutive model for porous media with recurring stress drops: From snow to foams and cereals

Porous media such as dry snow, cellular foams, or cereals, can experience abrupt and recurrent drops in stress when subjected to mechanical loading. While there appears to be little agreement on the initiating mechanism of stress drops, it is well-accepted that they correlate with the destruction of the meso-scale structure of the material. However, this observation has yet to supply a general predictive way to accommodate these stress drops at the constitutive level for porous media. Here, we develop a constitutive model to explain such behaviour in dry conditions. The model builds upon the concept of meso-related temperature, which characterises the fluctuating velocities of the meso-scale structure and is general to all heterogeneous porous media. We assume that a rise in meso-related temperature induces a loss of strength at the macro-scale, which leads to a stress drop. Furthermore, the meso-related temperature sinks into micro-related (thermal) temperature and thus allows for stress recovery after a drop. Our model exhibits different behaviours and stress drop regimes from these basic physical concepts, providing insight into previous experimental observations in porous media. While this is not an exhaustive model for any of the materials listed, it can provide a potential starting point for all of them.

A density map regression method and its application in the coal flotation froth image analysis

The surface feature of flotation froth is an indicator of the flotation process state. Image-based methods have long been considered as an indirect detector to access flotation working conditions. However, large and small bubbles stick together, resulting in shadows, occlusions and defocus problems in the flotation froth images acquired in the field. These problems lead to resistance to the accurate extraction of morphological features. This paper attempts to analyze the morphology of froth images from the perspective of bubble distribution. The proposed framework generates density maps measuring the sparsity of bubbles, which also serves as a meter to imply the morphology of froth images. In order to improve the quality of the regressed density map, label normalization was proposed to calibrate ground truth during the dataset production phase; the deconvolution module was introduced to the network to gain smoother bubbles boundaries; the loss selective drop mechanism was used to mitigate the negative impact of annotation deviation during the model training. The effectiveness of each module in the framework was verified by a series of ablation experiments on the coal flotation froth dataset. The experimental data shows that the error in measuring bubble mean size is 1.7%, the error in measuring ratio of the area between large and small bubbles is 0.8%, and the accuracy of measuring the spatial distribution of large and small bubbles is satisfactory.

Identity Checks & Correctness of Bank Account Using Penny Drop Procedure

Accuracy in identity of the person, his contact details, bank account are most essential data in any establishment to conduct any operations. These data must be collected and validated before on-boarding stage with requisite support evidence and must be maintained in the accounting system. In this fintech world there are many advancement in process to verify the correctness of the identity of the person and his bank account without major effort and time. Since the verification is done through the system there is no paper work and subsequent workflow can be smooth and reliable. Verification of identity of the person’s bank account in penny drop mechanism is discussed in this write-up.

The effect of electroactive length and intrinsic conductivity on the actuation behaviour of conducting polymer-based yarn actuators for textile muscles

Recently, electrically driven conducting polymer (CP) coated yarns have shown great promise to develop soft wearable applications because of their electrical and mechanical behaviour. However, designing a suitable yarn actuator for textile-based wearables with high strain is challenging. One reason for the low strain is the voltage drop along the yarn, which results in only a part of the yarn being active. To understand the voltage drop mechanism and overcome this issue intrinsically conductive yarns were used to create a highly conductive path along the full length of the yarn actuator. Ag plated knit-de-knit (Ag-KDK) structured polyamide yarns were used as the intrinsically conductive core material of the CP yarn actuators and compared with CP yarn actuators made of a non-conductive core knit-de-knit (KDK) yarn. The CP yarn actuators were fabricated by coating the core yarns with poly(3,4-ethylene dioxythiophene): poly(styrene sulfonic acid) followed by electrochemical polymerization of polypyrrole. Furthermore, to elucidate the effect of the capillarity of the electrolyte through the yarn actuator, two different approaches to electrochemical actuation were applied. All actuating performance of the materials were investigated and quantified in terms of both isotonic displacement and isometric developed forces. The resultant electroactive yarn exhibits high strain (0.64 %) in NaDBS electrolytes as compared to previous CP yarn actuator. The actuation and the electroactivity of the yarn were retained up to 100 cycles. The new highly conductive yarns will shed light on the development of next-generation textile-based exoskeleton suits, assistive devices, wearables, and haptics garments.

Effect of crevice gap on crevice corrosion initiation and development of 2205 duplex stainless steel in NaCl solution

The crevice geometry has an important influence on the initiation and development of crevice corrosion. The crevice gap size determines the volume of the crevice solution and the cross-sectional area of the material exchange channel between the crevice solution and bulk solution, and it is the dominant factor of the initiation and development mechanism of crevice corrosion. In this paper, the effect of crevice gap size on the crevice corrosion behavior of 2205 duplex stainless steel (DSS) in NaCl solution was investigated by electrochemical method combined with modeling. The quantitative contribution of the volume effect of crevice solution and the diffusion effect of H+ on the crevice corrosion initiation period, as well as the corrosion characteristics and mechanism at initiation and development periods of crevice corrosion, were discussed. Results show that the initiation process of crevice corrosion of 2205 DSS in 3.5 wt% NaCl solution follows the critical crevice solution mechanism. The crevice gap size affects the acidification rate of the crevice solution and the initiation period time of crevice corrosion through the volume effect and the diffusion effect. The influence of diffusion effect on the initiation period time was more significant than volume effect. The corrosion development process is mainly determined by the potential and current density distribution within the crevice, and thus follows the IR drop mechanism (I refers to the current and R refers to the resistance). The crevice gap size is the dominant factor for the development mechanism of crevice corrosion.