330 research outputs found
The Impact, Mechanism, and Practical Strategies of Outdoor Sports for College Students under the Normal Situation of the Epidemic
To study the outdoor activities of college students under the normal situation of the epidemic, explore their impact and mechanisms on physical and mental health, environmental protection, and sustainable development, and propose corresponding sustainable practice strategies. Through literature analysis, questionnaire surveys, and interviews, this study found that outdoor sports for college students can effectively improve their physical fitness, promote the protection and sustainable use of the natural environment, strengthen interpersonal interaction and emotional identity, and promote economic development and ecological civilization construction. However, there are also some problems and challenges, such as safety problems, non-standard management, environmental damage, etc. Therefore, it is necessary to establish a scientific and effective system of system guarantees and laws and regulations, standardize behavior, and accelerate the construction of ecological civilization
Research on promotion mode of dual channel supply chain considering consumer channel preference
This paper concentrates on the dual-channel supply chain considering consumer channel preference, which manufacturers through online direct sales and retailers through offline retail, and constructs different promotion models: manufacturers and retailers do not promote, the retailer does promotion and the manufacturer does promotion, while considering consumers’ channel preferences, study the impact of promotion on the profit and performance of supply chain system members, and finally get the best promotion strategy for retailers and manufacturers through comparative analysis. It is of extraordinary viable importance to make reasonable promotion decisions for members of the dual-channel supply chain system
Auricle shaping using 3D printing and autologous diced cartilage.
ObjectiveTo reconstruct the auricle using a porous, hollow, three-dimensional (3D)-printed mold and autologous diced cartilage mixed with platelet-rich plasma (PRP).MethodsMaterialise Magics v20.03 was used to design a 3D, porous, hollow auricle mold. Ten molds were printed by selective laser sintering with polyamide. Cartilage grafts were harvested from one ear of a New Zealand rabbit, and PRP was prepared using 10 mL of auricular blood from the same animal. Ear cartilage was diced into 0.5- to 2.0-mm pieces, weighed, mixed with PRP, and then placed inside the hollow mold. Composite grafts were then implanted into the backs of respective rabbits (n = 10) for 4 months. The shape and composition of the diced cartilage were assessed histologically, and biomechanical testing was used to determine stiffness.ResultsThe 3D-printed auricle molds were 0.6-mm thick and showed connectivity between the internal and external surfaces, with round pores of 0.1 to 0.3 cm. After 4 months, the diced cartilage pieces had fused into an auricular shape with high fidelity to the anthropotomy. The weight of the diced cartilage was 5.157 ± 0.230 g (P > 0.05, compared with preoperative). Histological staining showed high chondrocyte viability and the production of collagen II, glycosaminoglycans, and other cartilaginous matrix components. In unrestricted compression tests, auricle stiffness was 0.158 ± 0.187 N/mm, similar to that in humans.ConclusionAuricle grafts were constructed successfully through packing a 3D-printed, porous, hollow auricle mold with diced cartilage mixed with PRP. The auricle cartilage contained viable chondrocytes, appropriate extracellular matrix components, and good mechanical properties.Levels of evidenceNA. Laryngoscope, 129:2467-2474, 2019
Spatial Parameter Identification for MIMO Systems in the Presence of Non-Gaussian Interference
Reliable identification of spatial parameters for multiple-input multiple-output (MIMO) systems, such as the number of transmit antennas (NTA) and the direction of arrival (DOA), is a prerequisite for MIMO signal separation and detection. Most existing parameter estimation methods for MIMO systems only consider a single parameter in Gaussian noise. This paper develops a reliable identification scheme based on generalized multi-antenna time-frequency distribution (GMTFD) for MIMO systems with non-Gaussian interference and Gaussian noise. First, a new generalized correlation matrix is introduced to construct a generalized MTFD matrix. Then, the covariance matrix based on time-frequency distribution (CM-TF) is characterized by using the diagonal entries from the auto-source signal components and the non-diagonal entries from the cross-source signal components in the generalized MTFD matrix. Finally, by making use of the CM-TF, the Gerschgorin disk criterion is modified to estimate NTA, and the multiple signal classification (MUSIC) is exploited to estimate DOA for MIMO system. Simulation results indicate that the proposed scheme based on GMTFD has good robustness to non-Gaussian interference without prior information and that it can achieve high estimation accuracy and resolution at low and medium signal-to-noise ratios (SNRs)
A novel control system design for automatic feed drilling operation of the PLC-based oil rig
Aiming at the difficulties in realizing the accurate control due to the nonlinearity of the automatic drilling system of oil drilling rig, a design scheme is proposed by giving a constant drilled-pressure to the rig for fuzzy control. Sampling error with changes in the signal was sent into the fuzzy controller, which turned the signal into a fuzzy volume. Subsequently, a precise volume was obtained accordingly and then added to an actuator for the motor control. According to the MATLAB simulation results, the response could be faster and more stable compared with the traditional control
Large Multimodal Agents: A Survey
Large language models (LLMs) have achieved superior performance in powering
text-based AI agents, endowing them with decision-making and reasoning
abilities akin to humans. Concurrently, there is an emerging research trend
focused on extending these LLM-powered AI agents into the multimodal domain.
This extension enables AI agents to interpret and respond to diverse multimodal
user queries, thereby handling more intricate and nuanced tasks. In this paper,
we conduct a systematic review of LLM-driven multimodal agents, which we refer
to as large multimodal agents ( LMAs for short). First, we introduce the
essential components involved in developing LMAs and categorize the current
body of research into four distinct types. Subsequently, we review the
collaborative frameworks integrating multiple LMAs , enhancing collective
efficacy. One of the critical challenges in this field is the diverse
evaluation methods used across existing studies, hindering effective comparison
among different LMAs . Therefore, we compile these evaluation methodologies and
establish a comprehensive framework to bridge the gaps. This framework aims to
standardize evaluations, facilitating more meaningful comparisons. Concluding
our review, we highlight the extensive applications of LMAs and propose
possible future research directions. Our discussion aims to provide valuable
insights and guidelines for future research in this rapidly evolving field. An
up-to-date resource list is available at
https://github.com/jun0wanan/awesome-large-multimodal-agents.Comment: 15 pages, 4 figure
Automatic Identification of Space-Time Block Coding for MIMO-OFDM Systems in the Presence of Impulsive Interference
Signal identification, a vital task of intelligent communication radios, finds its applications in various military and civil communication systems. Previous works on identification for space-time block codes (STBC) of multiple-input multiple-output (MIMO) system employing orthogonal frequency division multiplexing (OFDM) are limited to additive white Gaussian noise. In this paper, we develop a novel automatic identification algorithm to exploit the generalized cross-correntropy function of the received signals to classify STBC-OFDM signals in the presence of Gaussian noise and impulsive interference. This algorithm first introduces the generalized cross-correntropy function to fully utilize the space-time redundancy of STBC-OFDM signals. The strongly-distinguishable discriminating matrix is then constructed by using the generalized cross-correntropy for multiple receive antennas. Finally, a decision tree identification algorithm is employed to identify the STBC-OFDM signals which is extended by the binary hypothesis test. The proposed algorithm avoids the traditionally required pre-processing tasks, such as channel coefficient estimation, noise and interference statistics prediction and modulation type recognition. Numerical results are presented to show that the proposed scheme provides good identification performance by exploiting the generalized cross-correntropy function of STBC-OFDM signals under impulsive interference circumstances
Comfort-Centered Design of a Lightweight and Backdrivable Knee Exoskeleton
This paper presents design principles for comfort-centered wearable robots
and their application in a lightweight and backdrivable knee exoskeleton. The
mitigation of discomfort is treated as mechanical design and control issues and
three solutions are proposed in this paper: 1) a new wearable structure
optimizes the strap attachment configuration and suit layout to ameliorate
excessive shear forces of conventional wearable structure design; 2) rolling
knee joint and double-hinge mechanisms reduce the misalignment in the sagittal
and frontal plane, without increasing the mechanical complexity and inertia,
respectively; 3) a low impedance mechanical transmission reduces the reflected
inertia and damping of the actuator to human, thus the exoskeleton is
highly-backdrivable. Kinematic simulations demonstrate that misalignment
between the robot joint and knee joint can be reduced by 74% at maximum knee
flexion. In experiments, the exoskeleton in the unpowered mode exhibits 1.03 Nm
root mean square (RMS) low resistive torque. The torque control experiments
demonstrate 0.31 Nm RMS torque tracking error in three human subjects.Comment: 8 pages, 16figures, Journa
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