Pickup Process Research Articles

Precision-induced localized molten liquid metal stamps for damage-free transfer printing of ultrathin membranes and 3D objects

Transfer printing, a crucial technique for heterogeneous integration, has gained attention for enabling unconventional layouts and high-performance electronic systems. Elastomer stamps are typically used for transfer printing, where localized heating for elastomer stamp can effectively control the transfer process. A key challenge is the potential damage to ultrathin membranes from the contact force of elastic stamps, especially with fragile inorganic nanomembranes. Herein, we present a precision-induced localized molten technique that employs either laser-induced transient heating or hotplate-induced directional heating to precisely melt solid gallium (Ga). By leveraging the fluidity of localized molten Ga, which provides gentle contact force and exceptional conformal adaptability, this technique avoids damage to fragile thin films and improves operational reliability compared to fully liquefied Ga stamps. Furthermore, the phase transition of Ga provides a reversible adhesion with high adhesion switchability. Once solidified, the Ga stamp hardens and securely adheres to the micro/nano-membrane during the pick-up process. The solidified stamp also exhibits the capability to maneuver arbitrarily shaped objects by generating a substantial grip force through the interlocking effects. Such a robust, damage-free, simply operable protocol illustrates its promising capabilities in transfer printing diverse ultrathin membranes and objects on complex surfaces for developing high-performance unconventional electronics.

An aggregate matching and pick-up model for mobility-on-demand services

This paper presents an Aggregate Matching and Pick-up (AMP) model to delineate the matching and pick-up processes in mobility-on-demand (MoD) service markets by explicitly considering the matching mechanisms in terms of matching intervals and matching radii. With passenger demand rate, vehicle fleet size and matching strategies as inputs, the AMP model can well approximate drivers’ idle time and passengers’ waiting time for matching and pick-up by considering batch matching in a stationary state. Properties of the AMP model are then analyzed, including the relationship between passengers’ waiting time and drivers’ idle time, and their changes with market thickness, which is measured in terms of the passenger arrival rate (demand rate) and the number of active vehicles in service (supply). The model can also unify several prevailing inductive and deductive matching models used in the literature and spell out their specific application scopes. In particular, when the matching radius is sufficiently small, the model reduces to a Cobb–Douglas type matching model proposed by Yang and Yang (2011) for street-hailing taxi markets, in which the matching rate depends on the pool sizes of waiting passengers and idle vehicles. With a zero matching interval and a large matching radius, the model reduces to Castillo model developed by Castillo et al. (2017) that is based on an instant matching mechanism, or a bottleneck type queuing model in which passengers’ matching time is derived from a deterministic queue at a bottleneck with the arrival rate of idle vehicles as its capacity and waiting passengers as its customers. When both the matching interval and matching radius are relatively large, the model also reduces to the bottleneck type queuing model. The performance of the proposed AMP model is verified with simulation experiments.

Comparative Analysis of Structure and Motion of Vision Logistics Robotic Arms

This paper combines visual recognition and robotic arm, optimizes the design of robotic arm structure, and researches the logistics robotic arm with six degrees of freedom and visual perception ability to enrich the logistics robotic use scene. Firstly, the visual recognition system is installed on the existing six-degree-of-freedom robotic arm, and the coordinate system is established by the light bar recognition method combined with the D-H parameter method. Secondly, a kinematic simulation model was established by using MATLAB, and the state of the joints was analyzed by using forward and inverse kinematic simulation and fifth degree polynomial interpolation. Finally, the actual logistics fixed-point transportation task is designed for trajectory planning. The results show that the robotic arm is able to be able to perform different grasping tasks in non-structural environments, around the visual analysis of the robotic arm as well as the optimization of the motion track, to enhance the efficiency of the comprehensive use of visual and tactile information, to improve the adaptability of the robotic hand grasping, and to be able to meet the precise control of the pick-up process and the use of the realization of the payload grasping and dexterous movement. The research in this paper provides a certain reference value for the propulsion robot arm to perform intelligent grasping tasks.

Development of Automatic Object Detection and IoT for Garbage Pickup Assignment Problem

Waste management remains a challenge in certain cities, particularly in allocating fleets responsible for collecting garbage from temporary disposal sites. Inadequate planning can lead to the accumulation of substantial waste piles. This study aims to enhance truck assignment by considering truck capacity and the collection route. The assignment process incorporates the fundamental concept of the transportation problem, precisely the northwest corner method. The volume of waste transported aligns with the resident or industrial population within the designated service area. The waste generation capacity determines the future fleet and quantity, forming a crucial element of the ensuing distribution channel. A monitoring system integrating object detection and the Internet of Things (IoT) has been devised to ensure effective garbage collection. Cameras strategically positioned at temporary disposal sites transmit real-time images. The system evaluates garbage collection capacity through object detection facilitated by neural network training. The research outcomes demonstrate the system's capability to identify waste pile levels and validate the garbage pickup process by the designated fleet. Future research should focus on assignment and scheduling in waste transportation, enabling fleet allocation within specific timeframes. Additionally, an object detection algorithm refinement is necessary for more precise identification of waste pile locations.

Enhanced Acceleration and Escape of Hydrogen Pickup Ions Upstream from Mars by Interplanetary Shocks

The pickup process of newly ionized hydrogen (H) from the Martian extended exosphere represents an important H+ escape channel on Mars. It is generally believed that interplanetary (IP) shocks can accelerate the pickup ions and, in turn, affect the pickup process. However, the underlying processes inherent to the acceleration are not yet fully understood. Here, we concentrate on the dynamic processes involved in acceleration arising from IP shock compression. We examine two typical IP shock events characterized by a sudden increase in the average energy of upstream H+ pickup ions across the shock. The H+ pickup ions continuously enter the field of view of Supra-Thermal And Thermal Ion Composition or Solar Wind Ion Analyzer on board the Mars Atmosphere and Volatile EvolutioN spacecraft in a narrow angular range. Moreover, they correspond to a similar part of their respective ring distributions in velocity space. By comparing measured and theoretical H+ pickup ion energies, we attribute the more energetic H+ pickup ions to the enhanced convection electric field acceleration caused by the shock compression. An increase in the guiding center drift speed across the shock implies a higher escape rate of the H+ pickup ions. Furthermore, the pitch-angle scattering could facilitate the escape of the higher energy H+ pickup ions from Mars. The results may shed light on the understanding of the energization and escape of planetary pickup ions in the solar system.

Economic optimization of fresh logistics pick-up routing problems with time windows based on gray prediction

The rapid development of modern cold chain logistics technology has greatly expanded the sales market of agricultural products in rural areas. However, due to the uncertainty of agricultural product harvesting, relying on the experience values provided by farmers for vehicle scheduling can easily lead to low utilization of vehicle capacity during the pickup process and generate more transportation cost. Therefore, this article adopts a non-linear improved grey prediction method based on data transformation to estimate the pickup demand of fresh agricultural products, and then establishes a mathematical model that considers the fixed vehicle usage cost, the damage cost caused by non-linear fresh fruit and vegetable transportation damage and decay rate, the cooling cost generated by refrigerated transportation, and the time window penalty cost. In order to solve the model, a hybrid simulated annealing algorithm integrating genetic operators was designed to solve this problem. This hybrid algorithm combines local search strategies such as the selection operator without repeated strings and the crossover operator that preserves the best substring to improve the algorithm’s solving performance. Numerical experiments were conducted through a set of benchmark examples, and the results showed that the proposed algorithm can adapt to problem instances of different scales. In 50 customer examples, the difference between the algorithm and the standard value in this paper is 2.30%, which is 7.29% higher than C&S. Finally, the effectiveness of the grey prediction freight path optimization model was verified through a practical case simulation analysis, achieving a logistics cost savings of 9.73%.

Simulation Analysis and Parameter Optimization of Residual Film Pickup Process Based on Finite Element Method

The extended duration of mulching in Xinjiang cotton fields leads to a significant decline in the tensile strength of plastic film. When recycling is in operation, the soil and the spring teeth of the machinery used can easily cause secondary damage and fracture the residual film. Establishing appropriate working parameters for recycling is essential to enhance the overall quality of collection efforts. By analyzing the motion process of a chain-tooth residual film pickup device, we identified key working parameters that significantly impact the efficiency of recycling. Employing the finite element method (FEM) and a coupled algorithm incorporating smooth particle hydrodynamics (SPH), we developed a coupled finite element model representing the interaction among spring teeth, soil, and residual film. Through simulation and analysis of the process of inserting the spring teeth into the soil to collect film, we derived the governing rules for residual film stress and deformation changes. Utilizing forward speed, rotational angular velocity, and angle of entry into the soil of the spring teeth as test factors and selecting the residual film stress and the residual film deformation as test indices, we conducted a multi-factor simulation test. We established a mathematical model correlating test factors with test indices, and the influence of each factor on the test index was analyzed. Subsequently, we optimized the working parameters of the spring teeth. The results indicated that the optimal working parameters are forward speed of 1111.11 mm/s, rotational angular velocity of 25 rad/s, and angle of entry into the soil of 30°. At these values, the average peak stress of residual film was 4.51 MPa and the height of residual film pickup was 84.48 mm. To validate the optimized the spring teeth impact on performance, field experiments were conducted with recovery rate and winding rate as test indices. The results demonstrated a 92.1% recovery rate and a 1.1% winding rate under the optimal combination of working parameters. The finite element model presented in this paper serves as a reference for designing and analyzing key components of residual film recycling machines.

Research on contactless intelligent medication pickup mode selection based on a hospital in China under COVID-19.

During an outbreak such as COVID-19, hospital staff needs to be in close contact with all types of patients visiting the hospital and the risk of cross-infection is extremely high. Payment and medication pickup is a mandatory part of a patient's hospital visit, with direct contact between healthcare workers and patients, and long waiting times in the hospital area, which can easily lead to the spread of disease infection. This paper designed the prototype of a contactless smart medicine cabinet based on RFID technology and optimized the patient consultation and medication pickup process to address these problems. We conducted a 50-day field observation of patients for consultation and medication pickup at the First Hospital in H city, Jiangsu Province, China, and randomly timed 1600 sets of data from Surgery (ophthalmology) and Internal patients, then we designed the prototype of a contactless smart medicine cabinet based on RFID technology, optimized the patient consultation and medication pickup process, comparing the traditional and intelligent models using AnyLogic. The results show that this contactless medicine cabinet was able to reduce the time taken by patients in consultation and medicine pickup by 18.74 minutes, increasing the overall efficiency of the consultation by 32.20%. The simulation revealed that this contactless intelligent medication pickup model was able to reduce the time taken by patients in consultation and medicine pickup, increasing the overall efficiency of the consultation, effectively reducing the frequency of contact between healthcare workers and patients, and reducing the risk of disease infection. The proposed technical model provides a new idea to solve the problems of long queues, low efficiency and high risk of infection for patients to consult and get medicine during epidemics. Especially within hospitals it has important theoretical and practical implications for epidemic prevention and control as well as future hospital management.

A security-constrained robust optimization for energy management of active distribution networks with presence of energy storage and demand flexibility

A discernible rise in the frequency and intensity of unpredictable events and their significant social and economic effects have made power system planners pay special attention to the security and reliability of power networks. For this purpose, this article tries to provide an efficient model for strengthening the security of active distribution networks based on multiple microgrids by optimally using energy storage resources and consumption management plans. In the proposed plan, a hierarchical two-stage approach has been developed in which the first stage models the incident and their impact on the distribution network. Then, in the next stage, preventive and corrective measures are implemented to increase system readiness and reduce damages caused by severe accidents. At this stage, various tools such as energy storage, distributed and renewable production sources have been used in addition to responsive loads. In the corrective phase, the independent microgrid partitioning method is used to restore the distribution network to increase the speed of load pickup process. In order to consider the uncertainty and the risk caused by events on the performance of the proposed plan, the problem is done by robust optimization to obtain more realistic results. Finally, in order to confirm the effectiveness of the proposed method in improving the security of distribution systems, a standard network of 33 buses was used with different operating conditions. The results confirm that the proposed security-constrained robust optimization plan not only reduces system operating costs, but also improves consumer security in the face of severe accidents. Although the increase in network security is associated with a slight increase in system costs, the benefit of reducing outages and optimal use of network capacity has led to the effectiveness of the proposed plan.

Study on the Management and Planning Methods of Transportation to and from Primary and Secondary Schools in Urban and Rural Areas

The transportation of urban and rural primary and secondary schools leads to traffic congestion in some sections, and the traffic order is chaotic, which seriously affects the travel of surrounding residents and greatly increases the additional traffic delay of pickup. How to effectively manage and plan the transportation of urban and rural primary and secondary schools and rationally plan the channelization of transportation roads have become a topic of great concern to the society. This paper will take several primary and secondary schools with representative traffic environment as the research object, analyze the behavior mechanism of the pick-up process, propose coping strategies for the school pick-up congestion problem under different road conditions, and plan a reasonable road channelization scheme and intersection design scheme. Finally, through the VISSIM simulation software, the proposed scheme and the original traffic environment are simulated and analyzed, and the vehicle delay before and after the improvement is compared, so as to find out whether the traffic planning and management scheme given in response to the school address in different traffic environments is reasonable. Through the simulation results, it is found that it is beneficial to reduce vehicle delay and avoid traffic jam by changing bidirectional to unidirectional on road section. In the vicinity of the intersection, one-way is the main way, and planning multiple drop-off points is helpful to solve the traffic congestion caused by school pick-up.

Due consideration of the breakup and direct reaction mechanisms within (d, p), (d, 2p), (d, xn2p), and (d, xn) reactions

Suitable account of available excitation-function of deuterons interaction with target nuclei components of candidates materials for the ITER fusion reactor, the European DEMO fusion reactor, and the IFMIF-DONES Irradiation Facility has been proved by consistent analysis of the reaction mechanisms involved in the complex deuteron-nucleus interaction. In this work the attention has been focused on the analysis of the deuteron activation cross sections related to the gas accumulation, (d, p), (d, 2p), (d, xn2p), and to the strong neutron emission, (d, xn), interaction processes of interest for the radiation damage and shielding design studies devoted to the structural materials selection. The key role of direct interactions, i.e., breakup, stripping and pick-up processes is stressed out by the comparison of data with theoretical and evaluation predictions.

Design and test of potato seeding apparatus based on double-layer seed picking scoop structure.

At present, potato seeders in China generally have poor uniformity of seed rows and high coefficients of variation in plant spacing during seed rows, causing difficulties for subsequent mechanized plant protection and harvesting. Based on the effect of seed discharge to analyze the sowing process, a potato seed discharger with a double-layer seed picking spoon structure was designed. By analyzing the seed discharging mechanism and its operation process, the shape and size structural parameters of the seed picking spoon were determined. Finite element simulation of the seed pickup process and seed carrying process of the seed discharging mechanism was carried out by EDEM software to determine the double-layer seed scoop scheme and the range of factors for subsequent tests. A two-factor test was conducted with seeding line speed and seed drop height as test factors, and plant spacing coefficient of variation and seed potato lateral offset dispersion as test indexes. The test results showed that the double-layer seeding spoon chain seeder reduced the coefficient of variation in plant spacing by 5.8%, and the dispersion in lateral offset by 5.5 mm, compared with the single seeding spoon seeder, when the seeding speed was 0.184 m/s and the height of falling seed was 9 cm.

Forward Chaining Method Implementation for AI-Powered Passenger Ojek Online and Drive Solutions

This research explores the application of artificial intelligence (AI)-based technology in the Grab application, an online passenger transportation service company in Southeast Asia. The main aim of this research is to improve service quality, safety and efficiency for Grab passengers and drivers, while solving traffic and location problems. The use of AI in this application opens up opportunities to optimize passenger pick-up and drop-off processes, improve navigation, and improve real-time traffic management. Special emphasis is placed on the application of the Forward Chaining method, an artificial intelligence technique that allows systems to make decisions based on predetermined rules. By implementing this method, Grab can predict passenger movements and arrange the best routes automatically, increasing time efficiency and reducing congestion. The implications of this research are very significant in the context of improving the quality of online transportation services, by providing a better experience for passengers and ensuring safety on every trip. The main contribution of this research is the development of an efficient and reliable AI system, as well as the application of Forward Chaining in the context of the Grab application. Additionally, this research provides an in-depth understanding of how AI technology can overcome traffic and location challenges, creating effective and reliable solutions for ride-hailing companies in the future. The results of this research provide a valuable contribution to the development of transportation technology, providing a basis for similar companies to explore the potential of applying artificial intelligence in their services. Thus, this research paves the way to greater innovation in the field of online transportation, creating a more efficient, safe and comfortable environment for users, and creating significant added value for the industry.

3D image steganography using cellular automata transform and depth estimation network

Traditional 3D image steganography is cumbersome and difficult owing to the special structure of 3D image, imposing a practical limit for its applications. Herein, we propose a 3D image steganography scheme utilizing cellular automata transformation (CAT). By using CAT with various rule numbers to hide images, the weakness of previous algorithms with only one transformation plane is overcome, and the hidden image quality can be improved by reducing energy loss. In the 3D reconstruction process, we apply a depth estimation algorithm based on a convolutional network to obtain corresponding depth maps from a single RGB image, simplifying the elemental image array (EIA) pickup process and even overcoming the phase difference problem caused by the traditional optical pickup process using lens arrays. Before hiding, we use the maximum length cellular automata (MLCA) to encrypt a single RGB image instead of encrypting EIA images with huge data, which greatly reduces the complexity of the encryption algorithm and improves efficiency. Finally, we reconstruct the decrypted image optically and obtain a full color and full parallax 3D image through the display device.

Load prediction of parcel pick-up points: model-driven vs data-driven approaches

ABSTRACT Pick-Up Points (PUPs) represent an alternative delivery option for online purchases. Parcels are delivered at a reduced cost to PUPs and wait until being picked up by customers or returned to the original warehouse if their sojourn time is over. When the chosen PUP is overloaded, the parcel may be refused and delivered to the next available PUP on the carrier tour. This paper presents and compares forecasting approaches for the load of a PUP to help PUP management companies balance delivery flows and reduce PUP overload. The parcel life-cycle has been taken into account in the forecasting process via models of the flow of parcel orders, the parcel delivery delays, and the pick-up process. Model-driven and data-driven approaches are compared in terms of load-prediction accuracy. For the considered example, the best approach (which makes use of the relationship of the load with the delivery and pick-up processes) is able to predict the load up to 4 days ahead with mean absolute errors ranging from 3.16 parcels (1 day ahead) to 8.51 parcels (4 days ahead) for a PUP with an average load of 45 parcels.

Tianwen-1 and MAVEN observations of Martian oxygen ion plumes

There is a significant Martian ion escape channel called the “plume”. Due to the lack of multi-point, high-resolution field and particle detections, the energization mechanism and source region identification of ion plumes by in situ measurements remain unclear. China's first Mars exploration mission, Tianwen-1, provides us an opportunity to study ion escape owing to the high altitude of its apoapsis (∼3 RM, RM is Mars radius). In this study, we take advantage of the joint observations of Tianwen-1 and Mars Atmosphere and Volatile EvolutioN (MAVEN) to study oxygen ion plumes. Our statistical results confirm the convection electric field acceleration as the energization mechanism of plume ions (up to >15 keV) in a more direct way than ever before. Our estimation suggests that most ion plumes originate from middle and low MSE (Mars Solar Electric) latitude of the northern dayside Martian ionosphere. This work improves our understanding of the pick-up process of the Martian escaping ions.

Particle Injection and Nonthermal Particle Acceleration in Relativistic Magnetic Reconnection* *Released January 10, 2023.

Magnetic reconnection in the relativistic regime has been proposed as an important process for the efficient production of nonthermal particles and high-energy emission. Using fully kinetic particle-in-cell simulations, we investigate how the guide-field strength and domain size affect the characteristic spectral features and acceleration processes. We study two stages of acceleration: energization up until the injection energy γ inj and further acceleration that generates a power-law spectrum. Stronger guide fields increase the power-law index and γ inj, which suppresses acceleration efficiency. These quantities seemingly converge with increasing domain size, suggesting that our findings can be extended to large-scale systems. We find that three distinct mechanisms contribute to acceleration during injection: particle streaming along the parallel electric field, Fermi reflection, and the pickup process. The Fermi and pickup processes, related to the electric field perpendicular to the magnetic field, govern the injection for weak guide fields and larger domains. Meanwhile, parallel electric fields are important for injection in the strong guide-field regime. In the post-injection stage, we find that perpendicular electric fields dominate particle acceleration in the weak guide-field regime, whereas parallel electric fields control acceleration for strong guide fields. These findings will help explain the nonthermal acceleration and emission in high-energy astrophysics, including black hole jets and pulsar wind nebulae.

Optimal cancellation penalty for competing ride-sourcing platforms under waiting time uncertainty

This paper investigates the optimal fare and penalty strategy of ride-sourcing platforms in a competing market. When ordering ride-sourcing services, passengers encounter waiting time variability due to the uncertainty in the matching and pickup processes. In some scenarios, some passengers order ride-sourcing services from multiple platforms to save waiting time, which results in subsequent order cancellations. To capture the behavior of order cancellation, this paper derives the cancellation probability based on the perceived inhomogeneous Poisson process. In view of the punishing effect and blocking effect of order cancellation penalty, this paper investigates the impact of order cancellation penalties on market equilibrium and platform revenue. We formulate a game-theoretic framework and obtain the duopoly market equilibrium to explore the optimal pricing (including penalties and fares) of different platforms. By incorporating passenger perceptions into the order cancellation behavior, this study produces insightful pricing schemes for the ride-sourcing platforms.

Resilient Distribution System Restoration With Communication Recovery by Drone Small Cells

Distribution system (DS) restoration after natural disasters often faces the challenge of communication failures to feeder automation (FA) facilities, resulting in prolonged load pick-up process. This letter discusses the utilization of drone small cells for wireless communication recovery of FA, and proposes an integrated DS restoration strategy with communication recovery. Demonstrative case studies are conducted to validate the proposed model, and its advantages are illustrated by comparing to benchmark strategies.

Multi-objective optimization for AGV energy efficient scheduling problem with customer satisfaction

<abstract><p>In recent years, it has been gradually recognized that efficient scheduling of automated guided vehicles (AGVs) can help companies find the balance between energy consumption and workstation satisfaction. Therefore, the energy consumption of AGVs for the manufacturing environment and the AGV energy efficient scheduling problem with customer satisfaction (AGVEESC) in a flexible manufacturing system are investigated. A new multi-objective non-linear programming model is developed to minimize energy consumption while maximizing workstation satisfaction by optimizing the pick-up and delivery processes of the AGV for material handling. Through the introduction of auxiliary variables, the model is linearized. Then, an interactive fuzzy programming approach is developed to obtain a compromise solution by constructing a membership function for two conflicting objectives. The experimental results show that a good level of energy consumption and workstation satisfaction can be achieved through the proposed model and algorithm.</p></abstract>