Sorting System Research Articles

Particle sorting method based on swirl induction.

Fluid-based methods for particle sorting demonstrate increasing appeal in many areas of biosciences due to their biocompatibility and cost-effectiveness. Herein, we construct a microfluidic sorting system based on a swirl microchip. The impact of microchannel velocity on the swirl stagnation point as well as particle movement is analyzed through simulation and experiment. Moreover, the quantitative mapping relationship between flow velocity and particle position distribution is established. With this foundation established, a particle sorting method based on swirl induction is proposed. Initially, the particle is captured by a swirl. Then, the Sorting Region into which the particle aims to enter is determined according to the sorting condition and particle characteristic. Subsequently, the velocities of the microchannels are adjusted to control the swirl, which will induce the particle to enter its corresponding Induction Region. Thereafter, the velocities are adjusted again to change the fluid field and drive the particle into a predetermined Sorting Region, hence the sorting is accomplished. We have extensively conducted experiments taking particle size or color as a sorting condition. An outstanding sorting success rate of 98.75% is achieved when dealing with particles within the size range of tens to hundreds of micrometers in radius, which certifies the effectiveness of the proposed sorting method. Compared to the existing sorting techniques, the proposed method offers greater flexibility. The adjustment of sorting conditions or particle parameters no longer requires complex chip redesign, because such sorting tasks can be successfully realized through simple microchannel velocities control.

A cosmic-ray database update: CRDB v4.1

The cosmic-ray database, CRDB, has been gathering cosmic-ray data for the community since 2013. We present a new release, CRDB v4.1, providing many new quantities and data sets, with several improvements made on the code and web interface, and with new visualisation tools. CRDB relies on the MySQL database management system, jquery and table-sorter libraries for queries and sorting, and PHP web pages and AJAX protocol for displays. A REST interface enables user queries from command line or scripts. A new (pip-installable) CRDB python library is developed and extensive jupyter notebook examples are provided. This release contains cosmic-ray dipole anisotropy data, high-energy p¯/p\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\bar{p}/p$$\\end{document} upper limits, some unpublished LEE and AESOP lepton time series, many more ultra-high energy data, and a few missing old data sets. It also includes high-precision data from the last three years, in particular the hundreds of thousands AMS-02 and PAMELA data time series (time-dependent plots are now enabled). All these data are shown in a gallery of plots, which can be easily reproduced from the public notebook examples. CRDB contains 316,126 data points from 504 publications, in 4111 sub-experiments from 131 experiments.

The Implementation and Potential Ramifications of Autonomous Driving Technology in The Realm of Freight Transportation and Logistics.

This paper aims to explore the application and potential impact of autonomous driving technology in the field of freight and logistics. First, the development of autonomous driving technology and its application in freight and logistics, including autonomous trucks, drones and drone delivery, as well as automated warehousing and sorting systems, are introduced. Then, the potential impacts of autonomous driving technology, such as improved efficiency, cost reduction, enhanced safety, and reduced environmental impact, are analyzed. The challenges faced by the application of autonomous driving technology, such as technological challenges, legal and ethical issues, and their impact on training and employment, are discussed. Finally, the potential advantages and strategies for addressing the application of autonomous driving technology in the field of freight and logistics are summarized, emphasizing the need to address ethical and legal issues in order to achieve sustainable and reasonable development.

Real‐time detection of Angelica dahurica tablet using YOLOX_am

AbstractIn the production of Angelica dahurica tablet (ADT), the manual sorting approach often leads to inefficiency, inconsistent standards, and subjective grading results. The traditional machine vision‐based sorting method, while helping to reduce the demand for labor in factories, suffers from problems such as incomplete contour detection and poor classification of dahurica tablets. To address the above problems, this paper proposes YOLOX_am, a novel deep learning‐based network that combines the fast detection ability of YOLOX and the feature weighting ability of the attention mechanism. In addition, a real‐time sorting system for dahurica tablets is also built and YOLOX_am is deployed in it. The experimental results show that the mAP of ADT's detection using the proposed model reaches 83.53%, which outperforms the original network YOLOX by 4.88%. Moreover, the detection speed of YOLOX_am reaches 1390 ms per image, which meets the requirement of real‐time sorting. Therefore, the combination of YOLOX and the attention mechanism is feasible and effective. YOLOX_am is both fast and accurate for ADT's detection and can be deployed in the sorting system to meet actual production needs.Practical applicationsThe traditional classification of defects in herbal tablets mainly relies on manual detection. This paper introduces a deep learning method into the sorting of herbal tablets. To solve the problem of subtle differentiation of tablets' defects, a neural network structure that can quickly and accurately detect small defective samples is proposed. This network has been applied to practical production and achieved high effectiveness.

Augmented reality-enabled human-robot collaboration to balance construction waste sorting efficiency and occupational safety and health

Construction waste sorting (CWS) is highly recommended as a key step for construction waste management. However, current CWS involves humans’ manual hand-picking, which poses significant threats to their occupational safety and health (OSH). Robotic sorting promises to change the situation by adopting modern artificial intelligence and automation technologies. However, in practice, it is usually challenging for robots to do an efficient job (e.g., measured by quickness and accuracy) owing to the difficulties in precisely recognizing compositions of the mixed and heterogeneous waste stream. Leveraging augmented reality (AR) as a communication interface, this research aims to develop a human-robot collaboration (HRC) approach to address the dilemmatic balance between CWS efficiency and OSH. Firstly, a model for human-robot collaborative sorting using AR is established. Then, a prototype for the AR-enable collaborative sorting system is developed and evaluated. The experimental results demonstrate that the proposed AR-enabled HRC method can improve the accuracy rate of CWS by 10% and 15% for sorting isolated waste and obscured waste, respectively, when compared to the method without human involvement. Interview results indicate a significant improvement in OSH, especially the reduction of contamination risks and machinery risks. The research lays out a human-robot collaborative paradigm for productive and safe CWS via an immersive and interactive interface like AR.

Tracking Grade Heterogeneity in a Panel Cave Mine: A Reconciliation Study Investigating the Impact of Mixing from an Ore Sorting Perspective

Bulk ore sorting is a preconcentration method applied to bulk streams or batches of material. The effectiveness of bulk ore sorting relies on the degree of the naturally occurring in situ grade heterogeneity of an ore deposit. The blending of ore during mining and material handling degrades the in situ grade heterogeneity initially present in an orebody and reduces the potential to apply bulk ore sorting. Block and panel cave mines experience mixing from the establishment of caves to the delivery of the caved ore to concentrators. This study focused on tracking the grade heterogeneity and quantifying the impact of mixing on the sorting potential of the Cadia East panel cave mine via the reconciliation of the grade measurements performed at different locations. The results showed that the copper and gold grades were almost fully homogenized via various mixing events identified for the mine. The tracked grade heterogeneity values revealed that the mixing during material handling, which included ore blending according to mine planning, reduced the grade variability more drastically than the mixing within the caves. As the ore travelled from its original in situ location, the grade distributions gradually transformed, and the grades eventually normalized around the mean values. Only insignificant amounts of low-grade material that could have potentially been discarded were reported to the on-belt sensor located at the surface. The results of this study are significant for cave mines exploring sorting systems for preconcentration as they highlight how mixing can impact the variability in ore grades.

Collision-free and smooth motion planning of dual-arm Cartesian robot based on B-spline representation

This paper discusses a new approach to motion planning of dual-arm gantry kinematic that solves the self-collision problem while ensuring G2-continuity and low curvatures. Starting from collision-free start and target points, the proposed method defines the geometric path of the end-effectors with classical five-segment planar trajectories, described by fifth-degree B-splines. The rototranslation of the loaded parts is evaluated in frames to define sampled overlapping curves, used to compute splines that act as deviation curves being added on the previously defined geometric paths in order to prevent collisions. Here, a quadratic programming minimization is employed to reduce the curvature of these spline and preserve the kinematics properties of the initial path. The kinematic constraints of the axes are ensured by iso-parametric trajectory planning, which results in an optimized motion profile to reduce the task execution time. Finally, the proposed approach is applied to a sorting system for laser machine (LST) having a dual-arm 7-d.o.f. gantry kinematic. The results of a case study of a typical sorting operation are presented and discussed to illustrate and clarify the method. The approach presented in this work can be applied to other robotic systems with similar kinematic structures, providing a useful tool for motion planning in pick-and-place applications.

A Fast Adaptive Binarization Method for QR Code Images Based on Dynamic Illumination Equalization

The advancement of Internet of Things (IoT) has enhanced the extensive usage of QR code images in various computer vision applications. Nonetheless, this has also brought forth several technical challenges. In particular, the logistics sorting system often encounters issues such as a low recognition rate and slow processing speed when dealing with QR code images under complex lighting conditions like uneven illumination. To address these difficulties, a method that focuses on achieving a fast adaptive binarization of QR code images through dynamic illumination equalization was proposed. First, an algorithm based on edge enhancement to obtain the position detection patterns within QR code images was applied, which enabled the acquisition of structural features in uneven illumination. Subsequently, QR code images with complex lighting conditions can achieve a fast adaptive binarization through dynamic illumination equalization. As for method validation, the experiments were performed on the two datasets that include QR code images influenced by strong light, weak light, and different shadow degrees. The results disclosed the benefits of the proposed method compared to the previous approaches; it produced superior recognition rates of 78.26–98.75% in various cases through commonly used decoders (Wechat and Zxing), with a faster processing speed of 0.0164 s/image, making it a proper method to satisfy real-time requirements in practical applications, such as a logistics sorting system.

Support vector machine-based object classification for robot arm system

In this paper, a support vector machine (SVM) model is trained to classify objects in the automatic sorting system using a robot arm. The robot arm is used to grab objects and move them to the right position according to their shape predicted by the SVM model. The position of objects in the image is identified by using the contouring technique. The centroid of objects is calculated from the image moment of the object's contour. The calibration is conducted to get the parameters of the camera and combine with the pinhole camera model to compute the 3D position of the objects. The feature vector for SVM training is the zone feature and the SVM kernel is the Gaussian kernel. In the experiment, the SVM model is used to classify four objects with different shapes. The results show that the accuracy of the SVM classifier is 99.72%, 99.4%, 99.4% and 99.88% for four objects, respectively.

Optimization study of intelligent decision-making system for coal processing plant based on big data analysis

Abstract Optimizing the intelligent decision-making system of coal processing plants is better to improve the economic efficiency of coal processing plants and realize the high-quality development of coal processing plants. In this paper, an integrated intelligent decision-making platform for a coal processing plant is constructed based on big data technology, and the intelligent data analysis techniques of the platform are optimized by using an improved whale optimization algorithm and BP neural network. Examples analyze the optimized crude coal slurry and flotation systems’ processes, and the economic benefits are analyzed. From the optimization of the crude coal slurry sorting system, the ash content in the 0.25mm particle size region was reduced from 55.37% to 13.12%, and the ash content in the −0.125mm particle size region was reduced from 42.68% to 15.96%. From the flotation system optimization, when the flotation time increases from 120s to 180s, the ash content increases from 16.27% to 17.19%, and then to 240s, the ash content increases to 19.44%. Using the integrated intelligent decision-making platform can achieve a net increase in revenue of 4,276,800 yuan for the crude coal slurry sorting system and a net increase of 11,274,200 yuan for the flotation system. This shows that the integrated intelligent decision-making platform can improve the coal processing plant’s quality and efficiency and promote intelligent production.

Electrical Characterization and Analysis of Single Cells and Related Applications.

Biological parameters extracted from electrical signals from various body parts have been used for many years to analyze the human body and its behavior. In addition, electrical signals from cancer cell lines, normal cells, and viruses, among others, have been widely used for the detection of various diseases. Single-cell parameters such as cell and cytoplasmic conductivity, relaxation frequency, and membrane capacitance are important. There are many techniques available to characterize biomaterials, such as nanotechnology, microstrip cavity resonance measurement, etc. This article reviews single-cell isolation and sorting techniques, such as the micropipette separation method, separation and sorting system (dual electrophoretic array system), DEPArray sorting system (dielectrophoretic array system), cell selector sorting system, and microfluidic and valve devices, and discusses their respective advantages and disadvantages. Furthermore, it summarizes common single-cell electrical manipulations, such as single-cell amperometry (SCA), electrical impedance sensing (EIS), impedance flow cytometry (IFC), cell-based electrical impedance (CEI), microelectromechanical systems (MEMS), and integrated microelectrode array (IMA). The article also enumerates the application and significance of single-cell electrochemical analysis from the perspectives of CTC liquid biopsy, recombinant adenovirus, tumor cells like lung cancer DTCs (LC-DTCs), and single-cell metabolomics analysis. The paper concludes with a discussion of the current limitations faced by single-cell analysis techniques along with future directions and potential application scenarios.

Design and tactile classification of flexible tactile sensor for soft gripper

Tactile object recognition is very important in robot sorting and handling system. The existing researches on tactile recognition mainly focus on rigid grippers, which cannot be directly applied to soft grippers with better safety and applicability. In this paper, a tactile sensor for soft gripper is proposed. The tactile sensor consists of a carbon composite Velostat and a flexible printed circuit designed for soft gripper. The sensor is equipped with signal scanning, amplifying and processing systems. A number of performance tests were carried out on the designed tactile sensor to prove that it has good performance in sensing sensitivity, loading stability, repeatability. In addition, tactile sensors are applied to tactile classification. The two fingers of the flexible gripper were loaded with a sensor and nine different objects were contacted. The tactile information of the objects was obtained through the stable gripper, and the tactile data was trained and classified by the support vector machine. Finally, the tactile recognition accuracy of the double-exponent data was 91.1%.

Current technological options for recycling packaging waste: Challenges and opportunities in India

AbstractPackaging in India comprises around 59% of total plastic consumption, with most of the waste originating from single‐use and short shelf‐life products. The plastic recycling industry is primarily made up of informal processing units which have predominantly been recycling Polyethylene terephthalate (PET) waste due to ease of availability, sorting, and higher upscale values than most other single‐use packaging. Other packaging, such as Polyethylene (PE) shopping bags, thin film and multi‐material packaging waste is either directed to downcycling, incineration or landfill. About 94% of total recycling in India is carried out through mechanical recycling, which comes through informal and fragmented recycling units. Most of the recycling units in India rely on rudimentary technologies. One example is a visual sorting system that involves manual handling to recycle plastic waste, which is resource and time intensive. There has been some advancement towards chemical and energy recovery techniques, but mostly been limited to pilot‐scale deployment. This article explores the existing and emerging technological options suitable for recycling post‐consumer flexible plastic packaging waste in India. It also discusses the status of multi‐material packaging waste, and the advancement being made for its recycling. The paper also explores India's increased momentum in the use of innovative recycling techniques, such as distributed recycling and manufacturing techniques and plastic waste in steel manufacturing.This article is categorized under: Climate and Environment > Ecosystem Services Climate and Environment > Circular Economy Emerging Technologies > Materials

Estonian and Norwegian Sheep Wool as a Textile Material

In Estonia, up to 90% of local wool is not adequately valued, while in Norway, due to the well-functioning wool-buying and -sorting system, a large part of local wool is used purposefully. However, both countries have room for improvement in terms of the better usage of local wool. This article provides an overview of the Estonian-Norwegian wool research conducted in from 2020 to 2023 and its main results. During the study, wool was collected from three Estonian and three Norwegian sheep breeds, semi-worsted yarn was made from it, and knitted and woven fabrics were produced. Wool, yarn, and fabrics were tested in numerous ways. The paper presents the main test results and suggests how wools with a wide range of qualities can be used in innovative ways to create textiles. The smart use of materials is based on the possibilities offered by medium-sized production and knowledge about local wool.

Health Hazards of Ultra-Processed Foods and The Challenges Facing Humanity

Over the past few years, researchers have proposed a food sort system depend on the level of processing, called NOVA, which includes four parts: low-processed foods, processed cooking sauces, processed foods and ultra-processed foods (UPFs). These foods were developed to meet the increasing pace of life. Initially, they were only used to supplement energy in special situations, but in recent years they have become an indispensable source of food, such as ice cream and chocolate. Studies by various researchers have shown that it is associated with many health problems: obesity, cardiovascular diseases and even cancer. The incidence of cancer soars with the proportion of UPFs in a person's dietary, especially for ovarian cancer. For every 10% rise in the ingestion of UPFs, there was a 6% growth in entire cancer mortality. This is a serious health risk for people. This article summarizes the current influences of UPFs on human life, in particular the major health impacts, and predicts their future trends.

Designing, Optimizing, and Validating a Low-Cost, Multi-Purpose, Automatic System-Based RGB Color Sensor for Sorting Fruits

The use of automatic systems in the agriculture sector enhances product quality and the country’s economy. The method used to sort fruits and vegetables has a remarkable impact on the export market and quality assessment. Although manual sorting and grading can be performed easily, it is inconsistent, time-consuming, expensive, and highly influenced by the surrounding environment. In this regard, this study aimed to design and optimize the performance of a low-cost, multi-purpose, automatic RGB color-based sensor for sorting fruits. The proposed automatic color sorting system consists of hardware components including a machine frame, belt and pulleys, conveyor belt, scanning zone, plastic boxes, electric components (stepper motors, RGB color sensors, Arduino Mega, motor drivers), and software components (Arduino IDE version 2.2.1 and C++). Calibration was performed for the light intensity sensor to measure the light intensity inside the scanning zone, the conveyor speed sensor, and the RGB color sensors by testing the RGB color channels. The sensor, the height, conveyor belt color, and light intensity should be carefully adjusted to ensure a high performance of the color-based sorting system. The results showed that the appropriate sensor height ranged from 15 to 30 mm, the optimum color of the conveyor belt was black, and scanning the objects at a light intensity of 25 lux achieved the best output signals. The RGB color sensors achieved an analytical performance similar to that obtained with manual sorting without requiring the use of computers for image processing like other automatic sorting systems do in order to gather RGB data.

Technologies for Separation of ‘X’ and ‘Y’ Spermatozoa in Bovines: An Overview

Several approaches to sperm sexing such as Albumin gradient, Identification of H-Y antigen, Free-flow electrophoresis, Detection of sex-specific proteins, Centrifugal counter current distribution, Volumetric differences, Percoll density gradient, Flow-cytometry, Laser ablation, etc were put forward by the scientists. However, the alteration in DNA content between X- and Y-sperm remains the key and only discriminating feature for sperm sorting based on which only Flow cytometry and Laser ablation techniques are being used commercially. Flow cytometry is based on precise staining of the DNA of sperm with the nucleic acid-specific dye, Hoechst 33342, to differentiate between the subpopulations of X- and Y-sperm. The fluorescently stained sperm are then sex-sorted using a specialized highspeed sorter. Laser ablation (LA) is a system and method for sorting a mixture of stained particles in a fluid flow path. The system and method includes an electromagnetic radiation source for exciting fluorescence emissions from the stained particles, a photodetector for detecting the fluorescence emissions, a processor for classifying the stained particles, and a photo-damaging laser for damaging selected particles in the flow path.

Evaluation of mixed #3–7 plastic waste from material recovery facilities (MRFs) in the United States

Plastic recycling rates are still low in the United States (U.S.), with less than 10% of municipal solid waste (MSW) plastic being recycled. Most unrecycled plastics are identified by Resin Identification Codes (RIC) from #3–7, which are commonly destined for landfill or waste-to-energy facilities (WTE). Therefore, the composition and quality of outbound bales containing #3–7 plastics were assessed to understand the potential to increase recycling rates. Three bales were sourced from three different Material Recovery Facilities (MRFs) located in the United States. Each bale was manually sorted and characterized for quality and performance via multiple plastic characterization techniques. Considerable differences in bale composition were observed between MRFs, which correlated with the technology used by each MRF in the sorting process. The differences were substantial in the residual levels of poly(ethylene terephthalate) (PET) and high-density polyethylene (HDPE), which are highly desired for mechanical recycling processes and not expected in #3–7 plastics bales. Traditional recycling processes including washing, extrusion, and injection molding of the sorted material were employed prior to the physical, thermal, and molecular characterization. Despite differences in bale composition by plastic type, some polymer properties were similar across MRFs. This research suggests that landfill-diverted mixed plastic waste can be utilized in the mechanical recycling of currently unrecycled materials, as processes can be designed to work with consistent polymer properties. It also highlights the need to upgrade the sorting systems to prevent waste feedstocks, which can be recycled with current technologies, from contaminating other plastic streams or reach landfills.

High Quantum Yield Shortwave Infrared Luminescent Tracers for Improved Sorting of Plastic Waste.

More complete recycling of plastic waste is possible only if new technologies that go beyond state-of-the-art near-infrared (NIR) sorting are developed. For example, tracer-based sorting is a new technology that explores the upconversion or down-shift luminescence of special tracers based on inorganic materials codoped with lanthanide ions. Specifically, down-shift tracers emit in the shortwave infrared (SWIR) spectral range and can be detected using a SWIR camera preinstalled in a state-of-the-art sorting machine for NIR sorting. In this study, we synthesized a very efficient SWIR tracer by codoping Li3Ba2Gd3 (MoO4)8 with Yb3+ and Er3+, where Yb3+ is a synthesizer ion (excited near 976 nm) and Er3+ emits near 1550 nm. Fine-tuning of the doping concentration resulted in a tracer (Li3Ba2Gd(3-x-y)(MoO4)8:xYb3+, yEr3+, where x = 0.2 and y = 0.4) with a high photoluminescence quantum yield for 1550 nm emission of 70% (using 976 nm excitation). This tracer was used to mark plastic objects. When the object was illuminated by a halogen lamp and a 976 nm laser, the three parts could be easily distinguished based on reflectance and luminescence spectra in the SWIR range: a plastic bottle made of polyethylene terephthalate, a bottle cap made of high-density polyethylene, and a label made of the tracer Li3Ba2Gd3(MoO4)8:Yb3+, Er3+. Importantly, the use of the tracer in sorting may require only the installation of a 976 nm laser in a state-of-the-art NIR sorting system.

Automated Object Sorting System with Real-Time Image Processing and Robotic Gripper Mechanism Control

This work represents an industrial sorting system where image processing is accompanied using a pick-and-place robotic gripper. The sorting of objects is done based on their shape and color. Here the color and shape of different objects are identified using image processing. For this, a webcam is used to capture images of the object in real-time and then process them via a digital computer. Python programming language is used for image processing in this work. After successfully identifying the color and shape of an object, the object is picked and placed at the desired position using the robotic gripper. Controlling the gripper mechanism is also executed using the Python programming language. It is controlled using the Arduino Uno microcontroller and a few DC servo motors. The gripper can move from 0° to 180°. The objects are brought in front of the camera using a belt conveyor system. After the complete fabrication and assembly, 4 objects of different shapes and colors are used to sort objects at 4 different angles. The objects are picked from 90° and is sorted in either 0°, 45°, 135°, or 180° position. This research work not only gives information about robotics but also can help industries sort complex objects automatically without any human interaction.