Conventional Sorting Methods Research Articles

Dual sequentially addressable dielectrophoretic array for high-throughput, scalable, multiplexed droplet sorting

Droplet microfluidics is a powerful tool for a diverse range of biomedical and industrial applications such as single-cell biology, synthetic biology, digital PCR, biosafety monitoring, drug screening, and food, feed, and cosmetic industries. As an integral part of droplet microfluidics, on-chip multiplexed droplet sorting has recently gained enthusiasm, since it enables real-time sorting of single droplets containing cells with different phenotypes into multiple bins. However, conventional sorting methods are limited in throughput and scalability. Here, we present high-throughput, scalable, multiplexed droplet sorting by employing a pair of sequentially addressable dielectrophoretic arrays (SADAs) across a microchannel on a microfluidic chip. A SADA is an on-chip array of electrodes, each of which is sequentially activated and deactivated in synchronization to the position and speed of a flowing droplet of interest. The dual-SADA (dSADA) structure enables high-throughput deflection of droplets in multiple directions in a well-controlled manner. For proof-of-concept demonstration and characterization of the dSADA, we performed fluorescence-activated droplet sorting (FADS) with a 3-way dSADA at a high throughput of 2450 droplets/s. Furthermore, to show the scalability of the dSADA, we also performed FADS with a 5-way dSADA at a high throughput of 473 droplets/s.

A Novel Hybrid Control Strategy for the Energy Storage Modular Multilevel Converters

In this paper, a novel hybrid control strategy has been proposed for the energy storage modular multilevel converters (ESMMC) to realize a nice current performance and ensure the state of change (SOC) of batteries to be balanced. Firstly, traditional proportional integral (PI) control was used to get the circulating current reference; then an improved model predictive control (MPC) method with the weighting factors being online tuned has been designed to obtain the accessing numbers of the submodules in each phase. Lastly, the conventional sorting method for the SOC balancing was given. Experimental comparisons indicate that this proposed novel control strategy can not only ensure a nice current control performance, but also effectively suppress the circulating current component, and it can save over 39.42% execution time in contrast with the traditional PI method, which is feasible for the digital implementation.

A probability-based multi-cycle sorting method for 4D-MRI: A simulation study.

To develop a novel probability-based sorting method capable of generating multiple breathing cycles of 4D-MRI images and to evaluate performance of this new method by comparing with conventional phase-based methods in terms of image quality and tumor motion measurement. Based on previous findings that breathing motion probability density function (PDF) of a single breathing cycle is dramatically different from true stabilized PDF that resulted from many breathing cycles, it is expected that a probability-based sorting method capable of generating multiple breathing cycles of 4D images may capture breathing variation information missing from conventional single-cycle sorting methods. The overall idea is to identify a few main breathing cycles (and their corresponding weightings) that can best represent the main breathing patterns of the patient and then reconstruct a set of 4D images for each of the identified main breathing cycles. This method is implemented in three steps: (1) The breathing signal is decomposed into individual breathing cycles, characterized by amplitude, and period; (2) individual breathing cycles are grouped based on amplitude and period to determine the main breathing cycles. If a group contains more than 10% of all breathing cycles in a breathing signal, it is determined as a main breathing pattern group and is represented by the average of individual breathing cycles in the group; (3) for each main breathing cycle, a set of 4D images is reconstructed using a result-driven sorting method adapted from our previous study. The probability-based sorting method was first tested on 26 patients' breathing signals to evaluate its feasibility of improving target motion PDF. The new method was subsequently tested for a sequential image acquisition scheme on the 4D digital extended cardiac torso (XCAT) phantom. Performance of the probability-based and conventional sorting methods was evaluated in terms of target volume precision and accuracy as measured by the 4D images, and also the accuracy of average intensity projection (AIP) of 4D images. Probability-based sorting showed improved similarity of breathing motion PDF from 4D images to reference PDF compared to single cycle sorting, indicated by the significant increase in Dice similarity coefficient (DSC) (probability-based sorting, DSC = 0.89 ± 0.03, and single cycle sorting, DSC = 0.83 ± 0.05, p-value <0.001). Based on the simulation study on XCAT, the probability-based method outperforms the conventional phase-based methods in qualitative evaluation on motion artifacts and quantitative evaluation on tumor volume precision and accuracy and accuracy of AIP of the 4D images. In this paper the authors demonstrated the feasibility of a novel probability-based multicycle 4D image sorting method. The authors' preliminary results showed that the new method can improve the accuracy of tumor motion PDF and the AIP of 4D images, presenting potential advantages over the conventional phase-based sorting method for radiation therapy motion management.

Indirect Finite Control Set Model Predictive Control of Modular Multilevel Converters

The modular multilevel converter (MMC) is a potential candidate for medium/high-power applications, specifically for high-voltage direct current transmission systems. One of the main challenges in the control of an MMC is to eliminate/minimize the circulating currents while the capacitor voltages are maintained balanced. This paper proposes a control strategy for the MMC using finite control set model predictive control (FCS-MPC). A bilinear mathematical model of the MMC is derived and discretized to predict the states of the MMC one step ahead. Within each switching cycle, the best switching state of the MMC is selected based on evaluation and minimization of a defined cost function. The defined cost function is aimed at the elimination of the MMC circulating currents, regulating the arm voltages, and controlling the ac-side currents. To reduce the calculation burden of the MPC, the submodule (SM) capacitor voltage balancing controller based on the conventional sorting method is combined with the proposed FCS-MPC strategy. The proposed FCS-MPC strategy determines the number of inserted/bypassed SMs within each arm of the MMC while the sorting algorithm is used to keep the SM capacitor voltages balanced. Using this strategy, only the summation of SM capacitor voltages of each arm is required for control purposes, which simplifies the communication among the SMs and the central controller. This paper also introduces a modified switching strategy, which not only reduces the calculation burden of the FCS-MPC strategy even more, but also simplifies the SM capacitor voltage balancing algorithm. In addition, this strategy reduces the SM switching frequency and power losses by avoiding the unnecessary switching transitions. The performance of the proposed strategies for a 20-level MMC is evaluated based on the time-domain simulation studies.

A 5.4 &lt;formula formulatype="inline"&gt;&lt;tex Notation="TeX"&gt;$\mu{\rm W}$&lt;/tex&gt;&lt;/formula&gt; Soft-Decision BCH Decoder for Wireless Body Area Networks

This paper presents an IEEE 802.15.6 compliant soft-decision BCH decoder for energy-constrained wireless body area networks. The proposed soft-decision decoder (SDD) provides a 1 dB coding gain compared to the hard-decision decoder (HDD). The improvement in BER performance can translate into power savings at the transmitter. The energy dissipation and area of the soft-decision BCH decoder is minimized by jointly considering the algorithm, architecture, and circuit parameters. An early termination strategy is proposed to reduce the number of redundant test patterns. Probabilistic sorting is proposed to determine the test patterns, and its hardware complexity is only 54.7% of the conventional sorting method. The HDD kernel is implemented by adopting the Peterson rule, reducing the area by 44.2%. A pass-transistor logic based Chien search circuit consumes 33.3% less energy compared to the standard-cell based implementation. The chip is designed to operate at the minimum energy point of 0.29 V, yielding an energy reduction of 94% compared to a direct-mapped SDD at SNR=5 dB. Fabricated in 90 nm CMOS, the chip dissipates 5.4 μW at 500 kHz, achieving a throughput of 6.38 Mbps.

Exact Histogram Specification Considering the Just Noticeable Difference

Exact histogram specification (EHS) transforms the histogram of an input image into the specified histogram. In the conventional EHS techniques, the pixels are first sorted according to their graylevels, and the pixels that have the same graylevel are further differentiated according to the local average of the pixel values and the edge strength. The strictly ordered pixels are then mapped to the desired histogram. However, since the conventional sorting method is inherently dependent on the initial graylevel-based sorting, the contrast enhancement capability of the conventional EHS algorithms is restricted. We propose a modified EHS algorithm considering the just noticeable difference. In the proposed algorithm, the edge pixels are pre-processed such that the output edge pixels obtained by the modified EHS can result in the local contrast enhancement. Moreover, we introduce a new sorting method for the pixels that have the same graylevel. Experimental results show that the proposed algorithm provides better image enhancement performance compared to the conventional EHS algorithms.

Reduced Switching-Frequency Voltage-Balancing Strategies for Modular Multilevel HVDC Converters

The modular multilevel converter (MMC) is a potential candidate for medium/high-power applications, specifically for high-voltage direct current (HVDC) transmission systems. One of the technical challenges associated with the control of an MMC is to carry out the submodule (SM) capacitor voltages balancing task without imposing any unnecessary switching transition among the SMs. This paper develops a general framework for the capacitor voltage balancing of an MMC. Based on the developed framework and with the objective of reducing the unnecessary switching transitions among the SMs, three capacitor voltage-balancing strategies are proposed and investigated: 1) a slow-rate balancing strategy based on the conventional sorting method; 2) a hybrid balancing strategy which combines a predictive method with the conventional sorting method; and 3) a fundamental-frequency balancing strategy. Performance of the proposed strategies for a point-to-point 21-level MMC-based HVDC system is evaluated based on time-domain simulation studies in the PSCAD/EMTDC software environment. The reported study results demonstrate the capability and tradeoffs of the proposed strategies to reduce the number of switching transitions and, consequently, the MMC losses, under various conditions.

SU‐C‐110‐02: Reducing 4D CT Artifacts Using Optimized Sorting Based on Anatomic Similarity

Purpose: Four‐dimensional (4D) computed tomography (CT) has been widely used as a tool to characterize respiratory motion in radiotherapy. The two most commonly used 4DCT algorithms sort images by respiratory phase or displacement into a predefined number of bins, and are prone to image artifacts at transitions between bed positions. The purpose of this work is to demonstrate a method of reducing motion artifacts in 4DCT by incorporating anatomic similarity into phase or displacement based sorting protocols. Methods: Ten patient datasets were retrospectively sorted using both displacement and phase based sorting algorithms. Conventional sorting methods allow selection of only the nearest neighbor image in time or displacement within each bin. In our method, for each bed position either the displacement or the phase defines the center of a bin range about which several candidate images are selected. The two dimensional correlation coefficients between slices bordering the interface between adjacent couch positions are then calculated for all candidate pairings. Two slices have a high correlation if they are anatomically similar. Candidates from each bin are then selected to maximize the slice correlation over the entire data set using Dijkstraˈs shortest path algorithm. To assess the reduction of artifacts, two thoracic radiation oncologists independently compared the re‐sorted 4D datasets pair‐wise with conventionally sorted datasets, blinded to the sorting method, to choose which had the least motion artifacts. Agreement between reviewers was evaluated using the weighted kappa score. Results: Anatomically based image selection resulted in 4DCT datasets with significantly reduced motion artifacts with both displacement (P=0.0063) and phase sorting (P=0.00022). The reviewers agreed 34 times and disagreed 6 times. Conclusions: Sorting using anatomic similarity significantly reduces 4DCT motion artifacts compared to conventional phase or displacement based sorting. This improved sorting algorithm is a straightforward extension of the two most common 4DCT sorting algorithms.

Reducing 4D CT artifacts using optimized sorting based on anatomic similaritya)

Four-dimensional (4D) computed tomography (CT) has been widely used as a tool to characterize respiratory motion in radiotherapy. The two most commonly used 4D CT algorithms sort images by the associated respiratory phase or displacement into a predefined number of bins, and are prone to image artifacts at transitions between bed positions. The purpose of this work is to demonstrate a method of reducing motion artifacts in 4D CT by incorporating anatomic similarity into phase or displacement based sorting protocols. Ten patient datasets were retrospectively sorted using both the displacement and phase based sorting algorithms. Conventional sorting methods allow selection of only the nearest-neighbor image in time or displacement within each bin. In our method, for each bed position either the displacement or the phase defines the center of a bin range about which several candidate images are selected. The two dimensional correlation coefficients between slices bordering the interface between adjacent couch positions are then calculated for all candidate pairings. Two slices have a high correlation if they are anatomically similar. Candidates from each bin are then selected to maximize the slice correlation over the entire data set using the Dijkstra's shortest path algorithm. To assess the reduction of artifacts, two thoracic radiation oncologists independently compared the resorted 4D datasets pairwise with conventionally sorted datasets, blinded to the sorting method, to choose which had the least motion artifacts. Agreement between reviewers was evaluated using the weighted kappa score. Anatomically based image selection resulted in 4D CT datasets with significantly reduced motion artifacts with both displacement (P = 0.0063) and phase sorting (P = 0.00022). There was good agreement between the two reviewers, with complete agreement 34 times and complete disagreement 6 times. Optimized sorting using anatomic similarity significantly reduces 4D CT motion artifacts compared to conventional phase or displacement based sorting. This improved sorting algorithm is a straightforward extension of the two most common 4D CT sorting algorithms.

A multiple points method for 4D CT image sorting

Artifacts affect 4D CT images due to breathing irregularities or incorrect breathing phase identification. The purpose of this study is the reduction of artifacts in sorted 4D CT images. The assumption is that the use of multiple respiratory related signals may reduce uncertainties and increase robustness in breathing phase identification. Multiple respiratory related signals were provided by infrared 3D localization of a configuration of markers placed on the thoracoabdominal surface. Multidimensional K-means clustering was used for retrospective 4D CT image sorting, which was based on multiple marker variables, in order to identify clusters representing different breathing phases. The proposed technique was tested on computational simulations, phantom experimental acquisitions, and clinical data coming from two patients. Computational simulations provided a controlled and noise-free condition for testing the clustering technique on regular and irregular breathing signals, including baseline drift, time variant amplitude, time variant frequency, and end-expiration plateau. Specific attention was given to cluster initialization. Phantom experiments involved two moving phantoms fitted with multiple markers. Phantoms underwent 4D CT acquisition while performing controlled rigid motion patterns and featuring end-expiration plateau. Breathing cycle period and plateau duration were controlled by means of weights leaned upon the phantom during repeated 4D CT scans. The implemented sorting technique was applied to clinical 4D CT scans acquired on two patients and results were compared to conventional sorting methods. For computational simulations and phantom studies, the performance of the multidimensional clustering technique was evaluated by measuring the repeatability in identifying the breathing phase among adjacent couch positions and the uniformity in sampling the breathing cycle. When breathing irregularities were present, the clustering technique consistently improved breathing phase identification with respect to conventional sorting methods based on monodimensional signals. In patient studies, a qualitative comparison was performed between corresponding breathing phases of 4D CT images obtained by conventional sorting methods and by the described clustering technique. Artifact reduction was clearly observable on both data set especially in the lower lung region. The implemented multiple point method demonstrated the ability to reduce artifacts in 4D CT imaging. Further optimization and development are needed to make the most of the availability of multiple respiratory related variables and to extend the method to 4D CT-PET hybrid scan.

Sorting and expansion of murine embryonic stem cell colonies using micropallet arrays

Isolation of cell colonies is an essential task in most stem cell studies. Conventional techniques for colony selection and isolation require significant time, labor, and consumption of expensive reagents. New microengineered technologies hold the promise for improving colony manipulation by reducing the required manpower and reagent consumption. Murine embryonic stem cells were cultured on arrays composed of releasable elements termed micropallets created from a biocompatible photoresist. Micropallets containing undifferentiated colonies were released using a laser-based technique followed by cell collection and expansion in culture. The micropallet arrays provided a biocompatible substrate for maintaining undifferentiated murine stem cells in culture. A surface coating of 0.025% gelatin was shown to be optimal for cell culture and collection. Arrays composed of surface-roughened micropallets provided further improvements in culture and isolation. Colonies of viable stem cells were efficiently isolated and collected. Colonies sorted in this manner were shown to remain undifferentiated even after collection and further expansion in culture. Qualitative and quantitative analyses of sorting, collection efficiency, and cell viability after release and expansion of stem cell colonies demonstrated that the micropallet array technology is a promising alternative to conventional sorting methods for stem cell applications.

Comparison of the Efficacy of Conventional Sorting Methods for the Removal of Aflatoxin-contaminated Peanuts

The efficacy of typical sorting methods which have been practically employed in industry for excluding aflatoxin-contaminated materials from peanuts was evaluated by determining aflatoxin concentration in the peanuts before and after sorting treatments. The efficacy of aflatoxin removal from panuets varied from almost 0 to 100% depending on the methods used.The aflatoxin concentration in peanuts was most effectively reduced by the manual exclusion of deteriorated peanuts, such as moldy or worm-eaten nuts, based on visual inspection. The effective removal of aflatoxin by using a color sorter required precise tuning of the operating conditions. Sifting and air-fan sorting had no significant effect.In some cases, these sorting procedures, even in combined use, could not reduce the aflatoxin concentration in peanuts to below 10ppb, which is the legal concentration limit under Japanese customs regulations.

A fast sequential algorithm for pixel grey level ranking in adaptive rank filters applied to digital images

A fast sequential algorithm is presented for ranking the pixel grey levels which occur in the window of a digital filter as it is passed over a two-dimensional image. The algorithm is based on continually updating the frequency distribution of the grey levels in the window and ranking them in a one-dimensional array. The proposed algorithm is applied to images containing 256 grey levels and is faster than conventional sorting methods when more than a single ranked parameter is required.

Cost‐Effective Solid‐Waste Characterization Methodology

Characterization of municipal and county solid wastes as well as projection of waste-generation and -disposal rates are needed to plan and implement disposal and recycling activities. A literature review of solid-waste characterization studies revealed that conventional sorting methods are expensive and yield data with great variability. The results of such characterization studies for metropolitan regions have large standard errors, and individual results often fall within the error bounds of reported national average values. An alternative and more cost-effective methodology for estimating county- and city-level solid-waste composition and generation is proposed. The method is based on converting economic sales data for a metropolitan region into estimates of kilograms of solid waste generated. Prototype conversion factors were derived using a material balance approach. The methodology was calibrated using King County, Wash., data and validated on two adjacent counties. The results are promising enough that the methodology should be tested in other parts of the nation. The cost to apply this methodology is a small fraction of the cost of conventional sorting methods, and comparable estimates of major solid-waste components may be possible.

A fast two-dimensional median filtering algorithm

We present a fast algorithm for two-dimensional median filtering. It is based on storing and updating the gray level histogram of the picture elements in the window. The algorithm is much faster than conventional sorting methods. For a window size of m × n, the computer time required is 0(n).

An Apparatus for Sorting Small Fluid-preserved Biological Specimens1

A dish for rapid sorting of berlesates and other bulk samples of small insects, etc. is described and figured. Its use save much time over conventional sorting methods.