delgado ruz, isabel · Figshare · 2022
Neuronal activity is known to be sparse, since only small populations of neurons showing above threshold spiking activity has been recorded on different cortical areas (imaging techniques and electrophysiology). However, existing sorting and clustering algorithms tend to discard neurons that show little activity (low firing rate, temporally sparse activity) or spikes from neurons that deviate from the mean (outliers from main cluster on high dimensional space). On the other hand, High Density Electrode Arrays allows for spike sorting and clustering which recovers units of small amplitude (voltage) that can not be sorted with other recording technologies. Here we review the different approaches followed on the literature for spike detection, feature extraction, sorting and clustering. We also discuss the importance of developing a simple architecture allowing for new developments to plug-in on existing analysis workflow. Additionally analogue aspects of the Action Potential (and sub-threshold activity) have been ignored on population analysis, sensory response characterisation and neural code studies. Mostly given the technological restrictions and access to technology, since for wire electrodes, or even tetrodes the view from different neuron’s spikes turns out to be binary given the restricted area and spatial resolution. Although these simplification has been enough for most tasks so far, they are certainly not enough for advanced and realistic characterisation of how information is processed and transmitted in the brain. Several open-source projects are available for processing electrophysiological data, but their inter-operation is restricted since an standardization and modular designs are still needed. Here we propose a framework’s model in order to freely develop modules that can be connected to each other, allowing for flexibility on the analysis process. Since processing required is heavily dependant on the dataset, experimental conditions and research question. Designing independent and reusable modules is the most reasonable solution.
Cited by 0Open access
Mounir Hamdi, Jianming Tong, Chung-Ta Kin · 2002
The Reconfigurable Array with Spanning Optical Buses (RASOB) has recently received a lot of attention from the research community. By taking advantage of the unique properties of optical transmission, the RASOB provides flexible reconfiguration and strong connectivities with low hardware and control complexities. In this paper, we use this architecture for the design of efficient sorting algorithms on the 1-D RASOB and the 2-D RASOB. Our parallel sorting algorithm on the 1-D RASOB, which sorts N data items using N processors in O(k) time where k is the size of the data items to be in bits, is based on a novel divide-and-conquer scheme. On the other hand, our parallel sorting algorithm on the 2-D RASOB is based on the sorting algorithm on the 1-D RASOB in conjunction with the well known Rotatesort algorithm. This algorithm sorts N data items on a 2-D RASOB of size N in O(k) time. These sorting algorithms outperform state-of-the-art sorting algorithms on reconfigurable arrays of processors with electronic buses.
Cited by 2
Gordon J. Christensen · The Journal of the American Dental Association · 1999
Cited by 14
Rare & Special e-Zone (The Hong Kong University of Science and Technology) · 1996
Cited by 0
Masashi Miyata, Toshikazu Hashimoto · 2024
We experimentally demonstrate a metalens array that sorts red (R), green (G), blue (B), and near-infrared (NIR) light on ultra-small pixels. We also demonstrate its capability to create a high-sensitivity RGB-NIR image sensor. © 2024 The Author(s)
Cited by 0
Wei Quan, Ping Li, Fengkai Xu · 2010
This article uses the radar beams scan characteristics of the phased array radar, and proposes an algorithm based on the rough sets theory to sort the signal of phased array radars. From the research of the character of the phased array radar's beam scanning manners, and use the PDW received from sensors as the set of attributes. So we can sort the phased array radar signal from the environment.
Cited by 5
Jung-Hun Lee, Young Ho Kim, Young-Geun Kim et al. · Journal of Sensor Science and Technology · 2010
A high-throughput sorting (HTS) system has been designed to separate target particles using a negative dielectrophoretic (n-DEP) force. The system consists of a meso-sized channel and a cantilever-type electrode(CE) array designed to separate a large number of target particles by discerning subtle difference of weight and dielectric material property of the particles. Using the polystyrene beads with various sizes of 10, 25 and <TEX>$50{\mu}m$</TEX>, the developed system exhibits high-throughput sorting of about 200 beads/sec and more than 80 % of separation efficiency.
Cited by 0Open access
delgado ruz, isabel · Figshare · 2022
Neuronal activity is known to be sparse, since only small populations of neurons showing above threshold spiking activity has been recorded on different cortical areas (imaging techniques and electrophysiology). However, existing sorting and clustering algorithms tend to discard neurons that show little activity (low firing rate, temporally sparse activity) or spikes from neurons that deviate from the mean (outliers from main cluster on high dimensional space). On the other hand, High Density Electrode Arrays allows for spike sorting and clustering which recovers units of small amplitude (voltage) that can not be sorted with other recording technologies. Here we review the different approaches followed on the literature for spike detection, feature extraction, sorting and clustering. We also discuss the importance of developing a simple architecture allowing for new developments to plug-in on existing analysis workflow. Additionally analogue aspects of the Action Potential (and sub-threshold activity) have been ignored on population analysis, sensory response characterisation and neural code studies. Mostly given the technological restrictions and access to technology, since for wire electrodes, or even tetrodes the view from different neuron’s spikes turns out to be binary given the restricted area and spatial resolution. Although these simplification has been enough for most tasks so far, they are certainly not enough for advanced and realistic characterisation of how information is processed and transmitted in the brain. Several open-source projects are available for processing electrophysiological data, but their inter-operation is restricted since an standardization and modular designs are still needed. Here we propose a framework’s model in order to freely develop modules that can be connected to each other, allowing for flexibility on the analysis process. Since processing required is heavily dependant on the dataset, experimental conditions and research question. Designing independent and reusable modules is the most reasonable solution.
Cited by 0Open access
Misato Hayashi, Hideko Takeshita · Primates · 2020
Cited by 3
Daniel Suárez-Barrera (22676654), Lucas Bayones (22676657), Norberto Encinas-Rodríguez (22676660) et al. · Figshare · 2025
This figure examines how precision (related to contamination) and recall (related to lost spikes) contribute to the spatial decay of the F1 score (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003527#pbio.3003527.g005" target="_blank">Fig 5</a>) when comparing Uniform Manifold Approximation and Projection (UMAP) and SpyKING CIRCUS (SC) on MEA recordings. Results are averaged over multiple MEAs. <b>(A, D)</b> Average spatial matrices for precision (A) and recall (D) computed using UMAP-based sorting. <b>(B, C)</b> Decay of precision, and fit of that decay (C), as electrode distance increases for UMAP. Triangles on (B) represent average precision values computed with UMAP-based sorting (light-blue) or SC (cyan) using the entire MEA signal. <b>(E, F)</b> Decay of recall, and fit of that decay (F), as electrode distance increases. Triangles on (E) represent average recall values computed with UMAP-based sorting (orange) or SC (yellow) using the entire MEA signal. Note that average for recall using SC is significantly low with respect to UMAP’s, indicating the loss of many GT spikes beyond the central electrode. By contrast, UMAP sustains higher precision and recall across a wider spatial range. MEA recordings supporting the analyses are available at [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003527#pbio.3003527.ref042" target="_blank">42</a>], and the code necessary for the analyses is available at [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003527#pbio.3003527.ref052" target="_blank">52</a>]. (PDF)
Cited by 0Open access
Aaron Stillmaker, Lucas Stillmaker, Bevan Baas · 2012
Data centers require significant and growing amounts of power to operate, and with increasing numbers of data centers worldwide, power consumption for enterprise workloads is a significant concern. Sorting is a key computational kernel in large database systems, and the development of energy efficient sorting capabilities would therefore significantly reduce data center power usage. We propose highly parallel sorting algorithms and mappings using a modular design for a fine-grained many-core system that greatly decreases the amount of energy consumed to perform sorts of arbitrarily large data sets. The memory, computational, and nearest-neighbor inter-processor communication hardware of the many-core processor array require relatively small die area. We present the design and implementation of several sorting variants that perform the first phase of an external sort. They are built using program kernels operating on independent processors in a many-core array with 256 bytes of data memory and fewer than 128 instructions per processor. The algorithms employed are simple and the vast majority of processors contain identical programs. Compared to a quicksort implementation on an Intel Core 2 Duo T9600 the highest throughput design achieves up to 27× higher throughput per chip area, and the most energy efficient sort yields a 330× reduction in energy dissipated per sorted block. Compared to a radix sort implementation on a GPU, the highest throughput design achieves up to 22× higher throughput per chip area, and the most energy efficient sort yields a 750× reduction in energy dissipated per sorted block.
Cited by 6
Lan Huang, Teng Gao, Feng Yang et al. · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · 2024
The exploration of utilizing reconfigurable circuits with parallel computing capabilities has been conducted to enhance sorting performance and reduce power consumption. However, most sorting algorithms using dedicated processors are based on parallelization designs of serial algorithms without considering the design method of large-scale integrated circuits. This results in various issues, including the overuse of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$I/O$ </tex-math></inline-formula> interface resources, on-chip storage resources, and complex layout wiring. In this article, we extend the 2-tuple relation in the uniform recurrence equation (URE) structure used to define the systolic array to n-tuples, and the extended structure is flexible in defining <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$I/O$ </tex-math></inline-formula> bandwidth and concurrency. Then we define the multiconcurrency systolic sorter array (MCSSA) algorithm based on the extended URE structure, which has a flexible <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4N/n$ </tex-math></inline-formula> time complexity based on the n-tuple relation. Moreover, this systolic array can simultaneously sort two independent sequences, increasing the reuse of resources. Afterwards, we encapsulate each n-tuple into a processing element (PE) cell. The entire MCSSA consists of these interconnected PE cells, each of which can be customized in terms of data bit width and type. Last but not least, we have improved the merge tree structure called MC-merge tree. The concurrency of this algorithm can also be flexibly defined, we use this algorithm combined with MCSSA to cope with large-scale sorting scenarios. In our experiments, we have demonstrated the speed-up ratio of MCSSA relative to other state of the art (SOTA) sorting algorithms. Inheriting the unity and simplicity from the Systolic Array architecture, MCSSA achieves a maximum <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$73.17\times $ </tex-math></inline-formula> acceleration ratio on the U200. In addition, the MC-merge tree expands the MCSSA sorting scale with a maximum of 450.56 times while maintaining the advantage of the acceleration ratio. The results of our study demonstrate that MCSSA and MC-merge tree have better acceleration, throughput and scalability advantages over other SOTA algorithms.
Cited by 1
Lee, Jin Hyung · Columbia Academic Commons (Columbia University) · 2020
Cited by 0Open access
Ming-Yang Chern · Figshare · 1983
Cited by 0Open access
Ziwei Zhu · 2010
A LED array automatic sorting system was designed in terms of LED lamp properties.The system can measure the quality of LED arrays and sort them automatically using the digital image processing to recognize them,analyze brightness and count them.In order to simplify hardware and reduce costs,measurement and control were performed by PC software.Users can fit filters and set parameters such as precision and exposure time according to different samples,which makes the system more portable and easy to maintain.
Cited by 0
Balaram Behera · Theoretical Computer Science · 2020
Cited by 0Open access
Akihiro Isozaki, Dunhou Huang, Yuta Nakagawa et al. · Microfluidics and Nanofluidics · 2021
Abstract 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.
Cited by 16Open access
Abdullah Sheneamer, Ahmed D. Alharthi, Hanan Hazazi · International Journal of Computer Applications · 2015
Data Structure is one of the fundamental areas of the computer science. Sorting is crucial in data structure, which creates the list of sequence items. In this paper, we present two techniques of sorting algorithm for natural numbers, which uses the array indexing methodology and insert that number into the proper index of the array without performing any element comparisons and swapping. The first algorithm improves Array-Indexed Sorting Algorithm for natural numbers [1] by adding negative numbers. The second algorithm is a new sorting algorithm that refers to Two Arrays-Indexed Sorting Algorithm for Natural Numbers (TAISN). The two techniques of sorting algorithm for natural numbers are efficient to give a much better performance than the existing sorting algorithms of the O(n 2 ) class, for large array size with same length of digits of input data.
Cited by 1Open access
Amitava Datta, Robyn Owens, Subbiah Soundaralakshmi · Lecture notes in computer science · 2000
Cited by 1
Eli Lansey, Isroel M. Mandel, Ian R. Hooper et al. · IEEE Transactions on Antennas and Propagation · 2015
We present experimental results demonstrating the spatial sorting of incoming radiation in two spectral ranges. A metasurface composed of a periodically patterned metal of subwavelength thickness with dielectric inclusions concentrates and localizes electromagnetic fields near the surface. Light of the separate spectral bands is channeled into different geometrically tuned cavities within each spatially repeating unit cell. Excitation of cavity modes facilitates this simultaneous spatial- and spectral-selective absorption. The measured reflection and field profiles are presented and the spectral and spatial selectivity are shown. A method to apply these concepts to split radiation into three spectral bands is also proposed.
Cited by 3