scholarly journals High-performance hardware implementation of a parallel database search engine for real-time peptide mass fingerprinting

2008 ◽  
Vol 24 (13) ◽  
pp. 1498-1502 ◽  
Author(s):  
I. A. Bogdan ◽  
J. Rivers ◽  
R. J. Beynon ◽  
D. Coca
Keyword(s):  
Real Time ◽  
Search Engine ◽  
High Performance ◽  
Hardware Implementation ◽  
Peptide Mass Fingerprinting ◽  
Database Search ◽  
Parallel Database ◽  
Peptide Mass

Hardware Implementation Optimization of Extended Kalman Filter for the Estimation of State of Charge of Li-Ion Battery

2015 ◽  
Vol 713-715 ◽  
pp. 1094-1098
Author(s):  
Hong Ce Zhang ◽  
Pu Shen Wang ◽  
Jiang Jiang ◽  
Hong Fei Cao
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Extended Kalman Filter ◽  
High Performance ◽  
Hardware Implementation ◽  
State Of Charge ◽  
Li Ion Batteries ◽  
Soc Estimation ◽  
Li Ion ◽  
Time Restriction

Extended Kalman Filter (EKF) is widely studied in the field of State of Charge (SOC) estimation of Li-ion batteries, however, in applications like Electric Vehicles (EV), there are usually a large number of individual battery cells. In order to meet the demand of real-time computation, MCU of high performance is essential. In this paper, we proposed a hardware structure to implement EKF which is economical in area and power consumption and could be easily integrated in a larger design and at the same time could satisfy the real-time restriction.

Real-Time High Jump Wearable Device with ESP8266 for High-Performance and Low-Injury

2018 ◽  
Vol 10 (3) ◽  
Author(s):  
Muhammad Faris Roslan ◽  
◽  
Afandi Ahmad ◽  
Abbes Amira ◽  
◽  
...  
Keyword(s):  
Real Time ◽  
High Performance ◽  
Wearable Device

Proteomic Analysis of Medicinal Plant Calotropis Gigantea by insilico Peptide Mass Fingerprinting

2020 ◽  
Vol 16 ◽  
Author(s):  
Saad Ur Rehman ◽  
Muhammad Rizwan ◽  
Sajid Khan ◽  
Azhar Mehmood ◽  
Anum Munir
Keyword(s):  
Medicinal Plant ◽  
Structure Prediction ◽  
3D Structure ◽  
Peptide Mass Fingerprinting ◽  
Protein Docking ◽  
Receptor Protein ◽  
Human Leukemia ◽  
Protein Database ◽  
Calotropis Gigantea ◽  
Peptide Mass

: Medicinal plants are the basic source of medicinal compounds traditionally used for the treatment of human diseases. Calotropis gigantea a medicinal plant belonging to the family of Apocynaceae in the plant kingdom and subfamily Asclepiadaceae usually bearing multiple medicinal properties to cure a variety of diseases. Background: The Peptide Mass Fingerprinting (PMF) identifies the proteins from a reference protein database by comparing the amino acid sequence that is previously stored in a database and identified. Method: The calculation of insilico peptide masses is done through the ExPASy PeptideMass and these masses are used to identify the peptides from MASCOT online server. Anticancer probability is calculated from the iACP server, docking of active peptides is done by CABS-dock the server. Objective: The purpose of the study is to identify the peptides having anti-cancerous properties by in-silico peptide mass fingerprinting. Results : The anti-cancerous peptides are identified with the MASCOT peptide mass fingerprinting server, the identified peptides are screened and only the anti-cancer are selected. De novo peptide structure prediction is used for 3D structure prediction by PEP-FOLD 3 server. The docking results confirm strong bonding with the interacting amino acids of the receptor protein of breast cancer BRCA1 which shows the best peptide binding to the Active chain, the human leukemia protein docking with peptides shows the accurate binding. Conclusion : These peptides are stable and functional and are the best way for the treatment of cancer and many other deadly diseases.

scholarly journals Artificial Intelligence-Assisted Colonoscopy for Detection of Colon Polyps: a Prospective, Randomized Cohort Study

2020 ◽  
Author(s):  
Yuchen Luo ◽  
Yi Zhang ◽  
Ming Liu ◽  
Yihong Lai ◽  
Panpan Liu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
High Performance ◽  
Detection System ◽  
Random Order ◽  
Colon Polyps ◽  
Clinical Environment ◽  
Polyp Detection ◽  
Link Type ◽  
Polyp Detection Rate

Abstract Background and aims Improving the rate of polyp detection is an important measure to prevent colorectal cancer (CRC). Real-time automatic polyp detection systems, through deep learning methods, can learn and perform specific endoscopic tasks previously performed by endoscopists. The purpose of this study was to explore whether a high-performance, real-time automatic polyp detection system could improve the polyp detection rate (PDR) in the actual clinical environment. Methods The selected patients underwent same-day, back-to-back colonoscopies in a random order, with either traditional colonoscopy or artificial intelligence (AI)-assisted colonoscopy performed first by different experienced endoscopists (> 3000 colonoscopies). The primary outcome was the PDR. It was registered with clinicaltrials.gov. (NCT047126265). Results In this study, we randomized 150 patients. The AI system significantly increased the PDR (34.0% vs 38.7%, p < 0.001). In addition, AI-assisted colonoscopy increased the detection of polyps smaller than 6 mm (69 vs 91, p < 0.001), but no difference was found with regard to larger lesions. Conclusions A real-time automatic polyp detection system can increase the PDR, primarily for diminutive polyps. However, a larger sample size is still needed in the follow-up study to further verify this conclusion. Trial Registration clinicaltrials.gov Identifier: NCT047126265

Progress Towards Arrays of Microcalorimeter X-Ray Detectors

2001 ◽  
Vol 7 (S2) ◽  
pp. 1050-1051 ◽  
Author(s):  
S.W. Nam ◽  
D.A. Wollman ◽  
Dale E. Newbury ◽  
G.C. Hilton ◽  
K.D. Irwin ◽  
...  
Keyword(s):  
Real Time ◽  
Energy Resolution ◽  
Count Rate ◽  
Small Area ◽  
High Performance ◽  
X Ray ◽  
Pixel Array ◽  
Primary Advantage ◽  
Low X ◽  
Single Pixel

The high performance of single-pixel microcalorimeter EDS (μ,cal EDS) has been shown to be very useful for a variety of microanalysis cases. The primary advantage of jxcal EDS over conventional EDS is the factor of 25 improvement in energy resolution (∽3 eV in real-time). This level of energy resolution is particularly important for applications such as nanoscale contaminant analysis where it is necessary to resolve peak overlaps at low x-ray energies. Because μcal EDS offers practical solutions to many microanalysis problems, several companies are proceeding with commercialization of single-pixel μal EDS technology. Two drawbacks limiting the application of uxal EDS are its low count rate (∽500 s−1) and small area (∽0.04 mm for a bare single pixel, ∽5 mm2 with a polycapillary optic). We are developing a 32x32 pixel array with a total area of 40 mm2 and with a total count rate between 105 s−1 and 106 s−1.

scholarly journals Stochastic-Depth Ambient Occlusion

2021 ◽  
Vol 4 (1) ◽  
pp. 1-15
Author(s):  
Jop Vermeer ◽  
Leonardo Scandolo ◽  
Elmar Eisemann
Keyword(s):  
Real Time ◽  
High Performance ◽  
Depth Map ◽  
Visual Quality ◽  
Ambient Light ◽  
Missing Information ◽  
Time Performance ◽  
Ambient Occlusion ◽  
Depth Buffer ◽  
Screen Space

Ambient occlusion (AO) is a popular rendering technique that enhances depth perception and realism by darkening locations that are less exposed to ambient light (e.g., corners and creases). In real-time applications, screen-space variants, relying on the depth buffer, are used due to their high performance and good visual quality. However, these only take visible surfaces into account, resulting in inconsistencies, especially during motion. Stochastic-Depth Ambient Occlusion is a novel AO algorithm that accounts for occluded geometry by relying on a stochastic depth map, capturing multiple scene layers per pixel at random. Hereby, we efficiently gather missing information in order to improve upon the accuracy and spatial stability of conventional screen-space approximations, while maintaining real-time performance. Our approach integrates well into existing rendering pipelines and improves the robustness of many different AO techniques, including multi-view solutions.

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