Single-point detection strategy for probing 2D SPR sensor array (Conference Presentation)

2020 ◽  
Author(s):  
Dongping Wang ◽  
Jacky Fong Chuen Loo ◽  
Yeung Yam ◽  
Shih-Chi Chen ◽  
Aaron Ho-Pui Ho
Keyword(s):  
Sensor Array ◽  
Single Point ◽  
Spr Sensor ◽  
Detection Strategy ◽  
Point Detection

Development of a sensitive DMD-based 2D SPR sensor array using single-point detection strategy for multiple aptamer screening

2020 ◽  
Vol 305 ◽  
pp. 127240 ◽  
Author(s):  
Dongping Wang ◽  
Jacky Fong Chuen Loo ◽  
Wei Lin ◽  
Qiang Geng ◽  
Erika Kit Shan Ngan ◽  
...  
Keyword(s):  
Sensor Array ◽  
Single Point ◽  
Spr Sensor ◽  
Detection Strategy ◽  
Point Detection

Traffic Classification Features and its Application in DDoS Detection

2013 ◽  
Vol 380-384 ◽  
pp. 2673-2676
Author(s):  
Ze Yu Xiong
Keyword(s):  
Detection Method ◽  
Single Point ◽  
Attack Detection ◽  
Traffic Classification ◽  
Ddos Attacks ◽  
Detection Scheme ◽  
Ddos Detection ◽  
Point Detection ◽  
Ddos Attack Detection ◽  
Collaborative Detection

DDoS attacks have relatively low proportion of normal flow in the boundary network at the attack traffic,In this paper,we establish DDoS attack detection method based on defense stage and defensive position, and design and implement collaborative detection of DDoS attacks. Simulation results show that our approach has good timeliness, accuracy and scalability than the single-point detection and route-based distributed detection scheme.

scholarly journals Efficient Detection Approach for DTMF Signal Detection

2019 ◽  
Vol 9 (3) ◽  
pp. 422
Author(s):  
Cheng-Yu Yeh ◽  
Shaw-Hwa Hwang
Keyword(s):  
Signal Detection ◽  
Single Point ◽  
Load Reduction ◽  
Optimal Frequency ◽  
Embedded Devices ◽  
Computational Load ◽  
Efficient Detection ◽  
Detection Approach ◽  
Point Detection ◽  
Tone Detection

A novel tone detection approach, designated as the multi-frequency detecting (MFD) algorithm, is presented in this work as an alternative to conventional single point detection approaches but it is an efficient way to achieve the aim of further computational load reduction for a dual-tone multi-frequency (DTMF) signal detection. The idea is that an optimal phase search is performed over the frequency band of interest in each tone detection, and then the optimal frequency response of a detector is built accordingly. In this manner, a DTMF detection task is done following one-time detection computation. This proposal demonstrates an overall computational load reduction of 80.49% and 74.06% in comparison with a discrete Fourier transform (DFT) approach and the Goertzel algorithm, respectively. This detection complexity reduction is an advantage and an important issue for applying DTMF detection technique to embedded devices.

scholarly journals Detection of multiple leakage points in water distribution networks based on convolutional neural networks

2019 ◽  
Vol 19 (8) ◽  
pp. 2231-2239 ◽  
Author(s):  
QianSheng Fang ◽  
JiXin Zhang ◽  
ChenLei Xie ◽  
YaLong Yang
Keyword(s):  
Water Resources ◽  
Distribution System ◽  
Water Distribution ◽  
Historical Data ◽  
Single Point ◽  
Distribution Networks ◽  
Detection Methods ◽  
Leakage Detection ◽  
Time Data ◽  
Point Detection

Abstract Currently, a total of 3.6 billion people live in water-deficient areas, and the population living in water-deficient areas may reach from 4.8 to 5.7 billion by 2050. Despite that, the water distribution system (WDS) loses an average of 35% of its water resources, and the leakage rates may reach even higher values in some regions. The dual pressures of the lack of water resources and severe WDS leakage become even more problematic considering that commonly used leakage detection methods are time-consuming, labour-intensive, and can only detect single-point leakages. For multiple leakage point detection, these methods often perform poorly. To solve the problem of multiple leakage point detection, this paper presents a method for multiple leakage point detection based on a convolutional neural network (CNN). A CNN can forecast the leakages from a macro-perspective. It extracts the features of the collected historical leakage data by constructing a CNN model and predicts whether the real-time data are leakage data or not based on the learning of the features that are extracted from the historical data. The experimental results show that the detection accuracies based on 21 sensors of one, two, and three leakage points are 99.63%, 98.58% and 95.25%, respectively. After the number of sensors is reduced to eight, the leakage detection accuracies of one, two, and three leakage points are 96.43%, 94.88% and 91.56%, respectively.

Integration of a PDMS/SU-8/Quartz Microfluidic Chip With a Novel Macroporous Poly Dimethylsiloxane (PDMS) Membrane for Isoelectric Focusing of Proteins Using Whole-Channel Imaging Detection

2010 ◽  
Author(s):  
Seyed Mostafa Shameli ◽  
Caglar Elbuken ◽  
Carolyn L. Ren ◽  
Janusz Pawliszyn
Keyword(s):  
Isoelectric Focusing ◽  
Single Point ◽  
Constant Electric Field ◽  
Stray Light ◽  
Detection Sensitivity ◽  
Detection Methods ◽  
Field Samples ◽  
Imaging Detection ◽  
Separation Of Proteins ◽  
Point Detection

Capillary isoelectric focusing (CIEF) is a high-resolution capillary electrophoresis (CE) technique for separating zwitterionic biomolecules, such as proteins and peptides. In this method, by generating a stable pH gradient along the length of the capillary and under the influence of a constant electric field, samples can be separated according to their different isoelectric points (pI). For identifying the focused zones in CIEF, the whole column imaging detection (WCID) is more reliable than any other single point detection methods since it avoids the need of focused peak mobilization, presenting several advantages such as lower detection time, minimized peak dispersion and consequently higher resolution. Capillary-based IEF-WCID has been invented by Convergent Bioscience Inc. (iCE280 analyzer) for separation of proteins and biomarkers [1–2]. In the iCE280 analyzer, hollow fibers are glued to the capillary to separate electrolytes from the samples and a metal slit with a 65 μm opening is glued to the top of the capillary to improve detection sensitivity by blocking stray light. However, this method has several limitations because of the use of capillary such as low throughput, difficulty to be integrated with other separation modes and low detection sensitivity.

Period Doubling Bifurcation Point Detection Strategy with Nested Layer Particle Swarm Optimization

2017 ◽  
Vol 27 (07) ◽  
pp. 1750101 ◽  
Author(s):  
Haruna Matsushita ◽  
Yusho Tomimura ◽  
Hiroaki Kurokawa ◽  
Takuji Kousaka
Keyword(s):  
Particle Swarm Optimization ◽  
Bifurcation Point ◽  
Particle Swarm ◽  
Period Doubling ◽  
Period Doubling Bifurcation ◽  
Swarm Optimization ◽  
Detection Strategy ◽  
The Stability ◽  
Point Detection ◽  
Discrete Time Dynamical Systems

This paper proposes a bifurcation point detection strategy based on nested layer particle swarm optimization (NLPSO). The NLPSO is performed by two particle swarm optimization (PSO) algorithms with a nesting structure. The proposed method is tested in detection experiments of period doubling bifurcation points in discrete-time dynamical systems. The proposed method directly detects the parameters of period doubling bifurcation regardless of the stability of the periodic point, but require no careful initialization, exact calculation or Lyapunov exponents. Moreover, the proposed method is an effective detection technique in terms of accuracy, robustness usability, and convergence speed.

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