scholarly journals Research on Music Multiterminal Audio Authentication Based on Wireless Network

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Dongmei Li
Keyword(s):  
Wireless Network ◽  
Hamming Distance ◽  
Sudden Change ◽  
Tamper Detection ◽  
Fuzzy Classification ◽  
Statistical Characteristics ◽  
Energy Calculation ◽  
Detection Ability ◽  
Music Signal ◽  
Audio Authentication

The current music multiterminal audio authentication algorithm does not consider the mutation of music signal, which leads to poor tamper detection ability and long time of audio authentication. By analyzing the characteristics and key technologies of wireless network, a wireless multiterminal audio system is established. The short-term energy calculation method is used to consider the sudden change of music signal. The music signal is divided into note segments, and chroma features of half order notes are extracted. The robust hash value is calculated by nonuniform quantization method. The dynamic time warping algorithm is used to align the notes, and the Hamming distance between the hash values of each two corresponding notes is calculated to obtain the measurement values of error series, statistical characteristics, and time distribution characteristics. According to the measurement value, the fuzzy classification method is applied to calculate the membership degree of the signals belonging to two different types of operation, and the authentication confidence degree is obtained. The tampered area of the music signal that has not passed the authentication is detected, and the music multiterminal audio authentication is realized. Experimental results show that the proposed algorithm has good tamper detection ability and can effectively shorten the audio authentication time.

scholarly journals Evaluation of Takagi-Sugeno-Kang fuzzy method in entropy-based detection of DDoS attacks

2018 ◽  
Vol 15 (1) ◽  
pp. 139-162 ◽  
Author(s):  
Miodrag Petkovic ◽  
Ilija Basicevic ◽  
Dragan Kukolj ◽  
Miroslav Popovic
Keyword(s):  
Network Traffic ◽  
Fuzzy System ◽  
False Positive Rate ◽  
Denial Of Service ◽  
Sudden Change ◽  
Change Point Detection ◽  
Statistical Characteristics ◽  
Ddos Attacks ◽  
Detection Process ◽  
Takagi Sugeno

The detection of distributed denial of service (DDoS) attacks based on internet traffic anomalies is a method which is general in nature and can detect unknown or zero-day attacks. One of the statistical characteristics used for this purpose is network traffic entropy: a sudden change in entropy may indicate a DDoS attack. However, this approach often gives false positives, and this is the main obstacle to its wider deployment within network security equipment. In this paper, we propose a new, two-step method for detection of DDoS attacks. This method combines the approaches of network traffic entropy and the Takagi-Sugeno-Kang fuzzy system. In the first step, the detection process calculates the entropy distribution of the network packets. In the second step, the Takagi-Sugeno-Kang fuzzy system (TSK-FS) method is applied to these entropy values. The performance of the TSK-FS method is compared with that of the typically used approach, in which cumulative sum (CUSUM) change point detection is applied directly to entropy time series. The results show that the TSK-FS DDoS detector reaches enhanced sensitivity and robustness in the detection process, achieving a high true-positive detection rate and a very low false-positive rate. As it is based on entropy, this combined method retains its generality and is capable of detecting various types of attack.

scholarly journals Automatic Classification Algorithm for Multisearch Data Association Rules in Wireless Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Cailing Li ◽  
Wenjun Li
Keyword(s):  
Wireless Network ◽  
Association Rules ◽  
Data Association ◽  
Automatic Classification ◽  
Classification Algorithm ◽  
Fuzzy Classification ◽  
Classification Error ◽  
Data Generation ◽  
High Coverage ◽  
Efficient Data

In order to realize efficient data processing in wireless network, this paper designs an automatic classification algorithm of multisearch data association rules in a wireless network. According to the algorithm, starting from the mining of multisearch data association rules, from the discretization of continuous attributes of multisearch data, generation of fuzzy classification rules, and the design of association rule classifier and other aspects, automatic classification is completed by using the mining results. Experimental results show that this algorithm has the advantages of small classification error, good real-time performance, high coverage rate, and high feasibility.

scholarly journals Node Selection Algorithm for Network Coding in the Mobile Wireless Network

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 842
Author(s):  
Dexia Jiang ◽  
Leilei Li
Keyword(s):  
Wireless Networks ◽  
Network Coding ◽  
Wireless Network ◽  
Minimum Energy ◽  
Search Time ◽  
Maximum Flow ◽  
Statistical Characteristics ◽  
Selection Algorithm ◽  
Intermediate Node ◽  
Flow Algorithm

In the multicast network, network coding has proven to be an effective technique to approach maximum flow capacity. Although network coding has the advantage of improving performance, encoding nodes increases the cost and delay in wireless networks. Therefore, minimizing encoding nodes is of great significance to improve the actual network’s performance under a maximum multicast flow. This paper seeks to achieve partial improvements in the existing selection algorithm of encoding nodes in wireless networks. Firstly, the article gives the condition for an intermediate node to be an encoding node. Secondly, a maximum flow algorithm, which depends on the depth-first search method, is proposed to optimize the search time by selecting the larger augmentation flow in each step. Finally, we construct a random graph model to simulate the wireless network and the maximum multicast flow algorithm to analyze the statistical characteristics of encoding nodes. This paper aims at the optimization to find the minimal number of required coding nodes which means the minimum energy consumption. Meanwhile, the simulations indicate that the curve of coding nodes tends to be a geometric distribution, and that the curve of the maximum flow tends to be symmetric as the network scale and the node covering radius increase.

Characteristics of precipitation and temperature in the Daqing River Basin

2020 ◽  
Author(s):  
Yufei Jiao ◽  
Jia Liu ◽  
Chuanzhe Li ◽  
Qingtai Qiu ◽  
Wei Wang
Keyword(s):  
River Basin ◽  
Moving Average ◽  
Sudden Change ◽  
Statistical Characteristics ◽  
Upward Trend ◽  
Periodic Analysis ◽  
Main Period ◽  
Wavelet Variance ◽  
Precipitation And Temperature ◽  
Periodic Changes

<p>The statistical characteristics of precipitation and temperature in the Daqing River Basin from 1980 to 2015 are analyzed, including the analysis of the homogeneity, trend, mutation and periodicity. Among them, the analysis of homogeneity is based on the method of cumulative value. The trend analysis adopts the methods of moving average, M-K test and R/S. M-K test is also used for the mutation analysis. The wavelet transform is used in the periodic analysis to draw the contour of real part and modulus of precipitation and temperature, as well as the map of the wavelet variance and the main period trend. The results show that the precipitation in the Daqing River Basin from 1980 to 2015 is uniform and has a significant upward trend, and has a sudden change in 2008. As for the periodicity, there are three kinds of periodic changes in 22-32 years, 8-16 years and 3-7 years. In the 22-32 year scale, there are two quasi oscillations of the dry and wet alternation, and four quasi oscillations in the 8-16 year scale. In the graph of the wavelet variance, the peak corresponds to the time scale of 28 years, which indicates that the oscillation of 28 years is the strongest, which is the first main period of precipitation change. From 1980 to 2015, the temperature in the Daqing River Basin is also uniform, and has an obvious upward trend, and has a sudden change in 1992. As for the periodicity, there are three kinds of periodic change, 5-10 years, 14-20 years and 25-32 years, respectively. In the 25-32 year scale, there are two quasi oscillations of dry and wet alternation, and three quasi oscillations in the 14-20 year scale. There are three obvious peaks in the map of wavelet variance, which correspond to the time scales of 28 years, 18 years and 8 years in turn.</p>

The value of Electron Microscope studies of imperfect natural diamonds

1990 ◽  
Vol 48 (4) ◽  
pp. 194-195
Author(s):  
J C Walmsley ◽  
A R Lang
Keyword(s):  
Electron Microscope ◽  
Classification Scheme ◽  
Natural Diamond ◽  
Sudden Change ◽  
Growth Conditions ◽  
Diamond Growth ◽  
Major Constituent ◽  
Natural Diamonds ◽  
Type Ia ◽  
Platelet Defects

Interest in the defects and impurities in natural diamond, which are found in even the most perfect stone, is driven by the fact that diamond growth occurs at a depth of over 120Km. They display characteristics associated with their origin and their journey through the mantle to the surface of the Earth. An optical classification scheme for diamond exists based largely on the presence and segregation of nitrogen. For example type Ia, which includes 98% of all natural diamonds, contain nitrogen aggregated into small non-paramagnetic clusters and usually contain sub-micrometre platelet defects on {100} planes. Numerous transmission electron microscope (TEM) studies of these platelets and associated features have been made e.g. . Some diamonds, however, contain imperfections and impurities that place them outside this main classification scheme. Two such types are described.First, coated-diamonds which possess gem quality cores enclosed by a rind that is rich in submicrometre sized mineral inclusions. The transition from core to coat is quite sharp indicating a sudden change in growth conditions, Figure 1. As part of a TEM study of the inclusions apatite has been identified as a major constituent of the impurity present in many inclusion cavities, Figure 2.

Adaptive identification methods of nonlinear random electrical signal

2020 ◽  
Vol 64 (1-4) ◽  
pp. 431-438
Author(s):  
Jian Liu ◽  
Lihui Wang ◽  
Zhengqi Tian
Keyword(s):  
Wavelet Transform ◽  
Electric Vehicle ◽  
Signal To Noise Ratio ◽  
Sudden Change ◽  
Electrical Signal ◽  
Signal Recognition ◽  
State Variable ◽  
Signal Characteristics ◽  
The Matrix ◽  
Kalman Filter Algorithm

The nonlinearity of the electric vehicle DC charging equipment and the complexity of the charging environment lead to the complex and changeable DC charging signal of the electric vehicle. It is urgent to study the distortion signal recognition method suitable for the electric vehicle DC charging. Focusing on the characteristics of fundamental and ripple in DC charging signal, the Kalman filter algorithm is used to establish the matrix model, and the state variable method is introduced into the filter algorithm to track the parameter state, and the amplitude and phase of the fundamental waves and each secondary ripple are identified; In view of the time-varying characteristics of the unsteady and abrupt signal in the DC charging signal, the stratification and threshold parameters of the wavelet transform are corrected, and a multi-resolution method is established to identify and separate the unsteady and abrupt signals. Identification method of DC charging distortion signal of electric vehicle based on Kalman/modified wavelet transform is used to decompose and identify the signal characteristics of the whole charging process. Experiment results demonstrate that the algorithm can accurately identify ripple, sudden change and unsteady wave during charging. It has higher signal to noise ratio and lower mean root mean square error.

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