Supervised Feature Learning for Offline Writer Identification Using VLAD and Double Power Normalization

As an indispensable part of identity authentication,offline writer identification plays a notable role in biology,forensics,and historical document analysis.However,identifying handwriting efficiently,stably,and quickly is still challenging due to the method of extracting and processing handwriting features.In this paper,we propose an efficient system to identify writers through handwritten images,which integrates local and global features from similar handwritten images.The local features are modeled by effective aggregate processing,and global features are extracted through transfer learning.Specifically,the proposed system employs a pre-trained Residual Network to mine the relationship between large image sets and specific handwritten images,while the vector of locally aggregated descriptors with double power normalization is employed in aggregating local and global features.Moreover,handwritten image segmentation,preprocessing,enhancement,optimization of neural network architecture,and normalization for local and global features are exploited,significantly improving system performance.The proposed system is evaluated on Computer Vision Lab(CVL)datasets and the International Conference on Document Analysis and Recognition(ICDAR)2013 datasets.The results show that it represents good generalizability and achieves state-of-the-art performance.Furthermore,the system performs better when training complete handwriting patches with the normalization method.The experimental result indicates that it’s significant to segment handwriting reasonably while dealing with handwriting overlap,which reduces visual burstiness.

Proposal and Pilot Study: A Generalization of the W or W'Statistic for Multivariate Normality

The aim of this paper is to present a generalization of the Shapiro-Wilk W-test or Shapiro-Francia W'-test for application to two or more variables. It consists of calculating all the unweighted linear combinations of the variables and their W- or W'-statistics with the Royston’s log-transformation and standardization, zln(1-W) or zln(1-W'). Because the calculation of the probability of zln(1-W) or zln(1-W') is to the right tail, negative values are truncated to 0 before doing their sum of squares. Independence in the sequence of these half-normally distributed values is required for the test statistic to follow a chi-square distribution. This assumption is checked using the robust Ljung-Box test. One degree of freedom is lost for each cancelled value. Defined the new test with its two variants (Q-test or Q'-test), 50 random samples with 4 variables and 20 participants were generated, 20% following a multivariate normal distribution and 80% deviating from this distribution. The new test was compared with Mardia’s, runs, and Royston’s tests. Central tendency differences in type II error and statistical power were tested using the Friedman’s test and pairwise comparisons using the Wilcoxon’s test. Differences in the frequency of successes in statistical decision making were compared using the Cochran’s Q test and pairwise comparisons using the McNemar’s test. Sensitivity, specificity and efficiency proportions were compared using the McNemar’s Z test. The generated 50 samples were classified into five ordered categories of deviation from multivariate normality, the correlation between this variable and p-value of each test was calculated using the Spearman’s coefficient and these correlations were compared. Family-wise error rate corrections were applied. The new test and the Royston’s test were the best choices, with a very slight advantage Q-test over Q'-test. Based on these promising results, further study and use of this new sensitive, specific and effective test are suggested.

Power-law Distribution of Normal Fault Displacement and Length and Estimation of Extensional Strain due to Normal Faults:A Case Study of the Sierra de San Miguelito, Mexico

The Sierra de San Miguelito is a relatively uplifted area and is constituted by a large amount of silicic volcanic rocks with ages from middle to late Cenozoic. The normal faults of the Sierra de San Miguelito are Domino-style and nearly parallel. The cumulative length and displacement of the faults obey power-law distribution. The fractal dimension of the fault traces is -1.49. Using the multi-line one-dimensional sampling, the calculated exponent of cumulative fault displacements is -0.66. A cumulative curve combining measurements of all four sections yielded a slope of -0.63. The displacement-length plot shows a non-linear relationship and large dispersion of data. The large dispersion in the plot is mainly due to the fault linkage during faulting. An estimation of extensional strain due to the normal faults is ca. 0.1830. The bed extension strain is always less than or equal to the horizontal extension strain. The deformation in the Sierra de San Miguelito occurred near the surface, producing pervasive faults and many faults are too small to appear in maps and sections at common scales. The stretching produced by small faults reach ca. 33% of the total horizontal elongation.

The Policy of Energy Saving,Pollution Control and Carbon Reduction based on the Cause Analysis of“Power Restriction”Event

In recent years,the“power restriction”measures were taken in many localities,industrial electricity consumption was interrupted,mainly in the“two high”(high energy consumption and high pollutant emission)enterprises.Take the“power restriction”event in 2021 as an example,this event affected a wide range of regions and disrupted people’s livelihood.It not only refers to the power switch and rationing measures taken by individual regions,but also includes differentiated policies implemented by over 20 provinces to limit power supply and industrial production.This paper investigated in detail and summarized the different requirements of power restriction across the country,through the comparison of annual growth rates of power generation and industrial added value,the comparison results of energy intensity,electricity production,power consumption and the industrial growth rate in each province are analyzed.Industrial enterprises and related industrial chains were most heavily affected by the“power restriction”event,mainly in steel,cement,electrolytic aluminum,industrial silicon,textile printing and dyeing,chemical fiber,chemical and other enterprises with high energy consumption and high pollutants emission.The measures to limit electricity will affect the normal production of enterprises to a certain extent,leading to not only the decrease of production efficiency,but also the increase of energy consumption and pollutant emission per unit product.Energy management measures such as differentiated electricity price have limited effect on the output of“two high”industrial products,and the economic leverage of differentiated electricity price is gradually being diluted by the price rise of end products.This paper analyzed the reasons and explored several key problems that need special attention.then recommended certain countermeasures for its appropriate application in the future.

Sustainable Investment Forecasting of Power Grids Based on theDeep Restricted Boltzmann Machine Optimized by the Lion Algorithm

This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine(DRBM)optimized by the Lion algorithm(LA).Firstly,two factors including transmission and distribution price reform(TDPR)and 5G station construction were comprehensively incorporated into the consideration of influencing factors,and the fuzzy threshold method was used to screen out critical influencing factors.Then,the LA was used to optimize the parameters of the DRBM model to improve the model’s prediction accuracy,and the model was trained with the selected influencing factors and investment.Finally,the LA-DRBM model was used to predict the investment of a power grid enterprise,and the final prediction result was obtained by modifying the initial result with the modifying factors.The LA-DRBMmodel compensates for the deficiency of the singlemodel,and greatly improves the investment prediction accuracy of the power grid.In this study,a power grid enterprise was taken as an example to carry out an empirical analysis to prove the validity of the model,and a comparison with the RBM,support vector machine(SVM),back propagation neural network(BPNN),and regression model was conducted to verify the superiority of the model.The conclusion indicates that the proposed model has a strong generalization ability and good robustness,is able to abstract the combination of low-level features into high-level features,and can improve the efficiency of the model’s calculations for investment prediction of power grid enterprises.

Research on Impact Mechanism and Power System of Urbanization in West China

Based on the current situation of urbanization development in West China, this paper analyses main factors responsible for sluggish urbanization in West China as follows: impact of environment factor, impact of population quality and quantity, lagging of public product service, stagnancy of technological development, backwardness of slow growth, and rigidity of system building. And then this paper analyses the restriction mechanism of urbanization in West China: at the superficial level, the constraints of urbanization in West China arise from the shortage of capital; at the profound level, the backward culture contributes to the constraints of urbanization in West China. The thread of resolving restriction mechanism of urbanization in West China is put forward from system, economy and culture. On the basis of this thread, we construct the power system for the development of urbanization in West China. The power system for urbanization in West China should be propelled by "four forces", namely, pull of external forces, cohesive strength of regional market environment, expansion power inside countryside, traction of industrial structure adjustment. Innovation is the engine of impetus for urbanization in West China; spatial clustering and modernization of industry is the major driving force for urbanization; the government behaviour, driving of foreign investment, great projects and other forces are supplementary power. Via the main power, we should take the market as medium to achieve the role of power in promoting urbanization.

European Powers’ Engagement in the Indian Ocean:Features, Motives and Implications

The increasing engagement of European powers in the Indian Ocean has turned the region into a hotspot where strategic coordination and policy differences among major powers are intertwined. While leading to significant changes in the regional landscape, challenges remain that restrict the outcomes and prospects of the engagement. A “soft” strategy is expected to make up for the deficiencies in “hard” input, and India’s strategic position will grow as it looms as the focal point for partnerships with European powers in the region.

Analysis and Practical Significance of Lenin＇s Legal Supervision Theory

In order to ensure that law can be effectively implemented, Lenin started from social reality and construction of regime in Soviet Russia, and systematically analyzed value significance and system construction of legal supervision, based on which he proposed to establish unified legal supervision system to fulfill the functions of legal supervision. The paper starts with theoretical basis and content of Lenin＇ s legal supervision, and expounds the importance of legal supervision in Soviet Russia.

Stability Monitoring and Control of Generation Based on the Synchronized Measurements in Nodes of Its Connection

Synchronized distributed measurements of mode parameters create a technical feasibility for development and implementing new technologies of control the mode stability and the admissibility of EPS （electric power system） mode. Discussion will focus on different models obtained from data synchronized measurements for operational and automatic emergency control without EPS being totally controlled. According to the proposed technology, the generator＇s output power restrictions are determined in real-time by the terms a static stability using the generators＇ mode model as a multipole with connection nodes of generators＇ electromotive forces （the matrix of SMA （self and mutual admittances） of electromotive forces of generators）. Potential applications of the technology are distribution network with the main substation and generators of commensurable capacity, and transmission network with large power plants （generators） distributed into the network. The one-level control system for all of generators with defining the generator＇s power limits relative to the main substation is implemented in the first case. In the second case, the two-level control system is brought in, based on the separation of large and small generation motion. The results of the method and technology efficiency verification are shown in the paper, by both computer simulations of the power system modes and its physical model.

A novel algorithm of adaptive IIR lattice notch filter and performance analysis

A novel adaptive algorithm of IIR lattice notch filter realized by all-pass filter is presented. The time-averaged estimation of cross correlation of the present instantaneous input signal and the past output signal is used to update the step-size, leading to a considerably improved convergence rate in a low SNR situation and reduced steady-state bias and MSE. The theoretical expression for steady-state bounds on the step-size is derived, and the influence factors on the stable performance of the algorithm theoretically are analyzed. A normalized power factor is then introduced to control variation of step-size in its steady-state bounds. This technique prevents divergence due to the influence of large power input signal and improves robustness. Numerical experiments are performed to demonstrate superiority of the proposed method.

Seismic reliability analysis of large electric power systems

Based on the De.Morgan laws and Boolean simplification, a recursive decomposition method is introduced in this paper to identify the main exclusive safe paths and failed paths of a network. The reliability or the reliability bound of a network can be conveniently expressed as the summation of the joint probabilities of these paths. Under the multivariate normal distribution assumption, a conditioned reliability index method is developed to evaluate joint probabilities of various exclusive safe paths and failed paths, and, finally, the seismic reliability or the reliability bound of an electric power system. Examples given in the paper show that the method is very simple and provides accurate results in the seismic reliability analysis.

Determination of Suitable Sites for Establishment of Large-Scale Concentrated Solar Power Plants in Kenya

The demand for energy in Kenya, especially for electricity, is increasing rapidly due to population growth, decentralization of governance, and technological and industrial development. Hydroelectricity, the core source of power, has proved unreliable due to the rapid climate change. In response, the country has ventured into other renewable sources to counter the issues posed by the alternative nonrenewable sources such as unreliability, high costs, and environmental degradation as seen with the use of diesel and kerosene. The purpose of this research is to determine the viability of setting up a large-scale concentrated solar power plantation in Kenya that will assist in stabilizing Kenya’s energy demand and supply as well as increase its affordability. The project is divided into three phases. The first phase conducts an overlay analysis to determine the Kenya’s solar energy potential. The results show that the northern region has the highest potential. The second step involves the creation of an exclusion mask which eliminates the unsuitable land forms and Land Use Land Cover. Based on the results, the best ten sites are situated in Turkana and Marsabit counties. The final phase involves the evaluation of the potential capacity of power that could be generated per square kilometer. The study finds out that the potential varies based on the technologies: parabolic trough, linear Fresnel reflector, or dish systems.

Assessment of Hybrid Concentrated Solar Power-Biomass Plant Generation Potential in Sahel: Case Study of Senegal

Concentrating Solar Power (CSP) is non-existent in Sahel. Such a situation arises from the high investment costs required by these energy infrastructures and from a lack of information on the identification of suitable sites to accommodate them. Conversely, CSP-biomass plants due to lower investment may be an option for CSP penetration in Sahel where Direct Normal Irradiation (DNI) is between 1400 kWh/m2/year and 2000 kWh/m2/year and significant biomass potential. This work presents the results of an identification of suitable sites for hybrid CSP-Biomass in the Sahel, case study of Senegal, taking into account the Direct Normal Irradiation, the availability of water, space and biomass potential. The identified sites have a DNI > 1600 kWh/m2/year. The biogas production capacity is equivalent to 5,096,563 m3/year. The quantity of Typha Australis, invasive plant in Senegal river valley available is estimated at more than 3 million tons. The capacity of electrical energy in this zone is estimated at 6.89 GWe for an installation surface estimated at 275.61 km2. The establishment of CSP/hybrid plants can also contribute to combat the proliferation of Typha Australis.

Robust Low-Power Algorithm for Random Sensing Matrix for Wireless ECG Systems Based on Low Sampling-Rate Approach

The main drawback of current ECG systems is the location-specific nature of the systems due to the use of fixed/wired applications. That is why there is a critical need to improve the current ECG systems to achieve extended patient’s mobility and to cover security handling. With this in mind, Compressed Sensing (CS) procedure and the collaboration of Sensing Matrix Selection (SMS) approach are used to provide a robust ultra-low-power approach for normal and abnormal ECG signals. Our simulation results based on two proposed algorithms illustrate 25% decrease in sampling-rate and a good level of quality for the degree of incoherence between the random measurement and sparsity matrices. The simulation results also confirm that the Binary Toeplitz Matrix (BTM) provides the best compression performance with the highest energy efficiency for random sensing matrix.

Validation of the Monte Carlo Model Designed to Simulate the Neutronic Characteristics of Advanced Boiling Water Reactor Assembly

In the last few years, interest in burnup calculations using Monte Carlo methods has increased. Previous burnup codes have used diffusion theory for the neutronic portion of the codes. Diffusion theory works well for most reactors. However, diffusion theory does not produce accurate results in burnup problems that include strong absorbers or large voids. MCNPX code based on Mont Carlo Method, is used to design a three dimensional model for a BWR fuel assembly in a typical operating temperature and pressure conditions. A test case was compared with a benchmark problem and good agreement was found. The model is used to calculate the distribution of pin by pin power and flux inside the assembly. The effect of axial variation of water （coolant） density, and of control rods motion on the neutron flux and power distribution is analyzed. The effect of addition of Gd2O3 to natural uranium （0.711%） on both the thermal neutron flux and normalized power are analyzed. The concentration of U^235, U^238, Pu^239, and its isotopes is also calculated at burn-up 50 GWD/T.

Solving Load Flow Problems of Power System by Explicit Pseudo-Transient Continuation (E-ψtc) Method

This paper is a further study of two papers [1] and [2], which were related to Ill-Conditioned Load Flow Problems and were published by IEEE Trans. PAS. The authors of this paper have some different opinions, for example, the 11-bus system is not an ill-conditioned system. In addition, a new approach to solve Load Flow Problems, E-ψtc, is introduced. It is an explicit method;solving linear equations is not needed. It can handle very tough and very large systems. The advantage of this method has been fully proved by two examples. The authors give this new method a detailed description of how to use it to solve Load Flow Problems and successfully apply it to the 43-bus and the 11-bus systems. The authors also propose a strategy to test the reliability, and by solving gradient equations, this new method can answer if the solution exists or not.

An Efficient Approach for Segmentation, Feature Extraction and Classification of Audio Signals

Due to the presence of non-stationarities and discontinuities in the audio signal, segmentation and classification of audio signal is a really challenging task. Automatic music classification and annotation is still considered as a challenging task due to the difficulty of extracting and selecting the optimal audio features. Hence, this paper proposes an efficient approach for segmentation, feature extraction and classification of audio signals. Enhanced Mel Frequency Cepstral Coefficient (EMFCC)-Enhanced Power Normalized Cepstral Coefficients (EPNCC) based feature extraction is applied for the extraction of features from the audio signal. Then, multi-level classification is done to classify the audio signal as a musical or non-musical signal. The proposed approach achieves better performance in terms of precision, Normalized Mutual Information (NMI), F-score and entropy. The PNN classifier shows high False Rejection Rate (FRR), False Acceptance Rate (FAR), Genuine Acceptance rate (GAR), sensitivity, specificity and accuracy with respect to the number of classes.

纪检监察学科话语体系的百年构建:历史演进与原创贡献

构建中国特色纪检监察学科话语体系是中国共产党矢志不渝的奋斗目标。在革命、建设和改革开放实践中,中国共产党根据执政历史方位、肩负主要任务和面临突出问题的变化,坚持把马克思主义政党学说与中华优秀传统监察文化结合起来,以纪检监察理论创新推动制度创新和实践创新,构建了纪检监察学科话语体系的“四梁八柱”,奠定了纪检监察学科发展的坚实基础。中国共产党纪检监察话语体系的百年构建作出了原创性贡献,这就是开辟了纪检监察学科话语构建的中国道路,积累了纪检监察学科话语体系构建的中国经验,形成了纪检和监察合署办公的中国方案,赢得了与资产阶级政党理论竞争的中国优势。

高压管汇材料疲劳性能测试及P-S-N模型曲线的拟合

高压管汇作为压裂设备中的主要易损件之一,其失效危害较大。它的失效原因主要是疲劳、冲蚀、腐蚀或者材料缺陷引起的刺漏和爆裂,其中尤以疲劳失效最不可预估。目前,对于高压管汇材料的疲劳性能研究不够深入,为解决高压管汇材料疲劳寿命的准确描述问题,以某国产高压管汇材料为例,进行了一系列疲劳试验,并基于试验数据,采用多种分布模型和不同S-N模型进行拟合分析,得出综合评价拟合能力最强的P-S-N模型。结果表明,该材料在中长疲劳寿命区,Weibull三参数模型在7级应力水平下综合评价能力最好;在存活率分别为50%、90%、99%、99.9%时,指数S-N模型的拟合系数均大于0.98,拟合能力最好。得出的P-S-N模型曲线可以为高压管汇的疲劳寿命以及安全设计提供依据。

二项分布双边收尾概率和假设检验统计量的几处修正

二项分布是广泛存在的一种离散型概率分布。服从二项分布B(n,p)的一个随机变量等于n个相互独立且服从贝努利分布B(1,p)的随机变量之和,二项分布包含参数p的估计与检验等同于贝努利分布参数p的估计与检验。本文修正常见教科书中有关二项分布双边收尾概率计算和假设检验统计量构建中存在的3处问题。(1)对二项分布B(n,p)的取值概率pk(k=0,1,…,n)从小到大排序,排序后的概率用p_((k))表示,观测值k的双边收尾精确概率等于■;(2)二项分布B(n,p)参数p与给定值p0的差异显著性检验统计量被修正为■,该统计量在大样本条件下近似服从正态分布N(p–p0,1);(3)二项分布B(n1,p1)和B(n2,p2)的参数p1和p2差异显著性检验统计量被修正为■,该统计量在大样本条件下近似服从正态分布N(p1–p2,1)。修正后的双边收尾概率是精确值,不会出现概率大于1的问题。修正后的2个检验统计量无论原假设是否成立,其大样本近似正态分布的方差均为1,有利于准确研究备择假设条件下检验统计量的功效。此外,文中还介绍了小样本条件下二项分布参数的精确检验,对比分析了准确检验与近似检验的异同;讨论了修正统计量的理论基础,给出了小概率和大样本的判定标准,列出了贝努利分布参数检验与正态分布均值检验的异同。期望读者能够从中了解到假设检验与统计推断作为统计学核心研究内容的全貌。