Entropy-Based Greedy Algorithm for Decision Trees Using Hypotheses

In this paper, we consider decision trees that use both conventional queries based on one attribute each and queries based on hypotheses of values of all attributes. Such decision trees are similar to those studied in exact learning, where membership and equivalence queries are allowed. We present greedy algorithm based on entropy for the construction of the above decision trees and discuss the results of computer experiments on various data sets and randomly generated Boolean functions.     

基于精密测角法的测绘相机分组渐进标定算法

针对精密测角法标定测绘相机内方位元素中理论误差和观测点分布状态对标定精度影响的问题,提出了一种基于精密测角法的分组渐进标定算法。提出的算法包括2个部分：采用分组渐近方式调整精密转台零点位置,减小了理论误差;对每组观测数据引入了数据一致性约束,消除观测值分布、数量对标定结果的影响。最后,给出了分组渐进算法的精度分析。实验数据显示,在相同试验环境条件下,分组渐进标定算法中主点、主距标定精度比精密测角算法分别提高了2.43倍和2.00倍,可达到2.12 μm和4.02 μm,表明分组渐进标定算法提高了标定精度。     

Exact Solutions of Supersymmetric KdV-a System via Bosonization Approach

Bosonization approach is applied in solving the most general N=1 supersymmetric Korteweg de-Vries equation with an arbitrary parameter a (sKdV-a) equation. By introducing some fermionic parameters in the expansion of the superfield, the sKdV-a equation is transformed to a new coupled bosonic system. The Lie point symmetries of this model are considered and similarity reductions of it are conducted. Several types of similarity reduction solutions of the coupled bosonic equations are simply obtained for all values of a. Some kinds of exact solutions of the sKdV-a equation are discussed which was not considered integrable previously.     

The Cuts Selection Method Based on Histogram Segmentation and Impact on Discretization Algorithms

The preprocessing of data is an important task in rough set theory as well as in Entropy. The discretization of data as part of the preprocessing of data is a very influential process. Is there a connection between the segmentation of the data histogram and data discretization? The authors propose a novel data segmentation technique based on a histogram with regard to the quality of a data discretization. The significance of a cut’s position has been researched on several groups of histograms. A data set reduct was observed with respect to the histogram type. Connections between the data histograms and cuts, reduct and the classification rules have been researched. The result is that the reduct attributes have a more irregular histogram than attributes out of the reduct. The following discretization algorithms were used: the entropy algorithm and the Maximal Discernibility algorithm developed in rough set theory. This article presents the Cuts Selection Method based on histogram segmentation, reduct of data and MD algorithm of discretization. An application on the selected database shows that the benefits of a selection of cuts relies on histogram segmentation. The results of the classification were compared with the results of the Naïve Bayes algorithm.     

不同插值算法在波前构建射线追踪中的应用与对比

针对波前构建法射线追踪中遇到的波前非网格节点处速度及速度导数的插值问题,对比分析目前在数字地形、数字导航中常用的几种插值算法(邻近域、双线性、分片线性、二维三次卷积)的插值误差.并结合波前构建法的特征,针对不同的插值算法,采取合理的程序设计思想,对同一模型应用不同的插值算法进行射线路径和计算效率的对比.通过对比分析可以得出,在波前构建法射线追踪中应用二维三次卷积插值,不但提高了射线路径的准确度,而且提高了射线追踪的效率,为下一步做偏移成像提供了精确的数据.     

Exact Travelling Solutions of Discrete sine-Gordon Equation via Extended Tanh-Function Approach

In this paper, we generalize the extended tanh-function approach, which was used to find new exact travelling wave solutions of nonlinear partial differential equations or coupled nonlinear partial differential equations, to nonlinear differential-difference equations. As illustration, two series of exact travelling wave solutions of the discrete sine-Gordon equation are obtained by means of the extended tanh-function approach.     

Exact Solutions of the Coupled KdV system via a Formally Variable Separation Approach

Most of the nonlinear physics systems are essentially nonintegrable.There in no very doog analytical approach to solve nonintegrable system.The variable separation approach is a powerful method in linear physics.In this letter,the formal variable separation approach is established to solve the generalized nonlinear mathematical physics equation.The method is valid not only for integrable models but also for nonintegrable models.Taking a nonintegrable coupled KdV equation system as a simple example,abundant solitary wave solutions and conoid wave solutions are revealed.     

Explicit and Exact Solutions to N-Order Schrödinger System via an Extended Mapping Approach

In this paper, we extend the mapping approach to the N-order Schrödinger equation. In terms of the extended mapping approach, new families of variable separation solutions with some arbitrary functions are derived.     

Exact Solution to (1+1)-Dimensional Higher-Order Schrödinger Equation via an Extended Mapping Approach

Starting from a special variable transformation and with the help of an extended mapping approach, the high-order Schrödinger equation (n=3,4) is solved. A new family of variable separation solutions with arbitrary functions is derived.     

Evaluation of Fast Sample Entropy Algorithms on FPGAs: From Performance to Energy Efficiency

Entropy is one of the most fundamental notions for understanding complexity. Among all the methods to calculate the entropy, sample entropy (SampEn) is a practical and common method to estimate time-series complexity. Unfortunately, SampEn is a time-consuming method growing in quadratic times with the number of elements, which makes this method unviable when processing large data series. In this work, we evaluate hardware SampEn architectures to offload computation weight, using improved SampEn algorithms and exploiting reconfigurable technologies, such as field-programmable gate arrays (FPGAs), a reconfigurable technology well-known for its high performance and power efficiency. In addition to the fundamental disclosed straightforward SampEn (SF) calculation method, this study evaluates optimized strategies, such as bucket-assist (BA) SampEn and lightweight SampEn based on BubbleSort (BS-LW) and MergeSort (MS-LW) on an embedded CPU, a high-performance CPU and on an FPGA using simulated data and real-world electrocardiograms (ECG) as input data. Irregular storage space and memory access of enhanced algorithms is also studied and estimated in this work. These fast SampEn algorithms are evaluated and profiled using metrics such as execution time, resource use, power and energy consumption based on input data length. Finally, although the implementation of fast SampEn is not significantly faster than versions running on a high-performance CPU, FPGA implementations consume one or two orders of magnitude less energy than a high-performance CPU.     

Forced Time-Dependent Harmonic Oscillator in a Static Magnetic Field: Exact Quantum and Classical Solutions

Exact wave functions of the forced time-dependent two-dimensional harmonic oscillator in a static magnetic field are derived by unitary transformation. The geometrical phase induced by the driving force is the phase of the de Broglie wave associated with the particle moving according to the classical equation. Extending the idea of the Heisenberg correspondence principle to the time-dependent system, the exact classical solution obtained from quantum matrix elements.     

Influence Cascades: Entropy-Based Characterization of Behavioral Influence Patterns in Social Media

Influence cascades are typically analyzed using a single metric approach, i.e., all influence is measured using one number. However, social influence is not monolithic; different users exercise different influences in different ways, and influence is correlated with the user and content-specific attributes. One such attribute could be whether the action is an initiation of a new post, a contribution to a post, or a sharing of an existing post. In this paper, we present a novel method for tracking these influence relationships over time, which we call influence cascades, and present a visualization technique to better understand these cascades. We investigate these influence patterns within and across online social media platforms using empirical data and comparing to a scale-free network as a null model. Our results show that characteristics of influence cascades and patterns of influence are, in fact, affected by the platform and the community of the users.     

An Entropy-Based Architecture for Detection of Sepsis in Newborn Cry Diagnostic Systems

The acoustic characteristics of cries are an exhibition of an infant’s health condition and these characteristics have been acknowledged as indicators for various pathologies. This study focused on the detection of infants suffering from sepsis by developing a simplified design using acoustic features and conventional classifiers. The features for the proposed framework were Mel-frequency Cepstral Coefficients (MFCC), Spectral Entropy Cepstral Coefficients (SENCC) and Spectral Centroid Cepstral Coefficients (SCCC), which were classified through K-nearest Neighborhood (KNN) and Support Vector Machine (SVM) classification methods. The performance of the different combinations of the feature sets was also evaluated based on several measures such as accuracy, F1-score and Matthews Correlation Coefficient (MCC). Bayesian Hyperparameter Optimization (BHPO) was employed to tailor the classifiers uniquely to fit each experiment. The proposed methodology was tested on two datasets of expiratory cries (EXP) and voiced inspiratory cries (INSV). The highest accuracy and F-score were 89.99% and 89.70%, respectively. This framework also implemented a novel feature selection method based on Fuzzy Entropy (FE) as a final experiment. By employing FE, the number of features was reduced by more than 40%, whereas the evaluation measures were not hindered for the EXP dataset and were even enhanced for the INSV dataset. Therefore, it was deduced through these experiments that an entropy-based framework is successful for identifying sepsis in neonates and has the advantage of achieving high performance with conventional machine learning (ML) approaches, which makes it a reliable means for the early diagnosis of sepsis in deprived areas of the world.     

New Family of Exact Solutions and Chaotic Soltions of Generalized Breor-Kaup System in （2＋1）-Dimensions via an Extended Mapping Approach

Starting from an extended mapping approach, a new type of variable separation solution with arbitrary functions of generalized （2＋1）-dimensional Broer-Kaup system （GBK） system is derived. Then based on the derived solitary wave solution, we obtain some specific chaotic solitons to the （2＋1）-dimensional GBK system.     

New Family of Exact Solutions and Chaotic Soltions of Generalized Breor-Kaup System in (2+1)-Dimensions via an Extended Mapping Approach

Starting from an extended mapping approach, a new type of variable separation solution with arbitrary functions of generalized (2 1)-dimensional Broer-Kaup system (GBK) system is derived. Then based on the derived solitary wave solution, we obtain some specific chaotic solitons to the (2 1)-dimensional GBK system.     

电网智能单元加密算法效率评估

随着智能电网发展和电力终端设备智能化和网络化的提升,基于TCP/IP协议的数据通信面临着传统的网络安全隐患;智能电网单元是电网控制的关键组成部分,负责电网业务数据的采集处理、控制指令的收发和执行等工作,涉及大量数据传输,如何保证数据的机密性,是电网系统正常运作的关键因素之一;针对智能单元的传输规约和传输数据的特点,通过模拟智能单元计算环境,在保密性需求的基础上,结合智能单元计算资源的实际情况,综合分析电力行业和国内常见密码算法,包括对称算法和非对称算法,从运算时间及稳定性,数据长度相关性,密钥长度相关性和加密模式几个方面对算法的性能进行综合性评估;为不同智能单元的机密性保护尤其是加密算法的选取提供理论基础和实验数据。     

A New Rational Algebraic Approach to Find Exact Analytical Solutions to a （2＋1）-Dimensional System

In this paper, we present a new rational algebraic approach to uniformly construct a series of exact analytical solutions for nonlinear partial differential equations. Compared with most existing tanh methods and other sophisticated methods, the proposed method not only recovers some known solutions, but also finds some new and general solutions. The solutions obtained in this paper include rational form triangular periodic wave solutions, solitary wave solutions, and elliptic doubly periodic wave solutions. The efficiency of the method can be demonstrated on （2＋1）-dimensional dispersive long-wave equation.     

Exact self-similar solitary waves and collisions in nonlinear optical media

This paper analyses bright and dark spatial self-similar waves propagation and collision in graded-index nonlinear waveguide amplifiers with self-focusing and self-defocusing Kerr nonlinearities. It finds an appropriate transformation for the first time such that the nonlinear Schrodinger equation （NLSE） with varying coefficients transform into standard NLSE. It obtains one-solitonlike, two-solitonlike and multi-solitonlike self-similar wave solutions by using the transformation. Furthermore, it analyses the features of the self-similar waves and their collisions.     

智能优化算法应用于近红外光谱波长选择的比较研究

近红外光谱(NIRS)是一种间接分析技术,其应用需建立相应的校正模型。为了提高模型的解释能力、预测准确度和建模效率,需要对NIRS进行波长选择,优选最小化冗余信息。智能优化算法是以生物的行为方式或物质的运动形态为背景,经过数学抽象建立算法模型,通过迭代计算来求解组合最优化问题,其核心策略是以某种目标函数为标准,基于多元校正建模并以逐步逼近的方法筛选出有效的波长点。选用蚁群优化(ACO)、遗传优化(GA)、粒子群优化(PSO)、随机青蛙(RF)和模拟退火(SA)5种智能优化算法对烟叶总氮和烟碱近红外光谱数据进行特征波长选择,结合偏最小二乘(PLS)算法,构建了多个烟叶总氮和烟碱的校正模型,结果显示：所选用两个数据集的总氮最优模型分别为PSO-PLS和GA-PLS模型,烟碱最优模型分别为GA-PLS和SA-PLS模型,五种智能优化算法所建模型预测性能并非全部优于全谱PLS模型,但是通过智能优化算法进行波长选择后建立的PLS模型大大简化,模型的预测精度、可解释性和稳定性均有所提高。同时也对优选波长进行了解释和分析,烟叶总氮特征波长优选组合为4 587~4 878和6 700~7 200 cm-1;烟叶烟碱特征波长优选组合为4 500~4 700和5 800~6 000 cm-1,优选出来的特征波长具有实际物理意义。     

Multivariable Heuristic Approach to Intrusion Detection in Network Environments

The Internet is an inseparable part of our contemporary lives. This means that protection against threats and attacks is crucial for major companies and for individual users. There is a demand for the ongoing development of methods for ensuring security in cyberspace. A crucial cybersecurity solution is intrusion detection systems, which detect attacks in network environments and responds appropriately. This article presents a new multivariable heuristic intrusion detection algorithm based on different types of flags and values of entropy. The data is shared by organisations to help increase the effectiveness of intrusion detection. The authors also propose default values for parameters of a heuristic algorithm and values regarding detection thresholds. This solution has been implemented in a well-known, open-source system and verified with a series of tests. Additionally, the authors investigated how updating the variables affects the intrusion detection process. The results confirmed the effectiveness of the proposed approach and heuristic algorithm.