Distributivity for a monad and a comonad

We give a systematic treatment of distributivity for a monad and a comonad as arises in incorporating category theoretic accounts of operational and denotational semantics, and in giving an intensional denotational semantics. We do this axiomatically, in terms of a monad and a comonad in a 2-category, giving accounts of the Eilenberg-Moore and Kleisli constructions. We analyse the eight possible relationships, deducing that two pairs are isomorphic, but that the other pairs are all distinct. We develop those 2-categorical definitions necessary to support this analysis.     

On the construction of free algebras for equational systems

The purpose of this paper is threefold: to present a general abstract, yet practical, notion of equational system; to investigate and develop the finitary and transfinite construction of free algebras for equational systems; and to illustrate the use of equational systems as needed in modern applications.     

Infinite trees and completely iterative theories: a coalgebraic view

Infinite trees form a free completely iterative theory over any given signature—this fact, proved by Elgot, Bloom and Tindell, turns out to be a special case of a much more general categorical result exhibited in the present paper. We prove that whenever an endofunctor H of a category has final coalgebras for all functors H( _ )+X, then those coalgebras, TX, form a monad. This monad is completely iterative, i.e., every guarded system of recursive equations has a unique solution. And it is a free completely iterative monad on H. The special case of polynomial endofunctors of the category is the above mentioned theory, or monad, of infinite trees.

This procedure can be generalized to monoidal categories satisfying a mild side condition: if, for an object H, the endofunctor H_+I has a final coalgebra, T, then T is a monoid. This specializes to the above case for the monoidal category of all endofunctors.     

Erratum and Addendum: Eilenberg-Moore algebras for stochastic relations

In Information and Computation 204 (2006), 1756–1781, the structure of Eilenberg-Moore algebras for the Giry monad for subprobabilities on Polish spaces is investigated in some detail by the present author. This note corrects a gap in one of the proofs. Additionally, it adapts the general results for the discrete Giry monad.     

Combining linguistic resources to create a machine-tractable Japanese-Malay dictionary

We present a method for combining two bilingual dictionaries to make a third, using one language as a pivot. In this case we combine a Japanese-English dictionary with a Malay-English dictionary, to produce a Japanese-Malay dictionary. Our method differs from previous methods in its improved matching through normalization of the pivot language. We have made a prototype dictionary of around 76,000 Japanese-Malay pairs for 50,000 Japanese head words.     

基于分布理论和遗传算法的多项式求根算法

本文提出了一种基于根分布理论和遗传算法的求复系数多项式全部根的算法。     

结合二维Logistic映射与二维离散余弦变换的数字图像隐藏技术

为了应对日益增大的图像安全问题, 提出一种结合二维Logistic映射与二维离散余弦变换(2D-DCT)的数字图像隐藏算法. 首先, 利用二维Logistic映射产生的混沌序列对秘密图像进行像素扩散与置乱, 从而达到对秘密图像的加密效果. 接着, 分块对载体图像进行二维离散余弦变换, 然后把扩散与置乱后的图像信息分存在变换后每块的右下角. 最后再进行二维离散余弦反变换(2D-IDCT), 并得到隐密图像. 实验结果也表明, 该算法安全可行且隐藏效果良好.     

瑞利衰落信道中最大比合并系统性能及多路信号合并算法研究

分集是数字通信中最有效的抗多径衰落技术,在无线通信中采用分集技术可以改善系统的差错性能。本文详细分析了空间分集中性能最佳的最大比合并方式(MRC)的差错性能,并通过计算机仿真,给出了误码曲线。最后本文还给出了一种可行的最大分集合并的具体算法和仿真结果。     

自适应窗隔匹配与深度学习相结合的RGB-D SLAM算法

在动态场景的SLAM系统中,传统的特征点法视觉SLAM系统易受动态物体的影响,使得图像前后两帧的动态物体区域出现大量的误匹配,导致机器人定位精度不高.为此,提出一种结合自适应窗隔匹配模型与深度学习算法的动态场景RGB-D SLAM算法.构建基于自适应窗隔匹配模型的视觉SLAM前端算法框架,该框架筛选图像帧后采用基于网格...     

结合LDA与Self-Attention的短文本情感分类方法

在对短文本进行情感分类任务的过程中,由于文本长度过短导致数据稀疏,降低了分类任务的准确率。针对这个问题,提出了一种基于潜在狄利克雷分布（LDA）与Self-Attention的短文本情感分类方法。使用LDA获得每个评论的主题词分布作为该条评论信息的扩展,将扩展信息和原评论文本一起输入到word2vec模型,进行词向量训练,使得该评论文本在高维向量空间实现同一主题的聚类,使用Self-Attention进行动态权重分配并进行分类。通过在谭松波酒店评论数据集上的实验表明,该算法与当前主流的短文本分类情感算法相比,有效地提高了分类性能。     

一种结合二维熵和模糊熵的图像分割方法

基于二维熵的分割方法是一种常用的阈值分割技术,其基本假设是对象区域和背景区域占据了二维直方图的绝大部分区域,即假设对象区域和背景区域的概率和近似为1。该方法存在的不足是忽略了边界区域的信息对分割结果的影响,鉴于此,提出了一种结合二维熵和模糊熵的图像分割方法,先采用二维熵对图像进行初步分割,再采用模糊熵作后续处理以弥补忽略边界信息带来的问题。实验结果表明,对于含噪图像,该文方法的分割效果是比较理想的。     

结合LDA与Word2vec的文本语义增强方法

文本的语义表示是自然语言处理和机器学习领域的研究难点,针对目前文本表示中的语义缺失问题,基于LDA主题模型和Word2vec模型,提出一种新的文本语义增强方法Sem2vec（semantic to vector）模型。该模型利用LDA主题模型获得单词的主题分布,计算单词与其上下文词的主题相似度,作为主题语义信息融入到词向量中,代替one-hot向量输入至Sem2vec模型,在最大化对数似然目标函数约束下,训练Sem2vec模型的最优参数,最终输出增强的语义词向量表示,并进一步得到文本的语义增强表示。在不同数据集上的实验结果表明,相比其他经典模型,Sem2vec模型的语义词向量之间的语义相似度计算更为准确。另外,根据Sem2vec模型得到的文本语义向量,在多种文本分类算法上的分类结果,较其他经典模型可以提升0.58%~3.5%,同时也提升了时间性能。     

一种像素与对象相结合的林区建筑物识别方法

针对林区建筑物遥感监测技术需求,为构建GF-2数据在林区建筑物识别中的应用方法,选取蜀南竹海风景名胜区为研究区,根据所选区域建筑物的GF-2影像特征,研究形成了像素级和对象级相结合的林区建筑物识别方法.首先利用基于递归特征消除法的随机森林算法对预处理后的GF-2影像进行特征筛选;然后通过对比支持向量机和随机森林分类器识...     

结合l1/2范数与显著性约束的背景减除

传统背景减除模型在背景静止和前景对象移动较快时提取到的前景效果较好,但当背景变化或前景对象移动缓慢时容易将动态背景误判为前景或检测出的前景有较多空洞。针对传统背景减除模型在动态背景和前景对象移动缓慢条件下存在前景检测精度下降的问题,提出一种基于l_1/2范数与显著性约束的背景减除模型。将观测数据分为低秩背景、运动前景和动态干扰3类,利用l_1/2范数约束运动前景加强前景稀疏性,有效抑制动态背景对前景提取造成的干扰,提高运动前景在动态背景中的检测精度。引入视频每一帧的显著性约束,通过对每一帧图像进行低秩稀疏分解来检测移动缓慢的目标。实验结果表明,该模型对于复杂场景具有较强的适应能力,可有效去除动态背景对前景的干扰,快速检测出移动缓慢的前景对象,相比于l_1/1/2-RPCA背景减除模型的平均查全率、查准率和调和平均值分别提升了9、14和10个百分点。     

Combining weak and strong mutation for a noninterpretive Java mutation system

Because of the computationally expensive cost of mutation testing, automated system support is indispensable for conducting mutation testing. Mutation systems can be classified into interpretive and noninterpretive, but recent systems are noninterpretive. Weak mutation is a well‐known cost reduction method of mutation testing, but it is not directly applicable to noninterpretive mutation systems. To address the problem and take advantage of the efficiency of weak mutation, this paper presents a combined weak and strong mutation for noninterpretive Java mutation systems. The new term ‘serialmutant’ is defined as a specialized program to conduct weak mutation against all mutants in an execution and report only weakly killed mutants as strong mutation candidates. Then strong mutation is conducted only for those reported mutants. The paper also describes an implementation based on a previous Java mutation tool, MuJava. Method‐level mutation operators for Java are also redesigned. Experimental results show that the proposed approach efficiently improves the mutation cost in a noninterpretive mutation system. Copyright © 2012 John Wiley & Sons, Ltd.     

基于深度学习和迁移学习的领域自适应中文分词

为了提高专业领域中文分词性能,以及弥补专业领域大规模标注语料难以获取的不足,该文提出基于深度学习以及迁移学习的领域自适应分词方法。首先,构建包含词典特征的基于深度学习的双向长短期记忆条件随机场(BI-LSTM-CRF)分词模型,在通用领域分词语料上训练得到模型参数;接着,以建设工程法律领域文本作为小规模分词训练语料,对通用领域语料的BI-LSTM-CRF分词模型进行参数微调,同时在模型的词典特征中加入领域词典。实验结果表明,迁移学习减少领域分词模型的迭代次数,同时,与通用领域的BI-LSTM-CRF模型相比,该文提出的分词方法在工程法律领域的分词结果F1值提高了7.02%,与预测时加入领域词典的BI-LSTM-CRF模型相比,分词结果的F1值提高了4.22%。该文提出的分词模型可以减少分词的领域训练语料的标注,同时实现分词模型跨领域的迁移。     

Robust and Accurate Monocular Visual Navigation Combining IMU for a Quadrotor

In this paper, we present a multi-sensor fusion based monocular visual navigation system for a quadrotor with limited payload, power and computational resources. Our system is equipped with an inertial measurement unit (IMU), a sonar and a monocular down-looking camera. It is able to work well in GPS-denied and markerless environments. Different from most of the keyframe-based visual navigation systems, our system uses the information from both keyframes and keypoints in each frame. The GPU-based speeded up robust feature (SURF) is employed for feature detection and feature matching. Based on the flight characteristics of quadrotor, we propose a refined preliminary motion estimation algorithm combining IMU data. A multi-level judgment rule is then presented which is beneficial to hovering conditions and reduces the error accumulation effectively. By using the sonar sensor, the metric scale estimation problem has been solved. We also present the novel IMU+3P (IMU with three point correspondences) algorithm for accurate pose estimation. This algorithm transforms the 6-DOF pose estimation problem into a 4-DOF problem and can obtain more accurate results with less computation time. We perform the experiments of monocular visual navigation system in real indoor and outdoor environments. The results demonstrate that the monocular visual navigation system performing in real-time has robust and accurate navigation results of the quadrotor.      

K波段线性功率合成放大器的设计与研究

毫米波放大器的设计已经越来越倾向于以具有体积小、重量轻、直流功耗低等优点的固态器件通过功率合成技术来实现。在成熟的波导T型合成结构基础上加以改进,实现了该放大器的合成效率高、尺寸小、易于散热、易于模块化等优点,再配合新研制出的一种具有幅度／相位特性补偿的预失真结构加以辅助,最终达到了在K波段高线性的功率输出。     

Combining expert knowledge and data mining in a medical diagnosis domain

The medical diagnosis system described here uses underlying knowledge in the isokinetic domain, obtained by combining the expertise of a physician specialised in isokinetic techniques and data mining techniques applied to a set of existing data. An isokinetic machine is basically a physical support on which patients exercise one of their joints, in this case the knee, according to different ranges of movement and at a constant speed. The data on muscle strength supplied by the machine are processed by an expert system that has built-in knowledge elicited from an expert in isokinetics. It cleans and pre-processes the data and conducts an intelligent analysis of the parameters and morphology of the isokinetic curves. Data mining methods based on the discovery of sequential patterns in time series and the fast Fourier transform, which identifies similarities and differences among exercises, were applied to the processed information to characterise injuries and discover reference patterns specific to populations. The results obtained were applied in two environments: one for the blind and another for elite athletes.     

基于J2EE，CORBA和WBM的综合网络管理系统

研究了综合网络管理系统的一种新的开发方法,并结合应用开发实例来进行分析。这一方法,主要采用J2EE和CORBA以及WBM相结合的技术,在综合网络管理和其他的企业应用中,都有着广泛的应用前景。重点介绍了采用J2EE的多层应用体系结构,同时使用CORBA构建底层应用,使用WBM技术构建上层应用,来开发综合网络管理系统的方法。通过J2EE和CORBA、WBM技术结合的典型开发模式的实例分析,说明了这种开发方法应用于综合网络管理系统的可行性和优越性。