A collaborative filtering framework based on both local user similarity and global user similarity

Collaborative filtering as a classical method of information retrieval has been widely used in helping people to deal with information overload. In this paper, we introduce the concept of local user similarity and global user similarity, based on surprisal-based vector similarity and the application of the concept of maximin distance in graph theory. Surprisal-based vector similarity expresses the relationship between any two users based on the quantities of information (called surprisal) contained in their ratings. Global user similarity defines two users being similar if they can be connected through their locally similar neighbors. Based on both of Local User Similarity and Global User Similarity, we develop a collaborative filtering framework called LS&GS. An empirical study using the MovieLens dataset shows that our proposed framework outperforms other state-of-the-art collaborative filtering algorithms.     

一种面向数据结构的策略翻译技术

策略翻译是目前策略管理研究的难点之一.针对以数据结构表示的策略,提出策略结构五元组概念,增设可扩展的词库,采用XML语言统一描述策略结构,设计通用的脚本分析模块,支持不同设备类型的策略结构,实现透明的策略翻译,提高了策略管理的伸缩性、统一性和透明性.     

Ajax技术在教学论坛制作中的应用

当用户访问传统的ASP技术制作的论坛,并进行多种操作时,会多次重载页面或在不同页面间跳转。造成用户视觉上的不舒服以及花费较多的等待时间。采用Ajax技术可以很好的解决这样的问题,本文给出了用Ajax技术实现教学论坛部分功能的设计方法,使访问者获得更好的Web体验。     

Notes数据库与非结构数据库实时同步的解决方案

随着现代信息技术、通信技术和计算机技术的高速发展,非结构数据库应用的范围、深度、规模也在不断扩大,数据同步问题不再局限于关系数据库之间,关系型数据库与非结构数据库之间的数据同步需求日益增多。文中介绍了实现Notes数据库与关系数据库同步的三种方法,及其优缺点。     

幽门螺杆菌TNF-α诱导蛋白的生物信息学分析

肿瘤坏死因子诱导蛋白Tipα是幽门螺杆菌特有的一个膜相关蛋白.它可以激活核因子κB,并诱导多种细胞因子和趋化因子的表达,导致胃炎和随后的肿瘤发生.它是幽门螺杆菌和胃癌发生之间的关键分子.本文利用生物信息学工具分析Tipα序列,预测其信号肽、跨膜区、疏水性、二级结构、三级结构等性质.结果:Tipα具有一段信号肽、脂蛋白信号肽酶切位点及脂盒模体.另外该蛋白没有跨膜区,可能是一个外周膜蛋白.Tipα的三级结构说明,该蛋白形成了一个致密的球状结构,Tipα的二级结构以α螺旋为主.     

基于UML的医院门诊管理信息系统

UML是一种重要的面向对象软件开发方法,本文简述用UML进行系统建模的方法和步骤。以医院门诊管理信息系统为例,讲述如何利用UML对其进行需求分析、系统设计、实现及测试的具体过程。     

生物视觉系统的神经网络编码模型综述

生物视觉系统的研究一直是计算机视觉算法的重要灵感来源。有许多计算机视觉算法与生物视觉研究具有不同程度的对应关系,包括从纯粹的功能启发到用于解释生物观察的物理模型的方法。从视觉神经科学向计算机视觉界传达的经典观点是视觉皮层分层层次处理的结构。而人工神经网络设计的灵感来源正是视觉系统中的分层结构设计。深度神经网络在计算机视觉和机器学习等领域都占据主导地位。许多神经科学领域的学者也开始将深度神经网络应用在生物视觉系统的计算建模中。深度神经网络多层的结构设计加上误差的反向传播训练,使得它可以拟合绝大多数函数。因此,深度神经网络在学习视觉刺激与神经元响应的映射关系并取得目前性能最好的模型同时,网络内部的单元甚至学习出生物视觉系统子单元的表达。本文将从视网膜等初级视觉皮层和高级视觉皮层(如,视觉皮层第4区(visual area 4,V4)和下颞叶皮层(inferior temporal,IT))分别介绍基于神经网络的视觉系统编码模型。主要内容包括:1)有关视觉系统模型的概念与定义;2)初级视觉系统的神经网络预测模型;3)任务驱动的高级视觉皮层编码模型。最后本文还将介绍最新有关无监督学习的神经编码...     

Evolutionary state-based novel multi-objective periodic bacterial foraging optimization algorithm for data clustering

Clustering divides objects into groups based on similarity. However, traditional clustering approaches are plagued by their difficulty in dealing with data with complex structure and high dimensionality, as well as their inability in solving multi-objective data clustering problems. To address these issues, an evolutionary state-based novel multi-objective periodic bacterial foraging optimization algorithm (ES-NMPBFO) is proposed in this article. The algorithm is designed to alleviate the high-computing complexity of the standard bacterial foraging optimization (BFO) algorithm by introducing periodic BFO. Moreover, two learning strategies, global best individual (gbest) and personal historical best individual (pbest), are used in the chemotaxis operation to enhance the convergence speed and guide the bacteria to the optimum position. Two elimination-dispersal operations are also proposed to prevent falling into local optima and improve the diversity of solutions. The proposed algorithm is compared with five other algorithms on six validity indexes in two data clustering cases comprising nine general benchmark datasets and four credit risk assessment datasets. The experimental results suggest that the proposed algorithm significantly outperforms the competing approaches. To further examine the effectiveness of the proposed strategies, two variants of ES-NMPBFO were designed, and all three forms of ES-NMPBFO were tested. The experimental results show that all of the proposed strategies are conducive to the improvement of solution quality, diversity and convergence.     

微波辅助萃取-超高效液相色谱/静电场轨道阱高分辨质谱法快速测定纺织品中有害有机溶剂残留量

建立了1个快速测定纺织品中有害有机溶剂残留量的超高效液相色谱/静电场轨道阱高分辨质谱(UPLC/Orbitrap HRMS)方法,该方法以乙醇为萃取溶剂,100℃下微波萃取纺织品中残留的有害有机溶剂,萃取液直接进行UPLC/Orbitrap HRMS,提取离子色谱峰面积外标法定量。对样品的提取条件、分析条件进行了优化。该方法的定量限为0.5μg/kg~10.0μg/kg。在3个不同加标浓度水平下,方法的平均加标回收率为81.8~94.5%,相对偏差偏差为3.8%~10.5%(n=9)。该方法简便快速,灵敏度高,定量限低,可有效地解决纺织品中残留的有害有机溶剂的快速测定问题。     

Monolithically integrated CoP nanowire array: An on/off switch for effective on-demand hydrogen generation via hydrolysis of NaBH<Subscript>4</Subscript> and NH<Subscript>3</Subscript>BH<Subscript>3</Subscript>

The issues of hydrogen generation and storage have hindered the widespread use and commercialization of hydrogen fuel cell vehicles.It is thus highly attractive,but the design and development of highly active non-noble-metal catalysts for on-demand hydrogen release from alkaline NaBH4 solution under mild conditions remains a key challenge.Herein,we describe the use of CoP nanowire array integrated on a Ti mesh (CoP NA/Ti) as a three-dimensional (3D) monolithic catalyst for efficient hydrolytic dehydrogenation of NaBH4 in basic solutions.The CoP NA/Ti works as an on/off switch for on-demand hydrogen generation at a rate of 6,500 mL/(min.g) and a low activation energy of 41 kJ/mol.It is highly robust for repeated usage after recycling,without sacrificing catalytic performance.Remarkably,this catalyst also performs efficiently for the hydrolysis of NH3BH3.