Web挖掘技术在E—learning中的应用研究

本文首先介绍了Web挖掘和电子学习（e—learning）＆其在商业和教育中的应用，然后在WebCT学习环境中对学生成绩做了一个模式分类的预测实验，证明了Web挖掘可以成为构建e—learning知识的一种方法，具有改善学生学习模式的潜在作用。     

e-learning:一种新型的学习模式

e—learning作为一种新型的学习模式，在学习的主体、客体以及主客体之间的关系上具有多元性、自主性、多重交互性、建构性等，显现出传统的学习模式所难以比拟的优势。目前e—learning的应用与研究尚处于初始阶段。有着广阔的发展情景。     

韩国重视U—learning实践与研究

2000年前后，韩国已经比较圆满地完成信息化基本工程建设。通讯光缆四通八达，电脑普及率高，整个社会的信息化程度也非常高。全国各中小学达到100％的入网率，生机比在6：1以上，信息技术与教学的整合的研究与实践非常蓬勃地开展。韩国教育技术学术界继E—learning的沸沸扬扬的探讨以后，近年来，出现了新的话题和研究领域——U—learning。     

Efficient privacy-preserving federated learning under dishonest-majority setting

<正>Federated learning(FL) is an emerging distributed learning paradigm that solves the problem of isolated data by jointly learning the global model through distributed clients.However, recent studies have shown that FL may not always guarantee sufficient privacy preservation, this is mainly because the model parameters(e.g., weights or gradients)may leak sensitive information to malicious adversaries.     

后网络课程时代审视15年来在线教育的转变

说起“网络课程”,大家都会很容易联想到上世纪末的产物——在线教育（E—learning）。E—learning的提出,让企业培训打破了疆域、时差的障碍。然而,这种崭新的教学形态提升了原有的传统教育效率,但带来并非根本教育体制的变化。自E—learning诞生至今的15年间,我们也迎来了一个新的教育时代。有人提出了MOOC（大型开放式网络课程）,学生可以免费获得“在线大学”的教育并获得公认的学历证书;也有人提出语音英语培训,让学生通过语音软件“单对单”深造外语。     

A Survey on Negative Transfer

Transfer learning(TL) utilizes data or knowledge from one or more source domains to facilitate learning in a target domain. It is particularly useful when the target domain has very few or no labeled data, due to annotation expense, privacy concerns,etc. Unfortunately, the effectiveness of TL is not always guaranteed. Negative transfer(NT), i.e., leveraging source domain data/knowledge undesirably reduces learning performance in the target domain, and has been a long-standing and challenging pro...     

Toward actionable testing of deep learning models

<正>Deep learning has become an important computational paradigm in our daily lives with a wide range of applications,from authentication using facial recognition to autonomous driving in smart vehicles. The quality of the deep learning models, i.e., neural architectures with parameters trained over a dataset, is crucial to our daily living and economy.     

Parallel Learning: Overview and Perspective for Computational Learning Across Syn2Real and Sim2Real

The virtual-to-real paradigm,i.e.,training models on virtual data and then applying them to solve real-world problems,has attracted more and more attention from various domains by successfully alleviating the data shortage problem in machine learning.To summarize the advances in recent years,this survey comprehensively reviews the literature,from the viewport of parallel intelligence.First,an extended parallel learning framework is proposed to cover main domains including computer vision,natural...     

GS1 Barcode GS1条码

GS1 e learning学习系统是国际物品编码协会开发和维护的一套介绍GS1系统、GDSN、EANCOM及供应链管理等内容的综合性在线基础培训教程，可以有效满足全球学员的学习需求。为让读者方便地掌握GS1系统知识，同时获取相关术语最原汁原味且准确的英文表达，本栏目用中英对照形式呈现课堂重点内容。     

Estimation of convergence rate for multi-regression learning algorithm

In many applications, the pre-information on regression function is always unknown. Therefore, it is necessary to learn regression function by means of some valid tools. In this paper we investigate the regression problem in learning theory, i.e., convergence rate of regression learning algorithm with least square schemes in multi-dimensional polynomial space. Our main aim is to analyze the generalization error for multi-regression problems in learning theory. By using the famous Jackson operators in approximation theory, covering number, entropy number and relative probability inequalities, we obtain the estimates of upper and lower bounds for the convergence rate of learning algorithm. In particular, it is shown that for multi-variable smooth regression functions, the estimates are able to achieve almost optimal rate of convergence except for a logarithmic factor. Our results are significant for the research of convergence, stability and complexity of regression learning algorithm.     

东芝数码复合机勇夺BLI实验室大奖

近日，东芝三款多动能数码复合机e—STUDIO282、e—STUDIO352和e—STIDO850历经耐久性、可靠性、打印质量、效率、易用性、经济性等多项标准的严格测评，以其突出的表现一举获得美国各名评测机构BU实验室2006年春季“年度推荐机型”奖。     

Hybrid3D: learning 3D hybrid features with point clouds and multi-view images for point cloud registration

In recent years, point cloud registration has achieved great success by learning geometric features with deep learning techniques. However, existing approaches that rely on pure geometric context still suffer from sensor noise and geometric ambiguities(e.g., flat or symmetric structure), which limit their robustness to real-world scenes. When 3D point clouds are constructed by RGB-D cameras, we can enhance the learned features with complementary texture information from RGB images. To this end, ...     

Towards real-time ML-based DDoS detection via cost-efficient window-based feature extraction

Distributed denial of service(DDoS) detection is still an open and challenging problem. In particular, sophisticated attacks, e.g., attacks that disguise attack packets as benign traffic always appear, which can easily evade traditional signature-based methods. Due to the low requirements for computing resources compared to deep learning, many machine learning(ML)-based methods have been realistically deployed to address this issue. However, most existing ML-based DDo S detection methods are hig...     

Fast training of Support Vector Machines using error-center-based optimization

1 Introduction Based on recent advances in statistical learning theory, Support Vector Machines (SVMs) compose a new class of learning system for pattern classification. Training a SVM amounts to solving a quadratic pro- gramming (QP) problem with a dense matrix. Stan- dard QP solvers require the full storage of this matrix, and their e?ciency lies in its sparseness, which make its application to SVM training with large training sets intractable. The SVM, pioneered by Vapnik and his te…     

A Reinforcement Learning-based Approach to Dynamic Job-shop Scheduling

Production scheduling is critical to manufacturing system.Dispatching rules are usually applied dynamically to schedule (?)he job in a dynamic job-shop.Existing scheduling approaches sel- dom address machine selection in the scheduling process.Composite rules,considering both machine selection and job selection,are proposed in this paper.The dynamic system is trained to enhance its learning and adaptive capability by a reinforcement learning(RL)algorithm.We define the concep- tion of pressure to describe the system feature.Designing a reward function should be guided by the scheduling goal to accurately record the learning progress.Competitive results with the RL-based approach show that it can be used as real-time scheduling technology.     

FURUTECH e-TP60电源

点评：FURUTECH公司e—TP60电源承继PRO．28N的e—TP60电源排插，虽然价位稍高于PRO28N，但在各方面表现均较PRO．28N要好上许多。若是您无法接受RTP一6将近两万元的身价，却又苦于找不到好的电源排插可用，我想这款e—TP60绝对能满足您在价位与声音两方面的要求。     

创新思想、优化教学——基于PBL教学模式的两个教学案例的研究比较

创新思想、优化教学，这是我国长期以来教学改革的目标。国外案例《水》和国内案例《生命之源——水》这两个教学案例都采用了一种新型的、有效的教学方式．即基于问题的学习(Problem—based learning．简称PBL)。它们在教学思想和教学观念上有一些突破．在教学方法、教学理念上有一些创新．这大大优化了教学。两个案例都设计、实施得不错，两者各有自己的优点．也存在一些各自的缺点。现对两个案例具体比较分析如下。     

数据质量和GOSN（全球数据同步网络）

GS1 e learning学习系统是国际物品编码协会开发和维护的一套介绍GS1系统、GDSN、EANCOM及供应链管理等内容的综合性在线基础培训教程，可以有效满足全球学员的学习需求。为让读者方便地掌握GS1系统知识，同时获取相关术语最原汁原味且准确的英文表达，本栏目自本年度第一期开始连续登载GS1重点内容，并以中英对照形式加以呈现。     

随e互联 无处不在

近日，中国移动的“随e行”在基于原有的GPRS广域无线上网解决方案基础上又有新的突破，增加了WLAN——无线局域上网这一高速无线上网方式，使无线上网速度更快捷、功能更强大。如果说中国移动日前推出的“随e行”，为人们打开了一扇通往自由互联的窗口，那么，接入了WLAN的“随e行”堪称如虎添翼，不仅可以“随时随地无线上网”，     

Model architecture level privacy leakage in neural networks

Privacy leakage is one of the most critical issues in machine learning and has attracted growing interest for tasks such as demonstrating potential threats in model attacks and creating model defenses.In recent years, numerous studies have revealed various privacy leakage risks(e.g., data reconstruction attack, membership inference attack, backdoor attack, and adversarial attack) and several targeted defense approaches(e.g., data denoising, differential privacy, and data encryption). However, ex...