疫情下高职“计算机信息技术”课程的教学探讨

新冠疫情的突如其来改变了人们很多原先的生活节奏,学校里的师生同样面临此困境。文章以高职教学中的基础课“计算机信息技术”为例,指出了线上教学时所面临的一些问题,并给出了一些解决的方法,论述了笔者在线上教学中所实施的教学步骤,力争做到线上线下教学效果的同质等效。

新形势下大学生“计算机信息技术”教学改革分析

近年来,社会各界对教育事业的重视程度越来越高,社会发展也对新时代人才提出了全新的要求。计算机信息技术应用作为现代人才的必备技能之一,得到了广大师生的普遍关注,对大学"计算机信息技术"相关课程进行改革与创新具有非常重要的现实意义。文章从"计算机信息技术"课程教学现状与问题入手,简要分析了相应的改革措施。

基于知识块的“计算机与信息技术基础”教学

文章针对某大学文科专业包括法学、社会工作、国际贸易等九个专业的250名学生,以及计算机科学与技术、网络工程专业200名学生做了问卷调查,先了解了“计算机与信息技术基础”教学的知识块掌握情况,然后提出了基于知识块的“计算机与信息技术基础”教学策略。

Vision based terrain reconstruction for planet rover using a special binocular bundle adjustment

This paper presents a pure vision based technique for 3D reconstruction of planet terrain. The reconstruction accuracy depends ultimately on an optimization technique known as 'bundle adjustment'. In vision techniques, the translation is only known up to a scale factor, and a single scale factor is assumed for the whole sequence of images if only one camera is used. If an extra camera is available, stereo vision based reconstruction can be obtained by binocular views. If the baseline of the stereo setup is known, the scale factor problem is solved. We found that direct application of classical bundle adjustment on the constraints inherent between the binocular views has not been tested. Our method incorporated this constraint into the conventional bundle adjustment method. This special binocular bundle adjustment has been performed on image sequences similar to planet terrain circumstances. Experimental results show that our special method enhances not only the localization accuracy, but also the terrain mapping quality.

A Metadata Model Based on Coupling Testing Information to Increase Testability of Component

A software component must be tested every time it is reused in order to assure quality of component itself and system in which it is to be integrated.So how to increase testability of component has become a key technology in the software engineering community.Here a method is introduced to increase component testability.And meanings of component testability and relative effective ways to increase testability are summarized.Then definitions of component coupling testing criterion,DU-I(Definition-Use Information) and OP-Vs(Observation-Point Values)are given.Base on these,a definition-use table is introduced,which includes DU-A and OP-Vs item,to help component testers to understand and observe interior details about component under test better.Then a framework of testable component based on above DU-table is given.These facilities provide ways to detect errors,observe state variables by observation-points based monitor mechanism.Moreover,above methods are applied to our application developed by ourselves before,and some test cases are generated.Then our method is compared with Orso method and Kan method using the same example,presenting the comparison results.The results illustrate the validity of our method,effectively generating test cases and killing more mutants.

BOOTSTRAPPING FOR EXTRACTING RELATIONS FROM LARGE CORPORA

A new approach of relation extraction is described in this paper. It adopts a bootstrap- ping model with a novel iteration strategy, which generates more precise examples of specific relation. Compared with previous methods, the proposed method has three main advantages: first, it needs less manual intervention; second, more abundant and reasonable information are introduced to represent a relation pattern; third, it reduces the risk of circular dependency occurrence in bootstrapping. Scalable evaluation methodology and metrics are developed for our task with comparable techniques over TianWang 100G corpus. The experimental results show that it can get 90% precision and have excellent expansibility.

Mining Maximal Frequent Patterns in a Unidirectional FP-tree

Because mining complete set of frequent patterns from dense database could be impractical, an interesting alternative has been proposed recently. Instead of mining the complete set of frequent patterns, the new model only finds out the maximal frequent patterns, which can generate all frequent patterns. FP-growth algorithm is one of the most efficient frequent-pattern mining methods published so far. However, because FP-tree and conditional FP-trees must be two-way traversable, a great deal memory is needed in process of mining. This paper proposes an efficient algorithm Unid_FP-Max for mining maximal frequent patterns based on unidirectional FP-tree. Because of generation method of unidirectional FP-tree and conditional unidirectional FP-trees, the algorithm reduces the space consumption to the fullest extent. With the development of two techniques: single path pruning and header table pruning which can cut down many conditional unidirectional FP-trees generated recursively in mining process, Unid_FP-Max further lowers the expense of time and space.

A Distributed Data Mining System Based on Multi-agent Technology

Distributed Data Mining is expected to discover preciously unknown, implicit and valuable information from massive data set inherently distributed over a network. In recent years several approaches to distributed data mining have been developed, but only a few of them make use of intelligent agents. This paper provides the reason for applying Multi-Agent Technology in Distributed Data Mining and presents a Distributed Data Mining System based on Multi-Agent Technology that deals with heterogeneity in such environment. Based on the advantages of both the CS model and agent-based model, the system is being able to address the specific concern of increasing scalability and enhancing performance.

Development of CAPP System for Small and Medium Size Apparel Enterprises

Existing computer-aided process planning （CAPP） systems for garment manufacturing emphasize all-purpose ones, lack specialism and availability. So, few developed is popular in the garment industries. This study is intended for developing a CAPP system, which aims at the actual condition of process planning in the small and medium size apparel enterprises （SMAs）. It enables the technologists of process planning to be quicker in generating suitable plans that are similar to existing styles or new. It also automatically provides labor cost by considering the shop-ricer caztiticns. Process planning is achieved by adopting the Hybrid Interactive-variant process planning mete. The proposed system has been realized in Borland Delphi 7 and Orade 8. For validation of the system, the software has been implemented successfully in a firm named Jingchen in China.

Image Registration Based on Improved Mutual Information with Hybrid Optimizer

An improved image registration method is proposed based on mutual infor- mation with hybrid optimizer. Firstly, mutual information measure is combined with morphological gradient information. The essence of the gradient information is that locations a large gradient magnitude should be aligned, but also the orientation of the gradients at those locations should be similar. Secondly, a hybrid optimizer combined PSO with Powell algorithm is proposed to restrain local maxima of mutual information function and improve the registration accuracy to sub-pixel level. Lastly, muhlresolution data structure based on Mallat decomposition can not only improve the behavior of registration function, but also improve the speed of the algorithm. Experimental results demonstrate that the new method can yield good registration result, superior to traditional optimizer with respect to smoothness and attraction basin as well as convergence speed.

Attribute reduction based on background knowledge and its application in classification of astronomical spectra data

To improve the efficiency of the attribute reduction, we present an attribute reduction algorithm based on background knowledge and information entropy by making use of background knowledge from research fields. Under the condition of known background knowledge, the algorithm can not only greatly improve the efficiency of attribute reduction, but also avoid the defection of information entropy partial to attribute with much value. The experimental result verifies that the algorithm is effective. In the end, the algorithm produces better results when applied in the classification of the star spectra data.

Data Mining and Visualization of Grid-Based City Emergency System

A cluster analyzing algorithm based on grids is introduced in this paper,which is applied to data mining in the city emergency system. In the previous applications, data mining was based on the method of analyzing points and lines, which was not efficient enough in dealing with the geographic information in units of police areas. The proposed algorithm maps an event set stored as a point set to a grid unit set, utilizes the cluster algorithm based on grids to find out all the clusters, and shows the results in the method of visualization. The algorithm performs well when dealing with high dimensional data sets and immense data. It is suitable for the data mining based on geogra-(phic) information system and is supportive to decision-makings in the city emergency system.

Integrated criteria for covert channel auditing

A new concept, the security level difference of a covert channel, is presented, which means the security level span from the sender to the receiver of the covert channel. Based on this, the integrated criteria for covert channel auditing are given. Whereas TCSEC (Trusted Computer System Evaluation Criteria) or CC (Common Criteria for Information Technology Security Evaluation) only use the bandwidth to evaluate the threat of covert channels, our new criteria integrate the security level difference, the bandwidth sensitive parameter, bandwidth, duration and instantaneous time of covert channels, so as to give a comprehensive evaluation of the threat of covert channels in a multilevel security system.

A Study on Acupressure Points Online Database

Acupuncture points or acupressure points have been popularly used for thousands years for Chinese to cure various illness or pains. The method comes with less or no side effects, comparing the western medicine chemicals. With the new computer information technologies, the ancient Chinese healing tool could be very convenient for people to take care of themselves at home or work. In this paper, the authors present their online database system for locating the acupressure points. A case study shows the details of the design and structure of the online system.

An entropy-based unsupervised anomaly detection pattern learning algorithm

Currently, most anomaly detection pattern learning algorithms require a set of purely normal data from which they train their model. If the data contain some intrusions buried within the training data, the algorithm may not detect these attacks because it will assume that they are normal. In reality, it is very hard to guarantee that there are no attack items in the collected training data. Focusing on this problem, in this paper, firstly a new anomaly detection measurement is proposed according to the probability characteristics of intrusion instances and normal instances. Secondly, on the basis of anomaly detection measure, we present a clustering-based unsupervised anomaly detection patterns learning algorithm, which can overcome the shortage above. Finally, some experiments are conducted to verify the proposed algorithm is valid.

Research and Review on Computer Forensics

With the development of Internet and information technology, the digital crimes are also on the rise. Computer forensics is an emerging research area that applies computer investigation and analysis techniques to help detection of these crimes and gathering of digital evidence suitable for presentation in courts. This paper provides foundational concept of computer forensics, outlines various principles of computer forensics, discusses the model of computer forensics and presents a proposed model.

Linguistic Truth Values Lattice Implication Algebras

In order to study uncertainty reasoning and automatic reasoning with linguistic terms, in this paper, the set of basic linguistic truth values and the set of modifiers are defined, according to common sense; partially orderings are defined on them. Based on it, a lattice implication algebra model L18 of linguistic terms is built; furthermore, its some basic properties are discussed.

Computer Audit Risk Control Research

The development of computer information technology makes the information of the audited unit more and more high. The introduction of accounting computerization information system makes the processing of enterprise economic business more convenient and efficient. Here came the computer controlled environment audit new risks, of course, the computer technology applied to the audit work to improve the audit efficiency by a lot, but also increased the complex information technology environment audit risk. Starting from the concept of computer audit risk, this paper analyzes and discusses the new risks and causes of audit under the computer condition, and puts forward some constructive risk control measures.

Ethics of Information Technologies in Knowledge Society

How should we define the ethics of information technology？ It is not a new field of study in the sense that it requires an entirely new ethical thinking. Rather, it is a field where we can try to use our traditional philosophical notions and apply them to this field of computer technology, information science, and knowledge society in order to define responsibility and accountability. Although relations of causalities may be blurred and complex because of the auto-poetic development of computers and information systems we may still have to face the fact that human beings are fundamentally responsible behind the responsibilities of the computers. So we can say that the concept of reliability and accountability is related to human responsibility in the field of Internet technology. Indeed, issues of hacking, viruses and intervention in computers also pose the problems of responsibility and violation of property and copyrights and here we face similar issues as when we talk about physical property rights although what happens is going on in cyberspace. Also we face fundamental problems about transparency, power and democracy of society as the result of the information revolution in knowledge. This shows how it becomes more and more difficult for governments and organizations to hide information and that information is becoming more and more public. We can also talk about the present development as a technology-driven information revolution in knowledge society. The information overload is a result of this revolution that is expressed in the Internet and that changes the relation of human beings to society where human beings need to access information technology and tools in order to be able to live and work in society.

A Scalable Communication Mechanism in Service Emergence Based on Bio-network

A scalable communication mechanism is proposed for service emergence based on bio-network.Service emergence is a novel model inspired by the characteristics of emergence and self-evolution in biological neuroendocrine and immune system,emergent communication means a group communication of mobile bio-entities.A series of protocol and algorithm are presented within frequently bio-entities migration and failure,it includes distribution and parallelization of message propagation method,a token-ring protocol that considerably improves the performance of emergence,and failure detection mechanisms.Experiment results show the desired capability via the proposed solution.