Contingency and disaster planning

With the expansion of data processing, especially mini-computers, there has been the realization of the need to protect the data processing function of an organization from interruption. Any review of the current scene recognizes the need for greater emphasis on contingency and disaster planning. Five major issues involved in disaster/recovery planning are analyzed in this article. The first is the misconceptions about what should be contained in, and the limitations of, disaster/recovery planning. Secondly, there is the analysis of the types and levels of possible disasters. Then there is a comparison of disaster/recovery planning and back-up processing planning. Next is an analysis of what should be in the disaster/recovery plans of an organization. Finally, there is an overview of user disaster/recovery plans.     

Sensitivity Analysis of User Equilibrium Flows Revisited

This paper addresses certain misconceptions regarding what is known and what may be expected when performing sensitivity analyses of network user equilibrium flow patterns. Our presentation relies on a simple observation: any given user equilibrium sensitivity analysis technique should be employed only when the regularity conditions on which it is based are satisfied. Violating regularity, as we show through previously published numerical examples, as well as new examples presented here for the first time, may well lead to incorrect results when the Tobin-Friesz sensitivity analysis method is applied. This is especially so when the most critical regularity assumption of the Tobin-Friesz method, namely that the unperturbed solution must be a nondegenerate extreme point, is violated. We also illustrate how a degenerate unperturbed solution may sometimes be modified to obtain an appropriate nondegenerate solution, thereby allowing the Tobin-Friesz method to be applied.     

WEAKEST LINK,OR…

Metaphorizing is the principal means with which to conduct our thinking. We use metaphors to make meaning and sense about the world around us. We use them, furthermore, to form a view on the nature of the subject of the study. Thus, they play an important role in understanding a subject. Our point of view will determine what insights we will make and what inferences we draw. It is essential to understand the meaning of the metaphor and what mental pictures—including unintended ones—it conveys. Using an inappropriate mental picture can cause serious misconceptions. The focal point of this article is metaphors used to describe information security. The first one is a commonly used metaphor in the information security industry—the link metaphor. The meaning and the problems evident with using this metaphor are discussed first. An alternative is then provided—the Formula 1 (F1) car metaphor. A detailed rationale for using this metaphor instead of the first one completes the article.     

Maintaining mental models of agents who have existential misconceptions

This work describes methods for using and maintaining models of agents who have existential misconceptions. Existential misconceptions are situations where agents are in disagreement about the existence of objects in some domain of discourse. This paper characterizes existential misconceptions, discusses related literature, and describes how to construct a model of an agent who has an existential misconception. This paper is concerned with two kinds of existential misconception. These are compression-based and dispersion-based. We provide algorithms to test for these existential misconceptions, to describe them, and to correct one kind of existential misconception (dispersion-based). We prove correctness theorems for these algorithms and have implemented them in COMMON LISP.     

On Some Alleged Misconceptions about Fuzzy Logic

Entemann (2002) defends fuzzy logic by pointing to what he calls misconceptions concerning fuzzy logic. However, some of these ;misconceptions are in fact truths, and it is Entemann who has the misconceptions. The present article points to mistakes made by Entemann in three different areas. It closes with a discussion of what sort of general considerations it would take to motivate fuzzy logic.     

Propositionally representing incomplete knowledge about existence

Abstract

This paper considers the problem of representing the knowledge state of an observed agent who has incomplete knowledge of existence. Agents in such knowledge states are said to have existential misconceptions. We describe preliminary work on representing the knowledge state of an agent who possesses existential misconceptions and how to detect when this occurs. The method is based on a simulation of the observed agent's processes of information acquisition. We describe an implementation of this system and study its operation in a simulated microworld. The agent's acquisition of existential misconceptions is correlated with the agent's inaccurate beliefs of equality. This makes it possible to characterize an agent's existential misconceptions by describing its inaccurate beliefs of equality.     

Solving the problem of how medical students solve problems

Although gathering and processing information are essential to medical problem solving, little is known about what strategies students use to gather information or how they use their cognitive skills to solve problems. We have developed computer-based problem-solving exercises in immunology to determine how students gather and process information. Graphic representations of students' search paths through different problems were developed to visualize how organized and focused their knowledge was, how well their organization related to critical concepts in immunology, where serious misconceptions (confusion or erroneous models) occurred, and whether proper knowledge links between conceptual domains existed. With rapid generation and interpretation of information on patterns and difficulties in problem solving, it should become possible to develop a specific and personal approach to each student's educational needs.     

The stability of analogically reconstructed probability knowledge among secondary mathematics students

Abstract:

The existence of probability misconceptions at various educational levels has been well documented. Furthermore, these misconceptions have been shown to be widespread and highly resistant to change. The author's previous research has shown considerable success in overcoming misconceptions in the short term by basing the knowledge reconstruction process on problems that draw out beliefs held by students that are in agreement with accepted theory and that are therefore expected to receive correct responses. Such problems are referred to as anchoring situations or anchors.

In this study, anchoring probability situations that are conceptually analogous to misconception‐prone target probability situations were generated and tested with secondary mathematics students. The testing showed that probability misconceptions were common but also that the generated anchors were effective in reconstructing misconception‐laden probability knowledge. A follow‐up test showed that 65% of the reconstructed knowledge was retained after six months.     

Prevention of reinjury

This paper will address steps to be taken to prevent reinjury from becoming chronic. The focus is on helping workers to better understand and apply to themselves the nature of the healing process, the adverse effects of disuse, and how to distinguish pain from suffering. The impact of the person's understanding of the nature of pain and its implications for promoting healing will also be considered. Pain from tissue injury persists largely because of failure to apply what is known about healing and the effects of disuse. This failure interacts with patient misconceptions about pain and healing. The result is a confounding of pain with suffering and an unnecessary persistence of pain and disability. The interplay of perception or cognitive labelling, suffering and the influence of consequences should be considered.     

A testing system for diagnosing misconceptions in DC electric circuits

A testing-based diagnosing system is implemented. The system has a problem library that collects some suitable problems and associated answers. The answers of each problem are related to misconceptions. Problem selector in the system provides some problems to test student. Based on the student's answers, the diagnoser in the system will discriminate the student's misconceptions. The problem selector and the diagnoser are implemented with matrix operations. For evaluating the performance of the system, the topic of basic DC electricity is used as the subject domain. There are nine types of misconceptions found in basic electricity. Based on the experimental results, the system has the satisfactory diagnosis.     

Cooperative behaviour in the FIDO system

One of the demands that are put on a Natural Language interface is that it behaves in a cooperative way, that is, roughly speaking, in the most useful and natural way.This problem has been addressed in the context of the FIDO system (Flexible Interface for Database Operations), and in particular two points have been examined: the generation of answers that take into account the expectations and presuppositions the user showed in his/her question; the correction of some semantic mistakes detected during the analysis of the input question.In particular, as far as the former point is concerned, two issues have been addressed: the correction of user's misconceptions regarding the stored data; the generation of answers as suited as possible to what the user asked and to the way he/she phrased his/her question.     

Learning and diagnosis of individual and class conceptual perspectives: an intelligent systems approach using clustering techniques

In a classroom, a teacher attempts to convey his or her knowledge to the students, and thus it is important for the teacher to obtain formative feedback about how well students are understanding the new material. By gaining insight into the students' understanding and possible misconceptions, the teacher will be able to adjust the teaching and to supply more useful learning materials as necessary. Therefore, the diagnosis of formative student evaluations is critical for teachers and learners, as is the diagnosis of patterns in the overall learning by a class in order to inform a teacher about the efficacy of his or her teaching. This paper investigates what might be called the “class learning diagnosis problem” by embedding important concepts in a test and analyzing the results with a hierarchical coding scheme. Based on previous research, the part-of and type-of relationships among concepts are used to construct a concept hierarchy that may then be coded hierarchically. All concepts embedded in the test items then can be formulated into concept matrices, and the answer sheets of the learners in a class are then analyzed to indicate particular types of concept errors. The trajectories of concept errors are studied to identify both individual misconceptions students might have as well as patterns of misunderstanding in the overall class. In particular, a clustering algorithm is employed to distinguish student groups who might share similar misconceptions. These approaches are implemented as an integrated module in a previously developed system and applied to two real classroom data sets, the results of which show the practicability of this proposed method.     

Three fundamental misconceptions of Artificial Intelligence

In discussions on the limitations of Artificial Intelligence (AI), there are three major misconceptions, identifying an AI system with an axiomatic system, a Turing machine, or a system with a model-theoretic semantics. Though these three notions can be used to describe a computer system for certain purposes, they are not always the proper theoretical notions when an AI system is under consideration. These misconceptions are not only the basis of many criticisms of AI from the outside, but also responsible for many problems within AI research. This paper analyses these misconceptions, and points out the common root of them: treating empirical reasoning as mathematical reasoning. Finally, an example intelligent system called NARS is introduced, which is neither an axiomatic system nor a Turing machine in its problem-solving process, and does not use model-theoretic semantics, but is still implementable in an ordinary computer.     

计算机组成原理优秀教材中的两个错误

长期以来,国内流行的某些计算机组成原理方面的教材存在两个错误,其一是相联存储器不按地址寻址的问题,其二是多模块交叉编址存储器带宽的计算问题。本文对这两个错误进行分析和探讨。指出了(1)按地址寻址是相联存储器不可缺少的功能;(2)交叉存储器的带宽约为顺序存储器带宽的m倍,m为模块数。     

Assessing students' conceptual understanding using an online three‐tier diagnostic test

When solving a mathematical problem, students who do not have sufficient conceptual understanding may perform poorly and exhibit misconceptions. This study was aimed to examine students' conceptual understanding and significant misconceptions when solving number sense‐related problems. An online three‐tier diagnostic test was administered to 125 fifth‐grade students with varied socio‐economic backgrounds in Hong Kong. Only 14.40% of the students exhibited high performance with high confidence, indicating that these students had a profound conceptual understanding of number sense. In addition, the majority of the students (66.40%) did not demonstrate number sense; these students exhibited several significant misconceptions and could solve the questions only by using a rule‐based method or guessing. Accordingly, most students performed unsatisfactorily on number sense‐related problems. This study is imperative in identifying early predictors and provides information for further compatible interventions in the teaching and learning of number sense in Hong Kong in particular and worldwide in general.     

浅析目前动漫教学中存在的误区

动漫教学在当今高校教育中所占比例越来越重,然而,由于诸多方面原因,当前动漫教学过程存在一些误区。本文从动漫基础教学、动漫教学的本土原创性和动漫教学培养目标几方面入手,旨在找出造成动漫教学重借鉴轻原创、重西方轻中国、重技术轻艺术的根本原因,以提高教学水平。     

Misconceptions about real-time databases

Increasingly, computer systems-even general purpose systems-are requiring real time support, so it's not surprising to hear more about real time databases. Unfortunately, there are many misconceptions about the real time aspects of databases. Mainstream database users who don't have any experience with real time systems mistakenly think they are synonymous with speed. Others argue that conventional database technology can be used in real time applications. To help bring order to the current state of confusion, the authors review nine common misconceptions about real time databases. They also describe key research areas that need to be addressed to encourage increased activity in this challenging area