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Managing of passwords in information systems is a very important task, yet nothing seems to be learned from the recent stories. The consequences of bad password management practices have led to the loss of lives, as in the case of suicides after the “Ashley Madison leak”. Password security is simply not taken seriously, despite problems being known since 1979 at least. Interestingly, the PICMET conference on-line system itself implements a bad password management policy as all passwords are stored and re-sent upon request by plaintext email. The objective of this paper is to present the underlying mechanisms that lead to bad password management policies. Memorability and memory decay, complexity, simplicity and other factors are presented and analyzed. A novel password management policy “Psychopass” is proposed, where a password can be created, memorized and recalled by thinking of an action sequence (visual representation) instead of a string of characters. In the experiment it was shown that users tend to better remember passwords under the “Psychopass” policy compared to other password management policies nowadays in effect. The results confirm that “Psychopass” policy is an alternative to the existing password management practices and can improve the resilience to the attacks on information systems.

One of the tasks of data mining is classification, which provides a mapping from attributes (observations) to pre-specified classes. Classification models are built by using underlying data. In principle, the models built with more data yield better results (are more accurate). However, the relationship between the available data and the performance is not well understood. How much data to use, or when to stop the learning process, are the key questions. In this paper we give a suggestion as when to stop the learning process.

In the paper a new outlier prediction method is presented that should improve the classification performance when mining the medical data. The method introduces the class confusion score metric that is based on the classification results of a set of classifiers, induced by an evolutionary decision tree induction algorithm. The classification improvement should be achieved by removing the identified outliers from a training set. Our proposition is that a classifier trained by a filtered dataset captures a better, more general knowledge model and should therefore perform better also on unseen cases. The proposed method is applied on the two cardio-vascular datasets and the obtained results are discussed.

The area of intelligent systems is one of the most important and successful. Some definitions state that in some way, intelligent systems are a form of information system. This was successfully introduced from the research domain of artificial intelligence in information systems practice. According to some references, the hardest single part of building any system, either information, software or intelligent, is deciding what to build. No other part of conceptual work is so difficult as establishing the detailed technical requirements. The authors propose reusability to support and influence requirements engineering. Reusability is actually a very simple activity that is not even listed in most dictionaries. In the software environment, requirements, design models, algorithms, test documents and many other products of the software process can be reused. However, our approach is not concentrated on software reusability, but rather on database and intelligent systems reusability which are not so often reused, but they are the main goal of the MetaBase project (T. Welzer et al., 1998). MetaBase is an object oriented repository which provides a structure for archiving reusable database components of several applications not only medical information systems. All possible conceptual models are classified according to business domain and functional domain of their application domains. The structure of the repository allows not only storage of reusable database components of several applications but also classifying and comparing components from different applications (T. Welzer et al., 1998).

The use of PROLOG for digital circuit simulation in the education process is discussed. It is noted that the curriculum of the University of Maribor gives electrical engineering students some basic knowledge of computer techniques and FORTRAN or Pascal. On this basis, PROLOG can be presented to the students in order to acquaint them with some fundamentals of this fifth-generation language. The students who have acquired basic knowledge of PROLOG are able to define digital circuits specification programs as well as other simple PROLOG rules. The experience that students gain makes them capable of understanding similar models of conventional engineering as well as the basic working of expert systems. >

The authors present guidelines that should be followed when designing the curricula for educating engineers who will be capable of managing and evaluating quality in the software design and development process. It is pointed out that quality management is impossible without planning. Consequently, the preparation of planning, which is divided into technical, quality, and resource plans, is of primary importance. In addition to the preparation of plans, a quality system that supports the elaboration of plans should be worked out. However, a quality system cannot be established without knowledge of process models, design methodologies and planning techniques, which requires that one observe standards from the group ISO 9000 and structured approaches. The authors present their experience regarding the level of knowledge that is satisfactory for the computer engineering level and for other predominantly electrical engineering levels, how and where to integrate software quality topics into the curriculum, which courseware to use, and how to persuade students that high quality software is not only code-weighted but that also depends on all attributes that make a software of high quality. >

A methodolgy/courseware for introducing such a quality system in software development organizations is described in this paper. The authors used the ISO standardization (ISO 9000-3: Standard for QA in design/development, production, installation and servicing) as the basis of the methodology and refined it with well known related process models. It is not limited to the standard but also concerns human factors regarding the continual improvements toward the quality system within training programs and group-work. The methodology is supported by an integrated software product which enables software process assessments and goal definitions and offers a hypertext based software-process-improvement knowledge base.

An experiment was conducted to highlight the technicality of two quite different but well known software development methodologies: System Analysis-System Design (SA-SD) and Jackson System Development (JSD). There was no attempt to reach a general conclusion about which software development methodology is better, looking from all aspects. Comparison was done by means of a questionnaire which was completed by 12 young engineers after they had finished their seminar work in postgraduate study. The results obtained speak in favor of the SA-SD methodology because it is more understandable to an engineer. >

The concept of the knowledge-based database designer, which is intended for conceptual database design, is dealt with. Because of its importance, it must be well designed and different tools should be combined to make this design more intelligent. The database design should be supported by expert (administrator know-how, CASE tool results) as well as problem-oriented knowledge of the application. >