REDUCED ATTRIBUTE ORIENTED HANDLING OF INCONSISTENCY IN DECISION GENERATION

Abstract Due to the discarded attributes, the effectual condition classes of the decision rules are highly different. To provide a unified evaluative measure, the derivation of each rule is depicted by the reduced attributes with a layered manner. Therefore, the inconsistency is divided into two primary categories in terms of the reduced attributes. We introduce the notion of joint membership function wrt. the effectual joint attributes, and a classification method extended from the default decision generation framework is proposed to handle the inconsistency. Keywords: reduced attributes, reduced layer, joint membership function, rough set Introduction Classification in rough set theory [1] is mainly composed of two components: feature extraction and decision synthesis. Many researches focus on the construction of classification algorithm, such as probabilistic method [2], decision trees[3] and parameterized rule inducing method This paper, based on the default rule extracting framewor

Early aspects: aspect-oriented requirements engineering and architecture design

This paper reports on the third Early Aspects: Aspect-Oriented Requirements Engineering and Architecture Design Workshop, which has been held in Lancaster, UK, on March 21, 2004. The workshop included a presentation session and working sessions in which the particular topics on early aspects were discussed. The primary goal of the workshop was to focus on challenges to defining methodical software development processes for aspects from early on in the software life cycle and explore the potential of proposed methods and techniques to scale up to industrial applications

SQL Injection Vulnerability Detection Using Deep Learning: A Feature-based Approach

SQL injection (SQLi), a well-known exploitation technique, is a serious risk factor for database-driven web applications that are used to manage the core business functions of organizations. SQLi enables an unauthorized user to get access to sensitive information of the database, and subsequently, to the application’s administrative privileges. Therefore, the detection of SQLi is crucial for businesses to prevent financial losses. There are different rules and learning-based solutions to help with detection, and pattern recognition through support vector machines (SVMs) and random forest (RF) have recently become popular in detecting SQLi. However, these classifiers ensure 97.33% accuracy with our dataset. In this paper, we propose a deep learning-based solution for detecting SQLi in web applications. The solution employs both correlation and chi-squared methods to rank the features from the dataset. Feed-forward network approach has been applied not only in feature selection but also in the detection process. Our solution provides 98.04% accuracy over 1,850+ recorded datasets, where it proves its superior efficiency among other existing machine learning solutions

Parameterizable Views for Process Visualization

In large organizations different users or user groups usually have distinguished perspectives over business processes and related data. Personalized views on the managed processes are therefore needed. Existing BPM tools, however, do not provide adequate mechanisms for building and visualizing such views. Very often processes are displayed to users in the same way as drawn by the process designer. To tackle this inflexibility this paper presents an advanced approach for creating personalized process views based on well-defined, parameterizable view operations. Respective operations can be flexibly composed in order to reduce or aggregate process information in the desired way. Depending on the chosen parameterization of the applied view operations, in addition, different "quality levels" with more or less relaxed properties can be obtained for the resulting process views (e.g., regarding the correctness of the created process view scheme). This allows us to consider the specific needs of the different applications utilizing process views (e.g., process monitoring tools or process editors). Altogether, the realized view concept contributes to better deal with complex, long-running business processes with hundreds up to thousands of activities

Identification of Biodiversity and Other Forest Attributes for Sustainable Forest Management: Siberian Forest Case Study

This paper attempts to identify characteristics of biodiversity and other (forest) ecosystem conditions that are considered essential for a description of ecosystem functioning and development of sustainable forest management practices in the Siberian forests. This is accomplished through an analysis of net primary production of phytomass (NPP) which acts as a proxy for ecosystem functioning. Rough Sets (RS) analysis is applied to study the Siberian ecoregions classified into compact and cohesive NPP performance classes. Through a heuristic procedure, a reduced set of attributes is generated for a NPP classification problem. In order to interpret relationships between various forest characteristics, so-called "interesting rules" are generated on a basis of reduced problem description. These "interesting rules" provide means to draw conclusions in the form of knowledge statements about functioning of the Siberian forests

Geoinformation, Geotechnology, and Geoplanning in the 1990s

Over the last decade, there have been some significant changes in the geographic information available to support those involved in spatial planning and policy-making in different contexts. Moreover, developments have occurred apace in the technology with which to handle geoinformation. This paper provides an overview of trends during the 1990s in data provision, in the technology required to manipulate and analyse spatial information, and in the domain of planning where applications of computer technology in the processing of geodata are prominent. It draws largely on experience in western Europe, and in the UK and the Netherlands in particular, and suggests that there are a number of pressures for a strengthened role for geotechnology in geoplanning in the years ahead

UML Inconsistencies Assessment

International audienceThe UML modelling language provides diagrams allowing multiple viewpoints of one system to be described. However, certain sets of elements of a model can be inconsistent. Inconsistencies are not drawbacks of the language as they highlight the presence of faults in the models. This paper proposes an assessment of the inconsistencies in order to estimate the effort which must be provided to handle them