Business Ontology for Evaluating Corporate Social Responsibility

This paper presents a software solution that is developed to automatically classify companies by taking into account their level of social responsibility. The application is based on ontologies and on intelligent agents. In order to obtain the data needed to evaluate companies, we developed a web crawling module that analyzes the company’s website and the documents that are available online such as social responsibility report, mission statement, employment structure, etc. Based on a predefined CSR ontology, the web crawling module extracts the terms that are linked to corporate social responsibility. By taking into account the extracted qualitative data, an intelligent agent, previously trained on a set of companies, computes the qualitative values, which are then included in the classification model based on neural networks. The proposed ontology takes into consideration the guidelines proposed by the “ISO 26000 Standard for Social Responsibility”. Having this model, and being aware of the positive relationship between Corporate Social Responsibility and financial performance, an overall perspective on each company’s activity can be configured, this being useful not only to the company’s creditors, auditors, stockholders, but also to its consumers.corporate social responsibility, ISO 26000 Standard for Social Responsibility, ontology, web crawling, intelligent agent, corporate performance, POS tagging, opinion mining, sentiment analysis

Application of shape grammar theory to underground rail station design and passenger evacuation

This paper outlines the development of a computer design environment that generates station ‘reference’ plans for analysis by designers at the project feasibility stage. The developed program uses the theoretical concept of shape grammar, based upon principles of recognition and replacement of a particular shape to enable the generation of station layouts. The developed novel shape grammar rules produce multiple plans of accurately sized infrastructure faster than by traditional means. A finite set of station infrastructure elements and a finite set of connection possibilities for them, directed by regulations and the logical processes of station usage, allows for increasingly complex composite shapes to be automatically produced, some of which are credible station layouts at ‘reference’ block plan level. The proposed method of generating shape grammar plans is aligned to London Underground standards, in particular to the Station Planning Standards and Guidelines 5th edition (SPSG5 2007) and the BS-7974 fire safety engineering process. Quantitative testing is via existing evacuation modelling software. The prototype system, named SGEvac, has both the scope and potential for redevelopment to any other country’s design legislation

Development of microcomputer-based mental acuity tests for repeated-measures studies

The purpose of this report is to detail the development of the Automated Performance Test System (APTS), a computer battery of mental acuity tests that can be used to assess human performance in the presence of toxic elements and environmental stressors. There were four objectives in the development of APTS. First, the technical requirements for developing APTS followed the tenets of the classical theory of mental tests which requires that tests meet set criteria like stability and reliability (the lack of which constitutes insensitivity). To be employed in the study of the exotic conditions of protracted space flight, a battery with multiple parallel forms is required. The second criteria was for the battery to have factorial multidimensionality and the third was for the battery to be sensitive to factors known to compromise performance. A fourth objective was for the tests to converge on the abilities entailed in mission specialist tasks. A series of studies is reported in which candidate APTS tests were subjected to an examination of their psychometric properties for repeated-measures testing. From this work, tests were selected that possessed the requisite metric properties of stability, reliability, and factor richness. In addition, studies are reported which demonstrate the predictive validity of the tests to holistic measures of intelligence

How to make privacy policies both GDPR-compliant and usable

It is important for organisations to ensure that their privacy policies are General Data Protection Regulation (GDPR) compliant, and this has to be done by the May 2018 deadline. However, it is also important for these policies to be designed with the needs of the human recipient in mind. We carried out an investigation to find out how best to achieve this.We commenced by synthesising the GDPR requirements into a checklist-type format. We then derived a list of usability design guidelines for privacy notifications from the research literature. We augmented the recommendations with other findings reported in the research literature, in order to confirm the guidelines. We conclude by providing a usable and GDPR-compliant privacy policy template for the benefit of policy writers

Knowledge Extraction from Natural Language Requirements into a Semantic Relation Graph

Knowledge extraction and representation aims to identify information and to transform it into a machine-readable format. Knowledge representations support Information Retrieval tasks such as searching for single statements, documents, or metadata. Requirements specifications of complex systems such as automotive software systems are usually divided into different subsystem specifications. Nevertheless, there are semantic relations between individual documents of the separated subsystems, which have to be considered in further processes (e.g. dependencies). If requirements engineers or other developers are not aware of these relations, this can lead to inconsistencies or malfunctions of the overall system. Therefore, there is a strong need for tool support in order to detects semantic relations in a set of large natural language requirements specifications. In this work we present a knowledge extraction approach based on an explicit knowledge representation of the content of natural language requirements as a semantic relation graph. Our approach is fully automated and includes an NLP pipeline to transform unrestricted natural language requirements into a graph. We split the natural language into different parts and relate them to each other based on their semantic relation. In addition to semantic relations, other relationships can also be included in the graph. We envision to use a semantic search algorithm like spreading activation to allow users to search different semantic relations in the graph

Social security as a subject of human geography research study

This article deals social security as a subject of human geography research study. The publication focuses on the social, economic, geoecological, information, mental and cultural components of social development of Ukraine. The main social problems and scientific aspects of social security in Ukraine are considere

Challenges Facing East Asian Immigrant Children in Sexual Abuse Cases

Immigrants from East Asia make up 14.21% of the total number of immigrants in Canada. These families face many challenges as they acculturate to North America but, sadly, some of these children may be at risk for sexual abuse. In this position paper, we outline the ways in which East Asian children are at a particular disadvantage when considering prosecution of those who perpetrate abuse compared to Western non-immigrant children. We focus specifically on two areas of concern: 1) Cultural differences that can impact the disclosure of sexual abuse; and, 2) Language differences which reduce the chances that perpetrators will be prosecuted for sexual abuse. The consequences for East Asian immigrant youth who allege (or are suspected) that they are victims of abuse are serious. East Asian children face an uphill battle to see justice in sexual abuse cases. Thus, a significant portion of immigrant children will not see their abusers punished and, worse, the knowledge that prosecution is unlikely makes East Asian immigrant children a targeted population for those who abuse