A Belief rule-based environmental responsibility assessment system for small and medium-sized enterprises

Various environmental management systems, standards and tools are being created to assist companies to become more environmental friendly. However, not all the enterprises have adopted environmental policies in the same scale and range. Additionally, there is no existing guide to help them determine their level of environmental responsibility and subsequently, provide support to enable them to move forward towards environmental responsibility excellence. This research proposes the use of a Belief Rule-Based approach to assess an enterprise’s level commitment to environmental issues. The Environmental Responsibility BRB assessment system has been developed for this research. Participating companies will have to complete a structured questionnaire. An automated analysis of their responses (using the Belief Rule-Based approach) will determine their environmental responsibility level. This is followed by a recommendation on how to progress to the next level. The recommended best practices will help promote understanding, increase awareness, and make the organization greener. BRB systems consist of two parts: Knowledge Base and Inference Engine. The knowledge base in this research is constructed after an in-depth literature review, critical analyses of existing environmental performance assessment models and primarily guided by the EU Draft Background Report on "Best Environmental Management Practice in the Telecommunications and ICT Services Sector". The reasoning algorithm of a selected Drools JBoss BRB inference engine is forward chaining, where an inference starts iteratively searching for a pattern-match of the input and if-then clause. However, the forward chaining mechanism is not equipped with uncertainty handling. Therefore, a decision is made to deploy an evidential reasoning and forward chaining with a hybrid knowledge representation inference scheme to accommodate imprecision, ambiguity and fuzzy types of uncertainties. It is believed that such a system generates well balanced, sensible and Green ICT readiness adapted results, to help enterprises focus on making improvements on more sustainable business operations.

Cultural and linguistic context and lexical inferencing in English language learning: A case study

In an increasingly multilingual world, English language has kept a marked predominance as a global language. In many countries, English is the primary choice for foreign language learning. There is a long history of research in English language learning. The same applies for research in reading. A main interest since the 1970s has been the reading strategy defined as inferencing or guessing the meaning of unknown words from context. Inferencing has ben widely researched, however, the results and conclusions seem to be mixed. While some agree that inferencing is a useful strategy, others doubt its usefulness. Nevertheless, most of the research seem to agree that the cultural background affects comprehension and inferencing. While most of these studies have been done with texts and contexts created by the researches, little has been done using natural prose. The present study will attempt to further clarify the process of inferencing and the effects of the text’s cultural context and the linguistic background of the reader using a text that has not been created by the researcher. The participants of the study are 40 international students from Turku, Finland. Their linguistic background was obtained through a questionnaire and proved to be diverse. Think aloud protocols were performed to investigate their inferencing process and find connections between their inferences, comments, the text, and their linguistic background. The results show that: some inferences were made based on the participants’ world knowledge, experience, other languages, and English language knowledge; other inferences and comments were made based on the text, its use of language and vocabulary, and few cues provided by the author. The results from the present study and previous research seem to show that: 1) linguistic background is a source of information for inferencing but is not a major source; 2) the cultural context of the text affected the inferences made by the participants according to their closeness or distance from it.