Verbalization and problem solving: insight and spatial factors

Original article can be found at: http://www.bpsjournals.co.uk/ Copyright The British Psychological SocietyTwo groups of participants attempted eight examples of each of four different problem types formed by combining insight v. non-insight and verbal v. spatial factors. The groups were given different verbalization instructions viz., Silent (N=40) or Direct Concurrent (N=40). There were significant differences between insight and non-insight tasks and between spatial and verbal tasks in terms of solution rates and latencies. Significant interactions between the verbal v. spatial factor and verbalization condition on solution rates and latencies reflected a greater (negative) effect of verbalizing on spatial as against verbal problems. However, no significant interactions of the insight v. non-insight factor with verbalization condition on solution rates or latencies were found. These results favoured the “business as usual” view of insight problem solving as against the “special process” view which predicted larger effects of verbalization for insight problems as against non-insight problems.Peer reviewe

RuleCNL: A Controlled Natural Language for Business Rule Specifications

Business rules represent the primary means by which companies define their business, perform their actions in order to reach their objectives. Thus, they need to be expressed unambiguously to avoid inconsistencies between business stakeholders and formally in order to be machine-processed. A promising solution is the use of a controlled natural language (CNL) which is a good mediator between natural and formal languages. This paper presents RuleCNL, which is a CNL for defining business rules. Its core feature is the alignment of the business rule definition with the business vocabulary which ensures traceability and consistency with the business domain. The RuleCNL tool provides editors that assist end-users in the writing process and automatic mappings into the Semantics of Business Vocabulary and Business Rules (SBVR) standard. SBVR is grounded in first order logic and includes constructs called semantic formulations that structure the meaning of rules.Comment: 12 pages, 7 figures, Fourth Workshop on Controlled Natural Language (CNL 2014) Proceeding

Remember Gerhard Richter in the Thunderstorm of Beethoven: The Influence of Cross-Sensory Coupling on Memory, Intercultural Communication, and the Verbalization of Paintings and Sounds

This interdisciplinary study focuses on the perception and verbalization of messages conveyed through instrumental music, soundscapes, and contemporary paintings. International young-adult university students learning German participated in a series of experiments conducted at Friedrich Schiller University in Jena, Germany. To incorporate globalization and cultural difference into this analysis, the author compared the reactions of Western and Asian participants to auditory and visual stimuli. This paper explores the concepts of mixed media, cross-sensory coupling, and esthetic synesthesia, and throws new light on the contribution of cross-sensory coupling to verbalization and to long-term memory processes, from encoding to retrieval. In addition, the author demonstrates how intercultural communication is based upon universal emotions aroused by contemporary paintings, instrumental music and soundscapes

A Model Driven Reverse Engineering Framework for Extracting Business Rules out of a Java Application

International audienceIn order to react to the ever-changing market, every organization needs to periodically reevaluate and evolve its company policies. These policies must be enforced by its Information System (IS) by means of a set of business rules that drive the system behavior and data. Clearly, policies and rules must be aligned at all times but unfortunately this is a challenging task. In most ISs implementation of business rules is scattered among the code so appropriate techniques must be provided for the discovery and evolution of evolving business rules. In this paper we describe a model driven reverse engineering framework aiming at extracting business rules out of Java source code. The use of modeling techniques facilitate the representation of the rules at a higher-abstraction level which enables stakeholders to understand and manipulate them

BPMN: A Meta Model for the Happy Path

Recently, the OMG has been working on developing a new standard for a business process management notation (BPMN). This standard development results in documents that contain the newest approved version of a standard or a standard proposal that can be ammended. It is our vision that such a standard document, that also serves as a specification for BPMN modeling tool developers could benefit from a fact-oriented model in which the same domain knowledge is represented conceptually as a list of concept definitions (including naming conventions), a set of information structure diagrams and the constraints or business rules that govern the instances of the information structure diagrams. In this paper we will show precisely, how such a fact-oriented conceptual view on a standard document can be created, and we will show how a fact-oriented approach can improve the completeness of a specification.management information;

COMPLIANCE TO QUALITY CRITERIA OF EXISTING REQUIREMENTS ELICITATION METHODS

In this article we define a requirements elicitation method based on natural language modelling. We argue that our method complies with synthesized quality criteria for RE methods, and compare this with the compliance of traditional RE methods (EER, ORM, UML). We show limited empirical evidence to support our theoretical argument.computer science applications;

LAPDoc: Layout-Aware Prompting for Documents

Recent advances in training large language models (LLMs) using massive amounts of solely textual data lead to strong generalization across many domains and tasks, including document-specific tasks. Opposed to that there is a trend to train multi-modal transformer architectures tailored for document understanding that are designed specifically to fuse textual inputs with the corresponding document layout. This involves a separate fine-tuning step for which additional training data is required. At present, no document transformers with comparable generalization to LLMs are available That raises the question which type of model is to be preferred for document understanding tasks. In this paper we investigate the possibility to use purely text-based LLMs for document-specific tasks by using layout enrichment. We explore drop-in modifications and rule-based methods to enrich purely textual LLM prompts with layout information. In our experiments we investigate the effects on the commercial ChatGPT model and the open-source LLM Solar. We demonstrate that using our approach both LLMs show improved performance on various standard document benchmarks. In addition, we study the impact of noisy OCR and layout errors, as well as the limitations of LLMs when it comes to utilizing document layout. Our results indicate that layout enrichment can improve the performance of purely text-based LLMs for document understanding by up to 15% compared to just using plain document text. In conclusion, this approach should be considered for the best model choice between text-based LLM or multi-modal document transformers.Comment: Under review at ICDAR202

Towards a Rule Interchange Language for the Web

This articles discusses rule languages that are needed for a a full deployment of the SemanticWeb. First, it motivates the need for such languages. Then, it presents ten theses addressing (1) the rule and/or logic languages needed on the Web, (2) data and data processing, (3) semantics, and (4) engineering and rendering issues. Finally, it discusses two options that might be chosen in designing a Rule Interchange Format for the Web