Cased Based Reasoning in Business Process Management Design

Tueschen, P., & dos Santos, V. D. (2021). Cased Based Reasoning in Business Process Management Design. In R. Silhavy (Ed.), Artificial Intelligence in Intelligent Systems - Proceedings of 10th Computer Science On-line Conference, 2021 (Vol. 2, pp. 722-741). (Lecture Notes in Networks and Systems; Vol. 229). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-77445-5_65Case-based reasoning (CBR), another form of artificial intelligence, stores and retrieves past cases that can be adapted to find a solution to a current problem. The new solution can then be retained and made available to solve other future problems. Business Process Management analyzes and optimizes business processes to make them more effective and efficient for an organization’s strategy to ultimately increasing shareholder value. CBR can help to support BPM, making better decisions with existing knowledge when solving process problems. This study investigates effectively store, retrieve, and adapt Business Process Management Notation (BPMN) solutions that best fit the underlying BPM problem using CBR as a tool. Therefore, a theoretical model was proposed, containing each CBR live cycle phase with different possible tools applied to BPMN diagrams, which was validated by expert interviews. This study concludes that a whole CBR life cycle can be applied to BPMN diagram problems with the need for human intervention. The objective was not to solve the whole problem but to contribute to a possible solution by using CBR through a theoretical model.authorsversionpublishe

Study on characteristics behavior of developing nozzle for aerosol spray

A new generation of aerosol technology are expand rapidly where the research and development are focused on the analysis of propellants, packaging and ingredients to make the aerosol has a high performance product. However, there are a few main problems with pressurised aerosol spray, which are the production of VOC and the quality of spraying process. Therefore, in this study the development of an internal nozzle has been investigated to analyse the characterictics of spray by using CFD simulation. The analysis is focused on various pressure supply up to 9bar, where the n-butane and water are applied as a liquid phases material. The simulation is done based on two types of selected nozzle design. The result shows that, the values of velocity, TKE and Reynolds Number for both liquid phases are increase when the pressure supply increased. It was observed that, when comparing the two type of nozzle design, it shown that the value of velocity and Reynolds number is relatively similar for both liquid phases, while the TKE value is more difference due to the material properties and nozzle design. Therefore, the use of water is acceptable as an alternative to substitute the n-butane liquid phase in producing an aerosol spray product

Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques

Nowadays an enormous quantity of heterogeneous and distributed information is stored in the digital University. Exploring online collections to find knowledge relevant to a user’s interests is a challenging work. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. In this work we propose a comprehensive approach for discovering E-learning objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We have used Case Based-Reasoning methodology to develop a prototype for supporting efficient retrieval knowledge from online repositories. We suggest a conceptual architecture for a semantic search engine. OntoUS is a collaborative effort that proposes a new form of interaction between users and digital libraries, where the latter are adapted to users and their surroundings

Design reuse research : a computational perspective

This paper gives an overview of some computer based systems that focus on supporting engineering design reuse. Design reuse is considered here to reflect the utilisation of any knowledge gained from a design activity and not just past designs of artefacts. A design reuse process model, containing three main processes and six knowledge components, is used as a basis to identify the main areas of contribution from the systems. From this it can be concluded that while reuse libraries and design by reuse has received most attention, design for reuse, domain exploration and five of the other knowledge components lack research effort

The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification

We present the Bayesian Case Model (BCM), a general framework for Bayesian case-based reasoning (CBR) and prototype classification and clustering. BCM brings the intuitive power of CBR to a Bayesian generative framework. The BCM learns prototypes, the "quintessential" observations that best represent clusters in a dataset, by performing joint inference on cluster labels, prototypes and important features. Simultaneously, BCM pursues sparsity by learning subspaces, the sets of features that play important roles in the characterization of the prototypes. The prototype and subspace representation provides quantitative benefits in interpretability while preserving classification accuracy. Human subject experiments verify statistically significant improvements to participants' understanding when using explanations produced by BCM, compared to those given by prior art.Comment: Published in Neural Information Processing Systems (NIPS) 2014, Neural Information Processing Systems (NIPS) 201

A Cased-Based Reasoning Decision Support System

Each bidding contractors estimates his likely costs of carrying out the work detailed in the project schedules and adds a percentage markup to form the bid value. The value of the markup crucially influences the chances of a bidder winning the contract. Clearly, a low markup value should increases the chance of winning but decrease the profit, whilst a high markup should increase the profit but decrease the chance of winning the contract. It is very difficult for contractors to decide a proper markup, which happens to produce a satisfactory balance between the probability of winning the contract and the profit generated as a result of winning the contract. This paper presents a case-based reasoning decision support system (CBR-DSS) that assists contractors in solving markup estimation problem. The CRR-DSS uses successful cases of previous completed projects to derive solution to new project markup estimation problem. The principle of the CBR-DSS is to analogy new project with previous projects. Key Words: Case-Based Reasoning, DSS, Bidding, Markup Résumé: Chaque contracteur demandé estime son coût d’application d’un travail détaillé dans les horaires et ajoute un percentage de maquillage pour avoir l’offre qui influence crucialement une éventuelle réussite d’un contrat. Evidemment une petite valeur de maquillage doit augmenter les chances de gagner mais réduire le profit tandis que un grand maquillage doit augmenter le profit mais réduire les chances d’arriver à un contract. Il est très difficile pour les contracteurs de décider une offre convenable, qui éventuellement produit une balance de satisfaction entre la probabilité d’achever le contrat et le profit considéré comme une réussite d’un contrat. Ce document présente un système du support decision rationnel basé sur les cas (CBR-DSS) qui permet aux contracteurs de s’engager dans la solution des problèmes estimés et demandés. Le CRR-DSS utilise des réussites de programmes pré-achévés qui servent à résoudre les problèmes d’estimation dans un nouveau programme. Le principe de CBR-DSS est trouver les solutions pour de nouveaux programmes par analogie ceux pré-achévés. Mots clés: Raisonnement basé sur les cas, DSS, offre, maquillage, acquisition Governmental

From real-world regulations to concrete norms for software agents: a case-based reasoning approach

When trying to use software agents (SAs) for real-world business and thereby putting them in a situation to operate under real-world laws, the abstractness of human regulations often poses severe problems. Thus, human regulations are written in a very abstract way, making them open to a wide range of interpretations and applicable for several scenarios as well as stable over a longer period of time. However, in order to be applicable for SAs, regulations need to be precise and unambiguous. This paper presents a case-based reasoning approach in order to bridge the gap between abstract human regulations and the concrete regulations needed for SAs, by developing and using a knowledge base that can be used for drawing analogies and thereby serves as reference for \translating" abstract terms in human regulations.(undefined

The desktop interface in intelligent tutoring systems

The interface between an Intelligent Tutoring System (ITS) and the person being tutored is critical to the success of the learning process. If the interface to the ITS is confusing or non-supportive of the tutored domain, the effectiveness of the instruction will be diminished or lost entirely. Consequently, the interface to an ITS should be highly integrated with the domain to provide a robust and semantically rich learning environment. In building an ITS for ZetaLISP on a LISP Machine, a Desktop Interface was designed to support a programming learning environment. Using the bitmapped display, windows, and mouse, three desktops were designed to support self-study and tutoring of ZetaLISP. Through organization, well-defined boundaries, and domain support facilities, the desktops provide substantial flexibility and power for the student and facilitate learning ZetaLISP programming while screening the student from the complex LISP Machine environment. The student can concentrate on learning ZetaLISP programming and not on how to operate the interface or a LISP Machine

Rescheduling with iterative repair

This paper presents a new approach to rescheduling called constraint-based iterative repair. This approach gives our system the ability to satisfy domain constraints, address optimization concerns, minimize perturbation to the original schedule, produce modified schedules, quickly, and exhibits 'anytime' behavior. The system begins with an initial, flawed schedule and then iteratively repairs constraint violations until a conflict-free schedule is produced. In an empirical demonstration, we vary the importance of minimizing perturbation and report how fast the system is able to resolve conflicts in a given time bound. We also show the anytime characteristics of the system. These experiments were performed within the domain of Space Shuttle ground processing