| 1. |
- Larsson, Jan Eric, et al.
(author)
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Improving expressional power and validation for multilevel flow models
- 2004
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In: Journal of Intelligent & Fuzzy Systems. - 1064-1246. ; 15:1, s. 61-73
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Journal article (peer-reviewed)abstract
- Multilevel flow modeling (MFM) is a modeling method for complex technical systems in which the goals and functions of the system are explicitly described. MFM can be used as a basis for root cause analysis, where primary root causes are separated from consequential faults, in complex fault situations. Model representations for use in diagnostic reasoning usually describe causality, between parameters, faults, of, process states. However, the causality of a system may vary depending on details in the construction, as well as over time with the process state. One contribution of this paper is a general method of describing varying causality in a simple and efficient way. The method has been tested using multilevel flow models. Causality is visible in measurements and can be used to increase process understanding. The standard cross-correlation technique is insufficient for causality detection in industrial processes. Another contribution of this paper is a new method that can detect causality in industrial signals, and thus be used to validate the design of multilevel flow models.
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| 2. |
- Lindgren, Helena, et al.
(author)
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Dierential diagnosis of dementia in an argumentation framework
- 2006
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In: Journal of Intelligent & Fuzzy Systems. - New York : IOS Press. - 1064-1246 .- 1875-8967. ; 17:4, s. 387-394
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Journal article (peer-reviewed)abstract
- In order to provide support for differential diagnosis of dementia in medical practice, logical specification of a single clinical guideline is not sufficient. Therefore, a synthesis guideline has been formalized using core features from selected clinical guidelines which report high sensitivity, using conventional two-valued propositional logic. This guideline is sufficient for capturing the major part of typical cases of patients in the domain. However, in order to provide support in atypical cases, additional clinical guidelines are needed in the reasoning process which report higher specificity but are pervaded with more uncertainty. In order to capture the different levels of significance in evidence expressed in the clinical guidelines an argumentation framework based on a many-valued propositional logic is adapted for the domain. This is accomplished in a context of transformations between logics. Formal frameworks will be given as well as a clinical case study where the sets of values that are attached to arguments correspond to the vocabulary used in the clinical guidelines, as well as the functions which compute the significance.
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| 3. |
- Oudshoff, AM, et al.
(author)
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Knowledge discovery in virtual community texts: Clustering virtual communities
- 2003
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In: Journal of Intelligent & Fuzzy Systems. - 1064-1246. ; 14:1, s. 13-24
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Journal article (peer-reviewed)abstract
- Automatic knowledge discovery from texts (KDT) is proving to be a promising method for businesses today to deal with the overload of textual information. In this paper, we first explore the possibilities for KDT to enhance communication in virtual communities, and then we present a practical case study with real-life Internet data. The problem in the case study is to manage the very successful virtual communities known as 'clubs' of the largest Dutch Internet Service Provider. It is possible for anyone to start a club about any subject, resulting in over 10,000 active clubs today. At the beginning, the founder assigns the club to a predefined category. This often results in illogical or inconsistent placements, which means that interesting clubs may be hard to locate for potential new members. The ISP therefore is looking for an automated way to categorize clubs in a logical and consistent manner. The method used is the so-called bag-of-words approach, previously applied mostly to scientific texts and structured documents. Each club is described by a vector of word occurrences of all communications within that club. Latent Semantic Indexing (LSI) is applied to reduce the dimensionality problem prior to clustering. Clustering is done by the Within Groups Clustering method using a cosine distance measure appropriate for texts. The results show that KDT and the LSI method can successfully be applied for clustering the very volatile and unstructured textual communication on the Internet.
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| 4. |
- van Veelen, M, et al.
(author)
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Model-based containment of process fault dissemination
- 2004
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In: Journal of Intelligent & Fuzzy Systems. - 1064-1246. ; 15:1, s. 47-59
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Journal article (peer-reviewed)abstract
- The past decade has witnessed a marked increase in distributed system complexity. This was driven by a maturing technology that steadily decreased the number of faults. Unfortunately these fewer faults have become exponentially more costly. It becomes mandatory to detect faults prior to taking effect on the network. Such an early detection requires a new test, detection and fault containment strategy, of which the outline and some basic ingredients are sketched here.
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| 5. |
- Ahnlund, Jonas, et al.
(author)
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Rule-based reduction of alarm signals in industrial control
- 2003
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In: Journal of Intelligent & Fuzzy Systems. - 1064-1246. ; 14:2, s. 73-84
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Journal article (peer-reviewed)abstract
- The proper handling of alarms is crucial to any automated process control. In practice, many alarms are only distractive and do not represent a potentially dangerous situation. This paper presents a methodology and a computerized tool that aims to remove such nuisance alarms, a so-called alarm cleanup. This is a general, systematic approach that takes advantage of the control system's built-in functions, and is a first step to an improved overall alarm situation. By the strong reduction of the alarm count, the efficient construction of fault diagnosis and isolation models becomes feasible. In a typical case study, the number of alarms received at the remote control room of an operational bio-fueled District Heating Plant was effectively reduced by 83%.
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| 6. |
- Bao, Jiangdong, et al.
(author)
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Cleaner production assessment of group company based on improved AHP and grey relational analysis
- 2018
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In: Journal of Intelligent & Fuzzy Systems. - : IOS Press. - 1064-1246 .- 1875-8967. ; 35:1, s. 439-444
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Journal article (peer-reviewed)abstract
- Cleaner production assessment is a measure of the state and level of cleaner production, also a necessary method of promoting cleaner production in enterprises. For the purpose of the improvement of cleaner production of enterprises, improved Analytic Hierarchy Process (AHP) model and grey relational analysis (GRA) are used to assess the same nature of the three enterprises of one group with seven quantitative indicators concordant with the Cleaner Production Report. The results are consistent with the clean production reports from three enterprises, which show that the integrated methods are feasible and objective, and can be used as a tool for internal cleaner production assessment.
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| 7. |
- Benali, B. Ait, et al.
(author)
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Arabic named entity recognition in social media based on BiLSTM-CRF using an attention mechanism
- 2022
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In: Journal of Intelligent & Fuzzy Systems. - : IOS Press. - 1064-1246 .- 1875-8967. ; 42:6, s. 5427-5436
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Journal article (peer-reviewed)abstract
- Named Entity Recognition (NER) is a vitally important task of Natural Language Processing (NLP), which aims at finding named entities in natural language text and classifying them into predefined categories such as persons (PER), places (LOC), organizations (ORG), and so on. In the Arabic context, the current NER approaches based on deep learning are mainly based on word embedding or character-level embedding as input. However, using a single granularity representation has problems with out-of-vocabulary (OOV), word embedding errors, and relatively simple semantic content. This paper presents a multi-headed self-attention mechanism implemented in the BiLSTM-CRF neural network structure to recognize Arabic named entities on social media using two embeddings. Unlike other state-of-the-art approaches, this approach combines character and word embedding at the embedding layer, and the attention mechanism calculates the similarity over the entire sequence of characters and captures local context information. The proposed approach better recognized NEs in Dialect Arabic, reaching an F1 value of 74.15% on Darwish's dataset (a publicly available Arabic NER benchmark for social media). According to our knowledge, our findings outperform the current state-of-the-art models for Arabic Named Entity Recognition on social media.
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| 8. |
- Brännström, Andreas, et al.
(author)
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Towards control in agents for human behavior change : an autism case
- 2024
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In: Journal of Intelligent & Fuzzy Systems. - 1064-1246 .- 1875-8967.
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Journal article (peer-reviewed)abstract
- This paper introduces an automated decision-making framework for providing controlled agent behavior in systems dealing with human behavior-change. Controlled behavior in such settings is important in order to reduce unexpected side-effects of a system’s actions. The general structure of the framework is based on a psychological theory, the Theory of Planned Behavior (TPB), capturing causes to human motivational states, which enables reasoning about dynamics of human motivation. The framework consists of two main components: 1) an ontological knowledge-base that models an individual’s behavioral challenges to infer motivation states and 2) a transition system that, in a given motivation state, decides on motivational support, resulting in transitions between motivational states. The system generates plans (sequences of actions) for an agent to facilitate behavior change. A particular use-case is modeled regarding children with Autism Spectrum Conditions (ASC) who commonly experience difficulties in everyday social situations. An evaluation of a proof-of-concept prototype is performed that presents consistencies between ASC experts’ suggestions and plans generated by the system.
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| 9. |
- Chhabra, Robin, et al.
(author)
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A linguistic approach to concurrent design
- 2015
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In: Journal of Intelligent & Fuzzy Systems. - 1064-1246 .- 1875-8967. ; 28:5, s. 1985-2001
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Journal article (peer-reviewed)abstract
- This paper outlines a concurrent design methodology for multidisciplinary systems, which employs tools of fuzzy theory for the tradeoff in the design space. This methodology enhances communication between designers from various disciplines through introducing the universal notion of satisfaction and expressing the behaviour of multidisciplinary systems using the notion of energy. It employs fuzzy rule-bases, membership functions and parametric connectives in fuzzy logic to formalize subjective aspects of design, resulting in a two-phase simplification of the multi-objective constrained optimization of a design process. The methodology attempts to find a pareto-optimal solution for the design problem. In the primary phase of the methodology, a fuzzy-logic model is utilized to identify a region in the design space that contains the pareto-optimal design state, and a proper initial state is suggested for the optimization in the secondary phase, where the pareto-optimal solution is found. Finally, the impact of the designer's subjective attitude on the design is adjusted based on a system performance by utilizing an energy-based model of multidisciplinary systems. As an application, it is shown that the design of a five-degree-of-freedom industrial robot manipulator can be enhanced by using the methodology.
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| 10. |
- Cielniak, Grzegorz, et al.
(author)
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People recognition by mobile robots
- 2004
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In: Journal of Intelligent & Fuzzy Systems. - 1064-1246 .- 1875-8967. ; 15:1, s. 21-27
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Journal article (peer-reviewed)abstract
- This paper addresses the problem of detecting and identifying persons with a mobile robot, by sensory fusion of thermal and colour vision information. In the proposed system, people are first detected with a thermal camera, using image analysis techniques to segment the persons in the thermal images. This information is then used to segment the corresponding regions of the colour images, using an affine transformation to solve the image correspondence between the two cameras. After segmentation, the region of the image containing a person is further divided into regions corresponding to the person's head, torso and legs. Temperature and colour features are then extracted from each region for input to a pattern recognition system. Three alternative classfication methods were investigated in experiments with a moving mobile robot and moving persons in an office environment. The best identification performance was obtained with a dynamic recognition method based on a Bayes classifier, which takes into account evidence accumulated in a sequence of images.
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