2024 |
Shafiq SI, Sanin C, Szczerbicki E, 'Decisional-DNA-Based Digital Twin Implementation Architecture for Virtual Engineering Objects', Cybernetics and Systems, 55 719-729 (2024) [C1]
Digital twin (DT) is an enabling technology that integrates cyber and physical spaces. It is well-fitted for manufacturing setup since it can support digitalized assets and data a... [more]
Digital twin (DT) is an enabling technology that integrates cyber and physical spaces. It is well-fitted for manufacturing setup since it can support digitalized assets and data analytics for product and process control. Conventional manufacturing setups are still widely used all around the world for the fabrication of large-scale production. This article proposes a general DT implementation architecture for engineering objects/artifacts used in conventional manufacturing. It will empower manufacturers to leverage DT for real-time decision-making, control, and prediction for efficient production. An application scenario of Decisional-DNA based anomaly detection for conventional manufacturing tools is demonstrated as a case study to explain the architecture.
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2023 |
Fathima A, Khan A, Uddin MF, Waris MM, Ahmad S, Sanin C, Szczerbicki E, 'Performance Evaluation and Comparative Analysis of Machine Learning Models on the UNSW-NB15 Dataset: A Contemporary Approach to Cyber Threat Detection', Cybernetics and Systems, (2023) [C1]
This research work utilizes the University of New South Wales Network Based 2015 (UNSW-NB15) dataset to investigate the dynamic nature of cyber threats, departing from the obsolet... [more]
This research work utilizes the University of New South Wales Network Based 2015 (UNSW-NB15) dataset to investigate the dynamic nature of cyber threats, departing from the obsolete Knowledge Discovery and Data Mining competition 1999 (KDD Cup99) dataset. The data preparation pipeline consists of essential procedures aimed at ensuring the integrity and appropriateness of the data for analysis. The method begins by removing null values, thereafter, applying one-hot encoding to categorical features, min-max scaling for data normalization, and label encoding for efficient management of binary labels. The process of feature selection is conducted utilizing the Pearson coefficient correlation. An exhaustive evaluation is conducted on six machine learning models for the purpose of binary classification. The evaluation takes into account key performance measures like accuracy, precision, recall, and F1 score. The Random Forest model demonstrated exceptional performance, with a remarkable accuracy of 99% and a robust F1 score of 98%. Additionally, it exhibited a well-balanced precision and recall at 98%. The Support Vector Machine, Gradient Boosting, Logistic Regression, Decision Tree, and K-Nearest Neighbors models exhibit notable performance, achieving accuracy and F1 scores around at the 98% level. During our investigation into multi-class classification research, we thoroughly examined numerous machine learning models, all of which exhibited robust performance, with accuracy rates ranging from 97% to 98%. The aforementioned results highlight the efficacy of these models in accurately classifying data, regularly achieving high levels of precision, recall, and F1 scores for positive case predictions. This study offers a current viewpoint on the identification of cyber threats and emphasizes the appropriateness of several machine learning models in this rapidly changing field.
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2023 |
Pokhrel K, Sanin C, Sakib MKH, Islam MR, Szczerbicki E, 'Improved Skin Disease Classification with Mask R-CNN and Augmented Dataset', Cybernetics and Systems, (2023) [C1]
Skin diseases are a significant global health concern, impacting millions worldwide. Severe diseases like psoriasis and dermatitis can coexist with more benign skin issues like ac... [more]
Skin diseases are a significant global health concern, impacting millions worldwide. Severe diseases like psoriasis and dermatitis can coexist with more benign skin issues like acne and eczema. Primary care physicians in tropical areas often treat patients with skin issues in locations where onchocerciasis and tinea imbricate are prominent, such infections might even take center stage. Usually, skin illnesses are disregarded medically and considered cosmetic, but they can have serious psychosocial effects, especially at an early age, and very few global studies have attempted to quantify the frequency of skin diseases. Nevertheless, the ability to make an accurate diagnosis at an early stage is crucial for successful treatment of complex diseases. However, Skin disease identification is a complex process. We introduce a state-of-the-art approach that uses Mask R-CNN in conjunction with an augmented dataset from the HAM10000 from the Harvard University Open Data Repository to achieve close to 80% accuracy in skin disease classification. We provide an in-depth analysis of our approach, covering data preprocessing, model architecture, training, and evaluation, along with detailed tables presenting training and testing results and associated hyperparameters.
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2023 |
Sanin C, 'Artificial Intelligence: Current Perspectives and Alternative Paths', TecnoLógicas, 26 e2731-e2731
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2022 |
Silva de Oliveira C, Sanin C, Szczerbicki E, 'Smart Knowledge Engineering for Cognitive Systems: A Brief Overview', CYBERNETICS AND SYSTEMS, 53 384-402 (2022) [C1]
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Nova |
2022 |
Shafiq SI, Sanin C, Szczerbicki E, 'Decisional DNA (DDNA) Based Machine Monitoring and Total Productive Maintenance in Industry 4.0 Framework', CYBERNETICS AND SYSTEMS, 53 510-519 (2022) [C1]
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Nova |
2022 |
Ahmed MB, Sanin C, Szczerbicki E, 'Smart Virtual Product Development: Manufacturing Capability Analysis and Process Planning Module', CYBERNETICS AND SYSTEMS, 53 468-481 (2022) [C1]
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Nova |
2022 |
de Castro RO, Sanin C, Levula A, Szczerbicki E, 'The Development of a Conceptual Framework for Knowledge Sharing in Agile IT Projects', Cybernetics and Systems, 53 529-540 (2022) [C1]
Organizations must adapt their resources to meet the challenges associated with changes in the work environment in order to remain competitive in the information era. Several rese... [more]
Organizations must adapt their resources to meet the challenges associated with changes in the work environment in order to remain competitive in the information era. Several research findings identify knowledge sharing as a means for an organization to improve its competitiveness. Knowledge sharing can be defined in a variety of ways, but it essentially refers to the exchange of knowledge from an information giver to an information receiver. This is a purposeful activity that adds value to the client organization, particularly in IT system that employs Agile methodology. For the scope of this paper, we are going to consider only Agile knowledge transfer in IT projects that occurs in two angles: business knowledge transfers from client to consultant; and IT technical knowledge transfers from consultant to client. However, when interdisciplinary teams are involved in Agile IT projects, the knowledge transfer mentioned before remains inefficient once the knowledge loss persists throughout the project life cycle. The conversion of conceptual knowledge, which only exists in the brains and minds of individuals, into explicit knowledge is essential for organizations to gain and maintain competitive advantages over its competitor. This study proposes an alternative conceptual framework to address conceptual knowledge transfer in IT projects that use Agile methodology.
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2021 |
de Castro RO, Sanin C, Szczerbicki E, Levula A, 'Where Did Knowledge Management Go?: A Comprehensive Survey', Cybernetics and Systems, 52 461-476 (2021) [C1]
Knowledge Management (KM) research outputs have been expanding exponentially in the past years, generating diversified topics, which lack integration and classification. It has be... [more]
Knowledge Management (KM) research outputs have been expanding exponentially in the past years, generating diversified topics, which lack integration and classification. It has been challenging for experts to classify KM because of its versatile open fields, and in our view, it contributes to the technocratic approach remaining behind the organizational approach. This paper highlights a way to classify KM publications through a pattern that will support technocratic developments representing knowledge in a more explicit form. This study uses a classification method that uses a template in a taxonomy shape, executing some procedures and allowing an accurate identification and organization of KM research outputs. The proposed taxonomy method is proven on a set of 150 different KM publications from the last 15years. This scheme is grouped into two main categories: Conceptual and Empirical which could enable academics and practitioners alike to better understand the current gaps that are prevalent in KM.
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2021 |
Bakhtari AR, Waris MM, Sanin C, Szczerbicki E, 'Evaluating Industry 4.0 Implementation Challenges Using Interpretive Structural Modeling and Fuzzy Analytic Hierarchy Process', Cybernetics and Systems, 52 350-378 (2021) [C1]
The fourth industrial revolution known as Industry 4.0 is reshaping and evolving the way industries produce products and individuals live and work therefore, gaining massive attra... [more]
The fourth industrial revolution known as Industry 4.0 is reshaping and evolving the way industries produce products and individuals live and work therefore, gaining massive attraction from academia, business, and politics. The manufacturing industries are optimistic regarding the opportunities that Industry 4.0 may offer such as improved efficiency, productivity and customization. The present research contributes to the Industry 4.0 literature by identifying, modeling, analyzing, and prioritizing the challenges in implementing Industry 4.0 in manufacturing industries. In doing so, the article first introduces the interpretive structural modeling (ISM) to develop the hierarchical relationships among the challenges and analyzes their mutual interactions. Further, ¿Matrice d¿Impacts Croises Multiplication Appliquee aun Classement¿ (MICMAC) analysis is used to categorize the challenges into four categories, namely autonomous, driver, dependent, and linkage based on their driving power and dependence power. Moreover, fuzzy analytic hierarchy process (F-AHP) methodology is used to prioritize the challenges based on three criteria: driving power, dependence power, and change management. The hierarchical model developed through ISM methodology shows that ¿lack of vision and leadership from top management (C12), lack of skills training program and education (C2), and uncertainty of return on investment (C9)¿ are the major challenges in implementing Industry 4.0 in manufacturing industries. The findings of F-AHP analysis suggest that ¿lack of vision and leadership from top management (C12), lack of skilled workforce (C3), lack of skills training program and education (C2), and uncertainty of return on investment (C9)¿ are some of the major challenges of implementing Industry 4.0. Finally, the obtained results show how challenges affect other so that to uncover the root cause triggering the other challenges. The industrial practitioners and managers can then take advantage of these analyses to know which challenge acts as the main barrier in implementing Industry 4.0 and to be focused first in order to reach a solution.
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Nova |
2021 |
Sohail N, Anwar SM, Majeed F, Sanin C, Szczerbicki E, 'Smart Approach for Glioma Segmentation in Magnetic Resonance Imaging using Modified Convolutional Network Architecture (U-NET)', Cybernetics and Systems, 52 445-460 (2021) [C1]
Segmentation of a brain tumor from magnetic resonance multimodal images is a challenging task in the field of medical imaging. The vast diversity in potential target regions, appe... [more]
Segmentation of a brain tumor from magnetic resonance multimodal images is a challenging task in the field of medical imaging. The vast diversity in potential target regions, appearance and multifarious intensity threshold levels of various tumor types are few of the major factors that affect segmentation results. An accurate diagnosis and its treatment demand strict delineation of the tumor affected tissues. Herein, we focus on a smart, automated, and robust segmentation approach for brain tumor using a modified 3D U-Net architecture. The pre-operative multimodal 3D-MRI scans of High-Grade Glioma (HGG) and Low-Grade Glioma (LGG) are used as data. Our proposed approach solves the problem of memory and system resource constraints by robustly applying dense network training on image patches of 3D volumes. It improves the border region artifact detection by applying convolutions at an appropriate phase in the proposed neural network. Multi-class imbalance data are handled by using Categorical Cross Entropy (CCE) loss developed by combining the Weighted Cross Entropy (WCE) with Weighted Multi-class Dice Loss (WMDL) functions, which enables the network to perform smart segmentation of the smaller tumorous regions. The proposed approach is tested and evaluated for the challenge datasets of multimodal MRI volumes of tumor patients. Experiments are performed to compute the average dice scores on BraTS-2019 and BraTS-2020 datasets for the whole tumor region.
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Nova |
2021 |
Ahmed MB, Majeed F, Sanin C, Szczerbicki E, 'Experience-Based Product Inspection Planning for Industry 4.0', Cybernetics and Systems, 52 296-312 (2021) [C1]
In this paper we describe how our Smart Virtual Product Development (SVPD) system can be used to enhance product inspection planning. The SVPD system is comprised of three main mo... [more]
In this paper we describe how our Smart Virtual Product Development (SVPD) system can be used to enhance product inspection planning. The SVPD system is comprised of three main modules, these being the design knowledge management (DKM) module, the manufacturing capability and process planning (MCAPP) module, and the product inspection planning (PIP) module. Experiential knowledge relating to formal decisional events is collected, stored and used by the system in the form of set of experiences (SOEs). Here we discuss the working mechanism of the PIP module and show how experiential knowledge relating to the inspection of products that have features and functions in common can be used to enhance product inspection planning during early stages of product development. Our discussion commences with an introduction to fundamental concepts and a general system overview. We then describe the development of our SVPD system¿s PIP module, and a case study we undertook for validation purposes. Results of the case study show that our system is capable of supporting product inspection planning in smart manufacturing, and thus has a vital role to play in Industry 4.0.
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Nova |
2020 |
de Oliveira CS, Giustozzi F, Zanni-Merk C, Sanin C, Szczerbicki E, 'Stream Reasoning to Improve Decision-Making in Cognitive Systems', Cybernetics and Systems, 51 214-231 (2020) [C1]
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Nova |
2020 |
Ahmed MB, Majeed F, Sanin C, Szczerbicki E, 'Smart virtual product development (SVPD) system to support product inspection planning in industry 4.0', Procedia Computer Science, 176 2596-2604 (2020) [C1]
This paper presents the idea of supporting product inspection planning process during the early stages of product life cycle for the experts working on product development. Aim of... [more]
This paper presents the idea of supporting product inspection planning process during the early stages of product life cycle for the experts working on product development. Aim of this research is to assist a collaborative product development process by using Smart Virtual Product Development (SVPD) system, which is based on Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA). The proposed system is developed to support three key aspects of industrial product development i.e. design, manufacturing, and product inspection. Therefore, it comprises of three main modules; design knowledge management (DKM), manufacturing capability and process planning (MCAPP), and product inspection planning (PIP). It collects, stores, and uses experiential knowledge from formal decisional events in the form of set of experience (SOE). This research enlightens the working mechanism of the PIP module, and shows how experiential knowledge related to product inspection can be used during the early stages of product development process. This experiential knowledge is extracted and stored from similar products having some common features and functions. First, the basic description and principles of the approach are introduced, then the prototype version of the system is developed and tested for product inspection planning (PIP) module for the case study, which verifies the feasibility of the proposed approach. The presented system successfully supports smart manufacturing and can play a vital role in Industry 4.0.
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Nova |
2020 |
Zhang H, Li F, Wang J, Wang Z, Shi L, Sanin C, Szczerbicki E, 'The Neural Knowledge DNA Based Smart Internet of Things', CYBERNETICS AND SYSTEMS, 51 258-264 (2020) [C1]
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Nova |
2020 |
Zhang H, Li F, Wang J, Zhou Y, Sanin C, Szczerbicki E, 'Experience-Based Cognition for Driving Behavioral Fingerprint Extraction', CYBERNETICS AND SYSTEMS, 51 103-114 (2020) [C1]
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Nova |
2020 |
Ahmed MB, Majeed F, Sanin C, Szczerbicki E, 'Enhancing Product Manufacturing through Smart Virtual Product Development (SVPD) for Industry 4.0', CYBERNETICS AND SYSTEMS, 51 246-257 (2020) [C1]
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Nova |
2020 |
Shafiq SI, Sanin C, Szczerbicki E, 'Knowledge-Based Virtual Modeling and Simulation of Manufacturing Processes for Industry 4.0', CYBERNETICS AND SYSTEMS, 51 84-102 (2020) [C1]
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Nova |
2019 |
Oliveira CSD, Sanin C, Szczerbicki E, 'Visual content representation and retrieval for cognitive cyber physical systems', Procedia Computer Science, 159 2249-2257 (2019) [C1]
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Nova |
2019 |
Shafiq SI, Szczerbicki E, Sanin C, 'Proposition of the methodology for Data Acquisition, Analysis and Visualization in support of Industry 4.0', Procedia Computer Science, 159 1976-1985 (2019) [E1]
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Nova |
2019 |
Ahmed MB, Sanin C, Szczerbicki E, 'Smart virtual product development (SVPD) to enhance product manufacturing in industry 4.0', Procedia Computer Science, 159 2232-2239 (2019) [C1]
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Nova |
2019 |
Bilal Ahmed M, Imran Shafiq S, Sanin C, Szczerbicki E, 'Towards Experience-Based Smart Product Design for Industry 4.0', Cybernetics and Systems, 50 165-175 (2019) [C1]
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Nova |
2019 |
Waris MM, Sanin C, Szczerbicki E, 'Establishing intelligent enterprise through community of practice for product innovation', Journal of Intelligent and Fuzzy Systems, 37 7169-7178 (2019) [C1]
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Nova |
2019 |
Shafiq SI, Szczerbicki E, Sanin C, 'Decisional-DNA Based Smart Production Performance Analysis Model', CYBERNETICS AND SYSTEMS, 50 154-164 (2019) [C1]
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Nova |
2019 |
Silva de Oliveira C, Sanin C, Szczerbicki E, 'Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)', Cybernetics and Systems, 50 197-207 (2019) [C1]
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Nova |
2019 |
Shafiq SI, Szczerbicki E, Sanin C, 'Decisional DNA based intelligent knowledge model for flexible manufacturing system', Journal of Intelligent and Fuzzy Systems, 37 7155-7167 (2019) [C1]
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Nova |
2019 |
Bilal Ahmed M, Sanin C, Shafiq SI, Szczerbicki E, 'Experience based decisional DNA to support smart product design', Journal of Intelligent and Fuzzy Systems, 37 7179-7187 (2019) [C1]
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Nova |
2019 |
Li F, Zhang H, Gao L, Wang J, Sanin C, Szczerbicki E, 'A Set of Experience-Based Smart Synergy Security Mechanism in Internet of Vehicles', CYBERNETICS AND SYSTEMS, 50 230-237 (2019) [C1]
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Nova |
2019 |
Sanin C, Zhang H, Shafiq I, Waris MM, de Oliveira CS, Szczerbicki E, 'Experience based knowledge representation for Internet of Things and Cyber Physical Systems with case studies', FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 92 604-616 (2019) [C1]
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Nova |
2018 |
de Oliveira CS, Sanin C, Szczerbicki E, 'Flexible Knowledge Vision Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning', Cybernetics and Systems, 49 355-367 (2018) [C1]
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Nova |
2018 |
Ahmed MB, Sanin C, Szczerbicki E, 'Experience-Based Decisional DNA (DDNA) to Support Product Development', Cybernetics and Systems, 49 399-411 (2018) [C1]
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Nova |
2018 |
Shafiq SI, Szczerbicki E, Sanin C, 'Manufacturing Data Analysis in Internet of Things/Internet of Data (IoT/IoD) Scenario', Cybernetics and Systems, 49 280-295 (2018) [C1]
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Nova |
2018 |
Waris MM, Sanin C, Szczerbicki E, 'Smart Innovation Engineering: Toward Intelligent Industries of the Future', Cybernetics and Systems, 49 339-354 (2018) [C1]
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Nova |
2018 |
De Oliveira CS, Sanin C, Szczerbicki E, 'Contextual Knowledge to Enhance Workplace Hazard Recognition and Interpretation in a Cognitive Vision Platform', Procedia Computer Science, 126 1837-1846 (2018) [C1]
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Nova |
2018 |
Souza Alves TD, De Oliveira CS, Sanin C, Szczerbicki E, 'From Knowledge based Vision Systems to Cognitive Vision Systems: A Review', Procedia Computer Science, 126 1855-1864 (2018) [C1]
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Nova |
2018 |
Li F, Zhang H, Wang J, Liu Y, Gao L, Xu X, et al., 'Toward Intelligent Vehicle Intrusion Detection Using the Neural Knowledge DNA', CYBERNETICS AND SYSTEMS, 49 412-419 (2018) [C1]
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Nova |
2017 |
Shafiq SI, Sanin C, Szczerbicki E, Toro C, 'Towards an experience based collective computational intelligence for manufacturing', FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 66 89-99 (2017) [C1]
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Nova |
2017 |
Waris MM, Sanin C, Szczerbicki E, Shafiq SI, 'A Semiautomatic Experience-Based Tool for Solving Product Innovation Problem', CYBERNETICS AND SYSTEMS, 48 231-248 (2017) [C1]
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Nova |
2017 |
Zhang H, Li F, Wang J, Wang Z, Shi L, Zhao J, et al., 'Adding Intelligence to Cars Using the Neural Knowledge DNA', CYBERNETICS AND SYSTEMS, 48 267-273 (2017) [C1]
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Nova |
2017 |
Zhang H, Sanin C, Szczerbicki E, Zhu M, 'Towards neural knowledge DNA', JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 32 1575-1584 (2017) [C1]
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Nova |
2017 |
Waris MM, Sanin C, Szczerbicki E, 'Smart innovation process enhancement using soeks and decisional dna', Journal of Information and Telecommunication, 1 290-303 (2017)
Product innovation always requires a foundation based on both knowledge and experience. The production and innovation process of products is very similar to the evolution process ... [more]
Product innovation always requires a foundation based on both knowledge and experience. The production and innovation process of products is very similar to the evolution process of humans. The genetic information of humans is stored in genes, chromosomes and DNA. Similarly, the information about the products can be stored in a system having virtual genes, chromosomes and decisional DNA (DDNA). The present paper proposes a semi-automatic system that facilitates product innovation process using a Smart Knowledge Management System comprising Set of Experience Knowledge Structure and DDNA. This system is called Smart Innovation Engineering System. Through this system, entrepreneurs and organizations will be able to perform the product innovation process technically and quickly, as it stores knowledge in the form of experiences of the past innovative decisions taken. This proposed system is dynamic in nature as it updates itself every time a decision is taken.
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2017 |
Zhang H, Li F, Wang J, Wang Z, Sanin C, Szczerbicki E, 'Experience-Oriented Intelligence for Internet of Things', CYBERNETICS AND SYSTEMS, 48 162-181 (2017) [C1]
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Nova |
2017 |
Sanin C, Shafiq I, Waris MM, Toro C, Szczerbicki E, 'Manufacturing collective intelligence by the means of Decisional DNA and virtual engineering objects, process and factory', JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 32 1585-1599 (2017) [C1]
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Nova |
2016 |
Zhang H, Sanin C, Szczerbicki E, 'When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing', Cybernetics and Systems, 47 140-148 (2016) [C1]
In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine... [more]
In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domains past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest neighbors), logistic regression, and AdaBoost in classification tasks, and the results show that our approach is very promising with regard to the enhancement of the accuracy of knowledge-based predictions required in complex decision-making problems.
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Nova |
2016 |
Waris MM, Sanin C, Szczerbicki E, 'Toward Smart Innovation Engineering: Decisional DNA-Based Conceptual Approach', Cybernetics and Systems, 47 149-159 (2016) [C1]
Knowledge and experience are essential requirements for product innovation. The presented paper proposes a systematic approach for product innovation support using a Smart Knowled... [more]
Knowledge and experience are essential requirements for product innovation. The presented paper proposes a systematic approach for product innovation support using a Smart Knowledge Management System comprising a Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA). This proposed system is dynamic in nature because it updates itself every time a new decision related to innovation is made. Through this system, the product innovation process can be performed semiautomatically and efficiently because it stores knowledge of past experiences of innovative decisions.
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Nova |
2016 |
Shafiq SI, Sanin C, Szczerbicki E, Toro C, 'Virtual Engineering Factory: Creating Experience Base for Industry 4.0', Cybernetics and Systems, 47 32-47 (2016) [C1]
In recent times, traditional manufacturing is upgrading and adopting Industry 4.0, which supports computerization of manufacturing by round-the-clock connection and communication ... [more]
In recent times, traditional manufacturing is upgrading and adopting Industry 4.0, which supports computerization of manufacturing by round-the-clock connection and communication of engineering objects. Consequently, Decisional DNA-based knowledge representation of manufacturing objects, processes, and system is achieved by virtual engineering objects (VEO), virtual engineering processes (VEP), and virtual engineering factories (VEF), respectively. In this study, assimilation of VEO-VEP-VEF concept in the Cyber-physical system-based Industry 4.0 is proposed. The planned concept is implemented on a case study. Also, Decisional DNA features such as similarity identification and phenotyping are explored for validation. It is concluded that this approach can support Industry 4.0 and can facilitate in real time critical, creative, and effective decision making.
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Nova |
2016 |
Shafiq SI, Sanin C, Toro C, Szczerbicki E, 'Virtual engineering process (VEP): a knowledge representation approach for building bio-inspired distributed manufacturing DNA', International Journal of Production Research, 54 7129-7142 (2016) [C1]
The objective of this research is to provide a user-friendly and effective way of representing engineering processes for distributed manufacturing systems so that they can develop... [more]
The objective of this research is to provide a user-friendly and effective way of representing engineering processes for distributed manufacturing systems so that they can develop, accumulate and share knowledge. The basic definition and principle of the approach is introduced first and then the prototype version of the system is developed and demonstrated with case studies, which verify the feasibility of the proposed approach. This paper proposes a novel concept of virtual engineering process (VEP), which is experience-based knowledge representation of engineering processes. VEP is an extension of our previous work on virtual engineering object (VEO). VEP model includes complete process knowledge required to manufacture a component. This knowledge is captured from three distinctive aspects related to manufacturing. First, information about the manufacturing operations involved. Second, information about the resources/machines required to perform operations and third, information about process level decisions that are taken. It also aims to combine/share experience of engineering objects, manufacturing processes, and systems. It applies bio-inspired knowledge engineering approach called decisional DNA and set of experience-based knowledge representation.
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Nova |
2015 |
Sanchez E, Toro C, Grana M, Sanin C, Szczerbicki E, 'Extended Reflexive Ontologies for the Generation of Clinical Recommendations', CYBERNETICS AND SYSTEMS, 46 4-18 (2015) [C1]
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Nova |
2015 |
Shafiq SI, Sanin C, Toro C, Szczerbicki E, 'Virtual Engineering Object (VEO): Toward Experience-Based Design and Manufacturing for Industry 4.0', CYBERNETICS AND SYSTEMS, 46 35-50 (2015) [C1]
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Nova |
2015 |
Zhang H, Sanin C, Szczerbicki E, 'Applying Decisional DNA to Internet of Things: The Concept and Initial Case Study', CYBERNETICS AND SYSTEMS, 46 84-93 (2015) [C1]
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Nova |
2015 |
Wang P, Sanin C, Szczerbicki E, 'Evolutionary algorithm and decisional DNA for multiple travelling salesman problem', Neurocomputing, 150 50-57 (2015) [C1]
In the real world, it is common to face optimization problems that have two or more objectives that must be optimized at the same time, that are typically explained in different u... [more]
In the real world, it is common to face optimization problems that have two or more objectives that must be optimized at the same time, that are typically explained in different units, and are in conflict with one another. This paper presents a hybrid structure that combines set of experience knowledge structures (SOEKS) and evolutionary algorithms, NSGA-II (Non-dominated Sorting Genetic Algorithm II), to solve multiple optimization problems. The proposed structure uses experience that is derived from a former decision event to improve the evolutionary algorithm's ability to find optimal solutions rapidly and efficiently. It is embedded in a smart experience-based data analysis system (SEDAS) introduced in the paper. Experimental illustrative results of SEDAS application to solve a travelling salesman problem show that our new proposed hybrid model can find optimal or close to true Pareto-optimal solutions in a fast and efficient way.
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Nova |
2015 |
Zambrano A, Toro C, Nieto M, Sotaquirá R, Sanín C, Szczerbicki E, 'Video semantic analysis framework based on run-time production rules - Towards cognitive vision', Journal of Universal Computer Science, 21 856-870 (2015) [C1]
This paper proposes a service-oriented architecture for video analysis which separates object detection from event recognition. Our aim is to introduce new tools to be considered ... [more]
This paper proposes a service-oriented architecture for video analysis which separates object detection from event recognition. Our aim is to introduce new tools to be considered in the pathway towards Cognitive Vision as a support for classical Computer Vision techniques that have been broadly used by the scientific community. In the article, we particularly focus in solving some of the reported scalability issues found in current Computer Vision approaches by introducing an experience based approximation based on the Set of Experience Knowledge Structure (SOEKS). In our proposal, object detection takes place clientside, while event recognition takes place server-side. In order to implement our approach, we introduce a novel architecture that aims at recognizing events defined by a user using production rules (a part of the SOEKS model) and the detections made by the client using their own algorithms for visual recognition. In order to test our methodology, we present a case study, showing the scalability enhancements provided.
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Nova |
2015 |
Shafiq SI, Sanin C, Szczerbicki E, Toro C, 'Virtual engineering objects: Effective way of knowledge representation and decision making', Studies in Computational Intelligence, 598 261-270 (2015) [C1]
This paper presents a knowledge representation case study by constructing Decisional DNA of engineering objects. Decisional DNA, as a knowledge representation structure not only o... [more]
This paper presents a knowledge representation case study by constructing Decisional DNA of engineering objects. Decisional DNA, as a knowledge representation structure not only offers great possibilities on gathering explicit knowledge of formal decision events but also it is a powerful tool for decision-making process. The concept of Virtual engineering Object (VEO), which is a knowledge and experience representation of engineering artefacts, is also discussed. In this paper, we present several Sets of Experience of engineering objects used in manufacturing that were collected for the construction of a VEO-chromosome within the VEO-Decisional DNA. VEO is used to enhance manufacturing systems with predicting capabilities, facilitating decision-making in engineering processes knowledge handling.
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Nova |
2014 |
Sanchez E, Toro C, Graña M, Sanín C, Szczerbicki E, 'Specification of extended reflexive ontologies in the context of CDSS', Studies in Health Technology and Informatics, 207 234-243 (2014) [C1]
Decision recommendations are a set of alternative options for clinical decisions (e.g. diagnosis, prognosis, treatment selection, follow-up and prevention) that are provided to de... [more]
Decision recommendations are a set of alternative options for clinical decisions (e.g. diagnosis, prognosis, treatment selection, follow-up and prevention) that are provided to decision makers by knowledge-based Clinical Decision Support Systems (k-CDSS) as aids. We propose to follow a reasoning over domain approach for the generation of decision recommendations, by gathering and inferring conclusions from production rules. In order to rationalize our approach we present a specification that will sustain the logic models supported in the Knowledge Bases we use for persistence. We introduce first the underlying knowledge model and then the necessary extensions that will convey towards the solution of the reported needs. The starting point of our approach is the work of Toro et al. [13] on Reflexive Ontologies (RO). We also propose an extension of RO, by including the handling and reasoning that production rules provide. Our approach speeds-up the recommendation generation process.
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Nova |
2014 |
Sanchez E, Peng W, Toro C, Sanin C, Graña M, Szczerbicki E, et al., 'Decisional DNA for modeling and reuse of experiential clinical assessments in breast cancer diagnosis and treatment', Neurocomputing, 146 308-318 (2014) [C1]
Clinical Decision Support Systems (CDSS) are active knowledge resources that use patient data to generate case specific advice. The fast pace of change of clinical knowledge impos... [more]
Clinical Decision Support Systems (CDSS) are active knowledge resources that use patient data to generate case specific advice. The fast pace of change of clinical knowledge imposes to CDSS the continuous update of the domain knowledge and decision criteria. Traditional approaches require costly tedious manual maintenance of the CDSS knowledge bases and repositories. Often, such an effort cannot be assumed by medical teams, hence maintenance is often faulty. In this paper, we propose a (semi-)automatic update process of the underlying knowledge bases and decision criteria of CDSS, following a learning paradigm based on previous experiences, such as the continuous learning that clinicians carry out in real life. In this process clinical decisional events are acquired and formalized inside the system by the use of the SOEKS and Decisional DNA experiential knowledge representation techniques. We propose three algorithms processing clinical experience to: (a) provide a weighting of the different decision criteria, (b) obtain their fine-tuning, and (c) achieve the formalization of new decision criteria. Finally, we present an implementation instance of a CDSS for the domain of breast cancer diagnosis and treatment. © 2014 Elsevier B.V.
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Nova |
2014 |
Shafiq SI, Sanín C, Szczerbicki E, 'Set of experience knowledge structure (SOEKS) and decisional DNA (DDNA): Past, present and future', Cybernetics and Systems, 45 200-215 (2014) [C1]
This article reviews research work on set of experience knowledge structure (SOEKS)-decisional DNA (DDNA) done in the past, ongoing, and planned for the future. Firstly, the conce... [more]
This article reviews research work on set of experience knowledge structure (SOEKS)-decisional DNA (DDNA) done in the past, ongoing, and planned for the future. Firstly, the concept of the knowledge representation technique of SOEKS-DDNA is discussed, and then an attempt is made to organize the past research related with it in chronological order. This work focuses on the review on SOEKS-DDNA, its application in different domains, the various implementation platforms, as well as its benefits and its limitations. The second part of this article provides an idea of the SOEKS-DDNA-related research endeavors currently carried out by us and the last part is a sneak peek into our planned future work. © 2014 Copyright Taylor & Francis Group, LLC.
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Nova |
2014 |
Calad-Alvarez A, Mejia-Gutierrez R, Sanin CM, Szczerbicki E, 'Smart experience engineering to support collaborative design problems based on constraints modelling', JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 27 655-666 (2014) [C1]
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Nova |
2013 |
Sanchez E, Toro C, Artetxe A, Grana M, Sanin C, Szczerbicki E, et al., 'Bridging challenges of clinical decision support systems with a semantic approach. A case study on breast cancer', PATTERN RECOGNITION LETTERS, 34 1758-1768 (2013) [C1]
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Nova |
2013 |
Mancilla-Amaya L, Szczerbicki E, Sanin C, 'A PROPOSAL FOR A KNOWLEDGE MARKET BASED ON QUANTITY AND QUALITY OF KNOWLEDGE', CYBERNETICS AND SYSTEMS, 44 118-132 (2013) [C1]
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Nova |
2013 |
Wang P, Sanin C, Szczerbicki E, 'PREDICTION BASED ON INTEGRATION OF DECISIONAL DNA AND A FEATURE SELECTION ALGORITHM RELIEF-F', CYBERNETICS AND SYSTEMS, 44 173-183 (2013) [C1]
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Nova |
2013 |
Artetxe A, Sanchez E, Toro C, Sanín C, Szczerbicki E, Graña M, Posada J, 'Impact of reflexive ontologies in semantic clinical decision support systems', Cybernetics and Systems, 44 187-203 (2013) [C1]
Ontology processing is arguably a time-consuming process with high associated computational costs. Query actions constitute a crucial part of the reasoning process and are a prima... [more]
Ontology processing is arguably a time-consuming process with high associated computational costs. Query actions constitute a crucial part of the reasoning process and are a primary source of time consumption. Reflexive ontologies (ROs) is a novel approach intended to reduce time consumption problems while providing a fast reaction from ontology-based applications. In this article we present the implementation of a knowledge-based clinical decision support system (CDSS) for the diagnosis of Alzheimer's disease, which was the benchmark used to evaluate the impact of RO in the overall performance of the system. The implementation details and the definition of the implementation methodology are exposed in this article, along with the results of the evaluation. Some novel techniques that aim to optimize the performance of ROs are also presented with highlights of the test application introduced in our previous work. © 2013 Taylor & Francis Group, LLC.
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Nova |
2013 |
Zhang H, Sanín C, Szczerbicki E, 'Implementing fuzzy logic to generate user profile in decisional dna television: The concept and initial case study', Cybernetics and Systems, 44 275-283 (2013) [C1]
In this article, we present a concept and case study of a novel approach that generates a television (TV) user's profile utilizing principles of fuzzy logic. A user profile r... [more]
In this article, we present a concept and case study of a novel approach that generates a television (TV) user's profile utilizing principles of fuzzy logic. A user profile refers to the user's basic information, such as gender, age, and profession. The generated profile has the potential to significantly improve Digital TV (DTV), making the service smarter and more user friendly. We apply the proposed approach to our previous work that introduced decisional DNA TV, which enables TV broadcasters to suggest program choices based upon the user's past viewing habits. Decisional DNA is a domain-independent, flexible, and standard experiential knowledge repository solution that allows for knowledge to be acquired, reused, evolved, and shared in an easy and portable way. The presented conceptual approach demonstrates how fuzzy logic methods can be deployed within DNA TV through an experimental implementation that generates a user profile by capturing viewing habits. © 2013 Taylor & Francis Group, LLC.
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Nova |
2012 |
Mancilla Amaya LE, Maldonado Sanin CA, Szczerbicki E, 'Quality assessment of experiential knowledge', Cybernetics and Systems, 43 96-113 (2012) [C1]
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Nova |
2012 |
Mancilla Amaya LE, Szczerbicki E, Maldonado Sanin CA, 'Estimating knowledge quantity in the e-decisional community', Cybernetics and Systems, 43 276-291 (2012) [C1]
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Nova |
2012 |
Maldonado Sanin CA, Mancilla Amaya LE, Zhang H, Szczerbicki E, 'Decisional DNA: The Concept and Its Implementation Platforms', Cybernetics and Systems, 43 67-80 (2012) [C1]
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Nova |
2012 |
Toro C, Sanchez E, Carrasco E, Mancilla Amaya LE, Maldonado Sanin CA, Szczerbicki E, et al., 'Using set of experience knowledge structure to extend a rule set of clinical decision support system for Alzheimer's disease diagnosis', Cybernetics and Systems, 43 81-95 (2012) [C1]
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Nova |
2012 |
Toro C, Vaquero J, Grana M, Maldonado Sanin CA, Szczerbicki E, Posada J, 'Building domain ontologies from engineering standards', Cybernetics and Systems, 43 114-126 (2012) [C1]
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Nova |
2012 |
Wang P, Maldonado Sanin CA, Szczerbicki E, 'Introducing the concept of decisional DNA-based web content mining', Cybernetics and Systems, 43 136-142 (2012) [C1]
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Nova |
2012 |
Zhang H, Maldonado Sanin CA, Szczerbicki E, 'Making digital TV smarter: Capturing and reusing experience in digital TV', Cybernetics and Systems, 43 127-135 (2012) [C1]
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Nova |
2012 |
Zhang H, Sanin C, Szczerbicki E, 'The Development of Decisional DNA DIGITAL TV', ADVANCES IN KNOWLEDGE-BASED AND INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, 243 1500-1508 (2012)
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2012 |
Wang P, Sanin C, Szczerbicki E, 'Decisional DNA with Embedded RELIEF-F and Linear Regression for Knowledge and Experience Management', ADVANCES IN KNOWLEDGE-BASED AND INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, 243 1531-1542 (2012)
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2012 |
Maldonado Sanin CA, Toro C, Zhang H, Sanchez E, Szczerbicki E, Carrasco E, et al., 'Decisional DNA: A multi-technology shareable knowledge structure for decisional experience', Neurocomputing, 88 42-53 (2012) [C1]
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Nova |
2011 |
Zuluaga GG, Maldonado Sanin CA, Szczerbicki E, 'Smart decision infrastructure: Architecture discussion', Cybernetics and Systems, 42 139-155 (2011) [C1]
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Nova |
2010 |
Zhang H, Sanin C, Szczerbicki E, 'Decisional DNA-based embedded systems: A new perspective', Systems Science, 36 21-26 (2010) [C1]
Nowadays, knowledge-based embedded systems have become a new trend on embedded systems. They are capable of knowledge acquisition, reusing, evolving and sharing. However, due to t... [more]
Nowadays, knowledge-based embedded systems have become a new trend on embedded systems. They are capable of knowledge acquisition, reusing, evolving and sharing. However, due to the lack of standardized solutions and development platforms, it is not only very hard to share knowledge among different knowledge-based embedded systems, but this also causes huge waste by redesign, redevelopment, and knowledge re-acquiring. In this paper, we propose the Decisional DNA-based Embedded Systems as a new approach to meet this demand. Decisional DNA is a domain-independent, flexible and standard knowledge representation structure. We apply Decisional DNA to embedded systems to make them acquire, reuse, evolve and share knowledge in an easy and standard way. As a result, we propose the features, architecture and application types for the embedded systems.
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2010 |
Mancilla-Amaya L, Sanín C, Szczerbicki E, 'A proposal for knowledge sharing in the E-Decisional Community using decisional DNA', Systems Science, 36 13-19 (2010) [C1]
The E-Decisional Community is a proposal that aims at enabling knowledge sharing between individuals and organizations, using the Set of Experience Knowledge Structure (SOEKS) and... [more]
The E-Decisional Community is a proposal that aims at enabling knowledge sharing between individuals and organizations, using the Set of Experience Knowledge Structure (SOEKS) and Decisional DNA as knowledge representations; it is based upon principles from Software Agents, Grid and Cloud computing. In this paper, we present an analysis of different agent communication and knowledge representation languages, with the purpose of defining a set of basic mechanisms to be used in the E-Decisional Community for knowledge exchange between its members.
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2010 |
Mancilla Amaya LE, Maldonado Sanin CA, Szczerbicki E, 'Smart knowledge-sharing platform for e-decisional community', Cybernetics and Systems, 41 17-30 (2010) [C1]
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Nova |
2010 |
Mancilla Amaya LE, Maldonado Sanin CA, Szczerbicki E, 'Using human behavior to develop knowledge-based virtual organizations', Cybernetics and Systems, 41 577-591 (2010) [C1]
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Nova |
2010 |
Zhang H, Maldonado Sanin CA, Szczerbicki E, 'Gaining knowledge through experience: Developing decisional DNA applications in robotics', Cybernetics and Systems, 41 628-637 (2010) [C1]
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Nova |
2009 |
Toro C, Graña M, Posada J, Sanín C, Szczerbicki E, 'An architecture for the semantic enhancement of virtual engineering applications', Studies in Computational Intelligence, 252 175-195 (2009) [C2]
Virtual Engineering (VE) is defined as the integration of geometric models and related engineering tools (such as analysis, simulation, optimization and decision-making, etc), wit... [more]
Virtual Engineering (VE) is defined as the integration of geometric models and related engineering tools (such as analysis, simulation, optimization and decision-making, etc), within a computerized environment that facilitates multidisciplinary and collaborative product development [1]. The focus of Virtual Engineering is to engage the human capacity for evaluation of complex systems and situations [2]. In this article, we present an architecture for the Semantic enhancement of Virtual Engineering Applications (VEA) through their embedded Virtual Engineering Tools. Our architecture follows a User-Intention-Domain schema and makes use of state of the art technologies like the Set of Experience Knowledge Structure and the Reflexive Ontologies in order to offer a better User experience with VEA. The main advantages of using Semantics in VEA can be summarized are: (i) an improved information and embedded Knowledge management, (ii) Enhancements in the search, knowledge and information sharing processes during the use of the VEA, (iii) The use of the intrinsic Knowledge embedded in the elements being described by the VEA and (iv) the empowerment of the User's knowledge and embedding of such knowledge in a structured and explicit conceptualization. © 2009 Springer-Verlag Berlin Heidelberg.
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2009 |
Sanín C, Mancilla-Amaya L, Szczerbicki E, Cayfordhowell P, 'Application of a multi-domain knowledge structure: The decisional DNA', Studies in Computational Intelligence, 252 65-86 (2009) [C2]
Knowledge engineering techniques are becoming useful and popular components of hybrid integrated systems used to solve complicated practical problems in different disciplines. Kno... [more]
Knowledge engineering techniques are becoming useful and popular components of hybrid integrated systems used to solve complicated practical problems in different disciplines. Knowledge engineering techniques offer features such as: learning from experience, handling noisy and incomplete data, helping with decision making, and predicting. This chapter presents the application of a knowledge structure to different fields of study by constructing Decisional DNA. Decisional DNA, as a knowledge representation structure, offers great possibilities on gathering explicit knowledge of formal decision events as well as a tool for decision making processes. Its versatility is shown in this chapter when applied to decisional domains in finances and energy. The main advantages of using the Decisional DNA rely on: (i) versatility and dynamicity of the knowledge structure, (ii) storage of day-to-day explicit experience in a single structure, (iii) transportability and share ability of the knowledge, and (iv) predicting capabilities based on the collected experience. Thus, after showing the results, we conclude that the Decisional DNA, as a unique structure, can be applied to multi-domain systems while enhancing predicting capabilities and facilitating knowledge engineering processes inside decision making systems. © 2009 Springer-Verlag Berlin Heidelberg.
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2009 |
Maldonado Sanin CA, Szczerbicki E, 'Experience-based knowledge representation: SOEKS', Cybernetics and Systems, 40 99-122 (2009) [C1]
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Nova |
2009 |
Maldonado Sanin CA, Szczerbicki E, 'Implementing decisional trust: A first approach for smart reliable systems', Cybernetics and Systems, 40 85-98 (2009) [C1]
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Nova |
2008 |
Maldonado Sanin CA, Szczerbicki E, 'Toward decisional DNA: Developing holistic set of experience knowledge structure', Foundations of Control and Management Sciences, - 109-122 (2008) [C2]
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Nova |
2008 |
Toro C, Maldonado Sanin CA, Szczerbicki E, Posada J, 'Reflexive ontologies: Enhancing ontologies with self-contained queries', Cybernetics and Systems, 39 171-189 (2008) [C1]
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Nova |
2008 |
Maldonado Sanin CA, Szczerbicki E, Toro C, 'Combining technologies to achieve decisional trust', Cybernetics and Systems, 39 743-752 (2008) [C1]
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2007 |
Maldonado Sanin CA, Szczerbicki E, Toro C, 'An OWL ontology of set of experience knowledge structure', Journal of Universal Computer Science, 13 209-223 (2007) [C1]
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2007 |
Maldonado Sanin CA, Toro C, Vaquero J, Szczerbicki E, Posada J, 'Implementing decisional DNA in industrial maintenance by a knowledge soupa extension', Systems Science, 33 61-68 (2007) [C1]
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2007 |
Maldonado Sanin CA, Szczerbicki E, 'Dissimilar sets of experience knowledge structure: A negotiation process for decisional DNA', Cybernetics and Systems, 38 455-473 (2007) [C1]
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2007 |
Maldonado Sanin CA, Szczerbicki E, 'Genetic algorithms for decisional DNA: Solving sets of experience knowledge structure', Cybernetics and Systems, 38 475-494 (2007) [C1]
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2007 |
Maldonado Sanin CA, Szczerbicki E, 'Towards the construction of decisional DNA: A set of experience knowledge structure java class within an ontology system', Cybernetics and Systems, 38 859-878 (2007) [C1]
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2006 |
Maldonado Sanin CA, Szczerbicki E, 'Using Set of Experience in the Process of Transforming Information into Knowledge', International Journal of Enterprise Information Systems, 2, No.2 45-62 (2006) [C1]
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Nova |
2006 |
Maldonado Sanin CA, Szczerbicki E, 'Extending set of experience knowledge structure into a transportable of language extensible markup language', Cybernetics and Systems, 37 97-117 (2006) [C1]
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2006 |
Maldonado Sanin CA, Szczerbicki E, 'Developing heterogeneous similarity metrics for knowledge administration', Cybernetics and Systems, 37 553-565 (2006) [C1]
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Nova |
2005 |
Maldonado Sanin CA, Szczerbicki E, 'Set of experience: a knowledge structure for formal decision events', Foundations of Control and Management Sciences, 3 95-113 (2005) [C1]
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