Journal of Intelligent & Fuzzy Systems - Volume 37, issue 6

Authors: Pinto, José Pedro | Viana, Paula

Article Type: Research Article

Abstract: The development of efficient methods for searching and browsing large assets of video content has been considered by the academia and content owners for long. Different approaches that range from manual structured annotations, to unstructured metadata collected from several sources, as well as multimedia processing for automatic description of the content, can be identified. The growth on the number of hours of video content put online in video sharing platforms has however shown that video retrieval is still quite inefficient as rich contextual data that describes the content is most of the times still not available. Additionally, metadata is usually …not linked to timed moments of content, making direct access to the most relevant moments not possible. In this paper, an approach for making web videos available in the YouTube platform more accessible is presented. The solution is based on a collaborative process presented as a game that enables collecting metadata from the crowd while implementing mechanisms that remove erroneous information usually encountered in this type of information. Metadata, exported to YouTube in the form of captions and descriptions, contributes to enhance video retrieval, guaranteeing a better user experience and exposure of the content. Show more

Keywords: Video tag, video retrieval, crowdsourcing, multimedia content annotation, gamification, social media, YouTube

DOI: 10.3233/JIFS-179333

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7207-7221, 2019

Authors: Jureczko, Marian | Nguyen, Ngoc Trung | Szymczyk, Marcin | Unold, Olgierd

Article Type: Research Article

Abstract: Defect prediction is a method of identifying possible locations of software defects without testing. Software tests can be laborious and costly thus one may expect defect prediction to be a first class citizen in software engineering. Nonetheless, the industry apparently does not see it that way as the level of practical usages is limited. The study describes the possible reasons of the low adoption and suggests a number of improvements for defect prediction, including a confusion matrix-based model for assessing the costs and gains. The improvements are designed to increase the level of practitioners acceptance of defect prediction by removing …the recognized by authors implementation obstacles. The obtained predictors showed acceptable performance. The results were processed through the suggested model for assessing the costs and gains and showed the potential of significant benefits, i.e. up to 90% of the overall cost of the considered test activities. Show more

Keywords: software metrics, software development process, defect prediction, re–open prediction, predicting feature defectiveness, defect prediction economy

DOI: 10.3233/JIFS-179334

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7223-7238, 2019

Authors: Czarnowski, Ireneusz | Jędrzejowicz, Piotr

Article Type: Research Article

Abstract: Class imbalance arises when the number of examples belonging to one class is much greater than the number of examples belonging to another. The discussed approach focuses on combining several techniques including data reduction and stacking with the aim of improving the performance of the machine classification in the case of imbalanced data. The paper proposes a cluster-based data reduction approach assuming that the instances are selected from a cluster, the data reduction is carried-out on instances belonging to the majority classes, and the aim of the instance selection is to reduce the imbalance ratio between the majority and minority …classes. The process of instance selection is carried out with using an agent-based population learning algorithm. To increase performance and generalization ability of the prototype-based machine learning classification it was decided to use the stacking technique. The proposed approach is validated experimentally using several benchmark datasets from the KEEL repository. Advantages and main features of the approach are discussed considering the results of the computational experiment. Show more

Keywords: Instance selection, clustering, stacking, imbalanced data, team of agents

DOI: 10.3233/JIFS-179335

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7239-7249, 2019

Authors: Phan, Huyen Trang | Nguyen, Ngoc Thanh | Tran, Van Cuong | Hwang, Dosam

Article Type: Research Article

Abstract: Sentiment analysis has been gaining importance in many applications such as recommendation systems, the decision making support and prediction models. Sentiment analysis helps to understand and evaluate public opinion regarding social events, product services, and political trends, especially the feelings expressed through comments by users in social networks such as Twitter, Facebook, and Instagram. There have been a lot of research attempts to address the tweets sentiment analysis problem with high accuracy, particularly in case of tweets that express a single sentiment towards a single object. However, the results of the classification are not highly accurate in cases such as …the following: a user expresses multiple sentiments towards a single object in a tweet; a user presents multiple sentiments towards multiple objects; and a user indicates a single sentiment towards multiple objects. Furthermore, the previous studies only analyze the sentiment of each tweet without considering the objects and the sentiment towards each object from an entire set of tweets. This study attempts to deal with the limitations of the previous methods; an approach is proposed herein, based on integrating the sentiment towards a particular object from all tweets related to that object. The proposed method focuses on determining the objects and indicating the sentiment towards the specific objects by combining the sentiments related to each object from the entire set of tweets. On experimental evaluation, the proposed method is observed to have achieved a fairly good result in terms of the error ratio and achieved information. Show more

Keywords: Sentiment-analysis, sentiment-integration, object-determination

DOI: 10.3233/JIFS-179336

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7251-7263, 2019

Authors: Nguyen, Van Tham | Nguyen, Ngoc Thanh | Tran, Trong Hieu

Article Type: Research Article

Abstract: In the stages of development of probabilistic expert systems, knowledge merging is a major concern. To deal with knowledge merging problems, several approaches have been put forward. However, in the proposed models, each original probabilistic knowledge base (PKB) is represented by a set of probabilistic functions fulfilling such knowledge base. The drawbacks of the solutions are that the output of model is also a set of probabilistic functions satisfying the resulting PKB and there is no algorithm for implementing the merging process of PKBs in which each of them consists of probabilistic constraints. In this paper, distance-based approach is utilized …to propose a new method of merging PKBs to ensure that both the input and output of methods are represented by sets of probabilistic constraints. To this aim, the relationship between the probability rules and the probabilistic constraints, and the several transformation methods for the representation of the original PKB are presented, a set of merging operators (MOs) is proposed, and several desirable logical properties are investigated and discussed. Several algorithms for merging PKBs are presented and the computational complexities of these algorithms are also analyzed and evaluated. Show more

Keywords: Probabilistic knowledge base, knowledge merging, merging operator, algorithm

DOI: 10.3233/JIFS-179337

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7265-7278, 2019

Authors: Nguyen, Van Du | Truong, Hai Bang | Merayo, Mercedes G. | Nguyen, Ngoc Thanh

Article Type: Research Article

Abstract: Recently, the use of the wisdom of crowds (WoC) for finding solutions to a wide range of real-life problems has dramatically expanded. Prior studies have revealed that diversity, independence, decentralization, and aggregation are the determinants of collective wisdom. However, these findings are often based on the so-called point estimates - single values are used as the representations of individual predictions on the task of estimating unknown quantities or predicting outcomes of future events. In some situations, interval values, which are often called interval estimates , can be used for such representations. Accordingly, one can provide an individual …prediction in the form of an interval value including a lower and an upper bounds. Taking into account this kind of representation, in this paper, we present a case study in which collectives of randomly selected predictions can outperform those of most accurate predictions. Then, we evaluate the WoC level by taking into account diversity and cardinality. The computational experiments have indicated that diversity is positively related to collective wisdom. Finally, we discuss some related theoretical and practical implications for further research. Show more

Keywords: Collective intelligence, wisdom of crowds, interval estimates

DOI: 10.3233/JIFS-179338

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7279-7289, 2019

Authors: Kozierkiewicz, Adrianna | Pietranik, Marcin | Sitarczyk, Mateusz

Article Type: Research Article

Abstract: Data integration is one of the trending topics in the modern computer science. It is not an uncommon task to deliver a unified perspective on a set of heterogenous data that would serve as a consensus of participating elements. Many computationally expensive solutions can be found in the literature. Moreover, one cannot determine how potential changes applied to inputs of these methods impact their results. In this paper we present a framework of managing evolving data and handling the entailments of the unforeseen alterations of inputs in terms of performing sound data integration in an acceptable time. We base our …work on the consensus theory and provide theoretical foundations, an experimental evaluation and a statistical analysis of obtained results. Show more

Keywords: consensus theory, knowledge integration, knowledge management

DOI: 10.3233/JIFS-179339

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7291-7302, 2019

Authors: Łuszpaj, Adam | Dobrowolski, Grzegorz

Article Type: Research Article

Abstract: An enormous volume of well-structured data with explicit semantics, in accordance with W3C’s standards, becomes a reality in the Web of Linked Data. However, the Semantic Web promise to turn it into a machine-processable global graph of knowledge still encounters numerous impediments. Efficient access and discovery along with the semantic heterogeneity have been identified as major stumbling blocks. Following the design principles for Semantic Web and Linked Data, we present ActiveDiscovery, a decentralized infrastructure for distributed SPARQL query evaluation based on its terminological entities, namely the ontologies used in a query. ActiveDiscovery’s main goal is to facilitate distributed and transparent …semantic search based on structural rather than keyword-based querying in the Semantic Web. Key architectural extensions regarding metadata, indexing and ontology alignment are proposed to achieve transparency for federated query execution in a decentralized manner. The rewriting procedure for extensional SPARQL query is considered regarding the proposed components and SERVICE clause as a standard recommendation for query federation. We investigate the feasibility of our approach and present preliminary results of initial evaluation. We conclude by indicating questions which need to be addressed in future work. Show more

Keywords: Semantic Web, query federation, ontologies, SPARQL, decentralized architecture

DOI: 10.3233/JIFS-179340

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7303-7312, 2019

Authors: Maleszka, Marcin

Article Type: Research Article

Abstract: In this paper we present an extended model of an unsupervised collective, that is a group where each member communicates with others to form opinions, instead of a single supervisor determining the overall collective knowledge. We describe the social influence theories that are the basis of the proposed model, and how they translate to a multi-agent model of the collective. We define two measures of social influence that are formalizations of concepts presented in sociological research. We perform a simulation experiment, where we observe the behavior of the collective in relation to those measures. Finally, we present a road-map of …future improvements possible in the model, working towards a real world test of its feasibility. Show more

Keywords: Unsupervised collective, collective knowledge, social influence, knowledge diffusion

DOI: 10.3233/JIFS-179341

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7313-7323, 2019

Authors: Hernes, Marcin | Sobieska-Karpińska, Jadwiga

Article Type: Research Article

Abstract:  The supply chain is a key element of successful operation of businesses in a turbulent economic situation. Swift management of delivery of raw materials and finished products while keeping costs as low as possible and maintaining proper customer service is becoming as vital as the quality and price of a product when gaining competitive advantage. This leads companies to a wide search for the best strategies that allow efficient management of the supply chain. The basic problem, however, is the occurrence of the so-called Forrester effect (also known as the bullwhip effect). It involves intensified transposing of changes in demand …onto the execution of product flow in supply chains. The aim of this article is to develop a manner to reduce the Forrester effect using the consensus method. The first part of the article analyzed the current state of knowledge on the discussed problem. Then it presented basic elements of the developed prototype of a SCM system and defined the meth-od for reducing the Forrester effect using a consensus algorithm. The final part of the article de-scribes the way to conduct an experiment that involves verifying the consensus algorithm and analyzes the results of the verification and their influence on the reduction of the Forrester effect. Show more

Keywords: Supply chain management, Forrester effect, consensus methods

DOI: 10.3233/JIFS-179342

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7325-7335, 2019

Authors: Maleszka, Bernadetta

Article Type: Research Article

Abstract: Traditional approaches to content-based recommendation and collaborative filtering do not suffer from cold-start problem, which is a challenge to recommend items for an unknown user. In this paper we present a Personalized Document Retrieval System which takes into account a social network information about the users. The overall idea of the system is to cluster users into groups of similar interests based on theirs usage data and to determine a representative profile for each of the groups. When a new user joins the system, he or she is classified into one of existing group based on his or her user …data and the representative profile of the group becomes a starting profile for the new user. This paper focuses on a method for updating ontology-based user profile using Bayesian network approach. We analyze some properties of proposed updating method and describe an idea of experimental evaluations. Show more

Keywords: Recommendation system, cold-start problem, user profile, social networks, collaborative filtering, Bayesian network

DOI: 10.3233/JIFS-179343

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7337-7346, 2019

Authors: Starzec, Mateusz | Starzec, Grażyna | Byrski, Aleksander | Turek, Wojciech | Kisiel-Dorohinicki, Marek

Article Type: Research Article

Abstract: Solving difficult, usually NP-hard problems, requires metaheuristic-based approach. Such algorithms are very often demanding from the point of view of computational power. Therefore various approaches to parallelize or distribute such systems were made. Many of such algorithms are structurally very easy to parallelize, e.g. evolutionary ones. However, swarm computing algorithms, in particular ACO (Ant Colony Optimization), in order to be implemented properly must use a significant amount of global knowledge (pheromones matrix). Therefore strict parallelization/distribution strategies for ACO are difficult to work-out. In the presented paper we propose a novel approach for parallelization and distribution of the most important element …of ACO, namely the pheromone table. Our prototype implementation is tested on a real-world HPC (High Performance Computing) infrastructure, with good observed scalability. At the end of this paper we present actual experimental results focusing on two class of problems, namely TSP (Travelling Salesman Problem) and VRPTW (Vehicle Routing Problem with Time Windows), using popular benchmarks. Show more

Keywords: parallel and distributed computing, ant colony optimization, swarm intelligence, high performance computing

DOI: 10.3233/JIFS-179344

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7347-7356, 2019

Authors: Bădică, Amelia | Bădică, Costin | Ivanović, Mirjana | Logofătu, Doina

Article Type: Research Article

Abstract: We analyze intermediation business processes that enable companies to use multiple distribution channels for expanding their market horizon of potential customers that are interested in purchasing their products and/or services. These distribution channels are represented by sequences of intermediation transactions supported by usually self-interested middle-agents that enable the connection of the providers with the end costumers. We propose a new formal model of network-structured intermediation business processes represented as Directed-Acyclic-Graphs. Using this model we obtained sound theoretical results of collectively profitable intermediation transactions. This paves the way for further proposal of optimal pricing strategies of the participating agents in semi-competitive …environments. Show more

Keywords: Welfare economics, intermediation networks, collective intelligence, multi-agent system, graph theory, linear algebra

DOI: 10.3233/JIFS-179345

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7357-7368, 2019

Authors: Floria, Sabina-Adriana | Leon, Florin | Logofătu, Doina

Article Type: Research Article

Abstract:  Social networks currently belong to a vast area of research as information spreads at a remarkable speed due to technology, and social connections have become easily accessible in the online environment. Social networks are dynamic entities, which new individuals can join, or other links can be lost because members no longer interact with one-another. Dynamic analysis of social networks is important in topology changes of the network and also in information diffusion. Some information that spreads through the social network may be untrue, hence in this paper we propose a protocol based on evidence theory with Dempster-Shafer and Yager’s rules …in which the network becomes more immune to false information. We also analyze the impact of topology change for an initial network by adding new connections in the information diffusion process. We show information diffusion by coloring the nodes of the network and also illustrate the time evolution of messages for a better accuracy in our comparisons. The experimental results confirm that the proposed model fits the behavior of inhibiting false information. Show more

Keywords: Information credibility, information diffusion, social networks, confidence degree

DOI: 10.3233/JIFS-179346

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7369-7381, 2019

Authors: Mazur, Zygmunt | Pec, Janusz

Article Type: Research Article

Abstract: In this paper we describe a heuristic procedure for solving the travelling salesman problem in the symmetric case without using the triangle inequality c ij  ≤ c ik  + c kj . A complete proof of the correctness of the algorithm and example of the presentation how the method works are given. There is estimated computational complexity, which is at most O(m2 ), where m is a number of the edges of the complete graph with n vertices -K n . There is shown also, it is possible obtain the following bound that HEURISTIC SOLUTION …OPTIMAL SOLUTION < 3 , if some specific inequality considering weights (costs) of edges is satisfied. Show more

Keywords: Symmetric travelling salesman problem (STSP), assignment problem, hamiltonian circuit, simple graph, simple circuit, complete graph Kn , list Li , heuristics

DOI: 10.3233/JIFS-179347

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7383-7388, 2019

Authors: Calvo, Iván | Merayo, Mercedes G. | Núñez, Manuel

Article Type: Research Article

Abstract: Uncertainty and imprecision play an important role in the specification and analysis of complex systems. Therefore, it is important to provide methodologies and tools to support the correct development of these systems. In this paper we present a new formalism, based on fuzzy automata , to facilitate the different phases involved in the development of a system where information is fuzzy . The formal syntax and semantics of our formalism are based on previous work, which has been adapted to be easily implemented and automated. We introduce a methodology to analyze systems modelled with one of our fuzzy automata. Finally, …we show how our framework can be used to define a model of the heart based on electrocardiograms (ECGs) and use this model to analyze data of real patients. Show more

Keywords: Fuzzy automata, formal specification, ECG

DOI: 10.3233/JIFS-179348

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7389-7399, 2019

Authors: Karim, Redwanul | Islam, M. A. Muhiminul | Simanto, Sazid Rahman | Chowdhury, Saif Ahmed | Roy, Kalyan | Al Neon, Adnan | Hasan, Md. Sajid | Firoze, Adnan | Rahman, Rashedur M.

Article Type: Research Article

Abstract: Information Extraction allows machines to decipher natural language through using two tasks: Named Entity Recognition and Relation Extraction. In order to build such a system for Bangla Language, in this work a Named Entity Recognition (NER) System is proposed, which requires a minimum information to deliver a decent performance having less dependency on handcrafted features. The proposed model is based on Deep Learning, which is accomplished through the use of a Densely Connected Network (DCN) in collaboration with a Bidirectional-LSTM (BiLSTM) and word embedding, i.e., DCN-BiLSTM. Such a system, specific to the Bangla language, has never been done before. Furthermore, …a unique dataset was made since no Named Entity Recognition dataset exists for Bangla language till date. In the dataset, over 71 thousand Bangla sentences have been collected, annotated, and classified into four different groups using IOB tagging scheme. Those groups are person, location, organization, and object. Due to Bangla’s morphological structure, character level feature extraction is also applied so that we can access more features to determine relational structure between different words. This is initially done with the use of a Convolutional Neural Network but is later outperformed by our second approach which is through the use of a Densely Connected Network (DCN). As for the training portion, it has been done for two variations of word embedding which are word2vec and glove, the outcome being the largest vocabulary size known to both models. A detailed discussion in regard to the methodology of the NER system is explained in a comprehensive manner followed by an examination of the various evaluation scores achieved. The proposed model in this work resulted in having a F1 score of 63.37, which is evaluated at Named Entity Level. Show more

Keywords: Named entity recognition, information extraction, word embedding, sequence labelling, Bi-LSTM, densely connected network, Bangla, annotation, dataset, NLP, neural network, character level feature extraction, CNN

DOI: 10.3233/JIFS-179349

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7401-7413, 2019

Authors: Smaïli, Kamel | Fohr, Dominique | González-Gallardo, Carlos-Emiliano | Grega, Michał | Janowski, Lucjan | Jouvet, Denis | Koźbiał, Arian | Langlois, David | Leszczuk, Mikołlaj | Mella, Odile | Menacer, Mohamed-Amine | Mendez, Amaia | Pontes, Elvys Linhares | SanJuan, Eric | Torres-Moreno, Juan-Manuel | Garcia-Zapirain, Begoña

Article Type: Research Article

Abstract: The aim of the work is to report the results of the Chist-Era project AMIS (Access Multilingual Information opinionS). The purpose of AMIS is to answer the following question: How to make the information in a foreign language accessible for everyone? This issue is not limited to translate a source video into a target language video since the objective is to provide only the main idea of an Arabic video in English. This objective necessitates developing research in several areas that are not, all arrived at a maturity state: Video summarization, Speech recognition, Machine translation, Audio summarization and Speech segmentation. …In this article we present several possible architectures to achieve our objective, yet we focus on only one of them. The scientific locks are be presented, and we explain how to deal with them. One of the big challenges of this work is to conceive a way to evaluate objectively a system composed of several components knowing that each of them has its limits and can propagate errors through the first component. Also, a subjective evaluation procedure is proposed in which several annotators have been mobilized to test the quality of the achieved summaries. Show more

Keywords: Automatic speech recognition, statistical machine translation, video summarization, text boundary segmentation, collecting data, text and audio summarization, objective and subjective evaluations

DOI: 10.3233/JIFS-179350

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7415-7426, 2019

Authors: Deb, Tonmoay | Ali, Mohammad Zariff Ahsham | Bhowmik, Sanchita | Firoze, Adnan | Ahmed, Syed Shahir | Tahmeed, Muhammad Abeer | Rahman, N.S.M. Rezaur | Rahman, Rashedur M.

Article Type: Research Article

Abstract: Understanding the context with generation of textual description from an input image is an active and challenging research topic in computer vision and natural language processing. However, in the case of Bengali language, the problem is still unexplored. In this paper, we address a standard approach for Bengali image caption generation though subsampling the machine translated dataset. Later, we use several pre-processing techniques with the state-of-the-art CNN-LSTM architecture-based models. The experiment is conducted on standard Flickr-8K dataset, along with several modifications applied to adapt with the Bengali language. The training caption subsampled dataset is computed for both Bengali and English …languages for further experiments with 16 distinct models developed in the entire training process. The trained models for both languages are analyzed with respect to several caption evaluation metrics. Further, we establish a baseline performance in Bengali image captioning defining the limitation of current word embedding approaches compared to internal local embedding. Show more

Keywords: Image captioning, CNN, LSTM, natural language processing, computer vision, Bengali image captioning, merge architecture, par-inject architecture, machine translated caption subsampling

DOI: 10.3233/JIFS-179351

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7427-7439, 2019

Authors: Anh, Kieu Que | Nagai, Yukari | Le Minh, Nguyen

Article Type: Research Article

Abstract:  With the development of social networks and online shopping sites, we can easily obtain valuable feedback from users. The crucial question is how to utilize customer feedback for supporting the development of product design in the early phases. For product design, understanding user needs or user requirements would help designers design a better product for users. Therefore, user requirements is considered as an important role in product design. This paper proposes a framework for assessing user requirements from websites to support designers. They key idea is to extract user requirements from online customer reviews and represent them into an appropriate …form for designers. We show that a support system consisting of feature aspect extraction, opinion summarization, and sentiment classification would be an useful tool for product design. Experimental results on a the data collected from the Amazon website show that supporting of opinion extraction techniques would be useful for designers in product design. Show more

Keywords: Opinion mining, product design, sentiment classification, users requirements (URs)

DOI: 10.3233/JIFS-179352

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7441-7451, 2019

Authors: Jodłowiec, Marcin | Krótkiewicz, Marek | Wojtkiewicz, Krystian

Article Type: Research Article

Abstract:  Knowledge representation is one of the most explored areas in nowadays computer science research. In this paper authors pursue definition and semantics of semantic networks that are defined as part of Semantic Knowledge Base being a hybrid knowledge oriented system. The approach presented in here aims at introducing advanced properties of networks such as cardinality, partitioning or certainty at the same time using simple structure based on two operands and operators. Following paper is an extension of a conference publication that introduced advanced aspects of semantic networks modelling with the use of Association-Oriented Metamodel. The extension includes a discussion related …to the formal description of the structure, as well as the description and use of association-oriented design patterns. Show more

Keywords: Semantic networks, Semantic Knowledge Base, partitioned semantic nets, association design patterns

DOI: 10.3233/JIFS-179353

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7453-7464, 2019

Authors: Chen, Chun-Hao | Chiang, Bing-Yang | Hong, Tzung-Pei | Wang, Ding-Chau | Lin, Jerry Chun-Wei | Gankhuyag, Munkhjargal

Article Type: Research Article

Abstract: Investment is always an interesting and important issue for people since the international financial crises are hard to predict and the government’s policy may have an influence on economic activities. In the past, many researches have been proposed on portfolio issues. In some of these studies, the group stock portfolio (GSP) is utilized to provide various alternative stocks to an investor. The diverse group stock portfolio (DGSP) optimization approach has then been designed because the diversity of industries within a group can affect the performance of a final GSP. However, these approaches still have some problems to be solved. In …this paper, we propose an algorithm to improve the efficiency and effectiveness of the previous work. In the proposed approach, a new chromosome representation and an enhanced fitness function are applied to find a better DGSP with lower risk than before. Moreover, we design a fuzzy grouping genetic algorithm (FGGA) based on the concept of collective intelligence which utilizes the fuzzy logic to dynamically tune the parameters in the evolution process for finding an appropriate DGSP. A mechanism is also designed to repair non-feasible chromosomes in the population. Through the above improvements, the proposed approach can not only focus on finding the best solution but also speed up the evolution process. Finally, experiments made on real datasets show the merits of the proposed approach. Show more

Keywords: Collective intelligence, diverse group stock portfolio, fuzzy grouping genetic algorithm, grouping problem, individual repair mechanism, portfolio optimization

DOI: 10.3233/JIFS-179354

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7465-7479, 2019

Authors: Grzonka, Daniel | Kołodziej, Joanna | Jakóbik, Agnieszka

Article Type: Research Article

Abstract: The monitoring of the computational processes in highly distributed environments remains challenging in today’s High Performance Computing. In this paper, we define the agent-based cloud monitoring system for supporting the computational tasks scheduling and resource allocation. The system consists of two types of agents, which may decide about the initialization of the schedule execution and monitor the work of the cloud computational nodes. The decision about running the new scheduling process is based on the expected number of available computational units in the specified time window. The efficiency of the proposed MAS-based model was justified through 40 empirical tests, where …clouds without and within the MAS support were compared. The multiagent system (MAS) effectiveness has been expressed in the average number of floating point operations completed at the cloud resources in one second. The obtained results show the importance of setting the optimal initial time for execution of the new schedule. Our experiments show that for running the new schedule, at least 25% of the computing units in the clouds should be in the idle mode. Also the batches of tasks should not be too large, cause the waiting time for new schedule for execution should be short and not greater than 10% of expected batch execution time. Show more

Keywords: multiagent systems, monitoring, computational cloud, autonomous agent, batch scheduling

DOI: 10.3233/JIFS-179355

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7481-7492, 2019

Authors: Huk, Maciej

Article Type: Research Article

Abstract: Contextual neural networks are effective and very usable machine learning models being generalization of multilayer perceptron. They allow to solve classification problems with high accuracy while strongly limiting activity of connections between hidden neurons. Within this article we present novel study of properties of contextual neuronal networks with Hard and Exponential Rectifier activation functions and of their influence on behavior of the Generalized Error Backpropagation method. It is used to show how to optimize efficiency of the sorting phase of this algorithm when applied to train evaluated models. This considerably extends our previous related paper which was limited to analysis …of contextual neuronal networks with Leaky Rectifier and Sigmoidal activation functions. This article includes wide description of contextual neural networks and generalized error backpropagation algorithm as well as the discussion of their connection with self-consistency paradigm, which is frequently used in quantum physics. Also the relation of the latter with sorting methods and considered rectifier functions during training of contextual neural networks is studied in details. Conclusions are backed up by the results of performed experiments. Reported outcomes of simulations confirm the ability of contextual neural networks to limit activity of connections between their neurons and – what is more important – indicate the detailed rules of selection of the most efficient sorting algorithm for updating scan-paths of contextual neurons that are using Hard and Exponential Rectifier activation functions. Presented results have considerable value both for research and practical applications – especially where the efficiency of training of contextual neural networks is crucial. Show more

Keywords: Classifiers, self-consistency, aggregation functions, scan-paths

DOI: 10.3233/JIFS-179356

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7493-7502, 2019

Authors: Nguyen, Binh Thanh

Article Type: Research Article

Abstract: The usefulness and ease of use of Big5 dashboard have been proposed to explore hierarchical structure of personality traits. First, Big5 system architecture and its components are described. Afterwards, we present how to calculate Big5 indicators from available big mobile data sets. Hereafter, Big5 traits can be predicted based on those just-specified indicators. To proof of our concepts, implementation results will be presented in the context of the Big5 dashboard which has been designed and developed to predict Big5 personalities in a representative and interactive manner.

Keywords: Big5 traits, personality, indicators, data warehouse, mobile logs, Naive Bayes classification, dashboard

DOI: 10.3233/JIFS-179357

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7503-7509, 2019

Authors: Le Thi, Hoai An

Article Type: Research Article

Abstract: This paper deals with a new and efficient collective optimization approach, based on DC (Difference of Convex functions) programming and DCA (DC Algorithm), powerful tools of nonconvex programming. Exploiting the efficiency and the flexibility of DCA we develop the so-called collaborative DCA in which divers DCA based algorithms are cooperated in an effective way. Two versions of collaborative DCA are proposed and their applications on clustering, a fundamental problem in unsupervised learning, are studied. Numerical experiments are performed on several datasets. The comparative results with three DCA component algorithms show that the collaborative DCA outperforms them on quality and it …realizes a good trade-off between the quality of solutions and the running time. Show more

Keywords: Collective optimization, DC programming, DCA, Collaborative DCA, Clustering.

DOI: 10.3233/JIFS-179358

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7511-7518, 2019

Authors: Li, Honggui | Trocan, Maria

Article Type: Research Article

Abstract: Isometric feature mapping (ISOMAP) is one of the classical methods of nonlinear dimensionality reduction (NLDR) and seeks for low dimensional (LD) structure of high dimensional (HD) data. However, the inverse problem of ISOMAP has never been investigated, which recovers the HD sample from the related LD sample, and its application prospect in data representation, generation, compression and visualization will be very brilliant. Because the inverse problem of ISOMAP is ill-posed and undetermined, the sparsity of HD data is employed to reconstruct the HD data from the corresponding LD data. The theoretical architecture of sparse reconstruction of ISOMAP representation comprises the …original ISOMAP algorithm, learning algorithm of sparse dictionary, general ISOAMAP embedding algorithm and sparse ISOMAP reconstruction algorithm. The sparse ISOMAP reconstruction algorithm is an optimization problem with sparse priors of the HD data, which is resolved by the alternating directions method of multipliers (ADMM). It is uncovered from the experimental results that, in the case of very LD ISOMAP representation, the proposed method outperforms the state-of-the-art methods, such as discrete cosine transformation (DCT) and sparse representation (SR), in the reconstruction performance of signal, image and video data. Show more

Keywords: Isometric feature mapping, inverse problem, sparse priors, sparse reconstruction, alternating directions method of multipliers

DOI: 10.3233/JIFS-179359

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7519-7536, 2019

Authors: Kurowski, Adam | Mrozik, Katarzyna | Kostek, Bozena | Czyzewski, Andrzej

Article Type: Research Article

Abstract:  In this paper, a methodology for automatic brain activity class identification of EEG (electroencephalographic) signals is presented. EEG signals are gathered from seventeen subjects performing one of the three tasks: resting, watching a music video and playing a simple logic game. The methodology applied consists of several steps, namely: signal acquisition, signal processing utilizing z-score normalization, parametrization and activity classification. The EEG signal is acquired from a headset containing 14 electrodes. For the parametrization two methods are used, namely, Discrete Wavelet Transform (DWT) employed as a reference parametrization technique and autoencoder neural network. Parameters obtained with those methods are fed …to the input of classifiers which assigned them to one of three activity classes. Then, the effectiveness of the assignment of the frames of EEG data into appropriate classes is observed and compared. Results obtained using both methods show differences in accuracy with regard to the task detected depending on factors such as type of parametrization or complexity of the classifier employed for EEG activity classification. Show more

Keywords: EEG signal, discrete wavelet transform (DWT), autoencoder, EEG signal classification

DOI: 10.3233/JIFS-179360

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7537-7543, 2019

Authors: Koczkodaj, Waldemar W. | Kakiashvili, T. | Li, Feng | Wolny-Dominiak, Alicja | Masiak, Jolanta

Article Type: Research Article

Abstract:  In this study, differential evolution (DE) optimization is proposed for rating scale predictability improvement. An arbitrary assignment of equal values for rating scale items is used as the classifier although domain experts are aware that the contribution of individual items may vary. Most academic examinations are conducted by the use of rating scales. Rating scales are also used in psychiatry (especially for screening). This study demonstrates that the differential evolution is effective for optimizing the predictability of rating scales.

Keywords: Rating scale, DE

DOI: 10.3233/JIFS-179361

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7545-7553, 2019

Authors: Phuc, Do

Article Type: Research Article

Abstract: Real world data is often interconnected, forming large and complex heterogeneous information networks (HINs) with multiple types of objects and links such as bibliographic network (DBLP) and knowledge bases (YaGo). Querying meta-paths requires exploration of path instances which can be computational cost in large HINs. However, existing meta-path based studies mostly focus on analytical applications of meta-paths, rather than systems to query meta-paths efficiently in large HINs. To bridge this gap, in this work we present SparkHINlog, a system based on Apache Spark, to handle meta-paths queries efficiently on large scale HINs. In SparkHINlog we propose an algorithm to not …only translate meta-paths to Datalog rules, but also to manage the working memory area of Datalog efficiently to increase the scalability of SparkHINlog. To avoid the computing overhead of join operation to discover path instances when evaluating these rules, we leverage Motif Finding, a powerful tool of GraphFrames Library. With motif finding, SparkHINLog can speed up the time to evaluate the rules by path finding on graph instead on joining two relations. We conduct experimental comparisons with SparkDatalog, the state-of-the-art large-scale Datalog system, and verify the efficacy and effectiveness of our system in supporting meta-path queries. Show more

Keywords: Bibliographic network, datalog rules, heterogeneous information networks, meta-path, spark graphframes

DOI: 10.3233/JIFS-179362

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7555-7566, 2019

Authors: Kisiel-Dorohinicki, Marek

Article Type: Research Article

Abstract: Agent-based metaheuristics computing paradigm (EMAS) has been proposed over 20 years ago by Cetnarowicz. Since then, many efforts were made in order to evaluate, formally analyze and further develop this paradigm towards creating new algorithms as EMAS hybrids, or EMAS-inspired techniques. However, at the same time a significant work has been done in order to build efficient software frameworks supporting this (and similar) computing paradigms. These frameworks were based not only on classic object-oriented programming, but also on functional approach and recently also utilizing heterogeneous infrastructure. This paper presents an overview of the most important findings in this area, including …novel ways of processing the agents and component orientation, which allow for both high flexibility and high efficiency of provided solutions. The discussed concepts are illustrated with a case study of a system solving hard computational problem leveraging GPGPU. Show more

Keywords: parallel and distributed computing, agent-based platform, metaheuristics

DOI: 10.3233/JIFS-179363

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7567-7578, 2019

Authors: Wikarek, Jarosław | Sitek, Paweł | Bocewicz, Grzegorz

Article Type: Research Article

Abstract: The resource constrained portfolio scheduling problem (RCPoSP), in which orders are grouped in portfolios, is proposed in this study. In the RCPoSP the objective is to deliver all orders in the portfolio at the same time after processing. This problem finds many applications in industrial services, manufacturing companies and, where all items (products, services, items etc.) ordered by the customer have to be delivered at the same time in one lot. The goal is to reduce the delivery costs and/or that all elements of the delivery have the same priority, etc. The presented problem also concerns the scheduling of new …orders in project portfolios and/or a new project portfolio etc. The minimizations of makespan and/or resource needs for the portfolio are also discussed. The authors present a reference model for the RCPoSP and an intelligent framework for modeling and solving the modeled problem based on the original hybrid approach. The opportunity to ask questions, receive answers as well as data representation in the form of facts constitute an invaluable intelligent support to users utilizing this framework. The goal is to provide an intelligent hybrid framework for stating and solving constraint satisfaction or optimization of RCPoSPs. The calculation examples illustrate the capabilities and computational efficiency of the proposed framework. Show more

Keywords: Resource constrained scheduling, constraint satisfaction problem, constraint logic programming, mathematical programming, decision support, group scheduling, fact-based representation, hybrid methods

DOI: 10.3233/JIFS-179364

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7579-7593, 2019

Authors: López-Fuentes, Francisco de Asís | Ibañez-Ramírez, Juan Alejandro | Chantes Barrios, Abigail

Article Type: Research Article

Abstract: Currently, distributed systems are used to store information in remote sites. However, these systems are exposed to different types of security risks such as virus, Trojans or ramsomware, and security mechanisms are required to protect the access to these data and guarantee their privacy and integrity. Authentication plays an important role for security issues in a computer system. Authentication is used to prove the user identity, and it is strongly related with the access control to limits the actions and operations that an authenticated user can do in a computer system. However, authentication is a previously step to the access …control, and it assumes that authentication of a user has been done successfully. Several cryptography methods can be integrated in an authentication mechanism in order to obtain robust authentication schemes. An authentication scheme based on Kerberos to access data in multiples domains is presented in this paper. A challenge in our authentication scheme is related with the authentication of Kerberos servers. To deal with this problem a keys distribution architecture is added to authentication scheme in order to authenticate the Kerberos servers in a secure way. Show more

Keywords: Security, authentication, access control, keys distribution, kerberos

DOI: 10.3233/JIFS-179365

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7595-7606, 2019

Authors: Siemiński, Andrzej | Kopel, Marek

Article Type: Research Article

Abstract: The paper verifies the usefulness of a parallel and adaptive Ant Colony Communities (ACC) for solving the dynamic Travelling Salesman Problem (DTSP). ACC consists of a set of client colonies with a server to coordinate their work. Each one of the client colonies implements a standard ACO algorithm. The paper contains a detailed analysis of the operation of ACO for static TSP in order to identify its most dominant parameters. Graph Generator is used to modify the distances in TSP. In order to catch up with the constant changes the ACC should work in parallel and to adopt to the …current distances. This is accomplished by modifying the number of iterations and changing the size of its internal prospective solutions buffer. Two implementations of ACC are presented: an asynchronous that works on computers connected through a LAN and a synchronous that uses a Hadoop environment. Numerous experiments clearly indicate, that the adaptive, parallel ACC outperforms both standard version of ACO as well as its versions adopted for DTSP. This is especially true for highly dynamic Graph Generators. Show more

Keywords: Dynamic TSP, Ant Colony Community, PACO, immigrant based colonies, ACO parallel implementation

DOI: 10.3233/JIFS-179366

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7607-7618, 2019

Authors: Tabakov, Martin | Quesada, Joel

Article Type: Research Article

Abstract:  In this research, we succeeded in introducing a new reasoning procedure which applies interval type-2 fuzzy sets into a rule induction process. Our proposal allows information granulation which resulted in achieving good experimental results. We introduced decision tables with elements assumed as interval type-2 fuzzy sets which greatly generalize information. Next, by applying corresponding rule induction procedure, we introduced the possibility to generate directly from a benchmark data fuzzy rulebases for type-2 fuzzy inference models. We strongly believe that our reasoning approach will be a proper solution for different research issues such as classification or ranking procedures as well as …determining knowledge for fuzzy inference models. The method proposed was tested in a classification problem verified by using medical benchmark data. Show more

Keywords: Fuzzy sets, fuzzy reasoning, interval type-2 fuzzy sets, data classification, data discovery, pawlak’s information system, information granulation, rule induction, fuzzy rules

DOI: 10.3233/JIFS-179367

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7619-7630, 2019

Authors: Nguyen, Ngoc Thang | Phan, Van Thanh | Malara, Zbigniew

Article Type: Research Article

Abstract: In recent decades, the Nonlinear Grey Bernoulli Model “NGBM (1, 1)” has been applied in various fields and achieved positive results. However, its prediction results may be inaccurate in different scenarios. In order to expand the field of application and to improve the predictive quality of the NGBM (1, 1) model, this paper proposes an effective model (named Fourier-NGBM (1, 1)). This model includes two main stages; first, we get the error values based on the actual data and predicted value of NGBM (1, 1). Then, we use a Fourier series to filter out and to select the low-frequency error …values. To test the superior ability of the proposed model, two numerical data sets were used. One is the historical data of annual water consumption in Wuhan from 2005 to 2012 in He et al. ’s paper, and the other is example data from Wang et al. ’s paper. The forecasted results prove that the performance of the Fourier-NGBM (1, 1) model is better than three other forecasting models, namely GM (1, 1), NGBM (1, 1) and the improved Grey Regression model. Furthermore, this study also applied the proposed model to forecast the electricity consumption in Vietnam up to the year 2020. The empirical results can offer valuable insights and provide basic information for model building to develop future policies regarding electrical industry management. In subsequent research, more methodologies can be used to reduce the residual error of the NGBM (1, 1) model, such as Markov chain or different kinds of Fourier functions. Additionally, the proposed model can be applied in different industries with fluctuating data and uncertain information. Show more

Keywords: Fourier series, nonlinear grey Bernoulli model, prediction accuracy, residual error, electricity consumption, Vietnam

DOI: 10.3233/JIFS-179368

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7631-7641, 2019

Authors: Madeyski, Lech | Kawalerowicz, Marcin

Article Type: Research Article

Abstract: BACKGROUND: Continuous Test-Driven Development (CTDD) is, proposed by the authors, enhancement of the well-established Test-Driven Development (TDD) agile software development and design practice. CTDD combines TDD with continuous testing (CT) that essentially perform background testing. The idea is to eliminate the need to execute tests manually by a TDD-inspired developer. OBJECTIVE: The objective is to compare the efficiency of CTDD vs TDD measured by the red-to-green time (RTG time), i.e., time from the moment when the project is rendered not compiling or any of the tests is failing, up until the moment when the project compiles and all …the tests are passing. We consider the RTG time to be a possible measurement of efficiency because the shorter the RTG time, the quicker the developer is advancing to the next phase of the TDD cycle. METHOD: We perform single case and small-n experiments in industrial settings presenting how our idea of Agile Experimentation materialise in practice. We analyse professional developers in a real-world software development project employing Microsoft.NET. We extend the contribution presented in our earlier paper by: 1) performing additional experimental evaluation of CTDD and thus collecting additional empirical evidence, 2) giving an extended, detailed example how to use and analyse both a single case and small-n experimental designs to evaluate a new practice (CTDD) in industrial settings taking into account natural constraints one may observe (e.g., a limited number of developers available for research purposes) and presenting how to reach more reliable conclusions using effect size measures, especially PEM and PAND which are more appropriate when data are not normally distributed or there is a large variation between or within phases. RESULTS: We observed reduced variance and trimmed means of the RTG time in CTDD in comparison to TDD. Various effect size measures (including ES, d-index, PEM, and PAND) indicate small, albeit non-zero, effect size due to CTDD. CONCLUSIONS: Eliminating the reoccurring manual task of selecting and executing tests and waiting for the results (by embracing CTDD) may slightly improve the development speed, but this small change on a level of a single developer, multiplied by a number of developers, can potentially lead to savings on the company or industry level. Show more

Keywords: empirical software engineering, agile software development, test-driven development, continuous test-driven development, human-centric experimentation, agile experimentation

DOI: 10.3233/JIFS-179369

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7643-7655, 2019

Authors: Choroś, Kazimierz

Article Type: Research Article

Abstract: The automatic detection of video genre is very desirable and necessary for further analysis of videos mainly when the video processing methods should be parameterized according to the specific video features. It improves first of all the efficiency of temporal segmentation. Temporal segmentation is usually the initial stage for the analysis of edited videos, for such processes as highlights detection, removing of undesirable parts like publicity, as well as selection of play segments in sports videos, etc. Then the temporal aggregation method based on the analysis of shot length and consisting in shot grouping into scenes of a given category …can be applied to significantly reduce processing time. The analyses and the observations of videos confirm that the editions of videos and the video structures significantly depend on the video genre. Many processes can be better performed if the genre of video is known and the methods and their parameters are adequate to the video genre. The paper presents the analyses and tests in the AVI Indexer showing the impact of shot length on the results of temporal segmentation, temporal aggregation, and genre detection of video edited in a standard and typical way for a given video genre. Show more

Keywords: Content-based video indexing, digital video structures, temporal segmentation, video shot categorization, temporal relations, automatic video genre classification, temporal aggregation, shot length analysis, AVI indexer

DOI: 10.3233/JIFS-179370

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7657-7667, 2019

Authors: Nguyen, Linh Anh | Nguyen, Ngoc-Thanh

Article Type: Research Article

Abstract:  We study the problem of minimizing interpretations in fuzzy description logics (DLs) under the Gödel semantics by using fuzzy bisimulations. The considered logics are fuzzy extensions of the DL 𝒜ℒ𝒞reg (a variant of propositional dynamic logic) with additional features among inverse roles, nominals and the universal role. Given a fuzzy interpretation ℐ and for E being the greatest fuzzy auto-bisimulation of ℐ w.r.t. the considered DL, we define the quotient ℐ/E of ℐ w.r.t. E and prove that it is minimum w.r.t. certain criteria. Namely, ℐ/E is a minimum fuzzy interpretation that validates the same set …of fuzzy terminological axioms in the considered DL as ℐ. Furthermore, if the considered DL allows the universal role, then ℐ/E is a minimum fuzzy interpretation bisimilar to ℐ, as well as a minimum fuzzy interpretation that validates the same set of fuzzy concept assertions in the considered DL as ℐ. Show more

Keywords: fuzzy description logic, fuzzy bisimulation, bisimilarity, Gödel semantics, minimization

DOI: 10.3233/JIFS-179371

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7669-7678, 2019

Authors: Zgraja, Jakub | Moulton, Richard Hugh | Gama, João | Kasprzak, Andrzej | Woźniak, Michał

Article Type: Research Article

Abstract: Data stream mining seeks to extract useful information from quickly-arriving, infinitely-sized and evolving data streams. Although these challenges have been addressed throughout the literature, none of them can be considered “solved.” We contribute to closing this gap for the task of data stream clustering by proposing two modifications to the well-known ClusTree data stream clustering algorithm: pruning unused branches and detecting concept drift. Our experimental results show the difficulty in tackling these aspects of data stream mining and the sensitivity of stream mining algorithms to parameter values. We conclude that further research is required to better equip stream learners for …the data stream clustering task. Show more

Keywords: Concept drift, data streams, ClusTree , on-line learning

DOI: 10.3233/JIFS-179372

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7679-7688, 2019

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7689-7689, 2019

Authors: Dastanian, Rezvan | Abiri, Ebrahim | Ghasempour, Mehdi

Article Type: Research Article

Abstract: In this paper a full wave rectifier is presented for RFID passive tags working at 960 MHz frequency. For designing the rectifier multi-stage structure, which has high sensitivity and efficiency, is used for the low amplitude input voltage. In order to eliminate the effect of pass transistors threshold voltage, bootstrap circuit which has cross coupled structure is utilized. For optimizing power conversion efficiency (PCE) and gaining high output voltage from the low input voltage the size of the elements and number of stages are modeled and optimized with neural network and TLBO algorithm, respectively. Due to the achieved results from the …TLBO algorithm 6 stages are considered for the rectifier designing. For the low input voltage 0.6 V, the power conversion efficiency and the output DC voltage are achieved 50.8% and 1.52 V, respectively. The simulation of the proposed rectifier is done with Cadence software in 0.18μ m CMOS technology and its layout equals to 0.00525mm2 . Show more

Keywords: Vth cancellation technique, rectifier, TLBO, PCE

DOI: 10.3233/JIFS-151237

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7691-7698, 2019

Authors: Samanlioglu, Funda | Ayağ, Zeki

Article Type: Research Article

Abstract: In this study, an intelligent, integrated approach is presented to help educators select the best simulation software package. Selecting the best simulation software package for educational use is a complex multiple criteria decision making (MCDM) problem with several potentially conflicting quantitative and qualitative criteria. In this paper, two fuzzy MCDM methods; fuzzy Analytic Hierarchy Process (F-AHP) and fuzzy VIsekriterijumska optimizacija i KOmpromisno Resenje (F-VIKOR) are integrated to evaluate educational use simulation software package alternatives. In the proposed fuzzy AHP-VIKOR approach, F-AHP is used to determine the fuzzy criteria weights and F-VIKOR is applied to rank simulation software package alternatives with …respect to these criteria. A case study is given where several educational use simulation software packages in Turkey are evaluated and ranked. Show more

Keywords: Simulation software package selection, fuzzy, multiple-criteria decision making, AHP, VIKOR

DOI: 10.3233/JIFS-172290

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7699-7710, 2019

Authors: Xie, Li-Li | Wu, Xiu-Yun

Article Type: Research Article

Abstract: The basic system of inquisitive semantics (InqB) established by Groenendijk et al. is a general inquisitive semantic theory which doesn’t concern fuzziness. To explain the fuzzy phenomena in natural languages, this paper extends InqB into the framework of M -fuzzifying setting and establishes a basic system of M -fuzzifying inquisitive semantics. To begin with, the notion of M -fuzzifying supporting mapping is defined, where M is a completely distributive lattice with an involution operator and each subset of the universal set of all possible worlds can be regarded as a support of any well-formed formula to some degree. Then …the notions of M -fuzzifying entailment order, M -fuzzifying truth mappings, M -fuzzifying informative content mappings and M -fuzzifying inquisitive content mappings are introduced and their properties are discussed. Further, the degrees of assertiveness, informativeness, inquisitiveness and questioning of a well-formed formula are defined, by which the M -fuzzifying assertive projection operator and the M -fuzzifying questioning projection operator are introduced and characterized. Finally, a necessary and sufficient condition is obtained, where a well-formed formula is exactly the disjunction of its unique M -fuzzifying assertive projection and unique M -fuzzifying questioning projection. Show more

Keywords: M-fuzzifying supporting mapping, M-fuzzifying inquisitive content mapping, M-fuzzifying informative content mapping, M-fuzzifying assertive projection operator, M-fuzzifying questioning projection operator

DOI: 10.3233/JIFS-182500

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7711-7723, 2019

Authors: Park, Jun Yong | Kim, Dong W. | Kang, Tae-Koo | Lim, Myo Taeg

Article Type: Research Article

Abstract: This paper proposes a biosignal distortion detection algorithm for a driver healthcare system based on a contact biosensor and a linked adaptive neuro-fuzzy inference system (ANFIS), and demonstrate its superiority using actual vehicle experiments. Contact biosensors are highly sensitive to vehicle vibration and turning. Although vehicle suspension contributes significantly to ride quality, vibration transfers to the driver and contact between the driver and biosensor can become unstable when executing a turn, causing the driver’s biosignal to not be measured well. This study estimated the driver’s biosignal state using acceleration, angular velocity, and slip ratio measurements obtained from sensor fusion. When …the measurement exceeded a defined threshold, the driver healthcare system removed unreliable biosignal data. We adopted ANFIS to improve the proposed sensor fusion algorithm estimate accuracy for the driver’s biosignal state and improved the healthcare system robustness to road conditions. The effectiveness of the proposed algorithm was demonstrated experimentally by comparing the system using sensor fusion and linked ANFIS. Show more

Keywords: Linked adaptive neuro fuzzy inference system, biosignal distortion detection, driver healthcare system, sensor fusion

DOI: 10.3233/JIFS-182532

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7725-7735, 2019

Authors: Zeng, Xiang-Tian | Yu, Gao-Feng | Wu, Jian

Article Type: Research Article

Abstract: In this paper, we present a newly developed methodology for solving hybrid multi-attribute decision making (HMADM) problems with multiple types of attribute values (MTAVs) by introducing the satisfaction degrees of alternatives’ closeness to the positive ideal solution for the decision maker (DM) and a compromise-typed variable weight decision method, where the weights of attributes are related to the satisfaction degrees of MTAVs and the DM’s behavior characteristics. An example is presented to show the application of the decision process and a detailed comparison analysis is provided to show the applicability and validity of the method proposed.

Keywords: Multiple attribute decision making, variable weight decision method, prospect theory, multiple types of attribute values

DOI: 10.3233/JIFS-182539

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7737-7746, 2019

Authors: Ðurić, Goran | Mitrović, Časlav | Komatina, Nikola | Tadić, Danijela | Vorotović, Goran

Article Type: Research Article

Abstract: Evaluation and analysis of failures which occur in the products or services in different economic areas are an important task of operational management. Solution of this problem leads to the increase of product’s/service’s quality, but in the same time it also increases business processes effectiveness and business goal’s realization. The treated problem is especially important in the information technologies domain. In this paper, the risk factors that may cause failures of the software are defined in compliance with the Failure Mode and Effect Analysis (FMEA) framework and they are assessed during the development and the maintenance phase. The relative importance …of these risk factors and their values at the level of each identified failure are described by pre-defined linguistic terms which are modelled by the interval type-2 trapezoidal fuzzy numbers (IT2TrFNs). The weights vector is calculated by using the Fuzzy Analytic Hierarchy Process (FAHP) with interval type-2 fuzzy sets. The rank of failures is obtained by using the complex proportional assessment (COPRAS) method. The example with real life data is illustrated to demonstrate the potential and applicability of the adopted methods. Show more

Keywords: MCDM, failures, software, FMEA, type-2 trapezoidal fuzzy numbers

DOI: 10.3233/JIFS-182541

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7747-7759, 2019

Authors: Zhu, Ye | Shen, Xuanjing | Liu, Yi

Article Type: Research Article

Abstract: To abandon the use of overlapping block division and resist the tampering factor of illumination change, a novel copy-move forgery detection method is proposed based on Maximally Stable Extremal Regions (MSERs) and the Local Intensity Order Pattern (LIOP), that integrates block-based and keypoints-based methods. The method involves the following steps: first, affine transformation invariant MSERs are used to maintain the geometrical transformation invariance and reduce computational complexity; second, LIOP features are used to describe the texture and resist illumination change; and finally, RANdom SAmple Consensus is applied to remove false matches. The experiments indicate that the proposed method has great …performance for scaling, rotation and illumination changes. Moreover, the method has the high robustness to Gaussian noise, Gaussian blur and JPEG compression. Show more

Keywords: Image forensics, copy-move forgery detection, maximally stable extremal regions, local intensity order pattern

DOI: 10.3233/JIFS-182647

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7761-7768, 2019

Authors: Khan, Shehroz S. | Ahmad, Amir | Mihailidis, Alex

Article Type: Research Article

Abstract:  Presence of missing values in a dataset can adversely affect the performance of a classifier. Single and Multiple Imputation are normally performed to fill in the missing values. In this paper, we present several variants of combining single and multiple imputation with bootstrapping to create ensembles that can model uncertainty and diversity in the data, and that are robust to high missingness in the data. We present three ensemble strategies: bootstrapping on incomplete data followed by (i) single imputation and (ii) multiple imputation, and (iii) multiple imputation ensemble without bootstrapping. We perform an extensive evaluation of the performance of the …these ensemble strategies on eight datasets by varying the missingness ratio. Our results show that bootstrapping followed by multiple imputation using expectation maximization is the most robust method even at high missingness ratio (up to 30%). For small missingness ratio (up to 10%) most of the ensemble methods perform equivalently but better than single imputation. Kappa-error plots suggest that accurate classifiers with reasonable diversity is the reason for this behaviour. A consistent observation in all the datasets suggests that for small missingness (up to 10%), bootstrapping on incomplete data without any imputation produces equivalent results to other ensemble methods. Show more

Keywords: Missingness, ensemble, bagging, multiple imputation, expectation maximization

DOI: 10.3233/JIFS-182656

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7769-7783, 2019

Authors: Thao, Nguyen Xuan | Ali, Mumtaz | Nhung, Le Thi | Gianey, Hemant Kumar | Smarandache, Florentin

Article Type: Research Article

Abstract: A divergence measure plays an important part in distinguishing two probability distributions and drawing conclusions based on that discrimination. In this paper, we proposed the concept of divergence measure of picture fuzzy sets. We also built some formulas of the proposed divergence measure of picture fuzzy sets anddiscussed some basic properties of this measure.Based on the proposedmeasure, we developed a multi-criteria decision-making algorithm. Finally, we applied the proposed multi-criteria decision-making algorithm in the medical diagnosis problem and the classification problem.

Keywords: Picture fuzzy set, picture fuzzy divergence measure, medical diagnosis, classification problem

DOI: 10.3233/JIFS-182697

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7785-7796, 2019