Journal of Intelligent & Fuzzy Systems - Volume 32, issue 2

Authors: Blazek, Pavel | Kuca, Kamil | Jun, Daniel | Krejcar, Ondrej

Article Type: Research Article

Abstract: The value of data is hidden in their organization, accessibility and usability. During a research the data are collected from external sources and created too. If they are not stored in a central database, it is difficult to reuse them and it could lead to inefficiency in a form of duplicated information and time wasting for finding the same information in public sources. An output of research can also be a long time expected medication as a biohazard substance. Both ideas have a common problem of sensitivity and security. It is necessary to protect these data either for secreting against …competitors or hiding information from terrorists. For the research team, the Biomedical Database System offers besides security also improvement of data flow in an organization, clear arrangement and efficiency. Show more

Keywords: Biomedical research, information system, data collecting, data processing, security

DOI: 10.3233/JIFS-169145

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1497-1508, 2017

Authors: Madeyski, Lech | Kitchenham, Barbara

Article Type: Research Article

Abstract: Researchers have identified problems with the validity of software engineering research findings. In particular, it is often impossible to reproduce data analyses, due to lack of raw data, or sufficient summary statistics, or undefined analysis procedures. The aim of this paper is to raise awareness of the problems caused by unreproducible research in software engineering and to discuss the concept of reproducible research (RR) as a mechanism to address these problems. RR is the idea that the outcome of research is both a paper and its computational environment. We report some recent studies that have cast doubts on the reliability …of research outcomes in software engineering. Then we discuss the use of RR as a means of addressing these problems. We discuss the use of RR in software engineering research and present the methodology we have used to adopt RR principles. We report a small working example of how to create reproducible research. We summarise advantages of and problems with adopting RR methods. We conclude that RR supports good scientific practice and would help to address some of the problems found in empirical software engineering research. Show more

Keywords: Reproducible research, empirical software engineering, scientific practice

DOI: 10.3233/JIFS-169146

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1509-1521, 2017

Authors: Horálek, Josef | Holík, Filip | Horák, Oldřich | Petr, Lukáš | Sobeslav, Vladimir

Article Type: Research Article

Abstract: This paper acquaints with a created application for generating Rainbow Tables and the results of testing Rainbow Tables, according to the length of the chosen chain. The paper presents a specialized application containing its own algorithms for reduction functions, changing the length of chain, generating Rainbow Tables and measuring the effectivity of the password search in detail. Within the executed tests, the dependence of Rainbow Tables size on the password length, the affection of the hash search by the size of the chosen chain and their links to collisions, which arise from the principle of using the reduction function, were …observed. The results objectively describe the pros and cons of using Rainbow Tables and show the possibilities and restrictions for their effective usage. Show more

Keywords: Rainbow Tables, hash, MD5, efficiency testing, breaking hash

DOI: 10.3233/JIFS-169147

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1523-1534, 2017

Authors: Błaszczyk, Piotr | Turek, Wojciech | Cetnarowicz, Krzysztof | Byrski, Aleksander

Article Type: Research Article

Abstract: In the paper we describe the process of development and verification of the novel traffic simulation method based on a credible driver model. The model is based on the actions of real drivers recorded in series of experiments. The developed simulation method reflects the unpredictable and totally individual characteristics of individual drivers. We show that the characteristics is a very significant factor in overall traffic efficiency. We believe that our credible driver model may become a basis for novel traffic management systems and active-safety mechanisms installed in the vehicles.

Keywords: Driver model, simulation, traffic management

DOI: 10.3233/JIFS-169148

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1535-1546, 2017

Authors: Nalepa, Jakub | Blocho, Miroslaw

Article Type: Research Article

Abstract: The pickup and delivery problem with time windows is an NP-hard discrete optimization problem with two objectives—to minimize the fleet serving transportation requests, and to minimize the distance traveled during this service. Although there exist exact algorithms for tackling this problem, they are still difficult to apply in massively large practical scheduling scenarios due to their time complexities. Hence, the approximate methods became the main stream of research in this field. In this paper, we propose an adaptive guided ejection search algorithm for solving the pickup and delivery with time windows. The pivotal part of this technique is the pre-processing …step, in which the instance characteristics concerning its underlying structure are extracted in the clustering and histogram-based analyses. Then, the k -nearest neighbor algorithm is applied to classify the instance to an appropriate class. Finally, the most suitable variant of our enhanced guided ejection search algorithm is adaptively chosen for solving this instance based on the classification outcome. An extensive experimental study performed on the full Li and Lim’s benchmark (encompassing 354 problem instances belonging to 6 classes) revealed that our pre-processing allows for achieving very high classification accuracy, thus for selecting the best variant of the enhanced guided ejection search. Show more

Keywords: Adaptation, k-NN algorithm, clustering, guided ejection search, PDPTW

DOI: 10.3233/JIFS-169149

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1547-1559, 2017

Authors: Hudziak, Mariusz | Pozniak-Koszalka, Iwona | Koszalka, Leszek | Kasprzak, Andrzej

Article Type: Research Article

Abstract: The objective of this paper is to give a tool for the practical users, looking for the efficient way for solving pathfinding problem, concerning planning the best paths for the simultaneously moving agents in the crowded environment with obstacles. The proposed approach is based on the two-stage approach. In the first stage, a navigation mesh for passable regions in rectangular 2D environment is created using Quad-trees algorithm. In the second stage, a path is found for each agent present in environment using Dijkstra or A* algorithm. To find efficient paths in crowded environment, density information for each passable region is …stored. Density information is further mapped on graph edges along with the distance values. The key point is that the moving agents reevaluate their paths accordingly to the re-planning strategy. Three strategies are considered: (i) periodical re-planning, (ii) periodical with initial re-planning, and (iii) the proposed way called event-driven re-planning. The created and implemented experimentation system can be adopted by the practical user for testing the two-stage combinations of algorithms. The results of investigations, based on simulation experiments made with this system, presented in the paper, showed that the proposed approach is promising. Show more

Keywords: Pathfinding, crowded environment, multi-agent, algorithm, experimentation system

DOI: 10.3233/JIFS-169150

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1561-1573, 2017

Authors: Zhang, Haoxi | Sanin, Cesar | Szczerbicki, Edward | Zhu, Ming

Article Type: Research Article

Abstract: In this paper, we propose the Neural Knowledge DNA, a framework that tailors the ideas underlying the success of neural networks to the scope of knowledge representation. Knowledge representation is a fundamental field that dedicates to representing information about the world in a form that computer systems can utilize to solve complex tasks. The proposed Neural Knowledge DNA is designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing devices. It is constructed in a similar fashion of how DNA formed: built up by four essential elements. As the DNA produces phenotypes, the Neural Knowledge DNA …carries information and knowledge via its four essential interrelated elements, namely, Networks, Experiences, States, and Actions; which store the detail of the artificial neural networks for training and reusing such knowledge. The novelty of this approach is that it uses previous decisional experience to collect and expand intelligence for future decision making formalized support. The experience based collective computational techniques of Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA) are used to develop aforesaid decisional sustenance. Together with artificial neural networks and reinforcement learning, the proposed Neural Knowledge DNA is used to catch knowledge of a very simple maze problem, and the results show that our Neural Knowledge DNA is a very promising knowledge representation approach for artificial neural network-based intelligent systems. Show more

Keywords: Neural knowledge DNA, neural networks, deep learning, reinforcement learning, knowledge representation

DOI: 10.3233/JIFS-169151

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1575-1584, 2017

Authors: Sanin, Cesar | Shafiq, Imran | Waris, Mohammad Maqbool | Toro, Carlos | Szczerbicki, Edward

Article Type: Research Article

Abstract: Engineering collective intelligence is paramount in current industrial times. This research proposes and presents case studies for collective knowledge structures required in the industry field. Knowledge structures such as Set of Experience and Decisional DNA are extended into more advanced knowledge structures for manufacturing processes. These structures are called Virtual Engineering Object, Virtual Engineering Process and Virtual Engineering Factory. All knowledge structures are implemented and tested in two industrial manufacturing cases of collective knowledge, plus one more case of manufacturing innovation where the case study results proved them as practical standards for engineering collective intelligence.

Keywords: Decisional DNA, set of experience knowledge structure, virtual engineering object, virtual engineering process, virtual engineering factory

DOI: 10.3233/JIFS-169152

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1585-1599, 2017

Authors: Wahyono, | Jo, Kang-Hyun

Article Type: Research Article

Abstract: Detecting human carrying baggage from video sequences is one of the important modules in identifying unattended baggage for video surveillance system. Hence, this paper addresses a framework for implementing such module. As the video was recorded using a static camera, the background modeling is firstly constructed for extracting foreground regions. These regions are considered as candidate of human by further verifying them using a general human detector. To identify whether the human is carrying baggage or not, the human region is divided into several components such as head, body, leg and baggage components according to the spatial information of baggage …relative to a human body proportion. The scalable histogram of oriented gradient features of each component are extracted and the feature dimension is reduced by applying genetic algorithm. The features are trained using a support vector machine (SVM) over each component regarded as a weak classifier. The boosting machine is employed to combine these weak classifiers into a strong classifier for final decision. In experiment, standard public dataset are used to evaluate the effectiveness of our proposed approach. The results verified that the proposed framework outperforms the state-of-the-art methods and can be considered as one of the solutions for aforementioned task. Show more

Keywords: Human carrying baggage detection, spatial component model, video surveillance, background modeling, boosting machine, genetic algorithm, support vector machine, scalable histogram of oriented gradient, unattended baggage

DOI: 10.3233/JIFS-169153

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1601-1613, 2017

Authors: Choroś, Kazimierz

Article Type: Research Article

Abstract: Content-based indexing methods need to analyze all frames of a video. Because such a procedure is extremely time consuming the indexing may be limited to the key-frames, i.e. to only one or to a few frames for every shot or for every video scene. The detection of the key-frame of a shot or of a scene requires very effective temporal segmentation methods. Content-based indexing of videos is based on the automatic detection of a video structure. A video shot is the main structural video unit. The temporal aggregation results in grouping of shots into scenes of a given category. Moreover, …the determination of the most likely category on the basis of time relations also reduces the analysis time enabling us to apply the adequate method of content-based indexing. The main problem is to select report shots and non-report shots because usually different indexing strategies should be applied. The paper examines the usefulness of the temporal aggregation method and pre-categorization of shots in news videos to reduce processing time taken by a very time-consuming content-based video indexing process. Show more

Keywords: Content-based video indexing, news videos, video structures, temporal aggregation, news shot categorization, digital video segmentation, category probability, video key-frames, temporal relations

DOI: 10.3233/JIFS-169154

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1615-1626, 2017