{"title":"The fuzzy properties of the ship control in collision situations","authors":"Mostefa Mohamed-Seghir","doi":"10.1109/INISTA.2017.8001141","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001141","url":null,"abstract":"This article focuses on fuzzy set theory as intelligent tools for navigator's decision-making to improve the safety of marine vessels in collision situations. A lot of progress has been made, especially in the field of artificial intelligence. The paper goal is to develop a decision support system based on artificial intelligence to determine a ship's trajectory in a collision situation. In this present work ship trajectory optimization in collision situations is presented as multistage decision-making in a fuzzy environment. The navigator's subjective assessment in making a decision are taken under consideration in the process model and it shows the modified membership function of constraints.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124467665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Y. O. Camada, Jés Jesus Fiais Cerqueira, A. M. N. Lima
{"title":"Stereotyped gesture recognition: An analysis between HMM and SVM","authors":"M. Y. O. Camada, Jés Jesus Fiais Cerqueira, A. M. N. Lima","doi":"10.1109/INISTA.2017.8001180","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001180","url":null,"abstract":"Stereotypic behaviours are present in both human and nonhuman primates. Usually, these behaviours are a welfare indicator. However, the stereotypic behaviours may be also a symptom of some mental disorder in the humans. A specific case is Autism Spectrum Disorder (ASD). The individuals with ASD may exhibit stereotypic behaviours through some gestures. The classic stereotyped gestures of autism are: (i) Body Rocking; (ii) Hand Flapping; and (iii) Top Spinning. This paper study the performance between two machine learning algorithms to recognition the stereotyped gestures typical of autism: (i) Hidden Markov Model [HMM]; and (ii) Support Vector Machine [SVM]. Sequence of orientations data from some joints obtained through a RGB-D (Red Green Blue - Depth) camera [Kinect®] are used for analysis. The results of these two machine learning algorithms are compared with state-of-the-art. The HMM approach proposed in this paper have shown 98.89% average recognition rate and 98.9% recall. This value is higher compared to the SVM approach and the others of art method presented.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127014279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Adaptive phasor estimation technique during off-nominal frequency","authors":"O. Thiab, L. Nogal, R. Kowalik","doi":"10.1109/INISTA.2017.8001159","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001159","url":null,"abstract":"the use of digital multifunction protection relays and their proper integration on power system and smart grid is an important element. However, the performance of digital relays depends on many factors and needs to be carefully evaluated. These factors may be caused correct operations with less performance or completely incorrect operations. Frequency deviation is one of those factors which results from unbalanced demand load and generation levels. Load characteristics and generation control response to demand load changes will effect on amount and duration of frequency deviations. Frequency decreases when demand load is higher than generation, whereas, it increases when load is less than generation. Protection relays are provided with frequency tracking to reduce the effects of frequency deviations on accuracy of relays decisions. In this paper traditional frequency tracking technique used on protection relays is modified to give a better performance during off-nominal frequency variations. The performance of the proposed algorithm is compared with traditional tracking using Least Square Error (LSQ), and Discrete Fourier transform (DFT) algorithm without any tracking, which are investigated in MATLAB environment.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125391881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Under question cultural boundaries: A semiospheric perspective based on enabling aspects of mythical characters","authors":"Emilia Nercissians","doi":"10.1109/INISTA.2017.8001203","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001203","url":null,"abstract":"Prior to the modern semiotics, the only discipline towards a systematic study of culture was Anthropology. Nowadays, cultural semiotics, as one of the sub-disciplines of semiotics tries to understand the culture and its related issues such as change, and tries to make it explicable by its methods such as participant observation as one of the common methods in ethnomethodology. Language as a social action carries series of codes. In the field study the author has directly observed the codes shared codes of the language between the sender and recipients in the interpretation process. The shared codes are integral parts of semiosphere. The value of these terms and their implication are emphasized in two rural areas called Shahkooh and Gharnabad as new contexts or scenes where the fusion of boundaries takes place. Of course, the words and concepts are not capable to function by themselves; each change is in need of an agent to put the concept of change in action. The agent or mythical figure of this change is a native son of the region who makes an interaction between the concepts of non-text, and text.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121859985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Adapting code maintainability to bat-inspired test case prioritization","authors":"M. Öztürk","doi":"10.1109/INISTA.2017.8001134","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001134","url":null,"abstract":"Time and budget constraints in developing a software create an adverse effect in terms of the adequacy of maintenance and test processes. This case can be considered as a burden for persons who account for test processes. In order to alleviate this burden, test case prioritization is one of the solutions. A nature-inspired method namely BITCP, which was developed based on bat algorithm, produced promising results. However, this method does not involve test case elements with respect to the code maintainability. In this work, the correlation between some code maintainability indicators including WMC, LCOM, and Coupling and cyclomatic complexity is investigated. IMPBITCP appears after adapting the results of the investigation to BITCP. The method is then compared with well known alternatives such as greedy-search, particle swarm optimization, and BITCP. The experiment involving six open source project showed that IMPCBITCP outperformed the others with respect to the APFD. The findings of the work indicates that if the factors affecting code maintenance are considered while developing test case prioritization techniques, APFD results becomes high and stable.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123551115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Music emotion analysis using semantic embedding recurrent neural networks","authors":"J. Jakubík, H. Kwasnicka","doi":"10.1109/INISTA.2017.8001169","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001169","url":null,"abstract":"The paper presents an original approach to music emotion recognition. We propose to use recurrent neural networks to separate the representation learning process from the classifier, which allows us to use a Support Vector Machine on top of a network to improve the results. We define a suitable loss function that is able to find a feature space in which similarity between vectors representing the music recordings corresponds to the similarity between their annotations. The proposed method was tested for regression and classification using two datasets. The results are presented and discussed.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127617096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Deep convolutional encoder-decoder network with model uncertainty for semantic segmentation","authors":"S. Isobe, Shuichi Arai","doi":"10.1109/INISTA.2017.8001187","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001187","url":null,"abstract":"We propose a new semantic segmentation method and the necessity of certainty for practical use of semantic segmentation in scene understanding. We implement a deep fully convolutional encoder-decoder neural network for semantic segmentation. This network architecture makes the segmentation accuracy improve by retaining boundary details in the extracted image representation. This accuracy means how much the segmentation results match to ground truth labels. However, the conventional evaluation method ignores unlabeled regions in ground truth labels. In other words, the segmentation results has not been evaluated in the regions of unknown objects. Toward practical use of the semantic segmentation, the evaluation should consider such regions. So it is necessary to recognize accurately whether the object is known or not. We call this factor certainty. Bayesian SegNet makes it possible to produce an uncertainty of the segmentation results with a measure of model uncertainty from the sampling of the posterior distribution of the model using Dropout. However, the uncertainty is not used for segmentation itself, and all pixels are classified into one of the predefined classes in this segmentation result. It means that the pixels within the regions of unknown objects are definitely misclassified as one of the predefined classes. Our study aims the improvement of certainty for semantic segmentation in road scene understanding with model uncertainty. Our method rejects the uncertain region and classifies it as an unknown object using the model uncertainty. We achieved improvement of certainty by our method as shown in the evaluation results. Furthermore, we indicated the possibility of the performance improvement on the deep convolutional encoder-decoder network architecture from the comparison of our network architecture with Bayesian SegNet architecture.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133216589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fuat Bakkal, S. Eken, Nurullah Samed Savas, A. Sayar
{"title":"Modeling and querying trajectories using Neo4j spatial and TimeTree for carpool matching","authors":"Fuat Bakkal, S. Eken, Nurullah Samed Savas, A. Sayar","doi":"10.1109/INISTA.2017.8001160","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001160","url":null,"abstract":"With the the exponential growth of location aware devices, analysis of human movements has been the subject of several studies. Problems related to urban mobility such as vehicle congestion are serious concern in cities. Carpooling is one of the solutions to soften congestion problem. This paper presents a novel matching method for carpooling. Trajectories are firstly modeled using Neo4j spatial and Neo4j TimeTree libraries. Then, temporal and locational filtering steps are operated. We extensively evaluate the efficiency and efficacy of the proposed system on Geolife trajectory dataset.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115136679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A combinatorial approach to construct core and generic gene co-expression networks of colon cancer","authors":"M. Ö. Cingiz, G. Biricik, B. Diri","doi":"10.1109/INISTA.2017.8001140","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001140","url":null,"abstract":"Biological experiments can be set in order to detect the causes of diseases. However, they are expensive and time consuming. Recent developments in sequencing technologies help researchers to more easily reveal the underlying mechanisms of the diseases. In this study, we propose a combinatorial method to construct generic and core gene co-expression networks (GCNs) to discover the genes and their interactions related to colon cancer. We apply five gene network inference (GNI) algorithms and combine their estimations with Simple Majority Voting to specify the frequently inferred gene interactions and obtain the resulting GCNs on two different gene expression datasets. We then apply the intersection and union operators on these GCNS to derive the core and generic GCNs, respectively. The evaluation results of overlap analysis and topological features of GCNs for the colon cancer show that the networks produced with the proposed approach fit to the power-law degree distribution better.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116007685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A new approach to recognize activities in smart environments based on cooperative game theory","authors":"Elaheh Ordoni, A. Moeini, K. Badie","doi":"10.1109/INISTA.2017.8001181","DOIUrl":"https://doi.org/10.1109/INISTA.2017.8001181","url":null,"abstract":"These days, a lot number of elderly people need health care which may cause huge financial costs, especially in formal case. Machine Learning and the profound achievements in sensing technology provide the opportunities to monitor people living independently at home and can detect a distress situation affordably. Although there are some approaches to do recognize activities for this purpose, but there has not been any game-theoretic approach in order to select the most efficient sensors to reduce the system's overhead by decreasing the number of features. In this paper, we present a new classifier to recognize activities in a smart environment that is based on selection of most efficient sensors by cooperative game theory. The sensors are selected in which provide more information about the target classes. We show the performance of our algorithm by simulation.","PeriodicalId":314687,"journal":{"name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122603125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}