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Physical Sciences and Mathematics Commons

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Electrical and Computer Engineering

2019

Clustering

Articles 1 - 4 of 4

Full-Text Articles in Physical Sciences and Mathematics

Exploring Bigram Character Features For Arabic Text Clustering, Dia Eddin Abuzeina Jan 2019

Exploring Bigram Character Features For Arabic Text Clustering, Dia Eddin Abuzeina

Turkish Journal of Electrical Engineering and Computer Sciences

The vector space model (VSM) is an algebraic model that is widely used for data representation in text mining applications. However, the VSM poses a critical challenge, as it requires a high-dimensional feature space. Therefore, many feature selection techniques, such as employing roots or stems (i.e. words without infixes and prefixes, and/or suffixes) instead of using complete word forms, are proposed to tackle this space challenge problem. Recently, the literature shows that one more basic unit feature can be used to handle the textual features, which is the twoneighboring character form that we call microword. To evaluate this feature type, …


A New Model To Determine The Hierarchical Structure Of The Wireless Sensor Networks, Resmi̇ye Nasi̇boğlu, Zülküf Teki̇n Erten Jan 2019

A New Model To Determine The Hierarchical Structure Of The Wireless Sensor Networks, Resmi̇ye Nasi̇boğlu, Zülküf Teki̇n Erten

Turkish Journal of Electrical Engineering and Computer Sciences

Wireless sensor networks are one of the rising areas of scientific research. Common purpose of these investigations is usually constructing optimal structure of the network by prolonging its lifetime. In this study, a new model has been proposed to construct a hierarchical structure of wireless sensor networks. Methods used in the model to determine clusters and appropriate cluster heads are k-means clustering and fuzzy inference system (FIS), respectively. The weighted averaging based on levels (WABL) defuzzification method is used to calculate crisp outputs of the FIS. A new theorem for calculation of WABL values has been proved in order to …


Evaluating The Attributes Of Remote Sensing Image Pixels For Fast K-Means Clustering, Ali̇ Sağlam, Nurdan Baykan Jan 2019

Evaluating The Attributes Of Remote Sensing Image Pixels For Fast K-Means Clustering, Ali̇ Sağlam, Nurdan Baykan

Turkish Journal of Electrical Engineering and Computer Sciences

Clustering process is an important stage for many data mining applications. In this process, data elements are grouped according to their similarities. One of the most known clustering algorithms is the k-means algorithm. The algorithm initially requires the number of clusters as a parameter and runs iteratively. Many remote sensing image processing applications usually need the clustering stage like many image processing applications. Remote sensing images provide more information about the environments with the development of the multispectral sensor and laser technologies. In the dataset used in this paper, the infrared (IR) and the digital surface maps (DSM) are also …


Efficient Hierarchical Temporal Segmentation Method For Facial Expression Sequences, Jiali Bian, Xue Mei, Yu Xue, Liang Wu, Yao Ding Jan 2019

Efficient Hierarchical Temporal Segmentation Method For Facial Expression Sequences, Jiali Bian, Xue Mei, Yu Xue, Liang Wu, Yao Ding

Turkish Journal of Electrical Engineering and Computer Sciences

Temporal segmentation of facial expression sequences is important to understand and analyze human facial expressions. It is, however, challenging to deal with the complexity of facial muscle movements by finding a suitable metric to distinguish among different expressions and to deal with the uncontrolled environmental factors in the real world. This paper presents a two-step unsupervised segmentation method composed of rough segmentation and fine segmentation stages to compute the optimal segmentation positions in video sequences to facilitate the segmentation of different facial expressions. The proposed method performs localization of facial expression patches to aid in recognition and extraction of specific …