• ALGAE
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• v.25 no.3
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• pp.115-120
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• 2010

The natural growth of a population of Gomphosphaeria aponina Kutzing (Chroococcales, Cyanoprocaryota) was studied in a cemented freshwater tank in Allahabad, India. This population appeared to be a polymorphic species. Different species of the genus Gomphosphaeria have been segregated based on morphological features of colonies, cells and mucilage. However, these features are not well defined for different species. Our observations revealed many feature variations and, interestingly, certain features that have been described for different Gomphosphaeria species were seen in a single population. In this study, records of such variable morphological features were possible due to the availability of numerous specimens and continuous observations for more than two years. Further, this study revealed two points: (i) more detailed morphological studies are required both from nature as well as in culture to identify critical differences among the species, and (ii) molecular characterization of taxa appears to be necessary for final species settlement.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.10
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• pp.1364-1369
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• 2018

Speech emotion recognition, which aims to classify speaker's emotional states through speech signals, is one of the essential tasks for making Human-machine interaction (HMI) more natural and realistic. Voice expressions are one of the main information channels in interpersonal communication. However, existing speech emotion recognition technology has not achieved satisfactory performances, probably because of the lack of effective emotion-related features. This paper provides a survey on various features used for speech emotional recognition and discusses which features or which combinations of the features are valuable and meaningful for the emotional recognition classification. The main aim of this paper is to discuss and compare various approaches used for feature extraction and to propose a basis for extracting useful features in order to improve SER performance.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1851-1863
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• 2015

– In the paper, to handle the problem of traditional bag-of-features model ignoring the spatial relationship of local features in human action recognition, we proposed a Multiscale Spatial Position Coding under Locality Constraint method. Specifically, to describe this spatial relationship, we proposed a mixed feature combining motion feature and multi-spatial-scale configuration. To utilize temporal information between features, sub spatial-temporal-volumes are built. Next, the pooled features of sub-STVs are obtained via max-pooling method. In classification stage, the Locality-Constrained Group Sparse Representation is adopted to utilize the intrinsic group information of the sub-STV features. The experimental results on the KTH, Weizmann, and UCF sports datasets show that our action recognition system outperforms the classical local ST feature-based recognition systems published recently.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.1
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• pp.51-65
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• 1995

This paper presents an automatic fixture planning system for machining processes of prismatic parts. A rationalized approach to integrate fixture planning with process planning is proposed and representation schemes for workpiece, part design information with features, machine tools, cutting tools and fixtures are developed. The proposed system implements two activities of fixture planning such as machining of reference surfaces and machining of features. For machining of reference surfaces, the machining sequence of reference surfaces is determined by using decision tables, which are drawn from relations of part dimension, degree of surface roughness, fixture type and its capacity, cutting tool's capacity and experienced planners' knowledge. For machining of features, a preferential machining orientation is selected for its feature which can be machined in more than one direction, and features with the same machining orientation are grouped, and the machining sequence of features is determined by interactive mode. A case study is performed to show the performance of the proposed system.

• Journal of Mechanical Science and Technology
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• v.16 no.6
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• pp.762-769
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• 2002

This paper presents how effective it is to use many features for improving the speed and accuracy of visual servo systems. Some rank conditions which relate the image Jacobian to the control performance are derived. The focus is to describe that the accuracy of the camera position control in the world coordinate system is increased by utilizing redundant features in this paper. It is also proven that the accuracy is improved by increasing the number of features involved. Effectiveness of the redundant features is evaluated by the smallest singular value of the image Jacobian which is closely related to the accuracy with respect to the world coordinate system. Usefulness of the redundant features is verified by the real time experiments on a Dual-Arm robot manipulator made by Samsung Electronic Co. Ltd..

• Journal of the Korean Society for Precision Engineering
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• v.18 no.4
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• pp.85-96
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• 2001

In this paper, part features are classified and then its coding system is constructed by the considered characteristics of features in assemble process. Analyzing the characteristics of features, code values about part features are determined. Assembly process is divided into five functions such as transporting, handing, approaching, alignment and joining, and then the detail parameters of each functions such as determined. Code values about assembly process are determined according to detail parameters. The detail parameters are kinds of available working method and assembly tools when each assembly function is going on. By the coding system, available assembly process can be grasped and perceived for the part that it is difficult to assemble.

• Science of Emotion and Sensibility
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• v.5 no.3
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• pp.11-20
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• 2002

There are Two new models developed for objective evaluation of fabric color patterns by applying a multiple regression analysis and an adaptive foray-rule-based system. The physical features of fabric color patterns are extracted through digital image processing and the emotional features are collected based on the psychological experiments of Soen[3, 4]. The principle physical features are hue, saturation, intensity and the texture of color patterns. The emotional features arc represented thirteen pairs of adverse adjectives. The multiple regression analyses and the adaptive fuzzy system are used as a tool to analyze the relations between physical and emotional features. As a result, both of the proposed models show competent performance for the approximation and the similar linguistic interpretation to the Soen's psychological experiments.

• Korean Management Science Review
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• v.29 no.1
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• pp.101-114
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• 2012

The demand for naval spare parts is intermittent and erratic. This feature, referred to as non-normal demand, makes forecasting difficult. Hierarchical forecasting using an aggregated time series can be more reliable to predict non-normal demand than direct forecasting. In practice the performance of hierarchical forecasting is not always superior to direct forecasting. The relative performance of the alternative forecasting methods depends on the demand features. This paper analyses the influence of the demand features on the performance of the alternative forecasting methods that use hierarchical and direct forecasting. Among various demand features variability, kurtosis, skewness and equipment groups are shown to significantly influence on the performance of the alternative forecasting methods.

• Journal of Korea Multimedia Society
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• v.14 no.12
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• pp.1544-1548
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• 2011

A process of choosing a subset of original features, so called feature selection, is considered as a crucial preprocessing step to image processing applications. There are already large pools of techniques developed for machine learning and data mining fields. In this paper, basically two methods, non-feature selection and feature selection, are investigated to compare their predictive effectiveness of classification. Color co-occurrence feature is used for defining image features. Standard Sequential Forward Selection algorithm are used for feature selection to identify relevant features and redundancy among relevant features. Four color spaces, RGB, YCbCr, HSV, and Gaussian space are considered for computing color co-occurrence features. Gray-level image feature is also considered for the performance comparison reasons. The experimental results are presented.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.2
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• pp.130-137
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• 2006

In this paper, we propose a method of selecting new types of rectangle features that are suitable for facial expression recognition. The basic concept in this paper is similar to Viola's approach, which is used for face detection. Instead of previous Haar-like features we choose rectangle features for facial expression recognition among all possible rectangle types in a 3${\times}$3 matrix form using the AdaBoost algorithm. The facial expression recognition system constituted with the proposed rectangle features is also compared to that with previous rectangle features with regard to its capacity. The simulation and experimental results show that the proposed approach has better performance in facial expression recognition.