• Journal of Biomedical Engineering Research
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• v.16 no.3
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• pp.345-352
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• 1995

The LPC cepstrum coefficients, which are an acoustic features of speech signal, have been widely used as the feature parameter for various speech recognition systems and showed good performance. The vocal tract area function is a kind of articulatory feature, which is related with the physiological mechanism of speech production. This paper proposes the vocal tract area function as an alternative feature parameter for speech recognition. The linear predictive analysis using Burg algorithm and the vector quantization are performed. Then, recognition experiments for 5 Korean vowels and 10 digits are executed using the conventional LPC cepstrum coefficients and the vocal tract area function. The recognitions using the area function showed the slightly better results than those using the conventional LPC cepstrum coefficients.

• Journal of Ecology and Environment
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• v.30 no.4
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• pp.315-318
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• 2007

Cooperative or non-territorial permanently social spiders are believed to have evolved from species showing subsocial maternal care. The transition from subsocial to cooperative social groups probably involved a transition from an outbreeding breeding system to one with inbreeding. Nepotistic recognition among siblings should facilitate the evolution of social cooperation through avoidance of inbreeding and maintenance of mutual tolerance between siblings. We conducted experiments to determine whether a mechanism for sibling recognition is present in the subsocial spider, Coelotes terrestris which displays extended maternal care in the form of food provisioning. The numbers of surviving individuals within unfed groups were observed and compared between non-sibling groups of ten spiderlings and groups of ten siblings. The number of survivors differed significantly between groups, with consistently fewer spiderlings surviving in the non-sibling groups than the sibling groups over the study period. This result suggests that sibling recognition and nepotism do occur in this subsocial species. The nepotism involved in the maternal social organization of the Coelotes might be an example of a preadaptation facilitating the evolution of permanent social life.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1998.04a
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• pp.314-320
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• 1998

Wear debris morphology is closely related to the wear mode and mechanism occured. Image recognition of wear debris is, therefore, a powerful tool in wear monitoring. But it has usually required expert's experience and the results could be too subjective. Development of automatic tools for wear debris recognition is needed to solve this problem. In this work, an algorithm for automatic wear debris recognition was suggested and implemented by PC base software. The presented method defined a characteristic 3-dimensional feature space where typical types of wear debris were separately located by the knowledge-based system and compared the similarity of object wear debris concerned. The 3-dimensional feature space was obtained from multiple feature vectors by using a multi-dimensional scaling technique. The results showed that the presented automatic wear debris recognition was satisfactory in many cases application.

• BMB Reports
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• v.41 no.2
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• pp.93-101
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• 2008

The major cell wall components of bacteria are lipopolysaccharide, peptidoglycan, and teichoic acid. These molecules are known to trigger strong innate immune responses in the host. The molecular mechanisms by which the host recognizes the peptidoglycan of Gram-positive bacteria and amplifies this peptidoglycan recognition signals to mount an immune response remain largely unclear. Recent, elegant genetic and biochemical studies are revealing details of the molecular recognition mechanism and the signalling pathways triggered by bacterial peptidoglycan. Here we review recent progress in elucidating the molecular details of peptidoglycan recognition and its signalling pathways in insects. We also attempt to evaluate the importance of this issue for understanding innate immunity.

• Tribology and Lubricants
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• v.15 no.2
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• pp.206-211
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• 1999

Wear debris morphology is closely related to the wear mode and mechanism occured. Image recognition of wear debris is, therefore, a powerful tool in wear monitoring. But it has usually required expert's experience and the results could be too subjective. Development of automatic tools for wear debris recognition is needed to solve this problem. In this work, an algorithm for automatic wear debris recognition was suggested and implemented by PC base software. The presented method defined a characteristic 3-dimensional feature space where typical types of wear debris were separately located by the knowledge-based system and compared the similarity of object wear debris concerned. The 3-dimensional feature space was obtained from multiple feature vectors by using a multi-dimensional scaling technique. The results showed that the presented automatic wear debris recognition was satisfactory in many cases application.

• Journal of Aerospace System Engineering
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• v.16 no.1
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• pp.49-55
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• 2022

The role of drones has been expanded to various fields such as agriculture, construction, and logistics. In particular, agriculture drones are emerging as an effective alternative to solve the problem of labor shortage and reduce the input cost. In this study therefore, we proposed the fruit recognition algorithm and harvesting mechanism for fruit harvesting drone system that can safely harvest fruits at high positions. In the fruit recognition algorithm, we employ "You-Only-Look-Once" which is a deep learning-based object detection algorithm and verify its feasibility by establishing a virtual simulation environment. In addition, we propose the fruit harvesting mechanism which can be operated by a single driving motor. The rotational motion of the motor is converted into a linear motion by the scotch yoke, and the opened gripper moves forward, grips a fruit and rotates it for harvesting. The feasibility of the proposed mechanism is verified by performing Multi-body dynamics analysis.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.3
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• pp.156-165
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• 2005

Human being recognizes the physical world by integrating a great variety of sensory inputs, the information acquired by their own action, and their knowledge of the world using hierarchically parallel-distributed mechanism. In this paper, authors propose the sensor fusion system that can recognize multiple 3D objects from 2D projection images and tactile informations. The proposed system focuses on improving recognition performance of 3D objects. Unlike the conventional object recognition system that uses image sensor alone, the proposed method uses tactual sensors in addition to visual sensor. Neural network is used to fuse the two sensory signals. Tactual signals are obtained from the reaction force of the pressure sensors at the fingertips when unknown objects are grasped by four-fingered robot hand. The experiment evaluates the recognition rate and the number of learning iterations of various objects. The merits of the proposed systems are not only the high performance of the learning ability but also the reliability of the system with tactual information for recognizing various objects even though the visual sensory signals get defects. The experimental results show that the proposed system can improve recognition rate and reduce teeming time. These results verify the effectiveness of the proposed sensor fusion system as recognition scheme for 3D objects.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1735-1736
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• 2008

In this research, a riding robot system named as "RideBot" is developed for health-care and entertainments. The developed riding robot can follow the intention of horseman and can simulate the motion of horse. The riding robot mechanisms are used for many functions of attitude detection, motion sensing, recognition, common interface and motion-generations. This riding robot can react on health conditions, bio-signals and intention informations of user. One of the objectives of this research is that the riding robot could catch user motion and operate spontaneous movements. In this paper, we develope the saddle mechanism which can generate 3 degrees-of-freedom riding motion based on the intention of horseman. Also, we develope reins and spur mechanism for the recognition of the horseman's intention estimation and the bio-signal monitoring system for the health care function of a horseman. In order to evaluate the performance of the riding robot system, we tested several riding motions including slow and normal step motion, left and right turn motion.

• Animal cells and systems
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• v.9 no.4
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• pp.211-213
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• 2005

In bird species that suffer brood parasitism, the question about which sex is responsible for egg rejection has important implications for determining the coevolutionary relationship between brood parasites and their hosts. In order to determine which sex rejects a parasitic egg in vinous-throated parrotbills (Paradoxornis webbianus) which have egg color dimorphism, we conducted model egg experiments and video-recorded the behavior of the focal pair. Both sexes showed rejection behavior to the parasitic eggs. It indicates that the vinous-throated parrotbill may have a high rejection rate and faster spread of any rejection alleles through out populations. However, further studies are still needed to confirm the egg recognition mechanism in this species, which will expand our knowledge of the evolutionary relationship between host and parasite.

• The Journal of the Acoustical Society of Korea
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• v.18 no.5
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• pp.44-51
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• 1999

This paper presents a massively parallel computational model for the efficient integration of speech and natural language understanding. The phoneme model is based on continuous Hidden Markov Model with context dependent phonemes, and the language model is based on a knowledge base approach. To construct the knowledge base, we adopt a hierarchically-structured semantic network and a memory-based parsing technique that employs parallel marker-passing as an inference mechanism. Our parallel speech recognition algorithm is implemented in a multi-Transputer system using distributed-memory MIMD multiprocessors. Experimental results show that the parallel speech recognition system performs better in recognition accuracy than a word network-based speech recognition system. The recognition accuracy is further improved by applying code-phoneme statistics. Besides, speedup experiments demonstrate the possibility of constructing a realtime parallel speech recognition system.