• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.1903-1911
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• 2016

As interest in MANET is increasing nowadays, research upon an efficient MANET routing protocol is actively under way. A LQA(Link Qualty Aware)-AODV routing protocol to deal with frequent changes of topology and wireless link variations under tactical operating conditions is proposed in this paper. The suggested LQA-AODV takes into account the channel capacity of each hop during the route request process of the traditional AODV protocol. In detail, LQA-AODV adds a channel capacity cost value to the RREQ message format that occurs during the routing process of the existing AODV Routing Protocol causing the accumulated channel capacity cost values of each sections to be compared before establishing a route. To verify the performance of LQA-AODV, NS2.35 was utilized and the Link-Quality Model was applied in order to reflect the tactical wireless environment. The simulation compares and analyzes LQA-AODV and the existing AODV, showing a large improvement over the traditional AODV in regards to the Packet Delivery Ratio, and End-to-End Delay.

• Journal of Communications and Networks
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• v.16 no.4
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• pp.397-406
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• 2014

Radio frequency (RF) jamming is a denial of service attack targeted at wireless networks. In resource-hungry scenarios with constant traffic demand, jamming can create connectivity problems and seriously affect communication. Therefore, the vulnerabilities of wireless networks must be studied. In this study, we investigate a particular type of RF jamming that exploits the semantics of physical (PHY) and medium access control (MAC) layer protocols. This can be extended to any wireless communication network whose protocol characteristics and operating frequencies are known to the attacker. We propose two efficient jamming techniques: A low-data-rate random jamming and a shot-noise based protocol-aware RF jamming. Both techniques use shot-noise pulses to disrupt ongoing transmission ensuring they are energy efficient, and they significantly reduce the detection probability of the jammer. Further, we derived the tight upper bound on the duration and the number of shot-noise pulses for Wi-Fi, GSM, and WiMax networks. The proposed model takes consider the channel access mechanism employed at the MAC layer, data transmission rate, PHY/MAC layer modulation and channel coding schemes. Moreover, we analyze the effect of different packet sizes on the proposed jamming methodologies. The proposed jamming attack models have been experimentally evaluated for 802.11b networks on an actual testbed environment by transmitting data packets of varying sizes. The achieved results clearly demonstrate a considerable increase in the overall jamming efficiency of the proposed protocol-aware jammer in terms of packet delivery ratio, energy expenditure and detection probabilities over contemporary jamming methods provided in the literature.

• CELLMED
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• v.2 no.2
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• pp.12.1-12.11
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• 2012

Traditional Medicinal System (TMS) is one of the centuries-old practices and long-serving companions to the human kind to fight against disease and to lead a healthy life. Every indigenous people have been using their unique approaches of TMS practice where among, the Chinese, Indian and African TMSs are world-wide renowned. India has a unique Indian System of Medicines (ISM) consisting of Ayurveda, Siddha, Unani, Naturopathy and Homoeopathy. Siddhars are the saints as well as the eminent scholars, who have attained Ashta-mahasiddhi [Tamil: (Ashta-Eight; Mahasiddhi-Power)] or enlightment. They have postulated, practiced, immensely contributed and have established the concept of the Tamil medicinal system called Siddha System of Medicine (SSM). From ancient time, SSM has flourished and has been widely practiced in the southern part of India particularly in Tamil Nadu. The induction of the modern medicinal system has immensely influenced the existence of SSM and has made the SSM principles and practices undervalued/extinct. However, at present, still a considerable group of people are using the SSM as a basic health-care modality. In this context, the present scrutiny deals with the TMS history, its significance with a special reference to SSM history, Siddhars, the basic concept of SSM, its diagnostic procedures, materia medica and treatment. Conclusively, Siddha is one of the most ancient indigenous health practices despite its several thorny challenges and issues, which needs to be flagged effectively and to be preserved and revitalized in the international arena in the near future.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.15-24
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• 2008

For high-dimensional classification tasks, such as face recognition, the number of samples is smaller than the dimensionality of the samples. In such cases, a problem encountered in linear discriminant analysis-based methods for dimension reduction is what is known as the small sample size (SSS) problem. Recently, to solve the SSS problem, a way of employing a dissimilarity-based classification(DBC) has been investigated. In DBC, an object is represented based on the dissimilarity measures among representatives extracted from training samples instead of the feature vector itself. In this paper, we propose a new method of optimizing DBCs using multi-level fusion strategies(MFS), in which fusion strategies are employed to represent features as well as to design classifiers. Our experimental results for benchmark face databases demonstrate that the proposed scheme achieves further improved classification accuracies.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.6
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• pp.100-105
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• 2017

This work presents an ECG biometric recognition system for the purpose of biometric authentication. ECG biometric approaches are divided into two major categories, fiducial-based and non-fiducial-based methods. This paper proposes a new non-fiducial framework using discrete cosine transform and a Random Forest classifier. When using DCT, most of the signal information tends to be concentrated in a few low-frequency components. In order to apply feature vector of Random Forest, DCT feature vectors of ECG heartbeats are constructed by using the first 40 DCT coefficients. RF is based on the computation of a large number of decision trees. It is relatively fast, robust and inherently suitable for multi-class problems. Furthermore, it trade-off threshold between admission and rejection of ID inside RF classifier. As a result, proposed method offers 99.9% recognition rates when tested on MIT-BIH NSRDB.

• The Journal of the Acoustical Society of Korea
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• v.20 no.1
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• pp.13-20
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• 2001

Adaptive digital filters with long impulse response such as acoustic echo canceller and active noise controller suffer from slow convergence and computational burden. Subband techniques and multirate signal processing have been recently developed to improve the problem of computational complexity and slow convergence in conventional adaptive filter. Any FIR transfer function can be realized as a serial connection of interpolators followed by subfilters with a sparse impulse response. In this case, each interpolator which is related to the column vector of Hadamard matrix has band-pass magnitude response characteristics shifted uniformly. Subband technique using Hadamard transform and decimation of subband signal to reduce sampling rate are adapted to system modeling and acoustic noise cancellation In this paper, delayless subband structure with nonuniform bandwidth has been proposed to improve the performance of the convergence speed without aliasing due to decimation, where input signal is split into subband one using tree-structured filter bank, and the subband signal is decimated by a decimator to reduce the sampling rate in each channel, then subfilter with sparse impulse response is transformed to full band adaptive filter coefficient using Hadamard transform. It is shown by computer simulations that the proposed method can be adapted to general adaptive filtering.

• Journal of Korea Game Society
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• v.14 no.2
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• pp.67-76
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• 2014

Recently there have been many interests on tangible sport games that can recognize the motions of players. In this paper, we propose essential technologies required for tangible games, which are methods for swing motion recognition and the calculation of shuttle cock's trajectory. When a user carries out a badminton swing while holding a smartphone with his hand, the motion signal generated by smartphone-embedded acceleration sensors is transformed into a feature vector through a Daubechies filter, and then its swing type is recognized using a k-NN based method. The method for swing motion presented herein provides an advantage in a way that a player can enjoy tangible games without purchasing a commercial motion controller. Since a badminton shuttle cock has a particular flight trajectory due to the nature of its shape, it is not easy to calculate the trajectory of the shuttle cock using simple physics rules about force and velocity. In this paper, we propose a method for calculating the flight trajectory of a badminton shuttle cock in which the wind effect is considered.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.4
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• pp.283-292
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• 2020

Artificial intelligence, which is one of the representative images of the 4th industrial revolution, has been highly recognized since 2016. This paper analyzed domestic paper trends for 'Artificial Intelligence', 'Machine Learning', and 'Deep Learning' among the domestic papers provided by the Korea Academic Education and Information Service. There are approximately 10,000 searched papers, and word count analysis, topic modeling and semantic network is used to analyze paper's trends. As a result of analyzing the extracted papers, compared to 2015, in 2016, it increased 600% in the field of artificial intelligence, 176% in machine learning, and 316% in the field of deep learning. In machine learning, a support vector machine model has been studied, and in deep learning, convolutional neural networks using TensorFlow are widely used in deep learning. This paper can provide help in setting future research directions in the fields of 'artificial intelligence', 'machine learning', and 'deep learning'.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1784-1789
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• 2013

In this paper, parallel orthogonal matching pursuit (POMP) is proposed to supplement the orthogonal matching pursuit (OMP) which has been widely used as a greedy algorithm for sparse signal recovery. The process of POMP is simple but effective: (1) multiple indexes maximally correlated with the observation vector are chosen at the firest iteration, (2) the conventional OMP process is carried out in parallel for each selected index, (3) the index set which yields the minimum residual is selected for reconstructing the original sparse signal. Empirical simulations show that POMP outperforms than the existing sparse signal recovery algorithms in terms of exact recovery ratio (ERR) for sparse pattern and mean-squared error (MSE) between the estimated signal and the original signal.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.641-647
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• 2018

Recently, CCTV, which provides video information for multiple purposes, has been transformed into an intelligent, and the range of automation applications increased using the computer vision. A highly reliable detection method must be performed for accurate recognition of pedestrians and vehicles and various methods are being studied for this purpose. In such an object detection system. In this paper, we propose a method to detect a large number of pedestrians by acquiring three characteristic information that features of color information using HSI, motion vector information and shaping information using HOG feature information of a pedestrian in a situation where a large number of pedestrians are moving. The proposed method distinguishes each pedestrian while minimizing the failure or confusion of pedestrian detection and tracking. Also when pedestrians approach or overlap, pedestrians are identified and detected using stored frame feature data.