• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.206-210
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• 2024

Industrial facilities that use modern IT technologies require the ensured reliability and security of information in automated enterprise management. Concurrently, so as to ensure a high quality of communication, it is necessary to expand the bandwidth of communication channels, which are limited by the physical parameters of the radio frequency spectrum. In order to overcome this contradiction, we propose the application of technology fundamental to ultra-wideband signals, in which the ratio between the bandwidth and its central part is greater than "one". For this reason, the information signal is emitted without a carrier frequency - simultaneously within the entire frequency band - provided that the signal level is lower than the noise level. For the transmission of information content, the method of positional-time coding is used, in which each information bit is encoded by hundreds of ultrashort pulses that arrive within a certain sequence. Mathematical models of signals and values observed in wireless communication systems with autocorrelation reception of modulated ultra-wideband signals are furthermore recommended. These assist in identifying features of the dependence of the error probability on the normalized signal-to-noise ratio and the signal base. Comparative analysis has shown that the best noise immunity of the systems considered in this paper is the communication system, which uses the time separation of the reference and information signals. During the first half of the bit interval, the switch closes the output of the transmitter directly to the generator of the ultra-wideband signal - forming a reference signal. In the middle of the bit interval, the switch alternates the output to one of two possible positions depending on the encoding signal - "zero" or "one", forming the information part of the ultra-wideband signal. It should also be noted that systems with autocorrelation reception and separate transmission of reference and information signals, provide a high level of structural signal secrecy. Furthermore, they provide the reliable transmission of digital information, especially in interference conditions.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.163-177
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• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.

• Journal of IKEEE
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• v.25 no.2
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• pp.273-279
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• 2021

In this paper, we propose an algorithm that shortens the learning time by performing individual learning using partitioning the deep learning structure. The proposed algorithm consists of four processes: network classification origin setting process, feature vector extraction process, feature noise removal process, and class classification process. First, in the process of setting the network classification starting point, the division starting point of the network structure for effective feature vector extraction is set. Second, in the feature vector extraction process, feature vectors are extracted without additional learning using the weights previously learned. Third, in the feature noise removal process, the extracted feature vector is received and the output value of each class is learned to remove noise from the data. Fourth, in the class classification process, the noise-removed feature vector is input to the multi-layer perceptron structure, and the result is output and learned. To evaluate the performance of the proposed algorithm, we experimented with the Extended Yale B face database. As a result of the experiment, in the case of the time required for one-time learning, the proposed algorithm reduced 40.7% based on the existing algorithm. In addition, the number of learning up to the target recognition rate was shortened compared with the existing algorithm. Through the experimental results, it was confirmed that the one-time learning time and the total learning time were reduced and improved over the existing algorithm.

• Journal of the Korean Graphic Arts Communication Society
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• v.18 no.1
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• pp.59-69
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• 2000

The characteristics of liquid crystal polymer composite(LCPC) films are possessed of large-area and flexible display, polarizer free, high contrast, wide angle of visual filed and high responsiveness. It is well known that the LCPC films consisting of a continuous LC phase embeded in a three-dimentional network of polymer matrix are formed by photopolymerization-induced phase separation. In this study, we have investigated the point that both liquid crystals and polymer having different properties have to coexiste as composed films. The purpose of this study has been the development of new application with liquid crystals and UV-curable monomers. In the results abtained on the miscibility of nematic liquid crystal and UV-curable resins, difunctional monomer HX-620 turned out to shows the best. From the results abtained on structures, electro-optical properties and dynamic visocoelasticity for LCPC films, the best mixing ratio of monomer to LC mixture were 3/7(photoinitiator; 4wt%) by weight, and this ratio has been provided the most thermal stability for LCPC films. In the results abtained on structure and discoloration properties of LCPC films, it has been demonstrated that consiste of a 8:2 mixture of chiral nematic liquid crystal and HX-620 has the greatest domain and it was the best discoloration.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.2
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• pp.112-124
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• 2004

A neural network based adaptive reconfigurable flight controller is presented for a class of discrete-time nonlinear flight systems in the presence of variations of aerodynamic coefficients and control effectiveness decrease caused by control surface damage. The proposed adaptive nonlinear controller is developed making use of the backstepping technique for the angle of attack, sideslip angle, and bank angle command following without two time separation assumption. Feedforward multilayer neural networks are implemented to guarantee reconfigurability for control surface damage as well as robustness to the aerodynamic uncertainties. The main feature of the proposed controller is that the adaptive controller is developed under the assumption that all of the nonlinear functions of the discrete-time flight system are not known accurately, whereas most previous works on flight system applications even in continuous time assume that only the nonlinear functions of fast dynamics are unknown. Neural networks learn through the recursive weight update rules that are derived from the discrete-time version of Lyapunov control theory. The boundness of the error states and neural networks weight estimation errors is also investigated by the discrete-time Lyapunov derivatives analysis. To show the effectiveness of the proposed control law, the approach is i]lustrated by applying to the nonlinear dynamic model of the high performance aircraft.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.389-394
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• 2006

Inaccurate localization exposes a robot to many dangerous conditions. It could make a robot be moved to wrong direction or damaged by collision with surrounding obstacles. There are numerous approaches to self-localization, and there are different modalities as well (vision, laser range finders, ultrasonic sonars). Since sensor information is generally uncertain and contains noise, there are many researches to reduce the noise. But, the correctness is limited because most researches are based on statistical approach. The goal of our research is to measure more exact robot location by matching between built VRML 3D model and real vision image. To determine the position of mobile robot, landmark-localization technique has been applied. Landmarks are any detectable structure in the physical environment. Some use vertical lines, others use specially designed markers, In this paper, specially designed markers are used as landmarks. Given known focal length and a single image of three landmarks it is possible to compute the angular separation between the lines of sight of the landmarks. The image-processing and neural network pattern matching techniques are employed to recognize landmarks placed in a robot working environment. After self-localization, the 2D scene of the vision is overlaid with the VRML scene.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1166-1179
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• 2013

In wireless sensor network (WSN) environments, environmental noises are generated by, for example, small passing animals, crickets chirping or foliage blowing and will interfere target detection if the noises are higher than the sensor threshold value. For accurate tracking by acoustic WSNs, these environmental noises should be filtered out before initiating track. This paper presents the effect of environmental noises on target tracking and proposes a new algorithm for the noise mitigation in acoustic WSNs. We find that our noise mitigation algorithm works well even for targets with sensing range shorter than the sensor separation as well as with longer sensing ranges. It is also found that noise duration at each sensor affects the performance of the algorithm. A detection algorithm is also presented to account for the Doppler effect which is an important consideration for tracking higher-speed ground targets. For tracking, we use the weighted sensor position centroid to represent the target position measurement and use the Kalman filter (KF) for tracking.

• Proceedings of the Materials Research Society of Korea Conference
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• 2009.11a
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• pp.14-14
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• 2009

High frequency electromagnetic(EM) waves are increasingly being applied in industries because of saturationat lower frequency bands as a result of huge demand. However, electromagneticinterference (EMI) has become a serious problem, and as a result, highfrequency EM absorbers are now being extensively studied. Also, recentdevelopments in absorber technology have focused on producing absorbers thatare thin, flexible, and strong. Hence, one-dimension ferrous nano-materials area potential research field, because of their interesting electronic andmagnetic properties. Commercially, EM wave absorbing products are made ofcomposites, which blend the insulating polymer with magnetic fillers. Inparticular, the shape of the magnetic fillers, such flaky, acicular, or fibrousmagnetic metal particles, rather than spherical, is essential for synthesizingthin and lightweight EM wave absorbers with higher permeability. High aspectratio materials exhibit a higher permeability value and therefore betterabsorption of the EM wave, because of electromagnetic anisotropy. Nanowires areusually fabricated by drawing, template synthesis, phase separation, selfassembly, and electrospinning with a thermal treatment and reduction process.Producing nanowires by the electrospinning method involves a conventionalsol-gel process that is simple, unique, and cost-effective. In thispresentation, Magnetic nanowire and dielectric materials coated magneticnanowire with a high aspect ratio were successfully synthesized by theelectrospinning process with heat treatment and reduction. In addition toestimating the EM wave absorption ability of the synthesized magnetic anddielectric materials coated magnetic nanowire with a network analyzer, weinvestigated the possibility of using these nanowires as high-frequency EM waveabsorbers. Furthermore, a wide variety of topics will be discussed such as thetransparent conducting nanowire and semiconducting nanowire/tube with theelectrospinning process.

• Korean Institute of Interior Design Journal
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• v.20 no.3
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• pp.119-126
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• 2011

Recently, in the fields of fashion, advertisement, film, literature, philosophy, etc., the word, 'Nomad', is being used frequently across the overall society. The contemporary society is actively incorporating "nomadic thinking" as a new social phenomenon across the boundaries of conventional fields. This is not an exception in the field of space design. This study, via the contemporary nomadic thinking, examined the relationship between space design's application possibility as a new trend and flexible space; then categorized the characteristics of flexible space into flexibility, temporariness, changeability, and correlation; and then analyzed expression characteristics of flexible space. As for unrestricted expression of scene, it was recognized that separation of scene and space leads space to meet the needs of surrounding environment and users; formation of changeable space enables uses of space from various perspectives; and combining external factors (energy, media technologies) with space leads space to self-evolution. Space is perceived as an living organism that is flexibly corresponding, via realistic movement and virtual movement, to the indefinite, diversified thinking of the contemporary society. Therefore, this study illuminates that nomadic thinking has significance as basic thinking to predict development and characteristics of design thinking through understanding the contemporary society with the basic thinking system that has been inherent without restrictions of being fixed to the present, past, and future.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.295-298
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• 2009

다중 표적을 감시하는 무선 센서 네트워크에서 다중 표적이 서로 교차하게 될 때 각각의 표적을 분리하는 문제는 표적의 추적, 탐지, 식별 등의 분야에서 매우 중요하다. 기존의 무선 센서 네트워크에서는 에너지 기반의 기법을 사용하기 때문에 다중 표적의 위치를 추정할 수 없거나, 기지국에서의 원 신호 분석 방법을 통해 표적의 종류를 식별하여 각각의 표적을 분리한다. 후자의 방법은 무선 센서 노드의 통신량과 연산량을 증가시켜 센서 노드의 생존 시간이 짧아지는 단점이 있고, 표적 분리까지 걸리는 시간으로 인해 실시간 처리가 어렵다. 본 논문에서는 무선 센서 노드에서 웨이블릿 변환을 이용한 특징을 추출하고 이를 이용해 다중 표적이 센서 영역 내에서 교차하게 될 때 표적을 분리하는 방법을 제안한다. 제안된 방법은 웨이블릿 상수의 주파수 정보를 이용하여 적은 연산으로 표적을 분리한다.