• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.3A
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• pp.311-318
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• 2008

We propose new pulse shapes for FCC-compliant ultra-wideband (UWB) radios. The projections onto convex sets (POCS) technique is used to optimize temporal and spectral shapes of UWB pulses under the constraints of all of the desired UWB signal properties: efficient spectral utilization under the FCC spectral mask, time-limitedness, and good autocorrelation. Simulation results show that for all values of the pulse duration, the new pulse shapes not only meet the FCC spectral mask most efficiently, but also have nearly the same autocorrelation functions. It is also observed that our truncated (i.e., strictly time-limited) pulse shapes outperform the truncated Gaussian monocycle in the BER performance of binary TH-PPM systems for the same pulse durations. The POCS technique provides an effective method for designing UWB pulse shapes in terms of its inherent design flexibility and joint optimization capability.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.4
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• pp.151-158
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• 2014

In this paper, we introduce an inference system using hard scatter partition method and model the nonlinear process. To do this, we use the hard scatter partition method that partition the input space in the scatter form with the value of the membership degree of 0 or 1. The proposed method is implemented by C-Means clustering algorithm. and is used for the initial center values by means of binary split. by applying the LBG algorithm to compensate for shortcomings in the sensitive initial center value. Hard-scatter-partitioned input space forms the rules in the rule-based system modeling. The premise parameters of the rules are determined by membership matrix by means of C-Means clustering algorithm. The consequence part of the rules is expressed in the form of polynomial functions and the coefficient parameters of each rule are determined by the standard least-squares method. The data widely used in nonlinear process is used to model the nonlinear process and evaluate the characteristics of nonlinear process.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.643-650
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• 2014

A hardware implementation of phase calculator for extracting 3D depth image from TOF(Time-Of-Flight) sensor is described. The designed phase calculator adopts redundant binary number systems and a pipelined architecture to improve throughput and speed. It performs arctangent operation using vectoring mode of DCORDIC(Differential COordinate Rotation DIgital Computer) algorithm. Fixed-point MATLAB simulations are carried out to determine the optimal bit-widths and number of iteration. The phase calculator has ben verified by FPGA-in-the-loop verification using MATLAB/Simulink. A test chip has been fabricated using a TSMC $0.18-{\mu}m$ CMOS process, and test results show that the chip functions correctly. It has 82,000 gates and the estimated throughput is 400 MS/s at 400Mhz@1.8V.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.8
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• pp.453-464
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• 2004

In order to solve the well-known drawback of reduced flexibility that is associate with ASIC implementations, this paper proposes a novel arithmetic unit over GF(2$^{m}$ ) for field programmable gate arrays (FPGAs) implementations of elliptic curve cryptographic processor. The proposed arithmetic unit is based on the binary extended GCD algorithm and the MSB-first multiplication scheme, and designed as systolic architecture to remove global signals broadcasting. The proposed architecture can perform both division and multiplication in GF(2$^{m}$ ). In other word, when input data come in continuously, it produces division results at a rate of one per m clock cycles after an initial delay of 5m-2 in division mode and multiplication results at a rate of one per m clock cycles after an initial delay of 3m in multiplication mode respectively. Analysis shows that while previously proposed dividers have area complexity of Ο(m$^2$) or Ο(mㆍ(log$_2$$^{m}$ )), the Proposed architecture has area complexity of Ο(m), In addition, the proposed architecture has significantly less computational delay time compared with the divider which has area complexity of Ο(mㆍ(log$_2$$^{m}$ )). FPGA implementation results of the proposed arithmetic unit, in which Altera's EP2A70F1508C-7 was used as the target device, show that it ran at maximum 121MHz and utilized 52% of the chip area in GF(2$^{571}$ ). Therefore, when elliptic curve cryptographic processor is implemented on FPGAs, the proposed arithmetic unit is well suited for both division and multiplication circuit.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.81-97
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• 2003

In this paper, we suggest a method of robust watermarking for protection of multimedia data using the wavelet transform and artificial neural network. for the purpose of implementation, we decompose a original image using wavelet transform at level 3. After we classify transformed coefficients of other subbands using neural network except fur the lowest subband LL$_3$, we apply a calculated threshold about chosen cluster as the biggest. We used binary logo watermarks to make sure that it is true or not on behalf of the Gaussian Random Vector. Besides, we tested a method of dual watermark insertion and extraction. For the purpose of implementation, we decompose a original image using wavelet transform at level 3. After we classify transformed coefficients of other subbands using neural network except for the lowest subband LL$_3$, we apply a above mentioned watermark insert method. In the experimental results, we found that it has a good quality and robust about many attacks.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.569-589
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• 2018

Cloud computing, also known as "country as you go", is used to turn any computer into a dematerialized architecture in which users can access different services. In addition to the daily evolution of stakeholders' number and beneficiaries, the imbalance between the virtual machines of data centers in a cloud environment impacts the performance as it decreases the hardware resources and the software's profitability. Our axis of research is the load balancing between a data center's virtual machines. It is used for reducing the degree of load imbalance between those machines in order to solve the problems caused by this technological evolution and ensure a greater quality of service. Our article focuses on two main phases: the pre-classification of tasks, according to the requested resources; and the classification of tasks into levels ('odd levels' or 'even levels') in ascending order based on the meta-heuristic "Bat-algorithm". The task allocation is based on levels provided by the bat-algorithm and through our mathematical functions, and we will divide our system into a number of virtual machines with nearly equal performance. Otherwise, we suggest different classes of virtual machines, but the condition is that each class should contain machines with similar characteristics compared to the existing binary search scheme.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.3121-3131
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• 2014

Vulnerabilities related to memory have been known as major threats to the security of a computer system. Actually, the number of attacks using memory vulnerability has been increased. Accordingly, various memory protection mechanisms have been studied and implemented on operating system while new attack techniques bypassing the protection systems have been developed. Especially, buffer overflow attacks have been developed as Return-Oriented Programing(ROP) and Jump-Oriented Programming(JOP) called Code Re-used attack to bypass the memory protection mechanism. Thus, in this paper, I analyzed code re-use attack techniques emerged recently among attacks related to memory, as well as analyzed various detection mechanisms proposed previously. Based on the results of the analyses, a mechanism that could detect various code re-use attacks on a binary level was proposed. In addition, it was verified through experiments that the proposed mechanism could detect code re-use attacks effectively.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1372-1381
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• 2017

In this paper, a texture feature extraction method using local energy and local correlation of Gabor transformed images is proposed and applied to an image retrieval system. The Gabor wavelet is known to be similar to the response of the human visual system. The outputs of the Gabor transformation are robust to variants of object size and illumination. Due to such advantages, it has been actively studied in various fields such as image retrieval, classification, analysis, etc. In this paper, in order to fully exploit the superior aspects of Gabor wavelet, local energy and local correlation features are extracted from Gabor transformed images and then applied to an image retrieval system. Some experiments are conducted to compare the performance of the proposed method with those of the conventional Gabor method and the popular rotation-invariant uniform local binary pattern (RULBP) method in terms of precision vs recall. The Mahalanobis distance is used to measure the similarity between a query image and a database (DB) image. Experimental results for Corel DB and VisTex DB show that the proposed method is superior to the conventional Gabor method. The proposed method also yields precision and recall 6.58% and 3.66% higher on average in Corel DB, respectively, and 4.87% and 3.37% higher on average in VisTex DB, respectively, than the popular RULBP method.

• Elastomers and Composites
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• v.39 no.4
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• pp.318-323
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• 2004

Cloud-point and bubble-point curves for poly(ethylene-co-13.8 mol% octene) ($PEO_{13.8}$) and Poly(ethylene-co-15.3 mol% octene) ($PEO_{15.3}$) were determined up to $150^{\circ}C$ and 450 bar in hydrocarbons which have different molecular size and structure. Whereas ($PEO_{15.3}$+ n-pentane) system has cloud-point and bubble-point type transitions, ($PEO_{15.3}$+ n-propane) and ($PEO_{15.3}$+ n-butane) systems do only cloud-point type transition. In cyclo-pentane, -hexane, -heptane, and -octane, $PEO_{15.3}$ has a bubble-point transition. ($PEO_{13.8}$+ n-butane) mixture has a critical mixture concentration at 5 wt% PEO. (PEO + hydrocarbon) mixtures exhibit LCST type behavior. Solubility of PEO increases with hydrocarbon size due to increasing dispersion interaction which is favorable to dissolve PEO.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.288-296
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• 2021

Automated face recognition in a runtime environment is gaining more and more important in the fields of surveillance and urban security. This is a difficult task keeping in mind the constantly volatile image landscape with varying features and attributes. For a system to be beneficial in industrial settings, it is pertinent that its efficiency isn't compromised when running on roads, intersections, and busy streets. However, recognition in such uncontrolled circumstances is a major problem in real-life applications. In this paper, the main problem of face recognition in which full face is not visible (Occlusion). This is a common occurrence as any person can change his features by wearing a scarf, sunglass or by merely growing a mustache or beard. Such types of discrepancies in facial appearance are frequently stumbled upon in an uncontrolled circumstance and possibly will be a reason to the security systems which are based upon face recognition. These types of variations are very common in a real-life environment. It has been analyzed that it has been studied less in literature but now researchers have a major focus on this type of variation. Existing state-of-the-art techniques suffer from several limitations. Most significant amongst them are low level of usability and poor response time in case of any calamity. In this paper, an improved face recognition system is developed to solve the problem of occlusion known as FRS-OCC. To build the FRS-OCC system, the color and texture features are used and then an incremental learning algorithm (Learn++) to select more informative features. Afterward, the trained stack-based autoencoder (SAE) deep learning algorithm is used to recognize a human face. Overall, the FRS-OCC system is used to introduce such algorithms which enhance the response time to guarantee a benchmark quality of service in any situation. To test and evaluate the performance of the proposed FRS-OCC system, the AR face dataset is utilized. On average, the FRS-OCC system is outperformed and achieved SE of 98.82%, SP of 98.49%, AC of 98.76% and AUC of 0.9995 compared to other state-of-the-art methods. The obtained results indicate that the FRS-OCC system can be used in any surveillance application.