• IEIE Transactions on Smart Processing and Computing
• /
• v.3 no.3
• /
• pp.110-117
• /
• 2014

This paper reports a depth-adaptive sharpness adjustment algorithm for stereoscopic perception improvement, and presents its field-programmable gate array (FPGA) implementation results. The first step of the proposed algorithm was to estimate the depth information of an input stereo video on a block basis. Second, the objects in the input video were segmented according to their depths. Third, the sharpness of the foreground objects was enhanced and that of the background was maintained or weakened. This paper proposes a new sharpness enhancement algorithm to suppress visually annoying artifacts, such as jagging and halos. The simulation results show that the proposed algorithm can improve stereoscopic perception without intentional depth adjustments. In addition, the hardware architecture of the proposed algorithm was designed and implemented on a general-purpose FPGA board. Real-time processing for full high-definition stereo videos was accomplished using 30,278 look-up tables, 24,553 registers, and 1,794,297 bits of memory at an operating frequency of 200MHz.

• The KIPS Transactions:PartA
• /
• v.13A no.6 s.103
• /
• pp.511-516
• /
• 2006

The data grid computing provides geographically distributed storage resources to solve computational problems with large-scale data. Unlike cache replacement policies in virtual memory or web-caching replacement, an optimal file replacement policy for data grids is the one of the important problems by the fact that file size is very large. The traditional file replacement policies such as LRU(Least Recently Used) LCB-K(Least Cost Beneficial based on K), EBR(Economic-based cache replacement), LVCT(Least Value-based on Caching Time) have the problem that they have to predict requests or need additional resources to file replacement. To solve theses problems, this paper propose SBR-k(Sized-based replacement-k) that replaces files based on file size. The results of the simulation show that the proposed policy performs better than traditional policies.

• Structural Engineering and Mechanics
• /
• v.45 no.6
• /
• pp.759-777
• /
• 2013

In this paper, a topology optimization method based on the element independent nodal density (EIND) is developed for continuum solids with multiple load cases and multiple constraints. The optimization problem is formulated ad minimizing the volume subject to displacement constraints. Nodal densities of the finite element mesh are used a the design variable. The nodal densities are interpolated into any point in the design domain by the Shepard interpolation scheme and the Heaviside function. Without using additional constraints (such ad the filtering technique), mesh-independent, checkerboard-free, distinct optimal topology can be obtained. Adopting the rational approximation for material properties (RAMP), the topology optimization procedure is implemented using a solid isotropic material with penalization (SIMP) method and a dual programming optimization algorithm. The computational efficiency is greatly improved by multithread parallel computing with OpenMP to run parallel programs for the shared-memory model of parallel computation. Finally, several examples are presented to demonstrate the effectiveness of the developed techniques.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.12 no.1
• /
• pp.1-10
• /
• 2017

Recently, with the ever-increasing complexity of industrial robot systems, it has been greatly attention to adopt a multi-core based motion controller with high cost-performance ratio. In this paper, we propose a software architecture that aims to utilize the computing power of multi-core processors. The key concept of our architecture is to use shared memory for the interplay between threads running on separate processor cores. And then, we have integrated our proposed architecture with an industrial standard compliant IDE for automatic code generation of motion runtime. For the performance evaluation, we constructed a test-bed consisting of a motion controller with Preempt-RT Linux based dual-core industrial PC and a 3-axis industrial robot platform. The experimental results show that the actuation time difference between axes is 10 ns in average and bounded up to 689 ns under $1000{\mu}s$ control period, which can come up with real-time performance for industrial robot.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.4
• /
• pp.706-714
• /
• 2008

In this paper, we suggest a practical and flexible system architecture for JTAG(Joint Test Action Group) protection of application processors. From the view point of security, the debugging function through JTAG port can be abused by malicious users, so the internal structures and important information of application processors, and the sensitive information of devices connected to an application processor can be leak. This paper suggests a system architecture that disables computing power of computers used to attack processors to reveal important information. For this, a user authentication method is used to improve security strength by checking the integrity of boot code that is stored at boot memory, on booting time. Moreover for user authorization, we share hard wired secret key cryptography modules designed for functional operation instead of hardwired public key cryptography modules designed for only JTAG protection; this methodology allows developers to design application processors in a cost and power effective way. Our experiment shows that the security strength can be improved up to $2^{160}{\times}0.6$second when using 160-bit secure hash algorithm.

• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.412-413
• /
• 2007

정보시스템의 개발 및 유지보수에 대한 기준은 과기처 등에서 제정한 'S/W 개발비 산정기준'을 준용하고 있다. 그러나 본 기준이 Business Computing 환경을 기준으로 작성되었고, 전력계통 제어를 비롯한 각종 공정제어시스템 구축 환경에 부적합할 뿐 아니라 시스템의 뼈대(Frame)를 구성하는 H/W의 규모 산정이 누락되어 있는 상태이다. 전력거래소는 우리나라의 전력계통 환경에 적합한 한국형 에너지관리시스템(이하 K-EMS)의 국산화 개발을 각종 첨단 S/W의 탑재 기준에 따라 단계별(Baseline, Prototype, Fullscale)로 추진하면서, 각 단계에 가장 적합한 하드웨어의 용량 산정 기준을 선정하는 작업을 진행하고 있다. 이는 정보시스템 개발에서 자원의 낭비를 최소화하고 전체 개발비용을 절감 할 수 있다는 점에서 매우 중요하다. 본 연구에서는 K-EMS 시스템 국산화 개발을 위해 K-EMS가 수용할 각종 응용프로그램별 특성을 감안한 하드웨어의 적정 용량 산정 기준과 적용방안을 제시하고, CPU, Memory 등 세부 항목에 대한 고려항목을 언급함으로써 최적의 K-EMS 하드웨어 Sizing 산정방안을 소개하고자 한다.

• Journal of Digital Convergence
• /
• v.17 no.9
• /
• pp.161-171
• /
• 2019

Government transactions over wireless electronic devices are not safe and hence the messages are prone to attack. Thereby, devices supporting wireless Internet must assure the same level of security and privacy as the wired network. National public key infrastructure (NPKI) for electronic government used in the wired environment is not suitable for wireless environment for mobile government (mGovernment) because of the limitations of computing power, memory capacity and restricted battery power. This requires the development of a new NPKI for mGovernment, denoted as mNPKI, to developing countries, which provides the same security level as the wired NPKI. For the wireless environment requirements, mNPKI is based on short lived certificates. Analysis shows that mNPKI is well suited to wireless Internet and provides the same security requirement from the wired NPKI.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.1
• /
• pp.239-245
• /
• 2019

RISC-V is a free and open ISA enabling a new era of processor innovation through open standard collaboration. Born in academia and research, RISC-V ISA delivers a new level of free, extensible software and hardware freedom on architecture, paving the way for the next 50 years of computing design and innovation. In this paper, according to the emergence of RISC-V architecture, we describe the RISC-V processor instruction set constituted by arithmetic logic, memory, branch, control, status register, environment call and break point instructions. Using ModelSim and Quartus-II, 38 instructions of RISC-V has been successfully simulated and synthesized.

• Journal of Internet Computing and Services
• /
• v.22 no.3
• /
• pp.9-16
• /
• 2021

This study aims to develop a human activity recognition (HAR) system as a Deep-Learning (DL) classification model, distinguishing various human activities. We solely rely on the signals from a wristband accelerometer worn by a person for the user's convenience. 3-axis sequential acceleration signal data are gathered within a predefined time-window-slice, and they are used as input to the classification system. We are particularly interested in developing a Deep-Learning model that can outperform conventional machine learning classification performance. A total of 13 activities based on the laboratory experiments' data are used for the initial performance comparison. We have improved classification performance using the Convolutional Neural Network (CNN) combined with an auto-encoder feature reduction and parameter tuning. With various publically available HAR datasets, we could also achieve significant improvement in HAR classification. Our CNN model is also compared against Recurrent-Neural-Network(RNN) with Long Short-Term Memory(LSTM) to demonstrate its superiority. Noticeably, our model could distinguish both general activities and near-identical activities such as sitting down on the chair and floor, with almost perfect classification accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.10
• /
• pp.2701-2717
• /
• 2023

In this paper, a hybrid fuzzy-based method is suggested for determining India's best system for power generation. This suggested approach was created using a fuzzy-based combination of the Giza Pyramids Construction (GPC) and Recalling-Enhanced Recurrent Neural Network (RERNN). GPC is a meta-heuristic algorithm that deals with solutions for many groups of problems, whereas RERNN has selective memory properties. The evaluation of the current load requirements and production profile information system is the main objective of the suggested method. The Central Electricity Authority database, the Indian National Load Dispatch Centre, regional load dispatching centers, and annual reports of India were some of the sources used to compile the data regarding profiles of electricity loads, capacity factors, power plant generation, and transmission limits. The RERNN approach makes advantage of the ability to analyze the ideal power generation from energy data, however the optimization of RERNN factor necessitates the employment of a GPC technique. The proposed method was tested using MATLAB, and the findings indicate that it is effective in terms of accuracy, feasibility, and computing efficiency. The suggested hybrid system outperformed conventional models, achieving the top result of 93% accuracy with a shorter computation time of 6814 seconds.