• Journal of Broadcast Engineering
• /
• v.26 no.4
• /
• pp.368-376
• /
• 2021

Artificial intelligence clouds help to efficiently develop the autonomous things integrating artificial intelligence technologies and control technologies by sharing the learned models and providing the execution environments. The existing autonomous things development technologies only take into account for the accuracy of artificial intelligence models at the cost of the increment of the complexity of the models including the raise up of the number of the hidden layers and the kernels, and they consequently require a large amount of computation. Since resource-constrained computing environments, could not provide sufficient computing resources for the complex models, they make the autonomous things violate time criticality. In this paper, we propose a digital twin software development framework that selects artificial intelligence models optimized for the computing environments. The proposed framework uses a load estimation DNN model to select the optimal model for the specific computing environments by predicting the load of the artificial intelligence models with digital twin data so that the proposed framework develops the control software. The proposed load estimation DNN model shows up to 20% of error rate compared to the formula-based load estimation scheme by means of the representative CNN models based experiments.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.11
• /
• pp.88-95
• /
• 2018

Maintainability indicates how easily a system can be restored to the normal state when a system failure occurs. Systems developed to have high maintainability can be competitive due to reduced maintenance time, workforce and resources. Quantification of the maintainability is possible in many ways, but only after prototype production or with historical data. As such, the graph theory and 3D model data have been used, but there are limitations in management efficiency and early use. To solve this problem, we studied the maintainability index of weapon systems using SysML-based modeling and simulation technique. A SysML structure diagram was generated to simultaneously model the system design and maintainability of system components by reflecting the maintainability attributes acquired from the system engineering tool. Then, a SysML parametric diagram was created to quantify the maintainability through simulation linked with MATLAB. As a result, an integrated model to account for system design and maintainability simultaneously has been presented. The model can be used from early design stages to identify components with low maintainability index. The design of such components can be changed to improve maintainability and thus to reduce the risks of cost overruns and time delays due to belated design changes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.6
• /
• pp.469-481
• /
• 2018

DL (Deep Learning) is getting popular in various fields to implement artificial intelligence that resembles human learning and cognition. DL based on complicate structure of the ANN (Artificial Neural Network) requires computing power and computation cost. Variety of DL models with improved performance have been developed with powerful computer specification. The main purpose of this paper is to detect buildings from aerial images and evaluate performance of Mask R-CNN (Region-based Convolutional Neural Network) developed by FAIR (Facebook AI Research) team recently. Mask R-CNN is a R-CNN that is evaluated to be one of the best ANN models in terms of performance for semantic segmentation with pixel-level accuracy. The performance of the DL models is determined by training ability as well as architecture of the ANN. In this paper, we characteristics of the Mask R-CNN with various types of the images and evaluate possibility of the generalization which is the ultimate goal of the DL. As for future study, it is expected that reliability and generalization of DL will be improved by using a variety of spatial information data for training of the DL models.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.15 no.4
• /
• pp.83-92
• /
• 2005

D-OCSP-KIS proposed by Koga and Sakurai not only reduces the number or OCSP Responder's certificate but also criers the certificate status validation about OCSP Responder to the client. Therefore, D-OCSP-KIS is an effective method that can reduce the communication cost, computational time and storage consumption in client, but it has some problems. In case an attacker accidentally acquires an OCSP Responder's session private key in a time period (e.g., one day), she can disguise as the OCSP Responder in the time period unless the OCSP Responder recognizes. She can offer the wrong response to the client using the hash value intercepted. And the server and user on I-commerce can have a serious confusion and damage. And the computation and releasing of hash chain can be a load to CA. Thus, we propose a method detecting immediately the exposure of an OCSP Responder's session private key and the abuse of hash value in D-OCSP-KIS.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.15 no.2
• /
• pp.23-36
• /
• 2005

The main obstacle hindering the wide deployment of identity-based cryptosystem is that the entity responsible for creating the private key has too much power. As a result, private keys are no longer private. One obvious solution to this problem is to apply the threshold technique. However, this increases the authentication computation, and communication cost during the key issuing phase. In this paper, we propose a new effi ient model for issuing multiple private keys in identity-based encryption schemes based on the Weil pairing that also alleviates the key escrow problem. In our system, the private key of a user is divided into two components, KGK (Key Description Key) and KUD(Key Usage Desscriptor), which are issued separately by different parties. The KGK is issued in a threshold manner by KIC (Key Issuing Center), whereas the KW is issued by a single authority called KUM (Key Usage Manager). Changing KW results in a different private key. As a result, a user can efficiently obtain a new private key by interacting with KUM. We can also adapt Gentry's time-slot based private key revocation approach to our scheme more efficiently than others. We also show the security of the system and its efficiency by analyzing the existing systems.

• Journal of Advanced Navigation Technology
• /
• v.26 no.5
• /
• pp.365-372
• /
• 2022

Compared to sensors mainly used in human activity recognition (HAR) systems, inertial measurement unit (IMU) sensors are small and light, so can achieve lightweight system at low cost. Therefore, in this paper, we propose a binary neural network (BNN) based gait pattern analysis system using IMU sensor, and present the design and implementation results of an FPGA-based accelerator for computational acceleration. Six signals for gait are measured through IMU sensor, and a spectrogram is extracted using a short-time Fourier transform. In order to have a lightweight system with high accuracy, a BNN-based structure was used for gait pattern classification. It is designed as a hardware accelerator structure using FPGA for computation acceleration of binary neural network. The proposed gait pattern analysis system was implemented using 24,158 logics, 14,669 registers, and 13.687 KB of block memory, and it was confirmed that the operation was completed within 1.5 ms at the maximum operating frequency of 62.35 MHz and real-time operation was possible.

• International Journal of Computer Science & Network Security
• /
• v.21 no.11
• /
• pp.345-353
• /
• 2021

Cloud computing represent a new era of computing that's forms through the combination of service-oriented architecture (SOA), Internet and grid computing with virtualization technology. Virtualization is a concept through which every cloud is enable to provide on-demand services to the users. Most IT service provider adopt cloud based services for their users to meet the high demand of computation, as it is most flexible, reliable and scalable technology. Energy based performance tradeoff become the main challenge in cloud computing, as its acceptance and popularity increases day by day. Cloud data centers required a huge amount of power supply to the virtualization of servers for maintain on- demand high computing. High power demand increase the energy cost of service providers as well as it also harm the environment through the emission of CO₂. An optimization of cloud computing based on energy-performance tradeoff is required to obtain the balance between energy saving and QoS (quality of services) policies of cloud. A study about power usage of resources in cloud data centers based on workload assign to them, says that an idle server consume near about 50% of its peak utilization power [1]. Therefore, more number of underutilized servers in any cloud data center is responsible to reduce the energy performance tradeoff. To handle this issue, a lots of research proposed as energy efficient algorithms for minimize the consumption of energy and also maintain the SLA (service level agreement) at a satisfactory level. VM (virtual machine) consolidation is one such technique that ensured about the balance of energy based SLA. In the scope of this paper, we explore reinforcement with fuzzy logic (RFL) for VM consolidation to achieve energy based SLA. In this proposed RFL based active VM consolidation, the primary objective is to manage physical server (PS) nodes in order to avoid over-utilized and under-utilized, and to optimize the placement of VMs. A dynamic threshold (based on RFL) is proposed for over-utilized PS detection. For over-utilized PS, a VM selection policy based on fuzzy logic is proposed, which selects VM for migration to maintain the balance of SLA. Additionally, it incorporate VM placement policy through categorization of non-overutilized servers as- balanced, under-utilized and critical. CloudSim toolkit is used to simulate the proposed work on real-world work load traces of CoMon Project define by PlanetLab. Simulation results shows that the proposed policies is most energy efficient compared to others in terms of reduction in both electricity usage and SLA violation.

• Korean Journal of Construction Engineering and Management
• /
• v.16 no.1
• /
• pp.52-63
• /
• 2015

Business facilities among domestic architectures have rapidly been constructed along with domestic economic development. It is an important facility taking the second largest proportion next to apartment buildings among current 31 building types of fire department classification of 2012 year for urban architectures. The expected service life of business facilities is 15 years, but 70% of those in urban areas have surpassed the 15 year service life as of the present 2014. Thus, the demand for urgent rehabilitation of such facilities is constantly increasing due to the aging and performance deterioration of the facilities'main finishing materials. Especially, the business facilities are being used for the lease of company office or private office, and such problems as aging and performance deterioration of the facilities could cause less competitive edge for leasing and real estate value depreciation for the O&M (Operation & Management) agent and the owner, respectively. Therefore, an effective planned rehabilitation as a preventive measure according to the standardized repair rate by the number of years after the construction is in need in order to prevent the aging and performance deterioration of the facilities(La et al. 2001). Nonetheless, domestic repair/rehabilitation standards based on the repair rate are mainly limited to apartment buildings and pubic institutions, resulting in impractical application of such standards to business facilities. It has been investigated and analyzed that annual repair rate data for each finishing material are required for examination of the applicability of the repair rate standard for the purpose of establishment of a repair plan. Hence, this study aimed at developing a repair rate computation model for finishing materials of the facilities and verifying the appropriateness of the annual repair rate for each finishing material through a case study after collecting and analyzing the repair history data of six business facilities. The results of this study are expected to contribute to the planning and implementation of more efficient repair/rehabilitation budget by preventing the waste of unpredicted repair cost and opportunity cost for the sake of the business facilities' owners and O&M agents.

• Journal of KIISE:Software and Applications
• /
• v.30 no.9
• /
• pp.829-842
• /
• 2003

In this Paper, we propose the new face detection and tracking method based on template matching for real-time applications such as, teleconference, telecommunication, front stage of surveillance system using face recognition, and video-phone applications. Since the main purpose of paper is to track a face regardless of various environments, we use template-based face tracking method. To generate robust face templates, we apply wavelet transform to the average face image and extract three types of wavelet template from transformed low-resolution average face. However template matching is generally sensitive to the change of illumination conditions, we apply Min-max normalization with histogram equalization according to the variation of intensity. Tracking method is also applied to reduce the computation time and predict precise face candidate region. Finally, facial components are also detected and from the relative distance of two eyes, we estimate the size of facial ellipse.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.42 no.6
• /
• pp.853-860
• /
• 2022

The purpose of this study is to suggest an improvement plan for the calculation method of the engineer standard wage rate (ESWR) and to compute a reasonable ESWR. To this end, an adequacy review of theESWR calculation criteria was conducted along with an extensive engineering industry survey. The survey results were analyzed using an effective response sample of 748 companies out of 1,000 survey samples extracted by stratifying the 5,879 survey population. The main results were as follows. ①When calculating the engineering service fee, the prime contractor's engineer wage is suitable for the ESWR. The ESWR can be estimated by the formula 'average wage÷[1-proportion of subcontract orders×(1-subcontract rate)].' ② The field survey showed that the number of monthly working days was 20.35-20.54 days at 99 % confidence interval, which was significantly different from the current standard (22 days). In addition, as a result of a legal review of the ESWR criteria, it was found that the number of working days should be calculated in accordance with the Labor Standards Act after 2022. ③ Applying government guidelines, the time difference between the wage survey and the ESWR application can be corrected by the past ESWR increase rate for a specific period. ④ Using modeling based on the analysis above, the current ESWR was 13.5-14.5 % lower than the appropriate level. A lower ESWR was driven by the non-reflection of subcontract structure (4.1 %), overestimation of monthly work days (6.8-7.8 %), and application of past wage (2.6 %). The proposed model is expected to be widely used in policy making, as it can provide a useful framework for calculating the standard wage rate in similar industries as well as calculating appropriate engineering fees.