• Journal of the Earthquake Engineering Society of Korea
• /
• v.27 no.2
• /
• pp.77-82
• /
• 2023

The structural analysis module is an essential part of any integrated structural system. Diverse integrated systems today require, from the analysis module, efficient real-time responses to real-time input such as earthquake signals, extreme weather-related forces, and man-made accidents. An integrated system may also be for the entire life span of a civil structure conceived during the initial conception, developed throughout various design stages, effectively used in construction, and utilized during usage and maintenance. All these integrated systems' essential part is the structural analysis module, which must be automated and computationally efficient so that responses may be almost immediate. The finite element method is often used for structural analysis, and for automation, many effective finite element meshes must be automatically generated for a given analysis. A computationally efficient finite element mesh generation scheme based on the r-h method of mesh refinement using strain deviations from the values at the Gauss points as error estimates from the previous mesh is described. Shape factors are used to sort out overly distorted elements. A standard cantilever beam analyzed by four-node plane stress elements is used as an example to show the effectiveness of the automated algorithm for a time-domain dynamic analysis. Although recent developments in computer hardware and software have made many new applications in integrated structural systems possible, structural analysis still needs to be executed efficiently in real-time. The algorithm applies to diverse integrated systems, including nonlinear analyses and general dynamic problems in earthquake engineering.

• Nuclear Engineering and Technology
• /
• v.56 no.6
• /
• pp.2343-2351
• /
• 2024

Accurately predicting the thermal hydraulic parameters of a transient reactor core under different working conditions is the first step toward reactor safety. Mass flow rate and temperature are important parameters of core thermal hydraulics, which have often been modeled as time series prediction problems. This study aims to achieve accurate and continuous prediction of core thermal hydraulic parameters under instantaneous conditions, as well as test the feasibility of a newly constructed gated recurrent unit (GRU) model based on the soft attention mechanism for core parameter predictions. Herein, the China Experimental Fast Reactor (CEFR) is used as the research object, and CEFR 1/2 core was taken as subject to carry out continuous predictive analysis of thermal parameters under transient conditions., while the subchannel analysis code named SUBCHANFLOW is used to generate the time series of core thermal-hydraulic parameters. The GRU model is used to predict the mass flow and temperature time series of the core. The results show that compared to the adaptive radial basis function neural network, the GRU network model produces better prediction results. The average relative error for temperature is less than 0.5 % when the step size is 3, and the prediction effect is better within 15 s. The average relative error of mass flow rate is less than 5 % when the step size is 10, and the prediction effect is better in the subsequent 12 s. The GRU model not only shows a higher prediction accuracy, but also captures the trends of the dynamic time series, which is useful for maintaining reactor safety and preventing nuclear power plant accidents. Furthermore, it can provide long-term continuous predictions under transient reactor conditions, which is useful for engineering applications and improving reactor safety.

• Journal of Smart Tourism
• /
• v.4 no.2
• /
• pp.5-14
• /
• 2024

This study explores the transformative potential of machine learning (ML) and ML-driven data analytics in the hospitality industry. It provides a comprehensive overview of this emerging method, from explaining ML's origins to introducing the evolution of ML-driven data analytics in the hospitality industry. The present study emphasizes the shift embodied in ML, moving from explicit programming towards a self-learning, adaptive approach refined over time through big data. Meanwhile, social media analytics has progressed from simplistic metrics deriving nuanced qualitative insights into consumer behavior as an industry-specific example. Additionally, this study explores innovative applications of these innovative technologies in the hospitality sector, whether in demand forecasting, personalized marketing, predictive maintenance, etc. The study also emphasizes the integration of ML and social media analytics, discussing the implications like enhanced customer personalization, real-time decision-making capabilities, optimized marketing campaigns, and improved fraud detection. In conclusion, ML-driven hospitality data analytics have become indispensable in the strategic and operation machinery of contemporary hospitality businesses. It projects these technologies' continued significance in propelling data-centric advancements across the industry.

• Journal of KIISE:Software and Applications
• /
• v.27 no.5
• /
• pp.529-542
• /
• 2000

Recent years, the use of multimedia information is rapidly increasing, and the video media is the most rising one than any others, and this field Integrates all the media into a single data stream. Though the availability of digital video is raised largely, it is very difficult for users to make the effective video access, due to its length and unstructured video format. Thus, the minimal interaction of users and the explicit definition of video structure is a key requirement in the lately developing image and video management systems. This paper defines the terms and hierarchical video structure, and presents the system, which construct the clustering-based video hierarchy, which facilitate users by browsing the summary and do a random access to the video content. Instead of using a single feature and domain-specific thresholds, we use multiple features that have complementary relationship for each other and clustering-based methods that use normalization so as to interact with users minimally. The stage of shot boundary detection extracts multiple features, performs the adaptive filtering process for each features to enhance the performance by eliminating the false factors, and does k-means clustering with two classes. The shot list of a result after the proposed procedure is represented as the video hierarchy by the intelligent unsupervised clustering technique. We experimented the static and the dynamic movie videos that represent characteristics of various video types. In the result of shot boundary detection, we had almost more than 95% good performance, and had also rood result in the video hierarchy.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.2
• /
• pp.618-633
• /
• 2014

Relay technology is becoming more important for mobile communications and wireless internet of things (IoT) networking because of the extended access network coverage range and reliable quality of service (QoS) it can provide at low power consumption levels. Existing mobile multihop relay (MMR) technology uses fixed-point stationary relay stations (RSs) and a divided time-frame (or frequency-band) to support the relay operation. This approach has limitations when a local fixed-point stationary RS does not exist. In addition, since the time-frame (or frequency-band) channel resources are pre-divided for the relay operation, there is no way to achieve high channel utilization using intelligent opportunistic techniques. In this paper, a different approach is considered, where the use of mobile/IoT devices as RSs is considered. In applications that use mobile/IoT devices as relay systems, due to the very limited battery energy of a mobile/IoT device and unequal channel conditions to and from the RS, both minimum energy consumption and QoS support must be considered simultaneously in the selection and configuration of RSs. Therefore, in this paper, a mobile RS is selected and configured with the objective of minimizing power consumption while satisfying end-to-end data rate and bit error rate (BER) requirements. For the RS, both downlink (DL) to the destination system (DS) (i.e., IoT device or user equipment (UE)) and uplink (UL) to the base station (BS) need to be adaptively configured (using adaptive modulation and power control) to minimize power consumption while satisfying the end-to-end QoS constraints. This paper proposes a minimum transmission power consuming RS selection and configuration (MPRSC) scheme, where the RS uses cognitive radio (CR) sub-channels when communicating with the DS, and therefore the scheme is named MPRSC-CR. The proposed MPRSC-CR scheme is activated when a DS moves out of the BS's QoS supportive coverage range. In this case, data transmissions between the RS and BS use the assigned primary channel that the DS had been using, and data transmissions between the RS and DS use CR sub-channels. The simulation results demonstrate that the proposed MPRSC-CR scheme extends the coverage range of the BS and minimizes the power consumption of the RS through optimal selection and configuration of a RS.

• Journal of IKEEE
• /
• v.13 no.4
• /
• pp.116-124
• /
• 2009

Recently the CPU performance of modem chipsets or multimedia processors of mobile phone is as high as notebook PC. That is why mobile phone has been emerged as a leading ICON on the convergence of consumer electronics. The various applications of mobile phone such as DMB, digital camera, video telephony and internet full browsing are servicing to consumers. To meet all the demands the image quality has been increasingly important. Mobile phone is a portable device which is widely using in both the indoor and outside environments, so it is needed to be overcome to deteriorate image quality depending on environmental light source. Furthermore touch window is popular on the mobile display panel and it makes contrast loss because of low transmittance of ITO film. This paper presents the image enhancement algorithm to be embedded on image enhancement SoC. In contrast enhancement, we propose Clipped histogram stretching method to make it adaptive with the input images, while S-shape curve and gain/offset method for the static application And CIELCh color space is used to sunlight readability enhancement by controlling the lightness and chroma components which is depended on the sensing value of light sensor. Finally the performance of proposed algorithm is evaluated by using histogram, RGB pixel distribution, entropy and dynamic range of resultant images. We expect that the proposed algorithm is suitable for image enhancement of embedded SoC system which is applicable for the small-sized mobile display.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.14 no.1
• /
• pp.81-88
• /
• 2003

For driver's convenience, the ACC(Adaptive Cruise Control) requires a system which determines the direction of vehicles and controls the vehicle to keep the distance among the automobiles constant. This paper describes the microstrip array antennas designed to operate at 24 GHz, and used as a direction indicator of moving vehicles. 8${\times}$2 transmit array antenna with wide beamwidth, 8${\times}$4 receive center array antenna, and two 8${\times}$8 receive array antennas with narrow beamwidth were designed and fabricated. Measurement results for the arrays showed that the azimuthal beamwidth is 50$^{\circ}$and the gain is 16.7 dBi for the transmit array antenna. For the receive array antenna, the center, the left, and the right array antenna have beamwidths of 20$^{\circ}$, 13$^{\circ}$, 13$^{\circ}$respectively, and have gains of more than 20 dBi. The left and right array antenna have the beam tilt angle of ${\pm}$18$^{\circ}$. The measured radiation patterns showed a good agreement with the simulated patterns, and the designed array antennas are suitable fur detecting 3 directions of the vehicle within the scan angle area.

• The KIPS Transactions:PartC
• /
• v.11C no.2
• /
• pp.263-268
• /
• 2004

The end-to-end characteristic Is an important factor for QoS support. Since network users and required bandwidths for applications increase, the efficient usage of networks has been intensively investigated for the better utilization of network resources. The distributed adaptive routing is the typical routing algorithm that is used in the current Internet. The DCLC(Delay Constrained 1.east Cost) path problem has been shown to be NP-hard problem. The path cost of LD path is relatively more expensive than that of LC path, and the path delay of LC path is relatively higher than that of LD path in DCLC problem. In this paper, we investigate the performance of heuristic algorithm for the DCLC problem with new factor which is probabilistic combination of cost and delay. Recently Dr. Salama proposed a polynomial time algorithm called DCUR. The algorithm always computes a path, where the cost of the path is always within 10% from the optimal CBF. Our evaluation showed that heuristic we propose is more than 38% better than DCUR with cost when number of nodes is more than 200. The new factor takes in account both cost and delay at the same time.

• Journal of KIISE:Software and Applications
• /
• v.36 no.2
• /
• pp.169-177
• /
• 2009

In this paper, we propose a new shot boundary detection method which is optimized for news video story parsing. This new news shot boundary detection method was designed to satisfy all the following requirements: 1) minimizing the incorrect data in data set for anchor shot detection by improving the recall ratio 2) detecting abrupt cuts and gradual transitions with one single algorithm so as to divide news video into shots with one scan of data set; 3) classifying shots into static or dynamic, therefore, reducing the search space for the subsequent stage of anchor shot detection. The proposed method, based on singular value decomposition with incremental clustering and mercer kernel, has additional desirable features. Applying singular value decomposition, the noise or trivial variations in the video sequence are removed. Therefore, the separability is improved. Mercer kernel improves the possibility of detection of shots which is not separable in input space by mapping data to high dimensional feature space. The experimental results illustrated the superiority of the proposed method with respect to recall criteria and search space reduction for anchor shot detection.

• Journal of KIISE:Software and Applications
• /
• v.37 no.2
• /
• pp.110-119
• /
• 2010

In this paper, we propose an automatic segmentation of the prostate using intensity distribution and gradient information in MR images. First, active shape model using adaptive intensity profile and multi-resolution technique is used to extract the prostate surface. Second, hole elimination using geometric information is performed to prevent the hole from occurring by converging the surface shape to the local optima. Third, the surface shape with large anatomical variation is corrected by using 2D gradient information. In this case, the corrected surface shape is often represented as rugged shape which is generated by the limited number of vertices. Thus, it is reconstructed by using surface modelling and smoothing. To evaluate our method, we performed the visual inspection, accuracy measures and processing time. For accuracy evaluation, the average distance difference and the overlapping volume ratio between automatic segmentation and manual segmentation by two radiologists are calculated. Experimental results show that the average distance difference was 0.3${\pm}$0.21mm and the overlapping volume ratio was 96.31${\pm}$2.71%. The total processing time of twenty patient data was 16 seconds on average.