• Journal of the Korea Society of Computer and Information
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• v.29 no.11
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• pp.31-40
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• 2024

In the summer, when the cooling load rises due to high temperatures, the hourly demand increases during the day and is relatively less at night compared to the day. These characteristics are considered important information in predicting summer electricity demand. However, if time information is simply expressed as a dummy variable, the model simply recognizes differences between time zones rather than learning changes in time. In this study, we would like to approach this problem by using a time variable using the Fourier transform. Time variables using the Fourier transform will be able to effectively learn differences between times. As a result of evaluating the type of time variable in the summer electricity demand forecast for 2022 and 2023 using the BiGRU model, the model using the time variable using Fourier transform showed the best performance with MAPE of 2.01% and 2.04% confirmed. The results of this study are expected to improve prediction accuracy in the summer when power usage increases and prevent problems such as large-scale power outages.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.1999-2007
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• 2010

Proxy Mobile IPv6(PMIPv6) is a network-based mobility management protocol and it does not require mobile node's involving in mobility management. In PMIPv6, the Mobile Access Gateway (MAG) incurs a high signaling cost to update the location of a mobile node to the remote Local Mobility Anchor (LMA) if it moves frequently. It may cause excessive signaling traffic and increase a high traffic load on LMA. Therefore, we propose a new mobility management scheme in proxy mobile IPv6 networks with dynamic paging support. To minimize signaling overhead, in our proposal, the size of the paging area is determined dynamically according the changes of mobility and traffic patterns of the mobile node. An analytic model is applied to determine the optimal size of the paging area. The cost analysis using fluid flow model presented in this paper shows that our proposal can achieve performance superior that of PMIPv6 scheme.

• Physical Therapy Rehabilitation Science
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• v.5 no.1
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• pp.34-39
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• 2016

Objective: Hip abductors play a role in providing stability and movement to the lower limbs. The purpose of this study was to examine the effects of hip abductor fatigue on static balance and gait in the general population. Design: One group pre-test post-test design. Methods: Thirteen university students in their twenties volunteered for the study and had underwent a functional assessment. To induce fatigue, the subjects were instructed to raise their dominant lower extremity up against a load of 50% of 1 repetition maximum while producing hip abduction in a side-lying position. Subjects were instructed to maintain an abduction speed of 30 repetitions per minute to induce fatigue. Muscle fatigue was considered to be established when subjects were unable to perform hip abduction three consecutive times along with the metronome. A post-test of balance and gait was performed immediately in order to prevent fatigue recovery. The center of pressure (COP) distance area was measured using the Zebris FDM-S Multifunction Force measuring plate. Gait performance was analyzed using the GAITRite. Results: The COP distance was increased after fatigue was induced. There was a significant increase in the standard deviation of the medio-lateral and antero-posteror distance (p<0.05). Although there was no significant difference in gait parameters, there was a significant decrease in single support time after fatigue was induced (p<0.05). Conclusions: There was an increase in static balance instability and a significant decrease in single support time during gait due to hip abductor muscle fatigue.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.5
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• pp.153-160
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• 2020

Energy Consumption Predictions for Industries has a prominent role to play in the energy management and control system as dynamic and seasonal changes are occurring in energy demand and supply. This paper introduces and explores the steel industry's predictive models of energy consumption. The data used includes lagging and leading reactive power lagging and leading current variable, emission of carbon dioxide (tCO2) and load type. Four statistical models are trained and tested in the test set: (a) Linear Regression (LR), (b) Radial Kernel Support Vector Machine (SVM RBF), (c) Gradient Boosting Machine (GBM), and (d) Random Forest (RF). Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) are used for calculating regression model predictive performance. When using all the predictors, the best model RF can provide RMSE value 7.33 in the test set.

• Geomechanics and Engineering
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• v.34 no.6
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• pp.697-726
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• 2023

Brittleness as an important property of rock plays a crucial role both in the failure process of intact rock and rock mass response to excavation in engineering geological and geotechnical projects. Generally, rock brittleness indices are calculated from the mechanical properties of rocks such as uniaxial compressive strength, tensile strength and modulus of elasticity. These properties are generally determined from complicated, expensive and time-consuming tests in laboratory. For this reason, in the present research, an attempt has been made to predict the rock brittleness indices from simple, inexpensive, and quick laboratory test results namely dry unit weight, porosity, slake-durability index, P-wave velocity, Schmidt rebound hardness, and point load strength index using multiple linear regression, exponential regression, support vector machine (SVM) with various kernels, generating fuzzy inference system, and regression tree ensemble (RTE) with boosting framework. So, this could be considered as an innovation for the present research. For this purpose, the number of 39 rock samples including five igneous, twenty-six sedimentary, and eight metamorphic were collected from different regions of Iran. Mineralogical, physical and mechanical properties as well as five well known rock brittleness indices (i.e., B₁, B₂, B₃, B₄, and B₅) were measured for the selected rock samples before application of the above-mentioned machine learning techniques. The performance of the developed models was evaluated based on several statistical metrics such as mean square error, relative absolute error, root relative absolute error, determination coefficients, variance account for, mean absolute percentage error and standard deviation of the error. The comparison of the obtained results revealed that among the studied methods, SVM is the most suitable one for predicting B₁, B₂ and B₅, while RTE predicts B₃ and B₄ better than other methods.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.9
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• pp.315-320
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• 2015

In cloud computing, server virtualization supports one or more virtual machines loaded on multiple operating systems on a single physical host server. Migration of a VM is moving the VM running on a source host to another physical machine called target host. A VM live migration is essential to support task performance optimization, energy efficiency and energy saving, fault tolerance and load balancing. In this paper, we propose open source based adaptive VM live migration technique. For this, we design VM monitoring module to decide VM live migration and open source based full-virtualization hypervisor.

• Smart Structures and Systems
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• v.19 no.2
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• pp.225-236
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• 2017

Railroad bridges in North America are an integral but aging part of the railroad network and are typically only monitored using visual inspections. When quantitative information is required for assessment, railroads often monitor bridges using accelerometers. However without a sensor to directly measure displacements, it is difficult to interpret these results as they relate to bridge performance. Digital Image Correlation (DIC) is a non-contact sensor technology capable of directly measuring the displacement of any visible bridge component. In this research, a railroad bridge was monitored under load using DIC and accelerometers. DIC measurements are directly compared to serviceability limits and it is observed that the bridge is compliant. The accelerometer data is also used to calculate displacements which are compared to the DIC measurements to assess the accuracy of the accelerometer measurements. These measurements compared well for zero-mean lateral data, providing measurement redundancy and validation. The lateral displacements from both the accelerometers and DIC at the supports were then used to determine the source of lateral displacements within the support system.

• Journal of Korea Multimedia Society
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• v.2 no.1
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• pp.22-29
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• 1999

In video-on-demand systems, movies are striped across the disks of the array in a video server to support multiple access. The blocks of the movies have to be placed carefully on the disks of the array in a video server in order to avoid load imbalance across these disks as well as to achieve maximum utilization of both space and bandwidth of these disks. This paper proposes a movie placement method called the GARR (group-alternation round-robin) that is based on the dynamic disk striping method considering the popularity of movie. The GARR uses group-alternation as movie selection policy and round-robin as data placement policy, where group-alternation allocates popular movie and unpopular movie groups to disks alternately. The performance of the GARR is evaluated by simulations.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.04a
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• pp.352-357
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• 2014

Recently the construction of stations under railway lines and railway sections passing through central area of cities are increasing, calling for an urgent establishment of countermeasures against railway vibration and its subsequent second-phase noise. Of technology developed up to now, the most efficient countermeasure is the floating slab track, a track system isolated from the sub-structure by springs. Developed in this study, anti-vibration device for floating slab track (HLRM-High Load Rubber Mount) Haman station affiliated to the primary measurement was conducted in October 2012, one year after the second measurement after 2013 to be carried out in November and we want to change that. It is expected to raise awareness for the need of technology self-support and to make a meaningful contribution to mitigating vibration and noise produced by the next-generation high-speed railway.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1729-1742
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• 2017

In designing System Protection Schemes (SPSs) in power systems, protecting transmission network against extreme undesired conditions becomes a significant challenge in mitigating the transmission line overloading. This paper presents an intelligent Special Protection and Control Scheme (SPCS) using of Differential Evolution with Adaptive Mutation (DEAM) approach to obtain the optimum generation rescheduling to solve the transmission line overloading problem in system contingency conditions. DEAM algorithm employs the attraction-repulsion idea that is applied in the electromagnetism-like algorithm to support the mutation process of the conventional Differential Evolution (DE) algorithm. Different N-1 contingency conditions under base and increase load demand are considered in this paper. Simulation results have been compared with those acquired from Genetic Algorithm (GA) application. Minimum severity index has been considered as the objective function. The final results show that the presented DEAM method offers better performance than GA in terms of faster convergence and less generation fuel cost. IEEE 30-bus test system has been used to prove the effectiveness and robustness of the proposed algorithm.