• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3151-3168
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• 2021

Internet of Things (IoT) connects several objects with embedded sensors and they are capable of exchanging information between devices to create a smart environment. IoT smart devices have limited resources, such as batteries, computing power, and bandwidth, but comprehensive sensing causes severe energy restrictions, lowering data quality. The main objective of the proposal is to build a hybrid protocol which provides high data quality and reduced energy consumption in IoT sensor network. The hybrid protocol gives a flexible and complete solution for sensor selection problem. It selects a subset of active sensor nodes in the network which will increase the data quality and optimize the energy consumption. Since the unused sensor nodes switch off during the sensing phase, the energy consumption is greatly reduced. The hybrid protocol uses Dijkstra's algorithm for determining the shortest path for sensing data and Ant colony inspired variable path selection algorithm for selecting active nodes in the network. The missing data due to inactive sensor nodes is reconstructed using enhanced belief propagation algorithm. The proposed hybrid method is evaluated using real sensor data and the demonstrated results show significant improvement in energy consumption, data utility and data reconstruction rate compared to other existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3923-3942
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• 2022

Environment, price, regulation, and other factors influence the price of agricultural products, which is a social signal of product supply and demand. The price of many agricultural products fluctuates greatly due to the asymmetry between production and marketing details. Horticultural goods are particularly price sensitive because they cannot be stored for long periods of time. It is very important and helpful to forecast the price of horticultural products which is crucial in designing a cropping plan. The proposed method guides the farmers in agricultural product production and harvesting plans. Farmers can benefit from long-term forecasting since it helps them plan their planting and harvesting schedules. Customers can also profit from daily average price estimates for the short term. This paper study the time series models such as ARIMA, SARIMA, and neural network models such as BPN, LSTM and are used for wheat cost prediction in India. A large scale available data set is collected and tested. The results shows that since ARIMA and SARIMA models are well suited for small-scale, continuous, and periodic data, the BPN and LSTM provide more accurate and faster results for predicting well weekly and monthly trends of price fluctuation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.4
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• pp.729-740
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• 1994

In the shape optimal design based on h-version of FEM, the ideal mesh for the initial geometry most probably will not be suitable for the final analysis. Thus, it is necessary to remesh the geometry of the model at each stage of optimization. However, the p-version of FEM appears to be a very attractive alternative for use in shape optimization. The main advantages are as follows; firstly, the elements are not sensitive to distortion for interpolation polynomials of order $p{\geq}3$; secondly, even singular problems can be solved more efficiently with p-version than with the h-version by proper mesh design; thirdly, the initial mesh design are identical. The 2-D p-version model for shape optimization is presented on the basis of Bezier's curve fitting, gradient projection method, and integrals of Legendre polynomials. The numerical results are performed by p-version software RASNA.

• The Journal of the Korea Contents Association
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• v.9 no.5
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• pp.76-83
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• 2009

This paper presents a compression method for animated meshes or mesh sequences which have a shared connectivity and geometry streams. Our approach is based on static semi-regular mesh compression algorithm introduced by Khodakovky et al. Our encoding algorithm consists of two stages. First, the proposed technique creates a semi-regular mesh sequence from an input irregular mesh sequence. For semi-regular remeshing of irregular mesh sequences, this paper adapts the MAPS algorithm. However, MAPS cannot directly be performed to the input irregular mesh sequence. Thus, the proposed remesh algorithm revises the MAPS remesher using the clustering information, which classify coherent parts during the animation. The second stage uses wavelet transformation and clustering information to compress geometries of mesh sequences efficiently. The proposed compression algorithm predicts the vertex trajectories using the clustering information and the cluster transformation during the animation and compress the difference other frames from the reference frame in order to reduce the range of 3D position values.

• The korean journal of orthodontics
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• v.39 no.4
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• pp.203-212
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• 2009

Objective: The aim of this study was to evaluate the strain induced in the cortical bone surrounding an orthodontic microimplant during insertion in a self-drilling manner. Methods: A 3D finite element method was used to simulate the insertion of a microimplant (AbsoAnchor SH1312-7, Dentos Co., Daegu, Korea) into 1 mm thick cortical bone. The shape and dimension of thread groove in the center of the cortical bone produced by the cutting flute at the apical of the microimplant was obtained from animal test using rabbit tibias. A total of 3,600 analysis steps was used to calculate the 10 turns and 5 mm advancement of the microimplant. A series of remesh in the cortical bone was allowed to accommodate the change in the geometry accompanied by the implant insertion. Results: Bone strains of well higher than 4,000 microstrain, the reported upper limit for normal bone remodeling, were observed in the peri-implant bone along the whole length of the microimplant. Level of strains in the vicinity of either the screw tip or the valley part were similar. Conclusions: Bone strains from a microimplant insertion in a self-drilling manner might have a negative impact on the physiological remodeling of cortical bone.