• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.43-52
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• 2018

Livestock production is the second largest economic activity of Pakistan's rural population, more specifically; sixty-seven percent of Pakistan's total population that live in rural areas sources their income from livestock activities. As this subsector of agriculture within rural Pakistan is so critical to Pakistan's economy it is especially important to further develop the sector through the introduction of cost effective, efficient, and practical technologies. In an effort to improve such an important sector within the agriculture sector in Pakistan research has been carried out to better understand the capabilities and feasibility of leveraging Internet of Things based technologies, such as, microprocessors and microcontrollers within Pakistan's livestock production and management. The internet of Things can potentially allow for the scaling of small-scale rural livestock production to larger operations through cost effective and efficient livestock management through the application of IoT technologies. This paper discusses the architecture models of IoT based smart animal farms and delves into the pitfalls and advantages of applying IoT technologies in this sector. In this work we will explore the cheap sensors to monitor the internal activities of cattle farm with the aim of using these sensors as part of system to detect the important operations that need on the time response. This system should provide the feed and water as required, and control the temperature in sheds to protect the cattle being ill and on heat, and humidity level .internet connection used to connect these devices with smartphones or computers. In this paper we proposed the architecture model of IoT based smart animal farm.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1493-1507
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• 2020

The LEOP Cal/Val (Launch and Early Operation Phase Calibration/Validation) was carried out during 6 months after KOMPSAT-3A (KOMPSAT-3A Korea Multi-Purpose Satellite-3A) was launched in March 2015. After LEOP Cal/Val was successfully completed, high resolution KOMPSAT-3A has been successfully distributing to users over the past 8 years. The sub-meter high-resolution satellite image data obtained from KOMPSAT-3A is used as basic data for qualitative and quantitative information extraction in various fields such as mapping, GIS (Geographic Information System), and national land management, etc. The KARI (Korea Aerospace Research Institute) periodically checks and manages the quality of KOMPSAT-3A's product and the characteristics of satellite hardware to ensure the accuracy and reliability of information extracted from satellite data of KOMPSAT-3A. To minimize the deterioration of image quality due to aging of satellite hardware, payload and attitude sensors of KOMPSAT-3A, continuous improvement of image quality has been carried out. In this paper, the Cal/Val work-flow defined in the KOMPSAT-3A development phase was illustrated for the period of before and after the launch. The MTF, SNR, and location accuracy are the key parameters to estimate image quality and the methods of the measurements of each parameter are also described in this work. On the basis of defined quality parameters, the performance was evaluated and measured during the period of after LEOP Cal/Val. The current status and characteristics of MTF, SNR, and location accuracy of KOMPSAT-3A from 2016 to May 2020 were described as well.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.141-148
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• 2022

Recently, reinforcement learning combined with deep neural network technology has achieved remarkable success in various fields such as board games such as Go and chess, computer games such as Atari and StartCraft, and robot object manipulation tasks. However, such deep reinforcement learning describes states, actions, and policies in vector representation. Therefore, the existing deep reinforcement learning has some limitations in generality and interpretability of the learned policy, and it is difficult to effectively incorporate domain knowledge into policy learning. On the other hand, dNL-RRL, a new relational reinforcement learning framework proposed to solve these problems, uses a kind of vector representation for sensor input data and lower-level motion control as in the existing deep reinforcement learning. However, for states, actions, and learned policies, It uses a relational representation with logic predicates and rules. In this paper, we present dNL-RRL-based policy learning for transportation mobile robots in a manufacturing environment. In particular, this study proposes a effective method to utilize the prior domain knowledge of human experts to improve the efficiency of relational reinforcement learning. Through various experiments, we demonstrate the performance improvement of the relational reinforcement learning by using domain knowledge as proposed in this paper.

• Journal of Practical Agriculture & Fisheries Research
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• v.23 no.2
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• pp.99-111
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• 2021

The connected farm that agricultural land, agricultural machinery and farmer are connected with an IoT gateway is in the commercialization stage. That has increased productivity, efficiency and profitability by intimate information exchange among those. In order to develop the educational program of intelligent agricultural machinery and the agricultural machinery safety education performance indicator, this study analyzed patent trends of agricultural machine with unmanned technology used in agriculture and efficiency technology applied advanced technologies such as ICT, robots and artificial intelligence. We investigated and analyzed patent trends in agricultural machinery of Korea, the USA and Japan as well as the countries in Europe. The United States is an advanced country in the field of unmanned technology and efficiency technology used in agriculture. Agricultural automation technology in Korea is insufficient compared to developed countries, which means rapid technological development is needed. In the sub-fields of field automation technology, path generation and following technology and working machine control technology through environmental awareness have activated.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.4
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• pp.227-233
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• 2022

The 3D-printing technique is used for manufacturing objects by adding multiple layers, and it is relatively easy to manufacture objects with complex shapes. The 3D concrete printing technique, which incorporates 3D printing into the construction industry, does not use a formwork when placing concrete, and it requires less workload and labor, so economical construction is possible. However, 3D-printed concrete is expected to have a lower strength than that of molded concrete. In this study, the properties of 3D-printed concrete were analyzed. To fabricate the 3D-printed concrete samples, the extrusion path and shape of the samples were designed with Ultimaker Cura. Based on this, G-codes were generated to control the 3D printer. The optimal concrete mixing proportion was selected considering such factors as extrudability and buildability. Molded samples with the same dimensions were also fabricated for comparative analysis. The properties of each sample were measured through a three-point bending test and uniaxial compression test, and a comparative analysis was performed.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.23-31
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• 2010

Due to the fact that fisheye lens can provide super wide angles with the minimum number of cameras, field-of-view over 180 degrees, many vehicles are attempting to mount the camera system. Not only use the camera as a viewing system, but also as a camera sensor, camera calibration should be preceded, and geometrical correction on the radial distortion is needed to provide the images for the driver's assistance. In this thesis, we introduce a geometric correction technique to minimize the loss of the image data from a vehicle fish-eye lens having a field of view over $180^{\circ}$, and a asymmetric distortion. Geometric correction is a process in which a camera model with a distortion model is established, and then a corrected view is generated after camera parameters are calculated through a calibration process. First, the FOV model to imitate a asymmetric distortion configuration is used as the distortion model. Then, we need to unify the axis ratio because a horizontal view of the vehicle fish-eye lens is asymmetrically wide for the driver, and estimate the parameters by applying a non-linear optimization algorithm. Finally, we create a corrected view by a backward mapping, and provide a function to optimize the ratio for the horizontal and vertical axes. This minimizes image data loss and improves the visual perception when the input image is undistorted through a perspective projection.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1C
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• pp.43-52
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• 2006

Despite several constitutive models have been proposed and applied, it is still difficult to choose a suitable model and to estimate adequate analysis parameters. Furthermore, a cyclic shear behavior under the volume change caused by the seepage is more complex. None of the constitutive model is available at present in the expression of the cyclic behavior of soil under an additional volume change condition by seepage. Therefore, a new geotechnical hybrid simulation system which can control the pore water immigration was developed. The system enables a quantitative evaluation of the residual deformation such as lateral spreading and settlement caused by the liquefaction. The seismic responses in a one-dimensional slightly inclined multilayered soil system are taken into consideration, and the soils are governed by both equation of motion and the continuity equation. Furthermore, the estimation and the selection of the soil parameter for the representation of the strong nonlinearity of the material are not required, because soil behaviors under the earthquake motions are directly introduced instead of a numerical soil constitutive model. This paper presents the concept and specifications of the system. By applying the system to an example problem, the permeability effect on the seismic response during cyclic shear is studied. The importance of the volume change characteristics of sandy soil during and after cyclic shear is shown in conclusion.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.69-75
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• 2024

This paper proposes an innovative cognitive IoT framework specifically designed for fog computing (FC) in the context of industrial Internet of Things (IIoT). The discourse in this paper is centered on the intricate design and functional architecture of the Cognitive IoT platform. A crucial feature of this platform is the integration of machine learning (ML) and artificial intelligence (AI), which enhances its operational flexibility and compatibility with a wide range of industrial applications. An exemplary application of this platform is highlighted through the Predictive Maintenance-as-a-Service (PdM-as-a-Service) model, which focuses on real-time monitoring of machine conditions. This model transcends traditional maintenance approaches by leveraging real-time data analytics for maintenance and management operations. Empirical results substantiate the platform's effectiveness within a fog computing milieu, thereby illustrating its transformative potential in the domain of industrial IoT applications. Furthermore, the paper delineates the inherent challenges and prospective research trajectories in the spheres of Cognitive IoT and Fog Computing within the ambit of Industrial Internet of Things (IIoT).

• Journal of Bio-Environment Control
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• v.29 no.4
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• pp.399-405
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• 2020

Recently, it is difficult to produce uniform scions and rootstocks with high quality in a greenhouse due to weather extremes. The closed transplant production system is useful for producing scions and rootstocks with desirable morphological characteristics by environment control regardless of weather outside. In this study, we investigated transpiration rates and growth of cucumber and tomato scions and rootstocks grown under different light intensity conditions for precise irrigation control in a closed transplant production system. Hanging system to measure continuously the weight of plug tray consisting of seedlings and substrate with load-cell was installed in each growing bed. Using this system, we confirmed initial wilting point of cucumber and tomato seedlings, and conducted subirrigation when moisture content of substrate was not below 50%. The irrigation time of cucumber scions and rootstocks were 7 and 6 days after sowing, respectively. In tomato scions and rootstocks grown under PPF (photosynthetic photon flux) 300 μmol·m^-2·s^-1, the irrigation time were 5, 8, 11, and 13 days after sowing. Increasing light intensity increased transpiration rates and differences of transpiration rates by light intensity was higher in tomato seedlings. The growth of cucumber and tomato seedlings was promoted by increasing light intensity, especially, hypocotyl elongation and stem thickening was affected by light intensity. Cumulative transpiration rate of plug tray in cucumber and tomato seedlings was increased by increasing light intensity, and daily transpiration rate per seedling was regressed by 1st-order linear equation with high correlation coefficient. Estimation of transpiration rates by weighing continuously plug tray of vegetable seedlings can be useful to control more accurately irrigation schedule in a closed transplant production system.

• Proceedings of the KOR-BRONCHOESO Conference
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• 1993.05a
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• pp.97-97
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• 1993

Primary tumor arises infrequently in the parotid gland and generally, only about 20 to 40 percent of which prove to be malignant. They are characterized by histopathologic diversity, slow tumor growth, significant proportion of patients who have received previous treatment elsewhere. We have reviewed retrospectively 101 cases of parotid gland tumors which were treated for the recent eight years (1985-1992), Non-neoplastic tumor-like lesions were all excluded.