• Journal of Korean Society of Forest Science
• /
• v.111 no.4
• /
• pp.567-582
• /
• 2022

Chainsaw use for motor-manual timber harvesting in South Korea is associated with worker safety issues. However, forestry operations such as timber harvesting have already been mechanized to reduce hazards to workers and increase productivity. This study analyzed the productivities and costs of felling and processing, felling and processing using an excavator-based stroke harvester for Pinus rigida and Quercus mongolica stands. To efficiently operate the stroke harvester, we developed a regression equation to estimate the productivities of felling and processing, felling, and processing operations,and we conducted sensitivity analysis of the operation costs using DBH and machine utilization. The felling and processing productivity was 6.53 and 4.02 m³/SMH for P. rigida a nd Q. mongolica, respectively, and the cost was 17,983 and 29,210 won/m³, respectively. The felling productivity for P. rigida a nd Q. mongolica wa s 40.9 and 23.0 m³/SMH, respectively, and the cost was 2,667 and 4,743 won/m³, respectively. The processing productivity for P. rigida and Q. mongolica was 8.25 and 7.75 m³/SMH, respectively, and the cost was 15,296 and 16,283 won/m³, respectively. In the developed regression equation, the DBH, traveling distance, and number of cuttings were found to be important factors (p<0.05). Therefore, it is necessary to construct a DB considering the various conditions and species associated with harvester operations, and further research is needed to increase the accuracy of predicting operation productivity and costs.

• Advances in materials Research
• /
• v.1 no.2
• /
• pp.129-146
• /
• 2012

Polycrystalline diamond is an ideal material for parts with micro-holes and has been widely used as dies and cutting tools in automotive, aerospace and woodworking industries due to its superior wear and corrosion resistance. In this research paper, the modeling and simultaneous optimization of multiple performance characteristics such as material removal rate and surface roughness of polycrystalline diamond (PCD) with ultrasonic machining process has been presented. The fuzzy logic and taguchi's quality loss function has been used. In recent years, fuzzy logic has been used in manufacturing engineering for modeling and monitoring. Also the effect of controllable machining parameters like type of abrasive slurry, their size and concentration, nature of tool material and the power rating of the machine has been determined by applying the single objective and multi-objective optimization techniques. The analysis of results has been done using the MATLAB 7.5 software and results obtained are validated by conducting the confirmation experiments. The results show the considerable improvement in S/N ratio as compared to initial cutting conditions. The surface roughness of machined surface has been measured by using the Perthometer (M4Pi, Mahr Germany).

• Journal of Power System Engineering
• /
• v.11 no.3
• /
• pp.22-28
• /
• 2007

Liquefied gas vaporizer is a machine to vaporize liquefied gas such as liquid nitrogen($LN_{2}$), liquefied natural gas(LNG), liquid oxygen($LO_{2}$) etc. For the air type vaporizer, the frozen dew is created by temperature drop (below 273 K) on vaporizer surface. The layer of ice make a contractions on vaporizer. The structure analysis on the heat transfer was studied to see the effect of geometric parameters of the vaporizer, which are length 1000 mm of various type vaporizer. Structure analysis result such as temperature variation, thermal stress and thermal strain have high efficiency of heat emission as increase of thermal conductivity. As the result, Frist, With-fin model shows high temperature distribution better than without-fin on the temperature analysis. Second, Without-fin model shows double contractions better then with-fin model under the super low temperature load on the thermal strain analysis. Third, Vaporizer fin can be apply not only heat exchange but also a stiffener of structure. Finally, we confirm that All model vaporizer can be stand for sudden load change because of compressive yield stress shows within 280 MPa on thermal stress analysis.

• Annual Conference of KIPS
• /
• 2024.05a
• /
• pp.891-894
• /
• 2024

The quest for reliability in Artificial Intelligence (AI) is progressively urgent, especially in the field of next generation wireless networks. Future Beyond 5G (B5G)/6G networks will connect a huge number of devices and will offer innovative services invested with AI and Machine Learning tools. Wireless communications, in general, and medium access control (MAC) techniques were among the fields that were heavily affected by this improvement. This study presents the applications and services of future communication networks. This study details the Medium Access Control (MAC) scheduler of Beyond-5G/6G from 3^rd Generation Partnership (3GPP) and highlights the current open research issues which are yet to be optimized. This study provides an overview of how AI plays an important role in improving next generation communication by solving MAC-layer issues such as resource scheduling and queueing. We will select C-V2X as our use case to implement our proposed MAC scheduling model.

• Journal of the korean academy of Pediatric Dentistry
• /
• v.44 no.3
• /
• pp.358-364
• /
• 2017

For the purpose of convenience and reducing time, newer bonding agents have been developed for composite resin restoration. Recently developed one bottle bonding system including etching, primer and adhesive can make procedures simpler and less technique-sensitive than old generation adhesives. The aim of this study was comparing the shear bond strength of new dentin bonding agents to the 5th generation bonding agent which had an etching step. 78 premolar teeth were randomly divided into three groups which were treated with $Tetric^{(R)}$ N-Bond Universal (Ivoclar Vivadent, Liechtenstein), $GC^{(R)}$ G-Premio BOND (GC Co., Japan) without additional etching step and $3M^{TM}$ Single Bond2 (3M ESPE, USA) with an etching step following manufacturer's instructions. $Filtek^{TM}$ Z-350 (3M ESPE, USA) composite resin was applied and light cured over bonding agents. For shear bond strength evaluation, universal testing machine was used with a wedge technique. As a result, shear bond strength of one step bonding agents was lower than two step bonding agent and there were statistically significant differences between them (p < 0.05). In addition, within the result of two new bonding agents, $Tetric^{(R)}$ N-Bond Universal showed significantly higher shear bond strength than $GC^{(R)}$ G-Premio BOND (p < 0.05).

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.32 no.5
• /
• pp.333-340
• /
• 2019

Tests using a middle velocity propulsion impact machine (MVPIM) were performed to verify the impact resistance capability of sandwich concrete panels (SCP) in a modular liquefied natural gas (LNG) outer tank, and numerical models were constructed and analyzed. $2{\times}2m$ specimens with plain sectional characteristics and specimens including a joint section were used. A 51 kg missile was accelerated above 45 m/s and impacted to have the design code kinetic energy. Impact tests were performed twice according to the design code and once for the doubled impact speed. The numerical models for simulating impact behaviors were created by LS-DYNA. The external steel plate and filled concrete of the panel were modeled as solid elements, the studs as beam elements, and the steel plates as elasto-plastic material with fractures; the CSCM material model was used for concrete. The front plate deformations demonstrated good agreement with those of other tests. However the rear plate deformations were less. In the doubled speed test for the plain section specimen, the missile punctured both plates; however, the front plate was only fractured in the numerical analysis. The impact energy of the missile was transferred to the filled concrete in the numerical analysis.

• Korea-Australia Rheology Journal
• /
• v.13 no.4
• /
• pp.169-177
• /
• 2001

Morphological, thermal, rheological, and mechanical properties of reactive compatabilized blends of poly(butylene terephthalate) (PBT) and Polyamide-6 (PA) containing EGMA copolymer were investigated using scanning electron microscopy (SEM), differential scanning calorimetry (DSC), advanced rheometric expansion system (ARES), and universal testing machine (UTM). From the results of thermal analysis by DSC, the melting point of the 30/70 PBT-PA blend was broadened after EGMA was added in the blends, since the enthalpy of melting of the PBT-PA somewhat decreased with the increase of EGMA content. From this result, it is suggested that the EGMA affected to the crystallization behavior and crystallinity of the PBT-PA blends. From SEM micrographs of the 70/30, 50/50, and 30/70 PBT-PA blends, the droplet size of the 30/70 PBT-PA blend was about 0.8 ${\mu}{\textrm}{m}$ which was smaller than that of the 50/50 and 70/30 PBT-PA blends. The complex viscosity of the 30/70 PBT-PA blend observed to be higher than that of the 50/50 and 70/30 PBT-PA blends. From the results of the morphology and rheological properties for the PBT-PA blends, it is suggested that the compatibility is increased in the 30/70 PBT-PA blend than the 50/50 and 70/30 PBT-PA blends. From the results of mechanical properties, it was found that the tensile strength of the 30/70 PBT-PA blend increased with the increase of EGMA up to 2 phr, while tensile strength of the blend in which EGMA content was higher than 2 phr decreased with the increase of EGMA content. From the results of morphological, thermal, rheological, and mechanical properties for the PBT-PA-EGMA blends, it is suggested that the EGMA could be used as a compatibilization role in the blends.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.10a
• /
• pp.514-517
• /
• 2017

In solar photovoltaic systems, power generation is greatly affected by the weather conditions, so it is essential to predict solar energy for stable load operation. Therefore, data on weather conditions are needed as inputs to machine learning algorithms for solar energy prediction. In this paper, we use 15 kinds of weather data such as the precipitation accumulated during the 3 hours of the surface, upward and downward longwave radiation average, upward and downward shortwave radiation average, the temperature during the past 3 hours at 2 m above from the ground and temperature from the ground surface as input data to the algorithm. We analyzed the statistical characteristics and correlations of weather data and extracted the downward and upward shortwave radiation averages as a major elements of a feature vector with high correlation of 70% or more with solar energy.

• International Journal of Computer Science & Network Security
• /
• v.21 no.12
• /
• pp.213-218
• /
• 2021

This paper proposes a technique for detecting a significant threat that attempts to get sensitive and confidential information such as usernames, passwords, credit card information, and more to target an individual or organization. By definition, a phishing attack happens when malicious people pose as trusted entities to fraudulently obtain user data. Phishing is classified as a type of social engineering attack. For a phishing attack to happen, a victim must be convinced to open an email or a direct message [1]. The email or direct message will contain a link that the victim will be required to click on. The aim of the attack is usually to install malicious software or to freeze a system. In other instances, the attackers will threaten to reveal sensitive information obtained from the victim. Phishing attacks can have devastating effects on the victim. Sensitive and confidential information can find its way into the hands of malicious people. Another devastating effect of phishing attacks is identity theft [1]. Attackers may impersonate the victim to make unauthorized purchases. Victims also complain of loss of funds when attackers access their credit card information. The proposed method has two major subsystems: (1) Data collection: different websites have been collected as a big data corresponding to normal and phishing dataset, and (2) distributed detection system: different artificial algorithms are used: a neural network algorithm and machine learning. The Amazon cloud was used for running the cluster with different cores of machines. The experiment results of the proposed system achieved very good accuracy and detection rate as well.

• Journal of Korean Society of Environmental Engineers
• /
• v.36 no.5
• /
• pp.317-324
• /
• 2014

Environmental tobacco smoke (ETS) samples were collected separately in mainstream and side-stream smoke using a self-designed smoking machine, and a total 40 of PM2.5 was collected with low volume air sampler at indoor environments with and without ETS in Daejeon, Korea. About 20 trace elements including toxic metals like As, Cr, Mn, Se, V, and Zn were determined in PM2.5 and ETS samples by instrumental neutron activation analysis (INAA). It is found that the emission factors of K, Cl, Na, and Al were much higher than those of toxic elements for both mainstream and side-stream smoke. The average concentration of PM2.5 was enriched by 1.5 times at smoking area ($58.7{\pm}18.1{\mu}g/m^3$) than at smoking free area ($38.6{\pm}12.7{\mu}g/m^3$). The concentration ratio of each element between smoking and smoking free area were ranged from 1.1 to 6.0 except Cu (1.0); especially, Ce (6.0), La (5.2), K (2.3), and Co (2.0) showed higher ratio, which suggests that the ETS is one of the possible increasing factors of PM2.5 and elemental concentration at indoor environment.