Journal of the Microelectronics and Packaging Society
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v.10
no.3
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pp.19-27
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2003
Surface finishes of PCB laminates are important in the solder joint reliability of flip chip package because the types and thicknesses of intermetallic compound(IMC), and compositions and hardness of solders are affected by them. In this study, effects of surface finishes of PCB on the low cycle fatigue resistance of Sn-based lead-free solders; Sn-3.5Ag, Sn-3.5Ag-XCu(X=0.75, 1.5), Sn-3.5Ag-XBi(X=2.5, 7.5) and Sn-0.7Cu were investigated for the Cu and Au/Ni surface finish treatments. Displacement controlled room temperature lap shear fatigue tests showed that fatigue resistance of Sn-3.5Ag-XCu(X=0.75, 1.5), Sn-3.5Ag and Sn-0.7Cu alloys were more or less the same each other but much better than that of Bi containing alloys regardless of the surface finish layer used. In general, solder joints on the Au/Ni finish showed better fatigue resistance than those on the Cu finish. Cross-sectional fractography revealed microcracks nucleation inside of the interfacial IMC near the solder mask edge, more frequently on the Cu than the Au/Ni surface finish. Macro cracks followed the solder/IMC interface in the Bi containing alloys, while they propagated in the solder matrix in other alloys. It was ascribed to the Bi segregation at the solder/IMC interface and the solid solution hardening effect of Bi in the $\beta-Sn$ matrix.
Kim, Su Jin;Park, Seo Jun;Jung, Sung Min;Noh, Jeong Ho;Hur, Youn Young;Nam, Jong Cheol;Park, Kyo Sun
Horticultural Science & Technology
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v.32
no.4
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pp.427-433
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2014
Trellising is an important cultural practice that affects grape quality and yield. Some grape cultivars require different trellising under different climate and soil conditions. To find suitable trellis conditions for grape cultivar 'Cheongsoo', we measured growth and fruit characteristics with three different trellis systems: curtain, Geneva double curtain (GDC), and modified T. The maximum light exposure of clusters in the curtain, GDC, modified T trellis systems was 670, 1,654, and $1,649{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, respectively. However, there was no difference in air temperature among the three trellis systems. Net $CO_2$ assimilation rate at $1,500{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$ light intensity was 13.4, 13.7, and $8.7{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$ in curtain, GDC, and modified T trellis systems, respectively. Trunk cross section area (TCSA) and bud burst rate were not significantly different among the three systems. Shoot number was 31.3, 47.0, and 37.0 in curtain, GDC, and modified T trellis systems, respectively. The shoot length was higher (243.9 cm) in the modified T trellis system than in the single curtain (171.1 cm) and GDC (151.5 cm) systems. Interior leaf number and leaf layer number were higher in the GDC system, in which there are two primary branches, in comparison to the modified T and curtain systems, which utilize one primary branch. Primary leaf area and lateral leaf area were significantly higher in the modified T trellis system in comparison to the GDC system. Berry weight, length and diameter, and total soluble solids were not significantly different among the three trellis systems. However, cluster weight and cluster number per tree were significantly higher in GDC. Titratable acidity was significantly lower in GDC. Collectively, our data suggest that the GDC trellis system is preferable for grape 'Cheongsoo' to maintain fruit quality and quantity in Korea.
In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.
The study was conducted to obtain the genetic information on heterosis and combining ability of the quantitative characters for F1 hybrid breeding in silkworms. Six parental varieties and each set of 30 diallel crosses in F1's were used as materials, and bred on the randomized complete block design with three replications. Fourteen characters were observed with the twenty samples in each tray. The data were analyzed for (1) heterosis and combining ability in F1 hybrid. The heterosis in the weight and the length of cocoon showed positively high at 24.51%, and 23.4%, respectively and the weight of the whole cocoon as well as the weight of the whole cocoon layer showed a siginificant heterosis ranging from 15.56% to 15.71% and from 17.14% to 19.01%, but the fifth and the total instar period showed negative heterosis. It was found that the combination between, C70XRomogua and N9 X Romogua showed highly a negative heterosis on the fifth instar period and for the cocoon weight. The female of N9+Sansuian and the male of Romogua X Sansurian have a high heterosis effect, on the cocoon shell weight, and Sansurian X Romogua(reciprocal) on the length and the weight of cocoon filament with no regard to sexuality. The significant maternal and cytoplasmic effect on heterosis of the cocoon weight and the cocoon shell weight were observed with the combinations, N9 X C5, N63 X C70 and on the length of the cocoon filament with the combinations, Sansurian X N63, Sansurian X C5, Sansurian X C70 and N9 X C70, N63 X C70 on the weight of cocoon filament. As mean squared of GCA, SCA and RCA were significant with these combining ability for all characters resulted from additive and non-additive altogether and there is a significant difference between reciprocals. Sansurian showed a negative GCA effect on the fifth and total larval duration, but the higher positive GCA effects took places with varieties N9 and C5 on the length, width, weight of cocoon, cocoon shell weight, percentage of cocoon shell weight, length and weight of cocoon filament, percentage of raw-silk with no regard to both generations and silkworm sexuality. The values of SCA between the cross combinations varied generation-wise and sex-wise. It was shown that SCA value for the fifth instar period was highly negative for Sansurian X C70, Romogua X C70, Sansurian X C5, Romogua X C5, but it was positive effect on the cocoon weight, cocoon shell weight with N9 X C5, and C70 X Sansurian, on the length of cocoon filament with N9 X C5, Romogua X Sansurian on the weight of cocoon filament between Romogua and N63 and on the percentage of raw-silk between the combination of Sansurian X Romoga.
Journal of Korean Society of Coastal and Ocean Engineers
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v.24
no.1
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pp.16-25
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2012
To calculate the total mass flux that change in dry and flood season in the Yeomha Channel of Gyeonggi Bay, the 13 hour bottom tracking observation was performed from the southern extremity. The value of the total mass flux(Lagrange flux) was calculated as the sum of the Eulerian flux value and stroke drift value and the tidal residual flow was harmonically analyzed through the least-squares method. Moreover, the average during the tidal cycle is essential to calculate the mass flux and the tidal residual flow and there is the need to equate the grid of repeatedly observed data. Nevertheless, due to the great differences in the studied region, the number of vertical grid tends to change according to time and since the horizontal grid differs according to the transport speed of the ship as a characteristic of the bottom tracking observation, differences occur in the horizontal and vertical grid for each hour. Hence, the present study has vertically and horizontally normalized(sigma coordinate) to equate the grid per each hour. When compared to the z-level coordinate system, the Sigma coordinate system was evaluated to have no irrationalities in data analysis with 5% of error. As a result of the analysis, the tidal residual flow displayed the flow pattern of sagging in the both ends in the main waterway direction of dry season. During flood season, it was confirmed that the tidal residual flow was vertical 2-layer flow. As a result of the total mass flux, the ebb properties of 359 cm/s and 261 cm/s were observed during dry and flood season, respectively. The total mass flux was moving the intertidal region between Youngjong-do and Ganghwa-do.
Journal of the korean academy of Pediatric Dentistry
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v.31
no.2
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pp.228-235
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2004
The development and proliferation of the mandibular condyle can be altered by changes in the biomechanical environment of the temporomandibular joint. The biomechanical loads were varied by feeding diets of different consistencies. The purpose of the present study was to determine whether changes of masticatory forces by feeding a soft diet can alter the trabecular bone morphology of the growing mouse mandibular condyle, by means of micro-computed tomography. Thirty-six female, 21 days old, C57BL/6 mice were randomly divided into two groups. Mice in the hard-diet control group were fed standard hard rodent pellets for 8 weeks. The soft-diet group mice were given soft ground diets for 8 weeks and their lower incisors were shortened by cutting with a wire cutter twice a week to reduce incision. After 8 weeks all animals were killed after they were weighed. Following sacrifice, the right mandibular condyle was removed. High spatial resolution tomography was done with a Skyscan Micro-CT 1072. Cross-sections were scanned and three-dimensional images were reconstructed from 2D sections. Morphometric and nonmetric parameters such as bone volume(BV), bone surface(BS), total volume(TV), bone volume fraction(BV/TV), surface to volume ratio(BS/BV), trabecular thickness(Tb. Th.), structure model index(SMI) and degree of anisotropy(DA) were directly determined by means of the software package at the micro-CT system. From directly determined indices the trabecular number(Tb. N.) and trabecular separation(Tb. Sp.) were calculated according to parallel plate model of Parfitt et al.. After micro-tomographic imaging, the samples were decalcified, dehydrated, embedded and sectioned for histological observation. The results were as follow: 1. The bone volume fraction, trabecular thickness(Tb. Th.) and trabecular number(Tb. N.) were significantly decreased in the soft-diet group compared with that of the control group (p<0.05). 2. The trabecular separation(Tb. Sp.) was significantly increased in the soft-diet group(p<0.05). 3. There was no significant differences in the surface to volume ratio(BS/BV), structure model index(SMI) and degree of anisotropy(DA) between the soft-diet group and hard-diet control group (p>0.05). 4. Histological sections showed that the thickness of the proliferative layer and total cartilage thickness were significantly reduced in the soft-diet group.
Kim, Joung-Ryul;Park, Jong-Sung;Choi, Young-Youn;Song, Oh-Sung
Journal of the Korean Vacuum Society
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v.17
no.6
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pp.528-537
/
2008
60 nm and 20 nm thick hydrogenated amorphous silicon(a-Si:H) layers were deposited on 200 nm $SiO_2$/single-Si substrates by inductively coupled plasma chemical vapor deposition(ICP-CVD). Subsequently, 30 nm-Ni layers were deposited by an e-beam evaporator. Finally, 30 nm-Ni/(60 nm and 20 nm) a-Si:H/200 nm-$SiO_2$/single-Si structures were prepared. The prepared samples were annealed by rapid thermal annealing(RTA) from $200^{\circ}C$ to $500^{\circ}C$ in $50^{\circ}C$ increments for 40 sec. A four-point tester, high resolution X-ray diffraction(HRXRD), field emission scanning electron microscopy(FE-SEM), transmission electron microscopy(TEM), and scanning probe microscopy(SPM) were used to examine the sheet resistance, phase transformation, in-plane microstructure, cross-sectional microstructure, and surface roughness, respectively. The nickel silicide from the 60 nm a-Si:H substrate showed low sheet resistance from $400^{\circ}C$ which is compatible for low temperature processing. The nickel silicide from 20 nm a-Si:H substrate showed low resistance from $300^{\circ}C$. Through HRXRD analysis, the phase transformation occurred with silicidation temperature without a-Si:H layer thickness dependence. With the result of FE-SEM and TEM, the nickel silicides from 60 nm a-Si:H substrate showed the microstructure of 60 nm-thick silicide layers with the residual silicon regime, while the ones from 20 nm a-Si:H formed 20 nm-thick uniform silicide layers. In case of SPM, the RMS value of nickel silicide layers increased as the silicidation temperature increased. Especially, the nickel silicide from 20 nm a-Si:H substrate showed the lowest RMS value of 0.75 at $300^{\circ}C$.
Objectives: The purpose of this study was to evaluate ${\mu}TBS$ (microtensile bond strength) of current dentin bonding adhesives which have different hydrophobicity with low-shrinkage silorane resin. Materials and Methods: Thirty-six human third molars were used. Middle dentin was exposed. The teeth were randomly assigned to nine experimental groups: Silorane self-etch adhesives (SS), SS + phosphoric acid etching (SS + pa), Adper easy bond (AE), AE + Silorane system bonding (AE + SSb), Clearfil SE bond (CSE), CSE + SSb, All-Bond 2 (AB2), AB2 + SSb, All-Bond 3 (AB3). After adhesive's were applied, the clinical crowns were restored with Filtek LS (3M ESPE). The 0.8 mm ${\times}$ 0.8 mm sticks were submitted to a tensile load using a Micro Tensile Tester (Bisco Inc.). Water sorption was measured to estimate hydrophobicity adhesives. Results: ${\mu}TBS$ of silorane resin to 5 adhesives: SS, 23.2 MPa; CSE, 19.4 MPa; AB3, 30.3 MPa; AB2 and AE, no bond. Additional layering of SSb: CSE + SSb, 26.2 MPa; AB2 + SSb, 33.9 MPa; AE + SSb, no bond. High value of ${\mu}TBS$ was related to cohesive failure. SS showed the lowest water sorption. AE showed the highest solubility. Conclusions: The hydrophobicity of adhesive increased, and silorane resin bond-strength was also increased. Additional hydrophobic adhesive layer did not increase the bond-strength to silorane resin except AB2 + SSb. All-Bond 3 showed similar ${\mu}TBS$ & water sorption with SS. By these facts, we could reach a conclusion that All-Bond 3 is a competitive adhesive which can replace the Silorane adhesive system.
Objectives: This study investigated the effect of infection control barrier thickness on power density, wavelength, and light diffusion of light curing units. Materials and Methods: Infection control barrier (Cleanwrap) in one-fold, two-fold, four-fold, and eightfold, and a halogen light curing unit (Optilux 360) and a light emitting diode (LED) light curing unit (Elipar FreeLight 2) were used in this study. Power density of light curing units with infection control barriers covering the fiberoptic bundle was measured with a hand held dental radiometer (Cure Rite). Wavelength of light curing units fixed on a custom made optical breadboard was measured with a portable spectroradiometer (CS-1000). Light diffusion of light curing units was photographed with DSLR (Nikon D70s) as above. Results: Power density decreased significantly as the layer thickness of the infection control barrier increased, except the one-fold and two-fold in halogen light curing unit. Especially, when the barrier was four-fold and more in the halogen light curing unit, the decrease of power density was more prominent. The wavelength of light curing units was not affected by the barriers and almost no change was detected in the peak wavelength. Light diffusion of LED light curing unit was not affected by barriers, however, halogen light curing unit showed decrease in light diffusion angle when the barrier was four-fold and statistically different decrease when the barrier was eight-fold (p < 0.05). Conclusions: It could be assumed that the infection control barriers should be used as two-fold rather than one-fold to prevent tearing of the barriers and subsequent cross contamination between the patients.
Kim, Kilho;Choi, Sangwoo;Chae, Moon-jung;Park, Heewoong;Lee, Jaehong;Park, Jonghun
Journal of Intelligence and Information Systems
/
v.25
no.1
/
pp.163-177
/
2019
As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.
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