Purpose - The existing marketing studies using Social Network Analysis have assumed that network structure variables are time-invariant. However, a node's network position can fluctuate considerably over time and the node's network structure can be changed dynamically. Hence, if such a dynamic structural network characteristics are not specified for virtual goods purchase model, estimated parameters can be biased. In this paper, by comparing a time-invariant network structure specification model(base model) and time-varying network specification model(proposed model), the authors intend to prove whether the proposed model is superior to the base model. In addition, the authors also intend to investigate whether coefficients of network structure variables are random over time. Research design, data, and methodology - The data of this study are obtained from a Korean social network provider. The authors construct a monthly panel data by calculating the raw data. To fit the panel data, the authors derive random effects panel tobit model and multi-level mixed effects model. Results - First, the proposed model is better than that of the base model in terms of performance. Second, except for constraint, multi-level mixed effects models with random coefficient of every network structure variable(in-degree, out-degree, in-closeness centrality, out-closeness centrality, clustering coefficient) perform better than not random coefficient specification model. Conclusion - The size and importance of virtual goods market has been dramatically increasing. Notwithstanding such a strategic importance of virtual goods, there is little research on social influential factors which impact the intention of virtual good purchase. Even studies which investigated social influence factors have assumed that social network structure variables are time-invariant. However, the authors show that network structure variables are time-variant and coefficients of network structure variables are random over time. Thus, virtual goods purchase model with dynamic network structure variables performs better than that with static network structure model. Hence, if marketing practitioners intend to use social influences to sell virtual goods in social media, they had better consider time-varying social influences of network members. In addition, this study can be also differentiated from other related researches using survey data in that this study deals with actual field data.
Journal of the Institute of Electronics Engineers of Korea CI
/
v.44
no.4
s.316
/
pp.28-35
/
2007
Airbone laser altimeters have been utilized for 3D topographic mapping of the earth, moon, and planets with high resolution and accuracy, which is a rapidly growing remote sensing technique that measures the round-trip time emitted laser pulse to determine the topography. The traveling time from the laser scanner to the Earth's surface and back is directly related to the distance of the sensor to the ground. When there are several objects within the travel path of the laser pulse, the reflected laser pluses are distorted by surface variation within the footprint, generating multiple echoes because each target transforms the emitted pulse. The shapes of the received waveforms also contain important information about surface roughness, slope and reflectivity. Waveform processing algorithms parameterize and model the return signal resulting from the interaction of the transmitted laser pulse with the surface. Each of the multiple targets within the footprint can be identified. Assuming each response is gaussian, returns are modeled as a mixture gaussian distribution. Then, the parameters of the model are estimated by LMS Method or EM algorithm However, each response actually shows the skewness in the right side with the slowly decaying tail. For the application to require more accurate analysis, the tail information is to be quantified by an approach to decompose the tail. One method to handle with this problem is proposed in this study.
A Clinical and bacteriologcal observation was performed 128 cases of chronic otitis media who had taken middle ear surgery at Dept. of otolaryngology of St. Benedict Hospital during the period of Feb. 1981 to Feb. 1983. The following results were obtained. 1) Among total 128 cases, male were 60 cases (46.9%) and female were 68 cases (53.1 %) and age distribution showed 48 cases (37.5 %) in 3rd decade, 37 cases (28.9 %) in 2nd decade and 27 cases (21.1 %) in 4th decade. 2) Site distribution were 71 cases (55.5%) in right, 57 cases (44.5 %) in left. 3) Degree of preoperative hearing loss were 64 cases (50%) in moderate, 32 cases (25% ) in mild, 27 cases (21.1 %) in severe and 5 cases (3.9%) were normal. 4) Central perforation were observed in 65 cases (50.8 %), total perforation in 44 cases (34.4 %), attic perforation in 12 cases (9.4 %) and marginal perforation in 7 cases (5.4 %). 5) Pathologic changes of middle ear and mastoid antrum showed granulation in 81 cases (63.3 %), cholesteatoma in 47 cases (36.7%). 6) The route of approach were 123 cases (96.1%) in postauricular, 3 cases (2.3%) in transmeatal and 2 cases (1.6 %) in endaural. 7) Type of operation were 53 cases (41.4 %) in intact canal wall tympanoplasty with mastoidectomy, 42 cases (32.8 %) in tympanoplasty without mastoidectomy, 23 cases (18%) in modified radical mastoidectomy and 10 cases (7.8%) in radical mastoidectomy. 8) Type of anesthesia were 95 cases (74.2 %) by local anesthesia, 33 cases (25.8 %) were by general anesthesia. 9) Among 93 specimens of culture, proteus (31.2%), staphylococcus (28.7%), pseudomonas (23.7 %), streptococcus (7.5 %) and etc. (8.7%) in order of frequency.
Moon, In Sik;Kown, Hyun Jin;Kim, Mi Hyeon;Chang, Se Myong;Ra, In Ho;Kim, Heung Tae
Smart Media Journal
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v.9
no.4
/
pp.176-186
/
2020
The size and shape of crops are diverse, and the growing environment is also different. Therefore, when one uses a drone to spray pesticides, the characteristics of each crop must be considered, and flight conditions such as the flight height and forwarding velocity of the drone should be changed. The droplet flow of pesticides is affected by various flight conditions, and a large change occurs in the sprayed area. As a result, an uneven distribution of liquid may be formed at the wake, and the transport efficiency will be decreased as well as there would be a risk of toxic scatter. Therefore, this paper analyzes the degree of distribution of pesticides to the crops through numerical analysis when pesticide is sprayed onto the selected three crops with different characteristics by using agricultural drones with different flight conditions. On the purpose of establishing a guideline for spraying pesticides using a drone in accordance with the characteristics of crops, this paper compares the amount of pesticides distributed in the crops at the wake of nozzle flow using the figure of merit, and the sum of transported liquid rate divided by the root mean square of the probability density function.
Kim, Yeongmin;Lee, Jungwan;Kim, Jungsoo;Ahn, Sehoon;Oh, Youngseok;Yi, Jin Woo;Kim, Wiedae;Um, Moon-kwang
Composites Research
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v.34
no.4
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pp.233-240
/
2021
VaRI(Vacuum assisted Resin Infusion) process, which is cost effective and suitable for manufacturing large-sized composites, is an OoA(Out-of Autoclave) process. For rapid resin infusion in the VaRI process, a DM(distribution media) is placed on top of the fabric. The resin is rapidly supplied in plane direction of the fiber along the DM, and then the supplied resin is impregnated in the out-of-plane direction of fiber. It is difficult to predict the flow of resin because the flow of in-plane direction and the out-of-plane direction occur together, and a 3D numerical analysis program is used to simulate the resin infusion process. However, in order to analyze in 3D, many elements are required in the out-of-plane direction of fabric. And the product size is larger, the longer the analysis time needs. Therefore, in this study, a method was suggested to reduce the time required for flow analysis by simplifying the 3D flow analysis to 2D flow analysis. The usefulness was verified by comparing the 3D flow analysis with the simplified 2D flow analysis at the same conditions. The filling time error was about 7% and the reduction of flow analysis time was about 95%. In addition, by utilizing the constant difference in the flow front between the top, middle, and bottom of the fabric of the 3D analysis, the flow front of the top, middle, and bottom of the fabric can be also predicted in the 2D flow analysis.
Gwan Ik, Park;Kyu Dong, Sim;Min Su, Kyeon;Sang Hwa, Lee;Jeong Hyun, Baek;Jong-Il, Park
Journal of Broadcast Engineering
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v.27
no.6
/
pp.923-935
/
2022
This paper deals with detection and classification of leaf diseases for phenomics systems. As the smart farm systems of plants are increased, It is important to determine quickly the abnormal growth of plants without supervisors. This paper considers the color distribution and shape information of leaf diseases, and designs two deep leaning networks in training the leaf diseases. In the first step, color distribution of input image is analyzed for possible diseases. In the second step, the image is first partitioned into small segments using mean shift clustering, and the color information of each segment is inspected by the proposed Color Network. When a segment is determined as disease, the shape parameters of the segment are extracted and inspected by proposed Shape Network to classify the leaf disease types in the third step. According to the experiments with two types of diseases (frogeye/rust and tipburn) for apple leaves and iceberg, the leaf diseases are detected with 92.3% recall for a segment and with 99.3% recall for an input image where there are usually more than two disease segments. The proposed method is useful for detecting leaf diseases quickly in the smart farm environment, and is extendible to various types of new plants and leaf diseases without additional learning.
Researchers are making contradictory claims through the concept of superstars and long tails about how the development of IT technology affects demand distribution. Unlike previous studies that focused on changes in demand from a macro point of view, this study explored whether the relationship between a company's marketing activities and consumer response differs depending on the product location (i.e., superstar vs. long tail) from a micro point of view. Based on the marketing mix framework, hypotheses were developed based on the relevant literature. In the case of empirical analysis, 2,835 daily data from 63 Korean films were tested using the quantile regression method. As a result of the analysis, it was found that the influence of marketing mix factors on sales varies depending on the location of the product. Specifically, the appeal breadth of the film and the effect of owned media are enhanced in superstar products, and the effect of acquisition media in long-tail products is enhanced and the negative effects of competition are mitigated. Unlike previous studies that focused on macroscopic changes in demand distribution, this study suggested marketing activities suitable for practitioners through microscopic analysis.
This study was conducted using text mining and network theory to extract useful information for application for occupancy and performance of permit tasks contained in the permit contents from the permit register, which is used only for the simple purpose of recording occupancy permit information. Based on text mining, we analyzed and compared the frequency of vocabulary occurrence and topic modeling in five regions, including Seoul, Gyeonggi, Gyeongsang, Jeolla, Chungcheong, and Gangwon, as well as normalization processes such as stopword removal and morpheme analysis. By applying four types of centrality algorithms, including stage, proximity, mediation, and eigenvector, which are widely used in network theory, we looked at keywords that are in a central position or act as an intermediary in the network. Through a comprehensive analysis of vocabulary appearance frequency, topic modeling, and network centrality, it was found that the 'installation' keyword was the most influential in all regions. This is believed to be the result of the Ministry of Environment's permit management office issuing many permits for constructing facilities or installing structures. In addition, it was found that keywords related to road facilities, flood control facilities, underground facilities, power/communication facilities, sports/park facilities, etc. were at a central position or played a role as an intermediary in topic modeling and networks. Most of the keywords appeared to have a Zipf's law statistical distribution with low frequency of occurrence and low distribution ratio.
In the study, three-dimensional geostatistical simulations on McMurray Formation which is the largest oil sand reservoir in Athabasca area, Canada were performed, and the optimal site for steam assisted gravity drainage (SAGD) was selected based on the predictions. In the selection, the factors related to the vertical extendibility of steam chamber were considered as the criteria for an optimal site. For the predictions, 110 borehole data acquired from the study area were analyzed in the Markovian transition probability (TP) framework and three-dimensional distributions of the composing media were predicted stochastically through an existing TP based geostatistical model. The potential of a specific medium at a position within the prediction domain was estimated from the ensemble probability based on the multiple realizations. From the ensemble map, the cumulative thickness of the permeable media (i.e. Breccia and Sand) was analyzed and the locations with the highest potential for SAGD applications were delineated. As a supportive criterion for an optimal SAGD site, mean vertical extension of a unit permeable media was also delineated through transition rate based computations. The mean vertical extension of a permeable media show rough agreement with the cumulative thickness in their general distribution. However, the distributions show distinctive disagreement at a few locations where the cumulative thickness was higher due to highly alternating juxtaposition of the permeable and the less permeable media. This observation implies that the cumulative thickness alone may not be a sufficient criterion for an optimal SAGD site and the mean vertical extension of the permeable media needs to be jointly considered for the sound selections.
This study was carried out to research the multimedia fate modeling, concentration distribution and impact assessment of polycyclic aromatic hydrocarbons (PAHs) emitted from automobiles, which are known as carcinogenic and mutation chemicals. The amount of emissions of PAHs was determined based on the census data of automobiles at a target S-city and emission factors of PAHs, where multimedia fugacity modeling was conducted by the restriction of PAHs transfer between air-soil at the impervious area. PAHs' Concentrations and their distributions at several environmental media were predicted by multimedia fugacity model (level III). The residual amounts and the distributions of PAHs through mass transfer of PAHs between environment media were used to assess the health risk of PAHs at unsteady state (level IV), where the sensitivity analyses of the model parameter of each variable were conducted based on Monte Carlo simulation. The experimental result at S-city showed that Fluoranthene among PAHs substances are the highest residual concentrations (60%, 53%, 32% and 34%) at all mediums (atmospheric, water, soil, sediment), respectively, where most of the PAHs were highly accumulated in the sediment media (more than 80%). A result of PAHs concentration changes in S-city over the past 34 years identified that PAHs emissions from all environmental media increased from 1983 to 2005 and decreased until 2016, where the emission of heavy-duty vehicle including truck revealed the largest contribution to the automotive emissions of PAHs at all environment media. The PAHs concentrations in soil and water for the last 34 years showed the less value than the legal standards of PAHs, but the PAHs in air exceeded the air quality standards from 1996 to 2016. The result of this study is expected to contribute the effective management and monitoring of toxic chemicals of PAHs at various environment media of Metropolitan city.
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