• Agribusiness and Information Management
• /
• v.8 no.1
• /
• pp.17-26
• /
• 2016

India is largest producer of banana in the world producing 29.72 million tonnes from an area of 0.803 million ha with a productivity of 35.7 MT ha-1 and accounted for 15.48 and 27.01 per cent of the world's area and production respectively (www.nhb.gov.in). In India, Tamil Nadu leads other states both in terms of area and production followed by Maharashtra, Gujarat and Andhra Pradesh. In Rayalaseema region of Andhra Pradesh, Kurnool district had special reputation in the cultivation of banana in an area of 5765 hectares with an annual production of 2.01 lakh tonnes in the year 2012-13 and hence, it was purposively chosen for the study. On $23^{rd}$ November 2003, the Government of Andhra Pradesh has commenced a comprehensive project called 'Andhra Pradesh Micro Irrigation Project (APMIP)', first of its kind in the world so as to promote water use efficiency. APMIP is offering 100 per cent of subsidy in case of SC, ST and 90 per cent in case of other categories of farmers up to 5.0 acres of land. In case of acreage between 5-10 acres, 70 per cent subsidy and acreage above 10, 50 per cent of subsidy is given to the farmer beneficiaries. The sampling frame consists of Kurnool district, two mandals, four villages and 180 sample farmers comprising of 60 farmers each from Marginal (<1ha), Small (1-2ha) and Other (>2ha) categories. A well structured pre-tested schedule was employed to collect the requisite information pertaining to the performance of drip irrigation among the sample farmers and Data Envelopment Analysis (DEA) model was employed to analyze the performance of drip irrigation in banana farms. The performance of drip irrigation was assessed based on the parameters like: Land Development Works (LDW), Fertigation costs (FC), Volume of water supplied (VWS), Annual maintenance costs of drip irrigation (AMC), Economic Status of the farmer (ES), Crop Productivity (CP) etc. The first four parameters are considered as inputs and last two as outputs for DEA modelling purposes. The findings revealed that, the number of farms operating at CRS are more in number in other farms (46.66%) followed by marginal (45%) and small farms (28.33%). Similarly, regarding the number of farmers operating at VRS, the other farms are again more in number with 61.66 per cent followed by marginal (53.33%) and small farms (35%). With reference to scale efficiency, marginal farms dominate the scenario with 57 per cent followed by others (55%) and small farms (50%). At pooled level, 26.11 per cent of the farms are being operated at CRS with an average technical efficiency score of 0.6138 i.e., 47 out of 180 farms. Nearly 40 per cent of the farmers at pooled level are being operated at VRS with an average technical efficiency score of 0.7241. As regards to scale efficiency, nearly 52 per cent of the farmers (94 out of 180 farmers) at pooled level, either performed at the optimum scale or were close to the optimum scale (farms having scale efficiency values equal to or more than 0.90). Majority of the farms (39.44%) are operating at IRS and only 29 per cent of the farmers are operating at DRS. This signifies that, more resources should be provided to these farms operating at IRS and the same should be decreased towards the farms operating at DRS. Nearly 32 per cent of the farms are operating at CRS indicating efficient utilization of resources. Log linear regression model was used to analyze the major determinants of input use efficiency in banana farms. The input variables considered under DEA model were again considered as influential factors for the CRS obtained for the three categories of farmers. Volume of water supplied ($X_1$) and fertigation cost ($X_2$) are the major determinants of banana farms across all the farmer categories and even at pooled level. In view of their positive influence on the CRS, it is essential to strengthen modern irrigation infrastructure like drip irrigation and offer more fertilizer subsidies to the farmer to enhance the crop production on cost-effective basis in Kurnool district of Andhra Pradesh, India. This study further suggests that, the present era of Information Technology will help the irrigation management in the context of generating new techniques, extension, adoption and information. It will also guide the farmers in irrigation scheduling and quantifying the irrigation water requirements in accordance with the water availability in a particular season. So, it is high time for the Government of India to pay adequate attention towards the applications of 'Information and Communication Technology (ICT) and its applications in irrigation water management' for facilitating the deployment of Decision Supports Systems (DSSs) at various levels of planning and management of water resources in the country.

• Journal of Korean Society of Transportation
• /
• v.23 no.3 s.81
• /
• pp.95-108
• /
• 2005

The purpose of this study is to develop the ITS evaluation model using the Probabilistic Risk Analysis (PRA) methodology and to demonstrate the goodness-of-fit of the large ITS projects through the comparative analysis between DEA and PRA model. The results of this study are summarized below. First, the evaluation mode] using PRA with Monte-Carlo Simulation(MCS) and Latin-Hypercube Sampling(LHS) is developed and applied to one of ITS projects initiated by local government. The risk factors are categorized with cost, benefit and social-economic factors. Then, PDF(Probability Density Function) parameters of these factors are estimated. The log-normal distribution, beta distribution and triangular distribution are well fitted with the market and delivered price. The triangular and uniform distributions are valid in benefit data from the simulation analysis based on the several deployment scenarios. Second, the decision making rules for the risk analysis of projects for cost and economic feasibility study are suggested. The developed PRA model is applied for the Daejeon metropolitan ITS model deployment project to validate the model. The results of cost analysis shows that Deterministic Project Cost(DPC), Deterministic Total Project Cost(DTPC) is the biased percentile values of CDF produced by PRA model and this project need Contingency Budget(CB) because these values are turned out to be less than Target Value(TV;85% value), Also, this project has high risk of DTPC and DPC because the coefficient of variation(C.V) of DTPC and DPC are 4 and 15 which are less than that of DTPC(19-28) and DPC(22-107) in construction and transportation projects. The results of economic analysis shows that total system and subsystem of this project is in type II, which means the project is economically feasible with high risk. Third, the goodness-of-fit of PRA model is verified by comparing the differences of the results between PRA and DEA model. The difference of evaluation indices is up to 68% in maximum. Because of this, the deployment priority of ITS subsystems are changed in each mode1. In results. ITS evaluation model using PRA considering the project risk with the probability distribution is superior to DEA. It makes proper decision making and the risk factors estimated by PRA model can be controlled by risk management program suggested in this paper. Further research not only to build the database of deployment data but also to develop the methodologies estimating the ITS effects with PRA model is needed to broaden the usage of PRA model for the evaluation of ITS projects.

• 한국균학회소식:학술대회논문집
• /
• 2018.05a
• /
• pp.27-27
• /
• 2018

The production scale of mushroom cultivation in Korea is approximately 600 billion won, which is 1.6% of the Korean gross agricultural output. Annually, ca. 190,000 tons of mushrooms are harvested in Korea. Although the numbers of mushroom farms and cultivators are constantly decreasing, the total mushroom yields are increasing due to the large-scale cultivation facilities and automation. The recent expansion of the well-being trend causes increase in mushroom consumption in Korea: annual per capita consumption of mushroom was 3.9kg ('13) that is a little higher than European's average. Thus the exports of mushrooms, mainly Flammulina velutipes and Pleurotus ostreatus, have been increased since the middle of 2000s. Recently, however, it is slightly reduced. However, Vietnam, Hong Kong, the United States, the Netherlands and continued to export, and the country has increased recently been exported to Australia, Canada, Southeast Asia and so on. Canned foods of Agaricus bisporus was the first exports of the Korean mushroom industry. This business has reached the peak of the sale in 1977-1978. As Korea initiated trade with China in 1980, the international prices of mushrooms were sharply fall that led to shrink the domestic markets. According to the high demand to develop new items to substitute for A. bisporus, oyster mushroom (Pleurotus ostreatus) was received the attention since it seems to suit the taste of Korean consumers. Although log cultivation technique was developed in the early 1970s for oyster mushroom, this method requires a great deal of labor. Thus we developed shelf cultivation technique which is easier to manage and allows the mass production. In this technique, the growing shelf is manly made from fermented rice straw, that is the unique P. ostreatus medium in the world, was used only in South Korea. After then, the use of cotton wastes as an additional material of medium, the productivity. Currently it is developing a standard cultivation techniques and environmental control system that can stably produce mushrooms throughout the year. The increase of oyster mushroom production may activate the domestic market and contribute to the industrial development. In addition, oyster mushroom production technology has a role in forming the basis of the development of bottle cultivation. Developed mushroom cultivation technology using bottles made possible the mass production. In particular, bottle cultivation method using a liquid spawn can be an opportunity to export the F.velutipes and P.eryngii. In addition, the white varieties of F.velutipes were second developed in the world after Japan. We also developed the new A.bisporus cultivar "Sae-ah" that is easy to grown in Korea. To lead the mushroom industry, we will continue to develop the cultivars with an international competitive power and to improve the cultivation techniques. Mushroom research in Korea nowadays focuses on analysis of mushroom genetics in combination with development of new mushroom varieties, mushroom physiology and cultivation. Further studied are environmental factors for cultivation, disease control, development and utilization of mushroom substrate resources, post-harvest management and improvement of marketable traits. Finally, the RDA manages the collection, classification, identification and preservation of mushroom resources. To keep up with the increasing application of biotechnology in agricultural research the genome project of various mushrooms and the draft of the genetic map has just been completed. A broad range of future studies based on this project is anticipated. The mushroom industry in Korea continually grows and its productivity rapidly increases through the development of new mushrooms cultivars and automated plastic bottle cultivation. Consumption of medicinal mushrooms like Ganoderma lucidum and Phellinus linteus is also increasing strongly. Recently, business of edible and medicinal mushrooms was suffering under over-production and problems in distribution. Fortunately, expansion of the mushroom export helped ease the negative effects for the mushroom industry.

• Journal of Korean Ophthalmic Optics Society
• /
• v.17 no.4
• /
• pp.365-372
• /
• 2012

Purpose: To investigate ocular higher order aberrations (HOA) and spherical aberration changes caused by an aspheric soft contact lens designed to reduce spherical aberration (SA) of the eye. Methods: Fifty subjects who have successfully experienced soft contact lenses were refitted with aspheric design (Soflens Daily Disposable: SDD, Bausch+Lomb) soft contact lens. Ocular higher order aberrations (HOA) and stand alone SA were measured and analyzed for a 4-mm pupil size using Wave-Scan Wavefront$^{TM}$ aberrometer (VISX, Santa Clara, CA, USA). High and low contrast log MAR visual acuity and contrast sensitivity function (CSF) were also measured under photopic and mesopic conditions (OPTEC 6500 Vision Tester$^{(R)}$). All measurements were conducted monocularly with an undilated pupil. Results: The RMS mean values for total HOA with SDD contact lenses were significantly lower than those at with unaided eyes (p<0.001) and a reduction for SA in the SDD was close to the baseline SA (zero ${\mu}m$) (p<0.001). For the SDD lens, there was a statistically significant correlation between the changes in the total HOA and the contact lens power (r=0.237, p=0.018) as well as between the changes in SA and the lens power (r=0.324, p=0.001). High contrast visual acuity (HCVA) and low contrast visual acuity (LCVA) with SDD lenses were $-0.063{\pm}0.062$ and $0.119{\pm}0.060$, respectively under photopic and $-0.003{\pm}0.063$ and $0.198{\pm}0.067$, respectively under mesopic condition. Contrast Sensitivity Function (CSF) with SDD lenses under both photopic and mesopic conditions was $3.095{\pm}0.068$ and $3.087{\pm}0.074$, respectively. Conclusions: The SDD contact lens designed to control SA reduced the total ocular HOA and SA of the eye, resulting in compensating for positive SA of the eyes. Thus, the optical benefits of the lens with SA control would be adopted for improving the quality of vision.

• Journal of Acupuncture Research
• /
• v.22 no.1
• /
• pp.77-90
• /
• 2005

Objective : Neuropathic pain sometimes arises from a partial peripheral nerve injury. This kind of pain is usually accompanied by spontaneous burning pain, allodynia and hyperalgesia. It has been well known that acupuncture is effective to the pain control from ancient time in Asia. However, it is not clear whether Electroacupuncture(EA) & Acupuncture(AC) can control neuropathic pain effectively. The aim of this study is to examine if Electroacupuncture&Acupuncture at Hu-gye(SI03), Wijung(BL4O), Hu-gye(SI03) Wijung(BL40) may be effective to the neuropathic pain (mechanical allodynia cold allodynia) in a rat model of neuropathic pain. Methods : A rat model of neuropathic pain was made by injurying tibial nerve and sural nerve while common peroneal nerve was maintained. After the neuropathic surgery, we examined if the rats exhibited the behavioral signs allodynia. The allodynia was assessed by stimulating the medial malleolus with von frey filament and acetone. Three weeks after the neuropathic surgery, electroacupuncture &, acupuncture stimulation was delivered to Hu-gye(SI03), Wijung(BL40), Hu-gye(SI03) Wijung(BL40) one time a day for one week. After that we examined the withdrawal response of neuropathic rats' legs by von frey filament and acetone stimulation, c-fos and AchE(Acetylcholine esterase) in the periaqe- ductal gray(PAG) of neuropathic rats' brain. Results : 1. Electroacupuncture&Acupuncture at Hu-gye(SI03), Wijung(BL40), Hu-gye(SI03) Wijung(BL4O) significantly decreased the withdrawal response of mechanically allodynia in EA-BL40+SI03 group and AC-SI03 group as compared with control group on 6th day. 2. Electroacupuncture &Acupuncture at Hu-gye(SI03), Wijung(BL40), Hu-gye (SI03) Wijung (BL40) significantly decreased the withdrawal response of chemical allodynia(cold allodynia) in EA-SI03 group, EA-BL40+SI03 group and AC-SI03 group as compared with control group on 6th day. 3. Electroacupuncture & Acupuncture at Hu-gye ( SI03), Wijung (BL40), Hu-gye (SI03) Wijung(BL40) significantly decreased the expression of c-fos in the periaqe- ductal gray(PAC) of neuropathic rats' brain in EA-BL40+SI03 group and AC-SI03 group as compared with control group. 4. Electroacupuncture&Acupuncture at Hu-gye(SI03), Wijung(BL40), Hu-gye (SI03) Wijung(BL40) significantly decreased the expression of AchE in the periaqe- ductal gray(PAG) of neuropathic rats' brain in EA-BL40+SI03 group and AC-SI03 group as compared with control group. Conclusions : Based on the above results it is assumed that Electroacupuncture at Hu-gye(SI03) Wijung(BL40) and Acupuncture at Hu-gye(SI03) can help the treatment of neuropathic pain.

• The KIPS Transactions:PartC
• /
• v.10C no.6
• /
• pp.683-694
• /
• 2003

We present X-tree Diff, a change detection algorithm for tree-structured data. Our work is motivated by need to monitor massive volume of web documents and detect suspicious changes, called defacement attack on web sites. From this context, our algorithm should be very efficient in speed and use of memory space. X-tree Diff uses a special ordered labeled tree, X-tree, to represent XML/HTML documents. X-tree nodes have a special field, tMD, which stores a 128-bit hash value representing the structure and data of subtrees, so match identical subtrees form the old and new versions. During this process, X-tree Diff uses the Rule of Delaying Ambiguous Matchings, implying that it perform exact matching where a node in the old version has one-to one corrspondence with the corresponding node in the new, by delaying all the others. It drastically reduces the possibility of wrong matchings. X-tree Diff propagates such exact matchings upwards in Step 2, and obtain more matchings downwsards from roots in Step 3. In step 4, nodes to ve inserted or deleted are decided, We aldo show thst X-tree Diff runs on O(n), woere n is the number of noses in X-trees, in worst case as well as in average case, This result is even better than that of BULD Diff algorithm, which is O(n log(n)) in worst case, We experimented X-tree Diff on reat data, which are about 11,000 home pages from about 20 wev sites, instead of synthetic documets manipulated for experimented for ex[erimentation. Currently, X-treeDiff algorithm is being used in a commeercial hacking detection system, called the WIDS(Web-Document Intrusion Detection System), which is to find changes occured in registered websites, and report suspicious changes to users.

• Journal of Intelligence and Information Systems
• /
• v.18 no.1
• /
• pp.125-141
• /
• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, total misclassification cost is more affected by FNE rather than FPE. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.

• Radiation Oncology Journal
• /
• v.20 no.3
• /
• pp.193-198
• /
• 2002

Purpose : Oligodendrogliomas (ODG) are a rare, slow growing, tumor in the brain, which can be cured by complete surgical resection, but as yet it is not known if postoperative adjuvant radiation therapy (RT) is essential, We analyzed the treatment results of patients with irradiated ODG to investigate the efficacy of RT in terms of survival rates and other influencing prognostic factors. Methods and Materials : Between March 1983 and December 1997, 42 patients with ODG were treated with RT at our hospital. The RT was peformed dally at a dose of $1.8\~2.0\;Gy$, at 5 fractions per week, to a total dose of between 39.6 Gy and 64.8 Gy (mean 53.3 Gy). The ages of the patients ranged between 5 and 62 years, with a median age of 39 years. The mean follow-up period was 63.4 months (8-152 months). The Kaplan-Meier method was used to assess the survival, and 5 year survival rates (5-YSR). Log rank tests and Cox regression analyses were used to define the significance of prognostic factors. Results : The majority of ODG in this study were located in the cerebral hemisphere $(83.3\%)$. ODG are slightly more common in men than women, and commonly occurs in middle age, between the 3rd and 4th decades. It has been recommended that RT is commenced within 4 weeks following surgery (5-YSR; $86\%\;vs.\;49\%;\;p<0.03$). Histologically well differentiated, as opposed to poorly differentiated, tumors were found to have a more favorable prognosis (p<0.02). The actuarial 5-YSR was $65.3\%$ (median survival 90 months). 5-YSR for the various extents of surgical excision, followed by external RT, was superior to that of biopsy only followed by external RT $(69.9\%\;vs.\;25.6\%,\;p<0.01)$. Tumor size and location, overall elapsed irradiation days, age, sex, whole brain irradiation as a course of treatment and chemotherapy, had no influence on the 5-YSR (p>0.05). Conclusion : A local involved field irradiation with conventional fractionation, commencing within 4 weeks following surgical excision of the tumor, was beneficial for the 5-YSR, but a total radiation dose exceeding 60 Gy did not improve the 5-YSR.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.41 no.6
• /
• pp.107-116
• /
• 2013

This study was undertaken to investigate the characteristics of retention and evapotranspiration in the extensive greening module of sloped and flat rooftops for stormwater management and urban heat island mitigation. A series of 100mm depth's weighing lysimeters planted with Sedum kamtschaticum. were constructed on a 50% slope facing four orientations(north, east, south and west) and a flat rooftop. Thereafter the retention and evapotranspiration from the greening module and the surface temperature of nongreening and greening rooftop were recorded beginning in September 2012 for a period of 1 year. The characteristics of retention and evapotranspiration in the greening module were as follows. The water storage of the sloped and flat greening modules increased to 8.7~28.4mm and 10.6~31.8mm after rainfall except in the winter season, in which it decreased to 3.3mm and 3.9mm in the longer dry period. The maximum stormwater retention of the sloped and flat greening modules was 22.2mm and 23.1mm except in the winter season. Fitted stormwater retention function was [Stormwater Retention Ratio(%)=-18.42 ln(Precipitation)+107.9, $R^2$=0.80] for sloped greening modules, and that was [Stormwater Retention Ratio(%)=-22.64 ln(X)+130.8, $R^2$=0.81] for flat greening modules. The daily evapotranspiration(mm/day) from the greening modules after rainfall decreased rapidly with a power function type in summer, and with a log function type in spring and autumn. The daily evapotranspiration(mm/day) from the greening modules after rainfall was greater in summer > spring > autumn > winter by season. This may be due to the differences in water storage, solar radiation and air temperature. The daily evapotranspiration from the greening modules decreased rapidly from 2~7mm/day to less than 1mm/day for 3~5 days after rainfall, and that decreased slowly after 3~5 days. This indicates that Sedum kamtschaticum used water rapidly when it was available and conserved water when it was not. The albedo of the concrete rooftop and greening rooftop was 0.151 and 0.137 in summer, and 0.165 and 0.165 in winter respectively. The albedo of the concrete rooftop and greening rooftop was similar. The effect of the daily mean and highest surface temperature decrease by greening during the summer season showed $1.6{\sim}13.8^{\circ}C$(mean $9.7^{\circ}C$) and $6.2{\sim}17.6^{\circ}C$(mean $11.2^{\circ}C$). The difference of the daily mean and highest surface temperature between the greening rooftop and concrete rooftop during the winter season were small, measuring $-2.4{\sim}1.3^{\circ}C$(mean $-0.4^{\circ}C$) and $-4.2{\sim}2.6^{\circ}C$(mean $0.0^{\circ}C$). The difference in the highest daily surface temperature between the greening rooftop and concrete rooftop during the summer season increased with an evapotranspiration rate increase by a linear function type. The fitted function of the highest daily surface temperature decrease was [Temperature Decrease($^{\circ}C$)=$1.4361{\times}$(Evapotranspiration rate(mm/day))+8.83, $R^2$=0.59]. The decrease of the surface temperature by greening in the longer dry period was due to sun protection by the sedum canopy. The results of this study indicate that the extensive rooftop greening will assist in managing stormwater runoff and urban heat island through retention and evapotranspiration. Sedum kamtschaticum would be the ideal plant for a non-irrigated extensive green roof. The shading effects of Sedum kamtschaticum would be important as well as the evapotranspiration effects of that for the long-term mitigation effects of an urban heat island.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.93-111
• /
• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.