• Journal of Intelligence and Information Systems
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• 제20권4호
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Ecology and Resilient Infrastructure
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• 제2권4호
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• pp.265-273
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• 2015

It is the better to take preventative measures against the natural intrusion in advance from invasive alien species that reduce biodiversity and cause economic loss to humans. If the prevention of intrusion and spread fails, we need to make active control and eradication. This study aims to introduce nutria (Myocastor coypus) control cases performed in the United Kingdom and the United States and to provide information for the contribution of nutria management measure improvements. The nutria eradication campaign in the United Kingdom was developed as a long-term plan based on sufficient understanding on the management target and objective and suitable support. Sufficient information on nutria was accumulated and the management strategy was flexibly modified according to the changes in management that were proactively reflected in the field. Regarding the eradication project at Chesapeake Bay in the United States, based on long-term ecological information, more advanced capture technology than in the United Kingdom were introduced and the eradication plan, strategy and implementation were configured by analyzing the strengths and weaknesses of the eradication campaign in the United Kingdom. The successful cases in the United Kingdom and the United State provide an information on how to improv the nutria management measure. For the eradication of nutria, it is necessary to reach a consensus between stakeholders and to form a consultative group between related organizations for periodic communication. Opinions on the field must be actively accepted in the consultation process for strategy and policy decision, and the eradication plan needs to be developed based on a management index. The eradication plan is required to be managed, evaluated and adjusted in a systematic way. Scientific management must be introduced and the management performance must be evaluated objectively so that a practical plan can be flexibly adjusted. It is also required to secure a long-term budget support and a stable organization and to input a concentrated budget at the proper period when there is high efficiency of eradication.

• Magazine of the Korean Society of Agricultural Engineers
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• 제21권3호
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• pp.104-120
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• 1979

I. Title of the Study Studies on the Development of Improved Subsurface Drainage Methods. -Drainage Performance of Various Subsurface Drain Materials- II. Object of the Study Studies were carried out to select the drain material having the highest performance of drainage; And to develop the water budget model which is necessary for the planning of the drainage project and the establishment of water management standards in the water-logged paddy field. III. Content and Scope of the Study 1. The experiment was carried out in the laboratory by using a sand tank model. The drainage performance of various drain materials was compared evaluated. 2. A water budget model was established. Various parameters necessary for the model were investigated by analyzing existing data and measured data from the experimental field. The adaptability of the model was evaluated by comparing the estimated values to the field data. IV. Results and Recommendations 1. A corrugated tube enveloped with gravel or mat showed the highest drainage performance among the eight materials submmitted for the experiment. 2. The drainage performance of the long cement tile(50 cm long) was higher than that of the short cement tile(25 cm long). 3. Rice bran was superior to gravel in its' drain performance. 4. No difference was shown between a grave envelope and a P.V.C. wool mat in their performance of drainage. Continues investigation is needed to clarify the envelope performance. 5. All the results described above were obtained from the laboratory tests. A field test is recommended to confirm the results obtained. 6. As a water balance model of a given soil profile, the soil moisture depletion D, could be represented as follows; $$D=\Sigma\limit_{t=1}^{n}(Et-R_{\ell}-I+W_d)..........(17)$$ 7. Among the various empirical formulae for potential evapotranspiration, Penman's formular was best fit to the data observed with the evaporation pans in Jinju area. High degree of positive correlation between Penman;s predicted data and observed data was confirmed. The regression equation was Y=1.4X-22.86, where Y represents evaporation rate from small pan, in mm/100 days, and X represents potential evapotranspiration rate estimated by Penman's formular. The coefficient of correlation was r=0.94.** 8. To estimate evapotranspiration in the field, the consumptive use coefficient, Kc, was introduced. Kc was defined by the function of the characteristics of the crop soil as follows; $Kc=Kco{\cdot}Ka+Ks..........(20)$ where, Kco, Ka ans Ks represents the crop coefficient, the soil moisture coefficient, and the correction coefficient, respectively. The value of Kco and Ka was obtained from the Fig.16 and the Fig.17, respectively. And, if $Kco{\cdot}Ka{\geq}1.0,$ then Ks=0, otherwise, Ks value was estimated by using the relation; $Ks=1-Kco{\cdot}Ka$. 9. Into type formular, $r_t=\frac{R_{24}}{24}(\frac{b}{\sqrt{t}+a})$, was the best fit one to estimate the probable rainfall intensity when daily rainfall and rainfall durations are given as input data, The coefficient a and b are shown on the Table 16. 10. Japanese type formular, $I_t=\frac{b}{\sqrt{t}+a}$, was the best fit one to estimate the probable rainfall intensity when the rainfall duration only was given. The coefficient a and b are shown on the Table 17. 11. Effective rainfall, Re, was estimated by using following relationships; Re=D, if $R-D\geq}0$, otherwise, Re=R. 12. The difference of rainfall amount from soil moisture depletion was considered as the amount of drainage required. In this case, when Wd=O, Equation 24 was used, otherwise two to three days of lag time was considered and correction was made by use of storage coefficient. 13. To evaluate the model, measured data and estimated data was compared, and relative error was computed. 5.5 percent The relative error was 5.5 percent. 14. By considering the water budget in Jinju area, it was shown that the evaporation amount was greater than the rainfall during period of October to March in next year. This was the behind reasonning that the improvement of surface drainage system is needed in Jinju area.

• Journal of Intelligence and Information Systems
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• 제18권4호
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• Korean Journal of Remote Sensing
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• 제30권2호
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• pp.241-249
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• 2014

The continuous observations for atmospheric aerosol were carried out during 3 years (2009-2011) by using a multi-wavelength Raman lidar at the Gwangju Institute of Science and Technology (GIST), Korea ($35.11^{\circ}N$, $126.54^{\circ}E$). The particle depolarization ratios were retrieved from the observations in order to distinguish the Asian dust layer. The vertical information of Asian dust layers were used as input parameter for the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model for analysis of its backward trajectories. The source regions and transport pathways of the Asian dust layer were identified. The most frequent source region of Asian dust in Korea was Gobi desert during observation period in this study. The statistical analysis on the particle depolarization ratio of Asian dust was conducted according to their transport route in order to retrieve the variation of optical properties of Asian dust during long-range transport. The transport routes were classified into the Asian dust which was transported to observation site directly from the source regions, and the Asian dust which was passed over pollution regions of China. The particle depolarization ratios of Asian dust which were transported via industrial regions of China was ranged 0.07-0.1, whereas, the particle depolarization ratio of Asian dust which was transported directly from the source regions to observation site were comparably higher and ranged 0.11-0.15. It is considered that the pure Asian dust particle from source regions were mixed with pollution particles, which is likely to spherical particle, during transportation so that the values of particle depolarization of Asian dust mixed with pollution was decreased.

• Korean Journal of Agricultural Science
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• 제8권1호
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• pp.90-96
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• 1981

To design more efficient agricultural machinery, the accurately measuring system among many other factors is essential. A light-beam oscillographic recorder is generally used in measuring dynamic strain but it is not compatible with the extremely high speed measuring system such as 1,000 m/s, also is susceptable to damage due to vibration while using the system in field. The recorder used light sensitive paper for strip chart recording. The reading and analysis of data from the strip charts is very cumbersome, errorneous and time consuming. A microcomputer was interfaced with A/D converter, microcomputer program was developed for measuring, system calibration was done and the strain generated from a cantilever beam vibrator was measured. The results are summarized as follows. 1. Microcomputer program was developed to perform strain measuring of agricultural machine elements and could be controled freely the measuring intervals, no. of channels and no. of data. The maximum measuring speed was $62{\mu}s$. 2. Calibration the system was performed with triangle wave generated from a function generator and checked by an oscilloscope. The sampled data were processed using HP 3000 minicomputer of Chungnam National University computer center the graphical results were triangle same as input wave and so the system have been out of phase distorsion and amplitude distorsion. 3. The strain generated from a cantilever beam vibrator which has free vibration period of 0.019 second were measured by the system controlled to have l.0 ms of time interval and its computer output showing vibration curve which is well filted to theoretical value. 4. Using microcomputer on measuring the strain of agricultural machine elements could not only save analyzing time and recording papers but also get excellent adaptation to field experiment, especially in measurement requiring high speed and good precision.

• Journal of Home Health Care Nursing
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• 제4권
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• pp.5-22
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• 1997

The purpose of the study was to development an information delivery system for the home nursing service, to demonstrate and to evaluate the efficiency of it. The period of research conduct was from September 1996 to August 31, 1997. At the 1st stage to achieve the purpose, Firstly Assessment tool for the patients with cerebral vascular disease who have the first priority of HNS among the patients with various health problems at home was developed through literature review. Secondly, after identification of patient nursing problem by the home care nurse with the assessment tool, the patient's classification system developed by Park (1988) that was 128 nursing activities under 6 categories was used to identify the home care nurse's activities of the patient with CAV at home. The research team had several workshops with 5 clinical nurse experts to refine it. At last 110 nursing activities under 11 categories for the patients with CVA were derived. At the second stage, algorithms were developed to connect 110 nursing activities with the patient nursing problems identified by assessment tool. The computerizing process of the algorithms is as follows: These algorithms are realized with the computer program by use of the software engineering technique. The development is made by the prototyping method, which is the requirement analysis of the software specifications. The basic features of the usability, compatibility, adaptability and maintainability are taken into consideration. Particular emphasis is given to the efficient construction of the database. To enhance the database efficiency and to establish the structural cohesion, the data field is categorized with the weight of relevance to the particular disease. This approach permits the easy adaptability when numerous diseases are applied in the future. In paralleled with this, the expandability and maintainability is stressed through out the program development, which leads to the modular concept. However since the disease to be applied is increased in number as the project progress and since they are interrelated and coupled each other, the expand ability as well as maintainability should be considered with a big priority. Furthermore, since the system is to be synthesized with other medical systems in the future, these properties are very important. The prototype developed in this project is to be evaluated through the stage of system testing. There are various evaluation metrics such as cohesion, coupling and adaptability so on. But unfortunately, direct measurement of these metrics are very difficult, and accordingly, analytical and quantitative evaluations are almost impossible. Therefore, instead of the analytical evaluation, the experimental evaluation is to be applied through the test run by various users. This system testing will provide the viewpoint analysis of the user's level, and the detail and additional requirement specifications arising from user's real situation will be feedback into the system modeling. Also. the degree of freedom of the input and output will be improved, and the hardware limitation will be investigated. Upon the refining, the prototype system will be used as a design template. and will be used to develop the more extensive system. In detail. the relevant modules will be developed for the various diseases, and the module will be integrated by the macroscopic design process focusing on the inter modularity, generality of the database. and compatibility with other systems. The Home care Evaluation System is comprised of three main modules of : (1) General information on a patient, (2) General health status of a patient, and (3) Cerebrovascular disease patient. The general health status module has five sub modules of physical measurement, vitality, nursing, pharmaceutical description and emotional/cognition ability. The CVA patient module is divided into ten sub modules such as subjective sense, consciousness, memory and language pattern so on. The typical sub modules are described in appendix 3.

• Journal of the Institute of Electronics Engineers of Korea SP
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• 제40권5호
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• pp.312-321
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• 2003

In this paper, we implement robot which are ability to recognize obstacles and moving automatically to destination. we present two results in this paper; hardware implementation of image processing board and software implementation of visual feedback algorithm for a self-controlled robot. In the first part, the mobile robot depends on commands from a control board which is doing image processing part. We have studied the self controlled mobile robot system equipped with a CCD camera for a long time. This robot system consists of a image processing board implemented with DSPs, a stepping motor, a CCD camera. We will propose an algorithm in which commands are delivered for the robot to move in the planned path. The distance that the robot is supposed to move is calculated on the basis of the absolute coordinate and the coordinate of the target spot. And the image signal acquired by the CCD camera mounted on the robot is captured at every sampling time in order for the robot to automatically avoid the obstacle and finally to reach the destination. The image processing board consists of DSP (TMS320VC33), ADV611, SAA7111, ADV7l76A, CPLD(EPM7256ATC144), and SRAM memories. In the second part, the visual feedback control has two types of vision algorithms: obstacle avoidance and path planning. The first algorithm is cell, part of the image divided by blob analysis. We will do image preprocessing to improve the input image. This image preprocessing consists of filtering, edge detection, NOR converting, and threshold-ing. This major image processing includes labeling, segmentation, and pixel density calculation. In the second algorithm, after an image frame went through preprocessing (edge detection, converting, thresholding), the histogram is measured vertically (the y-axis direction). Then, the binary histogram of the image shows waveforms with only black and white variations. Here we use the fact that since obstacles appear as sectional diagrams as if they were walls, there is no variation in the histogram. The intensities of the line histogram are measured as vertically at intervals of 20 pixels. So, we can find uniform and nonuniform regions of the waveforms and define the period of uniform waveforms as an obstacle region. We can see that the algorithm is very useful for the robot to move avoiding obstacles.

• KOREAN JOURNAL OF CROP SCIENCE
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• 제63권3호
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• pp.186-195
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• 2018

A field study was conducted over a 3-year period from 2014 to 2016 in the central plain area, Suwon, Korea, 1) to compare the biomass production between machine-transplanted and water-broadcast seeded silage rice and 2) to elucidate the growth factors that affect the difference in biomass production between the two cultivation practices. The heading date for the water-broadcast seeded silage rice was September 11-18, which was delayed by 11-17 days when compared to that for the machine-transplanted silage rice. On average, water-broadcast seeded silage rice had a shorter plant height, more panicles per area, and a greater biomass production because of the increased straw dry weight. However, the difference in dry weight of each plant organ between the two cultivation practices exhibited yearly variation. When the data were pooled across experimental years, cultivation practices, and varieties, biomass production was highly positively correlated with straw dry weight but not with panicle dry weight. When the ratio of water-broadcast seeding to machine-transplanting was analyzed, total dry weight and straw dry weight were positively associated with each other, whereas no relationship was found between total dry weight and panicle dry weight. Despite that water-broadcast seeded silage rice produced more panicles per area than machine-transplanted silage rice, the two cultivation practices had a similar dry weight per culm. Therefore, we conclude that the silage rice from the water-broadcast seeding, compared to the machine-transplanting, produced more biomass because of the combination of the increased panicle number per area and a similar dry weight per culm. These results suggest that silage rice could be produced through water-broadcast seeding to increase biomass production with low labor and cost input.

• Asian-Australasian Journal of Animal Sciences
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• 제21권1호
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• pp.107-119
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• 2008

To determine the true digestible phosphorus (TDP) requirement of growing pigs, two experiments were designed with the experimental diets containing five true digestible P levels (0.16%, 0.20%, 0.23%, 0.26% and 0.39%) and the ratio of total calcium to true digestible P (TDP) kept at 2:1. In Experiment 1, five barrows (Duroc${\times}$Landrace${\times}$Yorkshire) with an average initial body weight of 27.9 kg were used in a $5{\times}5$ Latin-square design to evaluate the effect of different dietary P levels on the digestibility and output of P and nitrogen. In Experiment 2, sixty healthy growing pigs (Duroc${\times}$Landrace${\times}$Yorkshire) with an average body weight (BW) of 21.4 kg were assigned randomly to one of the five dietary treatments (12 pigs/diet), and were used to determine the true digestible phosphorus (TDP) requirement of growing pigs on the basis of growth performance and serum biochemical indices. The results indicated that the true digestibility of P increased (p<0.05) linearly with increasing dietary TDP level below 0.26%. The true P digestibility was highest (56.6%) when dietary TDP was 0.34%. Expressed as g/kg dry matter intake (DMI), fecal P output increased (p<0.05) linearly with increasing P input. On the basis of g/kg fecal dry matter (DM), fecal P output was lowest for Diet 4 and highest (p<0.05) for Diet 5. The apparent digestibility of crude protein (CP) did not differ (p>0.05) among the five diets, with the average nitrogen output of 12.14 g/d and nitrogen retention of 66% to 74% (p>0.05), which suggested that there was no interaction between dietary P and CP protein levels. During the 28-d experimental period of Experiment 2, the average daily gain (ADG) of pigs was affected by dietary TDP levels as described by Eq. (1): $y=-809,532x^4+788,079x^3-276,250x^2+42,114x-1,759$; ($R^2=0.99$; p<0.01; y = ADG, g/d; x = dietary TDP, %), F/G for pigs by Eq. (2): $y=3,651.1x^4-3,480.4x^3+1,183.8x^2-172.5x+10.9$ ($R^2=0.99$; p<0.01; y = F/G; x = dietary TDP, %), and Total P concentrations in serum by Eq. (3): $y=-3,311.7x^4+3,342.7x^3-1,224.6x^2+195.6x-8.7$ (R2 = 0.99; p<0.01; y = total serum P concentration and x = dietary TDP, %). The highest ADG (782 g/d), the lowest F/G (1.07) and the highest total serum P concentration (3.1 mmol/L) were obtained when dietary TDP level was 0.34%. Collectively, these results indicate that the optimal TDP requirement of growing pigs is 0.34% of the diet at a total Ca to TDP ratio of 2:1.