• Journal of Information Processing Systems
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• 제18권3호
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• pp.443-456
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• 2022

An efficient and reasonable resource allocation strategy can greatly improve the service quality of Internet of Vehicles (IoV). However, most of the current allocation methods have overestimation problem, and it is difficult to provide high-performance IoV network services. To solve this problem, this paper proposes a network resource allocation strategy based on deep learning network model DDQN. Firstly, the method implements the refined modeling of IoV model, including communication model, user layer computing model, edge layer offloading model, mobile model, etc., similar to the actual complex IoV application scenario. Then, the DDQN network model is used to calculate and solve the mathematical model of resource allocation. By decoupling the selection of target Q value action and the calculation of target Q value, the phenomenon of overestimation is avoided. It can provide higher-quality network services and ensure superior computing and processing performance in actual complex scenarios. Finally, simulation results show that the proposed method can maintain the network delay within 65 ms and show excellent network performance in high concurrency and complex scenes with task data volume of 500 kbits.

• International conference on construction engineering and project management
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.459-462
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• 2015

Korean construction industry made a huge growth over several decades. However, domestic construction market has shrunk in recent years due to the domestic political environments and global economic crisis. Today, the international construction markets become more important to be investigated, and demands for international construction study have risen. The purpose of this study is to search for measures to compare the potential of Southeast Asian countries' construction markets and select strategic target countries where the Korean construction companies pursue to explore for future investments. The research team investigated a range of selection factors which can represent the construction market condition of each country. These factors included the size of the construction industry, economic growth potential, current relationship with Korea, the level of infrastructure development, political situation, etc. After collecting data, each selection factor was scored by experts' analyses and the total score was given to each country. As a result, the rating identified attractive countries for future investments: Myanmar, Vietnam, and Sri Lanka. For the target countries, analytical methods were used for in-depth market analysis that can provide comprehensive insight and strategic clue for development of short-/mid-/long-term roadmap and action plans. The research findings would be used to support rational decision making of construction investment advancing to the Southeast Asian economic growth.

• Journal of the Semiconductor & Display Technology
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• 제23권2호
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• pp.107-113
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• 2024

Scheduling of semiconductor test facilities has been crucial since effective scheduling contributes to the profits of semiconductor enterprises and enhances the quality of semiconductor products. This study aims to solve the scheduling problems for the wafer burn-in test facilities of the semiconductor back-end process by utilizing simulation and deep reinforcement learning-based methods. To solve the scheduling problem considered in this study. we propose novel state, action, and reward designs based on the Markov decision process. Furthermore, a neural network is trained by employing the recent RL-based method, named proximal policy optimization. Experimental results showed that the proposed method outperformed traditional heuristic-based scheduling techniques, achieving a higher due date compliance rate of jobs in terms of total job completion time.

• 한국생물공학회:학술대회논문집
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• 한국생물공학회 2003년도 생물공학의 동향(XII)
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• pp.40-44
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• 2003

Soil-borne infectious disease including Pythium aphanidermatum and Rhizoctonia solani causes severe damage to plants, such as cucumber. This soil-borne infectious disease was not controlled effectively by chemical pesticide. Since these diseases spread through the soil, chemical agents are usually ineffective. Instead, biological control, including antagonistic microbe can be used as a preferred control method. An efficient method was developed to select an antagonistic strain to be used as a biological control agent strain. In this new method, surface tension reduction potential of an isolate was included in the ‘decision factor’ in addition to the other factors, such as growth rate, and pathogen inhibition rate. Considering these 3 decision factors by a statistical method, an isolate from soil was selected and was identified as Bacillus sp. GB16. In the pot test, this strain showed the best performance among the isolated strains. The lowest disease incidence rate and fastest seed growth was observed when Bacillus sp. GB16 was used. Therefore this strain was considered as plant growth promoting rhizobacteria (PGPR). The action of surface tension reducing component was deduced as the enhancement of wetting, spreading, and residing of antagonistic strain in the rhizosphere. This result showed that new selection method was significantly effective in selecting the best antagonistic strain for biological control of soil-borne infectious plant pathogen. The antifungal substances against P. aphanidermatum and R. solani were partially purified from the culture filtrates of Bacillus sp. GB16. In this study, lipopeptide possessing antifungal activity was isolated from Bacillus sp. GB16 cultures by various purification procedures and was identified as a surfactin-like lipopeptide based on the Fourier transform infrared spectroscopy (FT-IR), nuclear magnetic resonance (NMR), high performance liquid chromatography mass spectroscopy (HPLC-MS), and quadrupole time-of-flight (Q-TOF) ESI-MS/MS data. The lipopeptide, named GB16-BS, completely inhibited the growth of Pythium aphanidermatum, Rhizoctonia solani, Penicillium sp., and Botrytis cineria at concentrations of 10 and 50 mg/L, respectively. A novel method to prevent the foaming and to provide oxygen was developed. During the production of surface active agent, such as lipopeptide (surfactin), large amount of foam was produced by aeration. This resulted in the carryover of cells to the outside of the fermentor, which leads to the significant loss of cells. Instead of using cell-toxic antifoaming agents, low amount of hydrogen peroxide was added. Catalase produced by cells converted hydrogen peroxide into oxygen and water. Also addition of corn oil as an oxygen vector as well as antifoaming agent was attempted. In addition, Ca-stearate, a metal soap, was added to enhance the antifoam activity of com oil. These methods could prevent the foaming significantly and maintained high dissolved oxygen in spite of lower aeration and agitation. Using these methods, high cell density, could be achieved with increased lipopeptide productivity. In conclusion to produce an effective biological control agent for soil-borne infectious disease, following strategies were attempted i) effective screening of antagonist by including surface tension as an important decision factor ii) identification of antifungal compound produced from the isolated strain iii) novel oxygenation by $H_2O_2-catalase$ with vegetable oil for antifungal lipopeptide production.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• 제8권4호
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• pp.81-93
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• 2013

The study attempted to explain the differences among the willingness of companies to accept the self-regulation. The study exemplified the $CO_2$ emissions record labelling program, as a self-regulation program which is considered as a concrete action for corporate social responsibility and substantiality management movement. The study investigated how companies respond to the request from a government to accept the program, which may be potentially contributed to both higher social and financial performance. It is hypothesized that first the company may decide whether the acceptance decision is strategic or non-strategic issues. when considered as non-strategic, the decision will be made on the basis of short term expected returns and costs comparison. It is hypothesized that when considered as strategic, the decision will be strongly influenced by the type of corporate perceptions toward environmental regulations, which has been accumulated by past experiences. Also, the study investigated the good management theory and the slack resources theory which differently predict the direction between social performances and financial performances. The results identified the significant relationships among most variables and supported the slack resources theory. Further, the ethical perception positively influenced the willingness to accept the self-regulation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 한국경영과학회/대한산업공학회 1999년도 춘계공동학술대회:정보화시대의 지식경영
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• pp.426-426
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• 1999

;There are many sources of uncertainty in a typical production and inventory system. There is uncertainty as to how many items customers will demand during the next day, week, month, or year. There is uncertainty about delivery times of the product. Uncertainty exacts a toll from management in a variety of ways. A spurt in a demand or a delay in production may lead to stockouts, with the potential for lost revenue and customer dissatisfaction. Firms typically hold inventory to provide protection against uncertainty. A cushion of inventory on hand allows management to face unexpected demands or delays in delivery with a reduced chance of incurring a stockout. The proposed strategies are used for the design of a probabilistic inventory system. In the traditional approach to the design of an inventory system, the goal is to find the best setting of various inventory control policy parameters such as the re-order level, review period, order quantity, etc. which would minimize the total inventory cost. The goals of the analysis need to be defined, so that robustness becomes an important design criterion. Moreover, one has to conceptualize and identify appropriate noise variables. There are two main goals for the inventory policy design. One is to minimize the average inventory cost and the stockouts. The other is to the variability for the average inventory cost and the stockouts The total average inventory cost is the sum of three components: the ordering cost, the holding cost, and the shortage costs. The shortage costs include the cost of the lost sales, cost of loss of goodwill, cost of customer dissatisfaction, etc. The noise factors for this design problem are identified to be: the mean demand rate and the mean lead time. Both the demand and the lead time are assumed to be normal random variables. Thus robustness for this inventory system is interpreted as insensitivity of the average inventory cost and the stockout to uncontrollable fluctuations in the mean demand rate and mean lead time. To make this inventory system for robustness, the concept of utility theory will be used. Utility theory is an analytical method for making a decision concerning an action to take, given a set of multiple criteria upon which the decision is to be based. Utility theory is appropriate for design having different scale such as demand rate and lead time since utility theory represents different scale across decision making attributes with zero to one ranks, higher preference modeled with a higher rank. Using utility theory, three design strategies, such as distance strategy, response strategy, and priority-based strategy. for the robust inventory system will be developed.loped.

• Journal of Korea Spatial Information System Society
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• 제2권2호
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• pp.59-74
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• 2000

Because efficiency of the 1st-phase NGIS investment(1995-2000) has not been clearly measured, the action taken in the 2nd-phase NGIS project requires NGIS budgets to be evaluated in terms of effectiveness. Especially, the effective investments in local governments are critical for the NGIS projects, because they execute the much larger amount of budgets in total than other GIS projects. As indicated, for the successful NGIS implementation, it is important to obtain continuous political and financial supports from decision makers. As a persuasion measure for the budget appropriation, CBA(Cost-Benefit Analysis) and CEA(Cost-Efficiency Analysis) can play an important role for the decision makers. The major concern of this paper is how to measure the costs and benefits of the GIS implementation by considering important characteristics of the GIS projects in local governments, and existing theories are reviewed for this concern. The GISs in local governments can have different stages in terms of its evolution and the effectiveness of the applications can be represented variously. To identify categories for measuring costs and benefits of the various GISs, case studies and success stories are reviewed from both the foreign and domestic research. The categories of costs and benefits are determined from the tangible and intangible aspects. The categories for the quantitative and qualitative measure are proposed to evaluate the GISs in local governments. After measuring costs and benefits, three key evaluation methods in cost-benefit analysis are suggested as follows: 1) the benefit: cost ratio (B/C), 2) Internal Rate of Return (IRR), and 3) the net present values (NPV) of the costs and benefits. The sensitivity and uncertainty analysis are also helpful to make a decision for the GIS budget appropriation in local governments. In conclusion, although cost-benefit analysis is not an easy undertaking, it is certain that it can play an important role in the future for the GIS funding decisions in local governments.

• Korean journal of applied entomology
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• 제54권3호
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• pp.159-167
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• 2015

In order to establish B. tabaci control in paprika greenhouses a fixed-precision-level sampling plan was developed. The sampling plan consisted of spatial distribution analysis, a sampling stop line, and decision making. Sampling was conducted simultaneously in two independent greenhouses (GH 1, GH 2). GH 1 and 2 were surveyed every week for 22 consecutive weeks, using 19 sampling locations in GH 1 and 9 sampling locations in GH 2. The plant in both greenhouses were divided into top (180-220 cm from the ground), middle (80-120 cm from the ground) and bottom (30-70 cm from the ground) sections and B. tabaci adults and pupae were observed on three paprika leaves at each position and recorded separately. GH 2 data were used to validate the fixed-precision sampling plan, which was developed using GH 1 data. In this study, spatial distribution analysis was performed using Taylor's power law with the pooled data of the top and bottom position (B. tabaci adults), and the middle and bottom positions (B. tabaci pupae), based on a 1-leaf sampling unit. Decision making was undertaken using the maximum of action threshold in accordance with previously published method, and the value was decided by the price of the plants. Using the results obtained in the greenhouse, simulated validation of the developed sampling plan by RVSP (Resampling Validation for Sampling Plan) indicated a reasonable level of precision.

• Journal of Global Scholars of Marketing Science
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• 제19권3호
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• pp.49-61
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• 2009

This article provides training exercises for executives into interpreting subroutine maps of executives' thinking in processing business and industrial marketing problems and opportunities. This study builds on premises that Schank proposes about learning and teaching including (1) learning occurs by experiencing and the best instruction offers learners opportunities to distill their knowledge and skills from interactive stories in the form of goal.based scenarios, team projects, and understanding stories from experts. Also, (2) telling does not lead to learning because learning requires action-training environments should emphasize active engagement with stories, cases, and projects. Each training case study includes executive exposure to decision system analysis (DSA). The training case requires the executive to write a "Briefing Report" of a DSA map. Instructions to the executive trainee in writing the briefing report include coverage in the briefing report of (1) details of the essence of the DSA map and (2) a statement of warnings and opportunities that the executive map reader interprets within the DSA map. The length maximum for a briefing report is 500 words-an arbitrary rule that works well in executive training programs. Following this introduction, section two of the article briefly summarizes relevant literature on how humans think within contexts in response to problems and opportunities. Section three illustrates the creation and interpreting of DSA maps using a training exercise in pricing a chemical product to different OEM (original equipment manufacturer) customers. Section four presents a training exercise in pricing decisions by a petroleum manufacturing firm. Section five presents a training exercise in marketing strategies by an office furniture distributer along with buying strategies by business customers. Each of the three training exercises is based on research into information processing and decision making of executives operating in marketing contexts. Section six concludes the article with suggestions for use of this training case and for developing additional training cases for honing executives' decision-making skills. Todd and Gigerenzer propose that humans use simple heuristics because they enable adaptive behavior by exploiting the structure of information in natural decision environments. "Simplicity is a virtue, rather than a curse". Bounded rationality theorists emphasize the centrality of Simon's proposition, "Human rational behavior is shaped by a scissors whose blades are the structure of the task environments and the computational capabilities of the actor". Gigerenzer's view is relevant to Simon's environmental blade and to the environmental structures in the three cases in this article, "The term environment, here, does not refer to a description of the total physical and biological environment, but only to that part important to an organism, given its needs and goals." The present article directs attention to research that combines reports on the structure of task environments with the use of adaptive toolbox heuristics of actors. The DSA mapping approach here concerns the match between strategy and an environment-the development and understanding of ecological rationality theory. Aspiration adaptation theory is central to this approach. Aspiration adaptation theory models decision making as a multi-goal problem without aggregation of the goals into a complete preference order over all decision alternatives. The three case studies in this article permit the learner to apply propositions in aspiration level rules in reaching a decision. Aspiration adaptation takes the form of a sequence of adjustment steps. An adjustment step shifts the current aspiration level to a neighboring point on an aspiration grid by a change in only one goal variable. An upward adjustment step is an increase and a downward adjustment step is a decrease of a goal variable. Creating and using aspiration adaptation levels is integral to bounded rationality theory. The present article increases understanding and expertise of both aspiration adaptation and bounded rationality theories by providing learner experiences and practice in using propositions in both theories. Practice in ranking CTSs and writing TOP gists from DSA maps serves to clarify and deepen Selten's view, "Clearly, aspiration adaptation must enter the picture as an integrated part of the search for a solution." The body of "direct research" by Mintzberg, Gladwin's ethnographic decision tree modeling, and Huff's work on mapping strategic thought are suggestions on where to look for research that considers both the structure of the environment and the computational capabilities of the actors making decisions in these environments. Such research on bounded rationality permits both further development of theory in how and why decisions are made in real life and the development of learning exercises in the use of heuristics occurring in natural environments. The exercises in the present article encourage learning skills and principles of using fast and frugal heuristics in contexts of their intended use. The exercises respond to Schank's wisdom, "In a deep sense, education isn't about knowledge or getting students to know what has happened. It is about getting them to feel what has happened. This is not easy to do. Education, as it is in schools today, is emotionless. This is a huge problem." The three cases and accompanying set of exercise questions adhere to Schank's view, "Processes are best taught by actually engaging in them, which can often mean, for mental processing, active discussion."

• Korean Journal of Environmental Biology
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• 제40권2호
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• pp.164-171
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• 2022

Frankliniella occidentalis is an invasive pest insect, which affects over 500 different species of host plants and transmits viruses (tomato spotted wilt virus; TSWV). Despite their efficiency in controling insect pests, pesticides are limited by residence, cost and environmental burden. Therefore, a fixed-precision level sampling plan was developed. The sampling method for F. occidentalis adults in pepper greenhouses consists of spatial distribution analysis, sampling stop line, and control decision making. For sampling, the plant was divided into the upper part(180 cm above ground), middle part (120-160 cm above ground), and lower part (70-110 cm above ground). Through ANCOVA, the P values of intercept and slope were estimated to be 0.94 and 0.87, respectively, which meant there were no significant differences between values of all the levels of the pepper plant. In spatial distribution analysis, the coefficients were derived from Taylor's power law (TPL) at pooling data of each level in the plant, based on the 3-flowers sampling unit. F. occidentalis adults showed aggregated distribution in greenhouse peppers. TPL coefficients were used to develop a fixed-precision sampling stop line. For control decision making, the pre-referred action thresholds were set at 3 and 18. With two action thresholds, N_max values were calculated at 97 and 1149, respectively. Using the Resampling Validation for Sampling Program (RVSP) and the results gained from the greenhouses, the simulated validation of our sampling method showed a reasonable level of precision.