The Journal of Korean Institute of Communications and Information Sciences
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v.36
no.11B
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pp.1363-1372
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2011
Flooding based routing protocols are usually used to disseminate information in wireless sensor networks. Those approaches, however, require message retransmissions to all nodes and induce huge collision rate and high energy consumption. In this paper, HoGoP (Hop based Gossiping Protocol) in which all nodes consider the number of hops from sink node to them, and decide own gossiping probabilities, is introduced. A node can decide its gossiping probability according to the required average reception percentage and the number of parent nodes which is counted with the difference between its hop and neighbors' ones. Therefore the decision of gossiping probability for network topology is adaptive and this approach achieves higher message reception percentage with low message retransmission than the flooding scheme. Through simulation, we compare the proposed protocol with some previous ones and evaluate its performance in terms of average reception percentage, average forwarding percentage, and forwarding efficiency. In addition, average reception percentage is analyzed according to the application requirement.
Journal of the Institute of Electronics and Information Engineers
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v.50
no.12
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pp.98-106
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2013
The duty-cycle synchronization among mobile sensor nodes with energy-harvesting is very important. The nodes should keep their duty-cycle same to others as much as possible because they have to cooperate each other and to consume energy efficiently. The distribution of node position in network affects not only node connectivity but also the active time of synchronized nodes, and it relates to network life-time finally. In this paper, we introduce a network topology change algorithm (TCA) for energy-harvesting mobile sensor networks based on self-synchronized duty-cycling. The algorithm tries to change a network topology into a balanced topology where the mobile sensor nodes are unified according to the density of the number of nodes. For TCA, both fluid flow algorithm and flock dispersion algorithm are proposed and they are evaluated through the simulation in agent based modeling language. TCA is applied to the energy-harvesting mobile sensor networks to improve the synchronization of duty-cycle and to reduce the variation of energy consumption among nodes.
Goo, Taewan;Apio, Catherine;Heo, Gyujin;Lee, Doeun;Lee, Jong Hyeok;Lim, Jisun;Han, Kyulhee;Park, Taesung
Genomics & Informatics
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v.19
no.1
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pp.11.1-11.8
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2021
For the novel coronavirus disease 2019 (COVID-19), predictive modeling, in the literature, uses broadly susceptible exposed infected recoverd (SEIR)/SIR, agent-based, curve-fitting models. Governments and legislative bodies rely on insights from prediction models to suggest new policies and to assess the effectiveness of enforced policies. Therefore, access to accurate outbreak prediction models is essential to obtain insights into the likely spread and consequences of infectious diseases. The objective of this study is to predict the future COVID-19 situation of Korea. Here, we employed 5 models for this analysis; SEIR, local linear regression (LLR), negative binomial (NB) regression, segment Poisson, deep-learning based long short-term memory models (LSTM) and tree based gradient boosting machine (GBM). After prediction, model performance comparison was evelauated using relative mean squared errors (RMSE) for two sets of train (January 20, 2020-December 31, 2020 and January 20, 2020-January 31, 2021) and testing data (January 1, 2021-February 28, 2021 and February 1, 2021-February 28, 2021) . Except for segmented Poisson model, the other models predicted a decline in the daily confirmed cases in the country for the coming future. RMSE values' comparison showed that LLR, GBM, SEIR, NB, and LSTM respectively, performed well in the forecasting of the pandemic situation of the country. A good understanding of the epidemic dynamics would greatly enhance the control and prevention of COVID-19 and other infectious diseases. Therefore, with increasing daily confirmed cases since this year, these results could help in the pandemic response by informing decisions about planning, resource allocation, and decision concerning social distancing policies.
It is difficult to evaluate the performance of process innovation of e-procurement which has large scale and complex processes. The existing evaluation methods for measuring the effects of process innovation have been mainly done with statistically quantitative methods by analyzing operational data or with qualitative methods by conducting surveys and interviews. However, these methods have some limitations to evaluate the effects because the performance evaluation of e-procurement process innovation should consider the interactions among participants who are active either directly or indirectly through the processes. This study considers the e-procurement process as a complex system and develops a simulation model based on MAS(Multi-Agent System) to evaluate the effects of e-procurement process innovation. Multi-agent based simulation allows observing interaction patterns of objects in virtual world through relationship among objects and their behavioral mechanism. Agent-based simulation is suitable especially for complex business problems. In this study, we used Netlogo Version 4.1.3 as a MAS simulation tool which was developed in Northwestern University. To do this, we developed a interaction model of agents in MAS environment. We defined process agents and task agents, and assigned their behavioral characteristics. The developed simulation model was applied to G2B system (KONEPS: Korea ON-line E-Procurement System) of Public Procurement Service (PPS) in Korea and used to evaluate the innovation effects of the G2B system. KONEPS is a successfully established e-procurement system started in the year 2002. KONEPS is a representative e-Procurement system which integrates characteristics of e-commerce into government for business procurement activities. KONEPS deserves the international recognition considering the annual transaction volume of 56 billion dollars, daily exchanges of electronic documents, users consisted of 121,000 suppliers and 37,000 public organizations, and the 4.5 billion dollars of cost saving. For the simulation, we analyzed the e-procurement of process of KONEPS into eight sub processes such as 'process 1: search products and acquisition of proposal', 'process 2 : review the methods of contracts and item features', 'process 3 : a notice of bid', 'process 4 : registration and confirmation of qualification', 'process 5 : bidding', 'process 6 : a screening test', 'process 7 : contracts', and 'process 8 : invoice and payment'. For the parameter settings of the agents behavior, we collected some data from the transactional database of PPS and some information by conducting a survey. The used data for the simulation are 'participants (government organizations, local government organizations and public institutions)', 'the number of bidding per year', 'the number of total contracts', 'the number of shopping mall transactions', 'the rate of contracts between bidding and shopping mall', 'the successful bidding ratio', and the estimated time for each process. The comparison was done for the difference of time consumption between 'before the innovation (As-was)' and 'after the innovation (As-is).' The results showed that there were productivity improvements in every eight sub processes. The decrease ratio of 'average number of task processing' was 92.7% and the decrease ratio of 'average time of task processing' was 95.4% in entire processes when we use G2B system comparing to the conventional method. Also, this study found that the process innovation effect will be enhanced if the task process related to the 'contract' can be improved. This study shows the usability and possibility of using MAS in process innovation evaluation and its modeling.
As reusability becomes recognized more importantly, with the introduction of ObjectOriented Programming Languages, developers not only want to reduce development duration, but also to develop a proper system robustly and safely by renovating the Hot Spot in order to reuse the existing framework. When we perform these works, we need the development environment which is the Rapid Application Development tool, and the RAD tools provide us with the convenient development environment. The need of RAD tools is recognized by every Object-Oriented programmer, and many business enterprises are developing them. In this paper, we will present a design and implementation of module-based modeler as a method for developing technique to constmct user-driven Intranet environment for the generation of the program based on the framework. The framework modeler used Java language that is independent on platform, and applied the technique of OMT editor that provides the UML notation partially. Additionally, The modeler also includes the notations that are not supported in OMT editor. In addition to this characteristic, it is structured to develop system consistently with applying the Agent pattern, which is a design pattern suggested by ourselves, to send messages occurred between various Views. The existing MVC(Model-View-Controller) architecture does not have this function. Thus, this tool has a flexibility when user's requirements are changed, or functions are extended.
Korean Journal of Agricultural and Forest Meteorology
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v.12
no.2
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pp.122-131
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2010
This paper introduces the concept of a virtual ecosystem and reports the following three mathematical approaches that could be widely used to construct such an ecosystem, along with examples: (1) a molecular dynamics simulation approach for animal flocking behavior, (2) a stochastic lattice model approach for termite colony behavior, and (3) a rule-based cellular automata approach for biofilm growth. The ecosystem considered in this study consists of artificial organisms and their environment. Each organism in the ecosystem is an agent that interacts autonomously with the dynamic environment, including the other organisms within it. The three types of model were successful to account for each corresponding ecosystem. In order to accurately mimic a natural ecosystem, a virtual ecosystem needs to take many ecological variables into account. However, doing so is likely to introduce excess complexity and nonlinearity in the analysis of the virtual ecosystem's dynamics. Nonetheless, the development of a virtual ecosystem is important, because it can provide possible explanations for various phenomena such as environmental disturbances and disasters, and can also give insights into ecological functions from an individual to a community level from a synthetic viewpoint. As an example of how lower and higher levels in an ecosystem can be connected, this paper also briefly discusses the application of the second model to the simulation of a termite ecosystem and the influence of climate change on the termite ecosystem.
To overcome the long design time/high computational effort/low computational performance of phylogenetic learning featuring selection and reproduction, this paper proposes a genetic representation based on XML. Since genetic programs (GP) and genetic operations of this representation are maintained by the invocation of the built-in off-the-shelf XML parser's API, the proposed approach features significant reduced time consumption of GP design process. Handling only semantically correct GPs with standard XML schema can reduce search space and computational effort. Furthermore, computational performance can be improved by the parallelism of GP caused by the utilization of XML, which is a feasible system and wire format for migration of genetic programs in heterogeneous distributed computer environments. To verify the proposed approach, it is applied to the evolution of social behaviors of multiple agents modeling the predator-prey pursuit problem. The results show that the approach can be applied for fast development and time efficiency of GPs.
Objectives : The purpose of this study was to investigate influencing factors on physician's intention to use cyber salesperson(cSP) to promote ethical drugs of pharmaceutical company. We considered influencing factors based on technology acceptance model(TAM) such as usefulness, easy of use, and attitude about cSP, and included trust and joyfulness of cSP. Methods : Measure items were developed from the previous studies. Data were collected from 1,012 physicians by using web-based self-administered structured questionnaire. Results : The major findings were as follows; First, attitude and intention to use cSP were not significantly varied by socio-demographic variables, such as sex, age, location, and Internet surfing time per day. Also, physician's characteristics such as training and professional level and type of employment were not significant to the variation of attitude and intention to use cSP. Second, structural equation modeling(SEM) analysis shows that usefulness and joyfulness were influencing factors of intention to use. Attitude was revealed as significant mediating factor to intention to use. Usefulness has indirect effect on intention to use via attitude. However, trust has not significant effect on intention to use, due to suppression effect. Conclusions : This results implies that cSP will be a useful agent to promote the ethical drugs to physician. Usefulness and joyfulness should be considered as important factors in designing and operating cSP in the Internet.
The aim of this study was to use the information deduced from biotopemap in Boryeong, Chungnam province conducted in 2011 and to select the wildlife survey point. The information used for the study was deduced from the knowledge and experience of wildlife specialists and was realized by 6 environmental variables (Outside distance from food vegetation, Outside distance from farm land, Outside distance from forest, Human density, Outside distance from road, Outside distance from water). 6 environmental variables were modeled by map overlay method and the model could deduce the correlation of 94.72% as a result of comparing with occurrence information. The areas predicted to have many occurrences were rural landscapes, forests, and valleys, and they can be used to deduce the quality wildlife survey results in the limit of survey range (area, schedule, and budget). However, it had the limit points such as the inside of forests was excluded, all species did not prefer the same habitat. The following studies are needed for this part in the future.
Climate change and low-carbon consumer movement is demanding proper response around the world while rising oil price increases consumers' needs for green car. As a preliminary study to establish an industrial platform for green car and bring out corporate strategies, this article aims to propose an academic research framework by using various methodologies including conceptual/mathematical modeling, system dynamics, and ABM from different angles. First, an analysis framework for the industrial platform was introduced to analyze green car cases, required elements were proposed, and econometrics was applied to build a basic model related to green platform (two-sided market). Also, to analyze from a dynamic perspective, a system dynamics model was applied to green car environment to build a system dynamics analysis model that is applicable to particular green car industry analysis. Lastly, an agent based model was used to study the way to activate the hybrid car market in Korea from individual consumers' perspective. Based on the result, vehicle policies that are either being enforced or planned to be enforced in the Korean HEV market can be analyzed.
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