• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.6
• /
• pp.1357-1378
• /
• 2013

Energy constraint of wireless sensor networks makes energy saving and prolonging the network lifetime become the most important goals of routing protocols. In this paper, we propose an Energy Efficient Chain-based Routing Protocol (EECRP) for wireless sensor networks to minimize energy consumption and transmission delay. EECRP organizes sensor nodes into a set of horizontal chains and a vertical chain. Chain heads are elected based on the residual energy of nodes and distance from the header of upper level. In each horizontal chain, sensor nodes transmit their data to their own chain head based on chain routing mechanism. EECRP also adopts a chain-based data transmission mechanism for sending data packets from the chain heads to the base station. The simulation results show that EECRP outperforms LEACH, PEGASIS and ECCP in terms of network lifetime, energy consumption, number of data messages received at the base station, transmission delay and especially energy${\times}$delay metric.

• Journal of Distribution Science
• /
• v.20 no.7
• /
• pp.47-56
• /
• 2022

Purpose: As the need to transition into the distribution of cleaner energy has garnered corporate and scholarly interests, this study aims to track the research trends in sustainable energy supply chains for five years before 2021. Research methodology: This study was conducted by a bibliometric literature review and analysis to map the field's evolution between 2016 and 2020. Out of an initial title search result of 2,484 papers from the Scopus engine, filtering led to 180 documents obtained. The data was exported in excel format (CSV) to VOSviewer software to generate and analyze network visualization of sustainable energy supply chain trends. Results: The results revealed China's the highest publishing country, with 36 research papers. The Journal of Cleaner Production was the top publishing source, with 22 papers per year. These findings showed five clusters formed in the bibliographic coupling of countries. Circular Economy and Green Supply Chain Management represent the current hot topics. Research gaps identified in the field included limited cross-industry testing and modifying sustainable supply chain models. Conclusion: This paper contributes to the sustainability literature on supply chains by providing an overview of trends and research directions for scholars' and practitioners' consideration in future research.

• Journal of Energy Engineering
• /
• v.19 no.1
• /
• pp.1-7
• /
• 2010

This experimental study suggests some alternatives for stable growth and environmental conservation, responding to the unstability of global energy market and the regulations to greenhouse gas reduction. It introduces the energy-chain approach optimizing the whole processes extending energy production, transfer, and exploitation. And the alternatives are covered from low-carbon & environment-friendly energy-specific innovation system, transformation of major industries to low-carbon & environment-friendly industries, upgrading of energy efficiency, procurement of energy sources to policy cluster.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.10 no.1
• /
• pp.181-193
• /
• 2014

The environment of supply chains is rapidly changed to global and eco-freindly work process. However, at current environment, it is not easy to grasp work flow and to analyze energy efficiency. Improving energy efficiency and visibility for goods flow can contribute to increases in customer attitudes and reductions in overall production costs Additionally, it can lead to increases in work efficiency and reductions in overall production costs. Until recently, efforts to improve energy performance focused on manufacturing industry. Those efforts have expanded to the supply chain. In this paper, we perform business process modeling about supply chain for visibility and sustainability - information and component flows - from assembly plants to logistics. This paper defines the work and information flows by modeling the underlying logical structures of the supply chain and the business processes that determine impact of visibility and sustainability. We model processes using the modeling methodology specified by UN/CEFACT. This methodology explains business process functionality and business transactions by UML diagram. The output of this paper would be useful in grasping work flow and capturing the used energy.

• Journal of Communications and Networks
• /
• v.13 no.1
• /
• pp.17-25
• /
• 2011

A convergecast is a popular routing scheme in wireless sensor networks (WSNs) in which every sensor node periodically forwards measured data along configured routing paths to a base station (BS). Prolonging lifetimes in energy-limited WSNs is an important issue because the lifetime of a WSN influences on its quality and price. Low-energy adaptive clustering hierarchy (LEACH) was the first attempt at solving this lifetime problem in convergecast WSNs, and it was followed by other solutions including power efficient gathering in sensor information systems (PEGASIS) and power efficient data gathering and aggregation protocol (PEDAP). Our solution-chain routing with even energy consumption (CREEC)-solves this problem by achieving longer average lifetimes using two strategies: i) Maximizing the fairness of energy distribution at every sensor node and ii) running a feedback mechanism that utilizes a preliminary simulation of energy consumption to save energy for depleted Sensor nodes. Simulation results confirm that CREEC outperforms all previous solutions such as LEACH, PEGASIS, PEDAP, and PEDAP-power aware (PA) with respect to the first node death and the average lifetime. CREEC performs very well at all WSN sizes, BS distances and battery capacities with an increased convergecast delay.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.9
• /
• pp.3468-3495
• /
• 2015

In this paper, we present a multi-chain based hierarchical topology control algorithm (MCHTC) for wireless sensor networks. In this algorithm, the topology control process using static clustering is divided into sensing layer that is composed by sensor nodes and multi-hop data forwarding layer that is composed by leader nodes. The communication cost and residual energy of nodes are considered to organize nodes into a chain in each cluster, and leader nodes form a tree topology. Leader nodes are elected based on the residual energy and distance between themselves and the base station. Analysis and simulation results show that MCHTC outperforms LEACH, PEGASIS and IEEPB in terms of network lifetime, energy consumption and network energy balance.

• Journal of Integrative Natural Science
• /
• v.2 no.1
• /
• pp.1-12
• /
• 2009

This miniaccount presents the selective examples of our recent discoveries in the photopolymerization of vinyl monomers using the organic initiators such as hydrosilanes, poly(hydroarylsilane)s, benzoin silyl ethers, and thianthrene cation radical. In the photopolymerization of vinyl monomers with silanes polysilanes, while the polymerization yields and polymer molecular weights of the poly(MMA)s containing the silyl moieties decreased, the TGA residue yields and intensities of SiH stretching IR bands increased as the mole ratio of the silanes over MMA increased. The hydroarylsilane and poly(hydroarylsilane) seemed to influence strongly on the photopolymerizaiton of olefinic monomers as both chain initiation and chain transfer agents. For the photohomopolymerization and photocopolymerization of MA and AA, the similar trends were observed. Benzoin silyl ethers and thianthrene cation radical also exhibit the photoinitiating ability in the photopolymerization of MMA.

• Journal of the Korea Safety Management & Science
• /
• v.14 no.4
• /
• pp.147-152
• /
• 2012

Supply chain including transportation expend the 21% of domestic energy consumption. It is necessary to diminish the excess energy usage at entire supply chain. This paper deals with the application of MFCA(Material Flow Cost Accounting) for SCM to save energy consumption. We construct the material center corresponding to each logistics function in order to apply the MFCA for GCM(Green Chain Management). We also construct the MFCA framework which consists of MFCA Database Management, MFCA Visualization, GCM Data Integration, GCM Data Tracking, and MFCA Data Predict & Assignment. We expect to help determining the range of logistics function to apply the MFCA for GCM.

• Nuclear Engineering and Technology
• /
• v.29 no.4
• /
• pp.320-326
• /
• 1997

The nuclide transport in the one-dimensional porous medium is considered as a first step in developing a decay chain transport in multidimensional inhomogeneous media. A method of solving conventional advection-dispersion equation with decay chain of arbitrary length by using the method of characteristics (MOC) is introduced. In specific cases where the advection are dominant rather than dispersion, the method is known to be useful : one of the most distinctive advantages in applying the model is that the MU minimizes the numerical dispersion, which is distinguished in such common numerical schemes as finite element method and finite difference method. The suggested model is considered to be effective through several illustrations for the case that decay chain of arbitrary length is involved during transport which is difficult to solve by standard numerical solutions if the medium becomes more complicated.

• Proceeding of EDISON Challenge
• /
• 2017.03a
• /
• pp.95-99
• /
• 2017

Protein contact map은 단백질 삼차구조에 대한 정보를 이차원의 이미지로 표현하는 방법의 하나로, 비교적 간략하지만 단백질 구조에 대한 핵심적 정보를 함축하고 있다. 이러한 단백질 구조를 바탕으로 단백질의 internal energy, solvation free energy, free energy 와 같은 열역학 함수를 도출할 수 있다. 본 연구에서는 이미지 인식에 대한 머신러닝 기법을 사용하여 단백질 구조를 함축하는 단백질의 contact map으로부터 단백질의 열역학적 함수를 예측하는 연구를 진행하였다. 단백질의 main-chain 간의 contact map, side-chain 간의 contact map, main-chain과 side-chain 간의 contact map 들로부터 단백질의 여러 가지 열역학적 함수를 예측하고자 했으며 최종적으로 Convolution Neural Network (CNN) 기법을 사용하여 단백질의 free energy를 ~18 kcal/mol의 범위에서 예측 가능함을 보였다. 본 연구를 바탕으로 단백질의 contact map과 열역학 함수 사이의 상관관계가 있으며, 머신러닝 기법을 사용하여 단백질 contact map으로부터 열역학적 함수를 예측하는 것이 가능함을 보였다.