• Environmental Engineering Research
• /
• v.25 no.3
• /
• pp.281-289
• /
• 2020

Environmental fate of ionizable organic pollutants such as perfluoroalkyl acids (PFAAs) are of increasing interest but has not been well understood because of uncertain values for parameters related with atmospheric interphase partitioning behavior. In the present study, not only the values for air-water partition coefficient (K_AW) and dissociation constant (pKa) of PFAAs were induced by adjusting to in situ measurements of air-water distribution coefficient between vapor phase and rainwater but also gas-particle partition coefficients were also estimated using three-phase partitioning model of ionizable organic pollutants, in situ measurements of PFAAs in aerosol and air vapor phase, and obtained parameter values. The pKa values of PFAAs we obtained were close to the minimum values suggested in literature except for perfluorooctane sulfonic acids, and COSMOtherm-modeled K_AW values were assessed to more appropriate among suggested values. When applying parameter values we obtained, it was predicted that air particle-associated fate and transport of PFAAs could be negligible and PFAAs could distribute ubiquitously along the transection from urban to rural region by pH-dependent phase transfer in air. Our study is expected to have some implications in prediction of the environmental redistribution of other ionizable organic compounds.

• The KIPS Transactions:PartD
• /
• v.15D no.1
• /
• pp.87-98
• /
• 2008

In company with the demand of powerful processing units for embedded systems, the method to develop embedded software is also required to support the demand in new approach. In order to improve the resource utilization and system performance, software modeling techniques have to consider the features of hardware architecture. This paper proposes a partitioning technique of UML-based software models, which focus the generation of the allocatable software components into multiprocessor architecture. Our partitioning technique, at first, transforms UML models to CBCFGs(Constraint-Based Control Flow Graphs), and then slices the CBCFGs with consideration of parallelism and data dependency. We believe that our proposition gives practical applicability in the areas of platform specific modeling and performance estimation in model-driven embedded software development.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.16 no.1
• /
• pp.9-15
• /
• 2021

Recently, it is increasingly necessary to run high-end neural network applications with huge computation overhead on top of resource-constrained embedded systems, such as wearable devices. While the huge computational overhead can be alleviated by distributed neural networks running on multiple separate devices, existing distributed neural network techniques suffer from a large traffic between the devices; thus are very vulnerable to communication failures. These drawbacks make the distributed neural network techniques inapplicable to wearable devices, which are connected with each other through unstable and low data rate communication medium like human body communication. Therefore, in this paper, we propose a distributed neural network partitioning technique that is resilient to communication failures. Furthermore, we show that the proposed technique also improves the inference accuracy even in case of no communication failure, thanks to the improved network partitioning. We verify through comparative experiments with a real-life neural network application that the proposed technique outperforms the existing state-of-the-art distributed neural network technique in terms of accuracy and resiliency to communication failures.

• Journal of the Korean Institute of Telematics and Electronics A
• /
• v.31A no.3
• /
• pp.53-67
• /
• 1994

This paper describes the design of a high-level synthesis system. SODAS-VP. which automatically generates hardwares executing operation sequences in pipelined fashion.Target architecture and clocking schemes to drive pipelined datapath are determined, and the handling of pipeline hazards which degrade the performance of pipeline is considered. Partitioning of an operation into load, operation, and store stages, each of which is executed in partitiones control step, is performend. Pipelinecl hardware is generated by handling pipeline hazards with internal forwarding or delay insertion techniques in partitioning process and resolving resource conflicts among the partitioned control steps with similarity measure as a priority function in module allocation process. Experimental results show that SODAS-VP generates hardwares that execute faster than those generated by HAL and ALPS systems. SODAS-VP brings improvement in execution speed by 17.1% and 7.4% comparing with HAL and ALPS systems for a MCNC benchmark program, 5th order elliptical wave filter,respectively.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.11
• /
• pp.20-26
• /
• 1994

In this paper, we propose an algorithm on partitioning a network into several subsets where the cost of a net which connects nodes in k subsets is given as k(k-1)/2 indicating the typical pattern of complete graphs. This problem is one of generalizations for multiple-way partitioning proposed by Sanchis. $^{[5]}$ Its solution can be applied to resource allocation problem in distributed systems. The proposed algorithm expanded the algorithm of Fiduccia and Mattheyses$^{[3]}$ to handle the multiple-way partitioning simultaneously. It has time and space complexity linear to the size of the network. To evaluate the performance of the proposed algorithm, we implemented also a traditional cluster growth method which groups connected nodes for nets, and compared experimental results with those of the proposed algorithm. The proposed algorithm shows some enhancement made.

• Korean Journal of Ichthyology
• /
• v.28 no.2
• /
• pp.79-86
• /
• 2016

Stomach contents of Amblychaeturichthys hexanema and A. sciistius (Perciformes: Gobiidae) from southeastern waters off Korea were analyzed to determine dietary habits and the presence of any inter- and intra-specific partitioning of food resources. These two species were bottom-feeding carnivores that consumed mainly benthic crustaceans, and other demersal invertebrates and planktonic organisms were also important in their diets. Non-metric multidimensional scaling (nMDS) ordination and multivariate analyses based on gravimetric contributions of the different prey taxa to stomach contents revealed significant inter-specific dietary differences; i.e. partitioning of food resources between the two species. Size-related changes, however, were not significant for their diets. Differences in the types and range of prey ingested by the two species could often be related to differences in the feeding behaviors. Our results of stomach contents analyses provide clear evidence of niche segregation between co-occurring A. hexanema and A. sciistius in southeastern Korean waters, which would reduce the likelihood of inter-specific competition for food resources.

• Journal of KIISE:Computer Systems and Theory
• /
• v.34 no.8
• /
• pp.337-347
• /
• 2007

An embedded system is called a multi-mode embedded system if it performs multiple applications by dynamically reconfiguring the system functionality. Further, the embedded system is called a multi-mode multi-task embedded system if it additionally supports multiple tasks to be executed in a mode. In this Paper, we address a HW/SW partitioning problem, that is, HW/SW partitioning of multi-mode multi-task embedded applications with timing constraints of tasks. The objective of the optimization problem is to find a minimal total system cost of allocation/mapping of processing resources to functional modules in tasks together with a schedule that satisfies the timing constraints. The key success of solving the problem is closely related to the degree of the amount of utilization of the potential parallelism among the executions of modules. However, due to an inherently excessively large search space of the parallelism, and to make the task of schedulabilty analysis easy, the prior HW/SW partitioning methods have not been able to fully exploit the potential parallel execution of modules. To overcome the limitation, we propose a set of comprehensive HW/SW partitioning techniques which solve the three subproblems of the partitioning problem simultaneously: (1) allocation of processing resources, (2) mapping the processing resources to the modules in tasks, and (3) determining an execution schedule of modules. Specifically, based on a precise measurement on the parallel execution and schedulability of modules, we develop a stepwise refinement partitioning technique for single-mode multi-task applications. The proposed techniques is then extended to solve the HW/SW partitioning problem of multi-mode multi-task applications. From experiments with a set of real-life applications, it is shown that the proposed techniques are able to reduce the implementation cost by 19.0% and 17.0% for single- and multi-mode multi-task applications over that by the conventional method, respectively.

• Proceedings of the IEEK Conference
• /
• 2002.07c
• /
• pp.1709-1712
• /
• 2002

In the microcell- or picocell-based system the frequent movements of the mobile bring about excessive traffics into the networks. A mobile location estimation mechanism can facilitate both efficient resource allocation and better QoS provisioning through handoff optimization. Existing location estimation schemes consider only LOS model and have poor performance in presence of multi- path and shadowing. In this paper we study a novel scheme which can increase estimation accuracy by considering NLOS environment

• International Journal of Computer Science & Network Security
• /
• v.22 no.5
• /
• pp.1-4
• /
• 2022

The growth in global population and industrialization has led to an increasing demand for electricity. Accordingly, the electricity providers need to increase the electricity generation. Due to the economical and environmental concerns associated with the generation of electricity from fossil fuels. Alternative power recourses that can potentially mitigate the economical and environmental are of interest. Renewable energy resources are promising recourses that can participate in producing power. Among renewable power resources, solar energy is an abundant resource and is currently a field of research interest. Photovoltaic solar power is a promising renewable energy resource. The power output of PV systems is mainly affected by the solar irradiation and ambient temperature. this paper investigates the utilization of machine learning unsupervised neural network techniques that potentially improves the reliability of PV solar power systems during integration into the electrical grid.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.4
• /
• pp.487-494
• /
• 2022

With the recent demand for analysis using data, the size of the knowledge graph, which is the data to be analyzed, gradually increased, reaching about 82 billion edges when extracted from the web as a knowledge graph. A lot of knowledge graphs are represented in the form of Resource Description Framework (RDF), which is a standard of W3C for representing metadata for web resources. Because of the characteristics of RDF, existing RDF storages have the limitations of processing time overhead when converting and storing large amounts of RDF data. To resolve these limitations, in this paper, we propose a method of compressing and converting large amounts of RDF data into integer IDs using MapReduce, and vertically partitioning and storing them. Our proposed method demonstrated a high performance improvement of up to 25.2 times compared to RDF-3X and up to 3.7 times compared to H2RDF+.