• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.7
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• pp.1025-1032
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• 1990

We proposed a neural network energy function for the optimal graph partitioning and its optimization method using Boltzmann Machine. We composed a Boltzmann Machine with the proposed neural network energy function, and the simulation results show that we can obtain an optimal solution with the energy function parameters of A=50, B=5, c=14 and D=10, at the Boltzmann Machine parameters of To=80 and \ulcorner0.07 for a 6-node 3-partition problem. As a result, the proposed energy function and optimization parameters are proved to be feasible for the optimal graph partitioning.

• Geomechanics and Engineering
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• v.33 no.1
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• pp.11-18
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• 2023

This study explores a new energy partitioning approach to determine the fracture toughness of 3-D printed pristine/recycled high density polyethylene (HDPE) blends employing the essential work of fracture (EWF) concept. The traditional EWF approach conducts a uniaxial tensile test with double-edge notched tensile (DENT) specimens and measures the total energy defined by the area under a load-displacement curve until failure. The approach assumes that the entire total energy contributes to the fracture process only. This assumption is generally true for extruded polymers that fracture occurs in a material body. In contrast to the traditional extrusion manufacturing process, the current 3-D printing technique employs fused deposition modeling (FDM) that produces layer-by-layer structured specimens. This type of specimen tends to include separation energy even after the complete failure of specimens when the fracture test is conducted. The separation is not relevant to the fracture process, and the raw experimental data are likely to possess random variation or noise during fracture testing. Therefore, the current EWF approach may not be suitable for the fracture characterization of 3-D printed specimens. This paper proposed a new energy partitioning approach to exclude the irrelevant energy of the specimens caused by their intrinsic structural issues. The approach determined the energy partitioning location based on experimental data and observations. Results prove that the new approach provided more consistent results with a higher coefficient of correlation.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.21 no.3
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• pp.397-410
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• 2023

This study examined the efficacy of various chlorinating agents in partitioning light water reactor spent fuel, with the aim of optimizing the chlorination process. Through thermodynamic equilibrium calculations, we assessed the outcomes of employing MgCl₂, NH₄Cl, and Cl₂ as chlorinating agents. A comparison was drawn between using a single agent and a sequential approach involving all three agents (MgCl₂, NH₄Cl, and Cl₂). Following heat treatment, the utilization of MgCl₂ as the sole chlorinating agent resulted in a moderate separation. Specifically, this method yielded a solid separation with 96.9% mass retention, 31.7% radioactivity, and 44.2% decay heat, relative to the initial spent fuel. In contrast, the sequential application of the chlorinating agents following heat treatment led to a final solid separation characterized by 93.1% mass retention, 5.1% radioactivity, and 15.4% decay heat, relative to the original spent fuel. The findings underscore the potential effectiveness of a sequential chlorination strategy for partitioning spent fuel. This approach holds promise as a standalone technique or as a complementary process alongside other partitioning processes such as pyroprocessing. Overall, our findings contribute to the advancement of spent fuel management strategies.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.5
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• pp.139-146
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• 2022

With the recent development of the Internet of Things (IoT) and the convergence of vehicles and IT technologies, high-performance applications such as autonomous driving are emerging, and multi-access edge computing (MEC) has attracted lots of attentions as next-generation technologies. In order to provide service to these computation-intensive tasks in low latency, many methods have been proposed to partition tasks so that they can be performed through cooperation of multiple MEC servers(MECSs). Conventional methods related to task partitioning have proposed methods for partitioning tasks on vehicles as mobile devices and offloading them to multiple MECSs, and methods for offloading them from vehicles to MECSs and then partitioning and migrating them to other MECSs. In this paper, the performance of task partitioning methods using offloading and migration is compared and analyzed in terms of service delay, blocking rate and energy consumption according to the method of selecting partitioning targets and the number of partitioning. As the number of partitioning increases, the performance of the service delay improves, but the performance of the blocking rate and energy consumption decreases.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.5
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• pp.241-251
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• 2007

Energy consumption in the instruction cacheaccounts for a significant portion of the total processor energy consumption. Therefore, reducing energy consumption in the instruction cache is important in designing embedded processors. This paper proposes a method for reducing dynamic energy consumption in the instruction cache by partitioning it to smaller (less energy-consuming) sub-caches. When a request comes into the proposed cache, only one sub-cache is accessed by utilizing the locality of applications. By contrast, the other sub-caches are not accessed, leading todynamic energy reduction. In addition, the proposed cache reduces dynamic energy consumption by eliminating the energy consumed in tag matching. We evaluated the energy efficiency by running cycle accurate simulator, SimpleScalar. with power parameters obtained from CACTI. Simulation results show that the proposed cache reduces dynamic energy consumption by $37%{\sim}60%$ compared to the traditional direct-mapped instruction cache.

• Journal of the Korean Recycled Construction Resources Institute
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• v.10 no.3
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• pp.219-226
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• 2022

In this experimental study, the effect of continuously changing the position of electromagnetic force using several coils and a relay switch on fracture energy was investigated. Normal mortar and steel slag mortar specimens in which 50 % and 100 % of sand was replaced with steel slag were cast and exposed to electromagnetic field. The electric field was induced by one coil without a relay switch as an existing method and by partitioning the coil and continuously changing the position using a relay switch. The fracture energy was calculated from the load-vertical displacement curve obtained from the experiment and compared with each other. As a result of the experiment, it was confirmed that the method of partitioning the coil and changing the position of electromagnetic force by using a relay switch is effective in increasing the fracture energy even if the same amount of power is used.

• Bulletin of the Korean Chemical Society
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• v.28 no.7
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• pp.1183-1186
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• 2007

A shake-flask method was used to determine the n-octanol/water partition coefficients of sulfamethazine, sulfadimethoxine, sulfamethoxydiazine, sulfamonomethoxine, sulfamethoxazole, sulfaquinoxaline and sulfachloropyrazine from (298.15 to 333.15) K. The results showed that the n-octanol/water partition coefficient of each sulfonamide decreased with the increase of temperature. Based on the fluid phase equilibrium theory, the thermodynamic relationship of n-octanol/water partition coefficient depending on the temperature is proposed, and the changes of enthalpy, entropy, and the Gibbs free energy function for sulfonamides partitioning in n-octanol/ water are determined, respectively. Sulfonamides molecules partitioning in n-octanol/water is mainly an enthalpy driving process, during which the order degrees of system increased. The temperature effect coefficient of n-octanol/water partition coefficient is discussed. The results show that its magnitude is the same as that of values in the literature.

• Journal of the Korea Society for Simulation
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• v.16 no.4
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• pp.57-65
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• 2007

In many sensor network applications, sensor nodes are deployed in open environments, and hence are vulnerable to physical attacks, potentially compromising the node's cryptographic keys. False sensing report can be injected through compromised nodes, which can lead to not only false alarms but also the depletion of limited energy resource in battery powered networks. Fan Ye et al. proposed that statistical en-route filtering scheme(SEF) can do verify the false report during the forwarding process. In this scheme, the choice of a partition value represents a trade off between resilience and energy where the partition value is the total number of partitions which global key pool is divided. If every partition are compromised by an adversary, SEF disables the filtering capability. Also, when an adversary has compromised a very small portion of keys in every partition, the remaining uncompromised keys which take a large portion of the total cannot be used to filter false reports. We propose a fuzzy-based adaptive partitioning method in which a global key pool is adaptively divided into multiple partitions by a fuzzy rule-based system. The fuzzy logic determines a partition value by considering the number of compromised partitions, the energy and density of all nodes. The fuzzy based partition value can conserve energy, while it provides sufficient resilience.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.12
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• pp.1195-1202
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• 1991

This paper describes a newly developed method of production simulation by using the Mixture of Cumulant Approximation (MOCA). In this method, the load is modelled as random variable (r.v.) which can be interpreted in terms of partitioning the load into various categories. We can consider the load shape of multi-modal characteristics. The number of load category and demarcation points of each load category are calculated automatically by using interpolation and least square method. Each generating unit of a supply system is modelled as r.v. of unit outage capacity according to the number of unit outage subset. Since the computation burden of each subset's moments increases exponentially as units are convolved to the system, we further derive the specific recursive formulae. In simulating the energy limited units, hydro unit simulation is performed using Energy Invariance Property and the simulation of pumped storage unit is modelled as compulsory and economic operations. The proposed MOCA method is applide to the test systems and the results are compared with those of cumulant and Booth Baleriaux method. It is verified that the MOCA method is considerably reliable and stable both pathological and well behaved system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4681-4702
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• 2016

Recently, Massive energy consumption in Cloud Storage System has attracted great attention both in industry and research community. However, most of the solutions utilize single method to reduce the energy consumption only in one aspect. This paper proposed an energy effective gear-shifting mechanism (E2GSM) in Cloud Storage System to save energy consumption from multi-aspects. E2GSM is established on data classification mechanism and data replication management strategy. Data is classified according to its properties and then be placed into the corresponding zones through the data classification mechanism. Data replication management strategies determine the minimum replica number through a mathematical model and make decision on replica placement. Based on the above data classification mechanism and replica management strategies, the energy effective gear-shifting mechanism (E2GSM) can automatically gear-shifting among the nodes. Mathematical analytical model certificates our proposed E2GSM is energy effective. Simulation experiments based on Gridsim show that the proposed gear-shifting mechanism is cost effective. Compared to the other energy-saved mechanism, our E2GSM can save energy consumption substantially at the slight expense of performance loss while meeting the QoS of user.