• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.24 no.1
• /
• pp.261-269
• /
• 2014

There are many researches on fast exponentiation algorithm which is used to implement a public key cryptosystem such as RSA. On the other hand, the malicious attacker has tried various side-channel attacks to extract the secret key. In these attacks, an attacker uses the power consumption or electromagnetic radiation of cryptographic devices which is measured during computation of exponentiation algorithm. In this paper, we propose a novel simple power analysis attack on m-ary exponentiation implementation. The core idea of our attack on m-ary exponentiation with pre-computation process is that an attacker controls the input message to identify the power consumption patterns which are related with secret key. Furthermore, we implement the m-ary exponentiation on evaluation board and apply our simple power analysis attack to it. As a result, we verify that the secret key can be revealed in experimental environment.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.9
• /
• pp.1516-1521
• /
• 2008

Recently, distribution load analysis using AMR (Automatic Meter Reading) data is researched in electric utilities. Load analysis method based on AMR system generates the typical load profile using load data of AMR customers, estimates the load profile of non-AMR customers, and analyzes the peak load and load profile of the distribution circuits and sectors per every 15 minutes/hour/day/week/month. Typical load profile is generated by the algorithm calculating the average amount of power consumption of each groups having similar load patterns. Traditional customer clustering mechanism uses only contract type code as a key. This mechanism has low accuracy because many customers having same contract code have different load patterns. In this research, We propose a customer clustring mechanism using k-means algorithm with contract type code and AMR data.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.4 no.2
• /
• pp.55-62
• /
• 2009

The power consumption of a high-end microprocessor increases very rapidly. High power consumption will lead to a rapid increase in the chip temperature as well. If the temperature reaches beyond a certain level, chip operation becomes either slow or unreliable. Therefore various approaches for Dynamic Thermal Management (DTM) have been proposed. In this paper, we propose a learning based temperature prediction scheme for a multi-core system. In this approach, from repeatedly executing an application, we learn the thermal patterns of the chip, and we control the temperature in advance through DTM. When the predicted temperature may go beyond a threshold value, we reduce the temperature by decreasing the operation frequencies of the corresponding core. We implement our temperature prediction on an Intel's Quad-Core system which has integrated digital thermal sensors. A Dynamic Frequency System (DFS) technique is implemented to have four frequency steps on a Linux kernel. We carried out experiments using Phoronix Test Suite benchmarks for Linux. The peak temperature has been reduced by on average $5^{\circ}C{\sim}7^{\circ}C$. The overall average temperature reduced from $72^{\circ}C$ to $65^{\circ}C$.

• Journal of Korean Society of Rural Planning
• /
• v.29 no.4
• /
• pp.55-67
• /
• 2023

This study investigated the correlation between impervious surface area rate(ISAR) and various urbanization indicators at the si-gun administrative level. For the years 2017 and 2021, we built correlation matrices to examine the relationships between ISAR and eight urbanization indicators, including total population, working-age population, residential power consumption, non-agricultural power consumption, paved road length, permitted development area, numbers of registered vehicles, and cadastral 'Dae' parcel area. Additionally, K-means clustering was employed to classify the 229 si-guns based on the ISAR change patterns. The analysis revealed a significant positive correlation between ISAR and urbanization indicators for both years studied. However, the interannual comparison showed a noticeably weaker correlation between changes in ISAR and urbanization indicators from 2017 to 2021. The K-means analysis also showed that si-guns with higher ISAR values, typically urban areas, demonstrated a weaker correlation, while the cluster consisting mostly of rural areas with lower ISAR displayed stronger correlations. These results suggested that ISAR should be a significant factor for consideration in sustainable rural planning and development strategies.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.2
• /
• pp.312-334
• /
• 2023

In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.13 no.2
• /
• pp.159-168
• /
• 2020

Current residential electricity rates, which are charged regardless of consumption patterns, have a problem of restricting consumer choice. In order to improve the problem, the Korea government started a demonstration project based on Time-Of-Use(TOU) pricing from September 2019. However, the analysis of its effect is still limited. This study analyzed the changes and limitations of TOU pricing compared to the current progressive pricing. The result showed that the high rate payer's bill decreased by up to 33.8 % while the low rate payer's bill increased by up to 117.7 %. This can lead to the problem of accepting electricity rates from a social point of view. In this study, TOU pricing based on progressive pricing was proposed to overcome the problem. The results presented the rate changes depending on the power consumption patterns while decreasing the average rate change from 32 % to -1.9 %. It means that the proposed pricing can support the TOU effect while maintaining the framework of the existing progressive pricing.

• Journal of Fashion Business
• /
• v.7 no.6
• /
• pp.21-31
• /
• 2003

The CLI(Consumer Life Information) is a new study to unite and create new values recognizing the importance of knowledge and information in information-oriented society based on domestic science and digital technology. The objective of this research is to define academic identity of consuming science and CLI, to analyze the theory, styles, manners, psychology and the concept of consumption, which is the base of consuming life, and to present the direction of CLI with tasks and three major axises of CLI. Nowadays, international order demands new paradigms from human beings. Especially, vision and creation of the values are settled as methodological ways considering the economic power. The CLI should be on the same horizon adjusting social change of pointing values and quality in consuming patterns of diversity and variety. Therefore, I would suggest the ways for the CLI to head for as follows. First, it is to perceive the 3 major Axises & Task of CLI. Second, it is to develope service (experiencing goods) and goods that can lead consuming lives. Third, it is to study merchandising strategy, to create new signs and symbols of goods, and to collaborate of R & D(reseach and developement) and Business. Fourth, it is to head for globalization. Consequantly, this study will be helpful to establish the theory of relationship between producer and consumer in fashion business included research and developments of qualitative goods.

• ETRI Journal
• /
• v.30 no.3
• /
• pp.412-420
• /
• 2008

A new scan partition architecture to reduce both the average and peak power dissipation during scan testing is proposed for low-power embedded systems. In scan-based testing, due to the extremely high switching activity during the scan shift operation, the power consumption increases considerably. In addition, the reduced correlation between consecutive test patterns may increase the power consumed during the capture cycle. In the proposed architecture, only a subset of scan cells is loaded with test stimulus and captured with test responses by freezing the remaining scan cells according to the spectrum of unspecified bits in the test cubes. To optimize the proposed process, a novel graph-based heuristic to partition the scan chain into several segments and a technique to increase the number of don't cares in the given test set have been developed. Experimental results on large ISCAS89 benchmark circuits show that the proposed technique, compared to the traditional full scan scheme, can reduce both the average switching activities and the average peak switching activities by 92.37% and 41.21%, respectively.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10b
• /
• pp.106-111
• /
• 1992

In order to achieve stable and efficient use of energy at iron and steel works, a model for the prediction of supply and demand of electric power system is developed on the basis of the information on operation and particular patterns of electric power consumption. The optimal amount of electric power to be purchased and the optimal fuel allocation for the in-house electric power plants are also obtained by a mixed-integer linear programming(MILP) and a nonlinear programming (NLP) solutions, respectively. The validity and the effectiveness of the proposed model are investigated by several illustrative examples. The simulation results show the satisfactory energy saving by the optimal solution obtained through this research.

• Journal of Mushroom
• /
• v.15 no.1
• /
• pp.45-53
• /
• 2017

Profitability of farmers has decreased mainly owing to low price while the gross amount of mushroom production has increased continuously in South Korea. In this regard, analyzing patterns of mushroom consumption is believed to be meaningful. We used a panel data set consisting of 667 families, from 2010 to 2015. Based on the panel data, mushroom consumption patterns of people living in city areas were examined. Multiple descriptive analysis methods and frequency analysis approaches were adopted in this study in terms of time and space dimensions, demographic properties, and purchase behaviors. The findings of this studyshow that mushroom purchase is highly dependent on seasonal events, which implies that the product consumption timing is predictable. In addition, yearly purchase amount patterns reflect that superstores have become the major mushroomtrading venues. This directly supports the need to establish supply chain capabilities for mushroom farmers so that they gain more bargaining power against enterprise-type groceries. Finally, functional features of mushroom can be linked with marketing promotion because purchase patterns demonstrate potential needs for healthcare food in mushroom categories. Based on the analyzed patterns, this paper provides insightful implications for policy makers who want to promote mushroom consumption.