• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.43 no.2
• /
• pp.189-196
• /
• 1994

This paper describes a parallel computing algorithm in Gauss elimination of Jacobian matrix to large-scale power system. The structure of Jacobian matrix becomes different according to ordering method of buses. In sequential computation buses are ordered to minimize the number of fill-in in the triangulation of the Jacobian matrix. The proposed method develops the parallelism in the Gauss elimination by using ND(nested dissection) ordering. In this procedure the level structure of the power system network is transformed to be long and narrow by using end buses which results in balance of computing load among processes and maximization of parallel computation. Each processor uses the sequential computation method to preserve the sqarsity of matrix.

• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.749-753
• /
• 1996

This paper presents a new method for first and second order eigen-sensitivity analysis of system matrix in augmented form. Eigen-sensitivity analysis provides invaluable informations in power system planning and operation. However, conventional eigen-sensitivity analysis methods, which need all the eigenvalues and eigenvectors, can not be applicable to large scale power systems due to large computer memory and computing time required. In the proposed method, all sensitivity computations for a mode are carried out using the augmented system matrix and its own eigenvalue and right & left eigenvectors. In other words sensitivity analysis for a mode does not need informations on the other eigenvalues and eigenvectors and sparsity technique can be fully utilized. Thus compuations can be done very efficiently with moderate computer memory and computing time even for large power systems. The proposed algorithm is tested for one machine infinite bus system.

• Journal of Electrical Engineering and Technology
• /
• v.11 no.4
• /
• pp.987-992
• /
• 2016

This study introduces an example environment where wireless devices are mobile, devices use dynamic voltage scaling, devices and tasks are heterogeneous, tasks have deadline, and the computation and communication power is dynamically changed for energy saving. For this type of environment, the efficient system-level energy management and resource management for task completion can be an essential part of the operation and design of such systems. Therefore, the resources are assigned to tasks and the tasks may be scheduled to maximize a goal which is to minimize energy usage while trying to complete as many tasks as possible by their deadlines. This paper also introduces mobility of nodes and variable transmission power for communication which complicates the resource management/task scheduling problem further.

• Electronics and Telecommunications Trends
• /
• v.33 no.6
• /
• pp.24-33
• /
• 2018

In the age of IoT, in which everything is connected to a network, there have been increases in the amount of data traffic, latency, and the risk of personal privacy breaches that conventional cloud computing technology cannot cope with. The idea of edge computing has emerged as a solution to these issues, and furthermore, the concept of ultra-low power edge intelligent semiconductors in which the IoT device itself performs intelligent decisions and processes data has been established. The key elements of this function are an intelligent semiconductor based on artificial intelligence, connectivity for the efficient connection of neurons and synapses, and a large-scale spiking neural network simulation framework for the performance prediction of a neural network. This paper covers the current trends in ultra-low power edge intelligent semiconductors including issues regarding their technology and application.

• Journal of Digital Convergence
• /
• v.9 no.6
• /
• pp.187-196
• /
• 2011

This study found the power analysis and increase plan of Smart work industry out. We did the internet survey with 117 experts of Smart work and analyzed International competitive power and Smart work marketability. The results was as follows: First, Experts recognized the growth about Cloud computing industry so that they were most high. Second, The thing which the earning of Smart work industry is high appeared a Security industry, Cloud computing industry, and Mobile office industry etc sequence. Third, The Smart work industry which an international technique power level is high appeared in a Smart e-learning industry, Mobile office industry, and Security industry etc sequence. Lastly, An Smart work industry which the concentration supports in the government dimension Security industry, Cloud computing industry, Smart work user SW industry, and Smart e-learning industry etc sequence. This research products will use for there even though it prepares a concentration support industry in the government dimension an activation policy.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.1
• /
• pp.173-180
• /
• 2022

Approximate Computing is a promising method for designing hardware-efficient computing systems. Approximate multiplication is one of key operations used in approximate computing methods for high performance and low power computing. An approximate 4-2 compressor can implement hardware-efficient circuits for approximate multiplication. In this paper, we propose an approximate multiplier with low area and low power characteristics. The proposed approximate multiplier architecture is segmented into three portions; an exact region, an approximate region, and a constant correction region. Partial product reduction in the approximation region are simplified using a new 4:2 approximate compressor, and the error due to approximation is compensated using a simple error correction scheme. Constant correction region uses a constant calculated with probabilistic analysis for reducing error. Experimental results of 8×8 multiplier show that the proposed design requires less area, and consumes less power than conventional 4-2 compressor-based approximate multiplier.

• Journal of Communications and Networks
• /
• v.12 no.4
• /
• pp.334-345
• /
• 2010

In this paper, we study optimal tradeoffs of achievable throughput versus consumed power in wireless ad-hoc networks formed by a collection of multiple antenna nodes. Relying on adaptive modulation and/or dynamic channel coding rate allocation techniques for multiple antenna systems, we examine the maximization of throughput under power constraints as well as the minimization of transmission power under throughput constraints. In our examination, we also consider the impacts of enforcing quality of service requirements expressed in the form of channel coding block loss constraints. In order to properly model temporally correlated loss observed in fading wireless channels, we propose the use of finite-state Markov chains. Details of fading statistics of signal-to-interference-noise ratio, an important indicator of transmission quality, are presented. Further, we objectively inspect complexity versus accuracy tradeoff of solving our proposed optimization problems at a global as oppose to a local topology level. Our numerical simulations profile and compare the performance of a variety of scenarios for a number of sample network topologies.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.44 no.6 s.360
• /
• pp.1-8
• /
• 2007

In wireless sensor network which uses limited battery, power consumption is very important factor for the survivality of the system. By using low-power communication to reduce power consumption, error rate is increased in typical conditions. This paper analyzes power consumption of specific error control coding (ECC) implementations. With identical link quality, ECC provides coding gain which save the power for transmission at the cost of computing power. In sensor node, transmit power is higher than computing power of Micro Controller Unit (MCU). In this paper, Viterbi algerian is applied to the low-transmit-power sensor networks in terms of network power consumption. Practically, Viterbi algorithm presents 20% of reduction of re-transmission in compared with Auto Repeat Request (ARQ) system. Furthermore, it is observed that network power consumption is decreased by almost 18%.

• Journal of Internet Computing and Services
• /
• v.6 no.6
• /
• pp.1-12
• /
• 2005

The number of web contents is enormous in the billions and rapidly growing, Most contents are state, but an increasing number are generated dynamically, Therefore, Internet-based client/server architecture of Contents Delivery Service System suffers from frequent disconnections and security threats casused by dependency of the server or overload. Idle computing resources in Internet are used for sloving these issues, In this paper, We implement and design the Content Delivery Service System for cyber education system using idle Computing Power in P2P computing to share computing resources, We implement not only internet infrastructure but also satellite infrastructure system. and designed to transfer real-time or non real-time contents.

• Computers and Concrete
• /
• v.25 no.1
• /
• pp.83-94
• /
• 2020

The use of fly ash in modern-day concrete technology aiming sustainable constructions is on rapid rise. Fly ash, a spinoff from coal calcined thermal power plants with pozzolanic properties is used for cement replacement in concrete. Fly ash concrete is cost effective, which modifies and improves the fresh and hardened properties of concrete and additionally addresses the disposal and storage issues of fly ash. Soft computing techniques have gained attention in the civil engineering field which addresses the drawbacks of classical experimental and computational methods of determining the concrete compressive strength with varying percentages of fly ash. In this study, models based on soft computing techniques employed for the prediction of the compressive strengths of fly ash concrete are collected from literature. They are classified in a categorical way of concrete strengths such as control concrete, high strength concrete, high performance concrete, self-compacting concrete, and other concretes pertaining to the soft computing techniques usage. The performance of models in terms of statistical measures such as mean square error, root mean square error, coefficient of correlation, etc. has shown that soft computing techniques have potential applications for predicting the fly ash concrete compressive strengths.