• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.5
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• pp.331-337
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• 2004

Target motion analysis with a sonar system in general uses a regular sampling time and thus obtains regular target information regardless of the target maneuver status. This often results in overconsumption of the limited sonar resources. We propose two methods of the IMM(interacting Multiple Model) PDAF algorithm for sonar resource management to improve target motion analysis performance and to save sonar resources in this paper. In the first method, two different process noise covariance which are used as mode sets are combined based on probability. In the second method, resource time which are processed from two mode sets is calculated based on probability and then considered as update time at next step. Performance of the proposed algorithms are compared with the other algorithms by a series of Monte Carlo simulation.

• International journal of advanced smart convergence
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• v.13 no.3
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• pp.109-116
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• 2024

With the advent of serverless computing, cloud customers no longer needed to maintain and manage server environments directly. Instead, cloud service providers took on that role, managing and maintaining the server environment according to customer requests, a concept known as Function as a Service (FaaS). This service demonstrated improvements in operational costs and resource utilization over traditional cloud computing, offering various advantages such as enhanced scalability. However, a delay occurred in processing and returning results to user requests, a phenomenon referred to as the cold start problem. This paper proposed the Time Warming Allocation Engine (TWAE) to improve resource management and mitigate the cold start problem in Function as a Service. The proposed engine comprised a collection module, a learning module, a classification module, and an allocation module. Additionally, it utilized a list called Pre-Warming. Through this approach, it suggested directions for improving cold start issues and resource utilization according to different time periods.

• Journal of Advanced Navigation Technology
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• v.11 no.3
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• pp.252-258
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• 2007

There has been a lot of research done in scheme guaranteeing user's mobility and effective resources management to satisfy the requested by users in the wireless/mobile networks. In this paper, we propose a predictive resource allocation scheme based on ARMA(Auto Regressive Moving Average) prediction model to meet QoS requirements(handoff dropping rate) for guaranteeing users' mobility. The proposed scheme predicts the demanded amount of resource in the future time by ARMA time series prediction model, and then reserves it. The ARMA model can be used to take into account the correlation of future handoff resource demands with present and past handoff demands for provision of targeted handoff dropping rate. Simulation results show that the proposed scheme outperforms the existing RCS(Reserved channel scheme) in terms of handoff connection dropping rate and resource utilization.

• Journal of Family Resource Management and Policy Review
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• v.12 no.1
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• pp.41-55
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• 2008

The purpose of this study was to clarify variables affecting time management practice and the relationship between the practice and academic achievement of middle school students. Questionnaires including a time management scale were used for this study and the survey data were taken from 352 middle school students in Seoul and Gyeonggi-do. The statistical methods for the analysis were frequency, percentage, average, t-test, ANOVA and Pearson's correlation. The variables affecting student time management were gender, their standard of living, parental educational level and parental occupation. Religion and residential area were indicated as variables affecting several subscales of time management but the academic year of student had no effect on student time management behavior. The relationship between time management and the academic achievement of middle school students was slightly positive. Developing programs for time management in the field of family resource management is also necessary.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2774-2796
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• 2015

Quality-of-service (QoS) provisioning for a cognitive mesh network (CMN) with heterogeneous services has become a challenging area of research in recent days. Considering both real-time (RT) and non-real-time (NRT) traffic in a multihop CMN, [1] studied cross-layer resource management, including joint access control, route selection, and resource allocation. Due to the complexity of the formulated resource allocation problems, which are mixed-integer non-linear programming, a low-complexity yet efficient algorithm was proposed there to approximately solve the formulated optimization problems. In contrast, in this work, we present an application of genetic algorithm (GA) to re-address the hard resource allocation problems studied in [1]. Novel initialization, selection, crossover, and mutation operations are designed such that solutions with enough randomness can be generated and converge with as less number of attempts as possible, thus improving the efficiency of the algorithm effectively. Simulation results show the effectiveness of the newly proposed GA-based algorithm. Furthermore, by comparing the performance of the newly proposed algorithm with the one proposed in [1], more insights have been obtained in terms of the tradeoff among QoS provisioning for RT traffic, throughput maximization for NRT traffic, and time complexity of an algorithm for resource allocation in a multihop network such as CMN.

• Journal of information and communication convergence engineering
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• v.15 no.1
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• pp.28-36
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• 2017

The medium access control (MAC) protocol based on dynamic time division multiple access/time division duplex (TDMA/TDD) is responsible for random access control and radio resource allocation in dynamic traffic environments. These functions of random access and resource allocation are very important to prevent wastage of resources and improve MAC performance according to various network conditions. In this paper, we propose new random access and resource allocation schemes to guarantee quality of service (QoS) and provide priority services in a dynamic TDMA/TDD system. First, for the QoS guarantee, we propose an adaptive random access and resource allocation scheme by introducing an access probability. Second, for providing priority service, we propose a priority-based random access and resource allocation scheme by extending the first adaptive scheme in both a centralized and a distributed manner. The analysis and simulation results show that the proposed MAC protocol outperforms the legacy MAC protocol using a simple binary exponential backoff algorithm, and provides good differential performance according to priorities with respect to the throughput and delay.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.439-449
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• 2023

This paper deals with a resource efficient artificial intelligence (AI) service architecture for multi-channel video streams. As an AI service, we consider the object detection model, which is the most representative for video applications. Since most object detection models are basically designed for a single channel video stream, the utilization of the additional resource for multi-channel video stream processing is inevitable. Therefore, we propose a resource efficient AI service framework, which can be associated with various AI service models. Our framework is designed based on the modular architecture, which consists of adaptive frame control (AFC) Manager, multiplexer (MUX), adaptive channel selector (ACS), and YOLO interface units. In order to run only a single YOLO process without regard to the number of channels, we propose a novel approach efficiently dealing with multi-channel input streams. Through the experiment, it is shown that the framework is capable of performing object detection service with minimum resource utilization even in the circumstance of multi-channel streams. In addition, each service can be guaranteed within a deadline.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.11
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• pp.987-995
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• 2016

One of evaluation indicators of candidate waveforms for 5G mobile communication is spectral efficiency improvement by OOB(Out of Band) power reduction technique. In this paper, time-frequency resource allocation characteristic of UFMC(Universal Filtered Multi-Carrier), FBMC(Filter Bank Multi-Carrier), and W-OFDM(Weighted Orthogonal Frequency Division Multiplexing) system is evaluated and analyzed. As simulation results, spectral efficiency characteristic of these systems have been improved according to time resource allocation. In this paper, we can confirm that each system has similar time-frequency efficiency characteristic when the number of transmission bit is same and four symbols are transmitted with the linear system condition. Also, we can conclude that FBMC system has the lowest time-frequency resource efficiency under the nonlinear condition.

• Journal of KIISE:Information Networking
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• v.31 no.1
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• pp.112-122
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• 2004

In this paper, we propose a mobility estimation model based on inner regions in a cell and a dynamic resource reservation scheme which can control dynamically classes of mobile hosts on the mobile network. The mobility estimation model is modeled based on the reducible Markov chain. And the mobility estimation model provides a new hand off probability and a new remaining time for the dynamic resource reservation scheme. The remaining time is n estimated time that mobile hosts can stay in a cell. The dynamic resource reservation scheme can reserve dynamically a requested resource according to the classes of mobile hosts. This scheme can efficiently improve the connection blocking probability and connection dropping probability.

• Journal of Korean Academy of Nursing
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• v.34 no.2
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• pp.278-289
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• 2004

Purpose: The purpose of this study was to classify the elderly in long-term care facilities using the Resource Utilization Group(RUG-III) and to examine the feasibility of a payment method based on the RUG-III classification system in Korea. Method: This study measured resident characteristics using a Resident Assessment Instrument-Minimum Data Set(RAI-MDS) and staff time. Data was collected from 530 elderly residents over sixty, residing in long-term care facilities. Resource use for individual patients was measured by a wage-weighted sum of staff time and the total time spent with the patient by nurses, aides, and physiotherapists. Result: The subjects were classified into 4 groups out of 7 major groups. The group of Clinically Complex was the largest (46.3%), and then Reduced Physical Function(27.2%), Behavior Problems (17.0%), and Impaired Cognition (9.4%) followed. Homogeneity of the RUG-III groups was examined by total coefficient of variation of resource use. The results showed homogeneity of resource use within RUG-III groups. Also, the difference in resource use among RUG major groups was statistically significant (p<0.001), and it also showed a hierarchy pattern as resource use increases in the same RUG group with an increase of severity levels(ADL). Conclusion: The results of this study showed that the RUG-Ill classification system differentiates resources provided to elderly in long-term care facilities in Korea.