• Asian-Australasian Journal of Animal Sciences
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• v.33 no.4
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• pp.605-614
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• 2020

Objective: This study was conducted to determine the effects of stale maize on growth performance, immunity, intestinal morphology, and antioxidant capacity in broilers. Methods: A total of 800 one-day-old male Arbor Acres broilers (45.4±0.5 g) were blocked based on body weight, and then allocated randomly to 2 treatments with 20 cages per treatment and 20 broilers per cage in this 6-week experiment. Dietary treatments included a basal diet and diets with 100% of control maize replaced by stale maize. Results: The content of fat acidity value was higher (p<0.05) while the starch, activities of catalase and peroxidase were lower (p<0.05) than the control maize. Feeding stale maize diets reduced (p<0.05) average daily feed intake (ADFI) throughout the experiment, feed conversion ratio (FCR) during d 0 to 21 and the whole experiment as well as relative weight of liver, spleen, bursa of Fabricius and thymus (p<0.05) on d 21. Feeding stale maize diets decreased jejunum villus height (VH) and VH/crypt depth (CD) (p<0.05) on d 21 and 42 as well as ileum VH/CD on d 42. The levels of immunoglobulin G, acid α-naphthylacetate esterase positive ratios and lymphocyte proliferation on d 21 and 42 as well as lysozyme activity and avian influenza antibody H₅N₁ titer on d 21 decreased (p<0.05) by the stale maize. Feeding stale maize diets reduced (p<0.05) serum interferon-γ, tumor necrosis factor-α, interleukin-2 on d 21 and interleukin-6 on d 21 and 42. Broilers fed stale maize diets had lower levels of (p<0.05) total antioxidative capacity on d 42, superoxide dismutase and glutathione peroxidase on d 21 and 42, but higher (p<0.05) levels of malondialdehyde on d 21 and 42. Conclusion: Feeding 100% stale maize decreased ADFI and FCR, caused adverse effects on immunity and antioxidant function and altered intestinal morphology in broilers.

• Journal of the Korean Society of Food Science and Nutrition
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• v.20 no.3
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• pp.276-280
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• 1991

The quality changes of brown rice during storage were determined by the method of quantitative analysis of n-hexanal, amylogram, texture and volume expansion. The qualities of stored brown rice were also analyzed with sensory evaluation of cooked milled rice obtained from brown rice, n-Hexanal content, peak viscosity and total setback of brown rice flour pastes increased substantially with the increased of storage period at 35$^{\circ}C$. Up to 10 months of storage at 35$^{\circ}C$, stale flavor obtained by a sensory method markedly increased, but stickiness decreased. The scores of overall preference were in good agreement with those of stale flavor (r=-0.98) and sticky texture (r=0.98). The correlation coefficient between stale flavor obtained by a sensory method and instrumetal analysis for stored brown rice was r=0.97.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.01a
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• pp.89-92
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• 2018

본 논문에서는 Edge computing 환경에서 다수의 노드들로 구성된 네트워크의 디바이스를 효율적으로 관리하기 위한 방법을 제안한다. 기존의 클라이언트-서버 모델은 모든 데이터와 그에 대한 요청을 중심 서버에서 처리하기 때문에, 다수의 노드로부터 생성된 많은 양의 데이터를 처리하는 데 빠른 응답속도를 보장하지 못한다. Edge computing은 분담을 통해 네트워크의 부담을 줄일 수 있는 IoT 네트워크에 적합한 방법으로, 데이터를 전송하고 받는 과정에서 네트워크의 대역폭을 사용하는 대신 서로 연결된 노드들이 협력해서 데이터를 처리하고, 또한 네트워크 말단에서의 데이터 처리가 허용되어 데이터 센터의 부담을 줄일 수 있다. 여러병렬 기계학습 모델 중 본 연구에서는 Stale Synchronous Parallel(SSP) 모델을 이용하여 Edge 노드에서 분산기계 학습에 적용하였다.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.3
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• pp.48-58
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• 2009

Geo-graphical routing protocols as GPSR are known to be very suitable and useful for vehicular ad-hoc networks. However, a corresponding node can include some stale neighbor nodes being out of a transmission range, and the stale nodes are pone to get a high priority to be a next relay node in the greedy mode. In addition, some useful redundant information can be eliminated during planarization in the recovery mode. This paper deals with a new recovery mode, the Greedy Border Superiority Routing(GBSR), along with an Adaptive Neighbor list Management(ANM) scheme. Each node can easily treat stale nodes on its neighbor list by means of comparing previous and current Position of a neighbor. When a node meets the local maximum, it makes use of a border superior graph to recover from it. This approach improve the packet delivery ratio while it decreases the time to recover from the local maximum. We evaluate the performance of the proposed methods using a network simulator. The results shown that the proposed protocol reveals much better performance than GPSR protocol. Please Put the of paper here.

• Weed & Turfgrass Science
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• v.3 no.3
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• pp.215-220
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• 2014

This study was conducted to evaluate potential weed control in organic farming field using false seedbed and stale seedbed techniques. The experiment was conducted in open upland fields during spring and fall crop seasons. The false seedbed was prepared before 2-4 weeks of crop culture and was treated with shallow tillage or flame weeding before transplanting. The weed suppression rates of false seedbed treatment in the spring crop experiments for Chinese cabbage, soybean, hot pepper and corn were 65-73%, 50-55%, 9-55% and 8-33%, respectively. According to crop growth and yield in this experiment, the false seedbed technique has some potential weed control for Chinese cabbage, soybean and corn. The weed suppression rates of stale seedbed treatments in the fall crop experiments for Chinese cabbage, spinach and carrot were 18-39%, 40-77% and 37-38%, respectively. Weed control efficacy of the stale seedbed in this study was lower, when compared with false seedbed.

• Journal of Communications and Networks
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• v.9 no.1
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• pp.43-49
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• 2007

The implementation of client polling as a weak cache coherence mechanism has two major drawbacks: Firstly, the cache may return a stale copy if the object is changed in the origin server while the cached copy is considered valid. Secondly, the cache can invalidate a cached copy that is still valid in the server. Therefore, we propose a multilevel pre-fetching (MLP) in conjunction with the client polling to refine these drawbacks. MLP is introduced to improve the level of freshness among the cached objects. The simulation results presented in this paper show that the proposed MLP significantly minimizes the number of stale objects and reduces the invalidation messages sent out to the server, i.e., increase the cache HIT rate.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.762-766
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• 2002

This paper proposes a method or estimating lifetime distribution for products under two-dimensional warranty in which age and usage are used simultaneously to determine the eligibility of a warranty claim. For such a case, existing methods reduce the two-dimensional time stale to a single stale assuming that the two variables have a functional relationship. This assumption is, however, not appropriate since the functional relationship is unknown in practice. In this paper, the field age and usage data are modeled with a bivariate lifetime distribution. Method of obtaining maximum likelihood estimators is outlined, their asymptotic properties are studied and specific formulas for a bivariate Weibull distribution are obtained. The proposed model is compared with the existing one which assumes a lineal relationship between the two variables Simulation studios are performed to investigate the effect of the degree of dependency between the two variables.

• The Journal of Bigdata
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• v.5 no.1
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• pp.189-195
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• 2020

We consider the stale problem which makes the training speed slow in the field of deep learning. The problem can be formulated as a single-machine scheduling problem with generalized due dates in which the objective is to minimize the total earliness and tardiness. We show that the problem can be solved in polynomial time if the orders of the small and the large jobs in an optimal schedule are known in advance.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.11
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• pp.592-600
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• 2001

To improve the performance of wide-issue Superscalar microprocessors, it is essential to increase the width of instruction fetch and issue rate. Data dependences are major hurdle to exploit ILP(Instruction-Level Parallelism) efficiently, so several related works have suggested that the limits imposed by data dependences can be overcome to some extent with the use of the data value prediction. But the suggested mechanisms may access the same value prediction table entry again before they have been updated with a real data value. They will cause incorrect value prediction by using stable data and incur misprediction penalty and lowering performance. In this paper, we propose a new hybrid value predictor which achieve high performance by reducing stale data. Because the proposed hybrid value predictor can update the prediction table speculatively, it efficiently reduces the number of mispredicted instruction due to stable due to stale data. For SPECint95 benchmark programs on the 16-issue superscalar processors, simulation results show that the average prediction accuracy increase from 59% for non-speculative update to 72% for speculative update.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.4
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• pp.21-34
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• 2023

Federated Learning is divided into synchronous federated learning and asynchronous federated learning. Asynchronous federated learning has a time advantage over synchronous federated learning, but asynchronous federated learning still has some challenges to obtain better performance. In particular, preventing performance degradation in non-IID training datasets, selecting appropriate clients, and managing stale gradient information are important for improving model performance. In this paper, we deal with K-asynchronous federated learning by using non-IID datasets. In addition, unlike traditional method using static K, we proposed an algorithm that adaptively adjusts K and we can reduce the learning time. Additionally, the we show that model performance is improved by using stale gradient handling method. Finally, we use a method of judging model performance to obtain strong model stability. Experiment results show that overall algorithm can obtain advantages of reducing training time, improving model accuracy, and improving model stability.