• Membrane and Water Treatment
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• v.14 no.2
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• pp.65-76
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• 2023

Given the limited water resources and the presence of multiple decision makers with different and usually conflicting objectives in the exploitation of water resources systems, especially dam's reservoirs; therefore, the decision to determine the optimal allocation of reservoir water among decision-makers and stakeholders is a difficult task. In this study, by combining a fuzzy VIKOR technique or fuzzy multi-criteria decision making (FMCDM) and the Young's bilateral bargaining model, a new method was developed to determine the optimal quantitative and qualitative water allocation of dam's reservoir water with the aim of increasing the utility of decision makers and stakeholders and reducing the conflicts among them. In this study, by identifying the stakeholders involved in the exploitation of the dam reservoir and determining their utility, the optimal points on trade-off curve with quantitative and qualitative objectives presented by Mojarabi et al. (2019) were ranked based on the quantitative and qualitative criteria, and economic, social and environmental factors using the fuzzy VIKOR technique. In the proposed method, the weights of the criteria were determined by each decision maker using the entropy method. The results of a fuzzy decision-making method demonstrated that the Young's bilateral bargaining model was developed to determine the point agreed between the decisions makers on the trade-off curve. In the proposed method, (a) the opinions of decision makers and stakeholders were considered according to different criteria in the exploitation of the dam reservoir, (b) because the decision makers considered the different factors in addition to quantitative and qualitative criteria, they were willing to participate in bargaining and reconsider their ideals, (c) due to the use of a fuzzy-logic based decision-making approach and considering different criteria, the utility of all decision makers was close to each other and the scope of bargaining became smaller, leading to an increase in the possibility of reaching an agreement in a shorter time period using game theory and (d) all qualitative judgments without considering explicitness of the decision makers were applied to the model using the fuzzy logic. The results of using the proposed method for the optimal exploitation of Iran's 15-Khordad dam reservoir over a 30-year period (1968-1997) showed the possibility of the agreement on the water allocation of the monthly total dissolved solids (TDS)=1,490 mg/L considering the different factors based on the opinions of decision makers and reducing conflicts among them.

• Korean Journal of Poultry Science
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• v.50 no.3
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• pp.133-141
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• 2023

We conducted a 5 × 5 diallel cross-combination test using 1,060 chickens from pure lines of Korean Rhode-C, -D, Korean Leghorn-F, -K, and Korean Native Yellowish-brown chicken (KNC-Y) to develop a new Korean native chicken layer breeder. The laying performance and combining ability, including livability, body weight, age of first egg-laying, hen-day egg production, and egg weight, were analyzed. The livability from birth to 48 weeks was 72.1±24.0%, with the highest observed in the YC and the lowest in the DK combination (P<0.01). The YC combination exhibited the highest general combining ability (GCA), while the YD combination showed the highest specific combining ability (SCA). Regarding body weight, combinations involving Leghorn showed lighter weights compared to combinations with Rhode and KNC-Y (P<0.01). Additionally, the offspring from the KNC-Y combination reached sexual maturity earlier than those from the Rhode combination. The hen-day egg production was 70.7±12.0%, with the highest seen in the CK combination at 86% (P<0.01). The effects of GCA and SCA on hen-day egg production were similar, with the SCA being highest in the YD combination and the GCA being highest in the Rhode-C. Significant differences in egg weight were observed among the combinations, with the eggs from Rhode and Leghorn combinations being heavier than those from combinations with KNC-Y (P<0.01). In conclusion, the YC and YD combinations, characterized by excellent livability, are highly desirable paternal strains, while the CF and CK combinations, with excellent laying performance and moderate egg weight, are preferred maternal strains for Korean native chicken layer breeders.

• Journal of the Korea Society of Computer and Information
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• v.25 no.9
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• pp.21-29
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• 2020

In this paper, we propose quantitative evaluation method that enable security comparison between Security Container Runtimes. security container runtime technologies have been developed to address security issues such as Container escape caused by containers sharing the host kernel. However, most literature provides only a analysis of the security of container technologies using rough metrics such as the number of available system calls, making it difficult to compare the secureness of container runtimes quantitatively. While the proposed model uses a new method of combining the degree of exposure of host system calls with various external vulnerability metrics. With the proposed technique, we measure and compare the security of runC (Docker default Runtime) and two representative Security Container Runtimes, gVisor, and Kata container.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.540-549
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• 2003

In collaborative recommendation two models are generally used: the user model and the article model. A user model learns correlation between users preferences and recommends an article based on other users preferences for the article. Similarly, an article model learns correlation between preferences for articles and recommends an article based on the target user's preference for other articles. In this paper, we investigates various combination methods of the user model and the article model for better recommendation performance. They include simple sequential and parallel methods, perceptron, multi-layer perceptron, fuzzy rules, and BKS. We adopt the multi-layer perceptron for training each of the user and article models. The multi-layer perceptron has several advantages over other methods such as the nearest neighbor method and the association rule method. It can learn weights between correlated items and it can handle easily both of symbolic and numeric data. The combined models outperform any of the basic models and our experiments show that the multi-layer perceptron is the most efficient combination method among them.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1817-1836
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• 2020

Network convergence is considered as one of the key solutions to the problem of achieving future high-capacity and reliable communications. This approach overcomes the limitations of separate wireless technologies. Efficient interface selection is one of the most important issues in convergence networks. This paper solves the problem faced by users of selecting the most appropriate interface in the heterogeneous radio-access network (RAN) environment. Our proposed scheme combines a hierarchical evaluation of networks and game theory to solve the network-selection problem. Instead, of considering a fixed weight system while ranking the networks, the proposed scheme considers the service requirements, as well as static and dynamic network attributes. The best network is selected for a particular service request. To establish a hierarchy among the network-evaluation criteria for service requests, an analytical hierarchy process (AHP) is used. To determine the optimum network selection, the network hierarchy is combined with game theory. AHP attains the network hierarchy. The weights of different access networks for a service are calculated. It is performed by combining AHP scores considering user's experienced static network attributes and dynamic radio parameters. This paper provides a strategic game. In this game, the network scores of service requests for various RANs and the user's willingness to pay for these services are used to model a network-versus-user game. The Nash equilibria signify those access networks that are chosen by individual user and result maximum payoff. The examples for the interface selection illustrate the effectiveness of the proposed scheme.

• International Journal of Industrial Entomology and Biomaterials
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• v.18 no.2
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• pp.69-75
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• 2009

Daba ecorace of Antheraea mylitta Drury (Lepidoptera: Saturniidae), the semi domesticated Indian tropical tasar silkworm being reared outdoor; the egg and silk yields are dependent of genotype environment interaction. The insufficient maintenance and multiplication of its P4 seed stock need a coherent as well as scientific strategy to safeguard breed potential, being commercially applied ecorace. The sort-out lines of P4 stock studied over five generations highlighting on commercial trait up gradation suits for a tropical crop season, revealed enhanced performance. The line with high pupal parents (T2) shown improved fecundity (12.9%) and the line with high shell parents (T3) recorded higher shell weight (40.0%) and silk ratio (24.1%). While, the line of high pupal female and high shell male (T4) reveal enhancement in fecundity (9.0%), egg hatching (14.1%), shell weight (50.0%), silk ratio (35.2%) and absolute silk yield (52.0%) indicating the need and role of varied basic seed stock lines. The approach could improve economically vital egg fecundity and cocoon shell weights besides balancing them in same line for commercial operation. The progressive show of lines (T1 to T4) along successive generations (G1 to G5), in spite of passing through seed crop (Jul-Aug) and commercial crop (Sep-Nov) seasons emphasize their compatibility. The study infers that the strategic plan of combining preferred parental phenotypes, methodical selection for desired commercial trait(s) through generations with best possible genotype environment interaction has enriched P4 stock with elevation in needy trait(s) besides assuring choice of suitable lines for seasons and regions and timely replenishment of basic seed of Daba ecorace.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.501-508
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• 2004

This paper proposes a virtual relevant document technique in the teaming phase for text categorization. The method uses a simple transformation of relevant documents, i.e. making virtual documents by combining document pairs in the training set. The virtual document produced by this method has the enriched term vector space, with greater weights for the terms that co-occur in two relevant documents. The experimental results showed a significant improvement over the baseline, which proves the usefulness of the proposed method: 71% improvement on TREC-11 filtering test collection and 11% improvement on Routers-21578 test set for the topics with less than 100 relevant documents in the micro average F1. The result analysis indicates that the addition of virtual relevant documents contributes to the steady improvement of the performance.

• The Journal of the Acoustical Society of Korea
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• v.13 no.4
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• pp.60-68
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• 1994

In this paper we propose a new Hybrid learning rule applied to multilayer feedforward neural networks, which is constructed by combining Hebbian learning rule that is a good feature extractor and Back-Propagation(BP) learning rule that is an excellent classifier. Unlike the BP rule used in multi-layer perceptron(MLP), the proposed Hybrid learning rule is used for uptate of all connection weights except for output connection weigths becase the Hebbian learning in output layer does not guarantee learning convergence. To evaluate the performance, the proposed hybrid rule is applied to classifier problems in two dimensional space and shows better performance than the one applied only by the BP rule. In terms of learning speed the proposed rule converges faster than the conventional BP. For example, the learning of the proposed Hybrid can be done in 2/10 of the iterations that are required for BP, while the recognition rate of the proposed Hybrid is improved by about $0.778\%$ at the peak.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.389-398
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• 2007

Case-based reasoning (CBR) is one of the most popular prediction techniques for medical diagnosis because it is easy to apply, has no possibility of overfitting, and provides a good explanation for the output. However, it has a critical limitation - its prediction performance is generally lower than other artificial intelligence techniques like artificial neural networks (ANNs). In order to obtain accurate results from CBR, effective retrieval and matching of useful prior cases for the problem is essential, but it is still a controversial issue to design a good matching and retrieval mechanism for CBR systems. In this study, we propose a novel approach to enhance the prediction performance of CBR. Our suggestion is the simultaneous optimization of feature weights, instance selection, and the number of neighbors that combine using genetic algorithms (GAs). Our model improves the prediction performance in three ways - (1) measuring similarity between cases more accurately by considering relative importance of each feature, (2) eliminating redundant or erroneous reference cases, and (3) combining several similar cases represent significant patterns. To validate the usefulness of our model, this study applied it to a real-world case for evaluating cytological features derived directly from a digital scan of breast fine needle aspirate (FNA) slides. Experimental results showed that the prediction accuracy of conventional CBR may be improved significantly by using our model. We also found that our proposed model outperformed all the other optimized models for CBR using GA.

• Quality Improvement in Health Care
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• v.7 no.2
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• pp.204-216
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• 2000

Background : There has been a concern that the quality of care provided to end-stage renal disease (ESRD) patients in the United States may not be as good as recommended. This paper illustrates a composite measure to assess, the quality of care received by ESRD patients undergoing in-center hemodialysis by incorporating outcomes for 4 major treatment areas. The 4 treatment areas are: dialysis treatments, anemia control, nutritional management, and blood pressure control. Methods : The major data source for the study was the United States Renal Data System (USRDS) Dialysis Morbidity and Mortality Study Wave 1 (DMMS-1) d Sixteen categories of a composite quality indicator were constructed by combining 4 dichotomous variables (16=2*2*2*2). representing the optimal vs. less than optimal level of outcome for each of the 4 treatment outcome measure respectively. Optimal outcome level for each treatment area was defined based on the recommendation from the National Kidney Foundation: (a) delivered dialysis doses (Kt/V) ${\geq}$ 1.2; (b) hematocrit level ${\geq}$ 30%; (c) serum albumin concentration ${\geq}$ 3.8g/dl ; and (d) blood pressure of <140 / <90mmHg. The 16 quality indicator were ranked according to their relative quality weights, which were estimated from its association with the relative risk of survival, adjusting for patient's baseline severity and dialysis facility characteristics. Results : Out of the entire sample of 2,179 patients, only 229 (10%) meet th recommended outcome levels for all 4 treatment areas. Overall, the study patients were distributed evenly over the 16 quality indicators, indicating a great variation in the quality of ESRD care. It appears that the rank of the 16 quality-indicators is driven by serum albumin concentration, suggesting that serum albumin concentration may be the most powerful predictor of ESRD patient survival among the 4 outcome measures. Conclusion : The developed quality indicator has the advantage of describin a range of care for dialysis patients and thus providing a more complete picture of care as compared to previous studies that have focused on only single or few components of the ESRD care.