• Journal of applied mathematics & informatics
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• v.42 no.3
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• pp.521-538
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• 2024

In this paper, using the notion of the imprecise set, the idea of an imprecise group is introduced including some examples. The two key rules of classical set theory are obeyed by this extended version of fuzzy sets, which the existing complement definition of a fuzzy set failed to do. With the support from general group theory, the paper also provides some fundamental properties of an imprecise group here. Additionally, it includes a few characteristics of imprecise subgroups, and abelian imprecise group.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.157-169
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• 2004

This paper presents a prescriptive approach to group decision making with group members' imprecise preference information. This includes an alternative method to Salo's inventive approach for identifying group's preferred alternative when attribute weights, consequences, and possibly group members' importance weights are specified in imprecise ways. The imprecise additive group value function can be decomposed into individual group member's imprecise decision making problems, which are finally aggregated to identify group's preferred alternative. The proposed approach is intuitive and easy to implement, and has merits in a couple of points. First. it is possible to view individual group member's inclinations toward conflicting alternatives and the degree of discrepancies to each other. Second, we can observe how much previous decision results of individual decision maker are influenced during interaction since decisions usually are not made at a single step especially in presence of partial preference information. Finally, the individual group member's decision results can be utilized for further investigation of dominance relations among alternatives in a case that interactive questions and responses fail to give a convergent group consensus.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.557-567
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• 2005

The increasing complexity of the socio-economic environments makes it less and less possible for single decision-maker to consider all relevant aspects of problem. Therefore are, many organizations employ groups in decision making. In this paper, we present a multiperson decision making method using fuzzy logic with linguistic quantifier when each of group members specifies imprecise judgments possibly both on performance evaluations of alternatives with respect to the multiperson criteria and on the criteria. Inexact or vague preferences have appeared in the decision making literatures with a view to relaxing the burdens of preference specifications imposed to the decision-makers and thus taking into account the vagueness of human judgments. Allowing for the types of imprecise judgments in the model, however, makes more difficult a clear selection of alternative(s) that a group wants to make. So, further interactions with the decision-makers may proceed to the extent to compensate for the initial comforts of preference specifications. These interaction may not however guarantee the selection of the best alternative to implement. To circumvent this deadlock situation, we present a procedure for obtaining a satisfying solution by the use of linguistic quantifier guided aggregation which implies fuzzy majority. This is an approach to combine a prescriptive decision method via a mathematical programming and a well-established approximate solution method to aggregate multiple objects.

• Journal of Intelligence and Information Systems
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• v.12 no.3
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• pp.15-32
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• 2006

The increasing complexity of the socio-economic environments makes it less and less possible for single decision-maker to consider all relevant aspects of problem. Therefore, many organizations employ groups in decision making. In this paper, we present a multiperson decision making method using fuzzy logic with linguistic quantifier when each of group members specifies imprecise judgments possibly both on performance evaluations of alternatives with respect to the multiple criteria and on the criteria. Inexact or vague preferences have appeared in the decision making literatures with a view to relaxing the burdens of preference specifications imposed to the decision-makers and thus taking into account the vagueness of human judgments. Allowing for the types of imprecise judgments in the model, however, makes more difficult a clear selection of alternative(s) that a group wants to make. So, further interactions with the decision-makers may proceed to the extent to compensate for the initial comforts of preference specifications. These interactions may not however guarantee the selection of the best alternative to implement. To circumvent this deadlock situation, we present a procedure for obtaining a satisfying solution by the use of linguistic quantifier guided aggregation which implies fuzzy majority. This is an approach to combine a prescriptive decision method via a mathematical programming and a well-established approximate solution method to aggregate multiple objects.

• Journal of Navigation and Port Research
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• v.29 no.6 s.102
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• pp.573-581
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• 2005

The outbound containers in a container terminal are classified into a few groups by their weights and stacked separately in a yard for easy and efficient handling. In order to maintain the balance of a ship during loading, containers of heavier weight groups should be fetched out of a yard and loaded onto the ship before those of lighter weight groups. However, the weight information used to determine the weight group is usually imprecise. Therefore stacks will actually be filled with mixture of different weight groups and rehandlings are unavoidable during loading operation. This paper presents a method for estimating the number of rehandlings caused by imprecise information and a scheme for generating a simple but efficient slot assignment rule. Experiments have shown that a rule generated by the proposed method can reduce the number of rehandlings by about $20\%$ compared to the traditional slot assignment method which stacks only the containers of the same weight group in a single stack.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.391-398
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• 2005

The outbound containers in a container terminal are classified into a few groups by their weights and stocked separately in a yard for easy and efficient handling. In order to maintain the balance of a ship during loading, containers of heavier weight groups should be fetched out of a yard and loaded onto the ship before those of lighter weight groups. However, the weight information used to determine the weight group is usually imprecise. Therefore stacks will actually be filled with mixture of different weight groups and rehandlings are unavoidable during loading operation. This paper presents a method for estimating the number of rehandlings caused by imprecise information and a scheme for generating a simple but efficient slot assignment rule. Experiments have shown that a rule generated by the proposed method can reduce the number of rehandlings by about 20%compared to the traditional slot assignment method which stacks only the containers of the same weight group in a single stack.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.05
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• pp.127-130
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• 1995

Chromosome analysis is an important and difficult task for clinical diagnosis, for mutagen dosimetry, and for biological research. It is expensive, time consuming and imprecise when performed manually. Efforts lo automate some or all of the procedures have continued for more than 30 years, with only limited success. An acquiring sample from chromosome group is not solved with automatic method. It is still performed by user. This paper represents the method of an automatic chromosome sample extraction which based on region splitting, and scan converted method.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.661-663
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• 1995

Chromosome analysis is an important and difficult task for clinical diagnosis for mutagen dosimetry, and for biological research. It is expensive, time consuming and imprecise when performed manually. Efforts to automate some or all of the procedures have continued for more than 30 years, with only limited success. An acquiring sample from chromosome group is not solved with automatic method. It is still performed by user. This paper represents the method of an automatic chromosome sample extraction which based on region splitting, and scan converted method.

• Journal of Ecology and Environment
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• v.37 no.4
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• pp.395-410
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• 2014

The genus Callophyllis is recorded as six separate species with imprecise species delimitation in Korea. To elucidate the species boundaries of Korean Callophyllis, we performed morphological observations and molecular analyses, and included three Japanese Callophyllis species from the type locality. From the results of molecular analyses using plastid rbcL and mitochondrial COI-5P genes, we confirmed ten Callophyllis species, including five cryptic ones: C. adhaerens, C. adnata, C. crispata, and C. japonica from Korea and Japan; C. hayamensis as an unrecorded species from Korea; C. cartilaginea, C. mollitia, C. repens, C. serratifolia, and C. undulata as new species from Korea. There were no Korean specimens that matched C. adnata or C. crispata from Japan, except Korean C. japonica, which formed a genetic group with the Japanese species. We obtained the interspecific divergences among the five cryptic species as 0.6-4.5% in rbcL and 2.8-8.4% in COI-5P. We recognized that the species diversity of Callophyllis has been underestimated from the northwestern Pacific region. The species boundary of Callophyllis from Korea and Japan will be a cornerstone to revealing the phylogenetic affinity of the genus distributed in both hemispheres of the western Pacific.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.13
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• pp.5549-5556
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• 2015

Background: Cancer has important social consequences with cancer registration as the basis of moving towards prevention. The present study aimed to estimate the completeness of registration of the ten most common cancers in patients referred to selected hospitals in Shiraz, Iran by using capture-recapture method. Materials and Methods: This cross-sectional analytical study was performed in 2014 based on the data of 2009, on a total of 4,388 registered cancer patients. After cleaning data from two sources, using capture-recapture common findings were identified. Then, the percentage of the completeness of cancer registration was estimated using Chapman and Chao methods. Finally, the effects of demographic and treatment variables on the completeness of cancer registration were investigated. Results: The results showed that the percentages of completeness of cancer registration in the selected hospitals of Shiraz were 58.6% and 58.4%, and influenced by different variables. The age group between 40-49 years old was the highest represented and for the age group under 20 years old was the lowest for cancer registration. Breast cancer had the highest registration level and after that, thyroid and lung cancers, while colorectal cancer had the lowest registration level. Conclusions: According to the results, the number of cancers registered was very few and it seems that factors like inadequate knowledge of some doctors, imprecise diagnosis about the types of cancer, incorrectly filled out medical documents, and lack of sufficient accuracy in recording data on the computer cause errors and defects in cancer registration. This suggests a necessity to educate and teach doctors and other medical workers about the methods of documenting information related to cancer and also conduct additional measures to improve the cancer registration system.