• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.3
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• pp.784-793
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• 2012

This paper deals with subcarrier allocation strategies for soft hand-over in OFDMA-based cellular systems. Two possible subcarrier allocation methods are considered for soft hand-over. One method is to use an identical subcarrier set between the two cells participating in the hand-over. The other is to use different subcarrier sets between the two cells. As expected, the different subcarrier strategy is better in terms of diversity order and BER than the identical subcarrier strategy. It will be shown that the BER performance difference between the two strategies is more noticeable with contiguous subcarrier allocation. But the different subcarrier strategy consumes twice more frequency resources than the other, and there is a trade-off between the two strategies in terms of BER and frequency resources. By considering the trade-off, we also propose a subcarrier allocation strategy for soft hand-over.

• Journal of Information Technology Applications and Management
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• v.27 no.6
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• pp.75-87
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• 2020

The Human Resource (HR) system comprises of various interrelated HR practices that forms the bundles. These bundles of Human Resource practices impact the organizational performance. The hard and soft HR bundles are the two sets of the same continuum that describes the strategic approach of the HR system. The purpose of this study is to identify the hard and soft HRM practices from the literature and then empirically test them with the help of factor analysis. The study is conducted on the service industry employees in India. The survey includes the employees from the middle and top-level executives of the service firms. The sample size for the study is 160. Principal component analysis with VARIMAX rotation and Confirmatory Factor Analysis was used to obtain the results. The data analysis was done on SPSS V.20 and AMOS V.22. The results provide knowledge of the HR practices under the hard and soft HRM bundles implemented in the service industry.

• Nonlinear Functional Analysis and Applications
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• v.28 no.3
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• pp.753-774
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• 2023

The fundamental aim of the proposed work is to introduce the concept of soft rectangular b-metric spaces, which involves generalizing the notions of rectangular metric spaces and b-metric spaces. Furthermore, an investigation into specific characteristics and topological aspects of the underlying generalization of metric spaces is conducted. Moreover, the research establishes fixed point theorems for mappings that satisfy essential criteria within soft rectangular b-metric spaces. These theorems offer a broader perspective on established results in fixed point theory. Additionally, several congruous examples are presented to enhance the understanding of the introduced spatial framework.

• Journal of applied mathematics & informatics
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• v.42 no.1
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• pp.31-47
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• 2024

The concept of hybrid structures integrates two powerful mathematical tools: soft sets and fuzzy sets. This paper extends the application of hybrid structures to ordered hypersemigroups. We introduce the notions of hybrid interior hyperideals in ordered hypersemigroups and demonstrate their equivalence with hybrid hyperideals in certain classes, including regular, intra-regular, and semisimple ordered hypersemigroups. Furthermore, we provide a characterization of semisimple ordered hypersemigroups in terms of hybrid interior hyperideals.

• Journal of Power Electronics
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• v.10 no.4
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• pp.335-341
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• 2010

In this paper, an interleaved soft switching boost converter for a Photovoltaic Power Conditioning System (PV-PCS) with high efficiency is proposed. In order to raise the efficiency of the proposed converter, a 2-phase interleaved boost converter integrated with soft switching cells is used. All of the switching devices in the proposed converter achieve zero current switching (ZCS) or zero voltage switching (ZVS). Thus, the proposed circuit has a high efficiency characteristic due to low switching losses. To analyze the power losses of the proposed converter, two experimental sets have been built. One consists of normal devices (MOSFETs, Fast Recovery (FR) diodes) and the other consists of advanced power devices (CoolMOSs, SiC-Schottky Barrier Diodes (SBDs)). To verify the validity of the proposed topology, theoretical analysis and experimental results are presented.

• Journal of the Korean Institute of Intelligent Systems
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• v.1 no.1
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• pp.9-25
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• 1991

This tutorial paper has been written for biologists, physicians or beginners in fuzzy sets theory and applications. This field is introduced in the framework of medical diagnosis problems. The paper describes and illustrates with practical examples, a general methodology of special interest in the processing of borderline cases, that allows a graded assignment of diagnoses to patients. A pattern of medical knowledge consists of a tableau with linguistic entries or of fuzzy propositions. Relationships between symptoms and diagnoses are interpreted as labels of fuzzy sets. It is shown how possibility measures (soft matching) can be used and combined to derive diagnoses after measurements on collected data. The concepts and methods are illustrated in a biomedical application on inflammatory protein variations. In the case of poor diagnostic classifications, it is introduced appropriate ponderations, acting on the characterizations of proteins, in order to decrease their relative influence. As a consequence, when pattern matching is achieved, the final ranking of inflammatory syndromes assigned to a given patient might change to better fit the actual classification. Defuzzification of results (i.e. diagnostic groups assigned to patients) is performed as a non fuzzy sets partition issued from a "separating power", and not as the center of gravity method commonly employed in fuzzy control. It is then introduced a model of fuzzy connectionist expert system, in which an artificial neural network is designed to build the knowledge base of an expert system, from training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the connections: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through MIN-MAX fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feed forward network is described and illustrated in the same biomedical domain as in the first part.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.137-145
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• 2013

Recently most mobile devices have soft keyboards on their LCD touch screens. Because of the tiny size of the touch screen of the soft keyboard, adjacent keys are mistakenly typed. Also utilizing a key for multiple key inputs causes key type errors. In this paper, we proposed an algorithm to recommend proper words to the user while the user continues to type keys, which helps to easily correct key type errors. In addition, we presented a soft keyboard called MissLess which implemented the recommendation algorithm. We evaluated recommendation performance of MissLess keyboard through experiments by using 3 test sets. The test results showed that the success ratio of recommendation reached up to about 90% although there were some differences between results. However it is needed to be considered that we recommended 4 words for an input word in this experiments.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.3-6
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• 2006

Methods for risk engineering is a bundle of engineering tools including fundamental concepts and approaches of soft computing with application to real issues of risk management. In this talk fundamental concepts and soft computing approaches of risk engineering will be introduced. As the term of risk implies both advantageous and hazardous uncertainty in its origins, a fundamental theory to describe uncertainties is introduced that includes traditional probability and statistical models, fuzzy systems, as well as less popular modal logic. In particular, modal logic capabilities to express various kinds of uncertainties are emphasized and relations with rough sets and evidence theory are described. Another topic is data mining related to problems in risk management. Some risk mining techniques including fuzzy clustering are introduced and a recently developed algorithm is overviewed. A numerical example is shown.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.51 no.7
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• pp.311-315
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• 2002

Chemical mechanical polishing (CMP) process was required for the global planarization of inter-metal dielectric(IMD), inter-level dielectric (ILD) layers of multi-layer interconnections. In this paper, we studied the characteristics of polishing pad, which can apply shallow trench isolation (STI)-CMP process for global planarization of multi-level interconnection structure. Also, we investigated the effects of different sets of polishing pad, such as soft and hard pad. As an experimental result, hard pad showed center-fast type, and soft pad showed edge-fast type. Totally, the defect level has shown little difference, however, the counts of scratch was detected less than 2 on JR111 pad. Through the above results, we can select optimum polishing pad, so we can expect the improvements of throughput and device yield.

• Environmental Engineering Research
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• v.25 no.3
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• pp.418-425
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• 2020

In this study soft computing techniques including, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were investigated for the prediction of Cr(VI) transport efficiency by novel Polymer Inclusion Membranes (PIMs). Transport experiments carried out by varying parameters such as time, film thickness, carrier type, carier rate, plasticizer type, and plasticizer rate. The predictive performance of ANN and ANFIS model was evaluated by using statistical performance criteria such as Root Mean Standard Error (RMSE), Mean Absolute Error (MAE), and Coefficient of Determination (R²). Moreover, Sensitivity Analysis (SA) was carried out to investigate the effect of each input on PIMs Cr(VI) removal efficiency. The proposed ANN model presented reliable and valid results, followed by ANFIS model results. RMSE and MAE values were 0.00556, 0.00163 for ANN and 0.00924, 0.00493 for ANFIS model in the prediction of Cr(VI) removal efficiency on testing data sets. The R² values were 0.973 and 0.867 on testing data sets by ANN and ANFIS, respectively. Results show that the ANN-based prediction model performed better than ANFIS. SA demonstrated that time; film thickness; carrier type and plasticizer type are major operating parameters having 33.61%, 26.85%, 21.07% and 8.917% contribution, respectively.