• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.3B
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• pp.472-486
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• 2000

This paper analysis the performance of joint receiving structure consisting of the decorrelating multiuser detection and beamfromenr-RAKE receive for DS-CDMA communication systems. In asynchronous transmission as the number of simultaneous users increase. the capacity of CDMA system becomes severly reduced due to the nonideal orthogonality between user-assigned PN sequences and improper power control. Accordingly, the CDMA receiving system becomes vulnerable to the multiple access interferences and the near-far problem under multipath fading channel environment. To withstand these undesired performance degradations, this paper proposes the new type of multiuser detection which has a form of the hybrid structure of concatenating beamformer-RAKE receiver and decorrelating multiuser detection. the beam former-RAKE receiver performs temporal and spatial diversity combining with alleviating fading effect and suppressing undesired interferences, and the multiuser detection plays a role of making the receiver robust to the near-far problem. Regarding the individual merit on the usage of either multiuser detection or beamformer-RAKE receiver, the hybrid one is expected to produce the enhanced performance in multipath fading CDMA channel. However major drawback of using decorrelating multiuser detection for practical deployment is arised from its computational complexity , which is exponentially increased as more number of users and transmitted symbols involve. To diminish the computational complexity, this paper exploits an efficient block Toeplitz inversion technique using matrix Levinson polynomial will be introduced. And this paper provided the mathematical analysis to show the efficiency of the proposed joint structure under the multipath propagation environment. And results of a series of exhaustive computer simulations are presented in order to demonstrate the overall performance of the proposed hybrid structure in multipath fading CDMA channel.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.2
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• pp.249-258
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• 1998

In land mobile communication, very extensive studies on pilot symbol assisted modulation (PSAM) have been made on fading compensation. This paper analyzes the effect of power amplifier nonlinearity on PSA-QAM with maximal ratio combining space diversity. In practical PSAM, information on fading is obtained through interpolation of the pilot symbols. We employed the interpolation filter which could minimize the average power of error and analyzed effects on the system performance of the number of filter taps, period of the pilot symbol frame, and the Doppler frequency. Nonlinear power amplifiers of class AB, B, and C were incorporated in the system models and their AM/AM and AM/PM characteristics were taken into account in the performance analysis. We showed the performance variations according to the types of the nonlinear power amplifiers in the AWGN and Rayleigh fading channels using nonlinear compensation technique, Cartesian Feedback Loop (CFB).

• Journal of KIISE
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• v.43 no.1
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• pp.61-70
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• 2016

In recent years, there has been a need for techniques for large-scale ontology inference in order to infer new knowledge from existing knowledge at a high speed, and for a diversity of semantic services. With the recent advances in distributed computing, developments of ontology inference engines have mostly been studied based on Hadoop or Spark frameworks on large clusters. Parallel programming techniques using GPGPU, which utilizes many cores when compared with CPU, is also used for ontology inference. In this paper, by combining the advantages of both techniques, we propose a new method for reasoning large RDFS ontology data using a Spark in-memory framework and inferencing distributed data at a high speed using GPGPU. Using GPGPU, ontology reasoning over high-capacity data can be performed as a low cost with higher efficiency over conventional inference methods. In addition, we show that GPGPU can reduce the data workload on each node through the Spark cluster. In order to evaluate our approach, we used LUBM ranging from 10 to 120. Our experimental results showed that our proposed reasoning engine performs 7 times faster than a conventional approach which uses a Spark in-memory inference engine.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.5
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• pp.3-10
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• 2020

According to Carol Duncan, the museum can be studied in the aspect of space and object from viewer experience. The paradigm of modern museums is shifting away from the object toward the human. The modern museum begins to have the diversity activities and the experience by the body. The purpose of this study is to analyze methods of Carlo Scarpa's museum works. An Italian architect, Carlo Scarpa had characterized montage architecture through fragments and isolations. This study reviews the works of Carlo Scarpa's museum focused on Museo di Castelvecchio. Carlo Scarpa had left the existing materials and coated it with new materials intentionally. This method makes the layer and it exposes the historical times. The layer is a reinterpreting technic of Venetian architecture. The perceptive experience appears at the exhibition boundary through light, material, pattern, axis, and composition of elements. Through the analysis, the architecture of Carlo Scarpa's museum provides a walking path and the composition of exhibition objects with visual logics. It makes and show us the experience with combining images. Carlo Scarpa had tried to expose the past times in the architecture of museum with expression on the layers and to connect the body's movements with seeing and gazing. This expression makes possible the perceptual experience. It can be understood as the montage characteristic. Through this, Carlo Scarpa's museum makes us relationship with historical architecture. Carlo Scarpa had planned a exhibitional promenade in the architecture of museums. In this regard, this is the museography of Carlo Scarpa's museums that should be paid attention to modern times in historical architecture.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1477-1483
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• 2020

The stability guarantee of wireless network based control systems is still challenging due to the lossy links and node failures. This paper proposes a hierarchical cluster-based network protocol called robust wireless sensor and actuator network (R-WSAN) by combining time, channel, and space resource diversity. R-WSAN includes a scheduling algorithm to support the network resource allocation and a control task sharing scheme to maintain the control stability of multiple plants. R-WSAN was implemented on a real test-bed using Zolertia RE-Mote embedded hardware platform running the Contiki-NG operating system. Our experimental results demonstrate that R-WSAN provides highly reliable and robust performance against lossy links and node failures. Furthermore, the proposed scheduling algorithm and the task sharing scheme meet the stability requirement of control systems, even if the controller fails to support the control task.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.385-391
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• 2022

The relevance of the published study lies in the fact that since the introduction of the first Global Distribution System, new information and communication technologies have constantly been changing the tourism industry. In the context of a current digital environment, travel agencies can't avoid participating in digital transformation processes aimed at rethinking operational models, skills, and organisational structures in the regions. This publication aims to present and provide a critical overview of digitalisation processes in tourism development in the regions of the Russian Federation, as well as to reflect on the challenges to the widespread digitalisation processes in the regional tourism sector. The subject of research is digitalisation processes, as they radically transform the modern tourism industry, in the regions as well. The pragmatic research paradigm was considered the most appropriate for the study of tourism digitalisation processes in the regions, as it does not require the selection of a specific theoretical basis for data collection. The pragmatic approach forms an alternative to classical theoretical approaches and serves as a particular type of grounded theory, combining both inductive and deductive methods. No software was used for the inductive part of the analysis. The deductive part was conducted using the qualitative data analysis software Nvivo 11. Given the wide diversity of interested parties in the regional tourism digital area, a stratified purposive sampling method was preferred due to its ability to adequately represent the full picture of the phenomenon under study. The selection and stratum criteria were chosen to maximise the representation of different perspectives in the regional tourism digital area. The novelty of the study is due to the digitalisation processes, with an implication of new needs, while opening up promising opportunities for more productive tourism business in the regions of the Russian Federation. Currently, e-tourism in the Russian Federation has become a subject of lively debate among scholars and practitioners. However, the involvement of advanced digitalisation technologies in the field of information processes in the regions of the Russian Federation is of a very sporadic character.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.747-752
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• 2023

This study is about interaction design types in the production of sensor-based media installations combining Arduino, an open source platform. By typifying the realized media installation works, we seek to explore the diversity and meaning of new media art expression methods. Based on the understanding of the interaction method of media art, the interaction design type in the production of media installation using sensors was divided into physical movement through motor control, 'artificial plants using ultrasonic sensors and motors', and 'virtual garden using light and sound sensors'. 'Moving images using tilt sensors' are classified into four types. Through this, it is expected that media software can be selected as an appropriate technology for the work and can be presented as an example of artistic expression that is evolving into various expressions.

• Korean Journal of Agricultural Science
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• v.51 no.1
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• pp.9-23
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• 2024

This study investigates the physiological and psychological effects of a nature-based outdoor activity program in an environment reflecting the characteristics of forest and coastal areas on 30 firefighters (average age: 40.4 ± 9.8 years) who are frequently exposed to dangerous situations. Blood pressure, pulse pressure, and heart rate variability were used as physiological measurement indicators, and the Korean versions of PANAS (positive affect and negative affect schedule), WEMWBS (Warwick-Edinburgh mental well-being scale), and PRS (perceived restorativeness scale) were used as psychological measurement indicators. For four days and three nights, the participants experienced programs at Hallyeohaesang Nature Center and the surrounding mountains, seas, and islands, utilizing forest resources such as trekking on forest trails, walking barefoot, taking aromatic footbaths, meditating in forest oxygen domes, and lying on relaxation chairs, and programs utilizing marine resources such as taking a boat to an island, walking on forest trails with seascape views, and sailing on a yacht. Participants' systolic blood pressure and pulse pressure decreased, and participants' positive emotions increased and negative emotions decreased after the program. There was a statistically significant increase in mental well-being and perceived restorative environment. Through this study, it was found that nature-based outdoor activity programs based on forest and marine resources are effective in physiological and psychological stability of firefighters. It is hoped that the results of this study will be applied to other high-risk workers for PTSD, who have high stress levels, by combining forest healing and marine healing, and expanding the scope and diversity of programs in more diverse environments and conditions.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.99-112
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• 2010

Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.

• Journal of Science Education
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• v.41 no.3
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• pp.426-446
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• 2017

The purpose of this study was to analyze undergraduate students' reasoning for solving a problem about a rock and investigate the roles and importance of critical evidence (CE) and critical resource models (CRMs) in abductive reasoning. Participants were 20 senior undergraduate students enrolled in a science major course in a university of education. They were asked to abductively infer geologic processes of sedimentary rocks having a lot of holes and represent them with models. Their reasoning were analyzed according to a scheme for modeling-based abductive reasoning. As a result, successful student reasoning was characterized by using a diversity of grains and lots of holes as CE, activating the sedimentary rock formation and weathering as CRMs, and combining the CRMs into a scientifically sound explanatory model (SSEM). By contrast, in the reasoning unsuccessful in proposing a SSEM, students activated the igneous rock (basalt) formation and deposition as resource models (RMs) based on the evidence of the holes in the rocks and diverse grains, respectively, and used the RMs to construct their own explanatory models (EMs). It was suggested that to construct SSEMs to solve earth scientific problems about rocks, students need to know what could be CE in a particular problem situation, take an integrative or systemic approach to a rock problem, use multiple RMs, and evaluate RMs or EMs in light of evidence.