• Journal of Communications and Networks
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• v.16 no.2
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• pp.162-171
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• 2014

Spectrum sensing is a key technical challenge for cognitive radio (CR). It is well known that multicycle cyclostationarity (MC) detection is a powerful method for spectrum sensing. However, a conventional MC detector is difficult to implement because of its high computational complexity. This paper considers reducing computational complexity by simplifying the test statistic of a conventional MC detector. On the basis of this simplification process, an improved MC detector is proposed. Compared with the conventional detector, the proposed detector has low-computational complexity and high-accuracy sensing performance. Subsequently, the sensing performance is further investigated for the cases of Rayleigh, Nakagami-m, Rician, and Rayleigh fading and lognormal shadowing channels. Furthermore, square-law combining (SLC) is introduced to improve the detection capability in fading and shadowing environments. The corresponding closed-form expressions of average detection probability are derived for each case by the moment generation function (MGF) and contour integral approaches. Finally, illustrative and analytical results show the efficiency and reliability of the proposed detector and the improvement in sensing performance by SLC in multipath fading and lognormal shadowing environments.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.677-687
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• 2016

Multi-way relay networks (MWRNs) allow multiple users to exchange information with each other through a single relay terminal. MWRNs are often incorporated with capacity achieving lattice codes to enable the benefits of high-rate signal constellations to be extracted. In this paper, we analytically characterize the symbol error rate (SER) performance of a functional decode and forward (FDF) MWRN in the presence of channel estimation errors. Considering M-ary quadrature amplitude modulation (QAM) with square constellations as an important special case of lattice codes, we obtain asymptotic expressions for the average SER for a user in FDF MWRN. The accuracy of the analysis at high signal-to-noise ratio is validated by comparison with the simulation results. The analysis shows that when a user decodes other users with better channel conditions than itself, the decoding user experiences better error performance. The analytical results allow system designers to accurately assess the non-trivial impact of channel estimation errors and the users' channel conditions on the SER performance of a FDF MWRN with M-QAM modulation.

• BMB Reports
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• v.38 no.6
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• pp.633-638
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• 2005

Biosynthesis of prostanoids is regulated by three sequential enzymatic steps, namely phospholipase $A_2$ enzymes, cyclooxygenase (COX) enzymes, and various lineage-specific terminal prostanoid synthases. Prostaglandin E synthase (PGES), which isomerizes COX-derived $PGH_2$ specifically to $PGE_2$, occurs in multiple forms with distinct enzymatic properties, expressions, localizations and functions. Two of them are membrane-bound enzymes and have been designated as mPGES-1 and mPGES-2. mPGES-1 is a perinuclear protein that is markedly induced by proinflammatory stimuli, is down-regulated by anti inflammatory glucocorticoids, and is functionally coupled with COX-2 in marked preference to COX-1. Recent gene targeting studies of mPGES-1 have revealed that this enzyme represents a novel target for anti-inflammatory and anti-cancer drugs. mPGES-2 is synthesized as a Golgi membrane-associated protein, and the proteolytic removal of the N-terminal hydrophobic domain leads to the formation of a mature cytosolic enzyme. This enzyme is rather constitutively expressed in various cells and tissues and is functionally coupled with both COX-1 and COX-2. Cytosolic PGES (cPGES) is constitutively expressed in a wide variety of cells and is functionally linked to COX-1 to promote immediate $PGE_2$ production. This review highlights the latest understanding of the expression, regulation and functions of these three PGES enzymes.

• International Journal of Costume and Fashion
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• v.4
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• pp.47-61
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• 2004

This study analyzed the buying patterns of American and Korean female college students in terms of criteria for clothing selection； store preferences； criteria for store selection； fashion information sources； expressions of customer dissatisfaction； purchasing frequency and motivations for purchasing clothes. The study was implemented through self-administered questionnaires which were back translated for validity. The samples consisted of 730 female college students majoring in the fields related to clothing and textiles： 310 U.S. and 412 Korean students. Likert scales were used for most measures with 1＝never or very unimportant and 5＝always or very important. Data were analyzed by factor analysis, analysis of covariance, Duncans multiple comparison, and t-test. Results are as follows： 1) Design factor was the most important criteria in clothing selection with no differences between country groups. There were, however, significant differences for psychological exhibition factors, practical and economic factors. 2) Both groups preferred specialty and department stores, with department stores more popular in Korea. 3) Merchandise was the most important store selection criterion and fashion magazines and self-experience were rated as the most important information sources for the both groups. 4) Korean group expressed their dissatisfaction with and observable problem with a product before purchase more often than U.S. group, but the U.S. group was more vocal about color loss or shrinkage after care procedures. 5) Some clear differences between the two countries emerged. Marketers targeting American consumers should pay more attention to practicality and service； to Korean consumers more symbolic meaning of products.

• Journal of the Korea Furniture Society
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• v.21 no.2
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• pp.133-143
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• 2010

Although past design developments that emphasized only the outer appearances of products were mostly concentrated on the areas of forms and colors in an attempt to satisfy humans' visual needs, it is expected that future designs to come will go in the direction to stimulate more diversified human senses. This means expansions to the five senses including the auditory sense, the sense of smell, the tactile sense and the taste and even to the area of synesthesia where two or more senses are stimulated or coexist. Although the dictionary definition of synesthesia is a concept of arousing another sense through a sense, studies of synesthesia in design go one step further from here to mean compound senses, that is, the synesthesia in an expanded meaning to feel an object (thing) through many sensory organs simultaneously. The synesthesia in the expanded meaning is applying multiple senses simultaneously in recognizing one thing to comprehensively judge and feel the thing. Recent design trends are going in a direction to basically satisfy humans' visual needs through controlled forms and colors while inducing another new feeling through expressions of diverse feels of materials within existing forms. In this change of the times, studies on furniture designs are conducted through factors of in synesthesia linked with other senses and have an important meaning that can enhance the value of designs.

• Biomolecules & Therapeutics
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• v.24 no.5
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• pp.475-481
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• 2016

PICK1, a PDZ domain-containing protein, is known to increase the reuptake activities of dopamine transporters by increasing their expressions on the cell surface. Here, we report a direct and functional interaction between PICK1 and dopamine $D_3$ receptors ($D_3R$), which act as autoreceptors to negatively regulate dopaminergic neurons. PICK1 colocalized with both dopamine $D_2$ receptor ($D_2R$) and $D_3R$ in clusters but exerted different functional influences on them. The cell surface expression, agonist affinity, endocytosis, and signaling of $D_2R$ were unaffected by the coexpression of PICK1. On the other hand, the surface expression and tolerance of $D_3R$ were inhibited by the coexpression of PICK1. These findings show that PICK1 exerts multiple effects on $D_3R$ functions.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.2
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• pp.178-184
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• 2009

The Nuclear Power Plant(NPP) industry in Korea has been making efforts to reduce the human errors which have largely contributed to about 150 nuclear reactor trips since 2001. Recently, the Crew Resource Management(CRM) training has risen as an alternative countermeasure against the nuclear reactor trips caused by human errors. The effectiveness of CRM training in NPP industry, however, has not been proven to be significant yet. In this study a return on investment(ROI) model is developed to measure the effectiveness of CRM training for the operators in Korean NPP. The model consists of mathematical expressions including multiple variables affecting the CRM training impacts and nuclear reactor trips. Implication of the model is discussed further in detail.

• Journal of the Korea Furniture Society
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• v.25 no.3
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• pp.173-181
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• 2014

Since the onset of the 21st century, digital technology has been widely adopted in various fields of art; it has enabled artists or designers to try diverse and brand-new ways of expression in literally every possible field of art, including painting, sculpture, and other design work. Furniture design is no exception. From the initial design step to the final production of furniture, modern digital skills are broadly utilized, creating a whole new set of designs that would otherwise be hardly conceivable and realizing a highly efficient furniture-making mechanism. More recently, the 3D printing technique, which is called a 21st century alchemy, has been successfully commercialized and is getting more popular, heralding yet another innovative shift in the area of furniture design and production. In this context, this study discusses the background of the furniture design using digital technology, and identifies the correlations between the modern digital technology and furniture design by redefining the concept of such digital technology. By reviewing multiple real-life cases, some of the key digital expressions found in modern furniture design are also analyzed. This study aims at suggesting the reason why digital technology is significant and promising in diverse ways for the development of modern furniture design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.6
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• pp.1606-1626
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• 2012

This paper investigates the performance of an amplify-and-forward (AF) two-way relaying system with antenna correlation. The system consists of two multiple-antenna sources, which exchange information via the aid of a single-antenna relay. In particular, we derive the exact outage probability expression. Furthermore, we provide a simple, tight closed-form lower bound for the outage probability. Based on the lower bound, we obtain the closed-form asymptotic outage probability and the average symbol error rate expressions at high signal-to-noise ratio (SNR), which reveal the system's diversity order and coding gain with antenna correlation. To investigate the system's throughput performance with antenna correlation, we also derive a closed-form lower bound for the average sum-rate, which is quite tight from medium to high SNR regime. The analytical results readily enable us to obtain insight into the effect of antenna correlation on the system's performance. Extensive Monte Carlo simulations are conducted to verify the analytical results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.2056-2069
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• 2014

In order to implement interactive and personalized Web services properly, it is necessary to understand the tangible and intangible responses of the users and to recognize their emotional states. Recently, some studies have attempted to build emotional state estimation models based on facial expressions. Most of these studies have applied multiple regression analysis (MRA), artificial neural network (ANN), and support vector regression (SVR) as the prediction algorithm, but the prediction accuracies have been relatively low. In order to improve the prediction performance of the emotion prediction model, we propose a novel SVR model that is optimized using a genetic algorithm (GA). Our proposed algorithm-GASVR-is designed to optimize the kernel parameters and the feature subsets of SVRs in order to predict the levels of two aspects-valence and arousal-of the emotions of the users. In order to validate the usefulness of GASVR, we collected a real-world data set of facial responses and emotional states via a survey. We applied GASVR and other algorithms including MRA, ANN, and conventional SVR to the data set. Finally, we found that GASVR outperformed all of the comparative algorithms in the prediction of the valence and arousal levels.