• Title/Summary/Keyword: P2P networks

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Eye Movement Program Consisting of Saccadic Eye Movement and Pursuit Eye Movement Improved Visual Memory in Institutionalized Elderly Person: Randomized controlled pilot study

  • Park, Yongnam;Bae, Youngsook
    • Journal of International Academy of Physical Therapy Research
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    • v.10 no.2
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    • pp.1768-1773
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    • 2019
  • Background: Aging reduces cognitive abilities, including visual memory (VM) and visual discrimination (VD). Since common cortical networks subserve eye movement and attention, voluntary eye movement may improve visual attention. Visual selective attention was major role for memory, and visual memory and visual attention are intimately related. Objective: To identify the improvement in VD and VM, after implementing the eye movement program consisting of saccadic eye movement (SEM) and pursuit eye movement (PEM) in the institutionalized healthy elderly. Design: Randomized controlled trial. Methods: The study involved a sample of 36 participants, and the mean age was 79.03 years (range 76~84 years). They were randomly allocated to the experimental group (n=16) and control group (n=20). Participants in the experimental group performed SEM 5 times per week for 4 weeks: twice daily at the same time in the morning and afternoon. The program was carried out for 3 minutes, and it consisted of SEM and PEM. The target's moving frequency was set at 0.5 Hz. VM and VD at the baseline and post-intervention were measured using Motor-Free Visual Perception test-4 (MFVPT-4). Results: VM significantly improved in the experimental group (p < .01), and significant differences were observed compared to the control group (p < .01). There was no significant change in VD. Conclusion: The eye movement program consisting of SEM and PEM increased VM more than VD. Therefore, eye movement program was feasible interventions for improving VM in institutionalized elderly persons.

Yeast two-hybrid assay with fluorescence reporter (형광 리포터를 활용한 효모 단백질 잡종 기법 개발)

  • Park, Seong Kyun;Seo, Su Ryeon;Hwang, Byung Joon
    • Korean Journal of Microbiology
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    • v.55 no.3
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    • pp.199-205
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    • 2019
  • Yeast two-hybrid (Y2H) technique has been used to study protein-protein interactions, but its application particularly to a large-scale analysis of protein interaction networks, is limited by the fact that the technique is labor-intensive, based on scoring colonies on plate. Here, we develop a new reporter for the measurement of the protein-protein interactions by flow cytometry. The yeast harboring interacting proteins can also be enriched by fluorescence-activated cell sorting (FACS) or magnetic-activated cell sorting (MACS). When two interacting proteins are present in the same yeast cell, a reporter protein containing 10 tandem repeats of c-myc epitope becomes localized on the surface of the cell wall, without affecting cell growth. We successful measured the surface display of c-myc epitope upon interacting p53 with SV40 T antigen by flow cytometry. Thus, the newly developed Y2H assay based on the display of c-myc repeat on yeast cell wall could be used to the simultaneous analysis of multiple protein-protein interactions without laborious counting colonies on plate.

Channel Searching Sequence for Rendezvous in CR Using Sidel'nikov Sequence (시델니코프 수열을 활용한 인지통신의 Rendezvous를 위한 채널 탐색 수열)

  • Jang, Jiwoong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.11
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    • pp.1566-1573
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    • 2021
  • Rendezvous is a process that assists nodes in a Cognitive Radio Networks (CRNs) to discover each other. In CRNs where a common control channel is unknown and a number of channels are given, it is important how two nodes find each other in a known search region. In this paper, I have proposed and analyzed a channel hopping sequence using Sidel'nikov sequence by which each node visits an available number of channels. I analyze the expected time to-rendezvous (TTR) mathematically. I also verify the Rendezvous performance of proposed sequence in the view of TTR under 2 user environment compared with JS algorithm and GOS algorithm. The Rendezvous performance of proposed sequence is much better than GOS algorithm and similar with JS algorithm. But when M is much smaller than p, the performance of proposed sequence is better than JS algorithm.

Classification of Tabular Data using High-Dimensional Mapping and Deep Learning Network (고차원 매핑기법과 딥러닝 네트워크를 통한 정형데이터의 분류)

  • Kyeong-Taek Kim;Won-Du Chang
    • Journal of Internet of Things and Convergence
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    • v.9 no.6
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    • pp.119-124
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    • 2023
  • Deep learning has recently demonstrated conspicuous efficacy across diverse domains than traditional machine learning techniques, as the most popular approach for pattern recognition. The classification problems for tabular data, however, are remain for the area of traditional machine learning. This paper introduces a novel network module designed to tabular data into high-dimensional tensors. The module is integrated into conventional deep learning networks and subsequently applied to the classification of structured data. The proposed method undergoes training and validation on four datasets, culminating in an average accuracy of 90.22%. Notably, this performance surpasses that of the contemporary deep learning model, TabNet, by 2.55%p. The proposed approach acquires significance by virtue of its capacity to harness diverse network architectures, renowned for their superior performance in the domain of computer vision, for the analysis of tabular data.

Artificial Neural Network with Firefly Algorithm-Based Collaborative Spectrum Sensing in Cognitive Radio Networks

  • Velmurugan., S;P. Ezhumalai;E.A. Mary Anita
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.7
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    • pp.1951-1975
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    • 2023
  • Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.

Electronic Word-of-Mouth in B2C Virtual Communities: An Empirical Study from CTrip.com (B2C허의사구중적전자구비(B2C虚拟社区中的电子口碑): 관우휴정려유망적실증연구(关于携程旅游网的实证研究))

  • Li, Guoxin;Elliot, Statia;Choi, Chris
    • Journal of Global Scholars of Marketing Science
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    • v.20 no.3
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    • pp.262-268
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    • 2010
  • Virtual communities (VCs) have developed rapidly, with more and more people participating in them to exchange information and opinions. A virtual community is a group of people who may or may not meet one another face to face, and who exchange words and ideas through the mediation of computer bulletin boards and networks. A business-to-consumer virtual community (B2CVC) is a commercial group that creates a trustworthy environment intended to motivate consumers to be more willing to buy from an online store. B2CVCs create a social atmosphere through information contribution such as recommendations, reviews, and ratings of buyers and sellers. Although the importance of B2CVCs has been recognized, few studies have been conducted to examine members' word-of-mouth behavior within these communities. This study proposes a model of involvement, statistics, trust, "stickiness," and word-of-mouth in a B2CVC and explores the relationships among these elements based on empirical data. The objectives are threefold: (i) to empirically test a B2CVC model that integrates measures of beliefs, attitudes, and behaviors; (ii) to better understand the nature of these relationships, specifically through word-of-mouth as a measure of revenue generation; and (iii) to better understand the role of stickiness of B2CVC in CRM marketing. The model incorporates three key elements concerning community members: (i) their beliefs, measured in terms of their involvement assessment; (ii) their attitudes, measured in terms of their satisfaction and trust; and, (iii) their behavior, measured in terms of site stickiness and their word-of-mouth. Involvement is considered the motivation for consumers to participate in a virtual community. For B2CVC members, information searching and posting have been proposed as the main purpose for their involvement. Satisfaction has been reviewed as an important indicator of a member's overall community evaluation, and conceptualized by different levels of member interactions with their VC. The formation and expansion of a VC depends on the willingness of members to share information and services. Researchers have found that trust is a core component facilitating the anonymous interaction in VCs and e-commerce, and therefore trust-building in VCs has been a common research topic. It is clear that the success of a B2CVC depends on the stickiness of its members to enhance purchasing potential. Opinions communicated and information exchanged between members may represent a type of written word-of-mouth. Therefore, word-of-mouth is one of the primary factors driving the diffusion of B2CVCs across the Internet. Figure 1 presents the research model and hypotheses. The model was tested through the implementation of an online survey of CTrip Travel VC members. A total of 243 collected questionnaires was reduced to 204 usable questionnaires through an empirical process of data cleaning. The study's hypotheses examined the extent to which involvement, satisfaction, and trust influence B2CVC stickiness and members' word-of-mouth. Structural Equation Modeling tested the hypotheses in the analysis, and the structural model fit indices were within accepted thresholds: ${\chi}^2^$/df was 2.76, NFI was .904, IFI was .931, CFI was .930, and RMSEA was .017. Results indicated that involvement has a significant influence on satisfaction (p<0.001, ${\beta}$=0.809). The proportion of variance in satisfaction explained by members' involvement was over half (adjusted $R^2$=0.654), reflecting a strong association. The effect of involvement on trust was also statistically significant (p<0.001, ${\beta}$=0.751), with 57 percent of the variance in trust explained by involvement (adjusted $R^2$=0.563). When the construct "stickiness" was treated as a dependent variable, the proportion of variance explained by the variables of trust and satisfaction was relatively low (adjusted $R^2$=0.331). Satisfaction did have a significant influence on stickiness, with ${\beta}$=0.514. However, unexpectedly, the influence of trust was not even significant (p=0.231, t=1.197), rejecting that proposed hypothesis. The importance of stickiness in the model was more significant because of its effect on e-WOM with ${\beta}$=0.920 (p<0.001). Here, the measures of Stickiness explain over eighty of the variance in e-WOM (Adjusted $R^2$=0.846). Overall, the results of the study supported the hypothesized relationships between members' involvement in a B2CVC and their satisfaction with and trust of it. However, trust, as a traditional measure in behavioral models, has no significant influence on stickiness in the B2CVC environment. This study contributes to the growing body of literature on B2CVCs, specifically addressing gaps in the academic research by integrating measures of beliefs, attitudes, and behaviors in one model. The results provide additional insights to behavioral factors in a B2CVC environment, helping to sort out relationships between traditional measures and relatively new measures. For practitioners, the identification of factors, such as member involvement, that strongly influence B2CVC member satisfaction can help focus technological resources in key areas. Global e-marketers can develop marketing strategies directly targeting B2CVC members. In the global tourism business, they can target Chinese members of a B2CVC by providing special discounts for active community members or developing early adopter programs to encourage stickiness in the community. Future studies are called for, and more sophisticated modeling, to expand the measurement of B2CVC member behavior and to conduct experiments across industries, communities, and cultures.

A CMOS Frequency divider for 2.4/5GHz WLAN Applications with a Simplified Structure

  • Yu, Q.;Liu, Y.;Yu, X.P.;Lim, W.M.;Yang, F.;Zhang, X.L.;Peng, Y.
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.11 no.4
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    • pp.329-335
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    • 2011
  • In this paper, a dual-band integer-N frequency divider is proposed for 2.4/5.2 GHz multi-standard wireless local area networks. It consists of a multi-modulus imbalance phase switching prescaler and two all-stage programmable counters. It is able to provide dual-band operation with high resolution while maintaining a low power consumption. This frequency divider is integrated with a 5 GHz VCO for multi-standard applications. Measurement results show that the VCO with frequency divider can work at 5.2 GHz with a total power consumption of 22 mW.

Sensor placement selection of SHM using tolerance domain and second order eigenvalue sensitivity

  • He, L.;Zhang, C.W.;Ou, J.P.
    • Smart Structures and Systems
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    • v.2 no.2
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    • pp.189-208
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    • 2006
  • Monitoring large-scale civil engineering structures such as offshore platforms and high-large buildings requires a large number of sensors of different types. Innovative sensor data information technologies are very extremely important for data transmission, storage and retrieval of large volume sensor data generated from large sensor networks. How to obtain the optimal sensor set and placement is more and more concerned by researchers in vibration-based SHM. In this paper, a method of determining the sensor location which aims to extract the dynamic parameter effectively is presented. The method selects the number and place of sensor being installed on or in structure by through the tolerance domain statistical inference algorithm combined with second order sensitivity technology. The method proposal first finds and determines the sub-set sensors from the theoretic measure point derived from analytical model by the statistical tolerance domain procedure under the principle of modal effective independence. The second step is to judge whether the sorted out measured point set has sensitive to the dynamic change of structure by utilizing second order characteristic value sensitivity analysis. A 76-high-building benchmark mode and an offshore platform structure sensor optimal selection are demonstrated and result shows that the method is available and feasible.

Joint Channel estimation in Asynchronous Amplify-And-Forward Relay Networks based on OFDM signaling (OFDM 신호를 이용한 비동기식 증폭 후 전달 중계망에서의 결합 채널 추정)

  • Yan, Yier;Jo, Gye-Mun;Balakannan, S.P.;Lee, Moon-Ho
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.46 no.1
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    • pp.55-62
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    • 2009
  • In this paper, we propose a method on the training sequence based on channel estimation issues for relay networks that employ amplify-and-forward(AF) transmission scheme. In $^{[1]}$ and $^{[2]}$, we have to point out that jointly estimating the channel from source to relay and from relay to destination suffers from many drawbacks in fast fading case because the estimation of previous pilots is not suitable for current channel. In this paper, we consider a new joint estimation of overall channel impulse response(CIR) using one OFDM signal without pilots. Using the maximum likelihood(ML) function, we derive a channel estimator by taking the frequency domain of transmitted signal as Gaussian and averaging the ML function over the resulting Gaussian distribution. Simulation results show that our proposed channel estimator performs a fraction of 1dB compared with $^{[1]}$ in high SNR region.

Impact of Social Support on Subjective Oral Health Status among Elderly People

  • Ahn, Eunsuk;Lee, Jin-Ha;Kim, Sun-Mi
    • Journal of dental hygiene science
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    • v.20 no.2
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    • pp.67-73
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    • 2020
  • Background: Owing to the increase in the aging population, the health problems of the elderly have become important social problems. Social support has a positive effect on improving the quality of life and prolonging the life of elderly people. It is one of the major factors that affects the oral health status of elderly people. The purpose of this study was to examine the relationship between oral health status and social support in elderly people using representative data. Methods: In this study, data from a community health survey in 2015 involving 63,929 elderly people aged over 65 years were analyzed. T-test and ANOVA analyses were performed to compare the general characteristics of and perception about social support. Additionally, a linear regression analysis was performed to confirm the relationship between perceptions about social support and subjective oral health status. Results: We found that sex, age, household income, education level, the presence of a spouse, existence of an unmet dental need, and regular oral check-up had a significant effect on subjective oral health status (p<0.05). In addition, when controlled for all factors, social support has a significant impact on subjective oral health status. Conclusion: The findings indicate that social support is associated with the subjective oral health status of Korean elderly. This suggests that community-level or government investment is required to improve the oral health of the elderly. In particular, policy interventions such as the establishment of facilities that promote social networks, especially facilities based on friendship networks, are needed.