• 한국멀티미디어학회논문지
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• 제24권5호
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• pp.667-675
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• 2021

The treatments for symptoms of Alzheimer's disease are being provided and for the early diagnosis several researches are undergoing. In this regard, by using T1-weighted images several classification techniques had been proposed to distinguish among AD, MCI, and Healthy Control (HC) patients. In this paper, we also used some traditional Machine Learning (ML) approaches in order to diagnose the AD. This paper consists of an improvised feature selection method which is used to reduce the model complexity which accounted an issue while utilizing the ML approaches. In our presented work, combination of subcortical and cortical features of 308 subjects of ADNI dataset has been used to diagnose AD using structural magnetic resonance (sMRI) images. Three classification experiments were performed: binary classification. i.e., AD vs eMCI, AD vs lMCI, and AD vs HC. Proposed Feature Selection method consist of a combination of Principal Component Analysis and Recursive Feature Elimination method that has been used to reduce the dimension size and selection of best features simultaneously. Experiment on the dataset demonstrated that SVM is best suited for the AD vs lMCI, AD vs HC, and AD vs eMCI classification with the accuracy of 95.83%, 97.83%, and 97.87% respectively.

• 스마트미디어저널
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• 제12권3호
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• pp.30-37
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• 2023

Alzheimer's disease (AD) symptoms are being treated by early diagnosis, where we can only slow the symptoms and research is still undergoing. In consideration, using T1-weighted images several classification models are proposed in Machine learning to identify AD. In this paper, we consider the improvised feature selection, to reduce the complexity by using wrapping techniques and Restricted Boltzmann Machine (RBM). This present work used the subcortical and cortical features of 278 subjects from the ADNI dataset to identify AD and sMRI. Multi-class classification is used for the experiment i.e., AD, EMCI, LMCI, HC. The proposed feature selection consists of Forward feature selection, Backward feature selection, and Combined PCA & RBM. Forward and backward feature selection methods use an iterative method starting being no features in the forward feature selection and backward feature selection with all features included in the technique. PCA is used to reduce the dimensions and RBM is used to select the best feature without interpreting the features. We have compared the three models with PCA to analysis. The following experiment shows that combined PCA &RBM, and backward feature selection give the best accuracy with respective classification model RF i.e., 88.65, 88.56% respectively.

• Genomics & Informatics
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• 제21권3호
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• pp.28.1-28.13
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• 2023

Mild cognitive impairment (MCI) is a clinical syndrome characterized by the onset and evolution of cognitive impairments, often considered a transitional stage to Alzheimer's disease (AD). The genetic traits of MCI patients who experience a rapid progression to AD can enhance early diagnosis capabilities and facilitate drug discovery for AD. While a genome-wide association study (GWAS) is a standard tool for identifying single nucleotide polymorphisms (SNPs) related to a disease, it fails to detect SNPs with small effect sizes due to stringent control for multiple testing. Additionally, the method does not consider the group structures of SNPs, such as genes or linkage disequilibrium blocks, which can provide valuable insights into the genetic architecture. To address the limitations, we propose a Bayesian bi-level variable selection method that detects SNPs associated with time of conversion from MCI to AD. Our approach integrates group inclusion indicators into an accelerated failure time model to identify important SNP groups. Additionally, we employ data augmentation techniques to impute censored time values using a predictive posterior. We adapt Dirichlet-Laplace shrinkage priors to incorporate the group structure for SNP-level variable selection. In the simulation study, our method outperformed other competing methods regarding variable selection. The analysis of Alzheimer's Disease Neuroimaging Initiative (ADNI) data revealed several genes directly or indirectly related to AD, whereas a classical GWAS did not identify any significant SNPs.

• Asian-Australasian Journal of Animal Sciences
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• 제18권8호
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• pp.1075-1079
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• 2005

The main objective of this study is to examine genetic changes in growth rate and carcass composition traits in group housed, ad libitum fed pigs, from lines of Large White divergently selected over four years for high and low post-weaning daily gain on a fixed but restricted ration. Genetic parameters for production and carcass traits were also estimated by using average information-restricted maximum likelihood applied to a multivariate individual animal model. All analyses were carried out on 1,728 records of group housed ad libitum fed pigs, and include a full pedigree of 5,324 animals. Estimates of heritability (standard errors in parentheses) were 0.11 (0.04) for lifetime daily liveweight gain (LDG), 0.13 (0.04) for daily carcass weight gain (CDG) and 0.28 (0.06) for carcass backfat (CFT). Genetic correlations between LDG and CDG were highly positive and between LDG and CFT negative, suggesting that selection for lifetime daily gain under commercial conditions of group housing with ad libitum feeding would result in favourable improvement in carcass traits. CFT showed negative genetic correlations with CDG. Correlated genetic responses evaluated as estimated breeding values (EBVs) were obtained from a multivariate animal model-best linear unbiased prediction analysis. After four years of divergent selection for 6 week post-weaning growth rate on restricted feeding, pigs performance tested on ad libitum feeding in groups exhibited changes in EBVs of 6.77 and -9.93 (g/d) for LDG, 4.25 and -7.08 (g/d) for CDG, and -1.42 and 1.55 (mm) for CFT, in the high and low lines, respectively. It is concluded that selection for growth rate on restricted feeding would significantly improve genetic performance and carcass composition of their descendants when group housed and ad libitum fed as is a common commercial practice.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권2호
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• pp.147-162
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• 2009

In this paper, we propose a Cooperative Transmission Strategy using Entropy-based Relay Selection in Mobile Ad-hoc Wireless Sensor Networks(MAWSN) with Rayleigh Fading Environments. The main features and contributions of the proposed cooperative transmission strategy are as follows. First, entropy-based relay selection is used to improve data transmission reliability from a source node to a destination node. Second, we present a theoretical analysis model for the proposed cooperative transmission strategy with the outage probability of the end-to-end performance. The performance of our protocol is evaluated using analysis and simulation.

• 마케팅과학연구
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• 제18권3호
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• pp.89-114
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• 2008

광고를 제작, 집행하는 과정에서 기업은 때로 본의 아니게 소비자에게 혼동을 야기 시켜 해당 제품이 무엇인지 잘 못 인지시키거나 제품 이미지를 잘 못 이해하게 하는 경우가 있다. 본 연구는 광고를 제작, 집행하는 과정에서 소비자가 특정 광고를 인지하고 이해하는 데 혼동을 일으키는 모든 제반 요소를 노이즈라고 정의하고 이 요인이 실재 존재하는 지, 또 광고 효과에 얼마나 영향을 미치는 지를 알아보고자 한다. 본 연구에서는 가능한 여러 형태의 광고 노이즈 현상 중 특히 한 모델이 동일 시점에서 여러 제품의 광고에 중복 출연함으로 인해 특정 광고에 대한 소비자 혼란을 야기시키는 광고 중복 출연에 따른 노이즈 현상과 한 제품의 광고에서 기용한 현재 광고모델이 과거 광고 모델과 다른 이미지를 가지고 있음으로 인해 해당 광고에 대한 소비자 혼란을 야기 시키는 모델 교체에 따른 광고 노이즈 현상을 연구 하고자 한다. 더 나아가 산업에서 많이 나타나고 있는 모델의 광고 중복 출연과 동일 제품에 대한 광고모델을 교체하는 것이 소비자 혼란을 일으킬 수 있고 소비자 혼란은 결국, 광고 효과에 부정적인 영향을 미칠 수 있다. 본 연구는 이와 더불어 여섯 가지 조절 변수를 찾아내어 광고 노이즈가 광고 효과에 미치는 부정적인 영향이 어느 경우에 더욱 커지거나 또는 감소하는 지를 알아보고자 하였다. 광고 중복 출연에 따른 노이즈가 광고 효과에 미치는 영향을 실증 분석한 결과를 해석하면 다음과 같이 정리할 수 있다. 첫째, 동시에 여러 광고에 출연하는 모델을 자사 브랜드광고에 기용하는 것은 브랜드 인지도와 브랜드 태도를 향상하는 데 모두 부정적인 역할을 한다. 둘째, 하지만, 광고 중복도가 높은 모델을 이용해야 한다면 특히 브랜드 인지도에 미치는 부정적인 영향을 줄이기 위해서 제품 이미지와 모델 이미지와의 적합성 정도가 높은 광고모델을 선정하는 것이 바람직하다. 셋째, 광고 중복도가 높은 모델을 이용할 경우, 자사 제품 광고에서 해당 모델이 유지해야 할 이미지가 해당 모델이 중복 출연한 광고 속에서 유지하는 이미지와 달리 하는 것이 자사 제품 인지도 향상에 도움이 되나 중요한 것은 자사 제품 태도 향상에는 효과 차이가 없다는 점이다. 넷째, 자사 모델이 중복 출연한 광고의 제품과 자사 제품이 유사할수록 모델의 광고 중복도는 브랜드 인지도와 브랜드 태도에 모두 부정적 영향을 미친다. 또한, 모델 교체로 인한 소비자 혼란이 광고 효과에 미치는 영향을 실증 분석한 결과를 해석하면 다음과 같다. 첫째, 한 제품의 광고에 여러 모델을 기용할수록 브랜드 인지도에 부정적 영향을 미치지만 브랜드 태도에는 오히려 긍정적 영향을 미치고 있었다. 둘째, 기존 광고 모델보다 현재 광고모델의 광고 적합성이 높으면 제품 광고의 모델 중복도가 브랜드에 미치는 부정적 영향은 약화되지만 브랜드 태도에 모델 중복도가 미치는 영향을 조절하지는 못했다. 셋째, 기존 모델과 현재 모델과의 이미지가 유사하면 모델 중복이 브랜드 인지도에 부정적인 영향을 미치지만 브랜드 태도에는 긍정적 영향을 미친다. 마지막으로 기존 광고와 현재 광고의 컨셉이 유사할 수록 제품 광고의 모델 중복도가 브랜드 인지도에 미치는 영향은 긍정적이었다. 특히, 본 연구에서 살펴본 두 가지 광고 노이즈 현상, 즉 동일 모델의 광고 중복출연이 모델 교체보다 광고 효과에 부정적인 영향을 미치는 경향이 있으며, 광고 노이즈 현상은 브랜드 태도보다는 브랜드 인지도 형성에 더 뚜렷한 영향을 미침을 알 수 있었다.

• 한국멀티미디어학회논문지
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• 제23권2호
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• pp.368-375
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• 2020

In this study, the area of interest(AOI) of Soju ad poster was tracked for analysis the time to frist fixation, the average of fixation duration and count by the study indexes. As a result of the analysis, Visual attention was higher the face than the body shape of the ad model. This means "when we look at printed ads, we see picture elements first, not language one" but language elements can't be overlooked either. Also, the importance of the model role could be verified by measuring the visual attention on the Soju ad poster. Based on the results of this study, if further research on ad posters is carried out and scientific and quantitative interpretation methods are presented, it can be used as product marketing data that can be reflected in ad model selection and poster design.

• 한국멀티미디어학회논문지
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• 제14권12호
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• pp.1559-1571
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• 2011

In wireless ad hoc networks, nodes communicate with each other using multihop routed transmission in which hop-by-hop cooperative diversity can be effectively employed. This paper proposes (i) two cooperation models for per-link cooperation (PLC) and per-node cooperation (PNC) for exploiting cooperative diversity in wireless ad hoc networks and (ii) a cooperative routing algorithm for the above models in which best relays are selected for cooperative transmission. First, two cooperation models for PLC and PNC are introduced and represented as an edge-weighted graph with effective link quality. Then, the proposed models are transformed into a simplified graph and a cooperative routing algorithm with O(n2) time is developed, where n is the number of nodes in the network. The effectiveness of the algorithm is confirmed for the two cooperation models using simulation.

• Journal of information and communication convergence engineering
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• 제19권3호
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• pp.136-141
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• 2021

Research on wireless sensor networks has focused on the monitoring and characterization of large-scale physical environments and the tracking of various environmental or physical conditions, such as temperature, pressure, and wind speed. We propose a stochastic mobility model that can be applied to a MANET (Mobile Ad-hoc NETwork). environment, and apply this mobility model to a newly proposed clustering-based routing protocol. To verify its stability and durability, we compared the proposed stochastic mobility model with a random model in terms of energy efficiency. The FND (First Node Dead) was measured and compared to verify the performance of the newly designed protocol. In this paper, we describe the proposed mobility model, quantify the changes to the mobile environment, and detail the selection of cluster heads and clusters formed using a fuzzy inference system. After the clusters are configured, the collected data are sent to a base station. Studies on clustering-based routing protocols and stochastic mobility models for MANET applications have shown that these strategies improve the energy efficiency of a network.

• 한국해양공학회지
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• 제22권3호
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• pp.64-70
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• 2008

A full-scale field experiment is an important part in the design of ships and offshore structures. Full-scale tests in the ice-covered sea, however, are usually very expensive and difficult tasks. Model tests in a refrigerated ice tank may substitute this difficulty of full-scale field tests. One of the major tasks to perform proper model tests in an ice towing tank is to select a realistic material for model ice which shows correct similitude with natural sea ice. This study focuses on the testing material properties and the selection of model ice material which will be used in an ice model basin. The first Korean ice model basin will be constructed at the Maritime & Ocean Engineering Research Institute (MOERI) in 2009. With an application to the MOERI ice model basin, in this study the material properties of EG/AD/S model ice of IOT (Institute for Ocean Technology) Canada, were tested. Through comprehensive bending tests, the elastic modulus and the flexural strength of EG/AD/S model ice were evaluated and the results were compared with published test results from Canada. Instead of using an ice model basin, a cold room facility was used for making a model ice specimen. Since the cold room adopts a different freezing procedure to make model ice, the strength of the model ice specimen differs from the published test results. The reason for this difference is discussed and the future development for a making model ice is recommended.