• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2022.06a
• /
• pp.54-57
• /
• 2022

본 논문에서는 심층 신경망 기반 점진적 다계층 오디오 코덱의 비트 전송률 효율 향상을 위한 엔트로피 모델 기반 양자화 방식을 제안한다. 최근 심층 신경망을 이용하여 전통적인 신호 처리 이론 기반의 상용 오디오 코덱들을 대체하기 위한 오디오 압축 및 복원 시스템에 관한 연구가 활발하게 이루어지고 있다. 그러나 아직은 기존 상용 코덱의 성능에 도달하지 못하고 있으며 특히 종단 간 오디오 압축 모델의 경우, 적은 정보량으로 높은 품질을 얻기 위해서는 부호화기의 양자화 구조를 개선하는 것이 필수적이다. 본 연구에서는 기존에 제안된 종단 간 오디오 압축 모델 중 하나인 점진적 다계층 오디오 코덱의 벡터 양자화기를 엔트로피 모델 기반 양자화기로 대체하고 전송률-왜곡 트레이드오프 관계를 활용하여 전송률을 다양한 형태로 조절할 수 있음을 보임으로써 엔트로피 모델 기반 양자화기 도입의 타당성을 검증한다.

• Ecology and Resilient Infrastructure
• /
• v.3 no.3
• /
• pp.189-200
• /
• 2016

The species distribution model would be a useful tool for understanding how invasive alien species spread over the country and what environmental variables contribute to their distributions. This study is focused on the potential distribution of two invasive alien species, the common ragweed (Ambrosia artemisiifolia) and knotgrass (Paspalum distichum) in the Korean Peninsula. The maximum entropy (Maxent) model was used for the prediction of their distribution by inferring their climatic environmental requirements from localities where they are currently known to occur. We obtained their presence data from the Global Biodiversity Information Facility and the Korean plant species databases and bioclimatic data from the WorldClim dataset. As a results of the modelling, the potential distribution predicted by global occurrence data was more accurate than that by native occurrence data. The variables determining the common ragweed distribution were precipitation of the driest month and annual mean temperature. Both annual and the coldest quarter mean temperatures were critical factors in determining the knotgrass distribution. The Maxent model could be a useful tool for the prediction of alien species invasion and the management of their expansion.

• Journal of Environmental Impact Assessment
• /
• v.25 no.6
• /
• pp.432-441
• /
• 2016

In this study, we predicted species distributions in Mt. Inwang and Mt. An as preceding research to build ecological corridor by considering connectivity of habitats which have been fragmented in the city. We analyzed species distributions by using Maxent (Maximum Entropy Approach) model with species presence. We used 23 points of mammals and 15 points of Titmouse (Parus major, P. palustris, P. varius) as target species from appearance points of species examined. We build 4 geography factors, 4 vegetation factors, and 2 distance factors as model variables In case of mammals, factors that affected species distribution model was Digital Elevation Model(DEM, 34%) followed by Distance from edge forest to interior (24.8%) and Species of tree (10%). On the other hand, in case of Parus species, factors that affected species distribution model were DEM (39.6%) followed by distance from road (35.4%) and Density-class (8.2%). Therefore, birds and mammals prefer interior of mountain, and this area needs to be protected.

• Korean Chemical Engineering Research
• /
• v.58 no.2
• /
• pp.197-208
• /
• 2020

This study was carried out to analyze spatial and temporal incidence characteristics of scrub typhus and predict the future incidence of scrub typhus since the incidences of scrub typhus have been rapidly increased among vector-borne diseases. A maximum entropy (MaxEnt) ecological model was implemented to predict spatial distribution and incidence rate of scrub typhus using spatial data sets on environmental and social variables. Additionally, relationships between the incidence of scrub typhus and critical spatial data were analyzed. Elevation and temperature were analyzed as dominant spatial factors which influenced the growth environment of Leptotrombidium scutellare (L. scutellare) which is the primary vector of scrub typhus. A temporal number of diseases by scrub typhus was predicted by a deep neural network (DNN). The model considered the time-lagged effect of scrub typhus. The DNN-based prediction model showed that temperature, precipitation, and humidity in summer had significant influence factors on the activity of L. scutellare and the number of diseases at fall. Moreover, the DNN-based prediction model had superior performance compared to a conventional statistical prediction model. Finally, the spatial and temporal models were used under climate change scenario. The future characteristics of scrub typhus showed that the maximum incidence rate would increase by 8%, areas of the high potential of incidence rate would increase by 9%, and disease occurrence duration would expand by 2 months. The results would contribute to the disease management and prediction for the health of residents in terms of public health.

• Bulletin of the Korean Chemical Society
• /
• v.34 no.9
• /
• pp.2753-2759
• /
• 2013

The aim of the present study is to explore the possibility of utilizing fly ash and loess, as alternative to activated carbon, for the adsorption of diazinon in water. Batch adsorption experiment was performed to evaluate the influences of various factors like initial concentration, contact time and temperature on the adsorption of diazinon. The adsorption data shows that fly ash is not effective for the adsorption of diazinon. The equilibrium data for both activated carbon and loess were fitted well to the Freundlich isotherm model. The pseudo-second-order kinetic model appeared to be the better-fitting model because it has higher $R^2$ compared to the pseudo-first-order kinetic model. The thermodynamic parameters such as free energy (${\Delta}G$), the enthalpy (${\Delta}H$) and the entropy (${\Delta}S$) were calculated. Contrary to loess, the ${\Delta}G$ values of activated carbon were negative at the studied temperatures. It indicates that the adsorption of diazinon by activated carbon is a favorable and spontaneous process. The positive ${\Delta}H$ values of activated carbon and loess suggest that the diazinon adsorption process is endothermic in nature. In addition, the positive ${\Delta}S$ values show that increased randomness occurs at the solid/solution surface during the adsorption of diazinon.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.31 no.1 s.256
• /
• pp.55-61
• /
• 2007

Recently simulation model becomes an essential tool for analysis and design of a system but it is often expensive and time consuming as it becomes complicate to achieve reliable results. Therefore, high-fidelity simulation model needs to be replaced by an approximate model, the so-called metamodel. Metamodeling techniques include 3 components of sampling, metamodel and validation. Cross-validation approach has been proposed to provide sequnatially new sample point based on cross-validation error but it is very expensive because cross-validation must be evaluated at each stage. To enhance the cross-validation of metamodel, sequential sampling method using candidate points and representative cross-validation is proposed in this paper. The candidate and representative cross-validation approach of sequential sampling is illustrated for two-dimensional domain. To verify the performance of the suggested sampling technique, we compare the accuracy of the metamodels for various mathematical functions with that obtained by conventional sequential sampling strategies such as maximum distance, mean squared error, and maximum entropy sequential samplings. Through this research we team that the proposed approach is computationally inexpensive and provides good prediction performance.

• ETRI Journal
• /
• v.42 no.2
• /
• pp.258-271
• /
• 2020

A correlation exists between luminance samples and chrominance samples of a color image. It is beneficial to exploit such interchannel redundancy for color image compression. We propose an algorithm that predicts chrominance components Cb and Cr from the luminance component Y. The prediction model is trained by supervised learning with Laplacian-regularized least squares to minimize the total prediction error. Kernel principal component analysis mapping, which reduces computational complexity, is implemented on the same point set at both the encoder and decoder to ensure that predictions are identical at both the ends without signaling extra location information. In addition, chrominance subsampling and entropy coding for model parameters are adopted to further reduce the bit rate. Finally, luminance information and model parameters are stored for image reconstruction. Experimental results show the performance superiority of the proposed algorithm over its predecessor and JPEG, and even over JPEG-XR. The compensation version with the chrominance difference of the proposed algorithm performs close to and even better than JPEG2000 in some cases.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.4
• /
• pp.1866-1883
• /
• 2019

As the youngest branch of information hiding, network covert timing channels conceal the existence of secret messages by manipulating the timing information of the overt traffic. The popular model-based framework for constructing covert timing channels always utilizes cumulative distribution function (CDF) of the inter-packet delays (IPDs) to modulate secret messages, whereas discards high-order statistics of the IPDs completely. The consequence is the vulnerability to high-order statistical tests, e.g., entropy test. In this study, a rich security model of covert timing channels is established based on IPD chains, which can be used to measure the distortion of multi-order timing statistics of a covert timing channel. To achieve rich security, we propose two types of covert timing channels based on nested lattices. The CDF of the IPDs is used to construct dot-lattice and interval-lattice for quantization, which can ensure the cell density of the lattice consistent with the joint distribution of the IPDs. Furthermore, compensative quantization and guard band strategy are employed to eliminate the regularity and enhance the robustness, respectively. Experimental results on real traffic show that the proposed schemes are rich-secure, and robust to channel interference, whereas some state-of-the-art covert timing channels cannot evade detection under the rich security model.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.9
• /
• pp.4665-4683
• /
• 2019

Previous methods build image annotation model by leveraging three basic dependencies: relations between image and label (image/label), between images (image/image) and between labels (label/label). Even though plenty of researches show that multiple dependencies can work jointly to improve annotation performance, different dependencies actually do not "work jointly" in their diagram, whose performance is largely depending on the result predicted by image/label section. To address this problem, we propose the adaptive attention annotation model (AAAM) to associate these dependencies with the prediction path, which is composed of a series of labels (tags) in the order they are detected. In particular, we optimize the prediction path by detecting the relevant labels from the easy-to-detect to the hard-to-detect, which are found using Binary Cross-Entropy (BCE) and Triplet Margin (TM) losses, respectively. Besides, in order to capture the inforamtion of each label, instead of explicitly extracting regional featutres, we propose the self-attention machanism to implicitly enhance the relevant region and restrain those irrelevant. To validate the effective of the model, we conduct experiments on three well-known public datasets, COCO 2014, IAPR TC-12 and NUSWIDE, and achieve better performance than the state-of-the-art methods.

• Korean Chemical Engineering Research
• /
• v.58 no.3
• /
• pp.458-465
• /
• 2020

Isotherms, kinetics and thermodynamic properties for adsorption of acid fuchsin (AF) dye by activated carbon were carried out using variables such as dose of adsorbent, pH, initial concentration and contact time and temperature. The effect of pH on adsorption of AF showed a bathtub with high adsorption percentage in acidic (pH 8). Isothermal adsorption data were fitted to the Freundlich, Langmuir, and Dubinin-Radushkevich isotherm models. Freundlich isothem model showed the highest agreement and confirmed that the adsorption mechanism was multilayer adsorption. It was found that adsorption capacity increased with increasing temperature. Freundlich's separation factor showed that this adsorption process was an favorable treatment process. Estimated adsorption energy by Dubinin-Radushkevich isotherm model indicated that the adsorption of AF by activated carbon is a physical adsorption. Adsorption kinetics was found to follow the pseudo-second-order kinetic model. Surface diffusion at adsorption site was evaluated as a rate controlling step by the intraparticle diffusion model. Thermodynamic parameters such as activation energy, Gibbs free energy, enthalpy entropy and isosteric heat of adsorption were investigated. The activation energy and enthalpy change of the adsorption process were 21.19 kJ / mol and 23.05 kJ / mol, respectively. Gibbs free energy was found that the adsorption reaction became more spontaneously with increasing temperature. Positive entropy was indicated that this process was irreversible. The isosteric heat of adsorption was indicated physical adsorption in nature.