Woo-Il Kim

Emission of polybrominated diphenyl ethers (PBDEs) in use of electric/electronic equipment and recycling of e-waste in Korea.

The emission rates of polybrominated diphenyl ethers (PBDEs) from electric/electronic products during their use and disposal were estimated. E-wastes, including televisions and refrigerators, gathered at recycling centers were also analyzed to estimate their emissions. The average concentrations of PBDEs in TV rear covers produced before and after the year 2000 were 145,027 mg/kg and 14,049 mg/kg, respectively. The PBDEs concentration in TV front covers was lower than the concentration in TV rear covers. The concentration in the components of the refrigerator samples ranged from ND to 445 mg/kg. We estimated the atmospheric emissions of PBDEs based on the concentrations. The annual emissions from TV rear covers produced before 2000 were calculated to be approximately 162.1 kg and after 2000, the annual emissions were 18.7 kg. Refrigerators showed the lowest annual emissions of PBDEs (0.7 kg). The atmospheric concentrations were also measured to calculate emissions generated during the recycling process. The highest concentration was 16.86 ng/m(3) emitted from the TV sets during the dismantling process. The concentrations of PBDEs generated in the plastic processing field ranged from 2.05 to 5.43 ng/m(3) depending on the products, and ambient air in open-air yards showed concentrations in the range of 0.32 to 5.55 ng/m(3). Emission factors for the recycling process were calculated using the observed concentrations. The estimated emissions according to the emission factors ranged from 0.3×10(-1) to 90.3 kg/year for open-air yards and from 0.1×10(-1) to 292.7 kg/year for the dismantling and crushing processes of TV set, depending on the production year.

Static and dynamic flow analysis of PBDEs in plastics from used and end-of-life TVs and computer monitors by life cycle in Korea

This study focused on a quantitative substance flow analysis (SFA) of polybrominated diphenyl ethers (PBDEs) in plastics from obsolete TVs and computer monitors that often contain large amounts of the flame retardants. According to the results of the static SFA study, 1.87 tons and 0.28 tons of PBDEs from newly manufactured TVs and computer monitors were introduced into households in 2011 in Korea, respectively. There were approximately 924 tons and 90.3 tons of PBDEs present in TVs and computer monitors in households during product use, respectively. The results of the dynamic SFA study indicated that in 2017 the amount of PBDEs from TVs and computer monitors in the recycling stage is expected to be 2.63 tons and 0.1 tons, respectively. Large fractions of PBDEs from used TVs are present in recycled plastics, while PBDE-containing computer monitors are exported to Southeast Asian countries. This research indicates that PBDEs were emitted the most from recycled plastic pellet processes upon recycling. Further study may be warranted to focus the flow of PBDEs in recycled plastic products in order to determine the final destination and disposal of these chemicals in the environment.

Deep Neural Network based learning and transferring mid-level audio features for acoustic scene classification

Deep Neural Network (DNN) based transfer learning has been shown to be effective in Visual Object Classification (VOC) for complementing the deficit of target domain training samples by adapting classifiers that have been pre-trained for other large-scaled DataBase (DB). Although there exists an abundance of acoustic data, it can also be said that datasets of specific acoustic scenes are sparse for training Acoustic Scene Classification (ASC) models. By exploiting VOC DNNs ability of learning beyond its pre-trained environments, this paper proposes DNN based transfer learning for ASC. Effectiveness of the proposed method is demonstrated on the database of IEEE DCASE Challenge 2016 Task 1 and home surveillance environment via representative experiments. Its improved performance is verified by comparing it to prominent conventional methods.

Deep neural network bottleneck features for acoustic event recognition

Bottleneck features have been shown to be effective in improving the accuracy of speaker recognition, language identification and automatic speech recognition. However, few works have focused on bottleneck features for acoustic event recognition. This paper proposes a novel acoustic event recognition framework using bottleneck features derived from a Deep Neural Network (DNN). In addition to conventional features (MFCC, Mel-spectrum, etc.), this paper employs rhythm, timbre, and spectrum-statistics features for effectively extracting acoustic characteristics from audio signals. The effectiveness of the proposed method is demonstrated on a database of real life recordings via experiments, and its robust performance is verified by comparing to conventional methods.

Voice Activity Detection in Noisy Environments Based on Double-Combined Fourier Transform and Line Fitting

A new voice activity detector for noisy environments is proposed. In conventional algorithms, the endpoint of speech is found by applying an edge detection filter that finds the abrupt changing point in a feature domain. However, since the frame energy feature is unstable in noisy environments, it is difficult to accurately find the endpoint of speech. Therefore, a novel feature extraction algorithm based on the double-combined Fourier transform and envelope line fitting is proposed. It is combined with an edge detection filter for effective detection of endpoints. Effectiveness of the proposed algorithm is evaluated and compared to other VAD algorithms using two different databases, which are AURORA 2.0 database and SITEC database. Experimental results show that the proposed algorithm performs well under a variety of noisy conditions.

Robust speaker direction estimation with microphone array using NMF for smart TV interaction

This paper proposes a robust speaker direction estimation method based on a microphone array for voice based interaction with smart TV. The proposed method uses speech basis and associated weights of non-negative matrix factorization for finding the speaker independent utterance direction from input signal with noise. The experimental results of the speaker direction estimation in real acoustic environment validate the effectiveness of the proposed algorithm in terms of representative performance measures compared to the conventional methods.

Generalized cross-correlation based noise robust abnormal acoustic event localization utilizing non-negative matrix factorization

In this paper, robust sound source localization for surveillance system is presented. In particular, we propose an algorithm for abnormal acoustic event localization using non-negative matrix factorization based frequency bin weighting. Based on the abnormal acoustic event localization experiments in real acoustic environment, the proposed algorithms excellent strength is validated in terms of representative performance measures compared to the conventional method.

Analytical method for combustible waste contaminated by the HF leakage from industrial process

Abstract: Hydrofluoric acid (HF), a typical inorganic acid, has been used in the industry for its various usageand classified as the toxic compound, because it can cause the pneumonia and pulmonary edema when it wasexposed to respiratory organs. The official environmental analytical method for fluorine and its compound inwaste has not been developed. For this reason, we have faced some problem to treat the contaminated wastesby the HF leakage from industrial process. In this study, prepared for analytical method for combustible waste(crop, trees, etc.) generated from HF leaking accident and to be applied as the official analytical method forfluorine contaminated waste when the fluorine and its compound will be regulated as a hazardous materialby the waste management law later.요약: 불화수소는 유리의 식각, 금속의 녹 제거 등 산업계에서 많이 사용되는 대표적인 무기산이며 노출 시 눈, 코, 목안을 강하게 자극하고, 흡입 시 폐렴, 폐수종 기관지염을 일으키는 대표적인 유독물질에해당하는 화학물질로 구분되어 있다. 현행 폐기물공정시험기준에는 불소화합물에 대한 함량분석방법이마련되어 있지 않아 최근 발생된 불화수소 누출사고로 발생된 불산에 오염된 농작물, 수목 등 가연성 폐기물의 신속하고 안전한 처리방법 마련에 어려움을 겪었다. 본 연구에서는 불화수소 누출사고로 발생된가연성 폐기물(농작물, 수목 등) 중 불소 및 불소화합물의 함량분석방법 마련을 통해 폐기물의 불산 오염여부를 판단하고 적절한 폐기물 처리방법을 제시하고, 향후 이 방법을 폐기물 관리법상에 지정폐기물에 함유된 유해물질로 불소 및 불소화합물에 대한 항목 추가 시 폐기물공정시험기준으로 활용하고자 한다.Key words: Hydrofluoric acid (HF), leaking accident, combustible waste, analytical method

An advanced feature compensation method employing acoustic model with phonetically constrained structure

This study proposes an effective model-based feature compensation method for robust speech recognition in background noise conditions. In the proposed scheme, an acoustic model with a phonetically constrained structure is employed for the Parallel Combined Gaussian Mixture Model (PCGMM [1]) based feature compensation method. The structure of the acoustic model includes a collection of context independent phone models. A phonetically constrained prior probability is formulated by integrating transition probability of phone models into the reconstruction procedure. Experimental results show that the PCGMM-based feature compensation employing the proposed phonetically constrained structure of acoustic model consistently outperforms the case of employing the conventional Gaussian mixture model. This demonstrates that the proposed configuration of the acoustic model is effective at improving the intelligibility of the speech reconstructed by the feature compensation method for speech recognition under diverse background noise conditions.

Content characteristics of persistent organic pollutants waste from paint, iron making and steel making process

This study has been carried out in order to effectively manage three groups of unregulated hazardous organic substances (PCDD/DFs, PAHs, PCBs) in South Korea. The investigated substances have been analyzed according to the test methods for hazardous substances in specified wastes provided by the National Institute of Environmental Research, Korea. Total contents of the organic compounds have been determined for hazardous wastes from three major industrial categories (paint, iron removal, steelmaking), such as waste organic solvent, waste paint or dust. By investigating the waste samples for 7 PAHs using GC/MSD, Naphthalene has been detected (N.D~1631.33 mg/kg). The highest Naphthalene concentration, which exceeded the korean marine dumping waste standard, was found in waste organic solvents and waste paints. Although a content analysis of 7 PCB isomers has been conducted, none of these compounds was detected. The analysis of PCDD/DFs has revealed that all samples meet the criterion for low POP content defined in the technical guidelines developed under the Basel Convention. The PCDD/DFs content in dust samples deriving from 10 manufacturing processes (billet, bloom) was determined to be in the range of N.D~5.66 ng I-TEQ/g waste.