• 제목/요약/키워드: Vehicle components

검색결과 946건 처리시간 0.028초

Evaluation of Incident Detection Algorithms focused on APID, DES, DELOS and McMaster (돌발상황 검지알고리즘의 실증적 평가 (APID, DES, DELOS, McMaster를 중심으로))

  • Nam, Doo-Hee;Baek, Seung-Kirl;Kim, Sang-Gu
    • Journal of Korean Society of Transportation
    • /
    • 제22권7호
    • /
    • pp.119-129
    • /
    • 2004
  • This paper is designed to report the results of development and validation procedures in relation to the Freeway Incident Management System (FIMS) prototype development as part of Intelligent Transportation Systems Research and Development program. The central core of the FIMS is an integration of the component parts and the modular, but the integrated system for freeway management. The whole approach has been component-orientated, with a secondary emphasis being placed on the traffic characteristics at the sites. The first action taken during the development process was the selection of the required data for each components within the existing infrastructure of Korean freeway system. After through review and analysis of vehicle detection data, the pilot site led to the utilization of different technologies in relation to the specific needs and character of the implementation. This meant that the existing system was tested in a different configuration at different sections of freeway, thereby increasing the validity and scope of the overall findings. The incident detection module has been performed according to predefined system validation specifications. The system validation specifications have identified two component data collection and analysis patterns which were outlined in the validation specifications; the on-line and off-line testing procedural frameworks. The off-line testing was achieved using asynchronous analysis, commonly in conjunction with simulation of device input data to take full advantage of the opportunity to test and calibrate the incident detection algorithms focused on APID, DES, DELOS and McMaster. The simulation was done with the use of synchronous analysis, thereby providing a means for testing the incident detection module.

Characterization of Concentrations of Fine Particulate Matter in the Atmosphere of Pohang Area (포항지역 대기 중 초미세먼지(PM$_{2.5}$)의 오염특성평가)

  • Baek, Sung-Ok;Heo, Yoon-Kyeung;Park, Young-Hwa
    • Journal of Korean Society of Environmental Engineers
    • /
    • 제30권3호
    • /
    • pp.302-313
    • /
    • 2008
  • The purposes of this study are to investigate the concentration levels of fine particles, so called PM$_{2.5}$, to identify the affecting sources, and to estimate quantitatively the source contributions of PM$_{2.5}$. Ambient air sampling was seasonally carried out at two sites in Pohang(a residential and an industrial area) during the period of March to December 2003. PM$_{2.5}$ samples were collected by high volume air samplers with a PM$_{10}$ Inlet and an impactor for particle size segregation, and then determined by gravimetric method. The chemical species associated with PM$_{2.5}$ were analyzed by inductively coupled plasma spectrophotometery(ICP) and ion chromatography(IC). The results showed that the most significant season for PM$_{2.5}$ mass concentrations appeared to be spring, followed by winter, fall, and summer. The annual mean concentrations of PM$_{2.5}$ were 36.6 $\mu$g/m$^3$ in the industrial and 30.6 $\mu$g/m$^3$ in the residential area, respectively. The major components associated with PM$_{2.5}$ were the secondary aerosols such as nitrates and sulfates, which were respectively 4.2 and 8.6 $\mu$g/m$^3$ in the industrial area and 3.7 and 6.9 $\mu$g/m$^3$ in the residential area. The concentrations of chemical component in relation to natural emission sources such as Al, Ca, Mg, K were generally higher at both sampling sites than other sources. However, the concentrations of Fe, Mn, Cr in the industrial area were higher than those in the residential area. Based on the principal component analysis and stepwise multiple linear regression analysis for both areas, it was found that soil/road dust and secondary aerosols are the most significant factors affecting the variations of PM$_{2.5}$ in the ambient air of Pohang. The source apportionments of PM$_{2.5}$ were conducted by chemical mass balance(CMB) modeling. The contributions of PM$_{2.5}$ emission sources were estimated using the CMB8.0 receptor model, resulting that soil/road dust was the major contributor to PM$_{2.5}$, followed by secondary aerosols, vehicle emissions, marine aerosols, metallurgy industry. Finally, the application and its limitations of chemical mass balance modeling for PM$_{2.5}$ was discussed.

토양 및 지하수 Investigation 과 Remediation에 대한 현장적용

  • Wallner, Heinz
    • Proceedings of the Korean Society of Soil and Groundwater Environment Conference
    • /
    • 한국지하수토양환경학회 2000년도 추계학술대회
    • /
    • pp.44-63
    • /
    • 2000
  • Situated close to Heathrow Airport, and adjacent to the M4 and M25 Motorways, the site at Axis Park is considered a prime location for business in the UK. In consequnce two of the UK's major property development companies, MEPC and Redrew Homes sought the expertise of Intergeo to remediate the contaminated former industrial site prior to its development. Industrial use of the twenty-six hectare site, started in 1936, when Hawker Aircraft commence aircraft manufacture. In 1963 the Firestone Tyre and Rubber Company purchased part of the site. Ford commenced vehicle production at the site in the mid-1970's and production was continued by Iveco Ford from 1986 to the plant's decommissioning in 1997. Geologically the site is underlain by sand and gravel, deposited in prehistory by the River Thames, with London Clay at around 6m depth. The level of groundwater fluctuates seasonally at around 2.5m depth, moving slowly southwest towards local streams and watercourses. A phased investigation of the site was undertaken, which culminated in the extensive site investigation undertaken by Intergeo in 1998. In total 50 boreholes, 90 probeholes and 60 trial pits were used to investigate the site and around 4000 solid and 1300 liquid samples were tested in the laboratory for chemical substances. The investigations identified total petroleum hydrocarbons in the soil up to 25, 000mg/kg. Diesel oil, with some lubricating oil were the main components. Volatile organic compounds were identified in the groundwater in excess of 10mg/l. Specific substances included trichloromethane, trichloromethane and tetrachloroethene. Both the oil and volatile compounds were widely spread across the site, The specific substances identified could be traced back to industrial processes used at one or other dates in the sites history Slightly elevated levels of toxic metals and polycyclic aromatic hydrocarbons were also identified locally. Prior to remediation of the site and throughout its progress, extensive liaison with the regulatory authorities and the client's professional representatives was required. In addition to meetings, numerous technical documents detailing methods and health and safety issues were required in order to comply with UK environmental and safety legislation. After initially considering a range of options to undertake remediation, the following three main techniques were selected: ex-situ bioremediation of hydrocarbon contaminated soils, skimming of free floating hydrocarbon product from the water surface at wells and excavations and air stripping of volatile organic compounds from groundwater recovered from wells. The achievements were as follows: 1) 350, 000m3 of soil was excavated and 112, 000m3 of sand and gravel was processed to remove gravel and cobble sized particles; 2) 53, 000m3 of hydrocarbon contaminated soil was bioremediated in windrows ; 3) 7000m3 of groundwater was processed by skimming to remove free floating Product; 4) 196, 000m3 of groundwater was Processed by air stripping to remove volatile organic compounds. Only 1000m3 of soil left the site for disposal in licensed waste facilities Given the costs of disposal in the UK, the selected methods represented a considerable cost saving to the Clients. All other soil was engineered back into the ground to a precise geotechnical specification. The following objective levels were achieved across the site 1) By a Risk Based Corrective Action (RBCA) methodology it was demonstrated that soil with less that 1000mg/kg total petroleum hydrocarbons did not pose a hazard to health or water resources and therefore, could remain insitu; 2) Soils destined for the residential areas of the site were remediated to 250mg/kg total petroleum hydrocarbons; in the industrial areas 500mg/kg was proven acceptable. 3) Hydrocarbons in groundwater were remediated to below the Dutch Intervegtion Level of 0.6mg/1; 4) Volatile organic compounds/BTEX group substances were reduced to below the Dutch Intervention Levels; 5) Polycyclic aromatic hydrocarbons and metals were below Inter-departmental Committee for the Redevelopment of Contaminated Land guideline levels for intended enduse. In order to verify the qualify of the work 1500 chemical test results were submitted for the purpose of validation. Quality assurance checks were undertaken by independent consultants and at an independent laboratory selected by Intergeo. Long term monitoring of water quality was undertaken for a period of one year after remediation work had been completed. Both the regulatory authorities and Clients representatives endorsed the quality of remediation now completed at the site. Subsequent to completion of the remediation work Redrew Homes constructed a prestige housing development. The properties at "Belvedere Place" retailed at premium prices. On the MEPC site the Post Office, amongst others, has located a major sorting office for the London area. Exceptionally high standards of remediation, control and documentation were a requirement for the work undertaken here.aken here.

  • PDF

Beneficial Effect of Korea Red Ginseng on Halitosis; Attenuation of H2S Induced Inflammatory Mediators and cystathionine γ-lyase Expression (고려홍삼의 구강악취 억제기능; H2S 생성에 따른 염증매개 유전자 및 cystathionine γ-lyase의 약화기능)

  • Choi, Ki-Seok;Lee, So-Jung;Lee, Jeong-Sang;Hong, Kyung-Sook;Kim, Jeong-Gon;Kim, Yoon-Jae;Hahm, Ki-Baik
    • Journal of Ginseng Research
    • /
    • 제33권4호
    • /
    • pp.367-377
    • /
    • 2009
  • Halitosis is a generally accepted marker of diseases in the oral cavity and of systemic and gastrointestinal disorders. Based on these authors' previous findings (that (1) there is a close association between H. pylori infection and halitosis; (2) Korea red ginseng may suppress the colonization of H. pylori, fight H. pylori-induced cytotoxicity, and impose significant anti-inflammatory actions in patients with chronic gastritis; and (3) H. pylori infection is linked with the generation of significant levels of volatile sulfur compounds (VSCs), and the levels of VSCs correlate significantly with H. pylori-associated mucosal damages), in the current study, the authors documented the molecular mechanisms of Korea red ginseng's efficacy in ameliorating halitosis. When the RAW 264.7 cells were treated with the $H_2S$ releasing compound NaHS, the mRNA expression of cystathionine ${\gamma}$-lyase (CSE), IL-6, COX-2, and iNOS were more significantly induced compared with the vehicle-treated group. The cytoskeletal components of ezrin's and moesin's mRNA expressions were elevated by NaHS treatment accompanied by the activation of MAPK, p38, and ERK. Korea red ginseng pretreatment reduced both the NaHS-induced CSE expression and the proinflammatory genes (e.g., IL-6, COX-2, and iNOS) in a concentration-dependent manner. The ERM expression and the phosphorylation of p38 were also significantly reduced by Korea-red-ginseng pretreatment. Overall, Korea red ginseng pretreatment imposed significant anti-inflammatory effects through the downregulation of the NaHS-triggered proinflammatory gene expression, CSE, and ERM mRNA expression. Korea red ginseng could thus be said to be a key remedy of halitosis and to be effective in relieving gastric inflammation.

Development of deep learning network based low-quality image enhancement techniques for improving foreign object detection performance (이물 객체 탐지 성능 개선을 위한 딥러닝 네트워크 기반 저품질 영상 개선 기법 개발)

  • Ki-Yeol Eom;Byeong-Seok Min
    • Journal of Internet Computing and Services
    • /
    • 제25권1호
    • /
    • pp.99-107
    • /
    • 2024
  • Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

An Intelligence Support System Research on KTX Rolling Stock Failure Using Case-based Reasoning and Text Mining (사례기반추론과 텍스트마이닝 기법을 활용한 KTX 차량고장 지능형 조치지원시스템 연구)

  • Lee, Hyung Il;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
    • /
    • 제26권1호
    • /
    • pp.47-73
    • /
    • 2020
  • KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.