• Title, Summary, Keyword: Network structure

Search Result 4,540, Processing Time 0.067 seconds

A Comparative Study about Industrial Structure Feature between TL Carriers and LTL Carriers (구역화물운송업과 노선화물운송업의 산업구조 특성 비교)

  • 민승기
    • Journal of Korean Society of Transportation
    • /
    • v.19 no.1
    • /
    • pp.101-114
    • /
    • 2001
  • Transportation enterprises should maintain constant and qualitative operation. Thus, in short period, transportation enterprises don't change supply in accordance with demand. In the result, transportation enterprises don't reduce operation in spite of management deficit at will. In freight transportation type, less-than-truckload(LTL) has more relation with above transportation feature than truckload(TL) does. Because freight transportation supply of TL is more flexible than that of LTL in correspondence of freight transportation demand. Relating to above mention, it appears that shortage of road and freight terminal of LTL is larger than that of TL. Especially in road and freight terminal comparison, shortage of freight terminal is larger than that of road. Shortage of road is the largest in 1990, and improved after-ward. But shortage of freight terminal is serious lately. So freight terminal needs more expansion than road, and shows better investment condition than road. Freight terminal expansion brings road expansion in LTL, on the contrary, freight terminal expansion substitutes freight terminal for road in TL. In transportation revenue, freight terminal's contribution to LTL is larger than that to TL. However, when we adjust quasi-fixed factor - road and freight terminal - to optimal level in the long run, in TL, diseconomies of scale becomes large, but in LTL, economies of scale becomes large. Consequently, it is necessary for TL to make counterplans to activate management of small size enterprises and owner drivers. And LTL should make use of economies of scale by solving the problem, such as nonprofit route, excess of rental freight handling of office, insufficiency of freight terminal, shortage of driver, and unpreparedness of freight insurance.

  • PDF

Traffic Forecasting Model Selection of Artificial Neural Network Using Akaike's Information Criterion (AIC(AKaike's Information Criterion)을 이용한 교통량 예측 모형)

  • Kang, Weon-Eui;Baik, Nam-Cheol;Yoon, Hye-Kyung
    • Journal of Korean Society of Transportation
    • /
    • v.22 no.7
    • /
    • pp.155-159
    • /
    • 2004
  • Recently, there are many trials about Artificial neural networks : ANNs structure and studying method of researches for forecasting traffic volume. ANNs have a powerful capabilities of recognizing pattern with a flexible non-linear model. However, ANNs have some overfitting problems in dealing with a lot of parameters because of its non-linear problems. This research deals with the application of a variety of model selection criterion for cancellation of the overfitting problems. Especially, this aims at analyzing which the selecting model cancels the overfitting problems and guarantees the transferability from time measure. Results in this study are as follow. First, the model which is selecting in sample does not guarantees the best capabilities of out-of-sample. So to speak, the best model in sample is no relationship with the capabilities of out-of-sample like many existing researches. Second, in stability of model selecting criterion, AIC3, AICC, BIC are available but AIC4 has a large variation comparing with the best model. In time-series analysis and forecasting, we need more quantitable data analysis and another time-series analysis because uncertainty of a model can have an effect on correlation between in-sample and out-of-sample.

Evaluation on Removal Efficiency of Methylene Blue Using Nano-ZnO/Laponite/PVA Photocatalyzed Adsorption Ball (Nano-ZnO/Laponite/PVA 광촉매 흡착볼의 메틸렌블루 제거효율 평가)

  • Oh, Ju Hyun;Ahn, Hosang;Jang, Dae Gyu;Ahn, Chang Hyuk;Lee, Saeromi;Joo, Jin Chul
    • Journal of Korean Society of Environmental Engineers
    • /
    • v.35 no.9
    • /
    • pp.636-642
    • /
    • 2013
  • In order to overcome drawbacks (i.e., filtration and recovery) of conventional powder type photocatalysts, nano-ZnO/Laponite/PVA (ZLP) photocatalyzed adsorption balls were developed by using in situ mixing of nanoscale ZnO as a photocatalyst, and Laponite as both adsorbent and supporting media in deionized water, followed by the poly vinyl alcohol polymerization with boric acid. The optimum mixing ratio of nano-ZnO:Laponite:PVA:deionized water was found to be 3:1:1:16 (by weight), and the mesh and film produced by PVA polymerization with boric acid might inhibit both swelling of Laponite and detachment of nanoscale ZnO from ZLP balls. Drying ZLP balls with microwave (600 watt) was found to produce ZLP balls with stable structure in water, and various sizes (55~500 ${\mu}m$) of pore were found to be distributed based on SEM and TEM results. In the initial period of reaction (i. e., 40 min), adsorption through ionic interaction between methylene blue and Laponite was the main removal mechanism. After the saturation of methylene blue to available adsorption sites for Laponite, the photocatalytic degradation of methylene blue occurred. The effective removal of methylene blue was attributed to adsorption and photocatalytic degradation. Based on the results from this study, synthesized ZLP photocatalyzed adsorption balls were expected to remove recalcitrant organic compounds effectively through both adsorption and photocatalytic degradation, and the risks of environmental receptors caused by detachment of nanoscale photocatalysts can be reduced.

Effect of Heat Treatment Conditions on the Characteristics of Gel Made from Arrowroot Starch in Korea Cultivars (국내산 칡 전분 젤 특성에 미치는 가열처리 조건의 영향)

  • Lee, Seog-Won;Kim, Hyo-Won;Han, Sung-Hee;Rhee, Chul
    • The Korean Journal of Food And Nutrition
    • /
    • v.22 no.3
    • /
    • pp.387-395
    • /
    • 2009
  • This study was conducted to investigate the effects of starch concentrations and heating conditions on the gel characteristics of arrowroot starch. Arrowroot starch gels with various pHs, and starch concentrations, were prepared using different temperatures and heating times, and then stored for 24 hrs at $4^{\circ}C$. The hardness of sample gels made at pH 2.0 and 4.0 increased as the starch concentration increased from 7% to 10%, with the maximum value of 94 N being obtained when the gel was prepared at pH 4.0 with a starch concentration of 10%. The maximum hardness of samples prepared with concentrations of starch ranging from 7~9% appeared at $80^{\circ}C$, regardless of the heating temperature and time. Furthermore, the hardness of samples prepared at greater than $100^{\circ}C$ was relatively lower than that of samples prepared at other temperatures. When a starch concentration of 8% was used, the degree of gelatinization(DR) increased as the heating temperature increased, with the maximum value of DR being about 76% at $120^{\circ}C$, regardless of heating time. After storage for 24 hrs, the hardness of samples prepared at $70^{\circ}C$, $80^{\circ}C$ and $90^{\circ}C$ appeared to decrease, while that of samples prepared at $100^{\circ}C$, $110^{\circ}C$ and $120^{\circ}C$ increased. The correlation between hardness and the degree of gelatinization or retrogradation was very high when samples were prepared at $80^{\circ}C$ with a starch concentration of 9%, as indicated by a correlation coefficient of greater than 0.95. Overall, the microstructures of freeze-dried arrowroot starch gel were composed of a continuous network of amylose and amylopectin with fragmented ghost structures in an excluded phase, but these ghost structures were more evident after storage and with increased heating temperature.

A Study on Speech Recognition Using the HM-Net Topology Design Algorithm Based on Decision Tree State-clustering (결정트리 상태 클러스터링에 의한 HM-Net 구조결정 알고리즘을 이용한 음성인식에 관한 연구)

  • 정현열;정호열;오세진;황철준;김범국
    • The Journal of the Acoustical Society of Korea
    • /
    • v.21 no.2
    • /
    • pp.199-210
    • /
    • 2002
  • In this paper, we carried out the study on speech recognition using the KM-Net topology design algorithm based on decision tree state-clustering to improve the performance of acoustic models in speech recognition. The Korean has many allophonic and grammatical rules compared to other languages, so we investigate the allophonic variations, which defined the Korean phonetics, and construct the phoneme question set for phonetic decision tree. The basic idea of the HM-Net topology design algorithm is that it has the basic structure of SSS (Successive State Splitting) algorithm and split again the states of the context-dependent acoustic models pre-constructed. That is, it have generated. the phonetic decision tree using the phoneme question sets each the state of models, and have iteratively trained the state sequence of the context-dependent acoustic models using the PDT-SSS (Phonetic Decision Tree-based SSS) algorithm. To verify the effectiveness of the above algorithm we carried out the speech recognition experiments for 452 words of center for Korean language Engineering (KLE452) and 200 sentences of air flight reservation task (YNU200). Experimental results show that the recognition accuracy has progressively improved according to the number of states variations after perform the splitting of states in the phoneme, word and continuous speech recognition experiments respectively. Through the experiments, we have got the average 71.5%, 99.2% of the phoneme, word recognition accuracy when the state number is 2,000, respectively and the average 91.6% of the continuous speech recognition accuracy when the state number is 800. Also we haute carried out the word recognition experiments using the HTK (HMM Too1kit) which is performed the state tying, compared to share the parameters of the HM-Net topology design algorithm. In word recognition experiments, the HM-Net topology design algorithm has an average of 4.0% higher recognition accuracy than the context-dependent acoustic models generated by the HTK implying the effectiveness of it.

A Microgravity for Mapping and Monitoring the Subsurface Cavities (지하 공동의 탐지와 모니터링을 위한 고정밀 중력탐사)

  • Park, Yeong-Sue;Rim, Hyoung-Rae;Lim, Mu-Taek;Koo, Sung-Bon
    • Geophysics and Geophysical Exploration
    • /
    • v.10 no.4
    • /
    • pp.383-392
    • /
    • 2007
  • Karstic features and mining-related cavities not only lead to severe restrictions in land utilizations, but also constitute serious concern about geohazard and groundwater contamination. A microgravity survey was applied for detecting, mapping and monitoring karstic cavities in the test site at Muan prepared by KIGAM. The gravity data were collected using an AutoGrav CG-3 gravimeter at about 800 stations by 5 m interval along paddy paths. The density distribution beneath the profiles was drawn by two dimensional inversion based on the minimum support stabilizing functional, which generated better focused images of density discontinuities. We also imaged three dimensional density distribution by growing body inversion with solution from Euler deconvolution as a priori information. The density image showed that the cavities were dissolved, enlarged and connected into a cavity network system, which was supported by drill hole logs. A time-lapse microgravity was executed on the road in the test site for monitoring the change of the subsurface density distribution before and after grouting. The data were adjusted for reducing the effects due to the different condition of each survey, and inverted to density distributions. They show the change of density structure during the lapsed time, which implies the effects of grouting. This case history at the Muan test site showed that the microgravity with accuracy and precision of ${\mu}Gal$ is an effective and practical tool for detecting, mapping and monitoring the subsurface cavities.

Urban archaeological investigations using surface 3D Ground Penetrating Radar and Electrical Resistivity Tomography methods (3차원 지표레이다와 전기비저항 탐사를 이용한 도심지 유적 조사)

  • Papadopoulos, Nikos;Sarris, Apostolos;Yi, Myeong-Jong;Kim, Jung-Ho
    • Geophysics and Geophysical Exploration
    • /
    • v.12 no.1
    • /
    • pp.56-68
    • /
    • 2009
  • Ongoing and extensive urbanisation, which is frequently accompanied with careless construction works, may threaten important archaeological structures that are still buried in the urban areas. Ground Penetrating Radar (GPR) and Electrical Resistivity Tomography (ERT) methods are most promising alternatives for resolving buried archaeological structures in urban territories. In this work, three case studies are presented, each of which involves an integrated geophysical survey employing the surface three-dimensional (3D) ERT and GPR techniques, in order to archaeologically characterise the investigated areas. The test field sites are located at the historical centres of two of the most populated cities of the island of Crete, in Greece. The ERT and GPR data were collected along a dense network of parallel profiles. The subsurface resistivity structure was reconstructed by processing the apparent resistivity data with a 3D inversion algorithm. The GPR sections were processed with a systematic way, applying specific filters to the data in order to enhance their information content. Finally, horizontal depth slices representing the 3D variation of the physical properties were created. The GPR and ERT images significantly contributed in reconstructing the complex subsurface properties in these urban areas. Strong GPR reflections and highresistivity anomalies were correlated with possible archaeological structures. Subsequent excavations in specific places at both sites verified the geophysical results. The specific case studies demonstrated the applicability of ERT and GPR techniques during the design and construction stages of urban infrastructure works, indicating areas of archaeological significance and guiding archaeological excavations before construction work.

A Control Method for designing Object Interactions in 3D Game (3차원 게임에서 객체들의 상호 작용을 디자인하기 위한 제어 기법)

  • 김기현;김상욱
    • Journal of KIISE:Computing Practices and Letters
    • /
    • v.9 no.3
    • /
    • pp.322-331
    • /
    • 2003
  • As the complexity of a 3D game is increased by various factors of the game scenario, it has a problem for controlling the interrelation of the game objects. Therefore, a game system has a necessity of the coordination of the responses of the game objects. Also, it is necessary to control the behaviors of animations of the game objects in terms of the game scenario. To produce realistic game simulations, a system has to include a structure for designing the interactions among the game objects. This paper presents a method that designs the dynamic control mechanism for the interaction of the game objects in the game scenario. For the method, we suggest a game agent system as a framework that is based on intelligent agents who can make decisions using specific rules. Game agent systems are used in order to manage environment data, to simulate the game objects, to control interactions among game objects, and to support visual authoring interface that ran define a various interrelations of the game objects. These techniques can process the autonomy level of the game objects and the associated collision avoidance method, etc. Also, it is possible to make the coherent decision-making ability of the game objects about a change of the scene. In this paper, the rule-based behavior control was designed to guide the simulation of the game objects. The rules are pre-defined by the user using visual interface for designing their interaction. The Agent State Decision Network, which is composed of the visual elements, is able to pass the information and infers the current state of the game objects. All of such methods can monitor and check a variation of motion state between game objects in real time. Finally, we present a validation of the control method together with a simple case-study example. In this paper, we design and implement the supervised classification systems for high resolution satellite images. The systems support various interfaces and statistical data of training samples so that we can select the most effective training data. In addition, the efficient extension of new classification algorithms and satellite image formats are applied easily through the modularized systems. The classifiers are considered the characteristics of spectral bands from the selected training data. They provide various supervised classification algorithms which include Parallelepiped, Minimum distance, Mahalanobis distance, Maximum likelihood and Fuzzy theory. We used IKONOS images for the input and verified the systems for the classification of high resolution satellite images.

The Relationship between Internet Search Volumes and Stock Price Changes: An Empirical Study on KOSDAQ Market (개별 기업에 대한 인터넷 검색량과 주가변동성의 관계: 국내 코스닥시장에서의 산업별 실증분석)

  • Jeon, Saemi;Chung, Yeojin;Lee, Dongyoup
    • Journal of Intelligence and Information Systems
    • /
    • v.22 no.2
    • /
    • pp.81-96
    • /
    • 2016
  • As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.

Compact Orthomode Transducer for Field Experiments of Radar Backscatter at L-band (L-밴드 대역 레이더 후방 산란 측정용 소형 직교 모드 변환기)

  • Hwang, Ji-Hwan;Kwon, Soon-Gu;Joo, Jeong-Myeong;Oh, Yi-Sok
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
    • /
    • v.22 no.7
    • /
    • pp.711-719
    • /
    • 2011
  • A study of miniaturization of an L-band orthomode transducer(OMT) for field experiments of radar backscatter is presented in this paper. The proposed OMT is not required the additional waveguide taper structures to connect with a standard adaptor by the newly designed junction structure which bases on a waveguide taper. Total length of the OMT for L-band is about 1.2 ${\lambda}_o$(310 mm) and it's a size of 60 % of the existing OMTs. And, to increase the matching and isolation performances of each polarization, two conducting posts are inserted. The bandwidth of 420 MHz and the isolation level of about 40 dB are measured in the operating frequency. The L-band scatterometer consisting of the manufactured OMT, a horn-antenna and network analyzer(Agilent 8753E) was used STCT and 2DTST to analysis the measurement accuracy of radar backscatter. The full-polarimetric RCSs of test-target, 55 cm trihedral corner reflector, measured by the calibrated scatterometer have errors of -0.2 dB and 0.25 dB for vv-/hh-polarization, respectively. The effective isolation level is about 35.8 dB in the operating frequency. Then, the horn-antenna used to measure has the length of 300 mm, the aperture size of $450{\times}450\;mm^2$, and HPBWs of $29.5^{\circ}$ and $36.5^{\circ}$ on the principle E-/H-planes.