• Journal of Navigation and Port Research
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• v.35 no.3
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• pp.235-241
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• 2011

The shuttle that currently connects Busan New Port to the logistics companies in the Hinterland has the following companies: first, resources are consumed redundantly as each logistics company has independent transport vehicles. Second, the companies are not taking advantage of geographical merits of clustered complexes because different vehicles are used each time due to irregular schedules. In this respect, this study had the following purposes to realize these solutions: first, heuristic approach was made for operation scheduling and real-time operating rules to configure the best possible dynamic plan. Second, the reduction of consumption of resources with the shuttle and the efficiency were examined through a simulation of pooling and dual cycling applied to logistics companies' shipping plans.

• Macromolecular Research
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• v.15 no.6
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• pp.565-574
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• 2007

In this study, five representative, commercially available polymers, Ultem 1000 polyetherimide, Kapton polyimide, phenolic resin, polyacrylonitrile and cellulose acetate, were used to prepare pyrolyzed polymer membranes coated on a porous {\alpha}-alumina$ tube via inert pyrolysis for gas separation. Pyrolysis conditions (i.e., final temperature and thermal dwell time) of each polymer were determined using a thermogravimetric method coupled with real-time mass spectroscopy. The surface area and pore size distribution of the pyrolyzed materials derived from the polymers were estimated from the nitrogen adsorption/desorption isotherms. Pyrolyzed membranes from polymer precursors exhibited type I sorption behavior except cellulose acetate (type IV). The gas permeation of the carbon/{\alpha}-alumina$ tubular membranes was characterized using four gases: helium, carbon dioxide, oxygen and nitrogen. The polyetherimide, polyimide, and phenolic resin pyrolyzed polymer membranes showed typical molecular sieving gas permeation behavior, while membranes from polyacrylonitrile and cellulose acetate exhibited intermediate behavior between Knudsen diffusion and molecular sieving. Pyrolyzed membranes with molecular sieving behavior (e.g., polyetherimide, polyimide, and phenolic resin) had a $CO_2/N_2$ selectivity of greater than 15; however, the membranes from polyacrylonitrile and cellulose acetate with intermediate gas transport behavior had a selectivity slightly greater than unity due to their large pore size.

• Journal of Aerospace System Engineering
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• v.8 no.2
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• pp.21-26
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• 2014

The aircraft manufacturers are constantly driving to reduce manufacturing lead times and cost at the same time as the product complexity increases and technology continues to change. Integrated Modular Avionics (IMA) is a solution that allows the aviation industry to manage their avionics complexity. IMA defines an integrated system architecture that preserves the fault containment and 'separation of concerns' properties of the federated architectures. In software side, the air transport industry has developed ARINC 653 specification as a standardized Real Time Operating System (RTOS) interface definition for IMA. It allows hosting multiple applications of different software levels on the same hardware in the context of IMA architecture. This paper describes a study that provided the avionics software design for separation of fault and backup of core function to reduce workload of pilot with cost efficiency.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.21-26
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• 2006

This paper focuses on modeling and predicting differential GPS corrections transmitted by marine radio-beacon systems using artificial neural networks. Various neural network structures with various training algorithms were examined, including Linear, Radial Biases, and Feedforward. Matlab Neural Network toolbox is used for this purpose. Data sets used in building the model are the transmitted pseudorange corrections and broadcast navigation message. Model design is passed through several stages, namely data collection, preprocessing, model building, and finally model validation. It is found that feedforward neural network with automated regularization is the most suitable for our data. In training the neural network, different approaches are used to take advantage of the pseudorange corrections history while taking into account the required time for prediction and storage limitations. Three data structures are considered in training the neural network, namely all round, compound, and average. Of the various data structures examined, it is found that the average data structure is the most suitable. It is shown that the developed model is capable of predicting the differential correction with an accuracy level comparable to that of beacon-transmitted real-time DGPS correction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5522-5540
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• 2018

Vehicular license plate (LP) recognition system has risen as a significant field of research recently because various explorations are currently being conducted by the researchers to cope with the challenges of LPs which include different illumination and angular situations. This research focused on restricted conditions such as using image of only one vehicle, stationary background, no angular adjustment of the skewed images. A real time vehicular LP recognition scheme is proposed for the skewed images for detection, segmentation and recognition of LP. In this research, a polar co-ordinate transformation procedure is implemented to adjust the skewed vehicular images. Besides that, window scanning procedure is utilized for the candidate localization that is based on the texture characteristics of the image. Then, connected component analysis (CCA) is implemented to the binary image for character segmentation where the pixels get connected in an eight-point neighbourhood process. Finally, optical character recognition is implemented for the recognition of the characters. For measuring the performance of this experiment, 300 skewed images of different illumination conditions with various tilt angles have been tested. The results show that proposed method able to achieve accuracy of 96.3% in localizing, 95.4% in segmenting and 94.2% in recognizing the LPs with an average localization time of 0.52s.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.7
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• pp.921-929
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• 2013

Huoyan goose is a Chinese local breed famous for its higher laying performance, but the problems of variety degeneration have emerged recently, especially a decrease in the number of eggs laid. In order to better understand the molecular mechanism that underlies egg laying in Huoyan geese, gene profiles in the pituitary gland of Huoyan geese taken during the laying period and ceased period were investigated using the suppression subtractive hybridization (SSH) method. Total RNA was extracted from pituitary glands of ceased period and laying period geese. The cDNA in the pituitary glands of ceased geese was subtracted from the cDNA in the pituitary glands of laying geese (forward subtraction); the reverse subtraction was also performed. After sequencing and annotation, a total of 30 and 24 up and down-regulated genes were obtained from the forward and reverse SSH libraries, respectively. These genes mostly related to biosynthetic process, cellular nitrogen compound metabolic process, transport, cell differentiation, cellular protein modification process, signal transduction, small molecule metabolic process. Furthermore, eleven genes were selected for further analyses by quantitative real-time PCR (qRT-PCR). The qRT-PCR results for the most part were consistent with the SSH results. Among these genes, Synaptotagmin-1 (SYT1) and Stathmin-2 (STMN2) were substantially over-expressed in laying period compared to ceased period. These results could serve as an important reference for elucidating the molecular mechanism of higher laying performance in Huoyan geese.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.414-418
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• 2003

VoIP is a core technology used to transmit both voice and data in an integrated packet' form. Within this technology, SIP is the signaling protocol used for 'real time' call services; particularly those where H323 is used. Yet, when considering the needs of mobile users, it is essential we integrate VoIp within the mobile technology so the mobile host is able to receive the 'packet' transported and by, and connected to, any available internet-address. For all this to occur, we need to improve Network Delay by reducing transmission problems associated with mobile services. If we are to obtain an optimal service then we must reduce any network delays which may arise from joining Mobile IP and VoIp services. This paper, therefore, considers how, unlike previous research, these delays may be improved through the use of the signaling technology\ulcorner SIP. It also considers how this research may be introduced into current wired and wireless integrated services enabling them to use the IP 'packet'.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.607-612
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• 2015

As the amount of vehicle's diagnostics data increases, the actors in automotive ecosystem will encounter difficulties to perform a real time analysis in order to simulate or to design new services according to the data gathered from the connected cars. In this paper, we have conducted a study of a Big Data solution that expresses the essential deep analytics to process and analyze vast quantities of vehicles on board diagnostics data generated by cars. Hadoop and its ecosystems have been deployed to process a large data and delivered useful outcomes that may be used by actors in automotive ecosystem to deliver new services to car owners. As the Intelligent transport system is involved to guarantee safety, reduce rate of crash and injured in the accident due to speed, addressing big data solution based on vehicle diagnostics data is upcoming to monitor real time outcome from it and making collection of data from several connected cars, facilitating reliable processing and easier storage of data collected.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3465-3479
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• 2017

Information-Centric Vehicular Ad Hoc Network (IC-VANET) is a promising network architecture for the future intelligent transport system. Video streaming applications over IC-VANET not only enrich infotainment services, but also provide the drivers and pedestrians real-time visual information to make proper decisions. However, due to the characteristics of wireless link and frequent change of the network topology, the packet loss seriously affects the quality of video streaming applications. In this paper, we propose a REceiver-Driven loss reCOvery Mechanism (REDCOM) to enhance video dissemination over IC-VANET. A Markov chain based estimation model is introduced to capture the real-time network condition. Based on the estimation result, the proposed REDCOM recovers the lost packets by requesting additional forward error correction packets. The REDCOM follows the receiver-driven model of IC-VANET and does not require the infrastructure support to efficiently overcome packet losses. Experimental results demonstrate that the proposed REDCOM improves video quality under various network conditions.

• International Journal of Highway Engineering
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• v.10 no.3
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• pp.19-31
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• 2008

Video image processing systems(VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on wide-area detection, i.e., multi-lane surveillance algorithm provide traffic parameters with single camera such as flow and velocity, as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. The objective of this research was to relate traffic safety to VIPS tracking and this paper has developed a computer vision system of monitoring individual vehicle trajectories based on image processing, and offer the detailed information, for example, volumes, speed, and occupancy rate as well as traffic information via tripwire image detectors. Also the developed system has been verified by comparing with commercial VIP detectors.