In order to give consideration to both comprehensive evaluation and efficient decision-making in collision avoidance decision-making process, a collision avoidance decision-making model based on collision circle is proposed by introducing the concept of collision circle. Firstly, the factors causing ship collision are analyzed. Secondly, the static and dynamic characteristics of collision circles are analyzed and summarized by using collision circle simulation cases. Thirdly, based on the static characteristics, a reasonably distributed collision avoidance decision model of (Possible Point of Collision,PPC) was established. Finally, the spatial data operations core algorithm (Java Topology Suite, JTS) is used for logical operation and visualization, so as to realize the ship collision avoidance evaluation and decision. The decision model was used to verify the accident scenario of "SANCHI", and the results showed that the obtained collision avoidance scheme was reasonable and in line with the "International Regulations for Preventing Collisions at Sea" and safety requirements, thus providing a reference for maritime operators to avoid collisions between ships.
Shipment size is unavailable and important in AIS-based trade volume estimates. A method of shipment size estimates based on AIS (Automatic Identification System) data and BP neural network is proposed. The ship's length, width, designed draught, current draught and deadweight ton are input parameters, the actual shipment size of the ship is output value, and the BP neural network is trained to estimate the actual shipment size of the iron ore carriers. Then, the AIS data is used to calculate the iron ore trade volume in 2018. Compared with customs data, the annual error of import volume of China is less than 0.5%. The result shows that the proposed method is accurate and practical.
N,N-dihydroxybenzene-1,3-dicarboximidoyl dichloride was synthesized from benzene-1,3-dicarboxaldehyde and characterized by fourier transform infrared spectroscopy (FT-IR) and nuclear magnetic resonance 1H and 13C NMR). The elastomer was prepared through the 1,3-dipolar cycloaddition of reaction between liquid polybutadiene (LPB) and isophthalonitrile oxide in this work. The tensile strength of different elastomer was enhanced from 0.14 MPa to 0.33 MPa as the elongation at break decreased from 145% to 73%, and the modulus increased from 0.09 kPa to 0.47 kPa. The parameters of kinetic indicated that the curing reaction was first order reaction and the apparent activation energy of each curing system was less than 10.10 kJ/mol when the content of N,N-dihydroxybenzene-1,3- dicarboximidoyl dichloride was increased from 7% to 12%. These results suggested that nitrile oxides achieved curing of polymer binders at room temperature and this work had definite guiding significance for the application of nitrile oxides in polymer binders.
The degradation of flutriafol in aqueous persulfate (S2O82–) system in the presence of selected transition metal ions was investigated. In the presence of Ag+ or Fe2+, flutriafol degradation occurs, whereas in the presence of Mn2+, Co2+, Ni2+, Cu2+, Zn2+ and Bi3+ ions, the degradation is less than 15%. The Ag+/ S2O82– aqueous system being the most effective was adopted for experimental and theoretical investigations. It was confirmed that pH of 3.0 is the most suitable, and that both · SO4–and ·OH– radicals are the main active species to afford flutriafol degradation, with the former contributes more than the latter. To elucidate degradation mechanism, molecular orbital calculations were performed and reaction intermediates identified by GC/MS and HPLC/MS/MS analyses. Three degradation pathways are proposed that involve the cleavage of C–N and C–C bonds as a result of ·SO4– attack, as well as the formation of hydroxylated products due to · OH radicals.
With the wide use of AIS system in the world, especially in ports and the waters with heavy traffic, AIS message loss may be related to environmental conditions, obstacle, limitation of VHF technology and AIS network overload, thereby reducing the AIS signal successful reception rate. This paper selected typical AIS data received by Yagi and Omni antennas at the same time in specific waters, uses grid and AIS data recovery technology, establishes the AIS signal coverage model, analyzes signal reception rate of Yagi antenna and Omni antenna of AIS base station, and verified the superiority of Yagi antenna in AIS signal reception rate.
Interpolation of ship motion vectors is able to be used for estimating the lost ship AIS dynamic information, which is important for replaying marine accidents and for analysing marine traffic data. The previous methods can only interpolate ship’s position, while not including ship's course and speed. In this paper, vector function is used to express the relationship between the ship’s time and space coordinates, and the tangent of the vector function and its change rate are able to express physical characteristics of ship’s course, speed and acceleration. The given AIS dynamic information can be applied to calculate the parameters of ship's vector function and then the interpolation model for ship motion vectors is developed to estimate the lost ship dynamic information at any given moment. Experiment results show that the ship motion vector function is able to depict the characteristics of ship motions accurately and the model can estimate not only the ship’s position but also ship’s course and speed at any given moment with limited differences.
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How to evaluate features and select nodes is one of the key issues in constructing decision trees. In this work fuzzy rough set theory is employed to design an index for evaluating the quality of fuzzy features or numerical attributes. A fuzzy rough decision tree algorithm, which can be used to address classification problems described with symbolic, real-valued or fuzzy features, is developed. As node selection, split generation and stopping criterion are three main factors in constructing a decision tree, we design different techniques to determine splits with different kinds of features. The proposed algorithm can directly generate a classification tree without discretization or fuzzification of continuous attributes. Some numerical experiments are conducted and the comparative results show that the proposed algorithm is effective compared with some popular algorithms.
The identification of areas of collision risk in restricted waters could play an important role in VTS services. Based on the concept of ship domain, this paper introduces a model for identifying collision risk between vessels in restricted waters, then puts forward an improved DBSCAN clustering algorithm for identifying areas of high collision risk, finally, the visualization algorithm is presented. The experimental results in this paper show the algorithm is capable of identifying and rendering areas of collision risk in restricted waters.
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Covering information systems and ordered information systems are two important types of information systems. In this paper the relationships between covering information systems and ordered information systems are first examined, and it is proved that these two types of information systems are isomorphic under given conditions and can be equivalently transformed into each other. Then, the approach to attribute reduction in ordered information systems is proposed. Based on the isomorphism and equivalence of transformation, the method of attribute reduction in a covering information system can be directly obtained according to the reduction approach in an ordered in- formation system. A practical example is employed to show that the proposed method is an effective technique to deal with complex data sets.
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Currently there are more and more ships sailing in inland waterways so that the traditional inland shipping management information system (ISMIS) becomes relatively backward. Based on the rapidly developed new information technologies, such as wireless sensor network, Internet-of-things, cloud-computing and so on, we propose a novel design of ISMIS, which is featured by low cost, environment-friendly, cross platform, high scalability and integrity and thus can efficiently improve the inland shipping management and inland water environment.
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In recent years, with the development of information technology, businesses have accumulated a lot of useful historical data, as the shipping industry does. These data can be found deposited a large number of "knowledge", for example, Shipping records for historical information, Ship-Port relations information, Ship-ship relations information, Port & shipping route relations, Shipping route information. It can provide intellectual support to shipping informatization development. Association rules in data mining technology is one of important technologies. The technology, based on sta-tistical methods, can mine the associated and implied "knowledge" from data warehouse ,which has a large number of accumulated data. Apart from this, the technology can also play an important role in the prediction. In this paper, based on FP-growth algorithm, we improve it forming Relevent ships routes. From the prevalent perspective of data mining, deal with the corresponding vessels' dynamic information, ac-quired from the AIS, such as data collection, data statistics. On this basis, get the ship-port relation and ship-ship relation after a certain level of data analysis, processing, handing. Furthermore, this paper use the numer-ous historical ship-port relation and ship-ship relation to build a mathematical model on the ship-port and ship-ship relation. And use the improved association algorithm, FP-growth algorithm, to acquire the strong association rules between ship-port and ship-ship, and eventually mine the similarity of the ship route. Main points of this paper as follows: Collect ,count and check the data, which is from ship dynamic information; Establish the mathematical model between ship-port and ship-ship relation; Improve the algorithm; Analyse the similarity of ship route more accurately using the improved algorithm.
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As there are more and more Automatic Identification System (AIS) sets have been deployed onboard, it is getting easier for people to trace vessels. Today, many online vessel monitoring services have been developed; however, most of them are based on AIS information. Because the coverage limitation of VHF frequency, which the AIS set works on, is normally no more than 25 nautical miles, so these systems can not track vessels when they are beyond the coverage of the shore-based AIS station. In order to track ves-sels in all sea areas, we developed a comprehensive vessel tracking system, namely ManyShips, which inte-grates AIS, Inmarsat and China Beidou navigation satellite system. The running result of the system shows that the Beidou satellite system can track vessels within Asian-Pacific region while the Inmarsat-C station polling service can help people tracking vessels within sea area A3.
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When using the Rapid freeze prototype (RFP) process to fabricate 3D tissue bone scaffold, the selecting of technological parameters directly affects lap ratio, which is the foundation of continuous fabrication and scaffold quality. Through analyzing the force of non-solidified fiber, Velocity ratio, liquid temperature, solid content, nozzle diameter and row spacing have been chosen as the influence factors and the L16 (45) orthogonal experiments have been done The experiments result is that material viscosity and row spacing is the most important factors for lap ratio influence. Optimal parameters combination has been got by range analysis. Finally, the mixed solution of gelatin-chitosan experiment with the optimal parameters has successfully produced multilayer tissue bone scaffold, including multiple scale structure.
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W artykule zaprezentowano process wytwarzania materiałów trójwymiarowych metoda gwałtownego oziębiania – RFP (rapid freeze prototype). Materiałem wyjściowym jest mieszanina żelatyny i chitozanu. Na proces tworzenia struktury ma wpływ wiele czynników, takich jak: temperatura cieczy, zawartość składnika stałego, rozmiary węzłów, średnica i odstępy między rzędami.
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This paper designed the method to control the electrospinning process stability basing on the analysis of Taylor-cone, and built the electric field adjust method to control the fiber diameter basing on the finite element analysis, experiments results showed that the stability was improved and diameter could the adjusted in micro-nano level.
PL
W artykule zaprezentowano metodę sterowania procesu produkcji nanowłókien bazująca na stożku Taylora i wykorzystaniu pola elektrycznego do kontroli średnicy włókna.
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A micro heat pipe’s (MHP) performance is largely determined by its capillary limit. Based on comprehensive analyses of lower backflow resistance of working fluid in trapezium-grooved-wick MHP and greater capillary suction in a sintered-wick MHP, this paper established the mathematical model of capillary limit for a MHP with the compound structure of a sintered wick on trapezium-grooved substrate. The analyses show that a MHP with such compound structure has a higher capillary limit than that a MHP with a simplex sintered- or trapezium-grooved wick structure.
PL
Właściwości podgrzewanej mikrorurki zależą od parametrów kapilary. W artykule zaprezentowano model matematyczny mikrorurki z kapilarą uwzględniający skład. Zaproponowano optymalizacje konstrukcji.
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The theory of fuzzy rough sets is claimed to be a powerful mathematical tool for dealing with uncertainty in data analysis. Unluckily, the classical model of fuzzy rough sets is sensitive to noisy information. This disadvantage limits the applicability of the model in practice. In this work, we present a robust fuzzy rough set model based on soft minimum enclosing ball, and introduce a new fuzzy dependency function with this model. Some properties of the new model are discussed. Finally, we conduct some experiments to test the effectiveness of the proposed model, and experimental results show that the soft minimum enclosing ball-based fuzzy rough set model is robust to noise.
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Colour quantisation algorithms are essential for displaying true colour images using a limited palette of distinct colours. The choice of a good colour palette is crucial as it directly deter- mines the quality of the resulting image. Colour quantisation can also be seen as a clustering problem where the task is to identify those clusters that best represent the colours in an image. In this paper we propose rough c-means and fuzzy rough c-means clustering algorithms for colour quantisation of images. Both approaches utilise the concept of lower and upper approximations of clusters to define palette colours. While in the rough c-means approach cluster centroids are refined iteratively through a linear combination of elements of the lower and upper approximations, the fuzzy rough c-means technique assigns variable membership values to the elements in the boundary region which in turn are incorporated into the calculation of cluster centres. Experimental results on a standard set of images show that these approaches performs significantly better than other, purpose built colour quantisation algorithms.
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Driver fatigue detection based on computer vision is considered as one of the most hopeful applications of image recognition technology. The key issue is to extract and select useful features from the driver images. In this work, we use the properties of image sequences to describe states of drivers. In addition, we introduce a kernelized fuzzy rough sets based technique to evaluate quality of candidate features and select the useful subset. Fuzzy rough sets are widely discussed in dealing with uncertainty in data analysis. We construct an algorithm for feature evaluation and selection based on fuzzy rough set model. Two classification algorithms are introduced to validate the selected features. The experimental results show the effectiveness of the proposed techniques.
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Traditionally, marine traffic congestion degree in restricted waters is usually deduced from traf-fic volume or traffic density. Both of which, however, can not be easily and accurately determined and can not fully reflect the traffic congestion degree. This paper uses the concept of main traffic flow velocity, which varies with the main traffic congestion from a statistics view, to determine the main traffic congestion degree in restricted waters. Main traffic flow velocity can be calculated by averaging the speeds of all ships equipped with an AIS transponder if the percentage of these ships over all vessels in the main traffic is great enough and they are well-distributed, and a fuzzy relationship is established to determine the traffic congestion degree under varying main traffic flow velocity. The concept of main traffic flow velocity provides a more intuitive and accurate way to evaluate the main traffic congestion degree of restricted waters than traffic density and traffic volume in certain situations, and can be easily implement.
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Feature selection is an important preprocessing step in pattern analysis and machine learning. The key issue in feature selection is to evaluate quality of candidate features. In this work, we introduce a weighted distance learning algorithm for feature selection via maximizing fuzzy dependency. We maximize fuzzy dependency between features and decision by distance learning and then evaluate the quality of features with the learned weight vector. The features deriving great weights are considered to be useful for classification learning. We test the proposed technique with some classical methods and the experimental results show the proposed algorithm is effective.
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