• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2473-2489
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• 2022

Urban development has brought about the increasing saturation of urban traffic demand, and traffic congestion has become the primary problem in transportation. Roads are in a state of waiting in line or even congestion, which seriously affects people's enthusiasm and efficiency of travel. This paper mainly studies the discrete domain path planning method based on the flow data. Taking the traffic flow data based on the highway network structure as the research object, this paper uses the deep learning theory technology to complete the path weight determination process, optimizes the path planning algorithm, realizes the vehicle path planning application for the expressway, and carries on the deployment operation in the highway company. The path topology is constructed to transform the actual road information into abstract space that the machine can understand. An appropriate data structure is used for storage, and a path topology based on the modeling background of expressway is constructed to realize the mutual mapping between the two. Experiments show that the proposed method can further reduce the interpolation error, and the interpolation error in the case of random missing is smaller than that in the other two missing modes. In order to improve the real-time performance of vehicle path planning, the association features are selected, the path weights are calculated comprehensively, and the traditional path planning algorithm structure is optimized. It is of great significance for the sustainable development of cities.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.878-886
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• 2011

The soybean is one of the oldest cultivated crops in the world. Microwave remote sensing is an important tool because it can penetrate into cloud independent of weather and it can acquire day or night time data. Especially a ground-based polarimetric scatterometer has advantages of monitoring crop conditions continuously with full polarization and different frequencies. In this study, soybean growth parameters and soil moisture were estimated using polarimetric discrimination ratio (PDR) by radar scatterometer. A ground-based polarimetric scatterometer operating at multiple frequencies was used to continuously monitor the soybean growth condition and soil moisture change. It was set up to obtain data automatically every 10 minutes. The temporal trend of the PDR for all bands agreed with the soybean growth data such as fresh weight, Leaf Area Index, Vegetation Water Content, plant height; i.e., increased until about DOY 271 and decreased afterward. Soil moisture lowly related with PDR in all bands during whole growth stage. In contrast, PDR is relative correlated with soil moisture during below LAI 2. We also analyzed the relationship between the PDR of each band and growth data. It was found that L-band PDR is the most correlated with fresh weight (r=0.96), LAI (r=0.91), vegetation water content (r=0.94) and soil moisture (r=0.86). In addition, the relationship between C-, X-band PDR and growth data were moderately correlated ($r{\geq}0.83$) with the exception of the soil moisture. Based on the analysis of the relation between the PDR at L, C, X-band and soybean growth parameters, we predicted the growth parameters and soil moisture using L-band PDR. Overall good agreement has been observed between retrieved growth data and observed growth data. Results from this study show that PDR appear effective to estimate soybean growth parameters and soil moisture.

• The Plant Pathology Journal
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• v.27 no.1
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• pp.33-36
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• 2011

The genome of a potyvirus isolate associated with chlorotic spots and vein banding symptoms on Spathiphyllum spp., in Andhra Pradesh state, India was amplified by RT-PCR using degenerate potyvirus primers, amplicons cloned, and sequence (1.6 kb) analyzed. This virus isolate shared maximum identity of 74.8% and 80.2% at coat protein (CP) gene nucleotide (906 nucleotides) and amino acid (302 amino acids) levels, respectively with Dasheen mosaic virus (DsMV)-M13 isolate reported from China. But its 3'-UTR (258 nucleotides) had maximum identity of 62.5% with DsMV-Vietnam isolate. The deduced molecular weight of CP is 33.57 kDa and it contained DAG triplet in its N-terminal region. In CP amino acid based phylogenetic analysis, this virus isolate represented a separate branch but closer to DsMV isolates cluster. Based on the molecular criteria set for the discrimination of species and genus in the Potyviridae family, the present virus isolate was identified as a distinct virus species in the genus Potyvirus and proposed the name Spathiphyllum chlorotic vein banding virus (SCVbV).

• Journal of Microbiology and Biotechnology
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• v.29 no.6
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• pp.887-896
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• 2019

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS)-based pathogen identification relies on the ribosomal protein spectra provided in the proprietary database. Although these mass spectra can discern various pathogens at species level, the spectra-based method still has limitations in identifying closely-related microbial species. In this study, to overcome the limits of the current MALDI-TOF MS identification method using ribosomal protein spectra, we applied MALDI-TOF MS of low-mass profiling to the identification of two genetically related Bacillus species, the food-borne pathogen Bacillus cereus, and the insect pathogen Bacillus thuringiensis. The mass spectra of small molecules from 17 type strains of two bacilli were compared to the morphological, biochemical, and genetic identification methods of pathogens. The specific mass peaks in the low-mass range (m/z 500-3,000) successfully identified various closely-related strains belonging to these two reference species. The intensity profiles of the MALDI-TOF mass spectra clearly revealed the differences between the two genetically-related species at strain level. We suggest that small molecules with low molecular weight, 714.2 and 906.5 m/z can be potential mass biomarkers used for reliable identification of B. cereus and B. thuringiensis.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.527-539
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• 2023

In the positioning algorithm of two-dimensional planar sensor array, the estimation error of time difference-ofarrival (TDOA) algorithm is difficult to avoid. Thus, how to achieve accurate positioning is a key problem of the positioning technology based on planar array. In this paper, a method of sensor reliability discrimination is proposed, which is the foundation for selecting positioning sensors with small error and excellent performance, simplifying algorithm, and improving positioning accuracy. Then, a positioning model is established. The estimation characteristics of the least square method are fully utilized to calculate and fuse the positioning results, and the non-uniform weighting method is used to correct the weighting factors. It effectively handles the decreased positioning accuracy due to measurement errors, and ensures that the algorithm performance is improved significantly. Finally, the characteristics of the improved algorithm are compared with those of other algorithms. The experiment data demonstrate that the algorithm is better than the standard least square method and can improve the positioning accuracy effectively, which is suitable for vibration detection with large noise interference.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.10
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• pp.1385-1392
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• 2003

An electromagnetic flowmeter(EMF) was developed and its characteristics were compared with a commercial EMF. The developed EMF was designed as the 100 mm nominal diameter. A signal processing circuit was also developed for generating the magnetic field and converting the flow signal to flowrate and flow quantity. In order to obtain a more stable and reliable flow signal, the double magnetizing frequency was adopted for magnetizing the coil of the EMF. For the characterization of the developed EMF, the uncertainty of calibrator was estimated within $\pm$0.5 %. The evaluation procedure of the uncertainty followed the ISO Guide to the Expression of Uncertainty in Measurement. It was found that the flow signals between the electrodes were about $\pm$60-$\pm$300$\mu$V, which were sufficient for the discrimination of flowmeter and the protection of noise. The test results against the calibrator showed the good linearity in the range of 3 ㎥/h and 70 ㎥/h. A commercialized design of the EMF based on the current study will be technically more competitive in domestic and foreign market.

• Journal of Korean Society of Rural Planning
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• v.23 no.2
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• pp.1-7
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• 2017

The purpose of this study is to develop a farm management diagnostic checklist form, which can be applied to any crops. First, upper indexes and subordinate indexes were identified through survey with expert, and weighted values for each subordinate index were calculated through AHP analysis. Second, as a reuslt of Analytic Hierarchy Process (AHP) analysis, marketing management (0.276) was found to be the most important index of all upper indexes. In the case of subordinate indexes, reflecting management evaluation (0.252) of management consciousness, quality enhancement efforts (0.332) of production management, locating new sales outlets (0.323) of marketing management, agriculture accounting (0.300) of finance management, and adjusting shipping dates (0.274) of risk management were found to be the highest. Third, the interval division using weight of farm receiving prices was higher discrimination in comparison to equal interval division of weighted values for each index. The newly developed farm management diagnostic checklist can be applied to any crops, as it utilizes indexes such as management consciousness, production management, marketing management, financial management, risk management, etc. based on professional opinions. In addition, it allows an objective evaluation of farm management situations by utilizing the weighted value of farm receiving prices.

• Journal of Biomedical Engineering Research
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• v.22 no.4
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• pp.369-375
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• 2001

The statistical regression model is one of the most frequently used clinical analysis methods. It has basic assumption of linearity, additivity and normal distribution of data. However, most of biological data in medical field are nonlinear and unevenly distributed. To overcome the discrepancy between the basic assumption of statistical model and actual biological data, we propose a new analytical method based on artificial neural network. The newly developed multilayer perceptron(MLP) is trained with 120 data set (60 normal, 60 patient). On applying test data, it shows the discrimination power of 0.76. The diabetic risk factors were also identified from the MLP neural network model and the logistic regression model. The signigicant risk factors identified by MLP model were post prandial glucose level(PP2), sex(male), fasting blood sugar(FBS) level, age, SBP, AC and WHR. Those from the regression model are sex(male), PP2, age and FBS. The combined risk factors can be identified using the MLP model. Those are total cholesterol and body weight, which is consistent with the result of other clinical studies. From this experiment we have learned that MLP can be applied to the combined risk factor analysis of biological data which can not be provided by the conventional statistical method.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.213-219
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• 2023

In recent years, popularity of deep learning (DL) is increased due to its ability to extract features from Hyperspectral images. A lack of discrimination power in the features produced by traditional machine learning algorithms has resulted in poor classification results. It's also a study topic to find out how to get excellent classification results with limited samples without getting overfitting issues in hyperspectral images (HSIs). These issues can be addressed by utilising a new learning network structure developed in this study.EfficientNet-B4-Based Convolutional network (EN-B4), which is why it is critical to maintain a constant ratio between the dimensions of network resolution, width, and depth in order to achieve a balance. The weight of the proposed model is optimized by Search and Rescue Operations (SRO), which is inspired by the explorations carried out by humans during search and rescue processes. Tests were conducted on two datasets to verify the efficacy of EN-B4, with Indian Pines (IP) and the University of Pavia (UP) dataset. Experiments show that EN-B4 outperforms other state-of-the-art approaches in terms of classification accuracy.

• Journal of Distribution Science
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• v.10 no.5
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• pp.45-55
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• 2012

In Korea, the parcel delivery service was launched officially in 1992, and the market has grown to 13.2 billion units, or 3.5 trillion won, as of 2011. The service companies accept small packages under 30 kg and deliver them on the next day in most domestic areas. This service plays an important role in business and personal activities. The parcel service companies have themselves designed the tariff for the delivery service based on two criteria: weight and the sum of three side lengths. Further, the tariff is graded in steps of three or four rate structures based on size (small, medium, large, and extra-small). However, the basic freight rate is generally decided according to the cargo's weight or measurement size, and an extra rate is added according to some factors (handling, stowability, liability, and so on). The parcel service tariff adopted by the companies is illogically designed, and this study was carried out to assess the need for redesigning the tariff structure. The cargo volume cannot be logically reflected by three side lengths. For example, two parcels measuring 160 cm based on three side lengths may have different volumes, one measuring 0.152 cbm (53.33 cm × 53.33 cm × 53.34 cm) and the other 0.05 cbm (100 cm × 50 cm × 10 cm). A small package of less than120 cm (sum of three side lengths) may have a volume of as much as 0.064 cbm (40 cm × 40 cm × 40 cm). Sample comparison showed that 17% of medium-size parcels (based on the sum of three side lengths) are small-volume packages, 24% of large-size parcels are small- or medium-volume packages, and 40% of extra-big-size parcels are big- or under-size packages. Therefore, if parcel service companies rate their services for volume cargo based on the three side lengths standard, users may have to pay higher than normal rates, particularly because a large percentage of parcels are volume cargo. According to this study, the average weight per 1 cbm is less than 300 kg. Therefore, users face an increasing risk of paying higher than logical freight charges. Generally, transportation companies are called "public interest enterprises," and parcel service companies operate as postal services. Public interest enterprises must provide the delivery service to all customers without discrimination at a reasonable service level and logical service charges. Therefore, parcels service tariffs must be designed and adopted logically. In this study, freight theories and prior research findings were used to consider the importance of freight rates, and distortion of parcel service rates based on the three side lengths system was verified through regression analysis of a parcel sample and sample comparison. In conclusion, volume sizes based on three side lengths have a higher correlation to the rate level than does the sum of three side lengths. Further, compared to the sum of three side lengths, volume size has a higher correlation to cargo weight, which is the most basic factor determining transportation cost. Therefore, the existing parcel service tariff should be changed to weight- and volume-based rates, and the tariff must be graded in steps of 8 to 10 higher rate structures for a logical freight schedule based on service cost.