• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.645-653
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• 2020

Recently studies on how to use the UAV (Unmanned Aerial Vehicle) are actively being conducted, and the National Geographic Information Institute published the 『Work Guidelines for Public Surveying of Unmanned Aerial Vehicles』. However, the guidelines do not provide the optimum shooting conditions required for each application. In this study, we tried to find the suitable shooting conditions for the production of 3D (Three-dimensional) spatial information and orthophoto. To this end, 45 experiments were conducted by various altitudes, overlaps, and camera angles within an above ground level of 150m. For evaluating the 3D modeling by shooting conditions, point densities of 9 verification areas were analyzed, and to evaluate the orthophotos, 1/1,000 digital maps were compared. Considering the quality of the output and the processing time for precise 3D construction, an altitude of 50m, an overlap of 70~80%, and a camera angle of 80~90° are suitable as shooting conditions, and an altitude of 100m and camera angle of 80~90° are suitable for orthophoto generation.

• The Journal of the Acoustical Society of Korea
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• v.40 no.1
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• pp.10-17
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• 2021

The cymbal transducer is a miniaturized version of the Class V flextensional transducer. It has low resonant frequency and high output pressure characteristics compared with its size. However, since it has high quality factor and low energy conversion efficiency as well, it is often used as an array rather than single. When used as an array, a big change in the frequency characteristics occurs in comparison with that of the single transducer due to the interaction between constituent transducers. In this study, we designed a pattern of cymbal array with a view to having broadband characteristics. Three transducers having different center frequencies were designed first. The designed cymbal transducers were used to construct all possible patterns of a 3 × 3 planar array. After analyzing frequency characteristics of these patterns, based on the results, we derived the most effective pattern to achieve a higher fractional bandwidth. The derived array pattern showed an improvement of the fractional bandwidth by 24.9 % in comparison with the reference model.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.32 no.2
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• pp.87-93
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• 2021

There are a number of voice analysis programs around the world. Domestic voice analysis is performed by relying heavily on specific commercial program. We intend to develop coding for voice analysis using Praat and apply it to clinical practice. This study consisted of Experiment 1 and Experiment 2. Experiment 1 was the development of automated voice analysis coding based on Praat. The coding was largely divided into a recording, an analysis, and a storage section. Experiment 2 was applied to the voice analysis of 2 male patients pre- and post-operation with this coding. The analysis parameters of this coding provided 26 parameters for vowel /a/, nine parameters for sentence analysis, and a total of 4 parameters for voice range profile analysis. In two male patients, the pitch and the intensity increased, the voice quality improved, and the sentence length decreased after surgery. The coding was well made, so the output was good in real time. The code is automated as much as possible to block manual errors and increases convenience and efficiency by generating the result sheet in real time.

• Communications of Mathematical Education
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• v.34 no.4
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• pp.421-437
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• 2020

Problem/Project based learning(PBL) is a student-centered teaching method in which students collaboratively solve problems and reflect their experiences. According to the results of PBL study and the experiences of the authors in PBL instruction, this paper introduced the necessities, output and significance of learning process PBL evaluation method and sums up our PBL evaluation process. The issue of appropriate and fair evaluation has been raised in untact (non-contact) university mathematics education due to the novel coronavirus (COVID-19) of the year 2020. To this end, when we had the course on for the summer semester held at S University in the summer of 2020. To ensure the fairness in evaluation and to improve the quality of our college math education, the PBL evaluation method was fully adapted. As a result, most of the students who took the lecture have learned a wide range of related knowledge without a single exception, and students agreed it is an ideal, fair, rational, and effective evaluation method applicable to other online courses in the era of untact education. This case was summarized in detail and introduced in this paper.

• Journal of Microbiology and Biotechnology
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• v.32 no.2
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• pp.149-159
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• 2022

Cancers of the lung and liver are the top 10 leading causes of cancer death worldwide. Thus, it is essential to identify the genes specifically expressed in these two cancer types to develop new therapeutics. Although many messenger RNA (mRNA) sequencing data related to these cancer cells are available due to the advancement of next-generation sequencing (NGS) technologies, optimized data processing methods need to be developed to identify the novel cancer-specific genes. Here, we conducted an analytical comparison between Bowtie2, a Burrows-Wheeler transform-based alignment tool, and Kallisto, which adopts pseudo alignment based on a transcriptome de Bruijn graph using mRNA sequencing data on normal cells and lung/liver cancer tissues. Before using cancer data, simulated mRNA sequencing reads were generated, and the high Transcripts Per Million (TPM) values were compared. mRNA sequencing reads data on lung/liver cancer cells were also extracted and quantified. While Kallisto could directly give the output in TPM values, Bowtie2 provided the counts. Thus, TPM values were calculated by processing the Sequence Alignment Map (SAM) file in R using package Rsubread and subsequently in python. The analysis of the simulated sequencing data revealed that Kallisto could detect more transcripts and had a higher overlap over Bowtie2. The evaluation of these two data processing methods using the known lung cancer biomarkers concludes that in standard settings without any dedicated quality control, Kallisto is more effective at producing faster and more accurate results than Bowtie2. Such conclusions were also drawn and confirmed with the known biomarkers specific to liver cancer.

• Journal of East Asia Management
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• v.3 no.1
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• pp.11-23
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• 2022

Under the circumstances of China's slower economic growth, the first document ofthe central committee of the CPC continue to focus on "three agricultures" problems, agriculture play a basic role on China's economic. Since 2007, the first document directly stresses the important role of agricultural and fisheries every year. Central Government Working Report of 2015 also stresses that under the new normal of economy, it is important to improve quality and efficiency of agriculture. Agricultural focus going forward will be on improving capacity of competitiveness, innovation and sustainable development.The fishery as an important part of agriculture plays a vital role in the protection of national food security, the prosperity of the rural economy and the optimization of national food structure. However, the situation faced on accelerating the speed of Chinese fisheries is still grim. As an important fishery breeding city in my country, Weihai has achieved remarkable results in the development of fisheries. Based on the input-output indicators of Weihai City from 2010 to 2020, this article uses the DEA model method to conduct a comprehensive analysis of the factors affecting the fishery production efficiency in Weihai City. This paper calculates the two stages of comprehensive efficiency, pure technical efficiency and scale efficiency, and comprehensive compares the two stages. The research results show that: From 2010 to 2020, the average comprehensive technical efficiency of Weihai fishery was 0.928, the average scale efficiency was 0.963, and the average pure technical efficiency was 0.963. The comprehensive technical efficiency of Weihai fishery production showed an upward and downward trend, the pure technical efficiency showed a downward and then upward trend, and the pure technical efficiency showed a fluctuating trend.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2131-2153
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• 2022

To achieve accurate detection of tuberculosis (TB) areas in chest radiographs, we design a chest X-ray TB area detection algorithm. The algorithm consists of two stages: the chest X-ray TB classification network (CXTCNet) and the chest X-ray TB area detection network (CXTDNet). CXTCNet is used to judge the presence or absence of TB areas in chest X-ray images, thereby excluding the influence of other lung diseases on the detection of TB areas. It can reduce false positives in the detection network and improve the accuracy of detection results. In CXTCNet, we propose a channel attention mechanism (CAM) module and combine it with DenseNet. This module enables the network to learn more spatial and channel features information about chest X-ray images, thereby improving network performance. CXTDNet is a design based on a sparse object detection algorithm (Sparse R-CNN). A group of fixed learnable proposal boxes and learnable proposal features are using for classification and location. The predictions of the algorithm are output directly without non-maximal suppression post-processing. Furthermore, we use CLAHE to reduce image noise and improve image quality for data preprocessing. Experiments on dataset TBX11K show that the accuracy of the proposed CXTCNet is up to 99.10%, which is better than most current TB classification algorithms. Finally, our proposed chest X-ray TB detection algorithm could achieve AP of 45.35% and AP50 of 74.20%. We also establish a chest X-ray TB dataset with 304 sheets. And experiments on this dataset showed that the accuracy of the diagnosis was comparable to that of radiologists. We hope that our proposed algorithm and established dataset will advance the field of TB detection.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.279-285
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• 2022

In this paper, as a liberal arts course for non-majors, we developed a basic practice case for convolutional neural networks, which is essential for designing a basic convolutional neural network course curriculum. The developed practice case focuses on understanding the working principle of the convolutional neural network and uses a spreadsheet to check the entire visualized process. The developed practice case consisted of generating supervised learning method image training data, implementing the input layer, convolution layer (convolutional layer), pooling layer, and output layer sequentially, and testing the performance of the convolutional neural network on new data. By extending the practice cases developed in this paper, the number of images to be recognized can be expanded, or basic practice cases can be made to create a convolutional neural network that increases the compression rate for high-quality images. Therefore, it can be said that the utility of this convolutional neural network basic practice case is high.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.312-334
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• 2023

In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.

• Economic Analysis
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• v.26 no.2
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• pp.43-71
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• 2020

This paper aims to derive macroeconomic implications by analyzing the business cycle characteristics of the youth unemployment. The results of empirical analysis seem to show that youth unemployment appears to be relatively less correlated with business cycle compared to other age groups, and thus it is difficult to explain the recent steady increase in the potential labor force as a result of the business cycle fluctuation alone. Moreover, the alternative unemployment measures of the youth group showing upward trend were estimated to be co-integrated with output measures. This co-integrated trend increase suggests that unlike other age groups, youth may be influenced by structural factors inherent in Korea's economic growth path. The fact that the wage difference based on firm size has widened steadily since the Asian financial crisis and that the proportion of large companies that provide relatively high-quality jobs compared to major industrialized countries is significantly lower may be the evidence of the structural changes in Korean youth labor market. The results of above analysis may explain why the job search periods for youth has lengthened amid these structural changes.