• Title/Summary/Keyword: Location based system

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Evaluation of Computed Tomography and Magnetic Resonance Imaging of Sinonasal Inverted Papilloma (비부비동 반전성 유두종의 전산화 단층촬영상과 자기공명영상의 분석)

  • Bai, Chang-Hoon;Seo, Young-Jung;Lee, Seok-Choon;Chen, Seung-Min;Baek, Un-Hoi;Jung, Eun-Chae;Song, Si-Youn;Kim, Yong-Dae
    • Journal of Yeungnam Medical Science
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    • v.22 no.2
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    • pp.191-198
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    • 2005
  • Background: Computed tomography (CT) is commonly used to evaluate the degree of sinus involvement in cases of inverted papilloma (IP). However, CT cannot differentiate tumor from adjacent inflammatory mucosa or retained secretions. By contrast, magnetic resonance imaging (MRI) has been reported to be useful in distinguishing IP from paranasal sinusitis. This study investigated whether preoperative assessment with MRI and CT accurately predict the extent of IP.1) Materials and methods: CT and MRI were retrospectively reviewed in 9 cases of IP. Patients were categorized into stages based on CT and MRI findings, according to the staging system proposed by Krouse. The involvement of IP in each sinus was also assessed. Results: Differentiation of IP from inflammatory disease may be more successful in routine cases where the inflammatory mucosa has low signal intensity on T1-weighted images and very high signal intensity on T2-weighted images. CT imaging could not differentiate tumor from adjacent inflammatory mucosa or retained secretions. Conclusion: Preoperative MRI of IP can predict the location and extent of the tumor involvement in the paranasal sinuses and sometimes predicts malignant changes.

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Correlations and Comparison among Swallowing Function, Dietary Level, Cognitive Function, Daily Living according to Characteristic in Stroke Patients with Dysphagia (삼킴장애가 있는 뇌졸중 환자의 특성에 따른 삼킴기능, 식이수준, 인지기능, 일상생활의 비교 및 상관관계)

  • Moon, Jong Hoon;Kim, Kye Ho;Won, Young Sik
    • 재활복지
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    • v.20 no.4
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    • pp.265-281
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    • 2016
  • This study was to investigate the correlation among swallowing function, dietary level, cognitive function, daily living, and comparison for general characteristics in stroke patients with dysphagia. Subjects of this study participated to 56 stroke patients with dysphagia. Outcome measures is evaluated by Functional Dysphagia Scale(FDS), and Amerian Speech-Language-Hearing Association National Outcomes Measurements System(ASHA NOMS), and Korean Mini-Mental State Examination(K-MMSE), and Korean Modified Barthel Index(K-MBI). Collected all data analyezed to independent t test for four assessments, and general characteristics of study subjects analyzed by pearson correlation coefficient for four assessments. Results of study, swallowing function according to lesion location differed significantly(p<.05). Cognitive function according to onset duration differed significantly(p<.05). Age of subjects and dietary level, cognitive function showed a significant correlation(p<.05). Swallowing function and dietary level, cognitive function showed a significant correlation(p<.05). Cognitive function and dietary level, daily living showed a significant correlation(p<.05). Based on current results, we suggest that swallowing rehabilitation for stroke patients with dysphagia performed with consideration for cognitive function and characteristic of patients.

Efficiency in the Provision of Employment Services for the Middle-aged: an Application of Spatial Analysis Using GIS (GIS 공간분석을 활용한 중장년 고용지원서비스 공급의 효율성 분석)

  • YI, Yoojin;LEE, Sang-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.1
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    • pp.78-92
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    • 2019
  • This study aims to evaluate the efficiency in the provision of employment services for the middle-aged by using spatial analysis in GIS. Based on location information of employment service institutions, we find service areas of the institutions and calculate regional rates of duplication and exclusion in terms of spatial coverage of the employment services. Taking into account potential demand for employment services, the regions with high priority in the provision of the services are identified. Among the regions, those with high exclusion rate of the services are designated as the regions of insufficient service level. Results indicate that Namyangju-si is a representative region of insufficient employment service level. To improve efficiency in the provision of employment services, we suggest to relocate employment service institutions that have been located in a region of high duplication rate such as Siheung-si, Danwon-gu, Gangnam-gu, Songpa-gu into the locality of Namyangju-si.

Secure Mutual Authentication Protocol for RFID System without Online Back-End-Database (온라인 백-엔드-데이터베이스가 없는 안전한 RFID 상호 인증 프로토콜)

  • Won, Tae-Youn;Yu, Young-Jun;Chun, Ji-Young;Byun, Jin-Wook;Lee, Dong-Hoon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.20 no.1
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    • pp.63-72
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    • 2010
  • RFID is one of useful identification technology in ubiquitous environments which can be a replacement of bar code. RFID is basically consisted of tag, reader, which is for perception of the tag, and back-end-database for saving the information of tags. Although the usage of mobile readers in cellular phone or PDA increases, related studies are not enough to be secure for practical environments. There are many factors for using mobile leaders, instead of static leaders. In mobile reader environments, before constructing the secure protocol, we must consider these problems: 1) easy to lose the mobile reader 2) hard to keep the connection with back-end-database because of communication obstacle, the limitation of communication range, and so on. To find the solution against those problems, Han et al. suggest RFID mutual authentication protocol without back-end-database environment. However Han et al.'s protocol is able to be traced tag location by using eavesdropping, spoofing, and replay attack. Passive tag based on low cost is required lots of communication unsuitably. Hence, we analyze some vulnerabilities of Han et al.'s protocol and suggest RFID mutual authentication protocol without online back-end-database in aspect of efficiency and security.

Status of Groundwater Potential Mapping Research Using GIS and Machine Learning (GIS와 기계학습을 이용한 지하수 가능성도 작성 연구 현황)

  • Lee, Saro;Fetemeh, Rezaie
    • Korean Journal of Remote Sensing
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    • v.36 no.6_1
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    • pp.1277-1290
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    • 2020
  • Water resources which is formed of surface and groundwater, are considered as one of the pivotal natural resources worldwide. Since last century, the rapid population growth as well as accelerated industrialization and explosive urbanization lead to boost demand for groundwater for domestic, industrial and agricultural use. In fact, better management of groundwater can play crucial role in sustainable development; therefore, determining accurate location of groundwater based groundwater potential mapping is indispensable. In recent years, integration of machine learning techniques, Geographical Information System (GIS) and Remote Sensing (RS) are popular and effective methods employed for groundwater potential mapping. For determining the status of the integrated approach, a systematic review of 94 directly relevant papers were carried out over the six previous years (2015-2020). According to the literature review, the number of studies published annually increased rapidly over time. The total study area spanned 15 countries, and 85.1% of studies focused on Iran, India, China, South Korea, and Iraq. 20 variables were found to be frequently involved in groundwater potential investigations, of which 9 factors are almost always present namely slope, lithology (geology), land use/land cover (LU/LC), drainage/river density, altitude (elevation), topographic wetness index (TWI), distance from river, rainfall, and aspect. The data integration was carried random forest, support vector machine and boost regression tree among the machine learning techniques. Our study shows that for optimal results, groundwater mapping must be used as a tool to complement field work, rather than a low-cost substitute. Consequently, more study should be conducted to enhance the generalization and precision of groundwater potential map.

A Study on the Regional Economic Revitalization Plan in Henan Province, China under 'One Belt and One Road' - Focusing on '5 Region' and '4 Road' ('일대일로' 하에 중국 허난성의 지역 경제 활성화 방안에 관한 연구 - '5 지역'과 '4 로'를 중심으로)

  • Wang, Kun;Zhang, Yizhou;Bae, Ki-Hyung
    • The Journal of the Korea Contents Association
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    • v.21 no.8
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    • pp.424-441
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    • 2021
  • The research is to analyze current situation of the coordinated development of "5 Region" and "4 Road" in Henan Province and put forward problems about the coordinated development of the "5 Region" and "4 Road" with the inland geographical location in China by drawing on the experience of the coordinated development of related industries in developed countries and regions based on China's "One Belt And One Road". According to the problems, a plan for the promotion of opening up to the outside world is provided. Through research, the following problems are found: First, the superposition advantage of five districts' and "four roads' has not been fully brought into play. Second, the collaborative linkage mechanism is not sound. Third, modern comprehensive transportation hub facilities are not fully completed. Fourth, the industrial support capacity is insufficient. Fifth, basic support is difficult to meet the needs of future development. The plan is as follows: First, building a top-level strategic platform and improve the policy support system. Second, we need to enhance the advantages of the four Silk Roads and accelerate their interconnected development. Third, establishing a coordination and mutual assistance mechanism to stimulate the superposition effect of industrial clusters. The significance of this study is that it can be used as research data to predict the future direction of China's "One Belt and One Road" policy and enlightenment to stimulate the economic revitalization of inland provinces.

A Study on Creation of Secure Storage Area and Access Control to Protect Data from Unspecified Threats (불특정 위협으로부터 데이터를 보호하기 위한 보안 저장 영역의 생성 및 접근 제어에 관한 연구)

  • Kim, Seungyong;Hwang, Incheol;Kim, Dongsik
    • Journal of the Society of Disaster Information
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    • v.17 no.4
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    • pp.897-903
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    • 2021
  • Purpose: Recently, ransomware damage that encrypts victim's data through hacking and demands money in exchange for releasing it is increasing domestically and internationally. Accordingly, research and development on various response technologies and solutions are in progress. Method: A secure storage area and a general storage area were created in the same virtual environment, and the sample data was saved by registering the access process. In order to check whether the stored sample data is infringed, the ransomware sample was executed and the hash function of the sample data was checked to see if it was infringed. The access control performance checked whether the sample data was accessed through the same name and storage location as the registered access process. Result: As a result of the experiment, the sample data in the secure storage area maintained data integrity from ransomware and unauthorized processes. Conclusion: Through this study, the creation of a secure storage area and the whitelist-based access control method are evaluated as suitable as a method to protect important data, and it is possible to provide a more secure computing environment through future technology scalability and convergence with existing solutions.

The Effect of Ground Heterogeneity on the GPR Signal: Numerical Analysis (지반의 불균질성이 GPR탐사 신호에 미치는 영향에 대한 수치해석적 분석)

  • Lee, Sangyun;Song, Ki-il;Ryu, Heehwan;Kang, Kyungnam
    • Journal of the Korean GEO-environmental Society
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    • v.23 no.8
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    • pp.29-36
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    • 2022
  • The importance of subsurface information is becoming crucial in urban area due to increase of underground construction. The position of underground facilities should be identified precisely before excavation work. Geophyiscal exporation method such as ground penetration radar (GPR) can be useful to investigate the subsurface facilities. GPR transmits electromagnetic waves to the ground and analyzes the reflected signals to determine the location and depth of subsurface facilities. Unfortunately, the readability of GPR signal is not favorable. To overcome this deficiency and automate the GPR signal processing, deep learning technique has been introduced recently. The accuracy of deep learning model can be improved with abundant training data. The ground is inherently heteorogeneous and the spacially variable ground properties can affact on the GPR signal. However, the effect of ground heterogeneity on the GPR signal has yet to be fully investigated. In this study, ground heterogeneity is simulated based on the fractal theory and GPR simulation is carried out by using gprMax. It is found that as the fractal dimension increases exceed 2.0, the error of fitting parameter reduces significantly. And the range of water content should be less than 0.14 to secure the validity of analysis.

Comparison of Semantic Segmentation Performance of U-Net according to the Ratio of Small Objects for Nuclear Activity Monitoring (핵활동 모니터링을 위한 소형객체 비율에 따른 U-Net의 의미론적 분할 성능 비교)

  • Lee, Jinmin;Kim, Taeheon;Lee, Changhui;Lee, Hyunjin;Song, Ahram;Han, Youkyung
    • Korean Journal of Remote Sensing
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    • v.38 no.6_4
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    • pp.1925-1934
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    • 2022
  • Monitoring nuclear activity for inaccessible areas using remote sensing technology is essential for nuclear non-proliferation. In recent years, deep learning has been actively used to detect nuclear-activity-related small objects. However, high-resolution satellite imagery containing small objects can result in class imbalance. As a result, there is a performance degradation problem in detecting small objects. Therefore, this study aims to improve detection accuracy by analyzing the effect of the ratio of small objects related to nuclear activity in the input data for the performance of the deep learning model. To this end, six case datasets with different ratios of small object pixels were generated and a U-Net model was trained for each case. Following that, each trained model was evaluated quantitatively and qualitatively using a test dataset containing various types of small object classes. The results of this study confirm that when the ratio of object pixels in the input image is adjusted, small objects related to nuclear activity can be detected efficiently. This study suggests that the performance of deep learning can be improved by adjusting the object pixel ratio of input data in the training dataset.

A Ship-Wake Joint Detection Using Sentinel-2 Imagery

  • Woojin, Jeon;Donghyun, Jin;Noh-hun, Seong;Daeseong, Jung;Suyoung, Sim;Jongho, Woo;Yugyeong, Byeon;Nayeon, Kim;Kyung-Soo, Han
    • Korean Journal of Remote Sensing
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    • v.39 no.1
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    • pp.77-86
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    • 2023
  • Ship detection is widely used in areas such as maritime security, maritime traffic, fisheries management, illegal fishing, and border control, and ship detection is important for rapid response and damage minimization as ship accident rates increase due to recent increases in international maritime traffic. Currently, according to a number of global and national regulations, ships must be equipped with automatic identification system (AIS), which provide information such as the location and speed of the ship periodically at regular intervals. However, most small vessels (less than 300 tons) are not obligated to install the transponder and may not be transmitted intentionally or accidentally. There is even a case of misuse of the ship'slocation information. Therefore, in this study, ship detection was performed using high-resolution optical satellite images that can periodically remotely detect a wide range and detectsmallships. However, optical images can cause false-alarm due to noise on the surface of the sea, such as waves, or factors indicating ship-like brightness, such as clouds and wakes. So, it is important to remove these factors to improve the accuracy of ship detection. In this study, false alarm wasreduced, and the accuracy ofship detection wasimproved by removing wake.As a ship detection method, ship detection was performed using machine learning-based random forest (RF), and convolutional neural network (CNN) techniquesthat have been widely used in object detection fieldsrecently, and ship detection results by the model were compared and analyzed. In addition, in this study, the results of RF and CNN were combined to improve the phenomenon of ship disconnection and the phenomenon of small detection. The ship detection results of thisstudy are significant in that they improved the limitations of each model while maintaining accuracy. In addition, if satellite images with improved spatial resolution are utilized in the future, it is expected that ship and wake simultaneous detection with higher accuracy will be performed.