• Title/Summary/Keyword: And Location Environments

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An Analysis of Factors Affecting Fear of Crime Considering Geographical Characteristics - Focused on Women in 20's who are Vulnerable to Crime - (지리적 특성을 고려한 범죄두려움 영향 요인 분석 - 범죄취약계층인 20대 여성을 중심으로 -)

  • Byun, Gidong;Ha, Mi-kyoung
    • Journal of the Architectural Institute of Korea Planning & Design
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    • v.36 no.5
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    • pp.23-32
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    • 2020
  • Recently, women's fear of crime continues to increase in space of everyday. By the way, the fear of crime has the spatial properties as crime. Therefore, The purpose of this study is to evaluate the spatial dependence of fear of crime and to suggest the physical environmental factors influencing fear of crime. For this, a spatial regression analysis using spatial weights was conducted based on the location data of the fear of crime measured through a survey. The results of this study are as follows; First, the fear of crime felt by women in their twenties who are vulnerable to crime has spatial dependence. Therefore, it is necessary to consider the spatial characteristics in analyzing the environmental factors affecting this. Second, in order to reduce the fear of crime, it is necessary to improve the environments of old housing and entertainment facilities. There is also a need for ongoing management. Third, careful consideration is needed in the installation of CCTV and street lights, which are factors influencing the fear of crime. It is necessary to establish a reasonable arrangement standard for CCTV and to analyze the street lighting in detail.

A Cell-based Indexing for Managing Current Location Information of Moving Objects (이동객체의 현재 위치정보 관리를 위한 셀 기반 색인 기법)

  • Lee, Eung-Jae;Lee, Yang-Koo;Ryu, Keun-Ho
    • The KIPS Transactions:PartD
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    • v.11D no.6
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    • pp.1221-1230
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    • 2004
  • In mobile environments, the locations of moving objects such as vehicles, airplanes and users of wireless devices continuously change over time. For efficiently processing moving object information, the database system should be able to deal with large volume of data, and manage indexing efficiently. However, previous research on indexing method mainly focused on query performance, and did not pay attention to update operation for moving objects. In this paper, we propose a novel moving object indexing method, named ACAR-Tree. For processing efficiently frequently updating of moving object location information as well as query performance, the proposed method is based on fixed grid structure with auxiliary R-Tree. This hybrid structure is able to overcome the poor update performance of R-Tree which is caused by reorganizing of R-Tree. Also, the proposed method is able to efficiently deal with skewed-. or gaussian distribution of data using auxiliary R-Tree. The experimental results using various data size and distribution of data show that the proposed method has reduced the size of index and improve the update and query performance compared with R-Tree indexing method.

Mobile IP User Mobility Model for Effective Mobility Management Accommodating Heterogeneous Networks under Cognitive Networking Environments (이종 네트워크간의 효과적 이동성 수용을 위한 이동 IP 네트워크 사용자 이동성 모델)

  • Cheon, Eun-Ji;Kim, Jeong-Ho
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.49 no.6
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    • pp.90-97
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    • 2012
  • In this paper, the new user mobility model which can be utilized to register user's location for interworking with heterogeneous overlay convergent networks under the time-varying radio propagation environment has been proposed. Thus the user mobility model is considered in order to evaluate the behaviors of users in the overlay convergent networks. This Mobile IP user mobility model will be very useful to model the user mobility behaviors and can be used to estimate the signaling traffic and frequency spectrum demands for massive data transfer for the heterogeneous overlay convergent networks.

Primary user localization using Bayesian compressive sensing and path-loss exponent estimation for cognitive radio networks

  • Anh, Hoang;Koo, Insoo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.10
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    • pp.2338-2356
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    • 2013
  • In cognitive radio networks, acquiring the position information of the primary user is critical to the communication of the secondary user. Localization of primary users can help improve the efficiency with which the spectrum is reused, because the information can be used to avoid harmful interference to the network while simultaneity is exploited to improve the spectrum utilization. Despite its inherent inaccuracy, received signal strength based on range has been used as the standard tool for distance measurements in the location detection process. Most previous works have employed the path-loss propagation model with a fixed value of the path loss exponent. However, in actual environments, the path loss exponent for each channel is different. Moreover, due to the complexity of the radio channel, when the number of channel increases, a larger number of RSS measurements are needed, and this results in additional energy consumption. In this paper, to overcome this problem, we propose using the Bayesian compressive sensing method with a calibrated path loss exponent to improve the performance of the PU localization method.

Spatio-Temporal Index Structure for Trajectory Queries of Moving Objects in Video (비디오에서 이동 객체의 궤적 검색을 위한 시공간 색인구조)

  • Lee, Nak-Gyu;Bok, Kyoung-Soo;Yoo, Jae-Soo;Cho, Ki-Hyung
    • The KIPS Transactions:PartD
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    • v.11D no.1
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    • pp.69-82
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    • 2004
  • A moving object has a special feature that it's spatial location, shape and size are changed as time goes. These changes of the object accompany the continuous movement that is called the trajectory. In this paper, we propose an index structure that users can retrieve the trajectory of a moving object with the access of a page. We also propose the multi-complex query that is a new query type for trajectory retrieval. In order to prove the excellence of our method, we compare and analyze the performance for query time and storage space through experiments in various environments. It is shown that our method outperforms the existing index structures when processing spatio-temporal trajectory queries on moving objects.

Real-time Vehicle Recognition Mechanism using Support Vector Machines (SVM을 이용한 실시간 차량 인식 기법)

  • Chang, Jae-Khun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.7 no.6
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    • pp.1160-1166
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    • 2006
  • The information of vehicle is very important for maintaining traffic order under the present complex traffic environments. This paper proposes a new vehicle plate recognition mechanism that is essential to know the information of vehicle. The proposed method uses SVM which is excellent object classification compare to other methods. Two-class SVM is used to find the location of vehicle plate and multi-class SVM is used to recognize the characters in the plate. As a real-time processing system using multi-step image processing and recognition process this method recognizes several different vehicle plates. Through the experimental results of real environmental image and recognition using the proposed method, the performance is proven.

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An Efficient Spatial Query Processing in Wireless Networks (무선 네트워크 환경에서 효율적인 공간 질의 처리)

  • Song, Doo Hee;Lee, Hye Ri;Park, Kwang Jin
    • KIPS Transactions on Computer and Communication Systems
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    • v.8 no.10
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    • pp.239-244
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    • 2019
  • In recent mobile environments, query processing costs have been rapidly increasing as users request large amounts of queries. In addition, the server's performance is increasing for many users to handle high-capacity queries, but the workload is increasing continuously. To solve these problems, we use the wireless broadcasting environment. However, in a existing wireless broadcasting environment, servers have a problem sending all the objects they manage to their clients. Therefore, we propose a new R-Bcast combining the advantages of demand-based and wireless broadcasting. R-Bcast is a technique that protects query information and reduces query processing time. Experiments have proved that R-Bcast is superior to conventional techniques.

Mobile Agent Middleware for Travel Information Service (여행정보 서비스를 위한 모바일에이전트 미들웨어)

  • Kang, Gi-Soon;Yoon, Yong-Ik
    • Journal of Korea Spatial Information System Society
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    • v.6 no.2 s.12
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    • pp.85-95
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    • 2004
  • Nowadays, the interests in travel are increasing with the changes into the ubiquitous computing environments, hence, our location-based travel information service system would be potentially invaluable to graft the Internet business models. Most of existing travel information services are provided in a one-way push manner from the contents providers to users, and they have drawbacks of enforcing users to search their needed information with the general Web surfing. Therefore, this paper propose the travel information system for gathering user information and for providing services that satisfy user requirements by filtering based on these information.

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Mechanism of RFID Authentication for u-Vehicle (u-Vehicle 환경에 적합한 RFID 인증 메커니즘)

  • Rhee, Yoon-Jung;Kim, Do-Hyeon
    • The Journal of the Korea Contents Association
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    • v.8 no.6
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    • pp.66-73
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    • 2008
  • The concept of u-Vehicle is a technological model that people try to build the ubiquitous world in the car which moves, by using the RFID technology as well as the telematics service based on the location. RFID is weak on the point of information security because RFID has possibility for being abused such as chasing, counterfeiting, and invading personal privacy. RFID's tags use a weak cryptographic algorithm. This paper presents the vulnerabilities of information security under u-Vehicle environments. To solve that, we propose a mechanism enhancing RFID tag's security but with low cost by reducing the number of mutual authentication stages and using the hash function.

A Modified Residual-based Extended Kalman Filter to Improve the Performance of WiFi RSSI-based Indoor Positioning (와이파이 수신신호세기를 사용하는 실내위치추정의 성능 향상을 위한 수정된 잔차 기반 확장 칼만 필터)

  • Cho, Seong Yun
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.7
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    • pp.684-690
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    • 2015
  • This paper presents a modified residual-based EKF (Extended Kalman Filter) for performance improvement of indoor positioning using WiFi RSSI (Received Signal Strength Indicator) measurement. Radio signal strength in indoor environments may have irregular attenuation characteristics due to obstacles such as walls, furniture, etc. Therefore, the performance of the RSSI-based positioning with the conventional trilateration method or Kalman filter is insufficient to provide location-based accurate information services. In order to enhance the performance of indoor positioning, in this paper, error analysis of the distance calculated by using the WiFi RSSI measurement is performed based on the radio propagation model. Then, an IARM (Irregularly Attenuated RSSI Measurement) error is defined. Also, it shows that the IARM error is included in the residual of the positioning filter. The IARM error is always positive. So, it is presented that the IARM error can be estimated by taking the absolute value of the residual. Consequently, accurate positioning can be achieved based on the IEM (IARM Error Mitigated) EKF with the residual modified by using the estimated IARM error. The performance of the presented IEM EKF is verified experimentally.