다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Much has been written about theory and practice in the law, and the tension between practitioners and theorists. Judges do not cite theoretical articles often; they rarely "apply" theories to particular cases. These arguments are not revisited. Instead the Essay explores the working and interaction of theory and practice, practitioners and theorists. The Essay starts with a story about solving a legal issue using our intellectual tools - theory, practice, and their progenies: experience and "gut." Next the Essay elaborates on the nature of theory, practice, experience and "gut." The third part of the Essay discusses theories that are helpful to practitioners and those that are less helpful. The Essay concludes that practitioners theorize, and theorists practice. They use these intellectual tools differently because the goals and orientations of theorists and practitioners, and the constraints under which they act, differ. Theory, practice, experience and "gut" help us think, remember, decide and create. They complement each other like the two sides of the same coin: distinct but inseparable.

Of Theory and Practice

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Process Control: A Practical Approach

Steganography is the technique for exchanging concealed secret information in a way to avoid suspicion. The aim of Steganography is to transfer secrete message to another party by hiding the data in a cover object, so that the imposter who monitors the traffic should not distinguish between genuine secret message and the cover object. This paper presents the comparative study and performance analysis of different image Steganography methods using various types of cover media ((like BMP/JPEG/PNG etc.) with the discussion of their file formats. We also discuss the embedding domains along with a discussion on salient technical properties, applications, limitations, and Steganalysis.

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A Comparative Study of Recent Steganography Techniques for Multiple Image Formats

Centralized publishing of big location data provides great convenience for various location-based interactive queries and services. Privacy protection of users' location information is an indispensable issue in the security of big data applications. Partition publishing is an effective way to release statistical information of two-dimensional big location data. By combining with the differential privacy model, it can provide more accurate range counting query service on the premise of ensuring location privacy. In order to further improve the availability of location data subsequent to centralized publishing, this paper analyzes the primary noise sources of partition publishing and discusses the constraints among publishing errors, the spatial partition structure, and privacy budget allocation. An unbalanced quadtree partition algorithm based on regional uniformity is proposed. Accordingly, the gradient privacy budget allocation scheme and adjustment method are designed to ensure the effectiveness of the differential privacy model. Experimental comparison of the real-world datasets proves the advantages of the proposed algorithm in improving the querying accuracy of the published data.

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Differential private spatial decomposition and location publishing based on unbalanced quadtree partition algorithm

Visual-based Unmanned Aerial Vehicles (UAVs) (e.g. equipped with an optical camera) have become more popular in daily life, because of their flexibility and convenience in capturing images&#x002F;videos. Existing works mainly focus on the image&#x002F;video capturing efficiency, but overlook the privacy violations that may be caused by the misuse of UAVs. In this paper, we study the Privacy Preserving Navigation (PPN) problem of the path planning of a UAV in 3D space to cover a 2D Target Area (TA), so that TA is covered while the privacy of sub-areas within TA is violated. We prove the PPN is NP-hard and propose a heuristic solution to PPN. The real word data trace driven emulation results show our solution is effective.

An Unmanned Aerial Vehicle Navigation Mechanism with Preserving Privacy

As a representative model for privacy preserving data publishing, K-anonymity has raised a considerable number of questions for researchers over the past few decades. Among them, how to achieve data release without sacrificing the users’ privacy and how to maximize the availability of published data is the ultimate goal of privacy preserving data publishing. In order to enhance the clustering effect and reduce the unnecessary computation, this paper proposes a weighted K-member clustering algorithm. A series of weight indicators are designed to evaluate the outlyingness of records, distance between records, and information loss of the published data. The proposed algorithm can reduce the influence of outliers on the clustering effect and maintain the availability of data to the best possible extent during the clustering process. Experimental analysis suggests that the proposed method generates lower information loss, improves the clustering effect, and is less sensitive to outliers as compared with some existing methods.

A weighted K-member clustering algorithm for K-anonymization

Dummy is one of the main methods used to protect location privacy. In existing methods, the efficiency of dummy generation is low, and the geographical semantic information of location is not fully taken into account. In order to solve these problems, a k -anonymous location privacy protection method of dummy based on geographical semantics was proposed in this paper. Firstly, the location data set in the rectangle region containing the real location is obtained from WiFi APs. Secondly, adopting the multicenter clustering algorithm based on max-min distance, some locations are selected. Its geographical distance between them is the farthest, and a candidate set of dummies is generated. Finally, by calculating the edit-distance between geographic name’s information of locations, the semantic similarity between any two locations in the candidate set is obtained, and k -1 locations with the minimum semantic similarity are selected as dummies. Experimental results show that the proposed method can ensure the physical dispersion and semantic diversity of locations, as well as the improvement of the efficiency of dummy generation. Meanwhile, the balance between privacy protection security and query service quality is achieved.

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A k-anonymous Location Privacy Protection Method of Dummy Based on Geographical Semantics.

With the constant expansion of vehiclescale and the continuous development of Internet of Vehicles, the network environment of the data resource of Internet of Vehicles is becoming more and more complex. Traditional access control models have been difficult to meet the requirements of various access control conditions and dynamic adaptive adjustment of access control strategy. Aimed at the problem of adaptive access control model of vehicular network big data environment, XACML powerful ability of expressing access strategy is used in the paper, and we conduct the risk quantification based on 10 counts of risk factors, risk threshold and risk quota mechanism are also used for risk management. Experimental verification indicated that the risk adaptive access control model is effective, the research results will have great significance for promoting the application research of Internet of Vehicles and its safety technology and improving people’s quality of life.

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Yan Yan

Papers

Differential private spatial decomposition and location publishing based on unbalanced quadtree partition algorithm

An Unmanned Aerial Vehicle Navigation Mechanism with Preserving Privacy

A weighted K-member clustering algorithm for K-anonymization

A k-anonymous Location Privacy Protection Method of Dummy Based on Geographical Semantics.

Adaptive Access Control Model of Vehicular Network Big Data Based on XACML and Security Risk.