• Title/Summary/Keyword: classification technique

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A Survey of System Architectures, Privacy Preservation, and Main Research Challenges on Location-Based Services

  • Tefera, Mulugeta K.;Yang, Xiaolong;Sun, Qifu Tyler
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.6
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    • pp.3199-3218
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    • 2019
  • Location-based services (LBSs) have become popular in recent years due to the ever-increasing usage of smart mobile devices and mobile applications through networks. Although LBS application provides great benefits to mobile users, it also raises a sever privacy concern of users due to the untrusted service providers. In the lack of privacy enhancing mechanisms, most applications of the LBS may discourage the user's acceptance of location services in general, and endanger the user's privacy in particular. Therefore, it is a great interest to discuss on the recent privacy-preserving mechanisms in LBSs. Many existing location-privacy protection-mechanisms (LPPMs) make great efforts to increase the attacker's uncertainty on the user's actual whereabouts by generating a multiple of fake-locations together with user's actual positions. In this survey, we present a study and analysis of existing LPPMs and the state-of-art privacy measures in service quality aware LBS applications. We first study the general architecture of privacy qualification system for LBSs by surveying the existing framework and outlining its main feature components. We then give an overview of the basic privacy requirements to be considered in the design and evaluation of LPPMs. Furthermore, we discuss the classification and countermeasure solutions of existing LPPMs for mitigating the current LBS privacy protection challenges. These classifications include anonymization, obfuscation, and an encryption-based technique, as well as the combination of them is called a hybrid mechanism. Finally, we discuss several open issues and research challenges based on the latest progresses for on-going LBS and location privacy research.

Analysis of Urban Agricultural Effects by Factors According to the Urban Citizens Income Level: Socially Sustainable Effect, Negative Effect, and Economically Sustainable Effect

  • Hong, In Kyoung;Chae, Young;Jang, Yoonah;Lee, Sang-Mi;Su, Jung Nam
    • Journal of People, Plants, and Environment
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    • v.21 no.6
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    • pp.461-471
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    • 2018
  • The role of urban agriculture should not be limited as a small-scale crop cultivation activity as it was, but it has to be considered as an entire process of a agriculture activity for the restoration of the city community. This study is based on the assumption that there has been a significant change in urban lifestyle and urban farming preference, considering the overall improvement in standard of living after implementation of five day work week system. It was conducted for urban citizens who were interested in actual urban agriculture for ages 19 and over who visited the Korea Urban Agriculture Exhibition in 2018. Only 115 valid samples were used for the empirical analysis. To analyze the demographic characteristics and effects of urban agriculture, frequency analysis and descriptive statistics were conducted. In order to analyze the reliability and validity of the measurement variables of the effect, the variables that deteriorate the validity were removed and 15 variables of the urban agricultural effect were selected. According to the result of factor analysis, three factors were extracted as follows: socially sustainable effect, negative effect and economically sustainable effect. In order to examine the effects of urban agriculture depending on income level, the one-way ANOVA, which is a statistical technique for verifying differences in the sample means, was performed. The psychological stability of people, the recovery of humanity through communion with nature, and the vitalization of agriculture linked with local agriculture had significant correlations with income level. The negative effect showed no significant correlation with income level. The improvement of the local environment was found to have an impact in relation with income level. We expect that there will be more studies on policies for the new types and models of urban agriculture in order to make it easier for urban citizens to approach it.

Improvement of KOMPSAT-5 Image Resolution for Target Analysis (객체 분석을 위한 KOMPSAT-5 영상의 해상도 향상 성능 분석)

  • Lee, Seung-Jae;Chae, Tae-Byeong
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.30 no.4
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    • pp.275-281
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    • 2019
  • A synthetic aperture radar(SAR) satellite is more effective than an optical satellite for target analysis because an SAR satellite can provide two-dimensional electromagnetic scattering distribution of a target during all-weather and day-and-night operations. To conduct target analysis while considering the earth observation interval of an SAR satellite, observing a specific area as wide as possible would be advantageous. However, wider the observation area, worse is the resolution of the associated SAR satellite image. Although conventional methods for improving the resolution of radar images can be employed for addressing this issue, few studies have been conducted for improving the resolution of SAR satellite images and analyzing the performance. Hence, in this study, the applicability of conventional methods to SAR satellite images is investigated. SAR target detection was first applied to Korea Multipurpose Satellite-5(KOMPSAT-5) SAR images provided by Korea Aerospace Research Institute for extracting target responses. Extrapolation, RELAX, and MUSIC algorithms were subsequently applied to the target responses for improving the resolution, and the corresponding performance was thereby analyzed.

Minimally Invasive Percutaneous Plate Osteosynthesis via a Deltoid-splitting Approach with Strut Allograft for the Treatment of Displaced 3- or 4-part Proximal Humeral Fractures

  • Noh, Young-Min;Kim, Dong Ryul;Kim, Chul-Hong;Lee, Seung Yup
    • Clinics in Shoulder and Elbow
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    • v.21 no.4
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    • pp.220-226
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    • 2018
  • Background: This study introduces a surgical technique with good clinical outcome useful in the treatment of osteoporotic displaced 3- or 4-part proximal humeral fractures. Methods: From May 2014 to February 2016, 16 patients with displaced 3- or 4-part proximal humeral fractures were treated by application of a locking plate with an endosteal strut allograft via a deltoid splitting approach with a minimum follow-up of 12 months. The allograft was inserted through a fractured gap of the greater tuberosity to support the humeral head and then fixed by a locking plate with meticulous soft tissue dissection to protect the axillary nerve. Surgical outcomes were evaluated by the American Shoulder and Elbow Surgeons (ASES) and visual analogue scale (VAS) scores, radiological imaging, and clinical examination. Fixation failure on radiographs was defined as a >$5^{\circ}$ loss of neck shaft angle (NSA) compared to that on an immediate postoperative radiograph. Avascular necrosis (AVN) of the humeral head was also evaluated. Results: In all cases, complete union was achieved. The ASES and VAS scores were improved to $85.4{\pm}2.1$ and $3.2{\pm}1.3$, respectively. Twelve patients (75.0%) had greater than a $5^{\circ}$ change in NSA; the average NSA change was $3.8^{\circ}$. Five patients (31.3%) had unsatisfactory ranges of motion exhibiting a <$100^{\circ}$ active forward flexion. No axillary nerve injuries or AVN were observed at the last follow-up. One patient was converted to reverse total arthroplasty due to severe pain and functional deficit. Conclusions: Minimally invasive fixation via a locking compression plate and an endosteal fibula strut allograft in Neer classification 3-or 4-part fractures with severe osteoporosis in elderly patients can achieve good clinical results.

Estimating the Behavior Path of Seafarer Involved in Marine Accidents by Hidden Markov Model (은닉 마르코프 모델을 이용한 해양사고에 개입된 선원의 행동경로 추정)

  • Yim, Jeong-Bin
    • Journal of Navigation and Port Research
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    • v.43 no.3
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    • pp.160-165
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    • 2019
  • The conduct of seafarer is major cause of marine accidents. This study models the behavior of the seafarer based on the Hidden Markov Model (HMM). Additionally, through the path analysis of the behavior estimated by the model, the kind of situations, procedures and errors that may have caused the marine accidents were interpreted. To successfully implement the model, the seafarer behaviors were observed by means of the summarized verdict reports issued by the Korean Maritime Safety Tribunal, and the observed results converted into behavior data suitable for HMM learning through the behavior classification framework based on the SRKBB (Skill-, Rule-, and Knowledge-Based Behavior). As a result of modeling the seafarer behaviors by the type of vessels, it was established that there was a difference between the models, and the possibility of identifying the preferred path of the seafarer behaviors. Through these results, it is expected that the model implementation technique proposed in this study can be applied to the prediction of the behavior of the seafarer as well as contribute to the prioritization of the behavior correction among seafarers, which is necessary for the prevention of marine accidents.

Surgical prevention of terminal neuroma and phantom limb pain: a literature review

  • Bogdasarian, Ronald N.;Cai, Steven B.;Tran, Bao Ngoc N.;Ignatiuk, Ashley;Lee, Edward S.
    • Archives of Plastic Surgery
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    • v.48 no.3
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    • pp.310-322
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    • 2021
  • The incidence of extremity amputation is estimated at about 200,000 cases annually. Over 25% of patients suffer from terminal neuroma or phantom limb pain (TNPLP), resulting in pain, inability to wear a prosthetic device, and lost work. Once TNPLP develops, there is no definitive cure. Therefore, there has been an emerging focus on TNPLP prevention. We examined the current literature on TNPLP prevention in patients undergoing extremity amputation. A literature review was performed using Ovid Medline, Cochrane Collaboration Library, and Google Scholar to identify all original studies that addressed surgical prophylaxis against TNPLP. The search was conducted using both Medical Subject Headings and free-text using the terms "phantom limb pain," "amputation neuroma," and "surgical prevention of amputation neuroma." Fifteen studies met the inclusion criteria, including six prospective trials, two comprehensive literature reviews, four retrospective chart reviews, and three case series/technique reviews. Five techniques were identified, and each was incorporated into a targetbased classification system. A small but growing body of literature exists regarding the surgical prevention of TNPLP. Targeted muscle reinnervation (TMR), a form of physiologic target reassignment, has the greatest momentum in the academic surgical community, with multiple recent prospective studies demonstrating superior prevention of TNPLP. Neurorrhaphy and transposition with implantation are supported by less robust evidence, but merit future study as alternatives to TMR.

Optimal Ratio of Data Oversampling Based on a Genetic Algorithm for Overcoming Data Imbalance (데이터 불균형 해소를 위한 유전알고리즘 기반 최적의 오버샘플링 비율)

  • Shin, Seung-Soo;Cho, Hwi-Yeon;Kim, Yong-Hyuk
    • Journal of the Korea Convergence Society
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    • v.12 no.1
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    • pp.49-55
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    • 2021
  • Recently, with the development of database, it is possible to store a lot of data generated in finance, security, and networks. These data are being analyzed through classifiers based on machine learning. The main problem at this time is data imbalance. When we train imbalanced data, it may happen that classification accuracy is degraded due to over-fitting with majority class data. To overcome the problem of data imbalance, oversampling strategy that increases the quantity of data of minority class data is widely used. It requires to tuning process about suitable method and parameters for data distribution. To improve the process, In this study, we propose a strategy to explore and optimize oversampling combinations and ratio based on various methods such as synthetic minority oversampling technique and generative adversarial networks through genetic algorithms. After sampling credit card fraud detection which is a representative case of data imbalance, with the proposed strategy and single oversampling strategies, we compare the performance of trained classifiers with each data. As a result, a strategy that is optimized by exploring for ratio of each method with genetic algorithms was superior to previous strategies.

Bias & Hate Speech Detection Using Deep Learning: Multi-channel CNN Modeling with Attention (딥러닝 기술을 활용한 차별 및 혐오 표현 탐지 : 어텐션 기반 다중 채널 CNN 모델링)

  • Lee, Wonseok;Lee, Hyunsang
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.12
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    • pp.1595-1603
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    • 2020
  • Online defamation incidents such as Internet news comments on portal sites, SNS, and community sites are increasing in recent years. Bias and hate expressions threaten online service users in various forms, such as invasion of privacy and personal attacks, and defamation issues. In the past few years, academia and industry have been approaching in various ways to solve this problem The purpose of this study is to build a dataset and experiment with deep learning classification modeling for detecting various bias expressions as well as hate expressions. The dataset was annotated 7 labels that 10 personnel cross-checked. In this study, each of the 7 classes in a dataset of about 137,111 Korean internet news comments is binary classified and analyzed through deep learning techniques. The Proposed technique used in this study is multi-channel CNN model with attention. As a result of the experiment, the weighted average f1 score was 70.32% of performance.

A data extension technique to handle incomplete data (불완전한 데이터를 처리하기 위한 데이터 확장기법)

  • Lee, Jong Chan
    • Journal of the Korea Convergence Society
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    • v.12 no.2
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    • pp.7-13
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    • 2021
  • This paper introduces an algorithm that compensates for missing values after converting them into a format that can represent the probability for incomplete data including missing values in training data. In the previous method using this data conversion, incomplete data was processed by allocating missing values with an equal probability that missing variables can have. This method applied to many problems and obtained good results, but it was pointed out that there is a loss of information in that all information remaining in the missing variable is ignored and a new value is assigned. On the other hand, in the new proposed method, only complete information not including missing values is input into the well-known classification algorithm (C4.5), and the decision tree is constructed during learning. Then, the probability of the missing value is obtained from this decision tree and assigned as an estimated value of the missing variable. That is, some lost information is recovered using a lot of information that has not been lost from incomplete learning data.

A study on the priorities through weight analysis for each index of performance evaluation of public sewage operation agency (공공하수도 관리대행 성과평가 지표별 가중치분석을 통한 우선순위에 대한 연구)

  • Wi, Mikyung;Park, Chulhwi
    • Journal of Korean Society of Water and Wastewater
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    • v.34 no.6
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    • pp.495-502
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    • 2020
  • The 37 indicators for performance evaluation of public sewage management agencies are divided into four major categories (agency manpower management ability, wastewater treatment plant operation and management, sludge and water reuse, service quality) in the first stage, and the necessity and score acquisition for the detailed indicators by each major category in the second stages. Priority was investigated through the Analytic Hierarchy Process (AHP) analysis technique for ease and relevance of company efforts. Also, based on the results of this analysis, integrated type weighting and relative importance were analyzed. As a result of the analysis, the weight and relative importance of the first stage classification were in the order of wastewater treatment plant operation and maintenance, operation agency manpower management ability, sludge and water reuse, and service quality. As a result of analyzing the weights and priorities of the detailed performance indicators in the second stage, it was found that operator's career years, the percentage of certification holding rate in operators, compliance with the effluent water quality standards, training times for operators, and efforts to manage hazardous chemicals were important. Some of the indicators of operation agency performance evaluation may include indicators in which the performance of the company's efforts is underestimated or overestimated. In order to improve this, it is necessary to give weights in consideration of the necessity of the indicator, the relevance of the company's efforts, and the ease of obtaining scores.