• Title/Summary/Keyword: Feature encoding

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An Improved Method of the Prime Number Labeling Scheme for Dynamic XML Documents (빈번히 갱신되는 XML 문서에 대한 프라임 넘버 레이블링 기법)

  • Yoo, Ji-You;Yoo, Sang-Won;Kim, Hyoung-Joo
    • Journal of KIISE:Databases
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    • v.33 no.1
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    • pp.129-137
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    • 2006
  • An XML labeling scheme is an efficient encoding method to determine the ancestor-descendant relationships of elements and the orders of siblings. Recently, many dynamic XML documents have appeared in the Web Services and the AXML(the Active XML), so we need to manage them with a dynamic XML labeling scheme. The prime number labeling scheme is a representative scheme which supports dynamic XML documents. It determines the ancestor-descendant relationships between two elements with the feature of prime numbers. When a new element is inserted into the XML document using this scheme, it has an advantage that an assigning the label of new element don't change the label values of existing nodes. But it has to have additional expensive operations and data structure for maintaining the orders of siblings. In this paper, we suggest the order number sharing method and algorithms categorized by the insertion positions of new nodes. They greatly minimize the existing method's sibling order maintenance cost.

Safety Evaluation of Bifidobacterium breve IDCC4401 Isolated from Infant Feces for Use as a Commercial Probiotic

  • Choi, In Young;Kim, Jinhee;Kim, Su-Hyeon;Ban, O-Hyun;Yang, Jungwoo;Park, Mi-Kyung
    • Journal of Microbiology and Biotechnology
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    • v.31 no.7
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    • pp.949-955
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    • 2021
  • Previously, our research group isolated Bifidobacterium breve IDCC4401 from infant feces as a potential probiotic. For this study, we evaluated the safety of B. breve IDCC4401 using genomic and phenotypic analyses. Whole genome sequencing was performed to identify genomic characteristics and investigate the potential presence of genes encoding virulence, antibiotic resistance, and mobile genetic elements. Phenotypic analyses including antibiotic susceptibility, enzyme activity, production of biogenic amines (BAs), and proportion of D-/L-lactate were evaluated using E-test, API ZYM test, high-performance liquid chromatography (HPLC), and D-/L-lactic acid assay respectively. The genome of B. breve IDCC4401 consists of 2,426,499 bp with a GC content of 58.70% and 2,016 coding regions. Confirmation of the genome as B. breve was provided by its 98.93% similarity with B. breve DSM20213. Furthermore, B. breve IDCC4401 genes encoding virulence and antibiotic resistance were not identified. Although B. breve IDCC4401 showed antibiotic resistance against vancomycin, we confirmed that this was an intrinsic feature since the antibiotic resistance gene was not present. B. breve IDCC4401 showed leucine arylamidase, cystine arylamidase, α-galactosidase, β-galactosidase, and α-glucosidase activities, whereas it did not show production of harmful enzymes such as β-glucosidase and β-glucuronidase. In addition, B. breve IDCC4401 did not produce any tyramine, histamine, putrescine, cadaverine, or 2-phenethylamine, which are frequently detected BAs during fermentation. B. breve IDCC4401 produced 95.08% of L-lactate and 4.92% of D-lactate. Therefore, our findings demonstrate the safety of B. breve IDCC 4401 as a potential probiotic for use in the food industry.

A User Driven Adaptive Bandwidth Video Streaming System (사용자 기반 가변 대역폭 영상 스트리밍 시스템)

  • Chung, Yeongjee;Ozturk, Yusuf
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.4
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    • pp.825-840
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    • 2015
  • Adaptive bitrate (ABR) streaming technology has become an important and prevalent feature in many multimedia delivery systems, with content providers such as Netflix and Amazon using ABR streaming to increase bandwidth efficiency and provide the maximum user experience when channel conditions are not ideal. Where such systems could see improvement is in the delivery of live video with a closed loop cognitive control of video encoding. In this paper, we present streaming camera system which provides spatially and temporally adaptive video streams, learning the user's preferences in order to make intelligent scaling decisions. The system employs a hardware based H.264/AVC encoder for video compression. The encoding parameters can be configured by the user or by the cognitive system on behalf of the user when the bandwidth changes. A cognitive video client developed in this study learns the user's preferences(i.e. video size over frame rate) over time and intelligently adapts encoding parameters when the channel conditions change. It has been demonstrated that the cognitive decision system developed has the ability to control video bandwidth by altering the spatial and temporal resolution, as well as the ability to make scaling decisions.

A Study on the Deep Neural Network based Recognition Model for Space Debris Vision Tracking System (심층신경망 기반 우주파편 영상 추적시스템 인식모델에 대한 연구)

  • Lim, Seongmin;Kim, Jin-Hyung;Choi, Won-Sub;Kim, Hae-Dong
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.45 no.9
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    • pp.794-806
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    • 2017
  • It is essential to protect the national space assets and space environment safely as a space development country from the continuously increasing space debris. And Active Debris Removal(ADR) is the most active way to solve this problem. In this paper, we studied the Artificial Neural Network(ANN) for a stable recognition model of vision-based space debris tracking system. We obtained the simulated image of the space environment by the KARICAT which is the ground-based space debris clearing satellite testbed developed by the Korea Aerospace Research Institute, and created the vector which encodes structure and color-based features of each object after image segmentation by depth discontinuity. The Feature Vector consists of 3D surface area, principle vector of point cloud, 2D shape and color information. We designed artificial neural network model based on the separated Feature Vector. In order to improve the performance of the artificial neural network, the model is divided according to the categories of the input feature vectors, and the ensemble technique is applied to each model. As a result, we confirmed the performance improvement of recognition model by ensemble technique.

Music Genre Classification using Spikegram and Deep Neural Network (스파이크그램과 심층 신경망을 이용한 음악 장르 분류)

  • Jang, Woo-Jin;Yun, Ho-Won;Shin, Seong-Hyeon;Cho, Hyo-Jin;Jang, Won;Park, Hochong
    • Journal of Broadcast Engineering
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    • v.22 no.6
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    • pp.693-701
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    • 2017
  • In this paper, we propose a new method for music genre classification using spikegram and deep neural network. The human auditory system encodes the input sound in the time and frequency domain in order to maximize the amount of sound information delivered to the brain using minimum energy and resource. Spikegram is a method of analyzing waveform based on the encoding function of auditory system. In the proposed method, we analyze the signal using spikegram and extract a feature vector composed of key information for the genre classification, which is to be used as the input to the neural network. We measure the performance of music genre classification using the GTZAN dataset consisting of 10 music genres, and confirm that the proposed method provides good performance using a low-dimensional feature vector, compared to the current state-of-the-art methods.

PPNC: Privacy Preserving Scheme for Random Linear Network Coding in Smart Grid

  • He, Shiming;Zeng, Weini;Xie, Kun;Yang, Hongming;Lai, Mingyong;Su, Xin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.3
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    • pp.1510-1532
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    • 2017
  • In smart grid, privacy implications to individuals and their families are an important issue because of the fine-grained usage data collection. Wireless communications are utilized by many utility companies to obtain information. Network coding is exploited in smart grids, to enhance network performance in terms of throughput, delay, robustness, and energy consumption. However, random linear network coding introduces a new challenge for privacy preserving due to the encoding of data and updating of coefficients in forwarder nodes. We propose a distributed privacy preserving scheme for random linear network coding in smart grid that considers the converged flows character of the smart grid and exploits a homomorphic encryption function to decrease the complexities in the forwarder node. It offers a data confidentiality privacy preserving feature, which can efficiently thwart traffic analysis. The data of the packet is encrypted and the tag of the packet is encrypted by a homomorphic encryption function. The forwarder node random linearly codes the encrypted data and directly processes the cryptotext tags based on the homomorphism feature. Extensive security analysis and performance evaluations demonstrate the validity and efficiency of the proposed scheme.

Design and Implementation of Component for Location Information of Moving Objects (이동체 위치정보 컴포넌트 설계 및 구현)

  • Lee, Hye-Jin;Kim, Jin-Suk
    • Journal of the Korean Association of Geographic Information Studies
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    • v.7 no.4
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    • pp.65-76
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    • 2004
  • This paper suggests design and implementation of moving objects management system using GML which is the XML encoding standard of geographic data. The proposed system integrates spatial data and moving objects data, utilizing the concept of Web Feature Services. While integrating data, standard data model and interfaces, proposed by OGC, are used. Since GML is standard for storing and transferring spatial/non-spatial data, interoperability and extendibility can be obtained. In addition, we propose efficient developing environment for the moving object management system by providing components having Web/Mobile interface. If the proposed component be development methods are used, it is easy to add or modifyservices in the mobile system and pla

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OLE File Analysis and Malware Detection using Machine Learning

  • Choi, Hyeong Kyu;Kang, Ah Reum
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.5
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    • pp.149-156
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    • 2022
  • Recently, there have been many reports of document-type malicious code injecting malicious code into Microsoft Office files. Document-type malicious code is often hidden by encoding the malicious code in the document. Therefore, document-type malware can easily bypass anti-virus programs. We found that malicious code was inserted into the Visual Basic for Applications (VBA) macro, a function supported by Microsoft Office. Malicious codes such as shellcodes that run external programs and URL-related codes that download files from external URLs were identified. We selected 354 keywords repeatedly appearing in malicious Microsoft Office files and defined the number of times each keyword appears in the body of the document as a feature. We performed machine learning with SVM, naïve Bayes, logistic regression, and random forest algorithms. As a result, each algorithm showed accuracies of 0.994, 0.659, 0.995, and 0.998, respectively.

Characterization of the Replication Region of the Enterococcus faecalis Plasmid p703/5

  • Song, Joon-Seok;Park, Jin-Hwan;Kim, Chan-Wha;Kim, Young-Woo;Lim, Wang-Jin;Kim, Ick-Young;Chang, Hyo-Ihl
    • Journal of Microbiology and Biotechnology
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    • v.9 no.1
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    • pp.91-97
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    • 1999
  • In this work, a 1.9-kb region of enterococcal plasmid p703/5 was isolated and the nucleotide sequence analysis of the region was performed. One major open reading frame (ORF) was identified encoding a polypeptide of 28 kDa. Database comparisons suggested that the protein showed some homology with other bacterial RepA proteins. Upstream of the ORF, a potential dnaA box, AT-rich region and 22-bp tandemly repeated sequences (DNA iterons), a feature typical for many replication ori sites, were recognized. Deletion analysis using Exonuclease III and several restriction enzymes indicated that the three elements and the gene product from the ORF were essential for replication and that the minimum unit of DNA required for replication resided on the 1.2-kb AvaII subfragment. Thus, this gene product was referred to as RepA.

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A Preprocessing Algorithm for Efficient Lossless Compression of Gray Scale Images

  • Kim, Sun-Ja;Hwang, Doh-Yeun;Yoo, Gi-Hyoung;You, Kang-Soo;Kwak, Hoon-Sung
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.2485-2489
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    • 2005
  • This paper introduces a new preprocessing scheme to replace original data of gray scale images with particular ordered data so that performance of lossless compression can be improved more efficiently. As a kind of preprocessing technique to maximize performance of entropy encoder, the proposed method converts the input image data into more compressible form. Before encoding a stream of the input image, the proposed preprocessor counts co-occurrence frequencies for neighboring pixel pairs. Then, it replaces each pair of adjacent gray values with particular ordered numbers based on the investigated co-occurrence frequencies. When compressing ordered image using entropy encoder, we can expect to raise compression rate more highly because of enhanced statistical feature of the input image. In this paper, we show that lossless compression rate increased by up to 37.85% when comparing results from compressing preprocessed and non-preprocessed image data using entropy encoder such as Huffman, Arithmetic encoder.

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