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한국정보처리학회> JIPS(Journal of Information Processing Systems)

JIPS(Journal of Information Processing Systems) update

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  • : 공학분야  >  전자공학
  • : KCI등재
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  • : 연속간행물
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  • : 1976-913x
  • : 2092-805X
  • : International journal of information processing systems(~2007)→Journal of information processing system(2008~)

수록정보
수록범위 : 1권1호(2005)~15권6호(2019) |수록논문 수 : 771
JIPS(Journal of Information Processing Systems)
15권6호(2019년 12월) 수록논문
최근 권호 논문
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KCI등재 SCOPUS

1Integration of Cloud and Big Data Analytics for Future Smart Cities

저자 : Jungho Kang , Jong Hyuk Park

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 15권 6호 발행 연도 : 2019 페이지 : pp. 1259-1264 (6 pages)

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Nowadays, cloud computing and big data analytics are at the center of many industries' concerns to take advantage of the potential benefits of building future smart cities. The integration of cloud computing and big data analytics is the main reason for massive adoption in many organizations, avoiding the potential complexities of on-premise big data systems. With these two technologies, the manufacturing industry, healthcare system, education, academe, etc. are developing rapidly, and they will offer various benefits to expand their domains. In this issue, we present a summary of 18 high-quality accepted articles following a rigorous review process in the field of cloud computing and big data analytics.

KCI등재 SCOPUS

2Cloud Storage Security Deduplication Scheme Based on Dynamic Bloom Filter

저자 : Xi-ai Yan , Wei-qi Shi , Hua Tian

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 15권 6호 발행 연도 : 2019 페이지 : pp. 1265-1276 (12 pages)

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Data deduplication is a common method to improve cloud storage efficiency and save network communication bandwidth, but it also brings a series of problems such as privacy disclosure and dictionary attacks. This paper proposes a secure deduplication scheme for cloud storage based on Bloom filter, and dynamically extends the standard Bloom filter. A public dynamic Bloom filter array (PDBFA) is constructed, which improves the efficiency of ownership proof, realizes the fast detection of duplicate data blocks and reduces the false positive rate of the system. In addition, in the process of file encryption and upload, the convergent key is encrypted twice, which can effectively prevent violent dictionary attacks. The experimental results show that the PDBFA scheme has the characteristics of low computational overhead and low false positive rate.

KCI등재 SCOPUS

3Automatic Pattern Setting System Reacting to Customer Design

저자 : Ying Yuan , Jun-ho Huh

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 15권 6호 발행 연도 : 2019 페이지 : pp. 1277-1295 (19 pages)

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With its technical development, digital printing is being universally introduced to the mass production of clothing factories. At the same time, many fashion platforms have been made for customers' participation using digital printing, and a tool is provided in platforms for customers to make designs. However, there is no sufficient solution in the production stage for automatically converting a customer's design into a file before printing other than designating a square area for the pattern designed by the customer. That is, if 30 different designs come in from customers for one shirt, designers have to do the work of reproducing the design on the clothing pattern in the same location and in the same angle, and this work requires a great deal of manpower. Therefore, it is necessary to develop a technology which can let the customer make the design and, at the same time, reflect it in the clothing pattern. This is defined in relation to the existing clothing pattern with digital printing. This study yields a clothing pattern for digital printing which reflects a customer's design in real time by matching the diagram area where a customer designs on a given clothing model and the area where a standard pattern reflects the customer's actual design information. Designers can substitute the complex mapping operation of programmers with a simple area-matching operation. As there is no limit to clothing designs, the various fashion design creations of designers and the diverse customizing demands of customers can be satisfied at low cost with high efficiency. This is not restricted to T-shirts or eco-bags but can be applied to all woven wear, including men's, women's, and children's clothing, except knitwear.

KCI등재 SCOPUS

4Perceptual Fusion of Infrared and Visible Image through Variational Multiscale with Guide Filtering

저자 : Xin Feng , Kaiqun Hu

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 15권 6호 발행 연도 : 2019 페이지 : pp. 1296-1305 (10 pages)

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To solve the problem of poor noise suppression capability and frequent loss of edge contour and detailed information in current fusion methods, an infrared and visible light image fusion method based on variational multiscale decomposition is proposed. Firstly, the fused images are separately processed through variational multiscale decomposition to obtain texture components and structural components. The method of guided filter is used to carry out the fusion of the texture components of the fused image. In the structural component fusion, a method is proposed to measure the fused weights with phase consistency, sharpness, and brightness comprehensive information. Finally, the texture components of the two images are fused. The structure components are added to obtain the final fused image. The experimental results show that the proposed method displays very good noise robustness, and it also helps realize better fusion quality.

KCI등재 SCOPUS

5Feature Selection Using Submodular Approach for Financial Big Data

저자 : Girija Attigeri , Manohara Pai M. M. , Radhika M. Pai

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 15권 6호 발행 연도 : 2019 페이지 : pp. 1306-1325 (20 pages)

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As the world is moving towards digitization, data is generated from various sources at a faster rate. It is getting humungous and is termed as big data. The financial sector is one domain which needs to leverage the big data being generated to identify financial risks, fraudulent activities, and so on. The design of predictive models for such financial big data is imperative for maintaining the health of the country's economics. Financial data has many features such as transaction history, repayment data, purchase data, investment data, and so on. The main problem in predictive algorithm is finding the right subset of representative features from which the predictive model can be constructed for a particular task. This paper proposes a correlation-based method using submodular optimization for selecting the optimum number of features and thereby, reducing the dimensions of the data for faster and better prediction. The important proposition is that the optimal feature subset should contain features having high correlation with the class label, but should not correlate with each other in the subset. Experiments are conducted to understand the effect of the various subsets on different classification algorithms for loan data. The IBM Bluemix Big Data platform is used for experimentation along with the Spark notebook. The results indicate that the proposed approach achieves considerable accuracy with optimal subsets in significantly less execution time. The algorithm is also compared with the existing feature selection and extraction algorithms.

KCI등재 SCOPUS

6Knowledge Base Associated with Autism Construction Using CRFs Learning

저자 : Ronggen Yang , Lejun Gong

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 15권 6호 발행 연도 : 2019 페이지 : pp. 1326-1334 (9 pages)

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Knowledge base means a library stored in computer system providing useful information or appropriate solutions to specific area. Knowledge base associated with autism is the complex multidimensional information set related to the disease autism for its pathogenic factor and therapy. This paper focuses on the knowledge of biological molecular information extracted from massive biomedical texts with the aid of widespread used machine learning methods. Six classes of biological molecular information (such as protein, DNA, RNA, cell line, cell component, and cell type) are concerned and the probability statistics method, conditional random fields(CRFs), is utilized to discover these knowledges in this work. The knowledge base can help biologists to etiological analysis and pharmacists to drug development, which can at least answer four questions in question-answering(QA) system, i.e., which proteins are most related to the disease autism, which DNAs play important role to the development of autism, which cell types have the correlation to autism and which cell components participate the process to autism. The work can be visited by the address http://134.175.110.97/bioinfo/index.jsp.

KCI등재 SCOPUS

7Saturation Prediction for Crowdsensing Based Smart Parking System

저자 : Mihui Kim , Junhyeok Yun

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 15권 6호 발행 연도 : 2019 페이지 : pp. 1335-1349 (15 pages)

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Crowdsensing technologies can improve the efficiency of smart parking system in comparison with present sensor based smart parking system because of low install price and no restriction caused by sensor installation. A lot of sensing data is necessary to predict parking lot saturation in real-time. However in real world, it is hard to reach the required number of sensing data. In this paper, we model a saturation predication combining a time-based prediction model and a sensing data-based prediction model. The time-based model predicts saturation in aspects of parking lot location and time. The sensing data-based model predicts the degree of saturation of the parking lot with high accuracy based on the degree of saturation predicted from the first model, the saturation information in the sensing data, and the number of parking spaces in the sensing data. We perform prediction model learning with real sensing data gathered from a specific parking lot. We also evaluate the performance of the predictive model and show its efficiency and feasibility.

KCI등재 SCOPUS

8Damage Mechanism of Drift Ice Impact

저자 : Li Gong , Zhonghui Wang , Yaxian Li , Chunling Jin , Jing Wang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 15권 6호 발행 연도 : 2019 페이지 : pp. 1350-1364 (15 pages)

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The ice damage occurs frequently in cold and dry region of western China in winter ice period and spring thaw period. In the drift ice condition, it is easy to form different extrusion force or impact force to damage tunnel lining, causing project failure. The failure project could not arrive the original planning and construction goal, giving rise to the water allocation pressure which influences diversion irrigation and farming production in spring. This study conducts the theoretical study on contact-impact algorithm of drift ices crashing diversion tunnel based on the symmetric penalty function in finite element theory. ANSYS/LS-DYNA is adopted as the platform to establish tunnel model and drift ice model. LS-DYNA SOLVER is used as the solver and LS-PREPOST is used to do post-processing, analyzing the damage degrees of drift ices on tunnel. Constructing physical model in the experiment to verify and reveal the impact damage mechanism of drift ices on diversion tunnel. The software simulation results and the experiment results show that tunnel lining surface will form varying degree deformation and failure when drift ices crash tunnel lining on different velocity, different plan size and different thickness of drift ice. The researches also show that there are damages of drift ice impact force on tunnel lining in the thawing period in cold and dry region. By long time water scouring, the tunnel lining surfaces are broken and falling off which breaks the strength and stability of the structure.

KCI등재 SCOPUS

9Summarizing the Differences in Chinese-Vietnamese Bilingual News

저자 : Jinjuan Wu , Zhengtao Yu , Shulong Liu , Yafei Zhang , Shengxiang Gao

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 15권 6호 발행 연도 : 2019 페이지 : pp. 1365-1377 (13 pages)

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Summarizing the differences in Chinese-Vietnamese bilingual news plays an important supporting role in the comparative analysis of news views between China and Vietnam. Aiming at cross-language problems in the analysis of the differences between Chinese and Vietnamese bilingual news, we propose a new method of summarizing the differences based on an undirected graph model. The method extracts elements to represent the sentences, and builds a bridge between different languages based on Wikipedia's multilingual concept description page. Firstly, we calculate the similarity between Chinese and Vietnamese news sentences, and filter the bilingual sentences accordingly. Then we use the filtered sentences as nodes and the similarity grade as the weight of the edge to construct an undirected graph model. Finally, combining the random walk algorithm, the weight of the node is calculated according to the weight of the edge, and sentences with highest weight can be extracted as the difference summary. The experiment results show that our proposed approach achieved the highest score of 0.1837 on the annotated test set, which outperforms the state-of-the-art summarization models.

KCI등재 SCOPUS

10Document Summarization Model Based on General Context in RNN

저자 : Heechan Kim , Soowon Lee

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 15권 6호 발행 연도 : 2019 페이지 : pp. 1378-1391 (14 pages)

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In recent years, automatic document summarization has been widely studied in the field of natural language processing thanks to the remarkable developments made using deep learning models. To decode a word, existing models for abstractive summarization usually represent the context of a document using the weighted hidden states of each input word when they decode it. Because the weights change at each decoding step, these weights reflect only the local context of a document. Therefore, it is difficult to generate a summary that reflects the overall context of a document. To solve this problem, we introduce the notion of a general context and propose a model for summarization based on it. The general context reflects overall context of the document that is independent of each decoding step. Experimental results using the CNN/Daily Mail dataset show that the proposed model outperforms existing models.

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1연안해역에서 석유오염물질의 세균학적 분해에 관한 연구

(2006)홍길동 외 1명심리학41회 피인용

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세종대학교 고려대학교 The University of Edinburgh 전북대학교 경기대학교
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  • 1 세종대학교 (3건)
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  • 3 The University of Edinburgh (2건)
  • 4 전북대학교 (1건)
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