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한국정보처리학회> JIPS(Journal of Information Processing Systems)

JIPS(Journal of Information Processing Systems) update

  • : 한국정보처리학회
  • : 공학분야  >  전자공학
  • : KCI등재
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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)~16권4호(2020) |수록논문 수 : 843
JIPS(Journal of Information Processing Systems)
16권4호(2020년 08월) 수록논문
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KCI등재 SCOPUS

1Future Trends of IoT, 5G Mobile Networks, and AI: Challenges, Opportunities, and Solutions

저자 : Ji Su Park , Jong Hyuk Park

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 16권 4호 발행 연도 : 2020 페이지 : pp. 743-749 (7 pages)

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Internet of Things (IoT) is a growing technology along with artificial intelligence (AI) technology. Recently, increasing cases of developing knowledge services using information collected from sensor data have been reported. Communication is required to connect the IoT and AI, and 5G mobile networks have been widely spread recently. IoT, AI services, and 5G mobile networks can be configured and used as sensor-mobile edgeserver. The sensor does not send data directly to the server. Instead, the sensor sends data to the mobile edge for quick processing. Subsequently, mobile edge enables the immediate processing of data based on AI technology or by sending data to the server for processing. 5G mobile network technology is used for this data transmission. Therefore, this study examines the challenges, opportunities, and solutions used in each type of technology. To this end, this study addresses clustering, Hyperledger Fabric, data, security, machine vision, convolutional neural network, IoT technology, and resource management of 5G mobile networks.

KCI등재 SCOPUS

2Hot Spot Analysis of Tourist Attractions Based on Stay Point Spatial Clustering

저자 : Yifan Liao

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 16권 4호 발행 연도 : 2020 페이지 : pp. 750-759 (10 pages)

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The wide application of various integrated location-based services (LBS social) and tourism application (app) has generated a large amount of trajectory space data. The trajectory data are used to identify popular tourist attractions with high density of tourists, and they are of great significance to smart service and emergency management of scenic spots. A hot spot analysis method is proposed, based on spatial clustering of trajectory stop points. The DBSCAN algorithm is studied with fast clustering speed, noise processing and clustering of arbitrary shapes in space. The shortage of parameters is manually selected, and an improved method is proposed to adaptively determine parameters based on statistical distribution characteristics of data. DBSCAN clustering analysis and contrast experiments are carried out for three different datasets of artificial synthetic twodimensional dataset, four-dimensional Iris real dataset and scenic track retention point. The experiment results show that the method can automatically generate reasonable clustering division, and it is superior to traditional algorithms such as DBSCAN and k-means. Finally, based on the spatial clustering results of the trajectory stay points, the Getis-Ord Gi* hotspot analysis and mapping are conducted in ArcGIS software. The hot spots of different tourist attractions are classified according to the analysis results, and the distribution of popular scenic spots is determined with the actual heat of the scenic spots.

KCI등재 SCOPUS

3Design and Implementation of a Digital Evidence Management Model Based on Hyperledger Fabric

저자 : Junho Jeong , Donghyo Kim , Byungdo Lee , Yunsik Son

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 16권 4호 발행 연도 : 2020 페이지 : pp. 760-773 (14 pages)

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When a crime occurs, the information necessary for solving the case, and various pieces of the evidence needed to prove the crime are collected from the crime scene. The tangible residues collected through scientific methods at the crime scene become evidence at trial and a clue to prove the facts directly against the offense of the suspect. Therefore, the scientific investigation and forensic handling for securing objective forensic in crime investigation is increasingly important. Today, digital systems, such as smartphones, CCTVs, black boxes, etc. are increasingly used as criminal information investigation clues, and digital forensic is becoming a decisive factor in investigation and trial. However, the systems have the risk that digital forensic may be damaged or manipulated by malicious insiders in the existing centralized management systems based on client/server structure. In this paper, we design and implement a blockchain based digital forensic management model using Hyperledger Fabric and Docker to guarantee the reliability and integrity of digital forensic. The proposed digital evidence management model allows only authorized participants in a distributed environment without a central management agency access the network to share and manage potential crime data. Therefore, it could be relatively safe from malicious internal attackers compared to the existing client/server model.

KCI등재 SCOPUS

4Localization of Subsurface Targets Based on Symmetric Sub-array MIMO Radar

저자 : Qinghua Liu , Yuanxin He , Chang Jiang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 16권 4호 발행 연도 : 2020 페이지 : pp. 774-783 (10 pages)

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For the issue of subsurface target localization by reverse projection, a new approach of target localization with different distances based on symmetric sub-array multiple-input multiple-output (MIMO) radar is proposed in this paper. By utilizing the particularity of structure of the two symmetric sub-arrays, the received signals are jointly reconstructed to eliminate the distance information from the steering vectors. The distance-independent direction of arrival (DOA) estimates are acquired, and the localizations of subsurface targets with different distances are realized by reverse projection. According to the localization mechanism and application characteristics of the proposed algorithm, the grid zooming method based on spatial segmentation is used to optimize the locaiton efficiency. Simulation results demonstrate the effectiveness of the proposed localization method and optimization scheme.

KCI등재 SCOPUS

5Type Drive Analysis of Urban Water Security Factors

저자 : Li Gong , Hong Wang , Chunling Jin , Lili Lu , Menghan Ma

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 16권 4호 발행 연도 : 2020 페이지 : pp. 784-794 (11 pages)

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In order to effectively evaluate the urban water security, the study investigates a novel system to assess factors that impact urban water security and builds an urban water poverty evaluation index system. Based on the contribution rates of Resource, Access, Capacity, Use, and Environment, the study adopts the Water Poverty Index (WPI) model to evaluate the water poverty levels of 14 cities in Gansu during 2011-2018 and uses the least variance method to evaluate water poverty space drive types. The case study results show that the water poverty space drive types of 14 cites fall into four categories. The first category is the dual factor dominant type driven by environment and resources, which includes Lanzhou, Qingyang, Jiuquan, and Jiayuguan. The second category is the three-factor dominant type driven by Access, Use, and Capability, which includes Longnan, Linxia, and Gannan. The third category is the four-factor dominant type driven by Resource, Access, Capability, and Environment, which includes Jinchang, Pingliang, Wuwei, Baiyin, and Zhangye. The fourth category is the five-factor dominant type, which includes Tianshui and Dingxi. The driven types impacting the urban water security factors reflected by the WPI and its model are clear and accurate. The divisions of the urban water security level supply a reliable theoretical and numerical basis for an urban water security early warning mechanism.

KCI등재 SCOPUS

6Aircraft Recognition from Remote Sensing Images Based on Machine Vision

저자 : Lu Chen , Liming Zhou , Jinming Liu

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 16권 4호 발행 연도 : 2020 페이지 : pp. 795-808 (14 pages)

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Due to the poor evaluation indexes such as detection accuracy and recall rate when Yolov3 network detects aircraft in remote sensing images, in this paper, we propose a remote sensing image aircraft detection method based on machine vision. In order to improve the target detection effect, the Inception module was introduced into the Yolov3 network structure, and then the data set was cluster analyzed using the k-means algorithm. In order to obtain the best aircraft detection model, on the basis of our proposed method, we adjusted the network parameters in the pre-training model and improved the resolution of the input image. Finally, our method adopted multi-scale training model. In this paper, we used remote sensing aircraft dataset of RSOD-Dataset to do experiments, and finally proved that our method improved some evaluation indicators. The experiment of this paper proves that our method also has good detection and recognition ability in other ground objects.

KCI등재 SCOPUS

7Voting and Ensemble Schemes Based on CNN Models for Photo-Based Gender Prediction

저자 : Kyoungson Jha

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 16권 4호 발행 연도 : 2020 페이지 : pp. 809-819 (11 pages)

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Gender prediction accuracy increases as convolutional neural network (CNN) architecture evolves. This paper compares voting and ensemble schemes to utilize the already trained five CNN models to further improve gender prediction accuracy. The majority voting usually requires odd-numbered models while the proposed softmax-based voting can utilize any number of models to improve accuracy. The ensemble of CNN models combined with one more fully-connected layer requires further tuning or training of the models combined. With experiments, it is observed that the voting or ensemble of CNN models leads to further improvement of gender prediction accuracy and that especially softmax-based voters always show better gender prediction accuracy than majority voters. Also, compared with softmax-based voters, ensemble models show a slightly better or similar accuracy with added training of the combined CNN models. Softmax-based voting can be a fast and efficient way to get better accuracy without further training since the selection of the top accuracy models among available CNN pre-trained models usually leads to similar accuracy to that of the corresponding ensemble models.

KCI등재 SCOPUS

8Joint Hierarchical Semantic Clipping and Sentence Extraction for Document Summarization

저자 : Wanying Yan , Junjun Guo

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 16권 4호 발행 연도 : 2020 페이지 : pp. 820-831 (12 pages)

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Extractive document summarization aims to select a few sentences while preserving its main information on a given document, but the current extractive methods do not consider the sentence-information repeat problem especially for news document summarization. In view of the importance and redundancy of news text information, in this paper, we propose a neural extractive summarization approach with joint sentence semantic clipping and selection, which can effectively solve the problem of news text summary sentence repetition. Specifically, a hierarchical selective encoding network is constructed for both sentence-level and documentlevel document representations, and data containing important information is extracted on news text; a sentence extractor strategy is then adopted for joint scoring and redundant information clipping. This way, our model strikes a balance between important information extraction and redundant information filtering. Experimental results on both CNN/Daily Mail dataset and Court Public Opinion News dataset we built are presented to show the effectiveness of our proposed approach in terms of ROUGE metrics, especially for redundant information filtering.

KCI등재 SCOPUS

9N-Step Sliding Recursion Formula of Variance and Its Implementation

저자 : Lang Yu , Gang He , Ahmad Khwaja Mutahir

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 16권 4호 발행 연도 : 2020 페이지 : pp. 832-844 (13 pages)

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The degree of dispersion of a random variable can be described by the variance, which reflects the distance of the random variable from its mean. However, the time complexity of the traditional variance calculation algorithm is O(n), which results from full calculation of all samples. When the number of samples increases or on the occasion of high speed signal processing, algorithms with O(n) time complexity will cost huge amount of time and that may results in performance degradation of the whole system. A novel multi-step recursive algorithm for variance calculation of the time-varying data series with O(1) time complexity (constant time) is proposed in this paper. Numerical simulation and experiments of the algorithm is presented and the results demonstrate that the proposed multi-step recursive algorithm can effectively decrease computing time and hence significantly improve the variance calculation efficiency for time-varying data, which demonstrates the potential value for time-consumption data analysis or high speed signal processing.

KCI등재 SCOPUS

10A Modified E-LEACH Routing Protocol for Improving the Lifetime of a Wireless Sensor Network

저자 : Maman Abdurohman , Yadi Supriadi , Fitra Zul Fahmi

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 16권 4호 발행 연도 : 2020 페이지 : pp. 845-858 (14 pages)

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This paper proposes a modified end-to-end secure low energy adaptive clustering hierarchy (ME-LEACH) algorithm for enhancing the lifetime of a wireless sensor network (WSN). Energy limitations are a major constraint in WSNs, hence every activity in a WSN must efficiently utilize energy. Several protocols have been introduced to modulate the way a WSN sends and receives information. The end-to-end secure low energy adaptive clustering hierarchy (E-LEACH) protocol is a hierarchical routing protocol algorithm proposed to solve high-energy dissipation problems. Other methods that explore the presence of the most powerful nodes on each cluster as cluster heads (CHs) are the sparsity-aware energy efficient clustering (SEEC) protocol and an energy efficient clustering-based routing protocol that uses an enhanced cluster formation technique accompanied by the fuzzy logic (EERRCUF) method. However, each CH in the E-LEACH method sends data directly to the base station causing high energy consumption. SEEC uses a lot of energy to identify the most powerful sensor nodes, while EERRCUF spends high amounts of energy to determine the super cluster head (SCH). In the proposed method, a CH will search for the nearest CH and use it as the next hop. The formation of CH chains serves as a path to the base station. Experiments were conducted to determine the performance of the ME-LEACH algorithm. The results show that ME-LEACH has a more stable and higher throughput than SEEC and EERRCUF and has a 35.2% better network lifetime than the E-LEACH algorithm.

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