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한국정보처리학회> JIPS(Journal of Information Processing Systems)

JIPS(Journal of Information Processing Systems) update

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

수록정보
18권2호(2022) |수록논문 수 : 11
간행물 제목
18권6호(2022년 12월) 수록논문
최근 권호 논문
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KCI등재 SCOPUS

저자 : Ruibo Ai , Cheng Li , Na Li

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 719-728 (10 pages)

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The prediction of short-term traffic flow is the theoretical basis of intelligent transportation as well as the key technology in traffic flow induction systems. The research on short-term traffic flow prediction has showed the considerable social value. At present, the support vector regression (SVR) intelligent prediction model that is suitable for small samples has been applied in this domain. Aiming at parameter selection difficulty and prediction accuracy improvement, the artificial bee colony (ABC) is adopted in optimizing SVR parameters, which is referred to as the ABC-SVR algorithm in the paper. The simulation experiments are carried out by comparing the ABC-SVR algorithm with SVR algorithm, and the feasibility of the proposed ABC-SVR algorithm is verified by result analysis. Continuously, the simulation experiments are carried out by comparing the ABC-SVR algorithm with particle swarm optimization SVR (PSO-SVR) algorithm and genetic optimization SVR (GA-SVR) algorithm, and a better optimization effect has been attained by simulation experiments and verified by statistical test. Simultaneously, the simulation experiments are carried out by comparing the ABC-SVR algorithm and wavelet neural network time series (WNN-TS) algorithm, and the prediction accuracy of the proposed ABC-SVR algorithm is improved and satisfactory prediction effects have been obtained.

KCI등재 SCOPUS

저자 : Suman Pandey , Yang-sae Moon , Mi-jung Choi

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 729-740 (12 pages)

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Netflix, Amazon Prime, and YouTube are the most popular and fastest-growing streaming services globally. It is a matter of great interest for the streaming service providers to preview their service infrastructure and streaming strategy in order to provide new streaming services. Hence, the first part of the paper presents a detailed survey of the Content Distribution Network (CDN) and cloud infrastructure of these service providers. To understand the streaming strategy of these service providers, the second part of the paper deduces a common quality-of-service (QoS) model based on rebuffering time, bitrate, progressive download ratio, and standard deviation of the On-Off cycle. This model is then used to analyze and compare the streaming behaviors of these services. This study concluded that the streaming behaviors of all these services are similar as they all use Dynamic Adaptive Streaming over HTTP (DASH) on top of TCP. However, the amount of data that they download in the buffering state and steady-state vary, resulting in different progressive download ratios, rebuffering levels, and bitrates. The characteristics of their On-Off cycle are also different resulting in different QoS. Hence a thorough adaptive bit rate (ABR) analysis is presented in this paper. The streaming behaviors of these services are tested on different access network bandwidths, ranging from 75 kbps to 30 Mbps. The survey results indicate that Netflix QoS and streaming behavior are significantly consistent followed by Amazon Prime and YouTube. Our approach can be used to compare and contrast the streaming services' strategies and fine-tune their ABR and flow control mechanisms.

KCI등재 SCOPUS

저자 : Youngjong Kim , Sungil Jang , Myung Ho Kim , Jinho Park

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 741-754 (14 pages)

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Openstack is widely used as a representative open-source infrastructure of the service (IaaS) platform. The Openstack Identity Service is a centralized approach component based on the token including the Memcached for cache, which is the in-memory key-value store. Token validation requests are concentrated on the centralized server as the number of differently encrypted tokens increases. This paper proposes the practical Byzantine fault tolerance (PBFT) blockchain-based Openstack Identity Service, which can improve the performance efficiency and reduce security vulnerabilities through a PBFT blockchain framework-based decentralized approach. The experiment conducted by using the Apache JMeter demonstrated that latency was improved by more than 33.99% and 72.57% in the PBFT blockchain-based Openstack Identity Service, compared to the Openstack Identity Service, for 500 and 1,000 differently encrypted tokens, respectively.

KCI등재 SCOPUS

저자 : Zhe Zhang , Yongchang Zhang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 755-762 (8 pages)

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The existing electrical engineering design method and the dynamic objective function in the application process of automatic control system fail to meet the unbounded condition, which affects the control tracking accuracy. In order to improve the tracking control accuracy, this paper studies the electrical engineering design method based on neural network and the application of automatic control system. This paper analyzes the structure and working mechanism of electrical engineering automation control system by an automation control model with main control objectives. Following the analysis, an optimal solution of controllability design and fault-tolerant control is figured out. The automatic control power coefficient is distributed based on an ideal control effect of system. According to the distribution results, an automatic control algorithm is based on neural network for accurate control. The experimental results show that the electrical automation control method based on neural network can significantly reduce the control following error to 3.62%, improve the accuracy of the electrical automation tracking control, thus meeting the actual production needs of electrical engineering automation control system.

KCI등재 SCOPUS

저자 : Xia Wei

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 763-769 (7 pages)

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Transportation allocation requires information such as storage location and order information. In order to guarantee the safe transmission and real-time sharing of information in all links, an intelligent transportation control system based on blockchain technology is designed. Firstly, the technical architecture of intelligent transportation information traceability blockchain and the overall architecture of intelligent transportation control system were designed. Secondly, the transportation management demand module and storage demand management module were designed, and the control process of each module was given. Then, the type of intelligent transportation vehicle was defined, the objective function of intelligent transportation control was designed, and the objective function of intelligent transportation control was constructed. Finally, the intelligent transportation control was realized by genetic algorithm. It was found that when the transportation order volume was 50×103, and the CPU occupancy of the designed system was only 11.8%. The reliability attenuation of the code deletion scheme was lower, indicating better performance of the designed system.

KCI등재 SCOPUS

저자 : Taiyo Ichinose , Tomoya Kawakami

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 770-783 (14 pages)

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Early evacuations reduce the damage caused by catastrophic events such as terrorism, tsunamis, heavy rains, landslides, and river floods. However, even when warnings are issued, people do not easily evacuate during these events. To shorten the evacuation time, initiative-evacuation and its executors, initiative evacuees, are crucial in inducing other evacuations. The initiative evacuees take the initiative in evacuating and call out to their surroundings. This paper proposes a fast method to induce initiative-evacuation based on social graphs. The candidates are determined in descending order of the number of links for each person. The proposed method was evaluated through simulations. The simulation results showed a significant reduction in evacuation time.

KCI등재 SCOPUS

저자 : Jiyong Jin

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 784-793 (10 pages)

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Grid-connected distributed power generation has been widely used in green energy generation. However, due to the distributed characteristics, distributed power generation is difficult to be dynamically allocated and monitored in the electrical control process. In order to solve this problem, this research combined the Internet of Things (IoT) with the automatic control system of electrical engineering to improve the control strategy of the power grid inverter according to the characteristics of the IoT system. In the research, a connection system of the power grid inverter and the IoT controller were designed, and the application effect was tested by simulation experiments. The results showed that the power grid inverter had strong tracking control ability for current and power control. Meanwhile, the electrical control system of the IoT could independently and dynamically control the three-phase current and power. The given value was reached within 50 ms after the step signal was input, which could protect the power grid from being affected by the current. The overall system could realize effective control, dynamic control and protective control.

KCI등재 SCOPUS

저자 : Huihui Xu , Fei Li

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 794-802 (9 pages)

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The recovery of reasonable depth information from different scenes is a popular topic in the field of computer vision. For generating depth maps with better details, we present an efficacious monocular depth prediction framework with coordinate attention and feature fusion. Specifically, the proposed framework contains attention, multi-scale and feature fusion modules. The attention module improves features based on coordinate attention to enhance the predicted effect, whereas the multi-scale module integrates useful low- and high-level contextual features with higher resolution. Moreover, we developed a feature fusion module to combine the heterogeneous features to generate high-quality depth outputs. We also designed a hybrid loss function that measures prediction errors from the perspective of depth and scale-invariant gradients, which contribute to preserving rich details. We conducted the experiments on public RGBD datasets, and the evaluation results show that the proposed scheme can considerably enhance the accuracy of depth prediction, achieving 0.051 for log10 and 0.992 for δ<1.253 on the NYUv2 dataset.

KCI등재 SCOPUS

저자 : Yoonjeong Choi , Yujin Lim

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 803-812 (10 pages)

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With the increasing number of mobile device users worldwide, utilizing mobile edge computing (MEC) devices close to users for content caching can reduce transmission latency than receiving content from a server or cloud. However, because MEC has limited storage capacity, it is necessary to determine the content types and sizes to be cached. In this study, we investigate a caching strategy that increases the hit ratio from small base stations (SBSs) for mobile users in a heterogeneous network consisting of one macro base station (MBS) and multiple SBSs. If there are several SBSs that users can access, the hit ratio can be improved by reducing duplicate content and increasing the diversity of content in SBSs. We propose a Deep Q-Network (DQN)-based caching strategy that considers time-varying content popularity and content redundancy in multiple SBSs. Content is stored in the SBS in a divided form using maximum distance separable (MDS) codes to enhance the diversity of the content. Experiments in various environments show that the proposed caching strategy outperforms the other methods in terms of hit ratio.

KCI등재 SCOPUS

저자 : Husheng Zhou

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 813-821 (9 pages)

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Intelligent monitoring, life entertainment, medical rehabilitation, and other fields are only a few examples where visual image technology is becoming increasingly sophisticated and playing a significant role. Recognizing Wushu, or martial arts, movements through the use of visual image technology helps promote and develop Wushu. In order to segment and extract the signals of Wushu movements, this study analyzes the denoising of the original data using the wavelet transform and provides a sliding window data segmentation technique. Wushu movement The Wushu movement recognition model is built based on the hidden Markov model (HMM). The HMM model is trained and taught with the help of the Baum-Welch algorithm, which is then enhanced using the frequency weighted training approach and the mean training method. To identify the dynamic Wushu movement, the Viterbi algorithm is used to determine the probability of the optimal state sequence for each Wushu movement model. In light of the foregoing, an HMM-based martial arts movements recognition model is developed. The recognition accuracy of the HMM model increases to 99.60% when the number of samples is 4,000, which is greater than the accuracy of the SVM (by 0.94%), the CNN (by 1.12%), and the BP (by 1.14%). From what has been discussed, it appears that the suggested system for detecting martial arts acts is trustworthy and effective, and that it may contribute to the growth of martial arts.

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KCI등재SCOUPUS

저자 : Youngjun Sung , Yoojae Won

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 173-187 (15 pages)

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A special government agency has been charged with implementing quality management to guarantee the quality of wild-simulated ginseng. However, these processes are carried out by use of documents, and this has resulted in information omission and high document management costs. To solve this problem, this study analyzed the existing quality management process by using a smart contract for the existing offline form and proposed a new quality management system for storing and managing all log data in the blockchain. This system reduced documentation management costs about quality management and recorded information in the previous step through the quality management steps, thus forming a step-by-step record chain. Experiments were conducted by implementing this system, which improved data integrity and reliability. Additionally, sensitive information, such as personal information, was included in the system by use of the off-chain technology.

KCI등재SCOUPUS

저자 : Ying Yang , Xu Zhang , Hu Pan

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 188-196 (9 pages)

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Recently, neural architecture search (NAS) has received increasing attention as it can replace human experts in designing the architecture of neural networks for different tasks and has achieved remarkable results in many challenging tasks. In this study, a path-based computation neural architecture encoder (PCE) was proposed. Our PCE first encodes the computation of information on each path in a neural network, and then aggregates the encodings on all paths together through an attention mechanism, simulating the process of information computation along paths in a neural network and encoding the computation on the neural network instead of the structure of the graph, which is more consistent with the computational properties of neural networks. We performed an extensive comparison with eight encoding methods on two commonly used NAS search spaces (NAS-Bench-101 and NAS-Bench-201), which included a comparison of the predictive capabilities of performance predictors and search capabilities based on two search strategies (reinforcement learning-based and Bayesian optimization-based) when equipped with different encoders. Experimental evaluation shows that PCE is an efficient encoding method that effectively ranks and predicts neural architecture performance, thereby improving the search efficiency of neural architectures.

KCI등재SCOUPUS

저자 : Sungchul Byun , Seong-soo Han , Chang-sung Jeong

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 197-207 (11 pages)

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The applications and user interfaces (UIs) of smart mobile devices are constantly diversifying. For example, deep learning can be an innovative solution to classify widgets in screen images for increasing convenience. To this end, the present research leverages captured images and the ReDraw dataset to write deep learning datasets for image classification purposes. First, as the validation for datasets using ResNet50 and EfficientNet, the experiments show that the dataset composed in this study is helpful for classification according to a widget's functionality. An implementation for widget detection and classification on RetinaNet and EfficientNet is then executed. Finally, the research suggests the Widg-C and Widg-D datasets―a deep learning dataset for identifying the widgets of smart devices―and implementing them for use with representative convolutional neural network models.

KCI등재SCOUPUS

저자 : Qiang Xiao , Hongshuang Wang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 208-222 (15 pages)

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Through the analysis of the coordination mechanism of the supply chain system of China's automobile manufacturing industry, the factors affecting the supply subsystem, the manufacturing subsystem, the sales subsystem, and the consumption subsystem are sorted out, the supply chain coordination index system based on the influence factor of four subsystems is established. The evaluation models of the coordination degree in the subsystem of the supply chain, the coordination degree among the subsystems, and the comprehensive coordination degree are established by using the efficiency coefficient method and the collaborative entropy method. Experimental results verify the accuracy of the evaluation model using the empirical analysis of the collaborative evaluation index data of China's automobile manufacturing industry from 2000 to 2019. The supply chain synergy of automobile manufacturing industry was low from 2001 to 2005, and it increased to a certain extent from 2006 to 2008 with a small growth rate from 0.10 to 0.15. From 2009 to 2013, the supply chain synergy of automobile manufacturing industry increased rapidly from 0.24 to 0.49, and it also increased rapidly but fluctuated from 2014 to 2019, first rising from 0.68 to 0.84 then dropping to 0.71. These results provide reference for the development of China's automobile manufacturing supply chain system and scientific decision-making basis for the formulation of relevant policies of the automobile manufacturing industry.

KCI등재SCOUPUS

저자 : Hyun-ju Yoo , Nammee Moon

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 223-234 (12 pages)

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The evaluation of the print quality of 3D printing has traditionally relied on manual work using dimensional measurements. However, the dimensional measurement method has an error value that depends on the person who measures it. Therefore, we propose the design of a new print quality measurement method that can be automatically measured using the field-of-view (FOV) model and the intersection over union (IoU) technique. First, the height information of the modeling is acquired from a camera; the output is measured by a sensor; and the images of the top and isometric views are acquired from the FOV model. The height information calculates the height ratio by calculating the percentage of modeling and output, and compares the 2D contour of the object on the image using the FOV model. The contour of the object is obtained from the image for 2D contour comparison and the IoU is calculated by comparing the areas of the contour regions. The accuracy of the automated measurement technique for determining, which derives the print quality value was calculated by averaging the IoU value corrected by the measurement error and the height ratio value.

KCI등재SCOUPUS

저자 : Weixin Yao , Dan Yang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 235-244 (10 pages)

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Many new techniques have been adopted in HEVC (High efficiency video coding) standard, such as quadtree-structured coding unit (CU), prediction unit (PU) partition, 35 intra-mode, and so on. To reduce computational complexity, the paper proposes two optimization algorithms which include fast CU depth range decision and fast PU partition mode decision. Firstly, depth range of CU is predicted according to spatial-temporal correlation. Secondly, we utilize the depth difference between the current CU and CU corresponding to the same position of adjacent frame for PU mode range selection. The number of traversal candidate modes is reduced. The experiment result shows the proposed algorithm obtains a lot of time reducing, and the loss of coding efficiency is inappreciable.

KCI등재SCOUPUS

저자 : Wonkyung Kim , Kukheon Lee , Sangjin Lee , Doowon Jeong

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 245-257 (13 pages)

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In the Internet of Things (IoT) era, the types of devices used by one user are becoming more diverse and the number of devices is also increasing. However, a forensic investigator is restricted to exploit or collect all the user's devices; there are legal issues (e.g., privacy, jurisdiction) and technical issues (e.g., computing resources, the increase in storage capacity). Therefore, in the digital forensics field, it has been a challenge to acquire information that remains on the devices that could not be collected, by analyzing the seized devices. In this study, we focus on the fact that multiple devices share data through account synchronization of the online platform. We propose a novel way of identifying the user's interest through analyzing the remnants of targeted advertising which is provided based on the visited websites or search terms of logged-in users. We introduce a detailed methodology to pick out the targeted advertising from cache data and infer the user's interest using deep learning. In this process, an improved learning model considering the unique characteristics of advertisement is implemented. The experimental result demonstrates that the proposed method can effectively identify the user interest even though only one device is examined.

KCI등재SCOUPUS

저자 : Changhao Piao , Xiaoyue Ding , Jia He , Soohyun Jang , Mingjie Liu

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 258-267 (10 pages)

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Weak over-the-horizon perception and blind spot are the main problems in intelligent connected vehicles (ICVs). In this paper, a V2V image transmission-based road condition warning method is proposed to solve them. The encoded road emergency images which are collected by the ICV are transmitted to the on-board unit (OBU) through Ethernet. The OBU broadcasts the fragmented image information including location and clock of the vehicle to other OBUs. To satisfy the channel quality of the V2X communication in different times, the optimal fragment length is selected by the OBU to process the image information. Then, according to the position and clock information of the remote vehicles, OBU of the receiver selects valid messages to decode the image information which will help the receiver to extend the perceptual field. The experimental results show that our method has an average packet loss rate of 0.5%. The transmission delay is about 51.59 ms in low-speed driving scenarios, which can provide drivers with timely and reliable warnings of the road conditions.

KCI등재SCOUPUS

저자 : Hyun-il Lim

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 268-281 (14 pages)

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The development of information technology is bringing many changes to everyday life, and machine learning can be used as a technique to solve a wide range of real-world problems. Analysis and utilization of data are essential processes in applying machine learning to real-world problems. As a method of processing data in machine learning, we propose an approach based on applying multiple linear regression models by interlacing data to the task of classifying similar software. Linear regression is widely used in estimation problems to model the relationship between input and output data. In our approach, multiple linear regression models are generated by training on interlaced feature data. A combination of these multiple models is then used as the prediction model for classifying similar software. Experiments are performed to evaluate the proposed approach as compared to conventional linear regression, and the experimental results show that the proposed method classifies similar software more accurately than the conventional model. We anticipate the proposed approach to be applied to various kinds of classification problems to improve the accuracy of conventional linear regression.

KCI등재SCOUPUS

저자 : Jung Hee Lee , Ji Su Park , Jin Gon Shon

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 282-291 (10 pages)

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This research applies a pre-trained bidirectional encoder representations from transformers (BERT) handwriting recognition model to predict foreign Korean-language learners' writing scores. A corpus of 586 answers to midterm and final exams written by foreign learners at the Intermediate 1 level was acquired and used for pre-training, resulting in consistent performance, even with small datasets. The test data were pre-processed and fine-tuned, and the results were calculated in the form of a score prediction. The difference between the prediction and actual score was then calculated. An accuracy of 95.8% was demonstrated, indicating that the prediction results were strong overall; hence, the tool is suitable for the automatic scoring of Korean written test answers, including grammatical errors, written by foreigners. These results are particularly meaningful in that the data included written language text produced by foreign learners, not native speakers.

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