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한국정보처리학회> JIPS(Journal of Information Processing Systems)> Sinusoidal Map Jumping Gravity Search Algorithm Based on Asynchronous Learning

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Sinusoidal Map Jumping Gravity Search Algorithm Based on Asynchronous Learning

Xinxin Zhou , Guangwei Zhu
  • : 한국정보처리학회
  • : JIPS(Journal of Information Processing Systems) 18권3호
  • : 연속간행물
  • : 2022년 06월
  • : 332-343(12pages)
JIPS(Journal of Information Processing Systems)

DOI


목차

1. Introduction
2. Gravity Search Algorithm
3. Sinusoidal Map Jumping Gravity Search Algorithm based on Asynchronous Learning
4. Experiment and Analysis
5. Conclusion
Acknowledgement
References

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초록 보기

To address the problems of the gravitational search algorithm (GSA) in which the population is prone to converge prematurely and fall into the local solution when solving the single-objective optimization problem, a sine map jumping gravity search algorithm based on asynchronous learning is proposed. First, a learning mechanism is introduced into the GSA. The agents keep learning from the excellent agents of the population while they are evolving, thus maintaining the memory and sharing of evolution information, addressing the algorithm’s shortcoming in evolution that particle information depends on the current position information only, improving the diversity of the population, and avoiding premature convergence. Second, the sine function is used to map the change of the particle velocity into the position probability to improve the convergence accuracy. Third, the Levy flight strategy is introduced to prevent particles from falling into the local optimization. Finally, the proposed algorithm and other intelligent algorithms are simulated on 18 benchmark functions. The simulation results show that the proposed algorithm achieved improved the better performance.

UCI(KEPA)

간행물정보

  • : 공학분야  > 전자공학
  • : KCI등재
  • : SCOPUS
  • : 격월
  • : 1976-913x
  • : 2092-805X
  • : 학술지
  • : 연속간행물
  • : 2005-2022
  • : 1014


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1Life Prediction of Hydraulic Concrete Based on Grey Residual Markov Model

저자 : Li Gong , Xuelei Gong , Ying Liang , Bingzong Zhang , Yiqun Yang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 457-469 (13 pages)

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Hydraulic concrete buildings in the northwest of China are often subject to the combined effects of low-temperature frost damage, during drying and wetting cycles, and salt erosion, so the study of concrete deterioration prediction is of major importance. The prediction model of the relative dynamic elastic modulus (RDEM) of four different kinds of modified concrete under the special environment in the northwest of China was established using Grey residual Markov theory. Based on the available test data, modified values of the dynamic elastic modulus were obtained based on the Grey GM(1,1) model and the residual GM(1,1) model, combined with the Markov sign correction, and the dynamic elastic modulus of concrete was predicted. The computational analysis showed that the maximum relative error of the corrected dynamic elastic modulus was significantly reduced, from 1.599% to 0.270% for the BS2 group. The analysis error showed that the model was more adjusted to the concrete mixed with fly ash and mineral powder, and its calculation error was significantly lower than that of the rest of the groups. The analysis of the data for each group proved that the model could predict the loss of dynamic elastic modulus of the deterioration of the concrete effectively, as well as the number of cycles when the concrete reached the damaged state.

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2Mukbang's Foodcasting beyond Korea's Borders: A Study Focusing on OTT Platforms

저자 : Jia Lim

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 470-479 (10 pages)

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Mukbang is a type of foodcasting where a host records or streams their eating rituals for audience consumption in live format. With origins in South Korea via the online broadcast genre found on Afreeca TV in the mid- 2000s, the phenomenon has since found global popularity. Its development as a full-fledged genre is based on a communication culture that invites people to a meal rather than to talk to one another; viewers watch in silence as a host consumes a copious number of dishes from Korean gastronomy to fast food to other ethnic cuisine on display. An invitation to eat means the beginning of a public relationship that quickly turns to a private shared experience. This study analyzes several Mukbang video postings and makes use of Linden's culture approach model to provide a view toward a number of cross-cultural connections by Koreans and non-Korean audiences. Prior to the study, 10 Korean eating shows were selected and used as standard models. Korean Mukbang mainly consists of eating behavior and ASMR, with very few storytelling or narrative devices utilized by its creators. For this reason, eating shows make a very private connection. In other ways, this paper shows how 28 Mukbangrelated YouTube contents selected by Ranker were evolving and examined through notions of acculturation and reception theory.

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3Tobacco Retail License Recognition Based on Dual Attention Mechanism

저자 : Yuxiang Shan , Qin Ren , Cheng Wang , Xiuhui Wang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 480-488 (9 pages)

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Images of tobacco retail licenses have complex unstructured characteristics, which is an urgent technical problem in the robot process automation of tobacco marketing. In this paper, a novel recognition approach using a double attention mechanism is presented to realize the automatic recognition and information extraction from such images. First, we utilized a DenseNet network to extract the license information from the input tobacco retail license data. Second, bi-directional long short-term memory was used for coding and decoding using a continuous decoder integrating dual attention to realize the recognition and information extraction of tobacco retail license images without segmentation. Finally, several performance experiments were conducted using a largescale dataset of tobacco retail licenses. The experimental results show that the proposed approach achieves a correction accuracy of 98.36% on the ZY-LQ dataset, outperforming most existing methods.

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4Analysis of Security Vulnerabilities for IoT Devices

저자 : Hee-hyun Kim , Jinho Yoo

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 489-499 (11 pages)

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Recently, the number of Internet of Things (IoT) devices has been increasing exponentially. These IoT devices are directly connected to the internet to exchange information. IoT devices are becoming smaller and lighter. However, security measures are not taken in a timely manner compared to the security vulnerabilities of IoT devices. This is often the case when the security patches cannot be applied to the device because the security patches are not adequately applied or there is no patch function. Thus, security vulnerabilities continue to exist, and security incidents continue to increase. In this study, we classified and analyzed the most common security vulnerabilities for IoT devices and identify the essential vulnerabilities of IoT devices that should be considered for security when producing IoT devices. This paper will contribute to reducing the occurrence of security vulnerabilities in companies that produce IoT devices. Additionally, companies can identify vulnerabilities that frequently occur in IoT devices and take preemptive measures.

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5Evaluation Method of College English Education Effect Based on Improved Decision Tree Algorithm

저자 : Fang Dou

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 500-509 (10 pages)

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With the rapid development of educational informatization, teaching methods become diversified characteristics, but a large number of information data restrict the evaluation on teaching subject and object in terms of the effect of English education. Therefore, this study adopts the concept of incremental learning and eigenvalue interval algorithm to improve the weighted decision tree, and builds an English education effect evaluation model based on association rules. According to the results, the average accuracy of information classification of the improved decision tree algorithm is 96.18%, the classification error rate can be as low as 0.02%, and the anti-fitting performance is good. The classification error rate between the improved decision tree algorithm and the original decision tree does not exceed 1%. The proposed educational evaluation method can effectively provide early warning of academic situation analysis, and improve the teachers' professional skills in an accelerated manner and perfect the education system.

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6Fuzzy Neural Network Active Disturbance Rejection Control for Two-Wheeled Self-Balanced Robot

저자 : Chao Wang , Xiao Jianliang , Cheng Zhang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 510-523 (14 pages)

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Considering the problems of poor control effect, weak disturbance rejection ability and adaptive ability of twowheeled self-balanced robot (TWSBR) systems on undulating roads, this paper proposes a fuzzy neural network active disturbance rejection controller (FNNADRC), that is based on fuzzy neural network (FNN) for online correction of active disturbance rejection controller (ADRC)'s nonlinear control rate. Firstly, the dynamic model of the TWSBR is established and decoupled, the extended state observer (ESO) is used to compensate dynamically and linearize the upright and displacement subsystems. Then, the nonlinear PD control rate and FNN are designed, and the FNN is used to modify the control parameters of the nonlinear PD control rate in real time. Finally, the proposed control strategy is simulated and compared with the traditional ADRC and fuzzy active disturbance rejection controller (FADRC). The simulation results show that the control effect of the proposed control strategy is slightly better than ADRC and FADRC.

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7TOD: Trash Object Detection Dataset

저자 : Min-seok Jo , Seong-soo Han , Chang-sung Jeong

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 524-534 (11 pages)

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In this paper, we produce Trash Object Detection (TOD) dataset to solve trash detection problems. A wellorganized dataset of sufficient size is essential to train object detection models and apply them to specific tasks. However, existing trash datasets have only a few hundred images, which are not sufficient to train deep neural networks. Most datasets are classification datasets that simply classify categories without location information. In addition, existing datasets differ from the actual guidelines for separating and discharging recyclables because the category definition is primarily the shape of the object. To address these issues, we build and experiment with trash datasets larger than conventional trash datasets and have more than twice the resolution. It was intended for general household goods. And annotated based on guidelines for separating and discharging recyclables from the Ministry of Environment. Our dataset has 10 categories, and around 33K objects were annotated for around 5K images with 1280×720 resolution. The dataset, as well as the pre-trained models, have been released at https://github.com/jms0923/tod.

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8Burmese Sentiment Analysis Based on Transfer Learning

저자 : Cunli Mao , Zhibo Man , Zhengtao Yu , Xia Wu , Haoyuan Liang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 535-548 (14 pages)

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Using a rich resource language to classify sentiments in a language with few resources is a popular subject of research in natural language processing. Burmese is a low-resource language. In light of the scarcity of labeled training data for sentiment classification in Burmese, in this study, we propose a method of transfer learning for sentiment analysis of a language that uses the feature transfer technique on sentiments in English. This method generates a cross-language word-embedding representation of Burmese vocabulary to map Burmese text to the semantic space of English text. A model to classify sentiments in English is then pre-trained using a convolutional neural network and an attention mechanism, where the network shares the model for sentiment analysis of English. The parameters of the network layer are used to learn the cross-language features of the sentiments, which are then transferred to the model to classify sentiments in Burmese. Finally, the model was tuned using the labeled Burmese data. The results of the experiments show that the proposed method can significantly improve the classification of sentiments in Burmese compared to a model trained using only a Burmese corpus.

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9Bi-directional Maximal Matching Algorithm to Segment Khmer Words in Sentence

저자 : Makara Mao , Sony Peng , Yixuan Yang , Doo-soon Park

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 549-561 (13 pages)

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In the Khmer writing system, the Khmer script is the official letter of Cambodia, written from left to right without a space separator; it is complicated and requires more analysis studies. Without clear standard guidelines, a space separator in the Khmer language is used inconsistently and informally to separate words in sentences. Therefore, a segmented method should be discussed with the combination of the future Khmer natural language processing (NLP) to define the appropriate rule for Khmer sentences. The critical process in NLP with the capability of extensive data language analysis necessitates applying in this scenario. One of the essential components in Khmer language processing is how to split the word into a series of sentences and count the words used in the sentences. Currently, Microsoft Word cannot count Khmer words correctly. So, this study presents a systematic library to segment Khmer phrases using the bi-directional maximal matching (BiMM) method to address these problematic constraints. In the BiMM algorithm, the paper focuses on the Bidirectional implementation of forward maximal matching (FMM) and backward maximal matching (BMM) to improve word segmentation accuracy. A digital or prefix tree of data structure algorithm, also known as a trie, enhances the segmentation accuracy procedure by finding the children of each word parent node. The accuracy of BiMM is higher than using FMM or BMM independently; moreover, the proposed approach improves dictionary structures and reduces the number of errors. The result of this study can reduce the error by 8.57% compared to FMM and BFF algorithms with 94,807 Khmer words.

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10Effect of Interactive Multimedia PE Teaching Based on the Simulated Annealing Algorithm

저자 : Mingfeng Zhao

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 562-574 (13 pages)

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As traditional ways of evaluation prove to be ineffective in evaluating the effect of interactive multimedia physical education (PE) teaching, this study develops a new evaluation model based on the simulated annealing algorithm. After the evaluation subjects and the principle of the evaluation system are determined, different subjects are well chosen to constitute the evaluation system and given the weight. The backpropagation neural network has been improved through the simulated annealing algorithm, whose improvement indicates the completion of the evaluation model. Simulation results show that the evaluation model is highly efficient. Compared with traditional evaluation models, the proposed one enhances students' performance in PE classes by 50%.

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1Highly Efficient and Precise DOA Estimation Algorithm

저자 : Xiaobo Yang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 3호 발행 연도 : 2022 페이지 : pp. 293-301 (9 pages)

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Direction of arrival (DOA) estimation of space signals is a basic problem in array signal processing. DOA estimation based on the multiple signal classification (MUSIC) algorithm can theoretically overcome the Rayleigh limit and achieve super resolution. However, owing to its inadequate real-time performance and accuracy in practical engineering applications, its applications are limited. To address this problem, in this study, a DOA estimation algorithm with high parallelism and precision based on an analysis of the characteristics of complex matrix eigenvalue decomposition and the coordinate rotation digital computer (CORDIC) algorithm is proposed. For parallel and single precision, floating-point numbers are used to construct an orthogonal identity matrix. Thus, the efficiency and accuracy of the algorithm are guaranteed. Furthermore, the accuracy and computation of the fixed-point algorithm, double-precision floating-point algorithm, and proposed algorithm are compared. Without increasing complexity, the proposed algorithm can achieve remarkably higher accuracy and efficiency than the fixed-point algorithm and double-precision floating-point calculations, respectively.

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2Tobacco Sales Bill Recognition Based on Multi-Branch Residual Network

저자 : Yuxiang Shan , Cheng Wang , Qin Ren , Xiuhui Wang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 3호 발행 연도 : 2022 페이지 : pp. 311-318 (8 pages)

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Tobacco sales enterprises often need to summarize and verify the daily sales bills, which may consume substantial manpower, and manual verification is prone to occasional errors. The use of artificial intelligence technology to realize the automatic identification and verification of such bills offers important practical significance. This study presents a novel multi-branch residual network for tobacco sales bills to improve the efficiency and accuracy of tobacco sales. First, geometric correction and edge alignment were performed on the input sales bill image. Second, the multi-branch residual network recognition model is established and trained using the preprocessed data. The comparative experimental results demonstrated that the correct recognition rate of the proposed method reached 98.84% on the China Tobacco Bill Image dataset, which is superior to that of most existing recognition methods.

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3A Novel Approach to Enhance Dual-Energy X-Ray Images Using Region of Interest and Discrete Wavelet Transform

저자 : Burhan Ullah , Aurangzeb Khan , Muhammad Fahad , Mahmood Alam , Allah Noor , Umar Saleem , Muhammad Kamran

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 3호 발행 연도 : 2022 페이지 : pp. 319-331 (13 pages)

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The capability to examine an X-ray image is so far a challenging task. In this work, we suggest a practical and novel algorithm based on image fusion to inspect the issues such as background noise, blurriness, or sharpness, which curbs the quality of dual-energy X-ray images. The current technology exercised for the examination of bags and baggage is “X-ray”; however, the results of the incumbent technology used show blurred and low contrast level images. This paper aims to improve the quality of X-ray images for a clearer vision of illegitimate or volatile substances. A dataset of 40 images was taken for the experiment, but for clarity, the results of only 13 images have been shown. The results were evaluated using MSE and PSNR metrics, where the average PSNR value of the proposed system compared to single X-ray images was increased by 19.3%, and the MSE value decreased by 17.3%. The results show that the proposed framework will help discern threats and the entire scanning process.

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4Sinusoidal Map Jumping Gravity Search Algorithm Based on Asynchronous Learning

저자 : Xinxin Zhou , Guangwei Zhu

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 3호 발행 연도 : 2022 페이지 : pp. 332-343 (12 pages)

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To address the problems of the gravitational search algorithm (GSA) in which the population is prone to converge prematurely and fall into the local solution when solving the single-objective optimization problem, a sine map jumping gravity search algorithm based on asynchronous learning is proposed. First, a learning mechanism is introduced into the GSA. The agents keep learning from the excellent agents of the population while they are evolving, thus maintaining the memory and sharing of evolution information, addressing the algorithm's shortcoming in evolution that particle information depends on the current position information only, improving the diversity of the population, and avoiding premature convergence. Second, the sine function is used to map the change of the particle velocity into the position probability to improve the convergence accuracy. Third, the Levy flight strategy is introduced to prevent particles from falling into the local optimization. Finally, the proposed algorithm and other intelligent algorithms are simulated on 18 benchmark functions. The simulation results show that the proposed algorithm achieved improved the better performance.

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5Improving Abstractive Summarization by Training Masked Out-of-Vocabulary Words

저자 : Tae-seok Lee , Hyun-young Lee , Seung-shik Kang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 3호 발행 연도 : 2022 페이지 : pp. 344-358 (15 pages)

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Text summarization is the task of producing a shorter version of a long document while accurately preserving the main contents of the original text. Abstractive summarization generates novel words and phrases using a language generation method through text transformation and prior-embedded word information. However, newly coined words or out-of-vocabulary words decrease the performance of automatic summarization because they are not pre-trained in the machine learning process. In this study, we demonstrated an improvement in summarization quality through the contextualized embedding of BERT with out-of-vocabulary masking. In addition, explicitly providing precise pointing and an optional copy instruction along with BERT embedding, we achieved an increased accuracy than the baseline model. The recall-based word-generation metric ROUGE- 1 score was 55.11 and the word-order-based ROUGE-L score was 39.65.

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6Contact Tracking Development Trend Using Bibliometric Analysis

저자 : Chaoqun Li , Zhigang Chen , Tongrui Yu , Xinxia Song

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 3호 발행 연도 : 2022 페이지 : pp. 359-373 (15 pages)

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The new crown pneumonia (COVID-19) has become a global epidemic. The disease has spread to most countries and poses a challenge to the healthcare system. Contact tracing technology is an effective way for public health to deal with diseases. Many experts have studied traditional contact tracing and developed digital contact tracking. In order to better understand the field of contact tracking, it is necessary to analyze the development of contact tracking in the field of computer science by bibliometrics. The purpose of this research is to use literature statistics and topic analysis to characterize the research literature of contact tracking in the field of computer science, to gain an in-depth understanding of the literature development status of contact tracking and the trend of hot topics over the past decade. In order to achieve the aforementioned goals, we conducted a bibliometric study in this paper. The study uses data collected from the Scopus database. Which contains more than 10,000 articles, including more than 2,000 in the field of computer science. For popular trends, we use VOSviewer for visual analysis. The number of contact tracking documents published annually in the computer field is increasing. At present, there are 200 to 300 papers published in the field of computer science each year, and the number of uncited papers is relatively small. Through the visual analysis of the paper, we found that the hot topic of contact tracking has changed from the past “mathematical model,” “biological model,” and “algorithm” to the current “digital contact tracking,” “privacy,” and “mobile application” and other topics. Contact tracking is currently a hot research topic. By selecting the most cited papers, we can display high-quality literature in contact tracking and characterize the development trend of the entire field through topic analysis. This is useful for students and researchers new to field of contact tracking ai well as for presenting our results to other subjects. Especially when comprehensive research cannot be conducted due to time constraints or lack of precise research questions, our research analysis can provide value for it.

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7Improvement of RocksDB Performance via Large-Scale Parameter Analysis and Optimization

저자 : Huijun Jin , Won Gi Choi , Jonghwan Choi , Hanseung Sung , Sanghyun Park

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 3호 발행 연도 : 2022 페이지 : pp. 374-388 (15 pages)

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Database systems usually have many parameters that must be configured by database administrators and users. RocksDB achieves fast data writing performance using a log-structured merged tree. This database has many parameters associated with write and space amplifications. Write amplification degrades the database performance, and space amplification leads to an increased storage space owing to the storage of unwanted data. Previously, it was proven that significant performance improvements can be achieved by tuning the database parameters. However, tuning the multiple parameters of a database is a laborious task owing to the large number of potential configuration combinations. To address this problem, we selected the important parameters that affect the performance of RocksDB using random forest. We then analyzed the effects of the selected parameters on write and space amplifications using analysis of variance. We used a genetic algorithm to obtain optimized values of the major parameters. The experimental results indicate an insignificant reduction (-5.64%) in the execution time when using these optimized values; however, write amplification, space amplification, and data processing rates improved considerably by 20.65%, 54.50%, and 89.68%, respectively, as compared to the performance when using the default settings.

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8Communication Resource Allocation Strategy of Internet of Vehicles Based on MEC

저자 : Zhiqiang Ma

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 3호 발행 연도 : 2022 페이지 : pp. 389-401 (13 pages)

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The business of Internet of Vehicles (IoV) is growing rapidly, and the large amount of data exchange has caused problems of large mobile network communication delay and large energy loss. A strategy for resource allocation of IoV communication based on mobile edge computing (MEC) is thus proposed. First, a model of the cloud-side collaborative cache and resource allocation system for the IoV is designed. Vehicles can offload tasks to MEC servers or neighboring vehicles for communication. Then, the communication model and the calculation model of IoV system are comprehensively analyzed. The optimization objective of minimizing delay and energy consumption is constructed. Finally, the on-board computing task is coded, and the optimization problem is transformed into a knapsack problem. The optimal resource allocation strategy is obtained through genetic algorithm. The simulation results based on the MATLAB platform show that: The proposed strategy offloads tasks to the MEC server or neighboring vehicles, making full use of system resources. In different situations, the energy consumption does not exceed 300 J and 180 J, with an average delay of 210 ms, effectively reducing system overhead and improving response speed.

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9Explainable Machine Learning Based a Packed Red Blood Cell Transfusion Prediction and Evaluation for Major Internal Medical Condition

저자 : Seongbin Lee , Seunghee Lee , Duhyeuk Chang , Mi-hwa Song , Jong-yeup Kim , Suehyun Lee

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 3호 발행 연도 : 2022 페이지 : pp. 392-400 (9 pages)

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Efficient use of limited blood products is becoming very important in terms of socioeconomic status and patient recovery. To predict the appropriateness of patient-specific transfusions for the intensive care unit (ICU) patients who require real-time monitoring, we evaluated a model to predict the possibility of transfusion dynamically by using the Medical Information Mart for Intensive Care III (MIMIC-III), an ICU admission record at Harvard Medical School. In this study, we developed an explainable machine learning to predict the possibility of red blood cell transfusion for major medical diseases in the ICU. Target disease groups that received packed red blood cell transfusions at high frequency were selected and 16,222 patients were finally extracted. The prediction model achieved an area under the ROC curve of 0.9070 and an F1-score of 0.8166 (LightGBM). To explain the performance of the machine learning model, feature importance analysis and a partial dependence plot were used. The results of our study can be used as basic data for recommendations related to the adequacy of blood transfusions and are expected to ultimately contribute to the recovery of patients and prevention of excessive consumption of blood products.

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10A Study on the Processing of Timestamps in the Creation of Multimedia Files on Mobile Devices

저자 : Jaehyeok Han , Sangjin Lee

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 3호 발행 연도 : 2022 페이지 : pp. 402-410 (9 pages)

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Digital data can be manipulated easily, so information related to the timestamp is important in establishing the reliability of the data. The time values for a certain file can be extracted following the analysis of the filesystem metadata or file internals, and the information can be utilized to organize a timeline for a digital investigation. Suppose the reversal of a timestamp is found on a mobile device during this process. In this case, a more detailed analysis is required due to the possibility of anti-forensic activity, but little previous research has investigated the handling and possible manipulation of timestamps on mobile devices. Therefore, in this study, we determine how time values for multimedia files are handled according to the operating system or filesystem on mobile devices. We also discuss five types of timestamps―file created (C), last modified (M), last accessed (A), digitalized (Di), and filename (FN) of multimedia files, and experimented with their operational features across multiple devices such as smartphones and cameras.

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자료제공: 네이버학술정보
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자료제공: 네이버학술정보

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