• Title/Summary/Keyword: Media Intelligence

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Fake News Detection for Korean News Using Text Mining and Machine Learning Techniques (텍스트 마이닝과 기계 학습을 이용한 국내 가짜뉴스 예측)

  • Yun, Tae-Uk;Ahn, Hyunchul
    • Journal of Information Technology Applications and Management
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    • v.25 no.1
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    • pp.19-32
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    • 2018
  • Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection method using Artificial Intelligence techniques over the past years. But, unfortunately, there have been no prior studies proposed an automated fake news detection method for Korean news. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (Topic Modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as multiple discriminant analysis, case based reasoning, artificial neural networks, and support vector machine can be applied. To validate the effectiveness of the proposed method, we collected 200 Korean news from Seoul National University's FactCheck (http://factcheck.snu.ac.kr). which provides with detailed analysis reports from about 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

Study of engine oil replacement times estimate method using fuzzy and neural network algorithm (퍼지 및 신경망 알고리즘을 이용한 엔진오일 교환 시기 예측 방법에 관한 연구)

  • Nam, Sang-Yep;Hong, You-Sik;Kim, Cheon-Shik
    • Journal of the Institute of Electronics Engineers of Korea TE
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    • v.42 no.4
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    • pp.15-20
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    • 2005
  • If we can forecast the replacement time of engine oil, we extend the life-time of our engine and increase the continued ratio. But, the replacement times of engine oil is influenced by the following elements: the distance that cars or vehicles travel, vehicles that run a short range, types of engine oil etc. that run a long distance. In this paper, We forecast engine oil replacement times by using fuzzy neural network algorithm. This algerian uses the data of distance covered, color of engine oil etc. Through a sequence of simulation, the exchange system of intelligence style engine oil decides on the replacement times of engine oil quite accurately. Therefore, We expect vehicles to become more convenient if the above algorithm is a lied to the present types of cars.

Analysis of Two-Way Communication Virtual Being Technology and Characteristics in the Content Industry (콘텐츠 산업에서 나타난 양방향 소통 가상존재 기술 및 특성 분석)

  • Kim, Jungho;Park, Jin Wan;Yoo, Taekyung
    • Journal of Broadcast Engineering
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    • v.25 no.4
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    • pp.507-517
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    • 2020
  • Along with the development of computer graphics, real-time rendering, motion capture, and artificial intelligence technology, virtual being that enables two-way communication has emerged in the content industry. Although the commercialization of technologies and platforms is creating a two-way communication virtual being, there is a lack of analysis of what characteristics this virtual being has and how it can be used in each field. Therefore, through technical background survey and case study for the production of virtual being, the two-way communication virtual being is analyzed on the characteristics necessary for emotional exchange. The characteristics needed for emotional exchange were divided into interaction, individuality, and autonomy, and this characteristic is classified as the focus and how two-way communication virtual being will be used in the content field. This study is expected to provide significant implications for the research of content production and utilization using virtual being as a basic study of virtual being, which analyzes the technical background and characteristics for two-way communication required for virtual being production.

Data Partitioning on MapReduce by Leveraging Data Utility (맵리듀스에서 데이터의 유용성을 이용한 데이터 분할 기법)

  • Kim, Jong Wook
    • Journal of Korea Multimedia Society
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    • v.16 no.5
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    • pp.657-666
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    • 2013
  • Today, many aspects of our lives are characterized by the rapid influx of large amounts of data from various application domains. The applications that produce this massive of data span a large spectrum, from social media to business intelligence or biology. This massive influx of data necessitates large scale parallelism for efficiently supporting a large class of analysis tasks. Recently, there have been extensive studies in using MapReduce framework to support large parallelism. While this technique has produced impressive results in diverse applications, the same can not be said for multimedia applications where most of users are interested in a small number of results having high or low score. Thus, in this paper, we develop the data partitioning algorithm which is able to efficiently process large data set having different data utility. The experiment results show that the proposed technique provides significant execution time gains over the existing solution.

AN ALGORITHM FOR CLASSIFYING EMOTION OF SENTENCES AND A METHOD TO DIVIDE A TEXT INTO SOME SCENES BASED ON THE EMOTION OF SENTENCES

  • Fukoshi, Hirotaka;Sugimoto, Futoshi;Yoneyama, Masahide
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.773-777
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    • 2009
  • In recent years, the field of synthesizing voice has been developed rapidly, and the technologies such as reading aloud an email or sound guidance of a car navigation system are used in various scenes of our life. The sound quality is monotonous like reading news. It is preferable for a text such as a novel to be read by the voice that expresses emotions wealthily. Therefore, we have been trying to develop a system reading aloud novels automatically that are expressed clear emotions comparatively such as juvenile literature. At first it is necessary to identify emotions expressed in a sentence in texts in order to make a computer read texts with an emotionally expressive voice. A method on the basis of the meaning interpretation that utilized artificial intelligence technology for a method to specify emotions of texts is thought, but it is very difficult with the current technology. Therefore, we propose a method to determine only emotion every sentence in a novel by a simpler way. This method determines the emotion of a sentence according to an emotion that words such as a verb in a Japanese verb sentence, and an adjective and an adverb in a adjective sentence, have. The emotional characteristics that these words have are prepared beforehand as a emotional words dictionary by us. The emotions used here are seven types: "joy," "sorrow," "anger," "surprise," "terror," "aversion" or "neutral."

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Generating Augmented Lifting Player using Pose Tracking

  • Choi, Jong-In;Kim, Jong-Hyun
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.5
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    • pp.19-26
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    • 2020
  • This paper proposes a framework for creating acrobatic scenes such as soccer ball lifting using various users' videos. The proposed method can generate a desired result within a few seconds using a general video of user recorded with a mobile phone. The framework of this paper is largely divided into three parts. The first is to analyze the posture by receiving the user's video. To do this, the user can calculate the pose of the user by analyzing the video using a deep learning technique, and track the movement of a selected body part. The second is to analyze the movement trajectory of the selected body part and calculate the location and time of hitting the object. Finally, the trajectory of the object is generated using the analyzed hitting information. Then, a natural object lifting scenes synchronized with the input user's video can be generated. Physical-based optimization was used to generate a realistic moving object. Using the method of this paper, we can produce various augmented reality applications.

A cavitation performance prediction method for pumps PART1-Proposal and feasibility

  • Yun, Long;Rongsheng, Zhu;Dezhong, Wang
    • Nuclear Engineering and Technology
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    • v.52 no.11
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    • pp.2471-2478
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    • 2020
  • Pumps are essential machinery in the various industries. With the development of high-speed and large-scale pumps, especially high energy density, high requirements have been imposed on the vibration and noise performance of pumps, and cavitation is an important source of vibration and noise excitation in pumps, so it is necessary to improve pumps cavitation performance. The modern pump optimization design method mainly adopts parameterization and artificial intelligence coupling optimization, which requires direct correlation between geometric parameters and pump performance. The existing cavitation performance calculation method is difficult to be integrated into multi-objective automatic coupling optimization. Therefore, a fast prediction method for pump cavitation performance is urgently needed. This paper proposes a novel cavitation prediction method based on impeller pressure isosurface at single-phase media. When the cavitation occurs, the area of pressure isosurface Siso increases linearly with the NPSHa decrease. This demonstrates that with the development of cavitation, the variation law of the head with the NPSHa and the variation law of the head with the area of pressure isosurface are consistent. Therefore, the area of pressure isosurface Siso can be used to predict cavitation performance. For a certain impeller blade, since the area ratio Rs is proportional to the area of pressure isosurface Siso, the cavitation performance can be predicted by the Rs. In this paper, a new cavitation performance prediction method is proposed, and the feasibility of this method is demonstrated in combination with experiments, which will greatly accelerate the pump hydraulic optimization design.

Reversible Watermarking For Relational Databases using DE (Difference Expansion) Algorithm (DE 알고리즘을 사용한 관계형 데이터베이스를 위한 가역 워터마킹)

  • Kim, Cheonshik
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.15 no.3
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    • pp.7-13
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    • 2015
  • Generally, watermarking can be used copyright for contents such as audios, videos, images, and texts. With the development of Internet, many malicious attackers illegally copy relational databases synchronized applications Therefore, it is needed for the protection of databases copyright, because databases involve various sensitive information such as personal information, information industry, and secret national intelligence. Thus, the protection of relational databases is a major research field in the databases research topics. In this paper, we will review previous researches related the protection of relational databases and propose new method for relational data. Especially, we propose watermarking scheme for databases using reversible method in this paper. As an experimental result, the proposed scheme is very strong to malicious attacks. In addition, we proved our proposed scheme is to apply real application.

An LDPC Code Replication Scheme Suitable for Cloud Computing (클라우드 컴퓨팅에 적합한 LDPC 부호 복제 기법)

  • Kim, Se-Hoe;Lee, Won-Joo;Jeon, Chang-Ho
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.49 no.2
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    • pp.134-142
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    • 2012
  • This paper analyze an LDPC code replication method suitable for cloud computing. First, we determine the number of blocks suitable for cloud computing through analysis of the performance for the file availability and storage overhead. Also we determine the type of LDPC code appropriate for cloud computing through the performance for three types of LDPC codes. Finally we present the graph random generation method and the comparing method of each generated LDPC code's performance by the iterative decoding process. By the simulation, we confirmed the best graph's regularity is left-regular or least left-regular. Also, we confirmed the best graph's total number of edges are minimum value or near the minimum value.

The Study on the importance of Next Digital Marketing Factors by Using AHP Method: AD STARS Ad Tech 2017 Case (AHP분석을 활용한 향후 디지털 마케팅 구성요인의 중요도 연구: 부산국제광고제 애드텍 2017 사례를 중심으로)

  • Kim, Shin-Youp;Shim, Sung Wook
    • Journal of Digital Contents Society
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    • v.19 no.1
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    • pp.1-10
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    • 2018
  • This study is to seek to find the importance of next digital marketing factors by using AHP method and analyze comparison between an advertising expert and a non-advertising expert. In results, the relative importance ranking is as follows; combination (0.26), transformation (0.259), optimization (0.243), and technology (0.238). The relative importance ranking of sub-factors is as follows: artificial intelligence and maching learning (0.086), big data (0.085), and contents curation (0.060). While the relative importance of combination and optimization for an advertising expert is higher than for non-advertising expert, the relative importance of transformation and technology for non-advertising is higher than for an advertising expert. This study provides managerial implication to build digital strategy based on these result.